List of articles (by subject) electrical and computer engineering
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Open Access Article
1 - Automatic Change Detection by Intelligent Backgrounding Method
M. Fathi H. ShakuriThe segmentation of foreground regions in image sequences is the first and the most important stage in many automated visual surveillance applications; and background subtraction is a method typically used for such applications. In this method, each new frame is compare MoreThe segmentation of foreground regions in image sequences is the first and the most important stage in many automated visual surveillance applications; and background subtraction is a method typically used for such applications. In this method, each new frame is compared with a model of the empty scene (which we call it ‘Background’), then those regions in the image that differ significantly from the background are identified as foreground. This paper presents a new background subtraction approach. In this method, each image is divided into similar NN blocks; then, some features are extracted from every block and the history of each feature are modeled as a combination of gaussian distributions. These distributions are updated after reception of every frame information. Then the gaussian distributions of the adaptive mixture models are evaluated to determine which one most likely describes the background and each block is classified as background or foreground based on the gaussians distributions which represents its feature value most effectively. The software implementations on personal computers show accepting capability of this approach for handling intruders to the scene, objects being introduced or removed from the scene, noises and unwanted changes in the background. Also, high speed of execution and reduced memory requirements makes this approach as a suitable method for high percentage of real-time applications Manuscript profile -
Open Access Article
2 - Speed Estimation and Sensorless Torque Optimization of Single Phase Induction Motor
S. Vaez-Zadeh - Personal page A. PaymanRecently, performance improvement and speed control of Single-Phase Induction Motors (SPIMs) have been paid attention. These aims is required the machine speed. In this paper, a method is proposed to estimate the SPIMs speed, and then, its application in torque optimiza MoreRecently, performance improvement and speed control of Single-Phase Induction Motors (SPIMs) have been paid attention. These aims is required the machine speed. In this paper, a method is proposed to estimate the SPIMs speed, and then, its application in torque optimization of the machine is investigated. For this purpose, the motor speed is obtained in terms of the motor parameters and stator flux linkage components by use of the SPIMs equations in stationary reference frame. By obtaining the flux linkage from motor windings voltages and currents, the motor speed is estimated desirably. Then the estimated speed is used to increase the average torque, to decrease the pulsation torque and to optimize the motor torque. After that, the simulation results in condition of using the real speed is compared with the estimated speed one. The low simulation error proves the validity of the proposed method Manuscript profile -
Open Access Article
3 - Optimal Design of Three-Phase Squirrel-Cage Induction Motor for Electric Vehicle
M. B. B. Sharifia J. FaizIn this paper a squirrel-cage three-phase induction motor, selected as the driving power of an EV, is designed optimally using Modified-Hooke-Jeeves optimization technique. The optimal designs are analyzed and compared with varying pole number, rated base speed and slot MoreIn this paper a squirrel-cage three-phase induction motor, selected as the driving power of an EV, is designed optimally using Modified-Hooke-Jeeves optimization technique. The optimal designs are analyzed and compared with varying pole number, rated base speed and slot shapes. This optimization technique has same advantages such as simple programming, non-gradient, short convergence time and independently variation of each parameter. Variation of design parameters of optimally designed motors versus rated base speed for 2 and 4-pole motors are presented and discussed. The results show that a 2-pole motor with parallel-sided stator and rotor slots and rated speed 1800 rpm have the best performance Manuscript profile -
Open Access Article
4 - A New Method in Design and Implementation of Electronic Synchronizer Based on Phase Locked Loop for Fast Paralleling of Diesel–Generators
M. parniani R. BagheriTo benefit form advantages of parallel operation of diesel-generators, their rapid and smooth synchronization is required. A new method in design and implementation of such a synchronizer, based on phase locked loop (PLL), is described and test results are presented. T MoreTo benefit form advantages of parallel operation of diesel-generators, their rapid and smooth synchronization is required. A new method in design and implementation of such a synchronizer, based on phase locked loop (PLL), is described and test results are presented. The synchronizer automatically controls the generator to achieve zero phase difference, and then issues the synchronization command. The main advantage of the method over other synchronizers is to lock on the perfect synchronous state using PLL. Thus, there is no need to consider circuit breaker operating time and to estimate proper synchronization instant. The result is faster and more reliable synchronization as compared to the existing types Manuscript profile -
Open Access Article
5 - A New Circuit for Protecting of Series Connected Power Thyristors
Mohammad Farzi S. A. Abrishamifar M. Mirzargar M. Fazeli -
Open Access Article
6 - Cooperation in Multi-Agent Systems Using Learning Automata
M. R. »hojasteh M. R. MeybodiAgents are software entities that act continuously and autonomously in a special environment. It is very essential for the agents to have the ability to learn how to act in the special environment for which they are designed to act in, to show reflexes to their environm MoreAgents are software entities that act continuously and autonomously in a special environment. It is very essential for the agents to have the ability to learn how to act in the special environment for which they are designed to act in, to show reflexes to their environment actions, to choose their way and pursue it autonomously, and to be able to adapt and learn. In multi-agent systems, many intelligent agents that can interact with each other, cooperate to achieve a set of goals. Because of the inherent complexity that exists in dynamic and changeable multi-agent environments, there is always a need to machine learning in such environments. As a model for learning, learning automata act in a stochastic environment and are able to update their action probabilities considering the inputs from their environment, so optimizing their functionality as a result. Learning automata are abstract models that can perform some numbers of actions. Each selected action is evaluated by a stochastic environment and a response is given back to the automata. Learning automata use this response to choose its next action. In this paper, the goal is to investigate and evaluate the application of learning automata to cooperation in multi-agent systems, using soccer server simulation as a test-bed. Because of the large state space of a complex multi-agent domains, it is vital to have a method for environmental states’ generalization. An appropriate selection of such a method can have a great role in determining agent states and actions. In this paper we have also introduced and designed a new technique called “The best corner in state square” for generalizing the vast number of states in the environment to a few number of states by building a virtual grid in agent’s domain environment. The efficiency of this technique in a cooperative multi-agent domain is investigated Manuscript profile -
Open Access Article
7 - A New High Level Model to Check CTL Properties in VHDL Environment
B. Alizadeh Z. NavabiThis paper describes the use of polynomial integer equations for high level model of digital circuits for property checking formal verification at this level. Most formal verification methods use low-level representations of a design like BDDs. BDD operations are not a MoreThis paper describes the use of polynomial integer equations for high level model of digital circuits for property checking formal verification at this level. Most formal verification methods use low-level representations of a design like BDDs. BDD operations are not applicable to a large datapath because of large CPU time and memory usage. In our method, a behavioral state machine is represented by a list of integer equations, and RT level properties are directly applied to this representation. Furthermore, this method is applied to circuits without having to separate their data and control sections. For this implementation, we use a canonical form of integer equations, which simplifies equations instead of solving them. This paper compares our results with those of the VIS verification tool that is a BDD based program Manuscript profile -
Open Access Article
8 - Optimization of LZ78 compression algorithm in tracing location of mobile communication users
M.R. mirsarraf Mohammad HakkakFor location updating of mobile users, two compression algorithms, namely, LZ78 and proposed compression algorithm (modified LZ78) are introduced in this paper to be used in PCS networks. Some problems related to using these algorithm are the usage of memory of dictiona MoreFor location updating of mobile users, two compression algorithms, namely, LZ78 and proposed compression algorithm (modified LZ78) are introduced in this paper to be used in PCS networks. Some problems related to using these algorithm are the usage of memory of dictionary in mobile users and HLR data base as well as the ambiguity about the last location of mobile users due to delay in location updating caused by the compression algorithm. The advantage of these algorithms is reduction at the number of location updatings for a mobile user. With some modifications in the LZ78 algorithm, its problems in implementation are reduced and its usage for PCS networks is enhanced. These changes result from combining this algorithm with distance based location updating algorithm and sending symbols corresponding to some limited neighborhoods identity instead of cell number by compression algorithm For comparison between LZ78 and proposed modified algorithm, we use simulation technique. The simulation program have two structures for PCS network, namely, square cells and hexagon cell networks. For mobile users, we considered two movement pattern: one is directional and the other is omnidirectional movement pattern. The outputs of the simulation program are the number of location updating, the maximum ambiguity of user location and size of dictionary for compression algorithms. Comparing the two algorithms by simulation, we observe that in the modified LZ78 algorithm the parameters of location updating number, maximum user ambiguity and size of dictionary are lower than those in the LZ78 algorithm. At the end of the article, cost of location management of mobile user versus call to mobility ratio (the average number of call toward user to the average number of its movement) is calculated. By comparing location management for LZ78 algorithm, modified LZ78 and distance based location updating algorithm, we observe that the cost of location management is reduced for modified LZ78 compression algorithm. Manuscript profile -
Open Access Article
9 - New Approach on Reliable Restoration in MPLS Based Networks
A. danaIn order to guaranty the quality of real time services on IP based networks, robust survivability with fast fault recovery and path restoration are the main goals. Many recent restoration methods spend much time for fault recovery and path restoration. MPLS based netwo MoreIn order to guaranty the quality of real time services on IP based networks, robust survivability with fast fault recovery and path restoration are the main goals. Many recent restoration methods spend much time for fault recovery and path restoration. MPLS based networks with connection –oriented ability can guaranty QoS by useful restoration method in short time. In this paper we proposed a new restoration mechanism base on pre-assigned end to end protection path .We apply self similar and Poisson process separately for modeling the traffic arrivals time . The comparative analysis between two models reveal the reliability growth gained through applying the proposed algorithm. Manuscript profile -
Open Access Article
10 - Equivalent Circuit Modeling of a Separate Absorption and Multiplication Avalanche Photodiode (SAM-APD)
Mohammad sorooshUsing some simplifying assumptions in a separate absorption and multiplication avalanche photodiode (SAM-APD), in this paper we develop a circuit model. Then, using this circuit model, we calculate the gain and the quantum efficiency of the device. To examine the accura MoreUsing some simplifying assumptions in a separate absorption and multiplication avalanche photodiode (SAM-APD), in this paper we develop a circuit model. Then, using this circuit model, we calculate the gain and the quantum efficiency of the device. To examine the accuracy of the device, we compare the results obtained from the model with the experimental results. A fairly good correspondence between the model an the experimental results, shows that this model is capable of predicting the device behavior, while varying different parameters such as applied bias, device size, and hence the light wavelength. Manuscript profile -
Open Access Article
11 - Circular Symmetric Coupled Microstrip Lines
Mohammad Khalaj-AmirhosseiniIn this paper a new kind of coupled lines called circular symmetric coupled microstrip transmission lines is introduced. At first the capacitance C and inductance L matrices of this kind of microstrip lines are determined by solving the laplace’s equation using fourier MoreIn this paper a new kind of coupled lines called circular symmetric coupled microstrip transmission lines is introduced. At first the capacitance C and inductance L matrices of this kind of microstrip lines are determined by solving the laplace’s equation using fourier series method. Then by some examples the capacitance C and inductance L matrices of this kind of microstrip lines are discussed Manuscript profile -
Open Access Article
12 - Design, Implementation and Measurement of Frequency Multipliers Using HEMT
A. Mohammadi R. KhosraviThe frequency multipliers are widely used in microwave and wireless transceivers. This paper introduces an accurate technique to model and to design a microwave frequency multiplier using HEMT transistors. Based upon this technique, a frequency doubler in C band and a f MoreThe frequency multipliers are widely used in microwave and wireless transceivers. This paper introduces an accurate technique to model and to design a microwave frequency multiplier using HEMT transistors. Based upon this technique, a frequency doubler in C band and a frequency tripler in Ku band are designed and implemented. The excellent agreement between simulation and measurement results shows the validity and the accuracy of the technique Manuscript profile -
Open Access Article
13 - A New Algorithm for Extracting the Noise Parameters of Microwave Two-ports
A. abdipour F. ArazmOne of the most important topics in designing the microwave circuits is the topic of noise and “noise parameter extraction of the circuits”. In this paper a new method is introduced for noise parameter extraction. The results of the new method are then compared with the MoreOne of the most important topics in designing the microwave circuits is the topic of noise and “noise parameter extraction of the circuits”. In this paper a new method is introduced for noise parameter extraction. The results of the new method are then compared with the results of one of the commonly used methods using the measured noise parameters of a microwave transistor Manuscript profile -
Open Access Article
14 - A New Corner Extraction Method and its Application to Vehicle De
E. Kabir M. Fathi H. Sadoghi YazdiCorner detection is employed in many areas of image processing and machine vision. Finding all corners, computing the exact position of the corner and robustness of the algorithm against noise are important criteria in corner detection. In this paper, using the singular MoreCorner detection is employed in many areas of image processing and machine vision. Finding all corners, computing the exact position of the corner and robustness of the algorithm against noise are important criteria in corner detection. In this paper, using the singular values of the matrix defined on the gradient of a small area of the image, a suitable corner is extracted. The proposed method in comparison with the computational method which is based on the eigenvalues of the cross correlation matrix of the gradient of image shows a better performance. It also yields good results in the presence of noise. These two methods were compared on the synthesized and real images of a traffic scene. The proposed method presented better results. Manuscript profile -
Open Access Article
15 - A Two Step Method for the Recognition of Printed Subwords
E. Kabir A. ebrahimiIn this paper a two step method for the recognition of printed subwords is proposed. Using characteristic loci features, the set of printed subwords are clustered into 300 clusters by k-means algorithm. Each cluster is represented by its mean. In the first step, each in MoreIn this paper a two step method for the recognition of printed subwords is proposed. Using characteristic loci features, the set of printed subwords are clustered into 300 clusters by k-means algorithm. Each cluster is represented by its mean. In the first step, each input is classified into 300 categories by minimum Euclidian distance from the cluster centers, and 10 closest clusters are found. In the second step, Fourier descriptors of the subword contour are used to classify the input subword into the members of these 10 clusters. The training set consists of 12700 Farsi subwords in 4 different fonts, Lotus, Mitra, Yagut and Zar, and 3 sizes of 10, 12 and 14. In a test, a set of 500 subwords was used. Considering the first class, top five and top ten classes, 71.4%, 95%, and 98.2% of these subwords were correctly classified. In the post processing, dots of the subword and their positions were used to improve the recognition results. This improved the recognition rate to 92.6%. Manuscript profile -
Open Access Article
16 - Adaptive Compression of Wide-Band Speech and Audio Using Wavelet Transform
M. H. SavojiThe design of a new codec at 32 kb/s for audio and high quality speech (bandwidth limited to 7 kHz and sampled at 16 kHz with 16 b/sample) is presented in this paper. This codec is a good substitute for the G721 ITU Standard and its 64 kb/s variant G722 that are based o MoreThe design of a new codec at 32 kb/s for audio and high quality speech (bandwidth limited to 7 kHz and sampled at 16 kHz with 16 b/sample) is presented in this paper. This codec is a good substitute for the G721 ITU Standard and its 64 kb/s variant G722 that are based on ADPCM and dating from the late 1980s. This new codec comprises adaptive wavelet transform coding, psycho-acoustic modeling, quantization and variable length entropy and run-length coding. The novelty here is the use of a parametric wavelet kernel and the way the wavelet packet tree (WPT) is expanded so that better matching is achieved with critical acoustic bands. The explicit kernel permits to control the sharpness of the basic half-band filter of which the filter used in the Fast Wavelet Transform (FWT) coding are derived. The psycho-acoustic modeling of MPEG1-Audio is used but instead of employing power spectrum for calculating the Signal-to-Mask ratio (S/M), we have directly used the energies of WPT output signals. As a consequence, the computation cost is reduced. The number of quantization bits in each band is controlled by the corresponding S/M ratio. The Variable Length Coding (VLC) used here is an extension of JPEG Huffman coding where some modifications are made to adapt this scheme to speech characteristics. The developed codec has the capability of reducing the bit-rate and controlling the required quality by changing the S/M ratios. Therefore, it can be used for fixed capacity channels by the same token. It is shown that this scheme has a very good quality at 32 kb/s and that the coded signal is quite indistinguishable from the PCM signal digitized at 16 kHz and 16 b/sample. Manuscript profile -
Open Access Article
17 - Speech Compression Based on Linear Prediction Model and Voiced and Unvoiced Cycles
K. YaghmaieVariable rate signal compression has found many applications where there is no serious limitation on delay and the signal parameters are not very susceptible to errors. Methods used to apply variable rate coding usually rely on the redundancies included in the signal. MoreVariable rate signal compression has found many applications where there is no serious limitation on delay and the signal parameters are not very susceptible to errors. Methods used to apply variable rate coding usually rely on the redundancies included in the signal. Such methods are different in final bit rate, quality of the synthetic signal and computational requirements. This paper presents a novel method for compression of speech signal in a variable scheme. Based on the known linear prediction method, a simple and efficient model is developed in which segments of the speech signal are classified as voiced or unvoiced using the innovative voiced and unvoiced cycle concept. Manuscript profile -
Open Access Article
18 - A New Evolutionary Estimation of Distribution Algorithm Based on Learning Automata
M. R. MeybodiIn order to overcome the poor behaviors of genetic algorithms in some problems other classes of evolutionary algorithms have been recently developed by researchers. Although these algorithms do not have the simplicity of classic genetic algorithms but they are superior MoreIn order to overcome the poor behaviors of genetic algorithms in some problems other classes of evolutionary algorithms have been recently developed by researchers. Although these algorithms do not have the simplicity of classic genetic algorithms but they are superior to genetic algorithms. The Probabilistic Model Building Genetic Algorithms or Estimation of Distribution Algorithms (EDAs) is one of these classes which is recently developed. In this paper we introduce a new estimation of distribution algorithm based on Learning Automata. The proposed algorithm is a model based search optimization method that uses a set of learning automata as a probabilistic model of the population of solutions in the search space. The proposed algorithm is a simple algorithm which has produced good results for the optimization problems considered in this problem. Manuscript profile -
Open Access Article
19 - Analysis, Design, and Fabrication of TEM Horn Antennas
Mohammad Khalaj-AmirhosseiniIn this paper, TEM horn antennas are reviewed as an ultra wideband antennas and then analyzed theoretically. The far zone fields, radiation patterns, directivity, and bandwidth of these antennas are determined. Also, the characteristic impedance and input reflection coe MoreIn this paper, TEM horn antennas are reviewed as an ultra wideband antennas and then analyzed theoretically. The far zone fields, radiation patterns, directivity, and bandwidth of these antennas are determined. Also, the characteristic impedance and input reflection coefficient of these antennas are determined using the taperd transmission lines model. Then some relations are introduced to optimum design of these antennas. Finally, two TEM horn antennas are designed and then are simulated, fabricated, and measured in an experiment. Manuscript profile -
Open Access Article
20 - Various Sources of Noise in Optical Fiber Communication Systems: A Review
M. K. Moravvej-FarshiThis paper reviews different sources of noise in optical fiber communication systems. The most important sources of noise, in such systems, are semiconductor lasers, optical amplifiers, and optical detectors. First, we review the relative intensity noise (RIN) and phas MoreThis paper reviews different sources of noise in optical fiber communication systems. The most important sources of noise, in such systems, are semiconductor lasers, optical amplifiers, and optical detectors. First, we review the relative intensity noise (RIN) and phase noise in semiconductor lasers. We show that, at low frequencies, RIN is negligible, and reaches its maximum at the damping frequency. RIN decreases with an increase in injection current, while it maximizes for the threshold current, at a certain frequency. The phase noise, which is related to laser line width, is constant below the damping frequency and increases to its maximum at the damping frequency. In semiconductor lasers, both RIN and phase noise decrease with an increase in the output power. Next, Amplified spontaneous emission (ASE) noise in erbium doped fiber amplifiers (EDFA) is reviewed. We show that, while ASE noise increases with an increase in the pump power, it decreases with an increase in the input signal power, for the various pump powers. Then, reviewing the formulation of noise figure (NF) in semiconductor optical amplifiers (SOA), we study the effects of cavity thickness and length on NF in both Fabry Perot (FP) and traveling wave amplifiers (TWA). Then we review sources of noise in an optical detector, and present an equivalent electric circuit model for it, including signal to noise ratio (SNR) and bit error rate (BER). Then, modal noise in a multimode optical fiber is reviewed. Finally, crosstalk as the main limiting parameter in optical multiplexer/demultiplexer units in multiwavelength systems is reviewed. Manuscript profile -
Open Access Article
21 - 3D Model Reconstruction by Silhouette, Stereo and Motion Features Fusion
H. Ghassemian H. EbrahimnezhadiIn this paper we propose a new approach to reconstruct the three-dimensional model of object using multi camera silhouettes during time. The main idea in this work is to reduce the current bottlenecks of three-dimensional model reconstruction including: ambiguous stereo MoreIn this paper we propose a new approach to reconstruct the three-dimensional model of object using multi camera silhouettes during time. The main idea in this work is to reduce the current bottlenecks of three-dimensional model reconstruction including: ambiguous stereo matching in low contrast regions; non-exact color adjustment between cameras which raises the matching uncertainty; shading and non-consistency of intensity duo to motion and varying the light angle which raises the motion estimation error; high dependency of silhouette method to the number of cameras. We propose a novel scheme to combine three popular methods i.e. stereo matching, motion and silhouette. The novelties of this work include: region growing for low color different neighborhood to increase the quality of background removing process, robust feature based stereo matching of multi camera images to find the exact place of some sparse singular points belong to the surface of object, singular points matching to robustly estimate the motion parameters in next frame. Also, we propose a hierarchical cone intersection method to extract the bounding edges visual hull from all the silhouettes captured by virtual cameras during time. Manuscript profile -
Open Access Article
22 - Top-Down Tracking Algorithm Based on Vehicle Trajectory Learning in the Traffic Scene
H. Sadoghi Yazdi M. Lotfizad M. Fathy E. KabirIn this paper, a trajectory learning-based vehicle tracking algorithm is presented which is a new top-down vehicle tracker. The history of trajectory is learnt by a novel sptio-temporal data base known center transition matrix, CTM. At first, the CTM is constructed on c MoreIn this paper, a trajectory learning-based vehicle tracking algorithm is presented which is a new top-down vehicle tracker. The history of trajectory is learnt by a novel sptio-temporal data base known center transition matrix, CTM. At first, the CTM is constructed on centers which are obtained using fuzzy clustering on vehicle trajectories. The i, j-th element of CTM indicates passing of the object from center i to center j in two consecutive frames which CTM is completed by multi-object tracking. The CTM is efficient in search of similar blobs in image sequences and can determine the radius and region of search and increasing of convergence rate of RLS predictor. The proposed tracking algorithm is tested in the intersection of a highway to a square which gives good results. Manuscript profile -
Open Access Article
23 - A Fast Algorithm for Hyperspectral Image Analysis Using SVM and Spatial Dependency
H. Ghassemian Ahmad KeshavarzRecent significant development in sensor technology makes possible Earth observational remote sensing system with unprecedented spectral resolution and data dimensionality. The value of these new sensor systems lies in their ability to acquire a nearly complete optical MoreRecent significant development in sensor technology makes possible Earth observational remote sensing system with unprecedented spectral resolution and data dimensionality. The value of these new sensor systems lies in their ability to acquire a nearly complete optical spectrum for each pixel in the scene. Such imaging spectrometry now makes possible the acquisition of data in hundreds of spectral bands simultaneously, and it is called hyperspectral images. With the limited number of training samples of hyperspectral images, the classification of these images using conventional feature extraction algorithms (PCA, ICA, PP, DBFE, DAFE and Wavelet) is considered useless. In this paper a two stages classification algorithm is proposed, by fussing the spatial and spectral information. In the first stage the classes of each pixel and its eight neighbors are identified, using a classical classification algorithm. In the second stage two primary classes of a pixel and its neighbors are compared in each node of decision tree by a SVM. The proposed, binary tree SVM, takes advantage of both the efficient computation of the tree architecture and the high classification accuracy of SVM. The hyperspectral data set used in our experiments is a scene from Indiana’s Indian Pine by the AVIRIS sensor. The examples results show the problem of limited training samples can be mitigated using the proposed algorithm; moreover the computational time is significantly reduced. This suggests that binary tree SVM could be a promising tool for classifying hyperspectral images. Manuscript profile -
Open Access Article
24 - Extraction and Modeling Context Dependent Phone Units for Improvement of Continuous Speech Recognition Accuracy by Phonemes Clustering
Mohammad Bahrani H. SametiThis paper proposes a proper context dependent method for improving the accuracy of a Persian continuous speech recognition system. Due to some constraints in speech recognition system, the multiple phone units approach is utilized for extracting context dependent phone MoreThis paper proposes a proper context dependent method for improving the accuracy of a Persian continuous speech recognition system. Due to some constraints in speech recognition system, the multiple phone units approach is utilized for extracting context dependent phone units. In this approach, each phoneme is clustered to some phoneme variations, and then each phoneme variation is modeled separately. Unsupervised phoneme clustering is done using k-means clustering algorithm. The new effective method is proposed for calculating the centroid of clusters. The proper number of cluster for each phoneme is determined according to amount of training data for that phoneme and recognition accuracy of that phoneme using context independent models. The number of clusters is then optimized by try and error methods. Then each cluster is modeled as a context dependent phone unit. The reduction in word error rate is about 22% using these models. Manuscript profile -
Open Access Article
25 - Array Processing Based on GARCH Model
H. Amiri H. Amindavar M. KamareiIn this paper, we propose a new model for additive noise based on GARCH time-series in arraysignal processing. Due to the some reasons such as complex implementation and computational problems, probability distribution function of additive noise is assumed Gaussian. In MoreIn this paper, we propose a new model for additive noise based on GARCH time-series in arraysignal processing. Due to the some reasons such as complex implementation and computational problems, probability distribution function of additive noise is assumed Gaussian. In the different applications, scrutiny and measurement of noise shows that noise can sometimes significantly non-Gaussian and thus the methods based on Gaussian noise will degrade in an actual conditions. Heavy-tail probability density function (PDF) and time-varying statistical characteristics (e.g.; variance) are the most features of the additive noise process. On the other hand, GARCH process has important properties such as heavy-tail PDF (as excess kurtosis) and volatility modeling through feedback mechanism onto conditional variance so that it seems the GARCH model is a good candidate for the additive noise model in the array processing applications. In this paper, we propose a new method based on GARCH using the maximum likelihood approach in array processing and verify the performance of this approach in the estimation of the Direction-of-Arrivals of sources against the other methods and using the Cramer-Rao Bound. Manuscript profile -
Open Access Article
26 - A Simple Method for Online Recognition of Farsi Subwords
S. M. Razavi E. KabirIn this paper, a method for online recognition of Farsi subwords is presented. First, the dots and other signs of the input subword and their relative locations are recognized and the related group to that subword is chosen. If there is only one member in that group, it MoreIn this paper, a method for online recognition of Farsi subwords is presented. First, the dots and other signs of the input subword and their relative locations are recognized and the related group to that subword is chosen. If there is only one member in that group, its class is assigned to the input subword, otherwise, the subword body is compared to those of the group members and the subword with minimum distance to the input subword is found. The recognition system also proposes a maximum of nine subwords in the next ranks. The proposed method was tested on a database of 11 samples of 1000 subwords from different writers. The correct recognition rate for the first choice was 74.95%. It reached to 97.87% for the top 10 choices. Manuscript profile -
Open Access Article
27 - Computer Aided Graphology for Farsi Handwriting
A. A. Bahrami Sharif E. KabirGraphology is the science of study and analysis of the personality of an individual from his/her style of handwriting. In western communities, the most important application of graphology is the recruitment of job applicants. In this regard, computer aided extraction an MoreGraphology is the science of study and analysis of the personality of an individual from his/her style of handwriting. In western communities, the most important application of graphology is the recruitment of job applicants. In this regard, computer aided extraction and analysis of features from handwriting can be of great assistance to graphologists. The most dominant features of handwriting employed in graphology include the shape of the page margins, line spacing, line skew, word slant, size of letters, text density, writing speed and regularity. In this paper a number of methods are proposed for automated extraction of some of these features from Farsi handwriting. Experimental results on 118 test samples of different writers are presented and discussed. Manuscript profile -
Open Access Article
28 - A Method Based on Learning Automata for Adaptation of the Vigilance factor in Fuzzy ARTMAP Network
M. Anjidani M. R. MeybodiIn this paper, a method based on learning automata for adaptation of the vigilance factor in Fuzzy ARTMAP network when used for classification problems is proposed. The performance of the proposed algorithm is independent of the initial value for vigilance factor. Fuzz MoreIn this paper, a method based on learning automata for adaptation of the vigilance factor in Fuzzy ARTMAP network when used for classification problems is proposed. The performance of the proposed algorithm is independent of the initial value for vigilance factor. Fuzzy ARTMAP network in which the vigilance factor adapted using learning automata generates smaller structure with higher recognition rate. To study the performance of the proposed method it has been applied to several problems: circle in square, spirals and square in square problems. The results of experiments show the effectiveness of the proposed method. Manuscript profile -
Open Access Article
29 - Performance Evaluation of Direct Sequence Ultra Wideband Systems in Multipath Fading Channels
M. Dashti Mohammad Abtahi Sh. Shirvani MoghaddamUltra Wideband (UWB) technology has attracted considerable interest in the research and standardization communities, due to its promising ability to provide high data rate at low cost with relatively low power consumption. UWB is characterized by transmitting extremely MoreUltra Wideband (UWB) technology has attracted considerable interest in the research and standardization communities, due to its promising ability to provide high data rate at low cost with relatively low power consumption. UWB is characterized by transmitting extremely short duration radio impulses. The signal energy is thus spread over a band of frequencies up to a few GHz. In this paper we outline the attractive features of direct sequence ultra wideband systems employing antipodal signaling (DS_BPSK). First, we compare TH_PPM and DS_UWB in terms of their multiple access performance in AWGN environment. Compared with TH_UWB, results show that DS_UWB supports a larger number of users communicating at higher data rates. Then, we evaluate the multiple access performance of DS_UWB in multipath fading channels. We consider partial Rake receiver structure with different number of Rake fingers. Results show that DS-UWB system using Rake receiver is able to sustain BER less than 10e-5 even in channels suffering from severe multipath fading. Using 10 fingers Rake receiver, about 12 dB improvement in performance of system can be achieved. Manuscript profile -
Open Access Article
30 - Model Reference Adaptive Control Design for a Teleoperation System with Output Prediction
K. Hosseini-Sunny H. R. Momeni F. Janabi-SharifiIn this paper a new control scheme is proposed to ensure stability and performance of the teleoperation systems while a wide range of time delay of transmission line is allowed. For this mean, time delay is estimated and used to predict the plant output. A model referen MoreIn this paper a new control scheme is proposed to ensure stability and performance of the teleoperation systems while a wide range of time delay of transmission line is allowed. For this mean, time delay is estimated and used to predict the plant output. A model reference adaptive controller (MRAC) is designed for the master site using the predicted output of the plant. The proposed control system indicates good stability and force tracking performance. For the slave site, an independent MRAC is designed and it is shown that a good tracking for the position and velocity signals is achieved. Manuscript profile -
Open Access Article
31 - To Determine a Desired Characteristic Equation for Ramp Input Signal
Mohammad Haeri M. S. TavazoeiBased on Bessel-Thompson filter design method, a new procedure is introduced to determine a desired closed loop characteristic equation for the step input signal. The transient and steady state responses of the calculated system are similar to those of the CDM (Coeffici MoreBased on Bessel-Thompson filter design method, a new procedure is introduced to determine a desired closed loop characteristic equation for the step input signal. The transient and steady state responses of the calculated system are similar to those of the CDM (Coefficient Diagram Method) controller. Using some properties from Laplace transform, the characteristic equation is then employed to obtain a new closed loop transfer function which results in appropriate response for the ramp input signal. To evaluate the newly defined closed loop transfer function, a RST output feedback controller is designed and simulated. Manuscript profile -
Open Access Article
32 - A New and Robust Steganography Method for Data Hiding in JPEG Images
A. R. Naghsh-NilchiData hiding is one of the effective solutions for the exchange of confidential messages in un-secure communication channels such as Internet. In this paper, we propose a new and effective steganography method for robust hiding of information in images with JPEG format. MoreData hiding is one of the effective solutions for the exchange of confidential messages in un-secure communication channels such as Internet. In this paper, we propose a new and effective steganography method for robust hiding of information in images with JPEG format. The data is hidden in DCT coefficients of JPEG conversion of a bitmap image using a low quantization rate (for instance, 75% quantization rate) and then convert back to bitmap format. The new bitmap image is converted to JPEG format again, but with a higher quantization rate (90%, for instance). This resulted JPEG image, which carries the hidden data, is robust against the known attacks such as compatibility, F5, outguess and POV attacks. The experimental results show that although the available data capacity using the proposed algorithm is reduced and limited compare to the other similar methods, but it has a more effective robustness under the these attacks. Manuscript profile -
Open Access Article
33 - A Modified Multi-Band Spectral Subtraction for A Modified Multi-Band Spectral Subtraction for Speech Enhancement
M. Bekrani H. Sadoghi YazdiIn this paper, a modified multi band spectral subtraction is proposed for speech denoising. In this method by estimating the non-stationary noise statistics an estimate of the SNR for the speech signal is obtained which is used in the adaptive averaging of the speech si MoreIn this paper, a modified multi band spectral subtraction is proposed for speech denoising. In this method by estimating the non-stationary noise statistics an estimate of the SNR for the speech signal is obtained which is used in the adaptive averaging of the speech signal frames. In addition, by employing such estimate an over-subtraction factor can be obtained which substantially reduces the musical noise. The adjustment of the final algorithm parameters is accomplished based on the obtained SNR, such that the final algorithm has a minimum musical noise and distortion in the speech signal. The obtained results from the Itakura-Saito, global SNR and segmental SNR show that the proposed algorithm has an output signal with a superior quality compared to the multi-band spectral subtraction algorithm and its modified version. Manuscript profile -
Open Access Article
34 - Robust Recognition of Direct and Telephony Speech Using Proper Extraction of Feature Vectors and Their Modification by Neural Networks Inversion
M. Vali S. A. Seyed SalehiA vast amount of research is going on for design of robust speech recognition in to alleviate speech variability conditions. One of the variability aspects is the difference between telephony speech and direct speech (recorded in noise free conditions). In this paper by MoreA vast amount of research is going on for design of robust speech recognition in to alleviate speech variability conditions. One of the variability aspects is the difference between telephony speech and direct speech (recorded in noise free conditions). In this paper by using a set of experiments, it is shown that LHCB parameters are superior to traditional MFCCs for speech recognition applications when they are used in a neural network based speech recognition system for both direct and telephony speech. Then by extraction of LHCBs from direct and telephony speech, and training of a MLP based speech recognition model, a direct and telephony speech recognition system is developed. Using a neural network inversion based on gradient descent method, the telephony speech feature vectors are modified toward to the direct speech feature vectors and by training a second network on modified telephony and direct speech feature vectors a 1.4% enhancement on speech recognition was achieved. Later, using general inversion method of neural networks both telephony and direct speech feature vectors are modified in a manner which mainly contains phonetic information and not other speech variations. Then by the training of the second neural network on this dataset, the system achieved 2.98% and 1.68% higher recognition rate for direct and telephony speech, respectively. Manuscript profile -
Open Access Article
35 - New Optimization Approach in the Design of Yagi Uda Antenna
A. A. Lotfi-Neyestanak F. Hojjat KashaniIn this paper, several methods for optimization of a 5-elements Yagi antenna are proposed using genetic algorithm, genetic algorithm inspired by simulated annealing, genetic algorithm based on fuzzy decision making, and particle swarm method. High speed run time of Supe MoreIn this paper, several methods for optimization of a 5-elements Yagi antenna are proposed using genetic algorithm, genetic algorithm inspired by simulated annealing, genetic algorithm based on fuzzy decision making, and particle swarm method. High speed run time of SuperNEC software, it has been used for analyzing the presented methods. The use of genetic algorithm or genetic algorithm inspired by simulated annealing for antenna optimization in a specific frequency band, needs long run time. Besides, reduction of the number of population and the amount of repetition, causes decrease in optimization precision. So, an optimization system base on fuzzy decision making is proposed. In addition, the particle swarm method which has a good convergence rate and good performance has been proposed to obtain a better optimization. The comparison between the proposed optimization methods shows that the genetic based on fuzzy decision making and the particle swarm methods have the best performance and functionality and the least run time. Manuscript profile -
Open Access Article
36 - Novel Phase Shifters for Microstrip Reflectarray Antenna
H. Horaizi K. Keyghobad Sh. HosseinzadehA popular method for creating required phase shifts for patches in a microstrip reflectarray uses open ended stubs attached to the patches. Uniform stubs are narrowband and hence limit the bandwidth of the array. In this paper, two novel methods for designing broadband MoreA popular method for creating required phase shifts for patches in a microstrip reflectarray uses open ended stubs attached to the patches. Uniform stubs are narrowband and hence limit the bandwidth of the array. In this paper, two novel methods for designing broadband reactive phase shifters are proposed based on the method of least squares. A structure The frequency response of s to be attached to theA popular method for creating required phase shifts for patches in a microstrip reflectarray uses open ended stubs attached to the patches. Uniform stubs are narrowband and hence limit the bandwidth of the array. In this paper, two novel methods for designing broadband reactive phase shifters are proposed based on the method of least squares. A structure consisting of transmission line sections, open-ended stubs, and resistors is considered for the phase shifter. Another one consists of transmission lines and open-ended. A least square error function is constructed for the required phase shift and the characteristic impedances, electrical lengths of transmission lines and resistances are obtained by its minimization. Then, the circuit is realized by microstrip lines to be attached to the microstrip patch. It is shown that the novel phase shifters create the required phase shifts in a broader bandwidth than those of uniform stub phase shifters. The frequency response of proposed microstrip line phase shifters are validated by the results obtained using AWR's Microwave Office software. Manuscript profile -
Open Access Article
37 - Design and Implementation of an IGBT Gate Driver with Necessary Protections and SMD Devices
M. Fazeli S. A. AbrishamifarThe Gate drivers in modern power converters which use the power IGBT must be provide several main operations such as electrical isolation, current amplifying, and protection against overcurrent and overvoltage conditions. This paper describes such a new circuit which is MoreThe Gate drivers in modern power converters which use the power IGBT must be provide several main operations such as electrical isolation, current amplifying, and protection against overcurrent and overvoltage conditions. This paper describes such a new circuit which is made using SMD devices suitable for driving the high and medium power IGBTs. This driver includes an isolated switching power supply, buffer circuits, and several protection circuits. It can operate by an input signal at TTL level and %50 duty cycle and is able to work up to 6A peak current. Manuscript profile -
Open Access Article
38 - Search Space Reduction in Fingerprint Recognition Based on Block Orientation Field
S. Helfroush H. GhassemianClassification is the first essential step in every automatic fingerprint recognition system. Regarding to the time and expense of recognition process, it has the benefit of search space reduction. Conventional classification methods are based on visible fingerprint cla MoreClassification is the first essential step in every automatic fingerprint recognition system. Regarding to the time and expense of recognition process, it has the benefit of search space reduction. Conventional classification methods are based on visible fingerprint classes. However, due to small number of these classes and nonuniform distribution of fingerprints among them, continuous classification scheme has been addressed. In this method, a similarity criterion is defined and a degree of likeness is assigned to the similarity of input fingerprint and each fingerprint in database. According to similarity criterion, matching of input fingerprint is begun first with the image in database that is more similar to input fingerprint. In this paper, a new similarity measuring method is proposed and used for continuous classification of fingerprints. The method is based on block orientation field. It is translation and rotation invariant and does not need core point existence and detection. Experimental results on FVC2000 database demonstrate the effectiveness of the proposed algorithm in search space reduction compared with the other methods. Manuscript profile -
Open Access Article
39 - CDF (2,2) Wavelet Lossy Image Compression on CPLD
A. A. Lotfi-Neyestanak Mohammad Mohaghegh Hazrati Mohammad Mohaghegh Hazrati N. AhmidiThis paper presents a hardware implementation of CDF(2,2) wavelet image compressor. The design demonstrates that high quality circuit implementation is possible through the use of suitable data organization (partitioned approach) and algorithm-to-architecture mappings ( MoreThis paper presents a hardware implementation of CDF(2,2) wavelet image compressor. The design demonstrates that high quality circuit implementation is possible through the use of suitable data organization (partitioned approach) and algorithm-to-architecture mappings (parallel-ism or pipelining). A VHDL code for CDF(2,2) was developed to satisfy our objective. Then it was synthesized in Foundation 5.1 software and downloaded to CPLD XC9572 by a JTAG ByteBlaster cable. The original image was transmitted through serial port. The AVR’s ATmega8535 was used to implement serial protocol to and back from the CPLD. The main goal is to reach a higher performance and throughput with a single CPLD. Details of the encoder design have been discussed and the results are presented. Manuscript profile -
Open Access Article
40 - Optimum Design and Fabrication of Pen-Shaped Antenna
Mohammad Khalaj-AmirhosseiniIn this paper, a pen-shaped antenna, called Vlasov antenna, is introduced. This antenna has a simple structure and can be constructed by creating a slant at the end of a circular waveguide. The main property of this antenna is its suitable radiation by excitation of som MoreIn this paper, a pen-shaped antenna, called Vlasov antenna, is introduced. This antenna has a simple structure and can be constructed by creating a slant at the end of a circular waveguide. The main property of this antenna is its suitable radiation by excitation of some modes such as TM01, which are symmetrical. The analysis of the antenna is done qualitatively and then the manner of its design is introduced. A pen-shaped antenna is designed in the X band and then is simulated, fabricated, and its performance is measured. Manuscript profile -
Open Access Article
41 - A New CMA Algorithm for Adaptive Array Systems with Rayleigh Channel Fading in the Mobile Communications Based on CDMA
E. Jedari Mohammad Hakkak M. KamareiIn this paper, we propose a time-varying multi-path vector channel model for the cellular CDMA-based communication system environment. A modified CMA to use in CDMA system environment is presented. We assume that the angular spread of each source to be large so that fad MoreIn this paper, we propose a time-varying multi-path vector channel model for the cellular CDMA-based communication system environment. A modified CMA to use in CDMA system environment is presented. We assume that the angular spread of each source to be large so that fading is non-coherent across the elements of the antenna array. The proposed modified CMA algorithm is more suitable in studying the convergence performance and the radiation patterns of uniform linear for tracking signal sources in CDMA mobile systems. Comparing the signal to noise ratio at the output of the algorithm of a uniform linear with the theoretical results proves the efficiency of the proposed algorithm. The BER performance with DBPSK modulation is also compared for CMA and VS-CMA algorithms in linear array. Manuscript profile -
Open Access Article
42 - Comparsion of Harmonic Propagation and Whack-a-mole Phenomena Compensation on Radial Distribution Feeder Using Parallel Active Power Filter with Constant and Controlled Gains
H. R. Ezzati A. Yazdian VarjaniIn order to damping harmonic propagation effect, the active power filters (APF) are installed on distribution systems. This installation also may cause harmonic oscillation effect named Whack-a-mole. In this paper using simulation results, the two mentioned effects are MoreIn order to damping harmonic propagation effect, the active power filters (APF) are installed on distribution systems. This installation also may cause harmonic oscillation effect named Whack-a-mole. In this paper using simulation results, the two mentioned effects are decreased efficiently for a ten-bus power radial distribution feeder for any nonlinear load connections (harmonic current or voltage source) by using constant gain Kv=1/Zc The characteristic impedance, Zc, is nondeterministic and variable, so the APF's gain should be controlled actively. In this paper the parallel active filter gain is designed such that by producing proper compensating current, the harmonic distortion on APF bus is controlled and the harmonic propagation and oscillation effects are prevented by keeping the harmonic distortion in an allowable interval. By adjusting APF gain, the effective compensation current will decrease and so the power loss and cost, the benefit of applying adjustable gain APF. Manuscript profile -
Open Access Article
43 - Multi-Objective Particle Swarm Classifier
Seyed-Hamid ZahiriA multi-objective particle swarm optimization (MOPSO) algorithm has been used to design a classifier which is able to optimize some important pattern recognition indices concurrently. These are Reliability, Score of recognition, and the number of hyperplanes. The propos MoreA multi-objective particle swarm optimization (MOPSO) algorithm has been used to design a classifier which is able to optimize some important pattern recognition indices concurrently. These are Reliability, Score of recognition, and the number of hyperplanes. The proposed classifier can efficiently approximate the decision hyperplanes for separating the different classes in the feature space and dose not have any over-fitting and over-learning problems. Other swarm intelligence based classifiers do not have the capability of simultaneous optimizing aforesaid indices and they also may suffer the over-fitting problem. The experimental results show that the proposed multi-objective classifier can estimate the optimum sets of hyperplanes by approximating the Pareto-front and provide the favorite user's setup for selecting aforesaid indices. Manuscript profile -
Open Access Article
44 - A New Ensemble Learning Method for Improvement of Classification Performance
S. H. Nabavi-Kerizi E. KabirThe combination of multiple classifiers is shown to be suitable for improving the performance of pattern recognition systems. Combining multiple classifiers is only effective if the individual classifiers are accurate and diverse. The methods have been proposed for dive MoreThe combination of multiple classifiers is shown to be suitable for improving the performance of pattern recognition systems. Combining multiple classifiers is only effective if the individual classifiers are accurate and diverse. The methods have been proposed for diversity creation can be classified into implicit and explicit methods. In this paper, we propose a new explicit method for diversity creation. Our method adds a new penalty term in learning algorithm of neural network ensembles. This term for each network is the product of its error and the sum of other networks errors. Experimental results on different data sets show that proposed method outperforms the independent training and the negative correlation learning methods. Manuscript profile -
Open Access Article
45 - Speech Coding Using Non-linear Prediction Based on Volterra Series Expansion
M. H. Savoji Gh. AlipoorIn recent years there has been a growing interest to employ non-linear predictive techniques and models in speech coding to further reduce bit-rate and therefore channel bandwidth. Usually neural nets are used for this purpose that result in an additional up to 3dB redu MoreIn recent years there has been a growing interest to employ non-linear predictive techniques and models in speech coding to further reduce bit-rate and therefore channel bandwidth. Usually neural nets are used for this purpose that result in an additional up to 3dB reduction in the excitation signal energy. Non-linear prediction can also be performed based on Volterra series expansion wherein the expansion is usually limited to first and second terms, for simplicity (quadratic prediction). Early studies have shown that employing Volterra filters results in a much higher reduction in excitation signal energy (6 to 10 dB), as compared with neural nets. But, because of instability, this reduction can not be materialized in terms of bit-rate reduction or signal to noise improvement. This instability in the decoder is triggered by computational errors (i.e. due to quantization of the excitation signal) and high sensitivity of algorithms to these errors. In the original work, presented here, the instability in the codec is studied in both forward and backward prediction schemes using LS and LMS algorithms respectively. It is shown that stability can be obtained at the cost of losing most of saving in excitation signal energy where final reduction level is as much as for neural nets. With forward prediction, after stabilizing, in spite of a small increasing in the operational complexity for 20 to 45% of frames including the quadratic term will be beneficial. So a scheme is developed to perform non-linear prediction only on these frames. This algorithm results in an improvement of up to 4 dB in final signal to noise ratio. Sequential backward quadrant prediction, although much more interesting from implementation point of view, does not lead to an appreciable better performance over linear prediction. Manuscript profile -
Open Access Article
46 - A New Approximate Analytical Method for Performance Analysis of Regular LDPC Codes Iterative Decoding on AWGN Channels
H. Samimi P. Azmi Mohammad hakakIn this paper we propose a new Gaussian-based analytical method for performance analysis of regular LDPC codes iterative decoding on AWGN channel. The proposed method has good accuracy and low complexity in comparison with current methods. Based on our developed analyti MoreIn this paper we propose a new Gaussian-based analytical method for performance analysis of regular LDPC codes iterative decoding on AWGN channel. The proposed method has good accuracy and low complexity in comparison with current methods. Based on our developed analytical equations, we present an error propagation model for the iterative decoder of LDPC codes which can be used as a simple tool for convergence analysis of LDPC codes on the AWGN channel. Manuscript profile -
Open Access Article
47 - A Parabolic Equation Approach for Modeling Wave Propagation through Window Structures
N. noori H. HoraiziIn this paper, the parabolic equation method is applied to analyze radio wave propagation through window structures. By this method, a typical window propagation situation is simulated for different window sizes and frame types. The simulation results are represented fo MoreIn this paper, the parabolic equation method is applied to analyze radio wave propagation through window structures. By this method, a typical window propagation situation is simulated for different window sizes and frame types. The simulation results are represented for both normal and oblique incident cases of uniform and non-uniform plane wave. Results from the implementation of the parabolic equation method show good agreement with FDTD reported simulations. Base on this study, as the parabolic equation method needs less memory size and CPU time against FDTD method, it can be used as an efficient algorithm to analyze this kind of problems. Manuscript profile -
Open Access Article
48 - Maximum Likelihood Detection in MIMO Communication Systems in Presence of Channel Estimation Error
M. biguesh A. A. farhoodi m.a. masnadi shiraziCapacity of wireless communication systems can be increased significantly by using arrays of antenna at the transmitter and receiver. In these so called multiple input multiple output (MIMO) communication systems, the algorithms used for detection of transmitted symbols MoreCapacity of wireless communication systems can be increased significantly by using arrays of antenna at the transmitter and receiver. In these so called multiple input multiple output (MIMO) communication systems, the algorithms used for detection of transmitted symbols are based on perfect channel state information (CSI) at the receiver side. The optimum detection approach in the sense of symbol error rate (SER) is Maximum likelihood (ML) detector. However, in the case of imperfect channel knowledge, the performance of this type of detection method degrades and symbol error rate (SER) increases. In this manuscript, we have briefly addressed the effect of imperfect channel knowledge on the performance of MIMO communication systems. Then, an analytical approach is proposed to cope with the destructive effect of CSI uncertainty on the ML detection algorithm and the performance of our proposed method is verified via computer simulations. Manuscript profile -
Open Access Article
49 - Design and Control of Three-Phase Shunt Active Power Filter Using the Sliding Mode Control and Energy Feedback
M. Nayeripour A. Yazdian Varjani M. Mohamadian H. R. mohammadiThe presence of nonlinear and unbalance loads in a three-phase network causes harmonics generation and dissipation in power network. One of the usual methods used for decreasing and eliminating these effects is the application of active and passive filter. The passive f MoreThe presence of nonlinear and unbalance loads in a three-phase network causes harmonics generation and dissipation in power network. One of the usual methods used for decreasing and eliminating these effects is the application of active and passive filter. The passive filter is designed for a particular kind of frequency and therefore eliminates a particular harmonics. Its weakness, however, is the possibility of its resonance with the equivalent network impedance and the large size of its elements. The active filter helps to remove the above problems. Moreover, this filter causes the harmonics to be rejected individually or all together and prohibits the occurrence of resonance with the network. One of the problems of these filters is the limited dynamics response that considers the steady state of harmonics. In this paper, unlike the previous methods on single phase analysis, the inverter used in active filter is analyzed more precisely, i.e., the simultaneous three- phase analysis. The ohmic effect of phase-inductances is also taken into account. The inverter control system makes use of two internal and external loops. The external loop produces suitable signal for on/off switching through sliding mode control. The internal loop utilizes energy feedback to adjust the capacitor voltages. This new method effectively improves the speed of dynamic filter response in comparison with the previously reported methods and is able to quickly compensate harmonics and load unbalancing. Manuscript profile -
Open Access Article
50 - The Effect of Updating Routing Tables of Neighboring Nodes in AntNet Algorithm by Assistant Agents
A. soltani M. R. akbarzadeh M. NaghibzadehAppropriate routing in data transfer is a challenging problem that can lead to improved performance of networks in terms of lower delay in delivery of packets and higher throughput. Considering the highly distributed nature of networks, several multi-agent based algorit MoreAppropriate routing in data transfer is a challenging problem that can lead to improved performance of networks in terms of lower delay in delivery of packets and higher throughput. Considering the highly distributed nature of networks, several multi-agent based algorithms, and in particular ant colony based algorithms, have been suggested in recent years. However, considering the need for quick optimization and adaptation to network changes, improving the relative slow convergence of these algorithms remains an elusive challenge. Our goal here is to reduce the time needed for convergence and to accelerate the routing algorithm’s response to network failures and/or changes by imitating pheromone propagation in natural ant colonies. More specifically, information exchange among neighboring nodes is facilitated by proposing a new type of ant (assistant ants) to the AntNet algorithm. This method is an extension of authors’ earlier work by allowing intermediate nodes, in addition to destination nodes, to produce assistant ants. The resulting algorithm, the “modified AntNet,” is then simulated via NS2 on NSF and NttNet network topologies. The network performance is evaluated under various conditions. Statistical analysis of results confirms that the new method can significantly reduce the average packet delivery time and rate of convergence to the optimal route when compared with standard AntNet. Index Terms: AntNet, mobile agent, network routing, assistant ants. Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran, vol. 5, no. 1, pp. 41-46, Spring 2007. * Corresponding author’s address: Dept. of Electrical Engineering, Birjand University, P. O. Box 97175-376, Birjand, I. R. Iran. Solving Multi-Criteria Decision Making Problems Using Artificial Neural Networks M. Abdoos* and N. Mozayani Abstract: Decision making is finding the best compromised solution from all feasible alternatives. Multi-criteria decision making is one of the most applied branches of decision making. Many methods have been presented for solving MCDM problems ever since. Among these methods, simple additive weighting, SAW, is the most commonly used method. In this paper, two methods are proposed for solving MCDM problems based on artificial neural networks. This paper shows an application of soft computing techniques in classic problems, such as decision making. Herein, two methods are presented based on both supervised and unsupervised neural networks. The results of the methods have been compared with SAW. Index Terms: Multi-criteria decision making, simple additive weighting method, perceptron network, artificial neural network, Kohonen network. Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran, vol. 5, no. 1, pp. 47-52, Spring 2007. * Corresponding author’s address: Dept. of Computer Eng., Iran University of Science and Technology, Narmak, Tehran, 16845, I. R. Iran. Appropriate routing in data transfer is a challenging problem that can lead to improved performance of networks in terms of lower delay in delivery of packets and higher throughput. Considering the highly distributed nature of networks, several multi-agent based algorithms, and in particular ant colony based algorithms, have been suggested in recent years. However, considering the need for quick optimization and adaptation to network changes, improving the relative slow convergence of these algorithms remains an elusive challenge. Our goal here is to reduce the time needed for convergence and to accelerate the routing algorithm’s response to network failures and/or changes by imitating pheromone propagation in natural ant colonies. More specifically, information exchange among neighboring nodes is facilitated by proposing a new type of ant (assistant ants) to the AntNet algorithm. This method is an extension of authors’ earlier work by allowing intermediate nodes, in addition to destination nodes, to produce assistant ants. The resulting algorithm, the “modified AntNet,” is then simulated via NS2 on NSF and NttNet network topologies. The network performance is evaluated under various conditions. Statistical analysis of results confirms that the new method can significantly reduce the average packet delivery time and rate of convergence to the optimal route when compared with standard AntNet. Index Terms: AntNet, mobile agent, network routing, assistant ants. Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran, vol. 5, no. 1, pp. 41-46, Spring 2007. * Corresponding author’s address: Dept. of Electrical Engineering, Birjand University, P. O. Box 97175-376, Birjand, I. R. Iran. Solving Multi-Criteria Decision Making Problems Using Artificial Neural Networks M. Abdoos* and N. Mozayani Abstract: Decision making is finding the best compromised solution from all feasible alternatives. Multi-criteria decision making is one of the most applied branches of decision making. Many methods have been presented for solving MCDM problems ever since. Among these methods, simple additive weighting, SAW, is the most commonly used method. In this paper, two methods are proposed for solving MCDM problems based on artificial neural networks. This paper shows an application of soft computing techniques in classic problems, such as decision making. Herein, two methods are presented based on both supervised and unsupervised neural networks. The results of the methods have been compared with SAW. Index Terms: Multi-criteria decision making, simple additive weighting method, perceptron network, artificial neural network, Kohonen network. Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran, vol. 5, no. 1, pp. 47-52, Spring 2007. * Corresponding author’s address: Dept. of Computer Eng., Iran University of Science and Technology, Narmak, Tehran, 16845, I. R. Iran. Appropriate routing in data transfer is a challenging problem that can lead to improved performance of networks in terms of lower delay in delivery of packets and higher throughput. Considering the highly distributed nature of networks, several multi-agent based algorithms, and in particular ant colony based algorithms, have been suggested in recent years. However, considering the need for quick optimization and adaptation to network changes, improving the relative slow convergence of these algorithms remains an elusive challenge. Our goal here is to reduce the time needed for convergence and to accelerate the routing algorithm’s response to network failures and/or changes by imitating pheromone propagation in natural ant colonies. More specifically, information exchange among neighboring nodes is facilitated by proposing a new type of ant (assistant ants) to the AntNet algorithm. This method is an extension of authors’ earlier work by allowing intermediate nodes, in addition to destination nodes, to produce assistant ants. The resulting algorithm, the “modified AntNet,” is then simulated via NS2 on NSF and NttNet network topologies. The network performance is evaluated under various conditions. Statistical analysis of results confirms that the new method can significantly reduce the average packet delivery time and rate of convergence to the optimal route when compared with standard AntNet. Index Terms: AntNet, mobile agent, network routing, assistant ants. Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran, vol. 5, no. 1, pp. 41-46, Spring 2007. * Corresponding author’s address: Dept. of Electrical Engineering, Birjand University, P. O. Box 97175-376, Birjand, I. R. Iran. Solving Multi-Criteria Decision Making Problems Using Artificial Neural Networks M. Abdoos* and N. Mozayani Abstract: Decision making is finding the best compromised solution from all feasible alternatives. Multi-criteria decision making is one of the most applied branches of decision making. Many methods have been presented for solving MCDM problems ever since. Among these methods, simple additive weighting, SAW, is the most commonly used method. In this paper, two methods are proposed for solving MCDM problems based on artificial neural networks. This paper shows an application of soft computing techniques in classic problems, such as decision making. Herein, two methods are presented based on both supervised and unsupervised neural networks. The results of the methods have been compared with SAW. Index Terms: Multi-criteria decision making, simple additive weighting method, perceptron network, artificial neural network, Kohonen network. Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran, vol. 5, no. 1, pp. 47-52, Spring 2007. * Corresponding author’s address: Dept. of Computer Eng., Iran University of Science and Technology, Narmak, Tehran, 16845, I. R. Iran. Appropriate routing in data transfer is a challenging problem that can lead to improved performance of networks in terms of lower delay in delivery of packets and higher throughput. Considering the highly distributed nature of networks, several multi-agent based algorithms, and in particular ant colony based algorithms, have been suggested in recent years. However, considering the need for quick optimization and adaptation to network changes, improving the relative slow convergence of these algorithms remains an elusive challenge. Our goal here is to reduce the time needed for convergence and to accelerate the routing algorithm’s response to network failures and/or changes by imitating pheromone propagation in natural ant colonies. More specifically, information exchange among neighboring nodes is facilitated by proposing a new type of ant (assistant ants) to the AntNet algorithm. This method is an extension of authors’ earlier work by allowing intermediate nodes, in addition to destination nodes, to produce assistant ants. The resulting algorithm, the “modified AntNet,” is then simulated via NS2 on NSF and NttNet network topologies. The network performance is evaluated under various conditions. Statistical analysis of results confirms that the new method can significantly reduce the average packet delivery time and rate of convergence to the optimal route when compared with standard AntNet. Manuscript profile -
Open Access Article
51 - Solving Multi-Criteria Decision Making Problems Using Artificial Neural Networks
M. abdoos N. MozayaniDecision making is finding the best compromised solution from all feasible alternatives. Multi-criteria decision making is one of the most applied branches of decision making. Many methods have been presented for solving MCDM problems ever since. Among these methods, si MoreDecision making is finding the best compromised solution from all feasible alternatives. Multi-criteria decision making is one of the most applied branches of decision making. Many methods have been presented for solving MCDM problems ever since. Among these methods, simple additive weighting, SAW, is the most commonly used method. In this paper, two methods are proposed for solving MCDM problems based on artificial neural networks. This paper shows an application of soft computing techniques in classic problems, such as decision making. Herein, two methods are presented based on both supervised and unsupervised neural networks. The results of the methods have been compared with SAW. Manuscript profile -
Open Access Article
52 - Missile Autopilot Design Using Fuzzy Gain-Scheduling
A. Akbarzadeh Kalat H. R. MomeniIn this paper a controller using fuzzy gain-scheduling for the channels of a tactical missile is designed such that in flight trajectories, performance is achieved. In this design method, the fuzzy gain-scheduling zone centers are determined by a training algorithm acco MoreIn this paper a controller using fuzzy gain-scheduling for the channels of a tactical missile is designed such that in flight trajectories, performance is achieved. In this design method, the fuzzy gain-scheduling zone centers are determined by a training algorithm according to dynamic pressure, Mach number and coefficients of linear model of system in major operating points. The fuzzy system is learned using combined genetic and linear least squares algorithms. In this manner both global optimum solution and fast convergence are reachable. Moreover the membership functions in fuzzy inference system are chosen with special and suitable properties, which cause simple and effective scheduling process. Performance of this method is shown with case study simulation result. Manuscript profile -
Open Access Article
53 - An Agent-Based Parallel Programming for Grid Programming
H. DeldariComputational grids have provided the usage of computational distributed resources for computation-intensive applications. The development of programs that use these capabilities is one of the challenging issues for grid computing. In this article, an effort has been ma MoreComputational grids have provided the usage of computational distributed resources for computation-intensive applications. The development of programs that use these capabilities is one of the challenging issues for grid computing. In this article, an effort has been made in order to solve this problem by presenting mobile-agent-based parallel programming on the grid. The presentation of this model, which has been materialized by extending Alchemi™ grid infrastructure, adding agent properties and navigational commands that let the user to develop his/her program by using agents’ mobility and communication between them. In order to evaluate the system, algorithm of matrix multiplication as well as algorithm of finding the convex hull of a series of points have been implemented in the mentioned system. Manuscript profile -
Open Access Article
54 - Development of a Secure Web Service Using RUPSec
S. M. Hosseininezhad G. Elahi P. JaferianSecurity issues are considered as major hurdles in extensive utilization of web services in enterprise. There has been work on standards, protocols, and technologies to answer some of these concerns. Nevertheless, problems arise and the issues remain. One needs to reco MoreSecurity issues are considered as major hurdles in extensive utilization of web services in enterprise. There has been work on standards, protocols, and technologies to answer some of these concerns. Nevertheless, problems arise and the issues remain. One needs to recognize security needs before he can tackle the task of selecting the right standard and mechanism to provide a secure system. In this paper, a case study is followed and thru that an approach for utilizing RUPSec for development of a secure web service is offered. The major objective has been to provide a way to discover and extract security needs of web services based on threats against them. Furthermore, RUPSec’s strength in pinpointing threats and security requirements is tested. Manuscript profile -
Open Access Article
55 - Determination of Control Variables in Power Systems to Maximum Load Restoration
H. Afrakhte A. Yazdian VarjaniThis paper presents a new method to maximize load restoration in faulted condition in power systems. Control variables which are used to restore maximum load include tap of power transformers, generation rescheduling, and load shedding in the worst case. Modeling is don MoreThis paper presents a new method to maximize load restoration in faulted condition in power systems. Control variables which are used to restore maximum load include tap of power transformers, generation rescheduling, and load shedding in the worst case. Modeling is done in three stages with various control variables arrangements. In the first stage of modeling, power transformer tap is used as a control variable. In the second stage, power transformers taps and generations rescheduling are considered. In the last stage, load shedding as another variable is added to decision variable spaces. Since the number of variables is high and final solution space can be nonlinear, genetic algorithm is used in the optimization process. The capabilities of the proposed method were assessed using IEEE-RTS test system with satisfactory results. Manuscript profile -
Open Access Article
56 - Experiments and New Mathematical Models for Prediction of Transformer Oil Characteristics under Environment Pressure Stress
Mohammad Mirzaie Ahmad Gholami H. R. TayebiMineral oil in transformer is used for its insulation property and thermal transfer to external environment. Transformer oil is always under air pressure variation effects due to contact to external by silica gel chamber and the pressure which depends on the height of s MoreMineral oil in transformer is used for its insulation property and thermal transfer to external environment. Transformer oil is always under air pressure variation effects due to contact to external by silica gel chamber and the pressure which depends on the height of sea level. Therefore air pressure can affect on insulation parameters and its age. Air pressure changing can cause oil viscosity variation. In this paper, the air pressure effects on oil properties are studied by the use of tests carried out and measuring of the insulation characteristics. In a laboratory environment, air pressure was changed from 40 to 1250 mmHg using a pump. Then conductivity/leakage current and breakdown voltage are measured and analyzed. These results are used to presenting estimation models and also for suggestion of a new simple model by mathematical methods and then the models were compared to each other. Manuscript profile -
Open Access Article
57 - An Antenna Radiation Pattern Measurement System at Ordinary Room Using Adaptive Filter
J. Dianat Ch. Ghobadi J. NouriniaIn this work the inverse transfer function of the measurement room is obtained using a linear and RLS (recursive least-squares algorithm) adaptive filter. At first, an antenna with known pattern (reference antenna) is placed in the test zone to obtain the optimal tap we MoreIn this work the inverse transfer function of the measurement room is obtained using a linear and RLS (recursive least-squares algorithm) adaptive filter. At first, an antenna with known pattern (reference antenna) is placed in the test zone to obtain the optimal tap weights of the adaptive filter. Once the filter converges, the learning stage finishes. After that the reference antenna is replaced with the test antenna and its pattern is measured and the data of the measurement is filtered by the optimal tap weights adaptive filter. The filter cancels the stray signals (reflected and scattered signal) and produces the radiation pattern of the test antenna. This technique is superior to that of others because it has better accuracy and it is less costly. Manuscript profile -
Open Access Article
58 - Nastaliq CAPTCHA
M. H. Shirali-Shahreza Mohammad Shirali-ShahrezaNowadays, many daily human activities such as education, trade, talks, etc are done by using the Internet. In such things as registration on Internet web sites, hackers write programs to make automatic false registration that waste the resources of the web sites while i MoreNowadays, many daily human activities such as education, trade, talks, etc are done by using the Internet. In such things as registration on Internet web sites, hackers write programs to make automatic false registration that waste the resources of the web sites while it may also stop it from functioning. Therefore, human users should be distinguished from computer programs. To this end, this paper presents a method for distinction of Persian and Arabic-language users from computer programs based on Persian and Arabic texts using Nastaliq font. In this method, the image of a Persian or Arabic word written in Nastaliq font is chosen from a dictionary, and it is shown to the user, then he is asked to type it. Considering that the presently available Persian and Arabic OCR programs cannot identify these words, the word can be identified only by a Persian or Arabic-language user. The proposed method has been implemented by the Java language. Manuscript profile -
Open Access Article
59 - Defect Detection in Textile Fabrics Using Modified Local Binary Patterns
F. Tajeripour E. Kabir a. sheikhiOne of the methods which can produce powerful features for texture classification is Local Binary Patterns, LBP. In this paper we propose a method for defect detection in textile fabrics using these features. In the training stage, at first step LBP operator is applied MoreOne of the methods which can produce powerful features for texture classification is Local Binary Patterns, LBP. In this paper we propose a method for defect detection in textile fabrics using these features. In the training stage, at first step LBP operator is applied to an image of defect free fabric, pixel by pixel, and the reference feature vector is computed. Then this image is divided into windows and LBP operator is applied on each of these windows. Based on comparison to the reference feature vector a suitable threshold for defect free windows is found. In the detection stage, a test image is divided into windows and using the threshold, defective windows can be detected. The proposed method is gray scale and shift invariant and can be used for defect detection in patterned and plain fabrics. Due to its simplicity online implementation is possible. Manuscript profile -
Open Access Article
60 - Design and Implementation of a 125 kV/1000 kVA High-Voltage Test System Using Series-Resonance Technique
A. A. Lotfi-Neyestanak H. R. Sadegh MohammadiThis paper presents the design, analysis, simulation, and implementation of a high-power resonance generator for testing high-voltage capacitive loads. The resonance generator includes a variable reactor which is the most important part of the system, a shielded isolat MoreThis paper presents the design, analysis, simulation, and implementation of a high-power resonance generator for testing high-voltage capacitive loads. The resonance generator includes a variable reactor which is the most important part of the system, a shielded isolation transformer, a voltage regulator (auto-transformer), an exciter transformer, a capacitive divider, a control cubicle, a digital voltmeter, a computer based partial discharge measurement system, a high-voltage filter, and a low-voltage filter. The paper describes the analysis and simulation of different parts of the system. It also presents the results of tests were performed using the implemented system on different capacitive loads, including the measurements of harmonic distortions and partial discharge. The inductance measurement of the implemented variable reactor matches with the simulation results. The partial discharge measurement of the implemented high-voltage series-resonance test system shows that the system is PD free up to 70 kV. Manuscript profile -
Open Access Article
61 - Analysis and Simulation of the Microwave Heating Process in Crude Oils using FDTD Technique
A. MohammadiA new method to simulate the microwave heating process in crude oils has been presented. Using convolution ( or differential) relation between E and H fields, (FD)2TD method is extracted by modifying the conventional FDTD technique for depressive materials. It is shown MoreA new method to simulate the microwave heating process in crude oils has been presented. Using convolution ( or differential) relation between E and H fields, (FD)2TD method is extracted by modifying the conventional FDTD technique for depressive materials. It is shown that the computer time and memory requirements to analyze and simulate the microwave heating process are extensively reduced. Eventually, the advantages of the technique to simulate the microwave heating process in crude oils are presented. Manuscript profile -
Open Access Article
62 - Letter to Sound Conversion for Persian Language Using Multi Layer Perceptrons
M. Namnabat M. M. HomayounpourConstruction of letter to sound (LTS) conversion systems in Persian is a difficult task. Because of the omission of some vowels in Farsi orthography, these systems in general have low efficiencies. In this paper, the structure of a letter to sound system, having three-l MoreConstruction of letter to sound (LTS) conversion systems in Persian is a difficult task. Because of the omission of some vowels in Farsi orthography, these systems in general have low efficiencies. In this paper, the structure of a letter to sound system, having three-layer architecture, was presented. The first layer is rule-based, and the second layer consists of five multi layer perceptron (MLP) neural networks and a controller section for pronunciations determination. The third layer has a MLP network for detection of geminated letters by using results obtained from the previous steps. The proposed system is designed to produce rational pronunciations for every word, where the rational pronunciation means a phonetic transcription, which follows the correct Farsi syllabification structure and the obvious rules of phonetics. The authors have achieved 88% and 61% correct letters and words performance respectively, which is quite satisfactory for a Farsi language LTS system. The correct letter criterion is the percentage of letters for which the pronunciations have been determined correctly and the correct word criterion is the percentage of words for which the pronunciations of the constituting letters have been determined correctly. Manuscript profile -
Open Access Article
63 - Performance Analysis of DFT block code in the Presence of Quantization Noise over Fading Channel
P. AzmiError control codes are among the most useful methods for mitigating the effect of fading and channel noise. Most of researches on error control codes are focused on the codes defined over finite (Galois) fields. In this paper, we consider DFT code defined over infinite MoreError control codes are among the most useful methods for mitigating the effect of fading and channel noise. Most of researches on error control codes are focused on the codes defined over finite (Galois) fields. In this paper, we consider DFT code defined over infinite Real field. We will analysis the performance of DFT code in the presence of quantization noise over fading channel. Our simulation results show that this code can efficiently suppress the effect of fading and channel noise. It will be shown that DFT code outperforms the well-known Reed Solomon code in low signal to noise ratio ranges. Manuscript profile -
Open Access Article
64 - An Exact Analytical Method for Performance Analysis of Maximal-Ratio and Equal-Gain Combining Diversity Schemes over Rayleigh Fading Channels in the Presence of Gaussian Channel Estimation Error
H. Samimi P. AzmiIn this paper, the probability of error of maximal-ratio combining (MRC) and equal-gain combining (EGC) diversity schemes with coherent binary phase shift keying (BPSK) is analyzed over Rayleigh fading channels in the presence of channel estimation error. The channel es MoreIn this paper, the probability of error of maximal-ratio combining (MRC) and equal-gain combining (EGC) diversity schemes with coherent binary phase shift keying (BPSK) is analyzed over Rayleigh fading channels in the presence of channel estimation error. The channel estimation errors cause errors in the required weighting coefficients of the diversity receivers. Such errors are generally modeled as complex Gaussian random variables. Based on this assumption, we develop novel exact analytical equations for the calculation of the probability of error in the presence of Gaussian errors in the weighting coefficients. Results show that the exact probability of error can be derived using the existing equations under the assumption of perfect channel estimation and by replacing the SNR with an effective SNR, which is due to the weighting coefficients errors. Manuscript profile -
Open Access Article
65 - Design and Implementation of a Circularly Polarized Microstrip Patch Antenna for GPS Application with Input VSWR Tuning Capability
A. A. HeidariIn this paper theoretical and experimental investigation of a right hand circularly polarized microstrip rectangular patch antenna have been presented. The antenna has a coaxial feed and designed for operating at L1 frequency (1575 MHz) of global positioning systems (GP MoreIn this paper theoretical and experimental investigation of a right hand circularly polarized microstrip rectangular patch antenna have been presented. The antenna has a coaxial feed and designed for operating at L1 frequency (1575 MHz) of global positioning systems (GPS). The antenna have been simulated and optimized using the HP-HFSS software in combination with Empipe3D. The inherently narrow bandwidth of the antenna was increased to 70 MHz using an air layer. A useful practical method was proposed in order to minimizing the input VSWR of the antenna. Theoretical and measured results have been presented and compared. Manuscript profile -
Open Access Article
66 - Investigation of New Structures for Carbon Nanotube FETs
R. Faez S. E. HosseiniA carbon nanotube field effect transistor (CNTFET) with Schottky contacts for the drain and the source has been investigated. It is shown that the saturation region of the transistor output characteristics is small. This limits the application of the transistor. To impr MoreA carbon nanotube field effect transistor (CNTFET) with Schottky contacts for the drain and the source has been investigated. It is shown that the saturation region of the transistor output characteristics is small. This limits the application of the transistor. To improve the saturation range in the output characteristics, new structures are proposed, and the simulation results are compared. The proposed structures have supperior output characteristics. Manuscript profile -
Open Access Article
67 - Design of a Low-Pass Switched Capacitor Fourth Order Chebyshev Filter Using an Improved Auto Zero Integrator
Mohammad Rashtian O. Hashemipour K. NaviIn this work the low-voltage high-speed auto zeroed integrator characteristics is improved by utilizing the non-linear properties of switches. Based on this improvement a newly designed structure for a low-pass filter is presented. The designed filter is a fourth order MoreIn this work the low-voltage high-speed auto zeroed integrator characteristics is improved by utilizing the non-linear properties of switches. Based on this improvement a newly designed structure for a low-pass filter is presented. The designed filter is a fourth order Chebyshev with pass band frequency of 500 KHz and sampling frequency of 5 MHz. Based on this method a fast and accurate sample and hold structure is introduced. The designed work is simulated using 0.25µm CMOS technology at 1.2 V supply voltage. Manuscript profile -
Open Access Article
68 - Analyzing Weighted Attack Graphs Using Genetic Algorithms
M. Abadi Saeed JaliliEach attack graph represents a collection of possible attack scenarios in a computer network. In this paper, we use weighted attack graphs (WAGs) for vulnerability assessment of computer networks. In these directed graphs, a weight is assigned to each exploit by the sec MoreEach attack graph represents a collection of possible attack scenarios in a computer network. In this paper, we use weighted attack graphs (WAGs) for vulnerability assessment of computer networks. In these directed graphs, a weight is assigned to each exploit by the security analyst. The weight of an exploit is proportionate to the cost required to prevent that exploit. The aim of analyzing a weighted attack graph is to find a critical set of exploits such that the sum of their weights is minimum and by preventing them no attack scenario is possible. In this paper, we propose a greedy algorithm, a genetic algorithm with a greedy mutation operator, and a genetic algorithm with a dynamic fitness function for analyzing the weighted attack graphs. The proposed algorithms are used to analyze a sample weighted attack graph and several randomly generated large-scale weighted attack graphs. The results of experiments show that the proposed genetic algorithms outperform the greedy algorithm and find a critical set of exploits with less total weight. Finally, we compare the performance of the second genetic algorithm with an approximation algorithm for analyzing several randomly generated large-scale simple attack graphs. The results of experiments show that our proposed genetic algorithm has better performance than the approximation algorithm and finds a critical set of exploits with less cardinality. Manuscript profile -
Open Access Article
69 - Adaptive Inverse Controller Design for Teleoperation Systems
M. Sha Sadeghi H. R. Momeni R. Amirifar S. GanjefarThis paper presents a new robust adaptive inverse control approach for a force-reflecting teleoperation system with varying time delay. In this approach, using the Smith predictor idea, an impedance controller and an adaptive inverse controller are designed, respectivel MoreThis paper presents a new robust adaptive inverse control approach for a force-reflecting teleoperation system with varying time delay. In this approach, using the Smith predictor idea, an impedance controller and an adaptive inverse controller are designed, respectively, for the master and slave robots such that the stability and performance of the closed-loop system are achieved in the presence of communication channels varying time delay. Also, based on robust control theory, two sufficient conditions for the stability of overall system are derived. The time domain desired specifications are contained in the design problem using the standard characteristic polynomials. Also, the proposed approach is compared with the sliding mode control. The simulation results show the proposed approach successfully compensates the position drift although time delay is randomly varying. Manuscript profile -
Open Access Article
70 - Optimization of Shunt Active Power Filter and Load Current with an Improved Sliding Mode Control
M. Nayeripour A. Yazdian Varjani M. MohamadianIn this paper, the compensation of load harmonic current is investigated using Lagrange function and minimization of load current active component. The results are compared with load harmonic current compensation using instantaneous three phase reactive power theory. N MoreIn this paper, the compensation of load harmonic current is investigated using Lagrange function and minimization of load current active component. The results are compared with load harmonic current compensation using instantaneous three phase reactive power theory. Next the PI and sliding mode controller are modified such that RMS value of error signal is minimized and state variables reach the sliding surface faster than conventional sliding mode controller. This improves the dynamic response of active power filter under load unbalance and harmonics conditions. Manuscript profile -
Open Access Article
71 - A New Method for Ripple Reduction of DC Voltage Using Active Filter
S. M. Dehghan A. Yazdian Varjani M. MohamadianFluctuations and ripples in voltage or current of DC power systems cause different malfunctions in operation of equipments and systems which are supplied by low quality distribution power systems. Therefore ripple reduction of voltage or current in DC power systems is v MoreFluctuations and ripples in voltage or current of DC power systems cause different malfunctions in operation of equipments and systems which are supplied by low quality distribution power systems. Therefore ripple reduction of voltage or current in DC power systems is very important. In this paper a new method is proposed to reduce ripple of DC voltage in high power system using an active power noise cancellation filter (APNCF). In the proposed method a hybrid system including series and parallel active filters for ripple reduction of load voltage and source current is used. Simulation and experimental results show the performance of the proposed method in dynamic and static states. Manuscript profile -
Open Access Article
72 - Detection of Coherent Radar Signals with Unknown Doppler Shift in Non-Gaussian Clutter
M. R. Taban A. mohammadi M. Modarres HashemiIn this paper the problem of detection of coherent radar signals with slow fluctuating amplitude and unknown Doppler shift in non-Gaussian clutter is considered. Coherent radar signal detection with unknown Doppler shift is rarely considered in the literature. It has be MoreIn this paper the problem of detection of coherent radar signals with slow fluctuating amplitude and unknown Doppler shift in non-Gaussian clutter is considered. Coherent radar signal detection with unknown Doppler shift is rarely considered in the literature. It has been demonstrated that in high resolution radars or in small grazing angles, the pseudo-Gaussian models are more accurate than Gaussian for clutter modeling. Optimum detection of signals with unknown Doppler shift in pseudo-Gaussian clutter contains a complicated multiple integral. Therefore, in this paper, generalized forms of the suboptimum GLR and CGLR detectors are proposed. Also, by estimating the random variable related to the clutter power (τ) in the test cell, GLRTLQ detector for unknown Doppler shift case is introduced and generalized. It is demonstrated that the proposed GLRTLQ detector has a simple structure and does not depend on the clutter distribution. The performances of the proposed detectors are evaluated by computer simulation. Manuscript profile -
Open Access Article
73 - A Nonoblivious Watermarking Scheme for Embedding Spread Spectrum-like Watermarks in the Wavelet Domain Using HVS Characteristics
A. R. zolghadr asli S. RezazadehIn this paper, we introduce a multiresolution watermarking method for copyright protection of digital images. The method is based on the discrete wavelet transform. A noise type Gaussian sequence is used as watermark. To embed the watermark robustly and imperceptibly, w MoreIn this paper, we introduce a multiresolution watermarking method for copyright protection of digital images. The method is based on the discrete wavelet transform. A noise type Gaussian sequence is used as watermark. To embed the watermark robustly and imperceptibly, watermark components are added to the significant coefficients of each selected subband by considering the human visual system (HVS) characteristics. Some small modifications are performed to improve HVS model. The host image is needed in watermark extraction procedure and Normalized Correlation Function (NCF) is used to measure similarities of extracted watermarks. It is shown that this method is robust against wide variety of attacks such as: additive noise, low pass filtering, compression, chopping, histogram equalization, rotation. Comparison with other methods shows the better performance of this suggested method. Manuscript profile -
Open Access Article
74 - A New Method for Short Block Length LDPC Code Design
M. Taki M. B. NezafatiIn this paper, we propose a new method for short block length Low Density Parity Check (LDPC) code design. The experimental results show that codes designed using the proposed algorithm have better performance compare to the other short block length LDPC codes. For LDPC MoreIn this paper, we propose a new method for short block length Low Density Parity Check (LDPC) code design. The experimental results show that codes designed using the proposed algorithm have better performance compare to the other short block length LDPC codes. For LDPC code design in short block length, two problems arise: first analytical estimation of code performance using density evolution method is unusable because of infinity of code length in this method. Second because of high code density, the probability of short loop in code graph (Girth) is high that dramatically reduces the code performance. We propose solution for both problems. First, code structure is designed in such a way that the code performance is near to that of the density evolution method estimates and second by improving Extended Bit Filling algorithm, short block length is controlled. Manuscript profile -
Open Access Article
75 - Fuzzy Evaluation of Long-Term Impacts of Electrical Appliances Efficiency Improvement on Load Pattern
M. Behrangrad M. Parsa-MoghaddamEvaluation of long-term home electrical appliance efficiency improvement scenarios on load and energy pattern needs comprehensive and precise modeling taking to account a variety of uncertainties. In the modeling process, all effective parameters should be considered. E MoreEvaluation of long-term home electrical appliance efficiency improvement scenarios on load and energy pattern needs comprehensive and precise modeling taking to account a variety of uncertainties. In the modeling process, all effective parameters should be considered. Estimation is the main source of information in this process which is a long-term large scale impact assessment procedure. Furthermore, the non homogeneous structure of load behavior in response to DSM policies makes the problem more sophisticated. The presented method implies fuzzy numbers to model the main uncertainties of the demand side reactions to the proposed DSM program. Here, the social classes of customers and their behaviors regarding energy utilization as well as time dependency of the problem parameters are taken into account. The paper focuses on the efficiency improvement of the electric appliances in Iran as a long-term DSM program, due to their considerable share in electricity consumption in residential sector. Finally, the numerical results are presented. Manuscript profile -
Open Access Article
76 - Combined Subtransmission Substation and Network Expansion Planning Using Genetic Algorithm, Ant Colony algorithm, and hybrid Ant Colony and Genetic Algorithm
V. Amir H. Seifi S. M. Sepasian g. r. yousefiThis research presents new algorithms for subtransmission simultaneous substation and network expansion planning. Given an existing system model, the projected load growth in a target year and various system expansion options, the algorithms find the optimal mix of sys MoreThis research presents new algorithms for subtransmission simultaneous substation and network expansion planning. Given an existing system model, the projected load growth in a target year and various system expansion options, the algorithms find the optimal mix of system expansion options to minimize the cost function subject to various system constraints and single contingencies on lines and transformers. The system expansion options considered include building new subtransmission lines/substations, the capacity to be upgraded and the service area of HV/MV substations. In this research, Genetic Algorithm (GA) with new coding, Ant Colony algorithm (AC) and hybrid Ant Colony and Genetic Algorithm (AC&GA) methods are employed. The optimization results are compared with successive elimination method to demonstrate the performance improvement. Manuscript profile -
Open Access Article
77 - An Adaptive Wavelet-Based Signal Denoising Schem
M. nasri H. Nezamabadi-pour S. SaryazdiIn this paper, a new class of nonlinear thresholding functions with a tunable shape parameter for wavelet-based signal denoising is presented. In addition, a new learning technique for training of thresholding neural network is introduced. Unlike to existing methods, bo MoreIn this paper, a new class of nonlinear thresholding functions with a tunable shape parameter for wavelet-based signal denoising is presented. In addition, a new learning technique for training of thresholding neural network is introduced. Unlike to existing methods, both the shape and the threshold parameters are tuned simultaneously using LMS rule. This permits us to consider the effects of both the threshold and the shape parameters on denoising. The proposed functions are tested in both universal-threshold and subband-adaptive denoising and compared with conventional functions. In addition, to evaluate the proposed training method, several numerical examples are performed. The experimental results obtained from denoising of several standard benchmark signals confirm the efficiency and effectiveness of the proposed methods. Manuscript profile -
Open Access Article
78 - Detection of Surface Defects on Apples for Quality Grading
M. Bazhan E. KabirIn this paper, two kinds of defects in Golden Delicious apples are recognized: bruise and russet. Russet is divided to two classes: russet in stem-end and russet out of stem-end. Apples are graded into three classes I, II and rejected, according to European standard. To MoreIn this paper, two kinds of defects in Golden Delicious apples are recognized: bruise and russet. Russet is divided to two classes: russet in stem-end and russet out of stem-end. Apples are graded into three classes I, II and rejected, according to European standard. To grade the apples, it is necessary to classify apple images into six classes: stem, calyx, bruise, russet in stem-end, russet out of stem-end and healthy. In this method, after pixel-based classification based on RGB color features by a perceptron neural network, correction in classification and stem detection is made. Hue and saturation features are used to correct the image regions classified to bruise. The correction of regions classified to calyx, russet in stem-end and russet out of stem-end is made based on the distance from the gravity center of the stem to the gravity center of each region. This paper presents a new method for defect classification and sub classification of russet to two classes, russet in stem-end and russet out of stem-end. Experimental results of the proposed algorithm show that the correct grading rate of 120 apple images is 81.66%. The grading errors result from misdetection of stem and errors in defect detection. Manuscript profile -
Open Access Article
79 - AUT-QPM: The New Framework to Query Evaluation for Data Warehouse Creation
N. Daneshpour Ahmad Abdollahzadeh BarforoushThe main reason of data warehouse systems failure is lack of justification proof. Analysis is an important task for decision about data warehouse creation. In this paper, we present the framework to justify data warehouse based on the input query types. We classify quer MoreThe main reason of data warehouse systems failure is lack of justification proof. Analysis is an important task for decision about data warehouse creation. In this paper, we present the framework to justify data warehouse based on the input query types. We classify query types and execute them on the databases and data warehouses with different sizes. The query response time and the number of I/O are evaluation parameters. In the experiments, different types of queries have been processed on databases and data warehouses and the results based on time and memory have been compared. These results are presented below: • For answering multidimensional queries and aggregated queries data warehouse systems will be required, • For answering nested queries and join queries, data warehouse system will be useful, • Database systems will be proper for answering simple queries and computational queries. In this work, the tools which can process the above ideas have been produced. The software will take user query and evaluate its process to decide having or not having data warehouses. Manuscript profile -
Open Access Article
80 - Investigation and Evaluation of Adaptive Nulling Methods of Array Antennas Using Genetic Algorithm
S. Jam M. DelroshanThis paper describes an approach to adaptive nulling with phased arrays. A genetic algorithm adjusts some of the least significant bits of the beam steering phase-shifters to minimize the total output power of the array. Also, some other criterions such as Mean Square E MoreThis paper describes an approach to adaptive nulling with phased arrays. A genetic algorithm adjusts some of the least significant bits of the beam steering phase-shifters to minimize the total output power of the array. Also, some other criterions such as Mean Square Error and Signal to Interference plus Noise Ratio are used and compared with each other. Using the least significant bits results in small perturbation in the main beam of the radiation pattern and puts the nulls in the direction of the interferences. Double search and weighted mutation are used to reduce the complexity of the algorithm. Also, the performance of genetic algorithm is compared with MPDR which is an optimum technique for beamforming. Finally, it is shown that the genetic algorithm performs superior to MPDR. Manuscript profile -
Open Access Article
81 - Design of E-plane and H-plane Waveguide Filters Using a Genetic Algorithm and Mode-Matching Method
A. Akbari Khezri A. R. AttariIn the conventional method for design of waveguide filters, equivalent circuits such as impedance or admittance inverters are used to model the waveguide discontinuities. These inverters are useful for design of filters with narrow bandwidth. In this paper using a genet MoreIn the conventional method for design of waveguide filters, equivalent circuits such as impedance or admittance inverters are used to model the waveguide discontinuities. These inverters are useful for design of filters with narrow bandwidth. In this paper using a genetic algorithm and mode-matching (MM) method, and without using the equivalent circuits, two E-plane and H-plane bandpass waveguide filters are designed. To verify the validity of MM method, the frequency response of filters is obtained by the PML-FDTD method. The two filters are also analyzed by the HFSS software. The results of MM method are in excellent agreement with the results provided by FDTD method and HFSS software. An important characteristic of a waveguide filter is the sensitivity of its frequency response to fabrication errors. In this paper, by using the Monte Carlo statistical method, sensitivity of the frequency response of E-plane and H-plane filters to fabrication errors are determined and compared with each other. Manuscript profile -
Open Access Article
82 - A Two-Stage Method for Classifiers Combination
S. H. Nabavi Karizi E. KabirEnsemble learning is an effective machine learning method that improves the classification performance. In this method, the outputs of multiple classifiers are combined so that the better results can be attained. As different classifiers may offer complementary informat MoreEnsemble learning is an effective machine learning method that improves the classification performance. In this method, the outputs of multiple classifiers are combined so that the better results can be attained. As different classifiers may offer complementary information about the classification, combining classifiers, in an efficient way, can achieve better results than any single classifier. Combining multiple classifiers is only effective if the individual classifiers are accurate and diverse. In this paper, we propose a two-stage method for classifiers combination. In the first stage, by mixture of experts strategy we produce different classifiers and in the second stage by using particle swarm optimization (PSO), we find the optimal weights for linear combination of them. Experimental results on different data sets show that proposed method outperforms the independent training and mixture of experts methods. Manuscript profile -
Open Access Article
83 - Radio Wave Propagation through Aperture Structures Using TLM
R. A. Sadeghzadeh A. A. Lotfi-Neyestanak Mohammad Jahanbakht m. n. MoghaddasiIn this paper transmission line matrix method is used to simulate the wave propagation through window structures. In this analysis a single window with precise dimensions and also a group of windows are considered. The effect of window’s dimension, window’s material, an MoreIn this paper transmission line matrix method is used to simulate the wave propagation through window structures. In this analysis a single window with precise dimensions and also a group of windows are considered. The effect of window’s dimension, window’s material, and angle of incidence are all evaluated in details and in each case, the method has been compared with other numerical results, such as FDTD, ray tracing, and finite element methods. Furthermore, in one case the implementation of TLM method was shown to have a good agreement with the measured values. Manuscript profile -
Open Access Article
84 - Blind Modulation Recognition of Communication Signals Based on Support Vector Machines
S. Shaerbaf M. Khademi Mohammad MolaviAutomatic modulation type classifier is a system which recognizes the modulation type of received signal automatically from some possible, pre-assumed types. Automatic modulation classification has applications such as spectrum surveillance, signal confirmation, interfe MoreAutomatic modulation type classifier is a system which recognizes the modulation type of received signal automatically from some possible, pre-assumed types. Automatic modulation classification has applications such as spectrum surveillance, signal confirmation, interference identification, software radio, etc. This paper, proposes a new method for recognition of 9 famous digital and analog modulations, which no need for prior knowledge of the signal to be recognized. This system is used to separate AM, FM, DSB and SSB in Analog modulations and 2ASK, 2PSK, 2FSK, 4PAM and 16QAM in digital modulations. Support Vector Machines (SVM) is used to classify these modulations and Genetic Algorithm is used to optimize Classifier Structure. Simulation results show that proposed algorithms have a good performance in comparison with other algorithms. Computational simplicity, High training speed and High classification rate, are the advantages of proposed algorithms. Manuscript profile -
Open Access Article
85 - Radar Detection in Gaussian Clutter Using Bayesian Estimation of Target
M. F. Sabahi M. Modarres Hashemi a. sheikhiIn many of detection problems the received signals models under two hypotheses, H0 and H1, are the same except that some model parameters have fixed value under H0. These models are so called Nested Models. One of the most important examples is detection of a target wit MoreIn many of detection problems the received signals models under two hypotheses, H0 and H1, are the same except that some model parameters have fixed value under H0. These models are so called Nested Models. One of the most important examples is detection of a target with unknown amplitude in the clutter. In this problem, one can assume similar models for received signals under H0 and H1 unless the target amplitude is assumed to be zero under H0. If the Bayesian approach used for treating unknown parameters, it can be shown that the likelihood ratio can be calculated as the ratio of the posterior and the prior probability of unknown parameters. Using this method a new detector for detection in Gaussian clutter is presented in this paper. Simulation results show that the proposed detector has much better performance compared with conventional GLRT detectors. It is also shown that a CFAR property is achieved provided that a small modifications in decision rule. Manuscript profile -
Open Access Article
86 - Blind Source Separation of Speech Signals Using a One-Dimensional Block DUET Algorithm
S. S. Fadaei M. H. KahaeiTo separate speech signals using blind techniques, the DUET algorithm is used in which each source signal is separated by masking the mixed signals in the Time-Frequency domain. To do so, a two dimensional Histogram of mixed parameters is generated which is computationa MoreTo separate speech signals using blind techniques, the DUET algorithm is used in which each source signal is separated by masking the mixed signals in the Time-Frequency domain. To do so, a two dimensional Histogram of mixed parameters is generated which is computationally burden, and thus, can not be used in real-time. In this paper, we introduce a new algorithm in which the separation process can be carried out online. Also, simulation results show that this algorithm has a comparable precision with respect to the DUET algorithm. Manuscript profile -
Open Access Article
87 - Forecasting the Number of Telecommunication Services’ Subscribers for the Next Years in the Country
A. Jahanbeigi M. E. KalantariEstimating the number of basic telephony services (fixed and mobile) and also residential users and enterprise subscribers of data services for the next years (up to 1389), is the goal of this paper. To predict the number of basic telephony services, the Cobb-Douglas mo MoreEstimating the number of basic telephony services (fixed and mobile) and also residential users and enterprise subscribers of data services for the next years (up to 1389), is the goal of this paper. To predict the number of basic telephony services, the Cobb-Douglas model, which uses the two important factors (the subscriber’s income and charge of service), is utilized. An increase of 18.48 and 27.18 million subscribers for fixed and mobile telephony services is predicted, respectively (in the time interval of 1385-89). The accuracy of estimates is also validated by comparing the results with actual numbers of subscription in the past years and also with global norms in the world (published by International Telecommunication Union). The potential number of residential users of data services is estimated to be about 14.43 million (or penetration rate of 19.6 percent for internet users), and enterprise subscribers about 217 thousand (in addition to governmental organizations) at the end of 1389. Finally, a range of demanded data services along with their required bit rates are identified in order to be used in bandwidth forecast and allocation in the next generation networks. Manuscript profile -
Open Access Article
88 - A New Statistical Approximation Method for SNR at EGC Rake Receiver over Independent Fading Channels
H. Samimi P. AzmiAn approximate analytical method for the evaluation of the cumulative distribution function (CDF) of the sum of L independent random variables (RVs) is presented. The proposed method is based on the convergent infinite series approach, which makes it possible to describ MoreAn approximate analytical method for the evaluation of the cumulative distribution function (CDF) of the sum of L independent random variables (RVs) is presented. The proposed method is based on the convergent infinite series approach, which makes it possible to describe the CDF in the form of an infinite series. The computation of the coefficients of this series needs complicated integrations over the RV’s probability density function (PDF). In some cases, the required integrations have closed-form in terms of confluent hypergeometric function and in other cases, the required integrations can not be analytically solved and have not a closed-form solution. In this paper, an approximation method for computation of the coefficients of the CDF series is presented that only needs the mean and the variance of the RV, so it has low computational complexity; it eliminates the need for calculation of complex functions and can be used as a unified tool for determining CDF of a sum of statistically independent RVs. To present an application for the developed approximation method, it is used to find the distribution of the sum of generalized Gamma (GG) RVs. The derived approximate expressions are used in the performance analysis of equal-gain combining (EGC) receivers operating over GG fading channels. The accuracy of the developed approximation method is verified by performing comparisons between exact existing results in the literature and computer simulations results. Manuscript profile -
Open Access Article
89 - A Hybrid Evolutionary Based Algorithm for HVAC-HVDC Transmission Expansion Planning Considering Losses and Security Constraints
S. Seyedshenava H. Seifi S. M. SepasianA hybrid genetic algorithm (GA)–simulated annealing (SA) approach, incorporating Differential Evolution (DE), fencing method (FM) as well as implicit enumeration method (IEM) is proposed in this paper for transmission expansion planning (TEP) of a grid, involving both H MoreA hybrid genetic algorithm (GA)–simulated annealing (SA) approach, incorporating Differential Evolution (DE), fencing method (FM) as well as implicit enumeration method (IEM) is proposed in this paper for transmission expansion planning (TEP) of a grid, involving both HVAC and HVDC links. The use of these algorithms makes a robust proposed approach by which for a hybrid HVAC-HVDC network, TEP may be performed fast and accurately. The proposed approach is assessed and evaluated for three test systems. Manuscript profile -
Open Access Article
90 - A Sensorless VSC-HVDC System for Connecting Asynchrony Distribution Systems
S. A. Abrishamifar E. AbiriIn this paper voltage source converter based HVDC (VSC-HVDC) is used for power transmission in asynchrony distribution systems. Direct power control (DPC) of three-phase space vector modulation (SVM) is employed for this control scheme. It is economically motivated to r MoreIn this paper voltage source converter based HVDC (VSC-HVDC) is used for power transmission in asynchrony distribution systems. Direct power control (DPC) of three-phase space vector modulation (SVM) is employed for this control scheme. It is economically motivated to replace the AC line voltage sensors with a virtual flux (VF) estimator. The control system is resistant to the majority of line voltage disturbances using by the idea of virtual flux. It is also effective to damp system oscillations and enhance power quality when power flow is reversed. Superior advantages of this method are good dynamic response and unity power factor of rectifier. Manuscript profile -
Open Access Article
91 - Transformers Oil Static Electrification Analysis by Using Open Cycle System
B. vahidi Gh. Rasuli HashemabadStatic electrification due to oil flow is the main reason for several electrical breakdown in large transformers. In the present paper this phenomenon has been investigated by the aid of open cycle system. Finally from tests results obtained by authors, the effects of a MoreStatic electrification due to oil flow is the main reason for several electrical breakdown in large transformers. In the present paper this phenomenon has been investigated by the aid of open cycle system. Finally from tests results obtained by authors, the effects of applied electric field, temperature and oil flow velocity on static electrification have been investigated. Manuscript profile -
Open Access Article
92 - “DANA”- An Agent with Understanding Persian Sentences and Performing Actions Abilities
M. Davoodabadi M. PalhangThe process of the comprehension of written natural language texts is usually called text understanding. Text understanding includes different processes and has many applications. One of the applications of natural language understanding systems is executing the imperat MoreThe process of the comprehension of written natural language texts is usually called text understanding. Text understanding includes different processes and has many applications. One of the applications of natural language understanding systems is executing the imperative sentences which has a wide usage in dialog based systems and robotics. Numerous works have been done in processing of Persian language but a few of them has considered the subject of Persian text understanding and performing actions after it. In this paper reports an implementation of a Persian understanding system called DANA. DANA accepts an imperative sentence or a question, applies morphological, syntactic and semantic analysis on it and creates a meaning representation. This system is able to understand some simple Persian sentences, responds to a few orders issued in Persian and answers some of user questions. The results of this project can be used for developing other types of natural language processing systems such as machine translation or question answering systems. Manuscript profile -
Open Access Article
93 - Determining of Classifiers Behavior Using Hidden Markov Model Based Decision Template
H. Sadoghi YazdiStudying of classifier behavior is interested from viewpoint of error checking and presentation of suitable solution for decreasing error rates and decreasing performance. Weakness operation of recognition system is because of small number of training samples, noisy sam MoreStudying of classifier behavior is interested from viewpoint of error checking and presentation of suitable solution for decreasing error rates and decreasing performance. Weakness operation of recognition system is because of small number of training samples, noisy samples, unsuitable extracted features, method of determining of system response. Presentation of suitable model for behavior or response of recognition system, we can improve operation of recognition system. In this paper, a new hidden Markov model based decision template is generated for modeling of neurons behavior in neural network. In existing methods, relation of neurons and interaction between them is not studied whereas; response of neural network includes response value of all neurons. So, relations of neurons are modeled using new hidden Markov decision templates. This method is used into three applications include recognition of Farsi number images, normal traffic in internet network, and recognition of types of vehicles. Increasing performance of neural network indicates to superiority of the proposed system. Manuscript profile -
Open Access Article
94 - Design and Simulation of a Two Stages OPAMP Using Positive Feedback for Achieving to a High Unity Gain Bandwidth and a High DC Gain
P. Moallem A. Shiri SichaniThe Fabrication of switch capacitor Filters and continuous time CMOS circuits, with a suitable unity gain bandwidth, a high DC gain and a high quality factor are a major challenge in integrated circuits design basically. This article is proposed a novel positive feedbac MoreThe Fabrication of switch capacitor Filters and continuous time CMOS circuits, with a suitable unity gain bandwidth, a high DC gain and a high quality factor are a major challenge in integrated circuits design basically. This article is proposed a novel positive feedback topology for designing of OPAMP kernel and then a sample of OPAMP based on this method by tuning of the fabrication parameters is designed. The results of simulations which are done in frequency and time domain demonstrate that unity gain bandwidth of the designed OPAMP is greater than 1.4GHz and DC gain is greater than 108dB that in comparison with similar designs based on positive feedback can demonstrate there are plentiful increment in unity gain bandwidth and suitable increment in DC gain. The phase margin of the designed OPAMP is greater than 170 degree. Moreover, investigation of the proposed design outputs in time domain demonstrates the stability of the proposed OPAMP. Manuscript profile -
Open Access Article
95 - Novel Automatic Clustering Technique Based on the Artificial Immune Algorithm
Seyed-Hamid ZahiriIn this paper a novel technique for automatic data clustering based on the artificial immune algorithm is proposed. The lengths of the antibodies are dynamically changed based on inter-clusters and intra-clusters distances by means of a fuzzy controller which has been a MoreIn this paper a novel technique for automatic data clustering based on the artificial immune algorithm is proposed. The lengths of the antibodies are dynamically changed based on inter-clusters and intra-clusters distances by means of a fuzzy controller which has been added to the immune algorithm to provide, also, a soft computing approach for data clustering. This idea leads to proper number of clusters and effective and powerful clustering process without any additional try and error efforts. Also the manual setting of the number of clusters is available in the proposed algorithm (like other unsupervised clustering approaches) after removing the fuzzy controller from the proposed clustering system. The method has been tested on the different kinds of the complex artificial data sets and well known benchmarks. The experimental results show that the performance of the proposed technique is much better than the k-means clustering algorithm (as a conventional one), specially for huge data sets with large feature vector dimensions. Furthermore, it is found that the performance of the proposed approach is comparable, sometimes better than the genetic algorithm based clustering technique (as an evolutionary clustering algorithm). Manuscript profile -
Open Access Article
96 - Application of PSO Algorithm in Economic and Emission Dispatch with Non-Smooth Cost Functions by Considering Transmission Losses and System Constraints
R. Hooshmand M. ParastegariPrecise and practical based economic dispatch is one of the most important problems in power systems. Thus, this paper proposes usage of particle swarm optimization (PSO) algorithm for solving economic dispatch problem. In this study real constraints of economic dispatc MorePrecise and practical based economic dispatch is one of the most important problems in power systems. Thus, this paper proposes usage of particle swarm optimization (PSO) algorithm for solving economic dispatch problem. In this study real constraints of economic dispatch problem are considered. For this purpose, it has been considered that the fuel cost function is a non-smooth one. On the other hand, reduction of the pollutants that is emitted from fossil fuel power plants is one of the goals of the optimization problem, so that we fulfill economic and emission dispatch at the same time for solving practical and optimum economic dispatch problem with consideration of many constraints in the operating point and transmission losses, these constraints are included in the proposed method. Finally, simulation results of the proposed method for economic dispatch are compared with those of the other methods such as tabu search, genetic algorithm, and artificial neural network. The results clearly show that the proposed method gives global optimum and fast solution compared to the other methods. Manuscript profile -
Open Access Article
97 - Design of UPFC Controller Using Bilinear Equation for Improving Power System Stability
M. Nayeripour A. Yazdian Varjani M. MohamadianIn this paper the model of UPFC is represented by a bilinear equation. Then with the second method of Lyapunov, the input of converter is derived such that the derivative of energy function is negative. The design of controller is carried out with two methods. In the fi MoreIn this paper the model of UPFC is represented by a bilinear equation. Then with the second method of Lyapunov, the input of converter is derived such that the derivative of energy function is negative. The design of controller is carried out with two methods. In the first method, the controller is linearized at operating point. In the second method, the nonlinear method is used in the series converter and the PI controller is used in the shunt converter. Reduction of first swing peak after fault clearing is the main advantage of designed controller with respect of PI controller. Manuscript profile -
Open Access Article
98 - Robust Position Control in DC Motor by Fuzzy Sliding Mode Control a Novel
M. Hendijani-Zadeh A. Yazdian Varjani M. MohamadianIn spite of improvement of the AC drive systems still the DC drives are widely used in industry. One of the problems associated with control of DC motor which might cause unsuccessful attempts for designing a proper controller would be the time-varying nature of DC moto MoreIn spite of improvement of the AC drive systems still the DC drives are widely used in industry. One of the problems associated with control of DC motor which might cause unsuccessful attempts for designing a proper controller would be the time-varying nature of DC motors parameters and variables which might be changed while working with the motion systems. In these conditions, the control system will not response properly. One of the best suggested solutions to overcome this problem would be the use of sliding mode control (SMC). SMC is not sensitive to parameters changes and yet would have a fair response to the systems variations. However, SMC suffers from some deficiencies including inflexibility in controller parameters. A Better response can be achieved by SMC in compare with classical methods but it is not the most optimized response. The fair solution can be defined through faster fulfillment of target, less overshoot and more consistency of the system against the changes of the parameters. In this paper, a new fuzzy based method is presented to increase the SMC ability to reach a more convenient solution. Optimized response can be achieved in terms of shorter settling time, less overshoot, and more stability. Manuscript profile -
Open Access Article
99 - Optimal Bidding in Electricity Market Using Game Theory
N. Baei M. Parsa-MoghaddamThis paper, presents a new approach for bidding strategy in spot electricity markets. A two-level optimization method is used for profit maximization of non-cooperative firms, while taking into account overall system constrains. In this approach, the market equilibrium MoreThis paper, presents a new approach for bidding strategy in spot electricity markets. A two-level optimization method is used for profit maximization of non-cooperative firms, while taking into account overall system constrains. In this approach, the market equilibrium points are determined as Nash Equilibria. In order to capture the behavior of all market participants and therefore, a much more competitive environment both the suppliers and consumers are considered as the players of the market. To avoid local maxima solutions, Genetic Algorithm based optimization is incorporated. The proposed method has been applied to IEEE 9 bus system with satisfactory results. Manuscript profile -
Open Access Article
100 - Dynamic Simulation of Electrical Arc Furnace Flicker
S. Meschi M. A. Golkar E. HashemzadehVoltage flicker and harmonics are the power quality problems which are introduced to the power system as a result of behavior of the arc furnace operation. To analyze harmonic and flicker generated by an arc furnace, accurate arc furnace models are needed. In this pape MoreVoltage flicker and harmonics are the power quality problems which are introduced to the power system as a result of behavior of the arc furnace operation. To analyze harmonic and flicker generated by an arc furnace, accurate arc furnace models are needed. In this paper, different arc furnace models with different level of complexity are reviewed. In the first part of this paper a new developed time domain static model based on a piece-wise linear approximation of the V-I characteristics of the arc furnace is presented. In the second part of the paper, dynamic model for an arc furnace using MATLAB (Simulink) is presented. In addition to this, the novelty of this simulation technique lies in the fact that the variation of power transmitted to the load by the arc furnace during the cycle of operation is considered, thus making the proposed model more accurate and dependent on the operating conditions of the load. Finally recommendations are made for the application of some of these models and the accuracy of the presented model to other models from the practical point of view by using MATLAB is shown. Manuscript profile -
Open Access Article
101 - Design and Implementation of Two Pipeline Architectures for Computing High-Order Moments of Grey-Level Images
M. Monajati E. KabirMoments are utilized in image processing for pattern recognition, machine vision and numerous feature extraction techniques. Due to computational complexity, it is difficult to use high order moments in real time processing. This paper presents the design of two new arc MoreMoments are utilized in image processing for pattern recognition, machine vision and numerous feature extraction techniques. Due to computational complexity, it is difficult to use high order moments in real time processing. This paper presents the design of two new architectures for real time computation of moments, up to order 14, M00 to M77, in gray level images, based on parallel systolic arrays and pipelining technique, using a 0.18μm CMOS technology. Implementation of the moment processing element (MPE) of the first architecture illustrates a processing speed of 125 frames/s for 1024×1024 grey-level images. The maximum operating frequency and the power consumption for an architecture with 5 elements is 133 MHz and 14.36 mW, respectively. Since the design is very low power, the number of parallel MPE’s can be easily increased. Simulation shows that with 11 parallel MPE’s, the first 49 moments of 1024×1024 image are computed with the speed of 30 frames/sec. To further decrease the latency of the first architecture, the second architecture is proposed, in which the add operation is performed only with a single adder and a compressor. Simulation shows that the latency of the second architecture is 3.3 times lower than that of the first architecture. Implementation of the second architecture illustrates the maximum operating frequency and the power consumption of 125 MHz and 58.34 mW, respectively. Operating frequency and power consumption of the second architecture is approximately the same as that of the first architecture which befit real time applications. Manuscript profile -
Open Access Article
102 - Improved Wavelet Spectral Subtraction Method Using LPC Analysis for Speech Enhancement
M. Heydari E. Nadernejad M. R. KaramiIn this paper, we proposed a new method for speech enhancement. The method is based on wavelet spectral subtraction. We use linear predictive coding (LPC) for noise estimation and extraction. The proposed method was compared with the wavelet spectral subtraction method. MoreIn this paper, we proposed a new method for speech enhancement. The method is based on wavelet spectral subtraction. We use linear predictive coding (LPC) for noise estimation and extraction. The proposed method was compared with the wavelet spectral subtraction method. The new method increased signal to noise ratio of the noise contaminated speech signal more than wavelet spectral subtraction method. Also, good results have been achieved in auditory test (Mean Opinion Score). Manuscript profile -
Open Access Article
103 - Rainfall Effects on Radio Wave Propagation at Ku and Ka Bands
A. A. Lotfi-NeyestanakTo simulate the effects of rain on the wave propagation, refractive index, size, and pattern of the rain drops should be characterized. By finding these parameters through the measurements, one is able to calculate scattering parameters from a particle and then extend i MoreTo simulate the effects of rain on the wave propagation, refractive index, size, and pattern of the rain drops should be characterized. By finding these parameters through the measurements, one is able to calculate scattering parameters from a particle and then extend it to a group of particles. In this study, attenuation, polarization changes, and phase shift are calculated by considering rainfall distribution and moment method. Based on the comparison of the simulation results and ITU recommendations, it is shown that ITU recommendations model is general and approximately presents average attenuation. Manuscript profile -
Open Access Article
104 - Classification of Breast Tumors on Sonogram Using Morphological Features of Tumors and Texture Features Behind and Around the Tumors
R. Jahandideh H. Behnam N. AhmadinejadUltrasonography is one of the most useful diagnostic tools for human soft tissue and is one of the methods that are in routine use for distinguishing benign and malignant breast tumors. But its diagnosis is operator dependent. In previous researches texture analysis fo MoreUltrasonography is one of the most useful diagnostic tools for human soft tissue and is one of the methods that are in routine use for distinguishing benign and malignant breast tumors. But its diagnosis is operator dependent. In previous researches texture analysis for solid breast mass classification is used. In those works texture features of the tumor are used, but sonologists notice to the features of the surrounding area of the tumors for their diagnosis. In this research as well as the morphological features of the mass the features of the surrounding area of the mass are also considered. MLP neural network is used for classification. 36 breast sonography images are used that 18 of them proved to be benign and 18 of them proved to be malignant through biopsy. The features are used in different combinations and it is shown that using the texture features of behind the tumor area and the same depth near the tumor provide meaningful result and also compensate the different adjustments of the systems. Manuscript profile -
Open Access Article
105 - A New Approach to Compress Multicarrier Phase-Coded Radar Signals
R. mohseni a. sheikhi m.a. masnadi shiraziMulticarrier phase coded signals have been recently introduced to achieve high range resolution in radar systems. As single carrier phase coded radars, the common method for compression of these signals, is using matched filter or computing the auto correlation function MoreMulticarrier phase coded signals have been recently introduced to achieve high range resolution in radar systems. As single carrier phase coded radars, the common method for compression of these signals, is using matched filter or computing the auto correlation function directly. In this paper we propose a new method based on fast Fourier transform (FFT) with lower computational load with respect to traditional approach. Furthermore, based on this new approach, a method for estimation of communication channel is introduced that can be used for improving detection performance and target position estimation in tracking mode. Manuscript profile -
Open Access Article
106 - On the Stability of Primal-Dual Congestion Control Algorithm in the Presence of Exogenous Disturbances
A. moarefianpour V. johari majdIn this paper, we consider the effects of exogenous disturbances on the closed-loop system of the congestion control problem in a network with general structure. This investigation is important since many of data flows in internet network are considered as unmodeled flo MoreIn this paper, we consider the effects of exogenous disturbances on the closed-loop system of the congestion control problem in a network with general structure. This investigation is important since many of data flows in internet network are considered as unmodeled flows. In contrast to previous works, we suppose that both senders and links in the network have dynamics. Each sender updates its sending rate to minimize its own cost function. The network is modeled based on fluid flow approximation with nonlinear dynamics for the links. In this research, we first derive the conditions for the existence of the system equilibrium point taking into account the constraint sets of the problem. Then, we prove input-to-state stability (ISS) of the closed-loop system for the congestion control problem with input and output disturbances in the network links. We further show that the obtain results are valid even when the routing matrix of the network varies. Finally, we verify the theoretical results by simulation on two different multi-link networks. Manuscript profile -
Open Access Article
107 - Design of Low Power High Speed Dilation Operator for Binary Images in CMOS Technology
M. hajirahimi E. KabirThis paper describes the design of hybrid wave-pipeline architecture for implementation of real time morphological dilation. With minor changes to this architecture, it can be utilized for erosion, closing, and opening operators. The new architecture results in higher s MoreThis paper describes the design of hybrid wave-pipeline architecture for implementation of real time morphological dilation. With minor changes to this architecture, it can be utilized for erosion, closing, and opening operators. The new architecture results in higher speed, less hardware complexity, and lower area and power dissipation compared to conventional pipeline implementation. In addition, it is faster than the wave-pipeline structure, without the difficulty of balancing the delay of long signal paths. Using the new architecture, three ASIC chips in 0.18µm CMOS are designed for binary image processing through Verilog. These chips dilate a 1024×1024 image by a 21×21 structuring element in 256.58μ s. The maximum frequency of the operations is 5.882 GHz, 5 GHz, and 4.167 GHz. For the power supply of 1.8 V and the 4.167 GHz frequency, the power dissipation is 597mW, 478 mW, and 410 mW, and the chip area is 0.118 mm2, 0.087 mm2, and 0.075 mm2, respectively. Manuscript profile -
Open Access Article
108 - Design of New TFCS Algorithm for Direction Finding of Multiple Speakers
M. atashbar M. H. KahaeiEstimation of speakers' directions is one of the interesting topics. In this paper, we introduce the TFCS algorithm for direction-of-arrival estimation of multiple speakers. In this algorithm, no limitations are imposed on the environment and speech signals. Simulation MoreEstimation of speakers' directions is one of the interesting topics. In this paper, we introduce the TFCS algorithm for direction-of-arrival estimation of multiple speakers. In this algorithm, no limitations are imposed on the environment and speech signals. Simulation results show that the proposed algorithm outperforms the recently addressed onset and spectral-based methods. Manuscript profile -
Open Access Article
109 - A New Voice Packing Method to Regenerate Lost Packets
Y. darmaniThis article introduces a new voice packing scheme to transfer voice samples over the Internet. This method aims to reduce the voice quality degradation caused by lost packets as far as possible. Regenerating lost voice packets in active nodes in the network, introduces MoreThis article introduces a new voice packing scheme to transfer voice samples over the Internet. This method aims to reduce the voice quality degradation caused by lost packets as far as possible. Regenerating lost voice packets in active nodes in the network, introduces more received voice quality at the receiver side compared with the other methods. This scheme is simulated using an unreliable network with an active node, and it shows more voice quality than the other schemes even if the network loses 50 percent of packets. Manuscript profile -
Open Access Article
110 - Using Adaptive Diffusion Coefficients in Partial Diffusion Equation for Image Noise Reduction
H. hassanpour M. nikpourThis paper proposes a new approach for image noise reduction using partial diffusion equation (PDE). Diffusion coefficient is an important parameter in PDE for image noise reduction. This parameter affects the noise reduction results and quality of edges in the denoised MoreThis paper proposes a new approach for image noise reduction using partial diffusion equation (PDE). Diffusion coefficient is an important parameter in PDE for image noise reduction. This parameter affects the noise reduction results and quality of edges in the denoised image. The existing PDE-based image denoising techniques experimentally adjust the diffusion coefficient. This paper proposes a new approach to adaptively adjust the diffusion coefficient. The proposed approach was applied on a number of standard images to evaluate its performance. The results indicate that the proposed approach outperform the existing PDE-based image denoisng techniques. Manuscript profile -
Open Access Article
111 - The Effect of Demand Response Programs on Iranian Electric Power Consumption
H. alami Gh. yousefi M. Parsa-MoghaddamDemand side management (DSM) is one of the most important methods which have been used to maximize the benefits of the electric power market participants. In the deregulated power systems, DSM is called demand response (DR). In this paper, two DR programs have been focu MoreDemand side management (DSM) is one of the most important methods which have been used to maximize the benefits of the electric power market participants. In the deregulated power systems, DSM is called demand response (DR). In this paper, two DR programs have been focused: time-of-use (TOU) and emergency demand response program (EDRP). In this paper DR is modeled considering both TOU and EDRP methods, simultaneously, using the single and multi period load models, based on the load elasticity concept. The proposed model is implemented on the peak load of the Iranian Power Grid and the optimum prices for TOU program and the optimum incentives for combined TOU and EDRP programs are determined. Manuscript profile -
Open Access Article
112 - A New Combined Strategy for Estimation of Individual Power Quality Parameters Using Adaptive Neural Network
H. R. Mohammadi A. Yazdian Varjani H. mokhtariWith respect to increment of power quality problems and also increasing application of sensitive devices to such problems, the power quality enhancement becomes a serious concern. The series-shunt and combined compensators can be used for compensation of voltage, curren MoreWith respect to increment of power quality problems and also increasing application of sensitive devices to such problems, the power quality enhancement becomes a serious concern. The series-shunt and combined compensators can be used for compensation of voltage, current, or both voltage and current. One of the most important stages for precise and optimized compensation of power quality parameters is the fast and accurate estimation of individual parameters. In this paper, a new combined strategy based on a unified adaptive estimator is proposed which is capable of detection and accurate estimation of individual power quality parameters. In comparison to other estimation methods, the proposed method has a simple structure, low computation, high precision and is capable of individual power quality parameters estimation. Therefore, the proposed method can be used for on-line application such as selective compensation in series, shunt active power filters, and unified power quality conditioner. The exclusive properties of the proposed strategy will be shown by simulation results in transient and steady state conditions. Manuscript profile -
Open Access Article
113 - A Novel Structure for Fault Current Limiterمحدودکننده جريان عيب، راکتور غير فوق هادی، افت ولتاژ، مدار جبرانکننده
M. abapour M. SabahiIn this paper a new structure for fault current limiter is proposed. In proposed structure the superconductor coil is replaced by a copper coil and the losses of copper coil and power electronic devices are compensated by an auxiliary circuit. The results show that the MoreIn this paper a new structure for fault current limiter is proposed. In proposed structure the superconductor coil is replaced by a copper coil and the losses of copper coil and power electronic devices are compensated by an auxiliary circuit. The results show that the proposed structure has less undesired effect on normal operation of system compared with ordinary superconductor type. The main advantageous of proposed structure are no need to superconductor technology and its control-less operation. The analytical analysis and designing characteristics for DC reactor are presented. Also, the simulation and experimental results are presented to show the effectiveness of proposed structure in fault current limitation. Manuscript profile -
Open Access Article
114 - Optimizing OLAP Queries by Mapping Data Cube to Two Dimensional Space
m.k. sohraby Ahmad Abdollahzadeh BarforoushData warehouse and OLAP are essential elements of decision support systems (DSS) and have been studied in database issues extensively. The requirements of decision support systems are different from on-line transactional processing systems. Query optimization and effici MoreData warehouse and OLAP are essential elements of decision support systems (DSS) and have been studied in database issues extensively. The requirements of decision support systems are different from on-line transactional processing systems. Query optimization and efficient data cube computation have primary roles in improving functionality of DSS. This paper presents a new method for query processing in data warehouses and computing data cubes using bottom-up cube computation techniques. Results of implementation show that the proposed algorithm outperforms two best known algorithms (based on time criterion), and is much faster than them in answering to monotonic query with large volume of data. Furthermore, 2-dimensional view of ex-cube and transforming the data cube to a hyper graph structure, reduce the required space of the algorithm when we aggregate subsets of cube's dimension. Manuscript profile -
Open Access Article
115 - Distributed Generation Sources Placement in Electric Power Distribution Networks under Uncertainty
H. Falaghi M. Parsa-MoghaddamThis paper presents a new multiobjective model for optimal placement of distributed generation sources in electric distribution network under load and market price uncertainties that finds out the non-dominated multiobjective solutions corresponding to the simultaneous MoreThis paper presents a new multiobjective model for optimal placement of distributed generation sources in electric distribution network under load and market price uncertainties that finds out the non-dominated multiobjective solutions corresponding to the simultaneous minimization of economic cost, technical risks, and economical risk due to uncertainties. Fuzzy sets theory is used to model the uncertainties. The proposed model is solved using a specialized genetic algorithm as the optimization tool. The performance of the proposed approach is assessed and appreciated by case study on a typical distribution network. Manuscript profile -
Open Access Article
116 - A New Configuration of Unified Power Quality Conditioner for Simultaneous Compensation in Adjacent Feeders
H. R. Mohammadi A. Yazdian Varjani H. mokhtariIn this paper a new configuration of unified power quality conditioner (UPQC) is proposed. In this new configuration, by adding a series converter in an adjacent feeder, the abilities of the UPQC are enhanced. The proposed configuration can be applied to adjacent feeder MoreIn this paper a new configuration of unified power quality conditioner (UPQC) is proposed. In this new configuration, by adding a series converter in an adjacent feeder, the abilities of the UPQC are enhanced. The proposed configuration can be applied to adjacent feeders to compensate for supply voltage and load current imperfections on the main feeder and fully compensation of supply voltage imperfections, especially interruption, on other feeder. In this configuration two series and one shunt converters are used which all are voltage source converters (VSC). All VSCs are connected back to back on the DC side and shared a common DC-link capacitor. The proposed configuration offers the following advantages: 1) Power transfer between two adjacent feeders for sag/swell and interruption compensation. 2) Using one shunt VSC for current compensation in main feeder and voltage regulation of common DC link capacitor between all VSCs. The simulation results obtained in PSCAD/EMTDC on a two bus/two feeder system show the effectiveness of the proposed configuration as well as the adopted control system. Manuscript profile -
Open Access Article
117 - Power System Stability Improvement Using QFT-Based Excitation Robust Control
A. Akbari Forod H. Seifi A. khaki sedighDue to uncertainties in system modeling as well as system parameters, current excitation systems are unable to perform quite satisfactorily over a wide range of operating conditions. In this paper a QFT-based excitation robust control is proposed which the above mention MoreDue to uncertainties in system modeling as well as system parameters, current excitation systems are unable to perform quite satisfactorily over a wide range of operating conditions. In this paper a QFT-based excitation robust control is proposed which the above mentioned uncertainties are, somehow, considered. The Horowitz second method is employed in the design of the nonlinear QFT controller. Manuscript profile -
Open Access Article
118 - Phase Comparison Protection Enhancement for Low-Current Faults Using Load Current Component Estimation
M. Sanaye-Pasand M. jaefari noknadiPhase angle between the currents measured at the two ends of a protected transmission line could be highly affected by load current component for high resistance internal faults. As a result, the phase comparison protection (PCP) scheme might fail to recognize these kin MorePhase angle between the currents measured at the two ends of a protected transmission line could be highly affected by load current component for high resistance internal faults. As a result, the phase comparison protection (PCP) scheme might fail to recognize these kinds of faults. In this paper a new approach is proposed to enhance the accuracy of PCP scheme to detect such kind of faults. The fault component of current signal is reconstructed using the estimation of load component of the current signal under fault condition. Therefore, the proposed method eliminates the phase angle difference due to the load component. The pre-fault current of the line is used as the estimation of the load current component during the fault condition. It is shown that this approximation enhances the performance of PCP scheme for high resistance faults. It also increases the accuracy of classifying fault type due to increase of the sensitivity of fault detection units. The proposed method is simulated for a test system and is examined for various fault conditions. Obtained results show major improvement in the performance of PCP scheme. Manuscript profile -
Open Access Article
119 - Sensitivity Based Static Congestion Management in Competitive Electricity Markets
Mohammad Tabrizian H. Seifi M. K. Sheikh-El-EslamiCongestion management is deal with in this paper. The algorithm proposed is based on active and reactive power dispatches of critical nodes, determined from a detailed sensitivity analysis. The electricity market considered is a hybrid model, in which firm transmission MoreCongestion management is deal with in this paper. The algorithm proposed is based on active and reactive power dispatches of critical nodes, determined from a detailed sensitivity analysis. The electricity market considered is a hybrid model, in which firm transmission rights may also be observed. The proposed algorithm is assessed and its capabilities evaluated for a typical test system. Manuscript profile -
Open Access Article
120 - Placement and Performance Analysis of UPFC in Restructured Power Systems
a.k. abrishami A. Yazdian Varjani H. SeifiIn this paper a new steady state modeling of unified power flow controller (UPFC) is proposed. Using this model, factors that affect the objective function of electricity market as a result of UPFC installation in power grid has been decomposed into four components, inc MoreIn this paper a new steady state modeling of unified power flow controller (UPFC) is proposed. Using this model, factors that affect the objective function of electricity market as a result of UPFC installation in power grid has been decomposed into four components, including line series impedance increase, shunt reactive power compensation, in-phase component of series voltage and quadrature component of series voltage. An UPFC has been placed in different points of a test system and impact of each component on objective function of electricity market has been measured by simulation and compared with results from analytical method. Both active and reactive locational marginal prices are calculated and their relation with settings of UPFC series part has been studied. Manuscript profile -
Open Access Article
121 - Adaptive Wavelet Thresholding for Denoising Speech Signals
F. sheikhalishahi H. R. abutalebi M. R. TabanThis paper addresses the problem of speech enhancement in wavelet domain. After decomposition of noisy signal into wavelet sub-bands, an adaptive thresholding process is applied on wavelet coefficients. In the proposed technique, small threshold value and hard thrsholdi MoreThis paper addresses the problem of speech enhancement in wavelet domain. After decomposition of noisy signal into wavelet sub-bands, an adaptive thresholding process is applied on wavelet coefficients. In the proposed technique, small threshold value and hard thrsholding function are used in sub-bands with high speech energy; vice versa, in sub-bands with low speech energy, large threshold value and soft thresholding function are employed. For other sub-bands (between above two extreme cases for speech energy), we use an adaptive thresholding function that is actually between soft- and hard-thresholding functions. The threshold value and thresholding function are determined by a parameter related to the ratio of speech and noise powers in each sub-band. Our extensive experiments show the superiority of proposed method in removing the background noise and reduction of speech distortion. It was also shown that both wavelet tree structure and wavelet type affect on the performance of speech de-noising system. Manuscript profile -
Open Access Article
122 - Cell ID Assignment in Cellular Networks for Location Management Based on Distance
A. R. zolghadr asli F. nazarpourIn the design of mobile cellular networks, the option of methods for location management of mobile users and updating this location is very important. In general, numerous methods of location management could be classified in two different categories named static and dy MoreIn the design of mobile cellular networks, the option of methods for location management of mobile users and updating this location is very important. In general, numerous methods of location management could be classified in two different categories named static and dynamic. Analysis and studies show that the second category imposes less computational load onto network. One of the algorithms in dynamic case is based on distance which has better performance compared to other algorithms which are based on time or movement. The important point in this technique is the calculation of cellular distance by mobile unit (MS). Because MSs could receive only cell codes or cell identification (cell ID) by BTSs, in this technique the mobile unit should be able to calculate the cellular distance from these codes (ID). In this paper the authors propose a method for cell ID assignment based on real geographic location of BTS in GPS system. The achieved IDs are then used for applying the distance based method for location management. We have also tested the performance of this method by simulation of a real cellular network in city of Yasuj, province of Kohkiluyeh in Iran. Manuscript profile -
Open Access Article
123 - Experimental Modeling of Two-Dimensional Systems with ARMA Structure
M. sadabadi M. shafiee M. karrariIn this paper, experimental modeling of two-dimensional discrete systems with ARMA structure is considered. Therefore two-dimensional model order selection and parameter estimation problems are proposed. This method shows that the information of AR and MA orders are imp MoreIn this paper, experimental modeling of two-dimensional discrete systems with ARMA structure is considered. Therefore two-dimensional model order selection and parameter estimation problems are proposed. This method shows that the information of AR and MA orders are implicitly contained in two different correlation matrices and the AR and MA orders of the 2-D ARMA model can be independently determined before parameter estimation. The two-dimensional model is assumed to be causal, stable, linear, and spatial shift-invariant with quarter plane (QP) support. Numerical Simulations are presented to show the good performance and effectiveness of the proposed method in two-dimensional discrete system with ARMA structure. Manuscript profile -
Open Access Article
124 - Optimization of the Nonlinear Behavior of Power Amplifiers in Satellite Digital Image Transmission Using Particle Swarm Method
A. A. Lotfi-Neyestanak Gh. sowlat Mohammad JahanbakhtNonlinear behavior of the power amplifiers in satellite transmitters causes a lot of errors in digital image transmission. So, even by using a moderate linearizer, the bit error rate (BER) will greatly improve. In this paper, the particle swarm optimization has been use MoreNonlinear behavior of the power amplifiers in satellite transmitters causes a lot of errors in digital image transmission. So, even by using a moderate linearizer, the bit error rate (BER) will greatly improve. In this paper, the particle swarm optimization has been used as an effective method with good conversion speed. Effects of an optimized cubic linearizer on digital image transmission are evaluated. The simulations results for the bit error rate as a function of signal to noise ratio (SNR), third order intercept point (TOI), and noise figure (NF) of low noise amplifier (LNA) are compared with each other. Manuscript profile -
Open Access Article
125 - A New Modified Unequal Error Protection Approach in the Video Transmission over Wireless Networks
H. ghaneiy M. Khademi J. chitizadehThe performance of video transmission over wireless channels is limited by the channel noise. Thus many error resilient tools have been incorporated into the MPEG-4 video compression method. In addition to these tools, the unequal error protection (UEP) technique has be MoreThe performance of video transmission over wireless channels is limited by the channel noise. Thus many error resilient tools have been incorporated into the MPEG-4 video compression method. In addition to these tools, the unequal error protection (UEP) technique has been proposed to protect the different parts in a MPEG4 video packet with different channel coding rates based on the rate compatible punctured convolutional (RCPC) codes. However, it is still not powerful enough to achieve a high visual quality over the wireless networks. To provide more robust MPEG-4 video transmission over wireless channels, this paper proposes a modified unequal error protection (MUEP) approach based on the content of the video scene. In proposed technique, channel coding rates for motion section of the video packet are determined based on the motion of the video scene. Experimental results show that the proposed technique enhances both subjective visual quality and PSNR about 1.5 dB, comparing to the traditional UEP method. Manuscript profile -
Open Access Article
126 - An Approach to Increase Internet Traffic Transmission Rate in All-Optical OPS Networks
اکبر غفارپور رهبرConsider an all-optical time-slotted OPS network in which Internet protocol has been used at upper layers. Contention is a major problem for such a network. It is shown in this paper that optical packet retransmission at the optical domain can improve Internet throughpu MoreConsider an all-optical time-slotted OPS network in which Internet protocol has been used at upper layers. Contention is a major problem for such a network. It is shown in this paper that optical packet retransmission at the optical domain can improve Internet throughput and can even reduce cost of OPS network implementation. In this technique, a copy of transmitted optical packets are saved in ingress switches and retransmitted when required, independent of TCP layer retransmission. In other words, retransmission may happen both at the optical layer and at the TCP layer. In this paper, an approach is proposed to reduce cost of OPS network implementation. In addition, Internet throughput is studied in slotted OPS network and an approach is proposed to increase Internet throughput and to improve throughput of long-hop connections. Manuscript profile -
Open Access Article
127 - NGN Management Model and Utility Networks’ Estimated Capital Investment in Operation Support Systems for the Next Years
A. Jahanbeigi M. E. KalantariBy the introduction of the concept of Next Generation Networks (NGN), the management of these networks has become an important issue. So, the requirements, goals and the overall architecture of NGN management systems are discussed in this paper. The functional classific MoreBy the introduction of the concept of Next Generation Networks (NGN), the management of these networks has become an important issue. So, the requirements, goals and the overall architecture of NGN management systems are discussed in this paper. The functional classification of Operation Support Systems (OSS) used in NGN management is also presented. Because of the need of utility networks (such as telephony, data, water, electricity and gas) in the country to OSS, the amount of required capital investment for deployment of Network Management System (NMS) and Customer Care and Billing System (CCBS), as main parts of OSS, are calculated for the next four years in this paper. To reach these estimates, the total number of subscribers in mentioned networks is forecasted for this period and information about per customer capita is also extracted. Two frameworks of, distributed and centralized, are considered. This assessment shows an approximate investment of M606$ and M432$ is needed for NMS and CCBS in distributed scenario, respectively. The same requirement in centralized scenario is M433$ and M322$ for NMS and CCBS, respectively. So, an approximate investment of M1040$ and M750$ is needed for OSS in distributed and centralized scenarios, respectively. Manuscript profile -
Open Access Article
128 - Estimation of the Required Capital Investment in Mobile Telephony Network's Equipments Based on Cobb-Douglas Demand Forecasting Model
A. Jahanbeigi M. E. KalantariThe goal of this paper is to estimate the capital investment in mobile telephony network's equipments, by using Cobb-Douglas model to forecast the number of subscribers for the next years in the country. Then by presenting a master plan for Base Station Subsystem (BSS) MoreThe goal of this paper is to estimate the capital investment in mobile telephony network's equipments, by using Cobb-Douglas model to forecast the number of subscribers for the next years in the country. Then by presenting a master plan for Base Station Subsystem (BSS) and Network Switching Subsystem (NSS) parts of the network, the required equipments and also the capital investment amounts are estimated. In the BSS plan, the number of Base Transceiver Stations (BTS) with various configurations and also Base Station Controllers (BSC) with different capacities and required accessories (such as tower, antenna, feeder, power supply and transmission equipments between BTSs and BSCs) are determined. In the NSS plan, an architecture is proposed for network's traffic (including signaling). The routing plan and required interfaces with Public Switched Telephone Network (PSTN) and Public Data Network (PDN) are also presented and the capacity of network's nodes and E1 links are determined. Based on the mentioned plan and also the typical cost of different equipments, offered by domestic and foreign vendors, the capital investment of 26.7 trillion Rials seems to be necessary to increase the penetration rate from 12.4% to 48.4% in mobile telephony network. Manuscript profile -
Open Access Article
129 - A Novel Wavelet Based Method for Improvement of Power Transformer Differential Relay against Magnetizing Inrush Current and CT Saturation
A. Rahmati M. Sanaye-PasandDifferential protective relay serves as the main protection of transformers against faults in the windings for many years. Unremitting tries for more smart of this protection relay have been done by different creative manufactures and up to now different methods and inv MoreDifferential protective relay serves as the main protection of transformers against faults in the windings for many years. Unremitting tries for more smart of this protection relay have been done by different creative manufactures and up to now different methods and inventions have been proposed for better operational of the differential relay. However, a differential protection for differential currents would be handicapped by difficulties due to several natural phenomena which are the cause of false differential currents and misoperate of the relay. Some of these phenomena, such as the inrush current and saturation of instrument current transformers, are the main concern in designing an efficient differential protection algorithm. This paper at first, proposes a new algorithm based on the Wavelet Transform (WT) to identify internal fault from magnetizing inrush in three phase power transformers. The internal faults can be accurately discriminated from inrush current less than a quarter a cycle after the disturbance. At following with definition of an index which it is extracted from the high frequencies by WT, the restrain current in bias-current characteristic of differential relay has been improved. Obtained results demonstrate that the proposed algorithm can provide the desired response and can be used as a very fast and accurate method. Manuscript profile -
Open Access Article
130 - Fault Location Algorithm in Practical Radial Distribution Systems Based on Voltage and Current Recorded by Digital Fault Recorders
S. Jamali V. TalavatThis paper presents a new impedance based fault location algorithm for practical radial distribution systems. The algorithm uses the fundamental components of voltages and currents recorded by a digital fault recorder usually installed at the head of main feeders. At f MoreThis paper presents a new impedance based fault location algorithm for practical radial distribution systems. The algorithm uses the fundamental components of voltages and currents recorded by a digital fault recorder usually installed at the head of main feeders. At first, the algorithm estimates the average loading and power factor of distribution transformers by using the pre-fault voltage and current phasors. Then from the post-fault voltage and current phasors, the preliminary candidates for fault location are determined by searching all the feeder sections. Finally, the actual fault location is determined by checking operated fuses/sectionalizers, or fault indicators. The fault location method has been developed as a software package named DFL (Digital Fault Locator) in “Electricity Networks Protection and Automation” research laboratory of Iran University of Science and Technology (IUST). The accuracy of the proposed algorithm has been validated by several fault conditions carried out on a 205-node 20 kV practical radial distribution feeder. The results of the developed software have shown very remarkable accuracy in fault location as presented in the paper. Manuscript profile -
Open Access Article
131 - A Pseudo Covariance Wavelet-based Feature Extraction Method to Biomarker Selection from Ovarian Cancer Proteomic Patterns
H. Montazery Kordy M. H. Miran-Baygi M. H. MoradiPathological changes within an organ can be reflected as proteomic patterns in blood. The mass spectrometry has been used as powerful tools to generate proteomic patterns from serum. The produced profiles can be viewed as high dimensional and correlation data for which MorePathological changes within an organ can be reflected as proteomic patterns in blood. The mass spectrometry has been used as powerful tools to generate proteomic patterns from serum. The produced profiles can be viewed as high dimensional and correlation data for which the features of scientific interest are the peaks. Due to this complexity of data, an appropriate analysis method is needed such as wavelet transform. In this study, we proposed a pseudo-covariance wavelet-based feature extraction method for dimension reduction and de-correlation between mass spectra data. Our algorithm was applied to datasets of ovarian cancer obtained from the National Cancer Institute of USA. The proposed algorithm was used to extract the set of proteins as potential biomarkers in each dataset from reconstructed mass spectra. The selected biomarkers were able to diagnose ovarian cancer patients from non-cancer with high accurate results using standard diagnosis criteria. Using different classification algorithms, our approach yielded an accuracy of 98%, specificity of 97%, and sensitivity of 98%. Manuscript profile -
Open Access Article
132 - Using Minimum Mean Squared Error Estimator for Quality Improvement of Abdominal Computerized Tomography Images Based on a Bivariate Laplacian Mixture Model for Complex Wavelet Coefficient
H. Rabbani M. VafadustOne of the important subjects in the wavelet-based image denoising based on the Bayes theorem is choosing the appropriate density function for modeling the wavelet coefficients. The interscale dependency between parent and child coefficients is one of the statistical p MoreOne of the important subjects in the wavelet-based image denoising based on the Bayes theorem is choosing the appropriate density function for modeling the wavelet coefficients. The interscale dependency between parent and child coefficients is one of the statistical properties of wavelets. So, in the recent years instead of univariate distribution, bivariate density functions have been suggested by the researchers and in this paper we use a mixture of bivariate Laplacian densities for this reason. Using this distribution we are able to model both heavy-tailed property and interscale dependency of wavelets. Using the mentioned density function for a minimum mean squared error estimator, we obtain a new shrinkage function for denoising. Applying this function to each subband of discrete complex wavelet transform of abdominal computerized tomography images, we will be able to improve the quality of these images better than some reported methods. Manuscript profile -
Open Access Article
133 - Performance Improvement of the Traditional SVM-Based Face Detection Method
M. Roohi G. Mirjalily M. T. SadeghiIn this paper, we propose some ideas to improve the performance of the traditional face detection based on support vector machine (SVM). The traditional SVM-based system for face detection detects faces by exhaustively scanning an image for face-like patterns at any pos MoreIn this paper, we propose some ideas to improve the performance of the traditional face detection based on support vector machine (SVM). The traditional SVM-based system for face detection detects faces by exhaustively scanning an image for face-like patterns at any possible scales. It divides the original image into overlapping sub-images by using a fixed-size cutting window and classifies them using the Support Vector Machine to determine the appropriate class (face or non-face). This approach has not an acceptable detection rate. In this paper to improve the performance, we use cutting windows with different sizes. We fuse the decisions obtained by using different windows. An important issue in the Support Vector Machine classifier is to shift the decision threshold adequately towards the better represented class. In this paper, a novel method is proposed for determining the threshold value adaptively. A post processing algorithm is also presented for reducing the false alarm rate. Experimental results using standard database show that the performance of the proposed SVM-based method is much better than the basic SVM classifier. Manuscript profile -
Open Access Article
134 - Energy Efficiency Trading, a New Tool for Long-Term Market Power Reduction in Restructured Environment
M. Behrangrad M. Parsa-Moghaddam M. K. Sheikh-El-EslamiIn this paper a new concept has been proposed to consider “Energy Efficiency” as a new commodity. The new commodity is based on DSM (Demand Side Management) and especially the strategic conservation techniques in the restructured environment. In the proposed method the MoreIn this paper a new concept has been proposed to consider “Energy Efficiency” as a new commodity. The new commodity is based on DSM (Demand Side Management) and especially the strategic conservation techniques in the restructured environment. In the proposed method the ability to improve efficiency is traded as a new commodity by some new players. The effect of new commodity trading is analyzed on the long-term market power reduction in parallel to available long-term solutions that mostly rely on generation solution. The numerical study according to real world data shows the potential and effectiveness of the proposed method. Manuscript profile -
Open Access Article
135 - Direct Power Control of an Active Filter by Constant Switching Frequency
E. AbiriActive filters are effective for eliminating harmonic currents and improving reactive power due to nonlinear loads and unbalanced sources. In this paper an effective and new method for Control of active filter is investigated. Direct Power Control (DPC) with space vecto MoreActive filters are effective for eliminating harmonic currents and improving reactive power due to nonlinear loads and unbalanced sources. In this paper an effective and new method for Control of active filter is investigated. Direct Power Control (DPC) with space vector modulation is employed for this control scheme. Also, the AC line voltage sensors with a virtual flux (VF) estimator are replaced. The control system is resistant to the majority of line voltage disturbances using by the idea of virtual flux and synchronous double reference frame phase-locked loop (SDRF-PLL) approach. Superior advantages of this method are simple algorithm, good dynamic response, constant switching frequency and resistant to the majority of line voltage disturbances. The operation of proposed control strategy is verified in SIMULINK/MATLAB simulation environment. The simulations show that this active filter is effective for eliminating reactive power injected from nonlinear loads and unbalanced sources. (NF) of low noise amplifier (LNA) are compared with each other. Manuscript profile -
Open Access Article
136 - On-line Eye Blink Suppression from EEG Signals Using Adaptive Independent Component Analysis for Brain Computer Interfacing
F. Shayegh A. ErfanianFor several years, many efforts have been done to use the electro-encephalogram (EEG) as a new communication channel between human brain and computer. This new communication channel is called EEG-based brain-computer interface (BCI). The aim of brain-computer interface MoreFor several years, many efforts have been done to use the electro-encephalogram (EEG) as a new communication channel between human brain and computer. This new communication channel is called EEG-based brain-computer interface (BCI). The aim of brain-computer interface (BCI) research is to establish a new communication channel that directly translates brain activities into sequences of control commands for an output device such as a computer application or a neuroprosthesis. The major advantage of EEG-based BCI is that no physical movement is required. The motor imagery is the essential part of the most EEG-based communication systems. One of the major problems in developing a real-time Brain Computer Interface (BCI) is the eye blink artifact suppression. Recently, a more effective method has been introduced for removing a wide variety of artifacts from multi-channel EEG signals based on blind source separation by Independent Component Analysis (ICA). However, the method requires visual inspection of ICA components and manual classification of the interference components. This can be time-consuming and is not desirable for real-time artifact suppression. Moreover, the real-time application of this method for artifact rejection has not been considered so far. In this paper, various ICA methods with adaptive learning algorithm are presented and evaluated by computer simulation. The results from real-data demonstrate that the proposed scheme removes perfectly eye blink artifacts from the contaminated EEG signals and is suitable for use during on-line EEG monitoring and EEG-based brain computer interface. Manuscript profile -
Open Access Article
137 - Probabilistic Evaluation of Total Transfer Capability of Transmission Networks in the Presence of Wind Farms
M. Ramezani H. Seifi M. Parsa-Moghaddam, wind farms are used to generate electric power in some parts of the world. With increasing penetration level of wind farms in electric power systems, modification of current tools to evaluate and manage the system is an important issue. Evaluation of total transfer ca More, wind farms are used to generate electric power in some parts of the world. With increasing penetration level of wind farms in electric power systems, modification of current tools to evaluate and manage the system is an important issue. Evaluation of total transfer capability (TTC) is one of the considerable tools in restructured power systems which is used to schedule future transactions between areas in multi area power systems to ensure security of network. In this paper, a method is proposed for probabilistic evaluation of TTC of multi area power systems in the presence of wind farms. Firstly, a general approach based on Monte Carlo simulation is used to simulate a system state considering system load and power output of wind farm and optimal power flow (OPF) is used to calculate TTC level for each state. Then risk analysis is used as a decision making tool to determine the appropriate TTC level for a fixed system load level. Finally, both of system load and power output of wind farm are considered and clustered input data are used to accelerate Monte Carlo convergence speed. To demonstrate the effectiveness of the proposed approaches IEEE-RTS is used. Manuscript profile -
Open Access Article
138 - Design and Analysis of Low Frequency Communication Multipath Channel to Safe Transmitting Speech Signal in Persian Gulf
H. Bakhshi H. ShahbaziOne of the important applications of underwater communication is speech transmission between two divers or between divers and ship or submarine. This paper describes a project designed to investigate and demonstrate underwater communication system in Persian Gulf for sp MoreOne of the important applications of underwater communication is speech transmission between two divers or between divers and ship or submarine. This paper describes a project designed to investigate and demonstrate underwater communication system in Persian Gulf for speech transmission in a real channel. At first, transmitter is designed, then channel with real data is simulated by neural network and at last receiver is designed. Transmitted data is speech signal that for more secure transmission and low frequency bandwidth, a cryptography algorithm and speech coding algorithm is applied in transmitter. Quadrature phase shift keying (QPSK) signaling is employed to make efficient use of the available channel bandwidth. In the receiver, linear equalizer and decision feedback equalizer (DFE) are tested and the best scheme is applied. Also, ray tracing method is used for simulation of sound waves propagation in Persian Gulf underwater communication channel. Manuscript profile -
Open Access Article
139 - Memetic Algorithm for Economic Dispatch with Nonsmooth Cost Functions
M. Neyestani M. M. Farsangi H. Nezamabadi-pourThis paper presents a new approach to economic dispatch (ED) problems with nonconvex cost functions using Memetic Algorithm (MA). The practical ED problem have nonconvex cost functions with equality and inequality constraints that make the problem of finding the global MoreThis paper presents a new approach to economic dispatch (ED) problems with nonconvex cost functions using Memetic Algorithm (MA). The practical ED problem have nonconvex cost functions with equality and inequality constraints that make the problem of finding the global optimum difficult using any mathematical approaches. In this paper, MA with three different local searches is suggested to deal with the equality and inequality constraints in the ED problem. To validate the results obtained by proposed MAs, a Real Genetic Algorithm (RGA) and an MA adopted from the literature are applied for comparison. Also, the results obtained by MAs and RGA are compared with the previous approaches reported in the literature. The results show that the MAs produce optimal or nearly optimal solutions for all study systems. Manuscript profile -
Open Access Article
140 - The New Generation of Partial Discharge Measuring Systems and Their Application in Defect Identification of High Voltage Equipment
H. R. Mirzaei A. Akbari A. Mazhab Jafari Mohammad KhareziThis paper presents a new impedance based fault location algorithm for practical radial distribution systems. The algorithm uses the fundamental components of voltages and currents recorded by a digital fault recorder usually installed at the head of main feeders.This paper presents a new impedance based fault location algorithm for practical radial distribution systems. The algorithm uses the fundamental components of voltages and currents recorded by a digital fault recorder usually installed at the head of main feeders. Manuscript profile -
Open Access Article
141 - GA-Based Optimized UPFC Controller for Improving Damping of Oscillations in Power Systems
S. A. Taher R. Hematti A. AbdolalipourIn this paper, the use of the supplementary controller of a Unified Power Flow Controller (UPFC) to improve damping of oscillations in Single Machine Infinite Bus (SMIB) system is investigated. The controller was designed based on a linearized modified Phillips Heffron MoreIn this paper, the use of the supplementary controller of a Unified Power Flow Controller (UPFC) to improve damping of oscillations in Single Machine Infinite Bus (SMIB) system is investigated. The controller was designed based on a linearized modified Phillips Heffron model of SMIB in state space form. In practice systems use simple Proportional Integral (PI) controllers to control UPFC. However, since the PI control parameters are usually tuned based on classical or trial-and-error approaches, they are incapable of obtaining a good dynamic performance for a wide range of operation conditions. To address this problem, in this research an optimization approach, based on the Genetic Algorithms (GA) method is proposed for the design of UPFC controller (supplementary damping controller) for increasing damping of power system oscillations is developed. Several linear and nonlinear time-domain simulation tests clearly show the effectiveness and validity of the proposed method in enhancing of oscillations257-260damping. Comparisons between the performances of both the proposed and conventional supplementary controllers are made. Computer test results show that proposed method is very effective in oscillations damping and in the meantime is more robust than its conventional counterpart. Manuscript profile -
Open Access Article
142 - Wavelength Conversion by Means of Second-Order Femtosecond Soliton Decay
A. Esmaeilian Marnani M. K. Moravvej-Farshi M. Ebnali-HeidariIn this paper, for the first time, we have reported the possibility of designing wavelength converter for second order femtosecond solitons, by studying its decaying behavior after confronting a localized perturbation in dispersion along an optical fiber. In our studies MoreIn this paper, for the first time, we have reported the possibility of designing wavelength converter for second order femtosecond solitons, by studying its decaying behavior after confronting a localized perturbation in dispersion along an optical fiber. In our studies, in addition to the important nonlinearities for femtosecond pulses, such as self steeping and stimulated Ramman scattering, we have investigated the effects of the third and fourth order dispersions. We have realized that inclusion of the fourth order dispersion effect in our calculations makes the soliton decay behavior somewhat symmetric. On the contrary, when β4=0, the soliton decay behave in an asymmetric manner. The nearly symmetric behavior of the emerging pulses from an upward step-like dispersion, made us to change β4 from –0.0002 ps4/km given in references, to –0.001 ps4/km, to achieve a symmetric behavior suitable for wavelength conversion. Manuscript profile -
Open Access Article
143 - Evaluating Two Approaches for Farsi OCR Based on Sub-Word Shape Recognition
H. Khosravi E. KabirTwo approaches for the recognition of printed Farsi documents based on sub-word shape recognition is proposed. First approach is based on recognition of sub-word shape as a whole and the second is based on the recognition of the body of sub-words. Sub-word body is const MoreTwo approaches for the recognition of printed Farsi documents based on sub-word shape recognition is proposed. First approach is based on recognition of sub-word shape as a whole and the second is based on the recognition of the body of sub-words. Sub-word body is constructed via removing dots and signs of the sub word. In second approach, information of dots and signs will be added after recognition of the body. Both approaches have two phases: training and test. In training phase, sub-words are clustered based on ISODATA algorithm. Initial centers of the clusters are computed through a hierarchical clustering algorithm. In first approach, sub-word recognition is performed in two stages: finding clusters close to the input sub-word and then finding the best match within the sub-words of these clusters. In the second approach another stage is required to find the final sub-word including dots and signs. Experimental results show that on clean images the first algorithm have better performance; 94% versus 93% in word level. But when dealing with low quality and noisy images, both algorithms are suffering from reduced accuracy. Sometimes this reduction is significant. The reasons of this behavior are inspected and some solutions are presented. Finally we compared both methods and inspected pros and cons of Farsi OCR based on sub-word shape. Manuscript profile -
Open Access Article
144 - Coherent Detection of Radar Targets with Moderately Fluctuating in Gaussian Clutter
M. R. TabanIn this paper, coherent radar detection of moderately fluctuating targets in Gaussian clutter is performed. In the previous works, the target vector has been modeled as a Gaussian random vector that is independent of clutter vector. In this paper, based on the coherence MoreIn this paper, coherent radar detection of moderately fluctuating targets in Gaussian clutter is performed. In the previous works, the target vector has been modeled as a Gaussian random vector that is independent of clutter vector. In this paper, based on the coherence assumption, by extending the Swerling models for radar targets to the moderate fluctuating cases, we propose a more accurate model for every fluctuating target. The proposed model shows that the Gaussian assumption for moderately fluctuating targets is not correct. Then, based on the proposed model, the optimal detection of moderately fluctuating targets in Gaussian clutter is performed and the GLR (Generalized Likelihood Ratio) test is obtained. Also, the ECD (Estimator-Correlator Detector) and OF (Optimal Filter) (that have been proposed as the best detectors in the previous works) are derived based on the new model. Computer simulation results show that the ECD has a superior performance than the other detectors. Nevertheless, the OF can be considered as an admissible detector because of the simpler algorithm and the performance close to the ECD. Although, the GLR detector has a suitable performance, but its performance is often lower than that ECD and OF while its algorithm is more complicated. Therefore, the GLR detector cannot compete to the ECD and OLD. Computer simulation results also show that these detectors do not have a convenient constant false alarm rate. Manuscript profile -
Open Access Article
145 - A Mathematical Model for Customer Behavior Prediction Based on Click Stream Analysis
M. M. Sepehri F. Mahdavi PajouhClick stream analysis is known as an effective method for customer’s viewing route prediction in a particular web site. Predicting Customer viewing behavior provides considerable advantages in different areas such as e-commerce, e-business and customer relationship mana MoreClick stream analysis is known as an effective method for customer’s viewing route prediction in a particular web site. Predicting Customer viewing behavior provides considerable advantages in different areas such as e-commerce, e-business and customer relationship management. This paper aims to provide a 0-1 mathematical model based on Markov models for evaluating the most probable viewing route of a customer in a website. This problem can be formulated as an especial case of well-known Prize Collecting Traveling Salesman Problem (PCTSP) which is a NP-hard problem and its sub tour elimination constraints are increased drastically by increasing the model parameters. Also an effective algorithm is introduced in this paper to solve this NP-hard model. For model validation, the proposed model was implemented by using the log files of a university web site server for 20 different users. Comparison of the results with commonly used Giudici algorithm shows that the proposed model yields better and exacter solutions. Manuscript profile -
Open Access Article
146 - A Hybrid Heuristic Algorithm for Optimal Power Flow in HVAC/HVDC Transmission Networks
S.J. Seyed-Shenava H. Seifi S. M. SepasianIn this paper, a model is presented for the optimal power flow of an HVAC/HVDC transmission network. OPF is a fundamental tool in power system operation and planning. The model proposed for optimal power flow includes network control parameters settings and HVDC links p MoreIn this paper, a model is presented for the optimal power flow of an HVAC/HVDC transmission network. OPF is a fundamental tool in power system operation and planning. The model proposed for optimal power flow includes network control parameters settings and HVDC links parameters tunings. Also, excessive equipment installation for appropriate operation of the network is minimized, while the network security margin is maximized. To solve the proposed model, a hybrid evolutionary algorithm by combining Particle Swarm Optimization (PSO) and Differential Evolution (DE) is proposed. The methodology is tested on IEEE-30 test system and compared with the results from other OPF techniques. Also the impact of HVDC links on OPF studies is illustrated by numerical examples. Manuscript profile -
Open Access Article
147 - Design of 15-Bit 12-MHz Nyquist Bandwidth 5th-Order Single Stage Sigma-Delta Modulator
M. TaghizadehIn this paper a 5th-Order single-loop Sigma-Delta Modulator with low distortion structure is presented. This structure, which uses integrator and IIR filter concurrently, has relatively less feedforward paths and modulator coefficients. Thus, its sensitivity to coeffici MoreIn this paper a 5th-Order single-loop Sigma-Delta Modulator with low distortion structure is presented. This structure, which uses integrator and IIR filter concurrently, has relatively less feedforward paths and modulator coefficients. Thus, its sensitivity to coefficient mismatching is reduced. To lower the power consumption of the modulator, the 2-order IIR filter block is implemented by single OTA, and a passive adder is used to realize input quantizer adder. Simulation results show that this structure can achieve 15-bit of resolution and 6 MHz input signal bandwidth, with 1.2 V supply voltage using a 0.13 µm CMOS technology. Power consumption of modulator is 53 mW. Comparing with other structures, the proposed modulator has higher performance because of increasing the DR and input bandwidth of modulator without extra increasing the power consumption. Manuscript profile -
Open Access Article
148 - Design of Two-Dimensional Diffractive Optical Elements Using the Extended Iterative Angular Spectrum Method
S. H. Kazemi M. M. Mirsalehi A. R. AttariThe iterative angular spectrum (IAS) method has been introduced by Mellin and Nordin for designing finite-aperture diffractive optical elements (FADOEs). We have extended this method to two-dimensional FADOEs and used it to design some optical devices. The first device MoreThe iterative angular spectrum (IAS) method has been introduced by Mellin and Nordin for designing finite-aperture diffractive optical elements (FADOEs). We have extended this method to two-dimensional FADOEs and used it to design some optical devices. The first device is a 1-to-7 beamsplitter that couples an optical beam to seven single-mode optical fibers with a diffraction efficiency of 84%. The second device is a beam-shaper that converts a Gaussian beam into a nearly flat beam with a diffraction efficiency of 74.8%. The third design is a 1-to-3 asymmetric beamsplitter. The fourth design includes three microlenses with different focal lengths. The desired intensity distribution patterns of all these designs are located at the near field region. We have investigated the sensitivity of the extended method by comparing the results obtained by this method with those obtained by three-dimensional finite difference time domain (3-D FDTD) method using perfect matched layer (PML). Also, a 1-to-5 beamsplitter is fabricated and the experimental results are presented. Manuscript profile -
Open Access Article
149 - A Simple and Effective Scheme for Hand Gesture Recognition in Finger Spelling of Farsi Alphabet
M. J. Barzegar Sakhvidi A. R. SharafatIn recent years, automated recognition of gestures in the finger spelling paradigm has become an active research area. Gesture is a combination of hand postures, hand movements, and face gestures; and finger spelling is a way of presenting alphabets of a word that does MoreIn recent years, automated recognition of gestures in the finger spelling paradigm has become an active research area. Gesture is a combination of hand postures, hand movements, and face gestures; and finger spelling is a way of presenting alphabets of a word that does not exist in the sign language dictionary. In this paper, we present a scheme for hand gesture recognition in finger spelling of Farsi alphabets, where a different shape for hand and fingers denote a different letter in the alphabet. Our scheme has five stages, namely, visual data gathering, preprocessing of the image, detection and extraction of hand’s features, feature reduction and consolidation, and finally, hand gesture recognition. For the last stage (hand gesture recognition), we employ three techniques, namely, the nearest neighbor using the Euclidian distance, the nearest neighbor using the normalized Euclidian distance, and neural networks. For reducing the feature space, we use the discrete cosine transform (DCT), which yields better results as compared to the discrete Fourier transform and Fourier coefficients. We achieved 99.1% correct recognition using neural networks, which is superior to existing schemes. Manuscript profile -
Open Access Article
150 - ECG Signal Handling, Using Differential Pulse Code Modulation Scheme
H. B. Bahar Y. S. KhiabaniDifferential pulse code modulation (DPCM) system plays an important role in communication systems. In this paper a considerable amount of theoretical analysis has been carried out on DPCM structure, degree of predictor and quantizer unit. Simulation has been done using MoreDifferential pulse code modulation (DPCM) system plays an important role in communication systems. In this paper a considerable amount of theoretical analysis has been carried out on DPCM structure, degree of predictor and quantizer unit. Simulation has been done using DPCM scheme. Here, instead of direct coding of signal, difference between two signals, input to DPCM and estimated output, is encoded. Consequently, application of the difference signal to quantizer unit, fewer bits for each sample is achieved at the output of the quantizer unit. In this study, Levinson-Durbin algorithm is utilized to design the optimal predictor. For the optimal quantized levels, classical together with Lloyd method are employed. Finally, second order predictor together with optimal quantized levels, 2-bit for normal case and 3-bit for optimal case, is successfully achieved to process ECG signal at DPCM scheme. Manuscript profile -
Open Access Article
151 - Application of Combinational Adaptive Load Shedding Schemes to Improve Power System Voltage Stability - Part I: General Concept & the Algorithms
A. Saffarian M. Sanaye-Pasand A. P. GhalehIn this paper three combinational adaptive load shedding schemes are proposed to enhance the power system stability especially voltage stability margins of the system following severe events. Nowadays, the security margin of power systems against various instabilities i MoreIn this paper three combinational adaptive load shedding schemes are proposed to enhance the power system stability especially voltage stability margins of the system following severe events. Nowadays, the security margin of power systems against various instabilities is decreased due to the developments, deregulation and competitions in the power industry. In this situation, traditional system protection schemes can not offer adequate protection especially against combinational events. In some combinational disturbances, after initial frequency drop the conventional protection schemes returns back the system frequency to its permissible values; however, the system eventually collapses due to severe voltage declines which result in voltage instability. In some other disturbances, severe voltage declines cause troubles in appropriate operation of the under frequency load shedding relays. In this paper three adaptive combinational load shedding schemes are proposed to counteract such disturbances. The proposed schemes use locally measured frequency and voltage signals and do not need any communication link. In the proposed algorithms, during under frequency condition, load shedding is started from the locations which have higher voltage decay and for longer period of time. The speed, location and amount of load shedding are changed adaptively depending on the disturbance location, voltage status of the system, and the rate of frequency decline. In the second part of this paper using model of a real network, various simulation studies are performed and performance of the proposed schemes is investigated. Manuscript profile -
Open Access Article
152 - Application of Combinational Adaptive Load Shedding Schemes to Improve Power System Voltage Stability - Part II: Simulation Results
A. Saffarian M. Sanaye-Pasand A. P. Ghalehpaper is part II of a two-part paper. In the first part, several adaptive combinational load shedding schemes were proposed to enhance the power system voltage stability. The main objective of the proposed schemes is to improve the voltage stability margin of the system Morepaper is part II of a two-part paper. In the first part, several adaptive combinational load shedding schemes were proposed to enhance the power system voltage stability. The main objective of the proposed schemes is to improve the voltage stability margin of the system following large and combinational disturbances. For major disturbances the frequency and voltage stability of the system are jeopardized simultaneously and the conventional schemes might fail to operate correctly. In this part, the proposed methods are simulated in a real network to evaluate their performance. To achieve realistic results, dynamic model of generators, automatic voltage regulators, governors and loads are considered in the simulations. Considering the importance of load modeling in these studies, the frequency and voltage dependence of static loads have been modeled accurately. Dynamic motor loads have also been modeled using aggregate equivalent induction motors at load buses. Performance of the proposed schemes is compared with each other also with performance of the conventional scheme for various combinational disturbances. Considering the obtained simulation results it is concluded that by using the proposed algorithms the power system becomes more robust against large disturbances and the probability of the power system instability is decreased. Manuscript profile -
Open Access Article
153 - Geodesic Path Based Image Inpainting Using Wavelet Transform
M. Jahangard S. Saryazdi H. Nezamabadi-pour عصمت راشدیIn image inpainting, distorted and damaged parts of image or selected objects are removed or replaced with the appropriate information. In this article, image inpainting is performed by using frequency information of wavelet transform. The fill-in is done by diffusion o MoreIn image inpainting, distorted and damaged parts of image or selected objects are removed or replaced with the appropriate information. In this article, image inpainting is performed by using frequency information of wavelet transform. The fill-in is done by diffusion of information of intact pixels into the damaged regions, which is begun from the outermost pixels and gradually the damaged region is reconstructed. To determine direction and the amount of diffusion, the geodesic path based image inpainting method is generalized by incorporating information of wavelet domain. The experimental results confirm superiority of the proposed method over the geodesic path based image inpainting method. Manuscript profile -
Open Access Article
154 - Online Signature Verification in Stationary Wavelet Transform Domain
M. Valizadeh E. KabirIn this paper, an online signature verification method using extended regression in stationary wavelet domain is presented. To calculate the similarity between two signatures by extended regression, we should equalize the time length of the corresponding signals in two MoreIn this paper, an online signature verification method using extended regression in stationary wavelet domain is presented. To calculate the similarity between two signatures by extended regression, we should equalize the time length of the corresponding signals in two signatures. Using all points of the signals to equalize their time length will decrease the difference between a genuine signature and its forgery. Here a new approach based on the extreme points warping of the signals is presented. This approach equalizes the time length of two signals without degrading the differences between them. Also we calculated the similarity of signatures by using the details of the signals in stationary wavelet transform, SWT, domain, which showed very good results. The proposed system was tested on SVC2004 signature database. The results were compared with the results of participant teams in the first international signature verification competition. We have gained EER=6% for skilled forgery signatures. Comparing the result, it shows that we stand in the second rank between all the participants. This system has no verification error for random forgery signatures and stands in the first rank. Our experimental results show that using SWT domain instead of time domain decreases the verification error rate by 35%. Manuscript profile -
Open Access Article
155 - A Contrast Independent Algorithm for Binarization of Document Images
M. Valizadeh E. KabirIn this paper, we present a contrast independent algorithm for binarization of degraded document images. The proposed algorithm does not require any parameter setting by user. Therefore, it can handle document images with variable foreground and background intensities a MoreIn this paper, we present a contrast independent algorithm for binarization of degraded document images. The proposed algorithm does not require any parameter setting by user. Therefore, it can handle document images with variable foreground and background intensities and low contrast documents. The proposed algorithm involves three consecutive stages. At the first stage, independent of contrast between foreground and background, sensible parts of each character are extracted using the modified water flow model, which is designed for the extraction of sensible part of each character and the drawbacks of water flow model are solved in this algorithm. In the second stage, the gray levels of foreground are estimated using the extracted text pixels and the gray levels of background are locally estimated by averaging the original image. At the third stage, for each pixel of image, the average of estimated foreground and background gray levels is defined as local threshold. After extensive experiments, the proposed binarization algorithm demonstrates superior performance against conventional binarization algorithms on a set of degraded document images captured with camera. Proposed algorithm efficiently extracts the low contrast texts. Manuscript profile -
Open Access Article
156 - A Method for Automatic Printing Carpet Map Reading and Comparing to C-Means Clustering
Ahmad Izadipour E. KabirThe subject of this paper is to read carpet pattern automatically by computer. This is composed of two steps: detection of vertical and horizontal lines in the pattern and color reduction. Color reduction is essential because of limitation of the number of colors that i MoreThe subject of this paper is to read carpet pattern automatically by computer. This is composed of two steps: detection of vertical and horizontal lines in the pattern and color reduction. Color reduction is essential because of limitation of the number of colors that is used in a carpet. To accomplish of this process, we must detect the grid lines on the carpet pattern automatically. These lines are two types: thin lines and thick lines. At the first stage, the distance between thin lines is obtained. Having the first thin line detected, the other thin lines are drawn using this distance. We use a Comb method for detection of thick lines. The major problem in line detection is lagging or leading of the lines due to the mismatch between sampling frequency of the scanner and image resolution. We compensate this distortion in various steps in our algorithm. In the second step, we want all the pixels in the same square, to have the same color. This is obtained by mapping colors to the best color in the palette. We propose three methods. In first method the user selects two selections per any colors. Palette is obtained from some processes in these selections. Those pixels that are in the middle of the squares are mapped to the palette. Then color histogram is computed. The color that has the maximum histogram value is assigned to the square. In order to decrease user’s interference, C-means clustering algorithm is used in two types. The centers of initial clusters are determined once with user’s interference and once randomly. Results of these three methods are compared. We tested our methods on 20 samples of carpet patterns, and the error rate was variable from 0.07% to 0.5% between samples. Manuscript profile -
Open Access Article
157 - Investigation of Sensing Range for High Speed Target Tracking in Wireless Sensor Networks
M. R. Zoghi M. H. KahaeiIn this paper, we propose a new approach for selection of subsets of active sensors with some constraints on energy consumption and estimation error for tracking of a target. The proposed approach exploits the decentralized estimation by using the extended information f MoreIn this paper, we propose a new approach for selection of subsets of active sensors with some constraints on energy consumption and estimation error for tracking of a target. The proposed approach exploits the decentralized estimation by using the extended information filter for target tracking. Furthermore, a cost function is defined using spatial correlation for sensor selection. Consequently, the Spatial Split algorithm is proposed based on spatial correlation coefficients for sensor selection. At last, for high speed targets, we propose a modification on spatial split algorithm by changing the sensing range with respect to the target speed. Simulation results show that the tracking accuracy is analogous to those of optimal estimation methods. It is also found that energy consumption decreases due to activating only necessary sensors. Manuscript profile -
Open Access Article
158 - Improving QoS and Reducing Transmit Power in Wireless Ad Hoc Networks by Distributed Power Control Using SINR and Transmit Power Pricing Functions
R. Haratian A. R. SharafatWe propose a scheme for improving QoS and reducing transmit power in wireless ad hoc networks by utilizing the signal-to-interference-plus-noise-ratio (SINR) and a pricing function that is proportional to the transmit power of each user. The performance of our proposed MoreWe propose a scheme for improving QoS and reducing transmit power in wireless ad hoc networks by utilizing the signal-to-interference-plus-noise-ratio (SINR) and a pricing function that is proportional to the transmit power of each user. The performance of our proposed method is analyzed by using game theory, where each user’s quality of service is a function of its SINR. The utility function for each user is defined by its desired SINR minus a pricing to provide adequate incentive for each user to choose its power level in such a way to maximize the aggregate of all users’ utilities (total network utility) instead of selfishly maximizing its own SINR. Simulation results show that the performance of the network is improved while the total power consumption is reduced. Manuscript profile -
Open Access Article
159 - Design a Unified Power Flow Controller (UPFC) Using Bilinear Sliding Mode Control Method
T. Niknam M. Nayeripour A. Yazdian Varjani M. MohamadianIn this paper, at first, a new model will be attained for unified power flow controller (UPFC) using state space equation of bilinear systems. Then, a complete novel method of designing UPFC controllers will be represented by the use of variant structure systems. In thi MoreIn this paper, at first, a new model will be attained for unified power flow controller (UPFC) using state space equation of bilinear systems. Then, a complete novel method of designing UPFC controllers will be represented by the use of variant structure systems. In this method, input signals of UPFC are designed through sliding mode controller. In order to design these kinds of controllers, at first, control rules are obtained by the use of designing four different slide levels and then setting their derivatives (which express dynamics of the flows of axes d and q, in serial and parallel transformers) to zero. In fact, applying the outputs of this controller to UPFC is equal to bring the flows of axes d and q to the reference value in both UPFC. In the other hand, internal dynamics (DC capacitor voltage) will be stabilized in UPFC by means of PI controller. The stability of the system is obtained through Lyapunov function. Manuscript profile -
Open Access Article
160 - Design and Implementation of a Text to Speech system for Kurdish Language with It's Quality Assessment
W. Barkhoda A. Bahrampour F. Akhlaqian H. FailiIn this paper the first text to speech system for Kurdish language has been introduced. Kurdish language has two standard scripts, Arabic and Latin. In the text analysis part besides treating common problems in various Kurdish texts, the problems involved in both standa MoreIn this paper the first text to speech system for Kurdish language has been introduced. Kurdish language has two standard scripts, Arabic and Latin. In the text analysis part besides treating common problems in various Kurdish texts, the problems involved in both standard scripts have been dealt with. Also, standard symbols have been introduced into which the system converts the input texts in each of the two scripts. For the first time for Kurdish language, intonation patterns for various sentence types have been determined. In the speech production part, three different synthesis systems based on allophone, syllable, and diaphone have been implemented. For quality assessment of the above mentioned systems and their comparison with each other, the four tests of MOS, Intelligibility, DRT, and MRT have been used. The test results show the high intelligibility of our systems, especially the system based on diaphone. Manuscript profile -
Open Access Article
161 - A Model Based on Entropy and Learning Automata for Solving Stochastic Games
B. Masoumi M. R. MeybodiStochastic games, as the generalization of Markov decision processes to the multi agent case, have long been used for modeling multi-agent system and are used as a suitable framework for Multi Agent Reinforcement Learning. Learning Automata (LA) were recently shown to b MoreStochastic games, as the generalization of Markov decision processes to the multi agent case, have long been used for modeling multi-agent system and are used as a suitable framework for Multi Agent Reinforcement Learning. Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. In this paper a model based on learning automata and the concept of entropy for finding optimal policies in stochastic games is proposed. In the proposed model, for each state in the environment of the game and for each agent an S-model variable structure learning automaton is placed that tries to learn the optimal action probabilities in those states. The number of its adjacent states determines the number of actions of each learning automaton in each state and every joint action corresponds to a transition to an adjacent state. Entropy of the probability vector for the learning automaton of the next state is used to help learning process and improve the learning performance and is used a quantitative problem independent measurement for learning progress. We have also implemented a new version of the proposed algorithm that balances exploration with exploitation yielding improved performance. The experimental results show that the proposed algorithm has better learning performance than the other learning algorithms in terms of cost and the speed of reaching the optimal policy. Manuscript profile -
Open Access Article
162 - Load Restoration in Distribution System in the Presence of Distributed Generation Considering Energy Storage Units
A. Moradkhani M. MohamadianDGs connected to distribution systems are increasing in size and number. Intentional islanding are proper alternatives to increase the reliability of end load in the network with does not access to any other branch. In other conditions these loads experiences permanent MoreDGs connected to distribution systems are increasing in size and number. Intentional islanding are proper alternatives to increase the reliability of end load in the network with does not access to any other branch. In other conditions these loads experiences permanent interruption. in load restoration operation, islanding is so important in the presence of DGs. Islanding is occurred when a part of distribution network is supplied only from DG sources. A new algorithm for distribution load restoration in the presence of DGs is presented in this thesis. the proposed approach minimizes the load interruption cost in restoration process based on Tabu search method. In this algorithm the maximum load with the most level of importance is restored in minimum time by reconfiguration, islanding and finally load shedding. Energy storage units and the location of synchronizing devices are considered in this thesis. The algorithm is implemented on a 32-bus test system and numerical results are presented. Manuscript profile -
Open Access Article
163 - A New Hardware Method for Direction Estimation in Fingerprint Images
E. Alibeigi S. Samavi Z. RahmaniOne of the main identity authentication methods is the use of fingerprints. The most popular biometric method is fingerprint analysis. Most of the automatic fingerprint systems are based on minutiae matching. Therefore, extraction of minutiae is a critical stage in the MoreOne of the main identity authentication methods is the use of fingerprints. The most popular biometric method is fingerprint analysis. Most of the automatic fingerprint systems are based on minutiae matching. Therefore, extraction of minutiae is a critical stage in the design of fingerprint authentication systems. Computation of direction of lines in fingerprints is a stage which affects the quality of the extracted minutiae. The existing algorithms require complex and time-consuming computations and are software-based. This paper presents a hardware implementation which has improved the current methods. The presented method is based on pipeline architecture and has proved to perform efficiently. Manuscript profile -
Open Access Article
164 - Stereo Acoustic Echo Cancellation Using MIMO Decorrelation Network Based NLMS Adaptive Filter
M. Bekrani M. LotfizadExistence of a high inter-channel correlation in a stereo communication system results in a considerable performance degradation in the associated stereo acoustic echo canceller and also weight misalignment of adaptive filters even after finalizing the convergence perio MoreExistence of a high inter-channel correlation in a stereo communication system results in a considerable performance degradation in the associated stereo acoustic echo canceller and also weight misalignment of adaptive filters even after finalizing the convergence period. In this paper an approach for improving the performance of NLMS adaptive filter is developed based on reducing the correlation of input signals employing a multi-input-multi-output decorrelation network. This approach has a low-complexity neural network structure and can train in a real-time manner. Simulation results show an improvement in weight convergence rate and misalignment employing the proposed method. Manuscript profile -
Open Access Article
165 - A Likelihood Ratio Approach to Information Fusion for Image-Based Fingerprint Verification
M. S. Helfroush M. MohammadpourImage-based fingerprint verification systems have been considered as a parallel method against the minutiae-based approach. This paper proposes a training based fusion method for fingerprint verification, using likelihood ratio (L.R). In this method, the matching scores MoreImage-based fingerprint verification systems have been considered as a parallel method against the minutiae-based approach. This paper proposes a training based fusion method for fingerprint verification, using likelihood ratio (L.R). In this method, the matching scores which are extracted from orientation, spectral and textural features are fused. In order to fuse these image-based features, the likelihood ratio approach has been employed. FVC2000 database has been selected to evaluate the method. Also, the proposed method has been compared to a similar one that uses the simple sum as its fusion system. The comparison results show that the proposed fusion method has made a significant improvement for the accuracy of matching system, so that the equal error rate (ERR) of proposed system has been reduced to 0.14%. Manuscript profile -
Open Access Article
166 - Application of Neuro Space Mapping in Modeling Semiconductor Devices
M. Gordi Armaki S. E. Hosseini Mohammad Kazem AnvarifardIn this paper an efficient method for modeling semiconductor devices using the drift-diffusion (DD) model and neural network is presented. Unlike HD model which is complicated, time consuming with high processing cost, the proposed method has lower complexity and higher MoreIn this paper an efficient method for modeling semiconductor devices using the drift-diffusion (DD) model and neural network is presented. Unlike HD model which is complicated, time consuming with high processing cost, the proposed method has lower complexity and higher simulate speed. In our method, a RBF neural network is used to modify DD parameters. The modified DD model can generate simulate results of accurate HD model. The proposed method is first applied to a silicon n-i-n diode in one dimension, and then to a silicon thin-film MOSFET in two dimensions, both for interpolation and extrapolation. The obtained results for basic variables, i.e., electron and potential distribution for different voltages, confirm the high efficiency of the proposed method. Manuscript profile -
Open Access Article
167 - Simplify Programming of TinyOS Applications for Wireless Sensor Networks
M. Khezri M. Sarram F. AdibniaSensor node operating system provides a limited number of common services for developers to construct applications for wireless sensor networks. The sensor network community selected TinyOS as the de facto standard with most existing applications, libraries and device d MoreSensor node operating system provides a limited number of common services for developers to construct applications for wireless sensor networks. The sensor network community selected TinyOS as the de facto standard with most existing applications, libraries and device drivers available for TinyOS. The programming model of TinyOS is event-based and is not easy to use. In this paper, we present a new task scheduler for TinyOS that includes a new computation concept, named Job. Jobs are a collaborative and non-preemptive way of multitasking. On the next step, we propose a programming model which combines the asynchronous basis of event-driven systems with a more classical programming interface for the developer. As a result, developer that uses such an interface in his application will be provided with the sequential view we wanted. This programming model is suitable for applications that have long running computations and there is a data flow dependency between different tasks. Manuscript profile -
Open Access Article
168 - Blind Number of Active Users Estimation and Synchronization in CDMA Systems with Unequal Power’s Signal on Flat Fading Channel
S. Ghavami V. TabatabvakiliBlind estimation of number of active users and synchronization of those have important role in identification of system’s parameters, for the spectrum surveillance system design of multi-user direct sequence spread spectrum systems. For the number of active user estimat MoreBlind estimation of number of active users and synchronization of those have important role in identification of system’s parameters, for the spectrum surveillance system design of multi-user direct sequence spread spectrum systems. For the number of active user estimation, signal’s eigenvalues of the received signal covariance matrix is distinguished from those of noise using an adaptive threshold. Analytical results and computer simulations show that signal of users with limited received power difference (less than 1.5 dB) can be synchronized using maximizing the Frobenious norm of the received signal covariance matrix. Moreover, this method is robust against of the carrier frequency offset which is due to Doppler shift in the carrier frequency of different users. By increasing difference among received powers of processed signals, performance of this method will be degraded. Hence, an iterative algorithm for interference cancellation of users with higher received power is proposed, which can be synchronize and estimate the number of active users with lower received power. The proposed method for number of active user estimation reduces computational complexity in comparison with the traditional methods for number of active user estimation, such as MDL and AIC, while keep the accuracy of estimation in low SNR regime. The performance of blind synchronization method in the flat fading channel is degraded; hence, a multi-antenna receiver is proposed to improve the probability of correct synchronization. Manuscript profile -
Open Access Article
169 - A New Method for Identification of Main Harmonic Source in PCC Based on the Superposition and Critical Impedance Methods
M. Moradloo H. R. KarshenasIn this paper, a new method for identification of dominant source in creation of current and voltage distortions in PCC bus is presented. In proposed method, using superposition method along with definition of harmonic contribution and combining them with the critical i MoreIn this paper, a new method for identification of dominant source in creation of current and voltage distortions in PCC bus is presented. In proposed method, using superposition method along with definition of harmonic contribution and combining them with the critical impedance algorithm, new indices are defined and novel algorithm is presented. In this algorithm contrary to the critical impedance method, there is no need for values of customer's harmonic impedances. Also there is no probability that proposed algorithm lead to incorrect identification of dominant source even in cases in which the shares of PCC sides are close to each other. This fact is shown by comparison between proposed algorithm and critical impedance method. The analysis is verified on IEEE 13-bus test system using DigSilent software. Manuscript profile -
Open Access Article
170 - Direct Torque Control in a Flying Capacitor Inverter with Reduction of Common Mode Voltage
Mohammad Arasteh S. Farhangi S. A. AbrishamifarBearing current in inverter-fed induction motors can result in premature bearing failure. This paper gives a detailed analysis of common mode voltage as the main source of bearing currents. Moreover, it presents an algorithm to reduce the common mode voltage in multilev MoreBearing current in inverter-fed induction motors can result in premature bearing failure. This paper gives a detailed analysis of common mode voltage as the main source of bearing currents. Moreover, it presents an algorithm to reduce the common mode voltage in multilevel DTC drive. Based on the given analysis, the common mode voltage is reduced to about 33 percent of the initial value. The simulation results in MATLAB/SIMULINK confirm the capability of the algorithm in common mode voltage reduction without degrading the electromagnetic torque and the speed response. The results of real world experiments using TMS320F2812 DSP processor are also provided. Manuscript profile -
Open Access Article
171 - Technical and Economic Evaluation of Implementing Outage Management System in Urban Distribution Systems in Iran
M. R. Hghifam E. AlishahiFaults in MV systems are the cause of almost 70 percent of outages in power system. By using suitable outage management methods, amount of power outages will be reduced in large extent. In Iran, traditionally outage management system was conducted by trial and error met MoreFaults in MV systems are the cause of almost 70 percent of outages in power system. By using suitable outage management methods, amount of power outages will be reduced in large extent. In Iran, traditionally outage management system was conducted by trial and error methods and relied on operators’ experience. The ever-increasing expansion of distribution networks has made it impossible to use traditional outage management systems. Outage management systems depend upon load type, load sensitivity, network type, amount of accumulation of load and population, and being rural or urban network. In this paper, at first a technical assessment for implementing outage management methods in distribution systems of Iran is carried out. An economic assessment of implementing outage management system in urban distribution systems of Iran with dense population is conducted. For this purpose a sample network of Afsarieh area of Tehran has been chosen. Manuscript profile -
Open Access Article
172 - Ensemble Feature Selection Strategy Based on Hierarchical Clustering in Electronic Nose
M. A. Bagheri Gh. A. MontazerThe redundancy problem of sensor response in electronic noses is still remarkable due to the cross-selectivity of chemical gas sensors which can degrade the classification performance. In such situations, a more efficient multiple classifier system can be obtained in ra MoreThe redundancy problem of sensor response in electronic noses is still remarkable due to the cross-selectivity of chemical gas sensors which can degrade the classification performance. In such situations, a more efficient multiple classifier system can be obtained in random feature space rather than in the original one. Ensemble Feature Selection (EFS) methods assume that there is redundancy in the overall feature set and better performance can be achieved by choosing different subsets of input features for multiple classifiers. By combining these classifiers the higher recognition rate can be achieved. In this paper, we propose a feature subset selection method based on hierarchical clustering of transient features in order to enhance the classifier diversity and efficiency of learning algorithms. Our algorithm is tested on the UCI benchmark data sets and then used to design an odor recognition system. The experimental results of proposed method based on hierarchical clustering feature subset selection and multiple classifier system demonstrate the more efficient classification performance. Manuscript profile -
Open Access Article
173 - Reducing Actuation Voltage of the Elliptical RF-MEMS Switches Using a Novel Cutting Pattern
Mohammad Jahanbakht A. A. Lotfi-Neyestanak M. Lotfi-Neyestanak Mohammad Tondro-AghmiyouniThe elliptical structure for the micro electromechanical switches with low actuation voltage is proposed to work at the Ka band. The actuation voltage of this structure is shown to further been reduced by 21% with transverse cutting patterns. This Switch will then be an MoreThe elliptical structure for the micro electromechanical switches with low actuation voltage is proposed to work at the Ka band. The actuation voltage of this structure is shown to further been reduced by 21% with transverse cutting patterns. This Switch will then be analyzed to extract its parameters such as Insertion Loss, Return Loss, and Deformation Posture. The effect of the actuation voltage on the deformation of the bridge will then be analyzed and the results would be compared with other common bridges. This switch may be used as a low loss and effective element for much complicated systems such as distributed phase shifters and phased array applications. Manuscript profile -
Open Access Article
174 - A New Method for Clustering Wind Speed Data in Wind Power Plants Using FCM and PSO Algorithms
H. Afrakhte Y. Bostani AmlashiFuzzy clustering Method (FCM) is a commonly used method of data clustering. But, when too much data are available, the use of this method usually may lead to non-homogeneous distribution of data. In this paper a new method for clustering of wind speed data in wind farms MoreFuzzy clustering Method (FCM) is a commonly used method of data clustering. But, when too much data are available, the use of this method usually may lead to non-homogeneous distribution of data. In this paper a new method for clustering of wind speed data in wind farms is presented. In this method, using the PSO algorithm, wind speed data is clustered and the obtained results are compared with those of FCM and K-means clustering methods. Simulation results indicate the proposed method has better convergence than K-means and FCM methods, especially in conditions which too much data are not available. Manuscript profile -
Open Access Article
175 - Accuracy and Speed Performance Improvement in Speaker Verification Using Genetic Programming
S. S. Sadat Sadidpour M. M. Homayounpour M. FasanghariIn speaker verification, a system investigates a person's identity and decides whether the person is a true client or an imposter. In this paper, genetic programming (GP) is used as a method for speaker modeling. When GP is used for construction of models for speakers, MoreIn speaker verification, a system investigates a person's identity and decides whether the person is a true client or an imposter. In this paper, genetic programming (GP) is used as a method for speaker modeling. When GP is used for construction of models for speakers, due to long training time to train GP models, training data compression is proposed in this paper. This idea reduced training time for 20 times. Training of several GP trees as a speaker's model is another idea presented in this paper to improve the speaker verification performance. In this method, training data are separated to a few clusters. Then a GP tree is trained for each cluster. Therefore, a speaker is modeled by several genetic programming trees. The verification performance increased from 50% to about 92% using the proposed method. Genetic programming performance was compared to some other discriminative methods such as Multi-Layer Perceptron neural network and Learning Vector quantization, and generative methods such as K-Means, GMM and LBG, GMM-UBM and VQ-MAP. Experiments show that Genetic programming is more effective than the other methods. Manuscript profile -
Open Access Article
176 - Texture Defect Detection Using Curvelet Transform
B. Moasheri H. Nezamabadi-pour S. Saryazdi S. AzadiniaThis article, an efficient system for texture defect detection based on curvelet transform is presented. The main idea is to model the defects in the texture image as one-dimensional discontinuities. Based on this idea, the curvelet transform is the most efficient meth MoreThis article, an efficient system for texture defect detection based on curvelet transform is presented. The main idea is to model the defects in the texture image as one-dimensional discontinuities. Based on this idea, the curvelet transform is the most efficient method for describing defects. First, in the learning phase, training samples of intact and defected blocks of the texture image are collected and transformed to the curvelet domain. Next, for each block a feature vector based on curvelet sub-bands is extracted and using a proposed method some important and effective features are determined for the desired texture. Then, a proper threshold for detecting defected from intact blocks is determined. In the performance phase, a vector containing the important features from each block of the texture is extracted and then the block by is classified. The results of simulation show that the proposed system is superior to the mean shift method in detecting defected texture blocks, and is less sensitive to the type of texture. Manuscript profile -
Open Access Article
177 - SVD-Based Adaptive Multiuser Detection for Optimized Chaotic DS-CDMA Systems
S. Shaerbaf S. A. SeyedinIn recent years, chaotic signals have created a new area in the designation of wideband communication systems. Most of the activity has focused on DS-CDMA systems, in which the conventional pseudo-noise sequences will be replaced by binary chaotic sequences. Unfortunat MoreIn recent years, chaotic signals have created a new area in the designation of wideband communication systems. Most of the activity has focused on DS-CDMA systems, in which the conventional pseudo-noise sequences will be replaced by binary chaotic sequences. Unfortunately, despite the advantages of chaotic systems such as aperiodicity, low cost generation and noise-like spectrum, the performance of most of such designs is not still suitable for multiuser wireless channels. In this paper, we propose a novel method based on singular value decomposition for adaptive multiuser detection in chaos-based DS-CDMA systems. We also propose a new genetic algorithm-based method for the optimal generation of chaotic sequences in such systems. Simulation results show that our proposed nonlinear receiver with optimized chaotic sequences outperforms the conventional DS-CDMA systems with “maximal length” codes as well as non-optimized chaos-based DS-CDMA systems in all channel condition, particularly for under-loaded CDMA condition, which the number of active users is less than processing gain. Manuscript profile -
Open Access Article
178 - Segmentation of Steel Surfaces towards Defect Detection Using New Gabor Composition Method
S. J. Alemasoom A. Monadjemi H. A. AlemasoomThe images of steel surfaces are generally textural images. There are different texture analysis methods to extract features from these images. In those methods using multi-scale/multi-directional analysis, Gabor filters are used for feature extraction. In this paper, w MoreThe images of steel surfaces are generally textural images. There are different texture analysis methods to extract features from these images. In those methods using multi-scale/multi-directional analysis, Gabor filters are used for feature extraction. In this paper, we extract texture features using the optimum Gabor filter bank. This filter bank is designed in a way that diverse filtering frequency and orientation will allow it to extract considerable amounts of texture information from the input images. We also introduce a new method called Gabor composition for segmentation and defect detection of steel surfaces. In this method, using two different algorithms, the input image is decomposed into detail images using an appropriate Gabor filter bank and then selected detail images are re composed. The created feature map illustrates the defective areas well. By calculating data distribution of detail images and comparing them, the second method of Gabor composition can accomplish segmentation without needing the normal images and the number of detail images to re-compose. Furthermore, we did different tests towards optimizing of segmentation by means of classifiers. Using a K-means classifier and adding gray levels to the extracted features, complete the segmentation procedure. The experimental results show that the Gabor composition method in most of the tests has got better defect detection performance than the ordinary K-means classifier and the standard wavelet method; also the Second method of Gabor composition has got the best performance over all. Manuscript profile -
Open Access Article
179 - Training of MLP Neural Network for Data Classification by GSA Method
M. Dehbashian Seyed-Hamid ZahiriNowadays, several techniques have presented for data classification. One of these techniques is neural network that has attracted many interests. In this classifier, selection a suitable learning method is very important for training of the network. Error back propagati MoreNowadays, several techniques have presented for data classification. One of these techniques is neural network that has attracted many interests. In this classifier, selection a suitable learning method is very important for training of the network. Error back propagation is the most usual training method of neural networks that late convergence and stopping in local optimum points are its weakness. New approach in neural networks training is the usage of heuristic algorithms. This paper suggests a new learning method namely gravitational search algorithm (GSA) in training of neural network for data classification. GSA method is the latest and the most novel version of swarm intelligence optimization methods. This algorithm is inspired fby the law of Newtonian gravity and mass concept in nature. In this paper, a MLP neural network is trained for classification of five benchmark data set by GSA method. Also, the proposed method efficiency in training and testing of neural network compared with those of two training methods error back propagation and particle swarm optimization. Final results showed the GSA method extraordinary performance for data correct classification in most of cases. Also, in these experiments the GSA method produced stable results in all of cases. In addition, the run time of GSA method is shorter than that of the PSO. Manuscript profile -
Open Access Article
180 - Design of Proportional-Integral Sliding Mode Controllers for Hyperchaotic Systems in the Presence of Uncertainty, Disturbance and Nonlinear Control Inputs
A. Abooee M. R. Jahed Motlagh Z. RahmaniIn this paper, robust controllers for a new hyperchaotic system are investigated in the presence of uncertainty, disturbance and nonlinear control inputs. The controllers are designed by considering two major goals: first to stabilize the hyperchaotic system in the pres MoreIn this paper, robust controllers for a new hyperchaotic system are investigated in the presence of uncertainty, disturbance and nonlinear control inputs. The controllers are designed by considering two major goals: first to stabilize the hyperchaotic system in the presence of uncertainties, disturbance and nonlinear control inputs; and second, to guarantee the prescribed disturbance attenuation, considering the defined performance index for it. Sliding mode control by defining three proportional integral switching surfaces is used to reach mentioned goals. Numerical simulations are used to exhibit the feasibility and performance of the proposed method. Manuscript profile -
Open Access Article
181 - A Biological Laboratory on Microelectronic Chip: Design, Fabrication, and Experimental Results
E. Ghafar-Zadeh Mohammad SawanIn this paper, a complementary metal–oxide semiconductor (CMOS) based Laboratory-on-Chip platform is presented for bacteria growth monitoring. This platform integrates a 0.18 µm CMOS chip with two microfluidic channels. The proposed CMOS chip manufactured by Taiwan Semi MoreIn this paper, a complementary metal–oxide semiconductor (CMOS) based Laboratory-on-Chip platform is presented for bacteria growth monitoring. This platform integrates a 0.18 µm CMOS chip with two microfluidic channels. The proposed CMOS chip manufactured by Taiwan Semiconductor Manufacturing Company (TSMC) features a differential capacitive sensor along with two reference and sensing interdigitized electrodes. Two microfluidic channels are thereafter implemented atop the electrodes through a direct-write assembly technique. These microchannels are filled with pure Luria-Bertani (LB) medium and Escherichia Coli (E. Coli) bacteria suspended in the LB medium, respectively. We demonstrate and discuss the experimental results by using two different bacteria concentrations in the order of 10^6 and 10^7 per 1 mL in the LB medium. Manuscript profile -
Open Access Article
182 - A Novel Proposed Algorithm to Tackle Glasses Wearing and Beard Issues in Facial IR Recognition
H. Komari Alaie M. KhademiFace recognition via thermal infrared images is a modern recognition method. It has been so interesting for many researchers during last ten years. This method which operates via thermal features and the situation of human face vessels has much more benefits than visual MoreFace recognition via thermal infrared images is a modern recognition method. It has been so interesting for many researchers during last ten years. This method which operates via thermal features and the situation of human face vessels has much more benefits than visual-based methods. In these images, the effect of environmental lights changes, which is one of the most important obstacles of face recognition via visual images, is totally eliminated. The most important face recognition problem via thermal infrared images is the existence of diffusion obstacles like glasses and beard, which block the exact extraction of the situation of face vessels. Considering the suggested algorithm, these problems have been completely solved. In this paper face recognition is done through face vessels. For extraction of the face features, the situation of vessel branches is used. Also by choosing appropriate classification, fake vessels and false branches has been omitted. On the other hand, the best feature is extracted by using Dynamic Time Wrapping algorithm which is resistant to nonlinear changes. The simulation on UTK-IRIS gallery set has showed the accurate recognition rate 95% on the images with glasses and 88% on the images with beard, so the proposed method has improved the recognition rate about 10% and 44% respectively on same gallery set compared with the best other works. Manuscript profile -
Open Access Article
183 - Improving Pose Manifold and Virtual Images Using Bidirectional Neural Networks in Face Recognition Using Single Image per Person
F. Abdolali S. A. Seyed SalehiIn this article, for the purpose of improving neural network models applied in face recognition using single image per person, a bidirectional neural network inspired of neocortex functional model is presented. In the proposed model, recognition is not performed in a si MoreIn this article, for the purpose of improving neural network models applied in face recognition using single image per person, a bidirectional neural network inspired of neocortex functional model is presented. In the proposed model, recognition is not performed in a single stage, but via two bottom-up and top-down phases and the recognition results of first stage is used for model adaptation. We have applied this novel adapting model in combination with clustering person and pose information technique to separate person and pose information and to estimate corresponding manifolds. To increase the number of training samples in the classifier neural network, virtual views of frontal images in the test dataset are synthesized using estimated manifolds. Training classifier network via virtual images obtained from bidirectional network, gives an accuracy rate of 85.45% on the test dataset which shows 1.82% improvement in accuracy of face recognition compared to training classifier with virtual images obtained from clustering person and pose information network. Manuscript profile -
Open Access Article
184 - Analysis of Supervised Learners to Extract Knowledge of Lighting Angels in Face Images
S. Naderi N. Moghadam Charkari E. KabirVariation of Light intensity and its direction have been the main challenges in many face recognition systems that lead to the different normal and abnormal shadows. Today, various methods are presented for face recognition under different lighting conditions which requ MoreVariation of Light intensity and its direction have been the main challenges in many face recognition systems that lead to the different normal and abnormal shadows. Today, various methods are presented for face recognition under different lighting conditions which require previous knowledge about Light source and the angle of radiation as well. In this paper, a new approach is proposed to extract the knowledge of/about the lighting angle/direction in face images based on learning techniques. At First, some effective coefficients on lighting variation are extracted on DCT domain. They will be used to determine lighting classes after normalization. Then, three different learning algorithms, Decision tree, SVM, and WAODE (Weightily Averaged One-Dependence Estimators) are used to learn the lighting classes. The algorithms have been tested on the well known YaleB and Extended Yale face databases. The comparative results indicate that the SVM achieves the best average accuracy for classification. On the other hand, WAODE Bayesian approach attains the better accuracy in classes with large lighting angle because of its resistance against data loss. Manuscript profile -
Open Access Article
185 - An Intelligent BGSA Based Method for Feature Selection in a Persian Handwritten Digits Recognition System
N. Ghanbari S. M. Razavi S. H. Nabavi KariziIn this paper, an intelligent feature selection method for recognition of Persian handwritten digits is presented. The fitness function associated with the error in the Persian handwritten digits recognition system is minimized, by selecting the appropriate features, us MoreIn this paper, an intelligent feature selection method for recognition of Persian handwritten digits is presented. The fitness function associated with the error in the Persian handwritten digits recognition system is minimized, by selecting the appropriate features, using binary gravitational search algorithm. Implementation results show that the use of intelligent methods is well able to choose the most effective features for this recognition system. The results of the proposed method in comparison with other similar methods based on genetic algorithm and binary particle method of optimizing indicates the effective performance of the proposed method. Manuscript profile -
Open Access Article
186 - Cost Allocation Framework for Small Signal Stability Ancillary Service in Deregulated Environment
E. Riahi Samani H. Seifi Mohammad Kazem Sheikh El EslamiAn ISO is responsible for responsible for keeping system security within its specified limits. Rapid demand increase on one hand and less investment on transmission system and the other hand, have resulted in more stress on existing transmission grids. Therefore, variou MoreAn ISO is responsible for responsible for keeping system security within its specified limits. Rapid demand increase on one hand and less investment on transmission system and the other hand, have resulted in more stress on existing transmission grids. Therefore, various types of stability should be monitored and controlled. The small signal stability (SSS) is a type which may be improved using power system stabilizers (PSS). In this paper, though using the non-dominated sorting genetic algorithm version II (NSGA-II), it is, initially, shown how the PSSs may affect the generation cost as well as the SSS. Moreover, the service provided by PSSs is introduced as an ancillary service. A cost allocation framework is prospect in which the PSS owners are properly paid for their services provided. Manuscript profile -
Open Access Article
187 - A New Switching Algorithm for Compensating the Voltage Deviation of NPC Inverter DC Link Capacitors in DTC Drive of Induction Motors
A. Sadeghi Larijani M. Shahparasti M. Mohamadian A. Yazdian VarjaniIn this paper a novel direct torque control algorithm based on switching table using three-level diode clamp inverter is introduced. Voltage deviation of DC link capacitors is one of the most significant problems of NPC three-level voltage source inverters. The voltage MoreIn this paper a novel direct torque control algorithm based on switching table using three-level diode clamp inverter is introduced. Voltage deviation of DC link capacitors is one of the most significant problems of NPC three-level voltage source inverters. The voltage imbalance of DC link capacitors will result in low level harmonics, undesirable torque variation and motor efficiency reduction. To resolve this problem, a closed loop algorithm is introduced in this paper, in addition to its simple implementation; the algorithm is able to control the voltage fluctuation of DC link capacitors within the desirable limits. The result of simulation and experimental implementation confirms the performance of this method despite capacitors reduced capacity. Manuscript profile -
Open Access Article
188 - A New Method for Locating Unknown Number of Emitters: Combination of Multiple Hypothesis Tracking and Data Association
S. V. Shojaedini R. KabiriIn this paper a new method is proposed for separation and geolocation of moving emitters using their radiated signal which has no assumption about their numbers, positions and signal types. In the first step of the proposed method, all available signals in a scene are r MoreIn this paper a new method is proposed for separation and geolocation of moving emitters using their radiated signal which has no assumption about their numbers, positions and signal types. In the first step of the proposed method, all available signals in a scene are received using several sensors. In the second step a vector of time differences of arrivals between the signal received by each sensor and signal received by the reference sensor is extracted and two spaces of TDOA vectors are constructed for successive time slots. Finally a combination of multiple hypothesis tracking and data association algorithms are applied to extract and confirm meaningful strings of vectors from successive TDOA vector spaces that each string indicates an emitter. Obtained results from evaluation of the proposed method and comparing them with results obtained from existing methods, show that it can separate and track several emitters with linear, nonlinear, constant velocity and variable velocity motions. Also the proposed method shows an acceptable ability to separate and track emitters with parallel and intersecting trajectories and maneuvering emitters with greater performance than existing methods and without losing processing speed. Manuscript profile -
Open Access Article
189 - Sharing Features and Abstractions across Data for Robust Speech Recognition
P. Zarei Eskikand S. A. Seyed SalehiIn this work, in order to increase the capacity of a recurrent neural network, we present a model for extracting common features and sharing them across data. As a result of using this model, extracted principle components of data will be invariant to unwanted variation MoreIn this work, in order to increase the capacity of a recurrent neural network, we present a model for extracting common features and sharing them across data. As a result of using this model, extracted principle components of data will be invariant to unwanted variations. The recurrent connection of the network removes the noise using a continuous attractor formed during the training phase. The defined speaker codes will be transformed to the information need for switching the continuous attractor in the input space. As a result, speaker variations can be compensated and the recognition will performed when a clean signal is available. We compared the performance of this method with a reference network described in the paper. The results show that the proposed model is more useful in removing noise and unwanted variations. We compared the performance of this method with the reference network. The results show that the proposed model performs better in removing noise and unwanted variations, it increased the phoneme recognition accuracy about 5% when the signal to noise ratio is 0 dB. Manuscript profile -
Open Access Article
190 - Improving Formant and Concatenative Speech Synthesis Techniques through Using Vocoders
N. Maghsoodi M. M. HomayounpourIn this paper an approach to improve the quality of synthetic speech in formant and concatenative synthesis techniques is described. To deal with this problem we focused on using vocoders. In concatenative speech synthesis the idea is based on post processing the genera MoreIn this paper an approach to improve the quality of synthetic speech in formant and concatenative synthesis techniques is described. To deal with this problem we focused on using vocoders. In concatenative speech synthesis the idea is based on post processing the generated speech to reduce discontinuities. The post processing is consists of integrating Straight method to synthesis system in order to smooth the boundary between units. On the other hand, in formant synthesis we used multi excitation linear predictive method to replace simple excitation signal in Klatt method with multiband excitation. Our synthesis techniques were evaluated with respect to naturalness, fluidity and intelligibility based on subjective methods. These experiments clarified that the naturalness of synthetic speech can be improved by using our smoothing methods and multiband excitation signal. Manuscript profile -
Open Access Article
191 - Printing Conductive Lines and Surfaces on Different Substrates Using Inkjet Printing Method
J. Nouri S. M. Bidoki A. A. HeidariPrinting technology is known as one of the most suitable methods for adding electrical functionalities to textiles and inkjet method because of advantages such as low cost, availability, flexibility, … is a special method amongst all available printing techniques. This MorePrinting technology is known as one of the most suitable methods for adding electrical functionalities to textiles and inkjet method because of advantages such as low cost, availability, flexibility, … is a special method amongst all available printing techniques. This is the objective of this research to employ the novel method of using reactive inks in order to react with each other after being jetted onto the substrate for fabrication of simple electric circuit components. In this method, dilute solution of silver salt and a reducing solution are subsequently printed on each substrate. Oxidation-Reduction reaction between two inks deposits metallic silver nanoparticles by in situ reduction of silver salt forming an electrically conductive surface. The best reducing agent for inkjet deposition of silver was found to be ascorbic acid at normal pH. Conductive lines and patterns were fabricated on paper, plastic films and textile fabrics using the above technique and the effect of different parameters on their final conductivity were investigated and tried to gain the highest possible conductivities on each substrate. Based on our observations and results; inkjet technology posses very high potential for fabrication of silver nanoparticles containing patterns with conductivities up to 5x105 S/m for use as circuitry components. Manuscript profile -
Open Access Article
192 - Boiler-Turbine Coordinated Control Based on Improved Sliding Mode Controller
S. Golmohammadi R. Hooshmand Mohammad عطائیIn order to participate steam power plant in power system frequency regulating, in addition to producing the base load, the boiler and turbine should be controlled coordinately. Lack of coordinated control may lead to instability, cause oscillation in producing power an MoreIn order to participate steam power plant in power system frequency regulating, in addition to producing the base load, the boiler and turbine should be controlled coordinately. Lack of coordinated control may lead to instability, cause oscillation in producing power and boiler parameters, and reducing the reliability and creating thermodynamic tension to devices. This paper proposes a sliding mode based controller to control two main boiler-turbine parameters; i.e., the turbine revolution and superheated steam pressure of the boiler output. For this purpose, complete and exact model of the subsystems including turbo-generator, turbine and related control systems are derived and the ability of the method is shown using this comprehensive model. The proposed method is simulated on the 320 MW unit of Islam-Abad power plant in Isfahan/Iran and its performance is compared with the related real PI controllers which have been used in this unit. The simulation results show the capability of the proposed controller system in controlling local network frequency and superheated steam pressure in the presence of load variations and disturbances. Manuscript profile -
Open Access Article
193 - Wind Power Modeling Using Fuzzy-Markov Approach in Power System Reliability
Ahmad GhaderiAs intermittent wind power generation becomes more significant in power generation, it becomes increasingly important to assess its impact on the generation reliability of power systems. Therefore, it is the objective of this paper to evaluate the impact of wind power o MoreAs intermittent wind power generation becomes more significant in power generation, it becomes increasingly important to assess its impact on the generation reliability of power systems. Therefore, it is the objective of this paper to evaluate the impact of wind power on the power system reliability. In this paper, different approaches of wind power modeling are explained. Markov chain Monte Carlo (MCMC) and ARMA method are used to model of wind power output. Then Fuzzy-Markov method for wind power modeling is proposed. The proposed method is capable of modeling wind farms that have insufficient wind speed data. Finally, capacity credit of wind power is calculated. Manuscript profile -
Open Access Article
194 - Neural Control of the Induction Motor Drive: Robust Against Rotor and Stator Resistances Variations and Suitable for Very Low and High Speeds
H. Moayedi Rad M. A. Shamsi-Nejad mohsen FarshadIn this paper, induction motor speed control drive is designed with application two multilayer feed-forward neural networks. That those are used one for generate PWM pulse and other for estimation of required torque and flux information. For trained of the PWM wave gene MoreIn this paper, induction motor speed control drive is designed with application two multilayer feed-forward neural networks. That those are used one for generate PWM pulse and other for estimation of required torque and flux information. For trained of the PWM wave generate neural network is used from compound information two voltage and current classic model. Also, against general classic models for generate of the switching pulses is used as compound from reference voltage and current two motor phases. With these ideas are eliminated problems of the voltage and current classic models (flux saturation in current model for high speeds and voltage drop in voltage model for low speeds). As voltage profile is improved in this paper. The required feedback signals estimation (including: rotor flux, torque, etc.) is estimated by multilayer feed-forward neural network. That for robustness of the above estimator against rotor and stator resistances variations in time work of motor is used from compound trained data of the voltage and current classic models, because the voltage and current of the general classic models to sequence are independent of rotor and stator resistances. The simulation results by MATLAB-Simulink verify the proposed drive in improvement of the speed profile in transient and steady-state operating modes. Also, it verify clearly robust of the proposed drive against rotor and stator resistances variations in time work. Manuscript profile -
Open Access Article
195 - Learning Stable Analysis Patterns for Intelligent Software Agents
S. Vafadar Ahmad Abdollahzadeh BarforoushArtificial Intelligence (AI) Techniques (such as learning) are used widely in agent-based systems. However, current research does not address a software engineering view on these techniques that support all the software development process. In this paper, we focus on re MoreArtificial Intelligence (AI) Techniques (such as learning) are used widely in agent-based systems. However, current research does not address a software engineering view on these techniques that support all the software development process. In this paper, we focus on requirement analysis – as the first step of the software development process and present techniques and tools to cover this shortage. In this regard, we provide a set of stable analysis patterns for learning capability of the agents. Stable analysis patterns are a set of meta-classes and their relations to analyze a specific issue in a domain-independent manner. Using stable analysis concepts, namely Enduring Business Themes (EBT), Business Objects (BO) and Industrial Objects (IO), these patterns represent the conceptual model of the learning. In this paper, we also apply these patterns on two case studies to investigate their applicability. These patterns are used as guidelines during analysis of learning. The main advantage of applying the stable analysis patterns in comparison with conventional analysis methods is modeling the knowledge of the learning analysis in addition to the ordinary classes of the domain. In addition, they generate more stable models via considering different levels of abstraction in the analysis. Manuscript profile -
Open Access Article
196 - Color reduction for Machine-Printed Carpet Pattern by Reinforcement Learning
M. Fateh E. Kabir M. Nili AhmadabadiAutomatic reading of carpet patterns Requires To find the original colors of the pattern in a scanned image. It includes detecting of pattern lines and reducing the number of colors in the image. Color reduction is done in two steps: Finding the best pallet and mapping MoreAutomatic reading of carpet patterns Requires To find the original colors of the pattern in a scanned image. It includes detecting of pattern lines and reducing the number of colors in the image. Color reduction is done in two steps: Finding the best pallet and mapping the image colors to the pallet colors. The accuracy of color reduction is so important that it may be required to ask for user intervention. The purpose of this study is to provide a new method in automatic color reduction with high accuracy. To achieve this target, reinforcement learning method is used which yields a 98% accuracy. This is a new method in color reduction and no one has used it yet. This method is defined with respect to the application and the amount of color reduction is such that does not degrade the accuracy. Therefore, the resulting pallet has more colors comparing to the original one. In the work reported in this article, first the grid lines of the pattern are detected. Then a single color is assigned to each box of the grid. After these steps, through the reinforcement learning method the color reduction is carried out. The results obtained from applying the proposed algorithm on some sample images are reported and discussed. Manuscript profile -
Open Access Article
197 - Improvement of GMM Model Using PSK for Spoken Language Recognition Systems
F. Ghasemian M. M. HomayounpourGaussian Mixture Model (GMM) is a simple and effective method for statistical modeling of the feature space which is widely used in spoken language recognition systems and EM algorithm is used for training the parameters of this model. In this paper, considering the wea MoreGaussian Mixture Model (GMM) is a simple and effective method for statistical modeling of the feature space which is widely used in spoken language recognition systems and EM algorithm is used for training the parameters of this model. In this paper, considering the weakness of GMM models, a new model named PAW-GMM is proposed. In this model, the power of each component of GMM in discriminating one language from the others is considered for determining the weights of components. Since PAW-GMM considers the discriminating property of GMM components, it could increase the accuracy of language recognition systems. Also one of the problems of GMM-PSK-SVM which is one of the best GMM models is the high complexity especially for high number of languages. Therefore UBM-PSK-SVM is proposed that has the same accuracy as GMM-PSK-SVM but lower complexity. Experiments on four languages of OGI corpus show the efficiency of the proposed techniques. Manuscript profile -
Open Access Article
198 - TiR-UWB Communication System Analysis and Compensation in an Imperfect CSI Scenario
H. Khaleghi Bizaki S. Alizadeh M. OkhovvatTime reversal method has been recently considered with great interest due to its ability of the receiver complexity mitigation in the UWB communication systems. However, the channel imperfection (Imperfect CSI) has the destroyed effects on the time-reversed UWB communic MoreTime reversal method has been recently considered with great interest due to its ability of the receiver complexity mitigation in the UWB communication systems. However, the channel imperfection (Imperfect CSI) has the destroyed effects on the time-reversed UWB communication system performance. In this paper, at first the BER equations have been calculated in the TiR-UWB systems with the simple matched filter receiver in an imperfect CSI scenario. Then, a two-stage algorithm is proposed to improve the TiR-UWB in such conditions. First stage of mentioned algorithm provides the pre-filter coefficients derivation based on MMSE criteria via channel estimation error covariance matrix and then, an iterative routine is obtained in second stage via the simple matched filter receiver based on the derived coefficients in first stage. Finally, exhaustive simulations are done to demonstrate the performance advantage attained by the improved algorithm. As an especial case, the TiR-UWB system performance is improved by the proposed algorithm in 3 steps. Manuscript profile -
Open Access Article
199 - Design and Simulation of Fuzzy-ANFIS Controller for Continuous Control of Transmitted Power by TCSC
A. Kargar M. HosseinzadehControl of transmitted active power is an important issue in operation and management of power systems especially in congestion or fault conditions. In these situations, Thyristor Controlled Series Capacitor (TCSC) is used to continuous control and increase the transmit MoreControl of transmitted active power is an important issue in operation and management of power systems especially in congestion or fault conditions. In these situations, Thyristor Controlled Series Capacitor (TCSC) is used to continuous control and increase the transmitted power due to these facts that TCSC can act dynamically and is able to stable the system during fault conditions. In this paper, the transmitted power is controlled in the ten megawatt span by using the TCSC. For this purpose, various controllers such as PID, fuzzy and Adaptive Network-based Fuzzy Interface System (ANFIS) are designed to continuous control of the transmitted power. Simulation results evaluate advantages and disadvantages these controllers. ANFIS controller is designed by open loop method which has a good transient response. However, it has a large steady state error and is very sensitive to the variations in system. Fuzzy and ANFIS controllers are combined to remove these defects. The simulation results verify the advantages of the fuzzy-ANFIS controller with respect to the other designed controllers. Manuscript profile -
Open Access Article
200 - Stegananalysis Method Based on Co-Occurrence Matrix and Neural Network
S. Ghanbari N. Ghanbari M. Keshtgari S. H. Nabavi KariziSteganography is the art of hidden writing and secret communication. The goal of steganography is to hide the presence of information in other information. steganalysis is the art and science of detecting messages hidden using steganography. Co-occurrence matrix is the MoreSteganography is the art of hidden writing and secret communication. The goal of steganography is to hide the presence of information in other information. steganalysis is the art and science of detecting messages hidden using steganography. Co-occurrence matrix is the matrix containing information about the relationship between values of adjacent pixel in an image. In this paper, we extract features from Gray Level C0-occurrense Matrix (GLCM) that are difference between cover image (image without hidden information) and stego image (image with hidden information). In the proposed algorithm, first, we use a combined method of steganography based on both location and conversion to hide the information in the image. Then, using GLCM matrix properties, we investigate some difference values in the GLCM of the cover and stego images. We can extract features that were different between cover and stego images. Features are used for training neural network. This algorithm was tested on 800 standard image databases and it can detect 83% of stego images. Manuscript profile -
Open Access Article
201 - Analysis of Long-Term Dynamics of a Power Market due to Bounded Rationality of Investors Decisions under Different Market Designs
E. Khorram H. Seifi Mohammad Kazem Sheikh El EslamiIn this paper, the long-term dynamics of an electricity market due to bounded rationality in investment decision is analyzed under different market designs, including energy only market (EO), market with operating reserve pricing (OR), market with fixed capacity payment MoreIn this paper, the long-term dynamics of an electricity market due to bounded rationality in investment decision is analyzed under different market designs, including energy only market (EO), market with operating reserve pricing (OR), market with fixed capacity payment (FCP) and demand curve-based capacity market (DC). System dynamics (SD) method is used to analyze the behavior. Also, the equilibrium path is determined for comparison purposes. The results indicate that the different market designs have very different dynamics and it is possible to mitigate power market dynamics by selecting proper market design. Manuscript profile -
Open Access Article
202 - A Study of the University Course Timetabling Problem by Using a Hybrid of Improved Memetic and Simulated Annealing Algorithms
M. Joudaki M. A. Montazeri S. R. MousaviCourse timetabling is a complex problem, happening at the beginning of every semester at universities. One of the most important problems related to this issue is various constraints. As a result of this, timetabling is performed in various methods at different departme MoreCourse timetabling is a complex problem, happening at the beginning of every semester at universities. One of the most important problems related to this issue is various constraints. As a result of this, timetabling is performed in various methods at different departments. Many works have been performed to solve this problem which majority of them have used metaheuristic based techniques. In this paper, an algorithm is based on hybridization of improved memetic algorithm and simulated annealing algorithm is proposed. Improvement in memetic algorithm means heuristic initializes population and modification in crossover operator. Also, an operator which is called improvement is designed for improvement of created chromosomes and decrease of violation of constraints. In addition, utilization of simulated annealing will result to increase of the exploitive search ability of memetic algorithm. The experimental results which based on standard data indicate this method is more efficient in comparison with some other new methods. Manuscript profile -
Open Access Article
203 - A Long Term Learning Scheme in CBIR Systems by Defining Semantic Templates Using Information of Similarity-Refinement Based Short Term Learning
عصمت راشدی H. Nezamabadi-pourIn This paper, a new scheme for long term learning in CBIR systems is proposed. In this scheme, semantic templates are extracted from information provided through relevance feedback process for short-term learning which use similarity refinement techniques. This informa MoreIn This paper, a new scheme for long term learning in CBIR systems is proposed. In this scheme, semantic templates are extracted from information provided through relevance feedback process for short-term learning which use similarity refinement techniques. This information will be used as semantic templates in future retrieval sessions to improve the precision of the CBIR system. Also, a similarity function is introduced to calculate the similarity between queries and semantic templates. The proposed method is examined on a database with 10000 color images. The experimental results and comparison with ‘iFind’ method, confirm the effectiveness of the proposed method. Manuscript profile -
Open Access Article
204 - Balloon Energy Based on Contourlet in Parametric Active Contour for Segmentation of Texture Object in Texture Background
P. Moallem H. Tahvilian A. MonadjemiObject boundaries detection is one of the interesting subjects in computer and image processing. Active contour models are one of the popular methods in object detection and segmentation. This paper presents a new method for segmentation of texture object by means of pa MoreObject boundaries detection is one of the interesting subjects in computer and image processing. Active contour models are one of the popular methods in object detection and segmentation. This paper presents a new method for segmentation of texture object by means of parametric active contour. In this proposed method, by adding a balloon energy to energy function of the parametric active contour model, the detection and segmentation of textured object against textured background would be achieved. In this method, texture feature of contour and object points are calculated by contourlet transform. Then by comparing these features with texture feature of target object, which are available as prior information, movement direction of balloon is defined, whereupon contour curves are expanded or contracted in order to adapt to the target boundaries. Experimental results demonstrate that the active contour based on contourlet (Contourlet-ACM) has higher segmentation accuracy than the active contour based on moment (Moment-ACM) and active contour based on DWHT (DWHT-ACM). Manuscript profile -
Open Access Article
205 - Economical Optimization of Capacity and Operational Strategy for Combined Heat and Power Systems
M. HajinazariAn optimization method has been developed to determine the optimal capacities for the CHP and boiler such that thermal and electrical energy demands can be satisfied with high cost efficiency. The proposed method offers an operational strategy in order to determine the MoreAn optimization method has been developed to determine the optimal capacities for the CHP and boiler such that thermal and electrical energy demands can be satisfied with high cost efficiency. The proposed method offers an operational strategy in order to determine the optimum value for boiler and CHP capacities which maximize an objective function based on the net present value (NPV). The reduction in operational strategy expenses arising from the monetary cost of the credit attainable by air pollution reduction is also taken into account in evaluation of the objective function. The optimal value for boiler and CHP capacities and the resulting projection for the optimal value of the objective function are derived using a hybrid optimization method involving the particle swarm optimization (PSO) and the linear programming algorithms. The viability of the proposed method is demonstrated by analyzing the decision to construct a CHP system for a typical hospital. Manuscript profile -
Open Access Article
206 - A New Algorithm for Fast Mode-Switching and Control of TCSC in Less than Half Cycle A New Algorithm for Fast Mode-Switching and Control of TCSC in Less than Half Cycle
M. Nayeripour M. M. MansuriThyristor Controlled Series Capacitor (TCSC) has been used for various purposes such as power system stability improving and increasing of loadability, loss reduction, line impedance compensation or power flow control. Fast switching of TCSC from capacitive mode to indu MoreThyristor Controlled Series Capacitor (TCSC) has been used for various purposes such as power system stability improving and increasing of loadability, loss reduction, line impedance compensation or power flow control. Fast switching of TCSC from capacitive mode to inductive mode and vice versa following the fault and clearing of it respectively, is an essential key for improving transient and even dynamic stability of power system which have not been considered significantly. In this paper a new algorithm for fast mode-switching and control of TCSC in less than half cycle is proposed for changing capacitive to inductive mode and vice versa in less than half cycle. Simulation results show that the proposed method is faster and more reliable in different conditions than the existing method and can be used more effective in transient and dynamic stability improvement. Manuscript profile -
Open Access Article
207 - A New Approach for Modeling and Global Optimum Solution of Transmission Expansion Planning Including Contingency Conditions
A. Nateghia H. Seifi Mohammad Kazem Sheikh El Eslami S. M. Sepasiants cause different neural responses containing a regular firing, or a long latency before firing with or without a leading spike. In this paper, the firing behavior of DCN pyramidal cells is simulated first Transmission Expansion Planning (TEP) is an important issue of Morets cause different neural responses containing a regular firing, or a long latency before firing with or without a leading spike. In this paper, the firing behavior of DCN pyramidal cells is simulated first Transmission Expansion Planning (TEP) is an important issue of power system planning studies. In literature, different methods are investigated to achieve good solutions for TEP. This paper uses Mixed Integer Linear Programming (MILP) and Mixed Integer Nonlinear Programming (MINLP) methods to study TEP. It also presents a new NLP model in which the integer variables are omitted. Moreover, the models are properly modified so that contingency conditions are also observed. Different combinations of cost functions such as the expansion cost, the operation cost and the cost of the losses are considered and compared. To reach a global optimum solution, BARON solver is applied. The proposed algorithm is applied on Garver 6-bus and IEEE-118 bus test systems. It is shown that modeling the problem by MINLP and NLP methods, in combination with a proper solver, can result in a quick optimum solution. Manuscript profile -
Open Access Article
208 - Simulation of Pyramidal Cells Firing Types and Adjustment of Their Characteristics by Means of Transient Potassium Currents
Z. Daneshparvar M. R. DaliriPyramidal cells of the dorsal cochlear nucleus (DCN) represent firing types with different latencies. They incorporate two transient potassium currents namely Ikif and Ikis with fast and slow inactivation gatings, respectively. Transient potassium currents i.e. currents MorePyramidal cells of the dorsal cochlear nucleus (DCN) represent firing types with different latencies. They incorporate two transient potassium currents namely Ikif and Ikis with fast and slow inactivation gatings, respectively. Transient potassium currents i.e. currents having both activation and inactivation gatings influence on the latency before firing. These currents cause different neural responses containing a regular firing, or a long latency before firing with or without a leading spike. In this paper, the firing behavior of DCN pyramidal cells is simulated first with a 3-variable conductance-based model. Next, mechanisms underlie neural responses of the model are analyzed by dynamical systems analysis methods. The model is a reduced version of Kanold and Manis model with 10 variables. Manuscript profile -
Open Access Article
209 - Risk-based Static and Dynamics Security Assessment and Its Enhancement with Particle Swarm Optimization Generation Realloca
M. Saeedi H. SeifiSecurity assessment is traditionally checked using a deterministic criterion. Based on that, the system may be considered as secured or unsecured. If an unsecured condition is detected, preventive actions are foreseen to make it secure. Recently, risk based security as MoreSecurity assessment is traditionally checked using a deterministic criterion. Based on that, the system may be considered as secured or unsecured. If an unsecured condition is detected, preventive actions are foreseen to make it secure. Recently, risk based security assessment is used in power systems. In this paper, risk-based static and dynamic security assessment is proposed and a new transient stability index is defined. In this paper, the risk index is used as an objective function in the generation reallocation algorithm. In this algorithm, the security is maintained using the generation reallocation. The algorithm is tested on IEEE 24-bus test system and its capabilities are assessed in comparison with a traditional OPF, in which the security is maintained based on a deterministic criterion. Particle Swarm Optimization (PSO) algorithm is used as the optimization tool. Manuscript profile -
Open Access Article
210 - Economic Evaluation for Independent Network with Inner Control Consist of Distributed Generation
A. KhandaniIn this paper, four scenarios of energy supply for consumers are compared using the proposed objective function and the most appropriate energy methods have been identified. Four energy scenarios are: energy only by the network, the networks and distributed resources, m MoreIn this paper, four scenarios of energy supply for consumers are compared using the proposed objective function and the most appropriate energy methods have been identified. Four energy scenarios are: energy only by the network, the networks and distributed resources, micro-grid systems only and micro grid connected to the upstream network. The objective function for these energy scenarios are calculated and compared for two different load connections, all loads on one feeder and each load on individual feeders. Proposed objective function for each scenario consists of two dimensions, cost and reliability. Cost dimension includes constant cost, current cost and reliability dimension includes non delivered energy for consumers. After conversion into one dimension, the objective function is solved using linear programming. The proposed method in this paper compared with similar methods and these results demonstrate that the method in this paper is more efficient and practical. Manuscript profile -
Open Access Article
211 - A New Formulation for the Probabilistic Congestion Management Using Chance Constrained Programming
M. Hojjat M. H. JavidiIn this paper, a new method for probabilistic congestion management considering power system uncertainties is proposed. Chance constrained programming (CCP) is used to formulate the probabilistic congestion management as an efficient approach for stochastic optimization MoreIn this paper, a new method for probabilistic congestion management considering power system uncertainties is proposed. Chance constrained programming (CCP) is used to formulate the probabilistic congestion management as an efficient approach for stochastic optimization problems. The CCP based probabilistic congestion management is solved utilizing a numerical approach by applying the Monte-Carlo technique into the real-coded genetic algorithm. The effectiveness of the proposed method is evaluated applying the method to the modified IEEE 9-bus test system. The results of the proposed approach are compared with those of the expected method to have a comprehensive study. The simulation results reflect the flexibility of the proposed approach in transmission congestion management. Manuscript profile -
Open Access Article
212 - Correction of the Load Tracking Method in Transmission Pricing Considering Correlation Coefficients
M. T. Ameli M. AnsariTransmission pricing has become one of the important issues of the power industry with the power industry´s restructuring. The pricing should be done fairly to achieve a healthy competitive environment. The load tracking method will be discussed in this paper. For this MoreTransmission pricing has become one of the important issues of the power industry with the power industry´s restructuring. The pricing should be done fairly to achieve a healthy competitive environment. The load tracking method will be discussed in this paper. For this purpose, various operating points were made around the nominal operating point at first, using statistical data. After that, the network load flow is being calculated for each operating point and the linear regression and correlation coefficients between each producer/consumer’s generation/consumption and the following power of each line, were being achieved and the players' share of the transmission cost is being calculated by combining this coefficients. The participation coefficients were being calculated at the end for the 39 Bus IEEE test system and its results will be compared with previous methods. The Comparison of the results show that the reviewed methods cover the transmission costs, but the determined share for each player using this paper’s method, has a greater proportion with the amount of the transmission network usage. Manuscript profile -
Open Access Article
213 - Determination of Formal Methods Capabilities for Software Specification and Analysis
H. Banki V. Ahmadi SabetSoftware developers face the problem of adopting a suitable formal method to developing their software. We aim to determine capability level of formal methods in software specification and analysis in four steps. The first step introduces the criteria by which the forma MoreSoftware developers face the problem of adopting a suitable formal method to developing their software. We aim to determine capability level of formal methods in software specification and analysis in four steps. The first step introduces the criteria by which the formal methods assess. The second and third ones deal with categorizing sorts of software and formal methods based on their solution methods. The fourth step determines fitness of some typical formal methods to specification and analysis of each software category. Manuscript profile -
Open Access Article
214 - A Comprehensive Method to Secure Time Synchronization in Wireless Sensor
Z. AhmadiOne of the important requirements of sensor networks is synchronization of the nodes. The importance of time in sensor networks causes the adversary tries to disturb time synchronization by altering and faking messages, delaying or replying them, compromising the nodes MoreOne of the important requirements of sensor networks is synchronization of the nodes. The importance of time in sensor networks causes the adversary tries to disturb time synchronization by altering and faking messages, delaying or replying them, compromising the nodes and sending false messages via them. Up to now, there is no method that is able to provide both synchronization and security needs of sensor networks simultaneously. In this paper, we suggest a method that is capable to provide precise synchronization, along with low communication and computational overhead, low convergence time and high security against internal and external attacks. Simulation and analytic results show the preference of our method compared to other available methods. Manuscript profile -
Open Access Article
215 - A New Approach for the Diagnosis of Mammographic Masses Based on BI-RADS Features and Opposition-Based Classification
F. Saki A. Tahmasbi Shahriar Baradaran ShokouhiFast and accurate classification of benign and malignant patterns in digital mammograms is of significant importance in the diagnosis of breast cancers. In this paper, we develop a new Computer-aided Diagnosis (CADx) system using a novel Opposition-based classifier to e MoreFast and accurate classification of benign and malignant patterns in digital mammograms is of significant importance in the diagnosis of breast cancers. In this paper, we develop a new Computer-aided Diagnosis (CADx) system using a novel Opposition-based classifier to enhance the accuracy and shorten the training time of the classification of breast masses. We extract a group of Breast Imaging-Reporting and Data System (BI-RADS) features from preprocessed mammography images and feed them to a Multi-Layer Perceptron (MLP). The MLP is then trained using a new learning rule which we will refer to as the Opposite Weighted Back Propagation (OWBP) algorithm. We evaluate the performance of the system, in terms of classification accuracy, using a Receiver Operational Characteristics (ROC) curve. The proposed system yields an area under ROC curve (Az) of 0.924 and an accuracy of 92.86 %. Furthermore, the speed analysis results suggest that, with the same network topology, the convergence rate of the proposed OWBP algorithm is almost 4 times faster than that of the traditional Back Propagation (BP) algorithm. Manuscript profile -
Open Access Article
216 - Intelligent Bargaining in Market Using Reinforcement Learning
M. A. Saadatjoo V. Derhami فاطمه سعادت جوUsing Information Technology techniques have been increased complication and dynamicity of supply-and-demand systems like auctions. In this paper, we introduce a novel method by applying Reinforcement Learning (RL) price offer as one of the robust methods of agent learn MoreUsing Information Technology techniques have been increased complication and dynamicity of supply-and-demand systems like auctions. In this paper, we introduce a novel method by applying Reinforcement Learning (RL) price offer as one of the robust methods of agent learning which can be used in interactive conditions with minimum level of information in auction and reverse auction. Negotiation as one of the challengeable and complicated behaviors is caused an agreement on price in auctions. The main aim of our method is maximizing seller’s and customer’s profits. We formulate seller and customer selection in form of two different RL problems. All of the RL parameters like states, actions, and reinforcement function are defined. Also, we describe an experimental method to compare with our proposed method for proving advantages of our method. Manuscript profile -
Open Access Article
217 - Modeling and Analysis Iterated Prison Dilemma Game by Grossberg Counter-Propagation Neural Network
Gh. A. Montazer N. Rastegar Ramshe Alireza AskarzadehMost of the time effective decisions in strategic situations such as competitive issues require a non-linear mapping between stimulus and response. Artificial neural networks can be an appropriate way for modeling and solving these kinds of problems. Prison Dilemma Game MoreMost of the time effective decisions in strategic situations such as competitive issues require a non-linear mapping between stimulus and response. Artificial neural networks can be an appropriate way for modeling and solving these kinds of problems. Prison Dilemma Game is a well-known game that is proposed in game theory. This paper tries to describe how using neural network, the iterated prisoner’s dilemma game can be modeled and analyzed. To do this a Grossberg Counter-Propagation Neural Network (GCP-NN) has been designed to play this game. Results show the capability of this method in complete modeling game. The results present the efficiency of the new method in comparison with the two conventional methods: Tit For Tat (TFT) strategy and Perceptron modeled game. Manuscript profile -
Open Access Article
218 - Extracting Bottlenecks Using Object Recognition in Reinforcement Learning
B. Ghazanfari N. Mozayani M. R. Jahed MotlaghExtracting bottlenecks improves considerably the speed of learning and the ability knowledge transferring in reinforcement learning. But, extracting bottlenecks is a challenge in reinforcement learning and it typically requires prior knowledge and designer’s help. This MoreExtracting bottlenecks improves considerably the speed of learning and the ability knowledge transferring in reinforcement learning. But, extracting bottlenecks is a challenge in reinforcement learning and it typically requires prior knowledge and designer’s help. This paper will propose a new method that extracts bottlenecks for reinforcement learning agent automatically. We have inspired of biological systems, behavioral analysts and routing animals and the agent works on the basis of its interacting to environment. The agent finds landmarks based in clustering and hierarchical object recognition. If these landmarks in actions space are close to each other, bottlenecks are extracted using the states between them. The Experimental results show a considerable improvement in the process of learning in comparison to some key methods in the literature. Manuscript profile -
Open Access Article
219 - Dual-Output Rectifier-Inverter System for Independently Supplying Two Three-Phase Loads
M. Heydari A. Yazdian Varjani M. MohamadianIn this paper a rectifier-inverter system including a three phase diode rectifier and a dual output inverter is proposed for independently supplying two three-phase loads. This system employs less number of semiconductor devices compared to former dual output inverters MoreIn this paper a rectifier-inverter system including a three phase diode rectifier and a dual output inverter is proposed for independently supplying two three-phase loads. This system employs less number of semiconductor devices compared to former dual output inverters proposed in the literature and uses only six active switches for controlling two three-phase loads. Reducing the number of switches and hence drive and control circuits and also cooling system may result in a reduction in overall cost of the system, may reduce its semiconductor power loss and as a result increases efficiency and reliability especially in applications with low and medium voltage and power ratings. The new configuration is introduced and its carrier-based PWM schemes are developed. Analysis of sizing of the DC link capacitors is also performed so as to minimize the DC link voltage ripple, to reduce the value of DC link capacitors and to improve the grid current THD and the grid current balance. Furthermore, loss profile of the system is studied and the results are compared with counterpart topologies. Simulation and experimental results are presented to verify the authenticity of the theoretical model. Manuscript profile -
Open Access Article
220 - Optimal Location for Distributed Generation Based on Uuncertain Data
H. GoodarziThe purpose of this paper is optimal location of distributed generation in electric distribution networks. Load uncertainty and desired voltage range has been modeled using fuzzy data theory. The objective function includes loss reduction, improvement of profile index a MoreThe purpose of this paper is optimal location of distributed generation in electric distribution networks. Load uncertainty and desired voltage range has been modeled using fuzzy data theory. The objective function includes loss reduction, improvement of profile index and voltage stability index with their relevant constraints, voltage constraints and transmittable power from the line. Load variation has been shown for three different time durations (peak, off peak and average).PSO technique has been used to optimize the objective function while Max-Min method has been applied to select the answer. Results produced from the proposed model have been provided in 5 different scenarios on a 33 bus system of IEEE. Manuscript profile -
Open Access Article
221 - Designing a Self-Tuning Frequency Controller Based on ANNs for an Isolated Microgrid
F. Habibi H. Bevrani J. MoshtagIncreasing electrical energy demand, as well as fossil fuel shortages and environmental concerns have caused to use uncommon sources such as distributed generations (DGs) and renewable energy sources (RESs) into modern power systems. A microgrid (MG) system consists of MoreIncreasing electrical energy demand, as well as fossil fuel shortages and environmental concerns have caused to use uncommon sources such as distributed generations (DGs) and renewable energy sources (RESs) into modern power systems. A microgrid (MG) system consists of several DGs and RESs which is responsible to provide both electrical and heat powers for local loads. Due to the MGs nonlinearity/complexity which is imposed to the conventional power systems, classical and nonflexible control structures may not represent desirable performance over a wide range of operating conditions. Therefore, more flexible/intelligent control methods are needed most of the past. Hence, in this paper addresses to design an online/self-tuning PI-controller based on artificial neural networks (ANNs) for optimal regulating the MG systems frequency. Manuscript profile -
Open Access Article
222 - Wideband Spectrum Sensing in Cognitive Radio Networks by Using Improved Energy Detector
Y. Eghbali M. Ahmadian Attari H. HassaniIn cognitive radio networks, spectrum sensing is of a great importance in determining spectrum holes. In this paper, the impact of improved energy detector on the wideband spectrum sensing is considered for accurate detection of spectrum holes. For this end, wideband sp MoreIn cognitive radio networks, spectrum sensing is of a great importance in determining spectrum holes. In this paper, the impact of improved energy detector on the wideband spectrum sensing is considered for accurate detection of spectrum holes. For this end, wideband spectrum is sub channelized into equal non-overlapping sub-bands. Our main concern is to find the thresholds of the individual sub-bands simultaneously. By formulating the spectrum sensing problem, in terms of convex optimization one, we seek for maximizing the opportunistic aggregate throughput of cognitive users. In numerical simulation section, it is illustrated that using improved energy detector, the opportunistic aggregate throughput is improved significantly. Manuscript profile -
Open Access Article
223 - Joint Detection of Correlated OFDM Subchannels for Wideband Spectrum Sensing in Cognitive Radio Networks
B. Rassouli A. OlfatIn this paper, we consider the wideband spectrum sensing in which primary users use OFDM modulation. Pulse shape of each subchannel is non-ideal which results in the leakage of power among adjacent subchannels. This phenomenon makes the received energy of each subchanne MoreIn this paper, we consider the wideband spectrum sensing in which primary users use OFDM modulation. Pulse shape of each subchannel is non-ideal which results in the leakage of power among adjacent subchannels. This phenomenon makes the received energy of each subchannel (test statistic of energy detector) correlated with those of other subchannels. Therefore, in order to jointly detect the state of primary network subchannels, we propose a simple iterative method and we observe its performance improvements in comparison to the disjointed method (in which the detection of each subchannel state is independent of the detection of other s Manuscript profile -
Open Access Article
224 - Introducing a New Actuation Signal to Improve the Reliability of Capacitive RF MEMS Switch
M. Zarghami Y. Mafinejad M. Zarghami Kh. MafinezhadIn this paper a modified novel dual pulse actuation signal has been proposed to reduce dielectric charging in microelectromechanical system switches. The waveform has a significant impact in reducing the dielectric charging; therefore the amount of charge density in the MoreIn this paper a modified novel dual pulse actuation signal has been proposed to reduce dielectric charging in microelectromechanical system switches. The waveform has a significant impact in reducing the dielectric charging; therefore the amount of charge density in the proposed waveform has decreased 7.2% than the dual pulse waveform, although the newest waveform (novel dual pulse) has shown a 5% reduction in dielectric charging. So, the proposed actuation signal waveform will increase the lifetime of switch. We utilized mathematical and transient circuit models to calculate the amount of charge density in the dielectric and finally, the new actuation signal waveform has shown better performance than the other prevalent actuation signal waveforms. Manuscript profile -
Open Access Article
225 - Designing an Optimal Proportional-Integral Sliding Surface for a Quarter Car Active Suspension System with Suspension Components Possessing Uncertain Constants and Nonlinear Characteristics
S. A. Zahiripour A. A. JalaliIn this paper, design of a controller for a quarter car active suspension system have been done with the focus on sliding mode strategy. Suspension components, including spring and shock-absorber have nonlinear characteristics with uncertain constants, but they have def MoreIn this paper, design of a controller for a quarter car active suspension system have been done with the focus on sliding mode strategy. Suspension components, including spring and shock-absorber have nonlinear characteristics with uncertain constants, but they have defined bound. To simplify the controller designing, feedback-linearization is proposed, then with using the optimal strategy, we obtain a proportional - integral sliding surface and a controller for meeting the sliding condition has been proposed. The design process is in a such way that not only, guarantees asymptotic stability of the suspension system in the presence of parametric uncertainties, but also the designer can supply his slightly trade-off between convenience of passengers and controllability of car, with setting some parameters. Manuscript profile -
Open Access Article
226 - Bidirectional Transformation of Structural Modeling Elements between the UML Class Diagram and Object-Z
A. Rasoolzadegan Ahmad Abdollahzadeh BarforoushIn this paper, a new mechanism is proposed to transform the structural modeling elements of the UML class diagram and Object-Z specifications into each other. A set of bidirectional rules is defined to transform the mentioned elements into each other. Bidirectional tran MoreIn this paper, a new mechanism is proposed to transform the structural modeling elements of the UML class diagram and Object-Z specifications into each other. A set of bidirectional rules is defined to transform the mentioned elements into each other. Bidirectional transformation of the UML class diagram, as one of the most useful diagrams of UML, and Object-Z specifications into each other prepares the ground for the use of the unique advantages of both formal and visual modeling methods. The feasibility of the proposed approach is evaluated using the multi-lift case study. The results of conducting the multi-lift case study show that the proposed mechanism is feasible. Manuscript profile -
Open Access Article
227 - Fuzzy Voting for Anomaly Detection in Cluster-Based Mobile Ad Hoc Networks
Mohammad Rahmanimanesh Saeed JaliliIn this paper, an attack analysis and detection method in cluster-based mobile ad hoc networks with AODV routing protocol is proposed. The proposed method uses the anomaly detection approach for detecting attacks in which the required features for describing the normal MoreIn this paper, an attack analysis and detection method in cluster-based mobile ad hoc networks with AODV routing protocol is proposed. The proposed method uses the anomaly detection approach for detecting attacks in which the required features for describing the normal behavior of AODV protocol are defined via step by step analysis of AODV protocol and independent of any attack. In order to learn the normal behavior of AODV, a fuzzy voting method is used for combining support vector data description (SVDD), mixture of Gaussians (MoG), and self-organizing maps (SOM) one-class classifiers and the combined model is utilized to partially detect the attacks in cluster members. The votes of cluster members are periodically transmitted to the cluster head and final decision on attack detection is carried out in the cluster head. In the proposed method, a fuzzy voting method is used for aggregating the votes of cluster members in the cluster head by which the performance of the method improves significantly in detecting blackhole, rushing, route error fabrication, packet replication, and wormhole attacks. In this paper, an attack analysis method based on feature sensitivity ranking is also proposed that determines which features are influenced more by the mentioned attacks. This sensitivity ranking leads to the detection of the types of attacks launched on the network. Manuscript profile -
Open Access Article
228 - Gravity Oriented One-Class Classifier Based on Support Vector Data Descriptor
H. Ghafarian H. Sadoghi Yazdi Y. AllahyariIn this paper, a one-class classifier based on the Support Vector Data Descriptor (SVDD) is proposed. In SVDD, even outlier samples which are out of the decision boundary, are affecting the boundary. This increases the error of the classifier. In the proposed classifier MoreIn this paper, a one-class classifier based on the Support Vector Data Descriptor (SVDD) is proposed. In SVDD, even outlier samples which are out of the decision boundary, are affecting the boundary. This increases the error of the classifier. In the proposed classifier, decision boundary is determined by all of the samples through a gravity oriented approach. In this way, two classifier is proposed which in one of them knowledge about outliers are also considered. The optimization problem of the proposed method is convex and can be used with the kernel methods. Experiments on the behavior of the proposed classifier regarding changes of the parameters were done. Comparing results of experiments with results of SVDD and Density Induced SVDD shows that the proposed method can decrease the effects of outliers. Manuscript profile -
Open Access Article
229 - Structure-Texture Image Decomposition for Content-Based Image Retrieval
S. Hayati S. Saryazdi H. Nezamabadi-pourIn this paper, a novel low-level image feature extraction and indexing scheme based on structure-texture image decomposition is presented. The main idea of this work is to decompose database images to structure and texture sub-images to decrease the destructive effects MoreIn this paper, a novel low-level image feature extraction and indexing scheme based on structure-texture image decomposition is presented. The main idea of this work is to decompose database images to structure and texture sub-images to decrease the destructive effects of simultaneous existence of structure and texture information in the image in indexing phase. It is also shown that precision in a typical content-based image retrieval system can considerably increase by combining the feature vectors extracted from structure and texture sub-images. An image database containing 10000 images of 82 different semantic groups is used to evaluate the proposed method. The results confirm the effectiveness of this method. Manuscript profile -
Open Access Article
230 - Designing Optimal Fuzzy Classifier Using Particle Swarm Optimization
Seyed-Hamid ZahiriAn important issue in designing a fuzzy classifier is setting its structural and mathematical fuzzy parameters (e.g., number of rules, antecedents, consequents, types and locations of membership functions). In fact, the variations of these parameters establish a wide MoreAn important issue in designing a fuzzy classifier is setting its structural and mathematical fuzzy parameters (e.g., number of rules, antecedents, consequents, types and locations of membership functions). In fact, the variations of these parameters establish a wide range high dimensional search space, which makes heuristic methods some suitable candidates to solve this problem (designing optimal fuzzy parameters). In this paper, a method is described for this purpose. In presented technique, all fuzzy parameters of a fuzzy classifier, are interpreted in structure of particles and PSO algorithm is employed to find the optimal one. Extensive experimental results on well-known benchmarks and practical pattern recognition problem (automatic target recognition) demonstrate the effectiveness of the proposed method. Manuscript profile -
Open Access Article
231 - Design of a New Format-Compliant Partial Encryption Scheme for H.264 Video Design of a New Format-Compliant Partial Encryption Scheme for H.264 Video
S. Rasoolifar M. KhademiH.264 is the latest video compression standard and its compression efficiency is twice as much as previous standards. Due to the advantages of this standard and its widespread use in various video applications, the protection of this standard has become necessary. In th MoreH.264 is the latest video compression standard and its compression efficiency is twice as much as previous standards. Due to the advantages of this standard and its widespread use in various video applications, the protection of this standard has become necessary. In this paper, a new partial encryption scheme is presented for H.264 video which keeps the video format unchanged. In this method, parameters with high sensitivity to H.264 video texture and motion components are encrypted during compression. That is, such parameters as Intra4x4PredMode, Intra Residual Data, Ref-Index and MVD are encrypted using stream ciphers. This encryption scheme obtains high encryption efficiency through reducing the encrypted data volume along with high perceptual security. In addition to these properties, parameter selection and encryption in the proposed method is implemented in a way that the encrypted video format is kept compliant and thus can be utilized in different applications such as commercial and entertainment applications. Manuscript profile -
Open Access Article
232 - Improved Maximum Power Point Tracking Off-Grid Solar Panels
A. R. ReisiSolar panels exhibit non-linear current–voltage characteristics producing maximum power at only one particular operating point. The maximum power point changes with temperature and light intensity variations. Different methods have been introduced for tracking the maxim MoreSolar panels exhibit non-linear current–voltage characteristics producing maximum power at only one particular operating point. The maximum power point changes with temperature and light intensity variations. Different methods have been introduced for tracking the maximum power point based on offline and online methods. In this paper a new method is presented to improve the performance of maximum power point tracking in off-grid solar panels. The proposed algorithm is a combination of two loops, set point calculation and fine tuning loops. First the set point loop approximates the maximum power using offline calculation of the open circuit voltage. The exact amount of the maximum power will, then, be tracked by the fine tuning loop which is based on perturbation and observation (P&O) method. The proposed method is simulated in Matlab/Simulink environment and experimentally verified using a laboratory prototype. In maximum power point tracking, the effects of frequency variation and disturbance amplitude on dynamic response and steady state performance are examined. Simulation and experimental results are compared with other methods and the effectiveness of the proposed method is evaluated. Manuscript profile -
Open Access Article
233 - Adaptive Control of Pitch Angle of Wind Turbine Using Human Brain Mechanisms of Emotional Learning
M. Hayatdavudi mohsen Farshad H. R. Najafi R. Sedaghati M. JoorabianThe purpose of this paper is optimal location of distributed generation in electric distribution networks. Load uncertainty and desired voltage range has been modeled using fuzzy data theory. The objective function includes loss reduction, improvement of profile index a MoreThe purpose of this paper is optimal location of distributed generation in electric distribution networks. Load uncertainty and desired voltage range has been modeled using fuzzy data theory. The objective function includes loss reduction, improvement of profile index and voltage stability index with their relevant constraints, voltage constraints and transmittable power from the line. Load variation has been shown for three different time durations (peak, off peak and average).PSO technique has been used to optimize the objective function while Max-Min method has been applied to select the answer. Results produced from the proposed model have been provided in 5 different scenarios on a 33 bus system of IEEE. Manuscript profile -
Open Access Article
234 - Electrical Islanding Detection in Electrical Distribution Networks with Distributed Generation Using Discrete Wavelet Transform and Artificial Neural Network
M. Heidari Orejloo S. Gh. Seifossadat M. RazazIn this paper a new algorithm is provided for detecting of electrical islands, based on analysis of transient signals using discrete wavelet transform (DWT) and artificial neural network (ANN). The neural network is taught for Classification of events to the "islands" o MoreIn this paper a new algorithm is provided for detecting of electrical islands, based on analysis of transient signals using discrete wavelet transform (DWT) and artificial neural network (ANN). The neural network is taught for Classification of events to the "islands" or "non-islands". Needed features for classification are extracted by DWT of DG transient voltage signal. DIgSILENT, MATLAB and WEKA softwares are used for simulation. Proposed method is tested on a CIGRE medium voltage distribution system with two different types of DGs. The final method is chosen from among 162 relay projects with respect to different criteria, including accuracy, speed, simplicity and cost efficiency is the best. With The analysis done in the best relay selection for DGs, the voltage signal, the mother wavelet db4 and seventh level wavelet transform are used. Simulation results show that this method in compared with existing methods, can detect the electrical islands, with a shorter time and higher accuracy. Manuscript profile -
Open Access Article
235 - Design Improvement of Synchronous Reluctance Motor Geometry, Using Neural-Network, Genetic Algorithm and Finite Element Method
M. Haghparast S. Taghipour Boroujeni A. Kargarappropriate approach to reach high efficiency in Synchronous Reluctance (SynRel) machines is to enhance these machines’ magnetic saliency. This is usually done by changing the geometry of machine and especially by changing the number and shape of rotor flux barriers. In Moreappropriate approach to reach high efficiency in Synchronous Reluctance (SynRel) machines is to enhance these machines’ magnetic saliency. This is usually done by changing the geometry of machine and especially by changing the number and shape of rotor flux barriers. In this paper an intelligent- method have been used to optimizing the design of SynRel motors based on magnetic saliency ratio. To achieve this aim, all of the motor parameters including stator geometry, axial length of machine, winding type, and number of flux barriers in rotor are assumed constant and just position of the rotor flux barriers are optimized. These positions have been defined by six parameters. Changing these parameters, the magnetic saliency of machine is calculated by finite element analysis (FEA). Using these values to train a neural network (NN), a modeling function is obtained for magnetic saliency of SynRel machine. Considering this NN as the target function in genetic algorithm (GA), the parameters of SynRel machine have been optimized and the best rotor structure with highest magnetic saliency has been obtained. Finally the abilities of NN in correct estimation of magnetic saliency and motor synchronization were approved by FEA and dynamic simulation. Manuscript profile -
Open Access Article
236 - Joint Bandwidth Extension and Vector Taylor Series Approaches to Enhance the Corrupted Narrowband Speech
S. Pourmohammadi M. Vali M. GhadyaniIn this paper, we introduce an efficient and previously unreported approach to enhance the quality of corrupted narrowband speech signal using joint Vector Taylor Series (VTS) and Bandwidth Extension (BWE) algorithms. First, feature vectors extracted from the noisy narr MoreIn this paper, we introduce an efficient and previously unreported approach to enhance the quality of corrupted narrowband speech signal using joint Vector Taylor Series (VTS) and Bandwidth Extension (BWE) algorithms. First, feature vectors extracted from the noisy narrowband signal have modified applying VTS technique. Then, the estimation of corresponding wideband features have derived from the compensated parameters using two different artificial BWE methods (Envelope prediction with GMM and Neural Network). Finally, the distance between the wideband feature vectors and their estimated values evaluated using Log Spectral Distortion (LSD) measurement criteria. The results of implementation clearly show the advantage of proposed idea to improve the quality of the contaminated speech. In addition, we show that artificial BWE of speech signal, based on the neural network envelope extension outperforms better results in comparison with the GMM algorithm. Manuscript profile -
Open Access Article
237 - Robustness of Speech Recognition Using Non-Linear Asymmetric Filter and Delta Spectral Characteristics
H. Farsi S. KuhimoghadamIn this paper, we propose a new feature extraction algorithm which is robust against noise. In the proposed algorithm, a non-linear filter with temporal masking are used for speech feature extraction and by applying delta spectral characteristics instead of delta cepstr MoreIn this paper, we propose a new feature extraction algorithm which is robust against noise. In the proposed algorithm, a non-linear filter with temporal masking are used for speech feature extraction and by applying delta spectral characteristics instead of delta cepstral, the accuracy of speech recognition is improved. Almost, all present Automatic Speech Recognition (ASR) systems use cepstral-delta and delta-delta characteristics for speech feature extraction. The aim of this paper is to reach the robust speech features which provide more accurate speech recognition under different noisy conditions. This is achieved by focusing on speech key features (especially non-stationary speech features) which highly differ from the noise signals. The obtaining experimental results show that the accuracy of speech recognition improves in comparison with traditional methods such as PLP and MFCC. Manuscript profile -
Open Access Article
238 - Bayesian Network Parameter Learning from Data Contains Missing Values
K. Etminani M. Naghibzadeh M. Emadi A. R. RazaviLearning Bayesian network structure from data has attracted a great deal of research in recent years. It is shown that finding the optimal network is an NP-hard problem when data is complete. This problem gets worse when data is incomplete i.e. contains missing values a MoreLearning Bayesian network structure from data has attracted a great deal of research in recent years. It is shown that finding the optimal network is an NP-hard problem when data is complete. This problem gets worse when data is incomplete i.e. contains missing values and/or hidden variables. Generally, there are two cases of learning Bayesian networks from incomplete data: in a known structure, and unknown structure. In this paper, we try to find the best parameters for a known structure by introducing the “effective parameter”, in a way that the likelihood of the network structure given the completed data being maximized. This approach can be attached to any algorithm such as SEM (structural expectation maximization) that needs the best parameters to be known to reach the optimal Bayesian network structure. We prove that the proposed method gains the optimal parameters with respect to the likelihood function. Results of applying the proposed method to some known Bayesian networks show the speed of the proposed method compared to the well-known methods. Manuscript profile -
Open Access Article
239 - A Requirement-Based Method to Software Architecture Testing
S. M. SharafiIn this paper, after a review on well-known scenario-based methods of SA evaluation, a different approach is introduced to find architectural defects. The proposed method at first, elicits the problems threatening the system's success. Then based on the analysis of the MoreIn this paper, after a review on well-known scenario-based methods of SA evaluation, a different approach is introduced to find architectural defects. The proposed method at first, elicits the problems threatening the system's success. Then based on the analysis of the problems and probable defects which could cause the problems, tests are designed and applied to the system in order to find the real defects specially the architectural ones. Results show that the proposed method could be use to find those architectural defects which may be remained covered after applying the other methods. Therefore, it could be used as a mean to SA testing and also as a complementary mechanism along with well-known SA evaluation methods. The proposed method and its components are presented in a systematic form. An illustration of its application on the architecture of a real system is presented and the results are compared with the results of applying ATAM on the same architecture. Manuscript profile -
Open Access Article
240 - Developing a New Version of Local Binary Patterns for Texture Classification
M. Pakdel M. H. ShakoorTexture classification is one of the main steps in image processing and computer vision applications. Feature extraction is the first step of texture classification process which plays a main role. Many approaches have proposed to classify textures since now. Among them MoreTexture classification is one of the main steps in image processing and computer vision applications. Feature extraction is the first step of texture classification process which plays a main role. Many approaches have proposed to classify textures since now. Among them, Local Binary Patterns and Modified Local Binary Patterns, because of simplicity and classification accuracy, have emerged as one of the most popular ones. The Local Binary Patterns have simple implementation, but with increase in the radius of neighborhood, computational complexity will be increased. Modified Local Binary Patterns assigns various labels to uniform textures and a unique label to all non-uniform ones. In this respect, the modified local binary pattern can't classify non uniform textures as well as uniform ones. In this paper a new version of Local Binary Pattern is proposed that has less computational complexity than Local Binary Patterns and more classification accuracy than Modified version. The proposed approach classifies non uniform textures as well as uniform ones. Also with change in the length of central gray level intervals, locality and globally of the features can be controlled. Classification accuracy on two standard datasets, Brodatz and Outex, indicates the efficiency of the proposed approach. Manuscript profile -
Open Access Article
241 - An Uncertain Distributed Method for Reasoning in Ontologies
F. Anoosha B. Tork Ladani M. A. NematbakhshSemantic web has been one of the most important research areas of computer science in recent years. The concept of ontology as one of the most elements of semantic web is used to formally describe the domain knowledge and to enable the reasoning capability. Semantic web MoreSemantic web has been one of the most important research areas of computer science in recent years. The concept of ontology as one of the most elements of semantic web is used to formally describe the domain knowledge and to enable the reasoning capability. Semantic web is a distributed system and ontologies may be developed on many different nodes, so centralized reasoning is very hard or even impossible in many cases. On the other hand, since the majority of information in semantic web is uncertain, considering the notion of uncertainty in ontological reasoning is crucial. In this paper a method for distributed reasoning in uncertain ontologies is proposed. For this purpose the distributed description logic (DDL) framework and the certainty theory are considered for distributed reasoning and modeling the uncertainty respectively. To evaluate the functionality and performance of the algorithm, we developed a case study on application of the proposed method in purifying the mappings between ontologies. The results show that our algorithm makes the mappings more precise than other similar methods. Manuscript profile -
Open Access Article
242 - A New Statistical Characteristics Based Method for Adaptive Learning Rate Adjustment in Learning Automata
M. R. Mollakhalili Meybodi M. R. MeybodiThe value of learning rate and its change mechanisms is one of the issues in designing learning systems such as learning automata. In most cases a time-based reduction function is used to adjust the learning rate aim at reaching stability in training system. So the lear MoreThe value of learning rate and its change mechanisms is one of the issues in designing learning systems such as learning automata. In most cases a time-based reduction function is used to adjust the learning rate aim at reaching stability in training system. So the learning rate is a parameter that determines to what extent a learning system is based on past experiences, and the impact of current events on it. This method is efficient but does not properly function in dynamic and non-stationary environments. In this paper, a new method for adaptive learning rate adjustment in learning automata is proposed. In this method, in addition to the length of time to learn, some statistical characteristics of actions probability vector of Learning Automata are used to determine the increase or decrease of learning rate. Furthermore, unlike existing methods, during the process of learning, both increase and decrease of the learning rate is done and Learning Automata responds effectively to changes in the dynamic random environment. Empirical studies show that the proposed method has more flexibility in compatibility to the non-stationary dynamic environments and get out of local maximum points and the learned values are closer to the true values. Manuscript profile -
Open Access Article
243 - Unsupervised Image Clustering Using Central Force Optimization Algorithm Unsupervised Image Clustering Using Central Force Optimization Algorithm
M. H. Mozafari Maref Seyed-Hamid ZahiriCentral Force Optimization (CFO) is a new member of heuristic algorithms which has been recently proposed and added to swarm intelligence algorithms. In this paper, an effective unsupervised image clustering technique is proposed, using CFO and called CFO-clustering. In MoreCentral Force Optimization (CFO) is a new member of heuristic algorithms which has been recently proposed and added to swarm intelligence algorithms. In this paper, an effective unsupervised image clustering technique is proposed, using CFO and called CFO-clustering. In the presented method, each probe includes the information of center of the clusters, and fitness function contains both inter-distance and intra-distance of the samples. Extensive experimental results show that the proposed CFO-clustering outperforms other similar clustering algorithms which were designed based on the evolutionary techniques. Manuscript profile -
Open Access Article
244 - Increment of Distributed Generation Penetration in Distribution Networks Using simultaneous Placement of Distributed Generation Resources and Energy Storage Systems
N. Biabani M. Ramezani H. FalaghiIn addition to the great benefits of distributed generation (DG) resources to power systems, there are some disadvantages. In spite of some benefits like decrease of received power from transmission grid, increment of DGs penetration can lead to voltage increase in dist MoreIn addition to the great benefits of distributed generation (DG) resources to power systems, there are some disadvantages. In spite of some benefits like decrease of received power from transmission grid, increment of DGs penetration can lead to voltage increase in distribution networks during off peak. Hence the recent efforts have been made to handle problems to increase the penetration of these resources. The use of energy storage systems (ESSs) is one of the ways to prevent defects may arise from use of DGs in power systems and can help to increase penetration of DGs in power systems. ESSs can save energy during off peak and deliver it to the network in peak hours; hence, these equipment can reduce power losses and prevent voltage deviation during off peak by increasing load due to ESS charging. In this paper, first DG allocation and ESS placement are introduced then simultaneous placement of DG and ESS to reduce power losses in the distribution network are described. The proposed models are solved using genetic algorithm as optimization tool. The obtained results show that simultaneous placement could increase DG penetration compared to the separate allocation of these devices and pro Manuscript profile -
Open Access Article
245 - Modeling the Effects of Demand Response on Generation Expansion Planning in Restructured Power Systems
M. Samadi M. H. Javidi M. S. GhazizadehDemand response is becoming a promising subject in operation of restructured power systems. As a result, recently more attention is paid to demand response programs. Customers can contribute in operation of power systems by deployment demand response. The growth of cust MoreDemand response is becoming a promising subject in operation of restructured power systems. As a result, recently more attention is paid to demand response programs. Customers can contribute in operation of power systems by deployment demand response. The growth of customers’ participation in such programs may affect planning of power systems. Therefore, it seems necessary to consider the effects of demand response in planning approaches. In this paper, the impact of demand responsiveness on decision making in generation expansion planning is modeled. Then, avoidance or deferment in installation of new generating units is comprehensively investigated and evaluated by introducing a new simple index. In addition, changes in investment cost and total cost paid by customers are investigated. The effects of demand responsiveness are studied from both the customers’ and generation companies (Gencos) points of view. The proposed model has been applied to modified IEEE 30-bus system and the results are discussed. Manuscript profile -
Open Access Article
246 - Reliability Insurance Contract as a New Method for Reliability Adjustment in Electrical Distribution Network
S. M. AbediSeveral regulation schemes such as Rate of Return (ROR) and Price Cap (PC) lack incentives for efficient investment. ROR lead to overinvestment and PC on the other hand lead to underinvestment. Regulator employs various forms of reward/penalty schemes (RPS) to cover inh MoreSeveral regulation schemes such as Rate of Return (ROR) and Price Cap (PC) lack incentives for efficient investment. ROR lead to overinvestment and PC on the other hand lead to underinvestment. Regulator employs various forms of reward/penalty schemes (RPS) to cover inherent weaknesses in PC. Adding RPS allow utilities to make cost effective reliability improvements in response to changes in technology and costs but since this schemes result in consumers purchasing reliability and delivery as a single, optimal level of investment can’t be insured. To solve this problem, in the recent year, the Reliability Insurance Scheme (RIS) has been introduced which through it the reliability and delivery services are unbundled and so the efficient investment is insured. In this paper, firstly, the investment structure under RIS is compared to that of traditional regulatory schemes and, according to this comparison; the advantages of RIS are illustrated. In the second step, under RIS, the effects of free-riding and investment delay on the investment dynamics are evaluated and finally the centralized method for alleviating these effects is proposed. Manuscript profile -
Open Access Article
247 - Determination of a New Model for Investigating Ultra-Saturation Phenomenon during the Enegization of the Loaded Three-Phase Power Transformer and Its Effect on Differential Protection
B. Noshad M. Razaz S. Gh. SeifossadatOne of the mal-operation of the power transformer differential protection that may occur during the energization of a loaded power transformer is the ultra-saturation phenomenon. In this paper, a new model to study the ultra-saturation phenomenon during the energizaton MoreOne of the mal-operation of the power transformer differential protection that may occur during the energization of a loaded power transformer is the ultra-saturation phenomenon. In this paper, a new model to study the ultra-saturation phenomenon during the energizaton of a loaded three-phase power transformer is presented and its effect on the differential protection of the power transformer is considered. For modeling of the ultra-saturation phenomenon, the nonlinear characteristic of the transformer core and the saturation effect of current transformers are considered. It is assumed that the load of the power transformer is a resistive and an inductive load. The mal-operation of the differential protection depends on a variety of factors the most important parameters of which are inception angle and residual flux. In this paper the parameters mentioned will study in different cases. In this paper, simulation is done by MATLAB program. Manuscript profile -
Open Access Article
248 - Design and Application of Parallel Four-Leg Inverters Sharing Nonlinear and Unbalance Loads
M. Hosseinpour M. Mohamadian A. Yazdian VarjaniThis paper investigates the performance of four-leg parallel inverters sharing unbalanced and nonlinear loads. An inner current and external voltage control loops are considered to control the parallel four-leg inverters. In this paper, a proportional controller for the MoreThis paper investigates the performance of four-leg parallel inverters sharing unbalanced and nonlinear loads. An inner current and external voltage control loops are considered to control the parallel four-leg inverters. In this paper, a proportional controller for the current internal loop as well as a proportional-resonant one for the voltage external loop are considered to support the proper performance of the system. The proposed system is able to feed balanced, unbalanced, and nonlinear loads and provides an appropriate sinusoidal voltage waveform for loads by accurately sharing power between the parallel inverters. Simulation results verify the accurate and proper performance of the proposed system. Manuscript profile -
Open Access Article
249 - Modeling and Simulation of Electric Arc for SF6 Circuit Breaker Using MHD Equations
D. Azizi M. R. Alizadeh Pahlavani Ahmad GholamiIn this paper, a dynamic arc model based on MHD (Magneto Hydro Dynamic) equations for a high voltage (HV) SF6 interrupter has been investigated and analyzed. Moreover, for simulating the insulating performance and interrupting characteristics of the SF6 interrupter, dyn MoreIn this paper, a dynamic arc model based on MHD (Magneto Hydro Dynamic) equations for a high voltage (HV) SF6 interrupter has been investigated and analyzed. Moreover, for simulating the insulating performance and interrupting characteristics of the SF6 interrupter, dynamic variation of the arc, such as arc moving in the presence of Lorentz force have been established, and the compressibility and viscosity of SF6 gas in the whole interrupting course has been taken into consideration. The mass-fraction equation is introduced to the model on the basis of traditional mass, momentum, and energy-balance equations. The distributions of temperature field, pressure field, and mass fraction in the arc chamber are calculated. Manuscript profile -
Open Access Article
250 - Capacitor-Free CMOS Low-Dropout Regulator with a Fast Path Embedded into the Error Amplifier
R. Fathipour A. SaberkariIn this paper, a CMOS output-capacitor-free low-dropout regulator (LDO) is presented in which a capacitor multiplier based on a current-mode amplifier is embedded into the error amplifier to enhance the dynamic specifications to load variations, pole splitting, and simu MoreIn this paper, a CMOS output-capacitor-free low-dropout regulator (LDO) is presented in which a capacitor multiplier based on a current-mode amplifier is embedded into the error amplifier to enhance the dynamic specifications to load variations, pole splitting, and simultaneously power saving. The proposed LDO topology is designed and simulated in HSPICE in a 0.35 µm CMOS process to provide a 1.8 V output voltage with a 200 mV dropout for a wide range output current between 0-100 mA while its quiescent current is 22 µA. In order to have a fair conclusion, the article reveals a FOM-based comparison with other reported designs. Manuscript profile -
Open Access Article
251 - Automated Implementation of Quantum Circuits on QFPGA for Emulation
M. Heidarzadeh Mohammad Danaee FarThis paper defines an optimal architecture for the FPGA using exact methods. In order to achieve this goal, optimal placement and routing solutions are found using the integer linear programming techniques. After redefining the internal architecture of the logic blocks, MoreThis paper defines an optimal architecture for the FPGA using exact methods. In order to achieve this goal, optimal placement and routing solutions are found using the integer linear programming techniques. After redefining the internal architecture of the logic blocks, quantum circuits are partitioned by a heuristic algorithm in order to reach maximum utilization of the resources inside logic blocks and minimum delay of the paths traversed by the q-bits in the circuit. Experimental results show that FPGA architecture modifications can result in the reduction of the delay of critical paths of circuits by up to half in some cases and in a considerable reduction of the number of channels used for routing. Furthermore, the results show that defining the logic blocks with 12 q-bits instead of 4 q-bits can decrease circuits delay and the number of used channels to a large extent. Manuscript profile -
Open Access Article
252 - Phrase Segmentation on Persian Texts Using Neural Networks
M. M. Mirdamadi A. M. Zareh Bidoki M. RezaeianWord and phrase segmentation is one of the main activities in natural languages processing (NLP). Many programs in NLP need to be preprocessed for extraction of text’s words and distinction phrases. Getting meaningful words with their prefix and suffix is the main and t MoreWord and phrase segmentation is one of the main activities in natural languages processing (NLP). Many programs in NLP need to be preprocessed for extraction of text’s words and distinction phrases. Getting meaningful words with their prefix and suffix is the main and the final goal of segmentation. This activity depends on various natural languages can be easy or hard. Persian is among the languages with complex preprocessing tasks. One of the complexity sources is handling different writing scripts. In written Persian texts, we have two kinds of spaces: short space and white space. Also there are various scripts for writing Persian texts, differing in the style of writing words, using or elimination of spaces within or between words, using various forms of characters and so on. In this paper, we want to suggest a statistical method for phrase segmentation on Persian texts using neural networks due to using in search engines. For this purpose, we use occurrence likelihood of uniwords and biwords in corpus. The suggested algorithm includes four steps and could detect about 89.6% of correct tokens. Experimental results show this method can improve the performance of the usual methods Manuscript profile -
Open Access Article
253 - Sub-Word Image Clustering in Old Printed Documents Using Template Matching
M. R. Soheili E. KabirDue to the rapid growth of digital libraries, digitizing large documents has become an important topic. In a quite long book, similar characters, sub-words and words will occur many times. In this paper, we propose a sub-word image clustering method for the applications MoreDue to the rapid growth of digital libraries, digitizing large documents has become an important topic. In a quite long book, similar characters, sub-words and words will occur many times. In this paper, we propose a sub-word image clustering method for the applications dealing with large uniform documents. We assumed that the whole document is printed in a single font and print quality is not good. To test our method, we created a dataset of all sub-words of a Farsi book. The book has 233 pages with more than 111000 sub-words manually labeled. We use an incremental clustering algorithm. Four simple features are extracted from each sub-word and compared with the corresponding features of each cluster center. If all features' differences lie within certain thresholds, the sub-word and the winner cluster center are finely compared using a template matching algorithm. In our experiments, we show that all sub-words of the book are recognized with more than 99.7% accuracy by assigning the label of each cluster center to all of its members. Manuscript profile -
Open Access Article
254 - Semi-Partitioning Multiprocessor Real-Time Scheduling in Data Stream Management Systems
M. Alemi M. HaghjooIn data stream management systems as long as streams of data arrive to the system, stored queries are executed on these data. Regarding high workload, high processing capacity is required, leading to consider multiple processors to cope with it. Partitioning approach, o MoreIn data stream management systems as long as streams of data arrive to the system, stored queries are executed on these data. Regarding high workload, high processing capacity is required, leading to consider multiple processors to cope with it. Partitioning approach, one of the main methods in multiprocessor real-time scheduling, bind each query to one of processors based on its utilization, ratio of estimated execution time to period, and instances of each query which should be completed under defined deadline can only be executed on specified processor. Each query which could not be assigned to any processor can be split based on utilization of processors and spread among them, causing to get closer to optimum result. This system has been examined with real network data, showing lower miss ratio and higher utilization in comparison to simple partitioning approach. Manuscript profile -
Open Access Article
255 - Persian Handwritten Word Recognition by Log-Polar Transform and Hidden Markov Model
Q. Nadalinia Charei K. Yaghmaie H. Fazlollahi Aghamalek S. M. RazaviIn this paper a recognition system for Persian words is introduced which utilizes the local higher order of the log-polar image autocorrelation for feature extraction of Persian sub-words. This feature extraction technique brings up leads to a system robustness in cases MoreIn this paper a recognition system for Persian words is introduced which utilizes the local higher order of the log-polar image autocorrelation for feature extraction of Persian sub-words. This feature extraction technique brings up leads to a system robustness in cases of writing variations alteration like scaled or rotated handwritings. Also using the log-polar transform, the sub-word image sampling will be performed so that most of acquired samples will be centered in a certain area. The proposed method uses the discrete Hidden Markov’s Model (HMM) as a classifier. Furthermore a net of dictionaries were employed to increase the reliability and precision of the system output. Finally, the Iran-Shahr database is utilized to evaluate the system performance. Comparing the results of the proposed method and other previous methods, proves that a less sensitivity has been achieved by the proposed method about handwriting variations. Manuscript profile -
Open Access Article
256 - Visual Target Tracking Using Geometrical Particle Filter and Analytic Color-Based Histogram Model
N. Ghasemi P. Moallem M. F. SabahiColor is an important feature to describe object in visual tracking. Color-based histogram is used to model the object properly and Bhattacharya distance is also used to measure the error between reference and candidate histogram. Particles filter estimate position of t MoreColor is an important feature to describe object in visual tracking. Color-based histogram is used to model the object properly and Bhattacharya distance is also used to measure the error between reference and candidate histogram. Particles filter estimate position of target while two-dimension affine transformation is used as state of the system. Considering geometric properties of affine transformation as affine group cause two-dimensional mapping of the object to be closer to the real three-dimensional model. Approximation of optimal importance function of particles filter is obtained from Taylor expansion of Bhattacharya distance. Experiments show the accuracy and stability of the proposed tracker for fast and complex movement of a color target versus the gray level geometric particle filtering algorithm. Manuscript profile -
Open Access Article
257 - Detection of Shaded Areas Boundary in Intravascular Ultrasound Images Using Active Contour
M. Basij M. Yazdchi P. Moallem A. TakiIntra vascular imaging is used for extracting more accurate information about the size and characteristics of plaques than coronary angiography. Sometimes shadows appear behind the calcification plaques that it makes some problem to process these images automatically. T MoreIntra vascular imaging is used for extracting more accurate information about the size and characteristics of plaques than coronary angiography. Sometimes shadows appear behind the calcification plaques that it makes some problem to process these images automatically. This paper describes a new approach for shadows region and border detection in Intra Vascular Ultrasound images. In the proposed algorithm, Otsu thresholding is utilized for identification of shadows location and the Active contours without edge is used for shadows border detection. According to experiments conducted on 30 samples, this proposed algorithm can able to detect shadow regions correctly with sensitivity of 86%. Manuscript profile -
Open Access Article
258 - A New Scheme for Automatic Classification of Power Quality Disturbances Based on Signal Processing and Machine Learning
M. Hajian A. Akbari ForodIdentification and classification of power quality disturbances (PQDs) are one of the most important functions of monitoring and protection of modern power systems. One of the most important issues in PQ analysis is automatic diagnosis of waveforms using an effective al MoreIdentification and classification of power quality disturbances (PQDs) are one of the most important functions of monitoring and protection of modern power systems. One of the most important issues in PQ analysis is automatic diagnosis of waveforms using an effective algorithm. This paper presents an effective method, for extracting features, using integration of discrete wavelet transform (DWT) and hyperbolic S transform (HST). Moreover, an efficient feature selection method namely Orthogonal Forward Selection (OFS) by incorporating Gram Schmidt (GS) procedure and forward selection is applied for selection of the best subset features. Multi support vector machines (MSVM), as famous classifier, is applied. Also, the variable parameters of the classifier are optimized using a powerful method namely particle swarm optimization (PSO). Six single disturbances and two complex disturbances as well pure sine (normal) selected as reference are considered for the classification. Sensitivity of the proposed expert system under different noisy conditions is investigated. Also, efficiency of the proposed methods by comparing the results of this study with the results of other papers is examined. Manuscript profile -
Open Access Article
259 - The Probabilistic Small Signal Stability Analysis and Coordinate Tuning of PSSs and TCSC in the Power System with Considering the Wind Farm Generation Uncertainty
H. Ahmadi H. SeifiWith the decreasing of the fossil fuels and increasing of the environmental pollution, using of renewable energy resources is growing rapidly. On the other hand, the restructured electricity industry causes to cooperation of the distributed generation resources in the c MoreWith the decreasing of the fossil fuels and increasing of the environmental pollution, using of renewable energy resources is growing rapidly. On the other hand, the restructured electricity industry causes to cooperation of the distributed generation resources in the competitive electricity market. In such situation, the presence of the wind farms in the power system in order to provide the system loads is quite favorable. However, wind farm generation depends on the wind speed and the uncertainty in the generation cause to some concerns about the connection and operation of the power system. So, in this paper, a probabilistic approach for small signal stability analysis with considering the wind farm generation uncertainty based on PCM method is proposed. The PCM method is based on the orthogonal polynomials which provide a linear model for desired output. The continuous changes of the wind farm generation level cause to variation on the operating point that the control equipment parameters should be adjusted based on the new operation conditions. Therefore, genetic algorithm and the approximate models which are obtained from the PCM method are used. In order to validate the proposed method, the IEEE 10-machine and IEEE 16-machine test system are used. Manuscript profile -
Open Access Article
260 - Lifetime Improvement of Real-Time Embedded Systems by Battery-Aware Scheduling
S. Manoochehri kargahi kargahiMany embedded systems and mobile devices use batteries as their energy suppliers. The lifetime of these devices is thus dependent on the battery behavior. Accordingly, battery management besides reducing the energy consumption of the respective system helps to increase MoreMany embedded systems and mobile devices use batteries as their energy suppliers. The lifetime of these devices is thus dependent on the battery behavior. Accordingly, battery management besides reducing the energy consumption of the respective system helps to increase the efficiency of such systems. Maximizing the battery lifetime is a quiet challenging problem due to the nonlinear behavior of batteries and its dependence on the characteristics of the discharge profile. This paper employs dynamic voltage scaling (DVS) to extend the lifetime of battery-operated real-time embedded systems. We propose a battery-aware scheduling algorithm to maximize the lifetime and efficiency of the battery. The proposed algorithm is based on greedy heuristics suggested by battery characteristic and power consumption of tasks to employs DVS. Two methods are used to evaluate the mentioned algorithms; the first one is based on the cost function derived from a high-level analytical model of battery, and the second one is based on Dualfoil, a low-level li-ion battery simulator. Experimental results show that the system lifetime can be increased about 4.3% to 19.6%in various situations (in terms of system workload and tasks power consumption). Manuscript profile -
Open Access Article
261 - Reconfiguration of Distribution Network in Deregulated Environment in the Presence of DGs
B. Arandian R. Hooshmand E. GholipourDistribution system companies (DISCOs) can reduce their cost by reconfiguration as the economic way for loss reduction. This paper presents a new method for reducing DISCO costs in deregulated environment by loss reduction and power generation control of Distributed Gen MoreDistribution system companies (DISCOs) can reduce their cost by reconfiguration as the economic way for loss reduction. This paper presents a new method for reducing DISCO costs in deregulated environment by loss reduction and power generation control of Distributed Generators (DGs). Because of changing the price of energy in this environment, different network load levels with different prices were considered. This complex optimization problem is solved by a new method based on shuffled frog leaping algorithm (SFLA). Also, influence of DG presence on objective function and load flow is considered. The proposed method is applied to IEEE 33-bus and 69-bus test systems to decrease the activity cost of DISCO in deregulated environment and its capability relative to other methods is shown. Manuscript profile -
Open Access Article
262 - Ring Resonator-Based Monolithic Integrated Optical Transceiver
M. Kari M. NikoufardIn this article, we designed a novel monolithic integrated optical transceiver based on the ring resonator structure on semi-insulating InP substrate at 1.55 μm wavelength. To separate the incoming continuous (λ2) and modulated (λ1) optical waves from the network, an op MoreIn this article, we designed a novel monolithic integrated optical transceiver based on the ring resonator structure on semi-insulating InP substrate at 1.55 μm wavelength. To separate the incoming continuous (λ2) and modulated (λ1) optical waves from the network, an optical ring resonator is utilized. The ring resonator has the p-i-n layer stack that also detects the incoming modulated optical wave (λ1). The continuous optical wave (λ2) is guided to the ring-resonator based modulator where it is modulated and finally directed toward a pair of ring resonator to reflected back to the network. Channel spacing between λ1 and λ2 is 200 GHz (1.6 nm) at wavelength ranges of 1520 to 1570 nm. This transceiver can illustrate a 40 GHz bandwidth. Manuscript profile -
Open Access Article
263 - Insurance Contract for the Transfer of Electrical Energy, an Incentive Method to Improve the Reliability
A. Khandani A. Akbari ForodIn competitive electricity market, maximizing the profit is the main objective in company’s decision making. Hence, Transmission companies (Trans Cos) are not interested in improving reliability and expanding existing structures without financial benefits. On the other MoreIn competitive electricity market, maximizing the profit is the main objective in company’s decision making. Hence, Transmission companies (Trans Cos) are not interested in improving reliability and expanding existing structures without financial benefits. On the other hand, consumers demand more reliable and high quality power. In this paper, transmission insurance plan is proposed as an incentive method to improve the reliability of electrical power transmission. In this method, an insurance contract concluded between insurance company and every customer. Insurance company spend a part of its revenue to increases the reliability of the transmission system and also pays for compensation of consumers not supplied energies. The proposed method is studied in a network with six buses. Results show that the proposed method increases network reliability. Manuscript profile -
Open Access Article
264 - Transmission Switching Considering Ddynamic Constraints in Joint Energy and Spinning Reserve Market
رحمت اعظمیIn this paper a joint energy and reserve market with transmission switching considering dynamic constraints has been proposed to minimize the cost of supplying load, reliability expenses and avoidance of transient instability in line switching. Transmission switching i MoreIn this paper a joint energy and reserve market with transmission switching considering dynamic constraints has been proposed to minimize the cost of supplying load, reliability expenses and avoidance of transient instability in line switching. Transmission switching is used during contingencies and steady state to determine optimal required energy and reserve values. To investigate the efficiency of the proposed strategy IEEE 14 bus test is studied. According to the obtained results, this strategy decreases energy and reserve marginal prices, as well as reliability cost. Manuscript profile -
Open Access Article
265 - Using Prominent Regions in Search Space Reduction for Recognition of Printed Farsi Subwords
H. Davoudi E. KabirIn the most common Lexicon reduction methods, lexicon words are clustered based on their holistic shape features and then each query word image is classified into the closest cluster. As the errors at this stage propagate to the subsequent stages, relevant clusters shou MoreIn the most common Lexicon reduction methods, lexicon words are clustered based on their holistic shape features and then each query word image is classified into the closest cluster. As the errors at this stage propagate to the subsequent stages, relevant clusters should be selected with a high degree of accuracy. In this paper we present a novel verification method which decides on the validity of the recognized clusters based on a proposed confidence measure. The level of confidence to the selected clusters is measured using local shape features in the verification phase, where it is determined that the selected cluster is acceptable or not. For this purpose, some local shape features of the input subword image are compared to the “prominent regions” of the corresponding cluster. The prominent regions of a cluster are some local regions that discriminate the members of that cluster compared to the other clusters. The proposed verification method along with some predefined rules is used to reduce the lexicon size of Farsi subwords. The experiments conducted on a set of 6895 common Farsi subwords show that our proposed method significantly reduces the search space while preserving the accuracy in an acceptable rate. Manuscript profile -
Open Access Article
266 - A Hybrid Algorithm for Terrain Simplification
F. Dabaghi Zarandi Mohammad GhodsiTerrain simplification problem is one of fundamental problems in computational geometry and it has many applications in other fields such as geometric information systems, computer graphics, image processing. Terrain is commonly defined by a set of n points in three dim MoreTerrain simplification problem is one of fundamental problems in computational geometry and it has many applications in other fields such as geometric information systems, computer graphics, image processing. Terrain is commonly defined by a set of n points in three dimension space. Major goal of terrain simplification problem is removing some points of one terrain so that maximum error of simplified surface is a certain threshold. There are two optimization goals for this problem: (1) min-k, where for a given error threshold , the goal is to find a simplification with the minimum number of points for which the error is that most , and (2) min-, where for a given number n, the goal is to find a simplification of at most m points that has the minimum simplification error. Simplification problem is NP-hard in optimal case. In this paper we present a hybrid algorithm for terrain simplification that performs in three phases. First, terrain is divided to some clusters, then any cluster is simplified independently and finally, the simplified clusters are merged. Our algorithm solves the problem in . The proposed algorithm is implemented and verified by experiments. Manuscript profile -
Open Access Article
267 - Left Ventricular Segmentation in Echocardiography Images by Manifold Learning and Dynamic Directed Vector Field Convolution
N. Mashhadi H. Behnam Ahmad Shalbaf Z. Alizadeh SaniCardiac diseases are the major causes of death throughout the world. The study of left ventricular (LV) function is very important in the diagnosis of heart diseases. Automatic tracking of the boundaries of the LV wall during a cardiac cycle is used for quantification o MoreCardiac diseases are the major causes of death throughout the world. The study of left ventricular (LV) function is very important in the diagnosis of heart diseases. Automatic tracking of the boundaries of the LV wall during a cardiac cycle is used for quantification of LV myocardial function in order to diagnose various heart diseases including ischemic disease. In this paper, a new automatic method for segmentation of the LV in echocardiography images of one cardiac cycle by combination of manifold learning and active contour based dynamic directed vector field convolution (DDVFC) is proposed. In this method, first echocardiography images of one cardiac cycle have been embedded in a two dimensional (2-D) space using one of the most popular manifold learning algorithms named Locally Linear Embeddings. In this new space, relationship between these images is well represented. Then, segmentation of the LV wall during a cardiac cycle is done using active contour based DDVFC. In this method, final contour of each segmented frame is used as the initial contour of the next frame. In addition, in order to increase the accuracy of the LV segmentation and also prevent the boundary distortion, maximum range of the active contour motion is limited by Euclidean distances between consequent frames in resultant 2-D manifold. To quantitatively evaluate the proposed method, echoacardiography images of 5 healthy volunteers and 4 patients are used. The results obtained by our method are quantitatively compared to those obtained manually by the highly experienced echocardiographer (gold standard) which depicts the high accuracy of the presented method. Manuscript profile -
Open Access Article
268 - Color Reduction of Hand-painted Carpet Patterns Before Discretization
M. Fateh E. KabirCarpet patterns are in two categories: machine-painted and hand-painted. Hand-painted patterns are divided into two groups: before and after discretization. The purpose of this study is color reduction of hand-painted patterns before discretization. There are some artic MoreCarpet patterns are in two categories: machine-painted and hand-painted. Hand-painted patterns are divided into two groups: before and after discretization. The purpose of this study is color reduction of hand-painted patterns before discretization. There are some articles about color reduction of hand-painted carpet patterns after discretization, but so far, there is not an article on patterns before discretization. The proposed algorithm consists of the following steps: image segmentation, finding the color of each region, color reduction around the edges and final color reduction with C-means. For 80 segments of different 20 patterns, the algorithm has an approximate of 96% accuracy. In other words, the colors of 96% of image pixels are found correctly. The high accuracy of this method is due to its fitness to the application. The proposed method is not fully automatic and requires the total number of colors as its input. Manuscript profile -
Open Access Article
269 - The Effects of SIP Register Flood Attack and Detection by Using Kullback–Leibler Distance
S. R. Chogan M. Fathy M. RamezaniVoice communications through internet uses VOIP which includes several protocols while its secrecy is very important issue. SIP is the most important signaling protocol whose attack detection may help system immunization. This paper is dedicated to the issue of SIP regi MoreVoice communications through internet uses VOIP which includes several protocols while its secrecy is very important issue. SIP is the most important signaling protocol whose attack detection may help system immunization. This paper is dedicated to the issue of SIP registration flood attacks. Attackers can send registration signals which have several dangers for registration server. In this paper, SIP register flood attacks is investigated by details and the effects of attack over registration server is illustrated. Finally, the effects of attack, regarding the ratios compared with a regular situation of the network, are evaluated in experiments done in a real network. Moreover, instead of Hellinger distance, Kullback–Leibler distance is used for register flood attacks detection and corresponding ROC curves show this approach has better performance. Manuscript profile -
Open Access Article
270 - Sub-Threshold 8T SRAM Cell with Improved Write-Ability and Read Stability
Gh. Pasandi S. M. FakhraieConventional 6T SRAM cell suffers from poor write-ability and poor read stability at low supply voltages. In this paper a new 8T SRAM cell is proposed that achieves improved write-ability and increased read stability at the same time. The proposed SRAM cell can successf MoreConventional 6T SRAM cell suffers from poor write-ability and poor read stability at low supply voltages. In this paper a new 8T SRAM cell is proposed that achieves improved write-ability and increased read stability at the same time. The proposed SRAM cell can successfully operate at small supply voltages as low as 275 mV whereas conventional 6T SRAM cell cannot. To show the prominence of the proposed cell and for better comparison, our SRAM cell, conventional 6T SRAM cell, and also three other SRAM cells from recent literature are designed in a 90nm industrial CMOS technology with the same conditions. Simulation results show that the proposed 8T SRAM cell decreases write and read delays by 47.5% and 50%, respectively at supply voltage of 800 mV. Our SRAM cell also improves power consumption for single write operation by 40% over the best design at supply voltage of 800 mV. Among the five designs compared, our design is the only one that operates at supply voltages as low as 275 mV. Finally, layout of the proposed SRAM cell is developed in 180 nm industrial CMOS technology and results of post-layout simulations are discussed. Manuscript profile -
Open Access Article
271 - Throughput Optimization in a Broadcast Network Using Adaptive Modulation, Coding and Transmit Power Provisioning Security Constraint
M. TakiA new transmission scheme is presented to improve utilization of resource in a broadcast network provisioning physical layer security. In the designed scheme, data of each user is only detectable at its corresponding receiver with a proper bit error rate (BER), while de MoreA new transmission scheme is presented to improve utilization of resource in a broadcast network provisioning physical layer security. In the designed scheme, data of each user is only detectable at its corresponding receiver with a proper bit error rate (BER), while detection BER at other unintended receivers is high enough for improper detection. Adaptive modulation, coding and transmit power is utilized based on the SNRs. Exact and approximate solutions for the formulated problem are presented where approximate solution has acceptable complexity and leads to the comparable results with the exact solution. Numerical evaluations show that a performance degradation is seen at the cost of providing security. Manuscript profile -
Open Access Article
272 - Select the Optimal Subset of LABP Features Based on CLA-EC Method in Face Recognition System
A. Hazrati Bishak K. Faez H. Barghi Jond S. GhateiIn this paper, we present a new efficient method based on local binary pattern descriptor, for face recognition. Because, the calculations in Local binary pattern are done between two pixels values, so, small changes in the binary pattern affect its performance. In this MoreIn this paper, we present a new efficient method based on local binary pattern descriptor, for face recognition. Because, the calculations in Local binary pattern are done between two pixels values, so, small changes in the binary pattern affect its performance. In this paper, a new local average binary pattern descriptor is presented based on cellular learning automata and evolutionary computation (CLA-EC). In the proposed method, first, the LABP operator are used to extract uniform local binary patterns from face images; it should be noted that, in LABP operator to obtain more robust feature representation, many sample points has been used. Then, the best subset of patterns found by CLA-EC methods, and the histogram of these patterns is obtained. Finally, support vector machine is used for classification. The results of experiment on FERET data base show the advantage of the proposed algorithm compared to other algorithms. Manuscript profile -
Open Access Article
273 - Spectral Shaping of Reconstruction Noise in Backward ADPCM Coding
قاسم علیپور محمدحسن ساوجیThe main idea in ADPCM coding is to remove the redundancies of the speech signal before quantization. One of the important characteristics of this coding scheme is the spectral flatness of the reconstruction noise in spite of its low level. It has been tried, in the pre MoreThe main idea in ADPCM coding is to remove the redundancies of the speech signal before quantization. One of the important characteristics of this coding scheme is the spectral flatness of the reconstruction noise in spite of its low level. It has been tried, in the present research, to improve the perceptual quality of the reconstructed signal by shaping the spectrum of the reconstruction noise using an all-zero filter in the backward ADPCM coding. By doing so, a useful compromise is achieved between the level and the spectral shape of the reconstruction noise. The obtained results show an improvement in the perceptual quality of the reconstructed signal (higher PESQ score) and an increase in the noise level (lower SNR). Manuscript profile -
Open Access Article
274 - Modeling, Assessment and Improvement of Demand and Supply Side Uncertainties in Long-term Dynamics of Power Markets
E. Khorram H. Seifi Mohammad Kazem Sheikh El EslamiIn this paper, the long-term dynamics of an electricity market is modeled, considering the load uncertainty. Moreover, the generation side uncertainties, including the uncertainties of the generators availabilities, the hydro generations and the wind generations are obs MoreIn this paper, the long-term dynamics of an electricity market is modeled, considering the load uncertainty. Moreover, the generation side uncertainties, including the uncertainties of the generators availabilities, the hydro generations and the wind generations are observed. The problem is analyzed by the System Dynamics (SD) method. Also, the effects of capacity payment on power market dynamics, with and without uncertainties, are modeled and analyzed. The simulation results show how the uncertainties may affect the long-term behavior of a power market. Moreover, it is shown how the effect of uncertainties on market dynamics, may be improved through capacity payment. Manuscript profile -
Open Access Article
275 - Composite Power System Reliability Modeling, Evaluation and Reliability-Based Analysis by Bayesian Networks
M. Eliassi H. SeifiBayesian Networks (BNs) as a strong framework for handling probabilistic events have been successfully applied in a variety of real-world problems, but they have received little attention in the area of composite power systems reliability assessment. Reliability assessm MoreBayesian Networks (BNs) as a strong framework for handling probabilistic events have been successfully applied in a variety of real-world problems, but they have received little attention in the area of composite power systems reliability assessment. Reliability assessment by BN provides some additional capabilities in comparison to conventional methods, both at the modeling and at the analysis levels. At the modeling level, several restrictive assumptions, implicit in the conventional methods, can be removed. At the analysis level, a variety of applicable reliability-based analysis which is hardly achievable in conventional methods, can be conveniently performed. This paper proposes a methodology based on Minimal Cutsets (MCs) to apply BNs to composite power system reliability modeling, reliability assessment and reliability-based analysis. To have a more accurate BN model, a new method of MC determination for composite power system is proposed. Bayesian structure is extracted, based on the determined MCs. Bayesian parameters are defined based on the logical relationships of nodes. To make the proposed method applicable to large composite power systems, virtual nodes are proposed and combined with Bayesian model. Also, a variety of reliability-based analyses are presented which are hardly achievable in conventional methods. The proposed method is validated by applying to RBTS and comparing the results with other reliability analysis methods. The proposed methodology is applied to the Reliability Test System (RTS), to show its feasibility in large networks. Manuscript profile -
Open Access Article
276 - Distributed Energy Resource Expansion Planning Considering Supporting Policies
A. Sheikhi Fini M. Parsa-Moghaddam Mohammad Kazem Sheikh El EslamiThis paper proposes a comprehensive framework for distributed energy resource (DER) expansion planning from investors’ viewpoint based on a combination of dynamic programming algorithm and game theory. In this framework, different aspects of DER planning i.e. their unce MoreThis paper proposes a comprehensive framework for distributed energy resource (DER) expansion planning from investors’ viewpoint based on a combination of dynamic programming algorithm and game theory. In this framework, different aspects of DER planning i.e. their uncertainties, risks, pollution, etc. are included. Wind turbines, gas engines and demand response (DR) programs are considered as DERs in this study. The intermittent nature and uncertainty of wind power generation and also uncertainty of demand response programs will cause the investors to consider risk in their investment decisions. In order to overcome this problem, a modified model has been derived to study the regulatory intervention impacts on wind expansion planning and implementing DR programs. Dynamic programming method is utilized for this problem solving and in each step, the Nash equilibrium point is calculated using Cournot model. A model based on intermittent nature of wind power generation and uncertainties of DR programs is developed which can calculate the optimal investment strategies. The effectiveness of the proposed model is proved through implementing on a test system. Manuscript profile -
Open Access Article
277 - A Framework for Congestion Management and Clearing of Energy and Reserve in Multiple Markets
A. Karimi Varkani H. Seifi Mohammad Kazem Sheikh El EslamiEnergy exchange among the electricity markets is a new issue in modern power systems. This issue, especially in Europe, has been identified as a market coupling. In this paper, a framework for congestion management and clearing of multiple electricity markets, in which MoreEnergy exchange among the electricity markets is a new issue in modern power systems. This issue, especially in Europe, has been identified as a market coupling. In this paper, a framework for congestion management and clearing of multiple electricity markets, in which the market participants can place their bids simultaneously in different markets across an interconnection, is proposed. In this framework, the markets dispatch the energy and the reserve, independently. A central coordinator entity, then, runs the allocation of transmission capacity among the electricity markets. Three methods for simultaneous clearing of the energy and reserve are also proposed. The possibility of implementation of the proposed methods in multiple markets is discussed. The numerical results for three-area 15-bus and IEEE RTS-96 test systems in a triple-market case are presented, to demonstrate the effectiveness of the proposed approach as compared with the other approaches. Manuscript profile -
Open Access Article
278 - A Control approach with Controllable Response Time for Power Control of the Power Electronic Based Distributed Generation Resources in Microgrids
E. Zare Abandankeshi مجید شهابیMost wind turbines, photovoltaic and fuel cells need a DC/AC converter as an interface for connection to the main grid. Power electronics based distributed generation resource has two parts: power circuit and control circuit of converter. In this paper, a new method whi MoreMost wind turbines, photovoltaic and fuel cells need a DC/AC converter as an interface for connection to the main grid. Power electronics based distributed generation resource has two parts: power circuit and control circuit of converter. In this paper, a new method which is based on current control by using internal model control method is presented, in order to control active and reactive power of power electronics interfaced distributed generation resource. The main benefit of using internal model control method is that it can reduce number of required parameters for PI controller tuning to one parameter which is desired closed-loop band width (). It should be mentioned that parameter can be computed regarding response rise time. Therefore, values of KI and KP can be determined with the selection of desired band width. So, the system can be designed just with the selection of one parameter (rise time tr). The proposed control method can be used in micro-grids containing power electronic interfaced DGs, in both modes of operation (connected to grid and islanded micro-grid). Manuscript profile -
Open Access Article
279 - Unity Power Factor MPPT for PMSG Wind Turbines Equipped with Matrix Converter
A. Nateghi H. Kazemi KaregarIn this paper, a new control method is proposed for extracting the maximum power of wind turbines equipped with Permanent Magnet Synchronous Generator (PMSG), which is connected to the grid via a matrix converter. The method calculates the optimal rotation speed of wind MoreIn this paper, a new control method is proposed for extracting the maximum power of wind turbines equipped with Permanent Magnet Synchronous Generator (PMSG), which is connected to the grid via a matrix converter. The method calculates the optimal rotation speed of wind turbine and finds the optimal operation point by hill climbing method. The proposed method is simple and it does not need to use some complex methods such as field oriented and rotor position estimation. Wind turbine speed, electrical torque and consequently maximum output power of wind turbine are obtained by the perfect control of output phases and amplitudes of matrix converter. Moreover, the maximum power is injected to the grid under unity power factor. The proposed method is simulated in MATLAB programming software and the obtained results approve the validity of the method. Manuscript profile -
Open Access Article
280 - Bandwidth and Gain Extension Technique for CMOS Distributed Amplifiers Using Negative Capacitance and Resistance Cell
seyed amin alavi E. Alavi Ahmad HakimiIn this paper, a new structure composed of a negative capacitance and resistance is presented in order to increase gain and bandwidth of distributed amplifiers. The proposed structure is used at the gate transmission line of the distributed amplifier and the obtained ci MoreIn this paper, a new structure composed of a negative capacitance and resistance is presented in order to increase gain and bandwidth of distributed amplifiers. The proposed structure is used at the gate transmission line of the distributed amplifier and the obtained circuit has been simulated using 0.13µm CMOS model. The negative capacitance at the gate transmission line decreases parasitic effects of gain cells and increases amplifier bandwidth and accordingly increases voltage gain. The generated negative resistance decreases transmission lines losses and increases bandwidth. Simulated voltage gain is 15dB with ±0.5 dB gain flatness over 0.5-49 GHz frequency band. Circuit input and output are matched with 50Ω resistance; and input and output return losses are -8.15 dB and -9.2 dB, respectively. This circuit has a noise figure less than 4.6 and its power consumption is 99 mW from 1.8 V power supply. Manuscript profile -
Open Access Article
281 - Designing an Adaptive Sliding-Mode Controller for Car Active Suspension System Using an Optimal logarithmic Sliding Surface
S. A. Zahiripour R. Tafaghodi A. A. Jalali S. K. Mousavi MashhadiIn this paper, a quarter car active suspension system with a hydraulic actuator, has been controlled by sliding mode coupled with an adaptive approach. To deal with all kinds of uncertainty arising from the effect of external perturbation or the any nonlinear behavior s MoreIn this paper, a quarter car active suspension system with a hydraulic actuator, has been controlled by sliding mode coupled with an adaptive approach. To deal with all kinds of uncertainty arising from the effect of external perturbation or the any nonlinear behavior system, sliding mode control has been used. In the proposed method the sliding surface, by using an optimal strategy to minimize the optimal cost function is derived, so the result is a logarithmic sliding surface. Adaptive algorithms proposed in this paper because of the nonlinear variability by time and not bounded uncertainty in the system. While the effects of parameter uncertainties and external disturbances to system performance have been dramatically reduced, the stability of control system proves based on the Lyapanof theory. The proposed control method has been done on a quarter car active suspension system with a hydraulic actuator. Simulation results of the proposed method show that the activation of suspension system by the proposed method increases its performance compare with the passive suspension system. Manuscript profile -
Open Access Article
282 - A Geometric Model for MIMO Channel with Distributed of Scatterers between the Base Station and the User
F. Zadeh-Parizi M. Mehrjoo J. ahmadi-ShokouhThe paper presents a geometry-based MIMO channel model for outdoor-to-indoor applications. The propagation channel model is derived when indoor scatterers are located on a hollow-disk around the user and a distribution of outdoor scatterers exists between the base stati MoreThe paper presents a geometry-based MIMO channel model for outdoor-to-indoor applications. The propagation channel model is derived when indoor scatterers are located on a hollow-disk around the user and a distribution of outdoor scatterers exists between the base station and the user. The closed-form Cross-Correlation Function (CCF) is derived for the aforementioned scenario. This function depends on various parameters of interest including the distance between the base station and the user, the spacing among antennas elements, and the directions of the antennas elements. The numerical CCF values are obtained with Radiowave Propagation Simulator (RPS) software for the building of Electrical and Computer Engineering School at the University of Sistan and Baluchestan. The results show that considering the outdoor scatterers increases the accuracy of the CCF and the capacity computation significantly. Manuscript profile -
Open Access Article
283 - A New eDLA-Based Framework for Finding Optimal Stochastic Sub-Graph
M. R. Mollakhalili Meybodi M. R. MeybodiIn this paper a new structure of learning automata which is called as extended distributed learning automata (eDLA) is introduced. A new eDLA-based iterative sampling method for finding optimal sub-graph in stochastic graphs is proposed. Some mathematical analysis of th MoreIn this paper a new structure of learning automata which is called as extended distributed learning automata (eDLA) is introduced. A new eDLA-based iterative sampling method for finding optimal sub-graph in stochastic graphs is proposed. Some mathematical analysis of the proposed algorithm is presented and the convergence property of the algorithm is studied. Our study shows that the proposed algorithm can be converge to the optimal sub-graph. Manuscript profile -
Open Access Article
284 - A Multi-Resolution Learning Based Method for Multimodal Medical Image Registration
S. S. Alehojat Khasmakhi M. R. KeyvanpourThe main purpose in various methods of image registration is to find the transformation parameters for accurate mapping an image onto another image coordinates. In medical sciences creating a precise mapping between medical images data is very important in application MoreThe main purpose in various methods of image registration is to find the transformation parameters for accurate mapping an image onto another image coordinates. In medical sciences creating a precise mapping between medical images data is very important in application such as diagnosis and treatment. Accordingly, several approaches have been proposed for image registration. The compression of results and performance between different image registration algorithms was the main motivation for this research to design and implement a new hybrid algorithm so that provide high accuracy in multimodal image registration. Automating the image registration process by using machine learning approach is the innovation of this method compared to previous ones. To this end, the proposed method which is named multi resolution learning is composed of multi resolution decomposition and a hierarchical neural network which it learn the transformation parameters by using global properties of the image and uses learned transformation parameter for image registration. The proposed method is implemented and tested on the medical images of Vanderbilt university database. Experiment result show acceptable accuracy for the proposed method compared with other methods. Manuscript profile -
Open Access Article
285 - Implementation of a Fuzzy Multi-Agent Model for City Evacuation Traffic Management Using Probabilistic Automata
A. R. Karbaschian Saeed Setayeshi arash SharifiBecause of importance of quickly city evacuation during natural or unnatural happenings, it’s essential to apply an optimized control policy to prevent congestion and stop of vehicles. Existing works for traffic management in critical conditions have paid little attenti MoreBecause of importance of quickly city evacuation during natural or unnatural happenings, it’s essential to apply an optimized control policy to prevent congestion and stop of vehicles. Existing works for traffic management in critical conditions have paid little attention to artificial intelligence approaches. Therefore, the main goal of authors in this research is offering an optimized and intelligent control policy for city evacuation traffic. This policy uses fuzzy inference system for decision making of each agent and probabilistic automata for optimizing performance of agents as for their preferences during time. To check degree of success of offered control policy, Agent Base Simulation in RStudio and Netlogo environments have been implemented using RNetlogo and frbs packages in R language. Simulation results show traffic load distribution, using maximum capacity of roads and congestion prevention by suggested policy. With regard to communication technologies such as GPS, smart phones, automatic tax payment systems in roads and … that have been developed in recent years, it is also possible to implement suggested critical traffic control policy in real world. Manuscript profile -
Open Access Article
286 - A New Extended Distributed Learning Automata-Based Algorithm for Parameter Learning of a Bayesian Network
M. R. Mollakhalili Meybodi M. R. MeybodiIn this paper a new learning automata-based algorithm is proposed for learning of parameters of a Bayesian network. For this purpose, a new team of learning automata which is called eDLA is used. In this paper the structure of Bayesian network is assumed to be fixed. Ne MoreIn this paper a new learning automata-based algorithm is proposed for learning of parameters of a Bayesian network. For this purpose, a new team of learning automata which is called eDLA is used. In this paper the structure of Bayesian network is assumed to be fixed. New arriving sample plays role of the random environment and the accuracy of the current parameters generates the random environment reinforcement signal. Linear algorithm is used to update the action selection probability of the automata. Another key issue in Bayesian networks is parameter learning under circumstances that new samples are incomplete. It is shown that new proposed method can be used in this situation. The experiments show that the accuracy of the proposed automata based algorithm is the same as the traditional enumerative methods such as EM. In addition to the online learning characteristics, the proposed algorithm is in accordance with the conditions in which the data are incomplete and due to the use of learning automaton, has a little computational overhead. Manuscript profile -
Open Access Article
287 - Introducing a New Version of Binary Ant Colony Algorithm to Solve the Problem of Feature Selection
S. Kashef H. Nezamabadi-pourThe use of metaheuristic algorithms is a good choice for solving optimization problems. In this paper, a novel feature selection algorithm based on Ant Colony Optimization (ACO), called Advanced Binary ACO (ABACO), is presented. This algorithm is an advanced version of MoreThe use of metaheuristic algorithms is a good choice for solving optimization problems. In this paper, a novel feature selection algorithm based on Ant Colony Optimization (ACO), called Advanced Binary ACO (ABACO), is presented. This algorithm is an advanced version of binary ant colony optimization, which attempts to solve the problems of ACO and BACO algorithms by combination of these two. The performance of proposed algorithm is compared to the performance of Binary Genetic Algorithm (BGA), Binary Particle Swarm Optimization (BPSO), and some prominent ACO-based algorithms on the task of feature selection on 12 well-known UCI datasets. Simulation results verify that the algorithm provides a suitable feature subset with good classification accuracy using a smaller feature set than competing feature selection methods. Manuscript profile -
Open Access Article
288 - Control of the Interference and Increasing Capacity by Creating a Phase Difference between the Signals Sent in LTE Network
H. Mirsalari N. NedaAccording to the entry of new networks such as LTE and WiMAX that is based OFDM in country, the need to research and evaluate the performance of these networks is inevitable. In this paper we investigated the performance of different frequency allocation schemes in an L MoreAccording to the entry of new networks such as LTE and WiMAX that is based OFDM in country, the need to research and evaluate the performance of these networks is inevitable. In this paper we investigated the performance of different frequency allocation schemes in an LTE network. We first introduced the frequency allocation schemes include Reuse-1, Reuse-3, partial frequency reuse, sectoring, cell division region and soft frequency reuse, and then by creating a phase difference between two signals in a MISO channel in standard LTE, and combine it with some of these schemes such as sectorization and cell division region with the sectoring interference will significantly decreased in such networks. The simulation results show that the phase differences between the signals(which it’s called the one pre-order scheme) in MISO channel, due to the rotation of the antenna radiation pattern depending on the position of mobile users, and also the soft frequency reuse scheme for the full allocation of OFDM carriers to each cell and sending with less power for users of the cell center, leads to the substantial gain in the total network capacity, under the different traffics. Manuscript profile -
Open Access Article
289 - A Secure Algorithm to Overcome Fingerprint Classification Problems
F. Mirzaei H. Ebrahimpour-Komleh M. BiglariFingerprint as a biometric has the most applications in verification and identification systems, because of its specific properties. In identification systems, input image is compared with all of images stored in the database. In huge databases, the comparison will take MoreFingerprint as a biometric has the most applications in verification and identification systems, because of its specific properties. In identification systems, input image is compared with all of images stored in the database. In huge databases, the comparison will take large amounts of time; Consider FBI databases, for instance. Image classification is one of the approved methods to increase the identification speed. Only one class is assigned to each fingerprint in tradition absolute classification. Various reasons like noise or lack of all the singularity points in captured region, cause the problem in determination of an absolute class for all the images. In this article, a new method based on probabilistic classification is presented. In the proposed approach, a set of classes are considered for each input image with a specific probability. These classes are searched in order of their probabilities priority in matching stage. Experiments on well-known FVC2002 database, exhibit the effect of probable classification clearly. Using only the second and third classes assigned by the proposed method, the identification system achieves about 18% increase in accuracy and 2-3 times speedup in compared to the traditional methods. Manuscript profile -
Open Access Article
290 - Topology Control in Wireless Sensor Networks Using Two-Level Fuzzy Logic
A. Abdi Seyedkolaei A. ZakerolhosseiniWireless sensor networks are a new generation of networks that from sensors uses to get information about itself environment and communication this sensors is as wireless. One of the issues that is very important in wireless sensor networks is Discussion reducing energy MoreWireless sensor networks are a new generation of networks that from sensors uses to get information about itself environment and communication this sensors is as wireless. One of the issues that is very important in wireless sensor networks is Discussion reducing energy consumption and increasing network lifetime. Topology control is one of the methods to reduce energy consumption and increase the lifetime of the network. Since different methods of topology control, to reduce energy consumption and enhance the network lifetime is proposed that including them is the clustering and one of the most famous clustering methods is LEACH. In this paper, we try to present a new clustering method that is superior compared to leach and other improved methods after the LEACH. we use in our clustering method from two-level fuzzy logic that be causing reduce energy consumption and increase the network lifetime compared to other methods and to prove the superiority of our method compared with other methods, we present a comparison using MATLAB software. Manuscript profile -
Open Access Article
291 - PLAER: Penalty Base Learning Automata for Energy Aware Routing in WSN
M. Parvizi Omran A. Moeni H. Haj Seyyed JavadiSensors in WSN work with batteries that have limited energy capacity. Therefore, reduction in power consumption is a very important issue. In this paper, we present a new routing algorithm to reduce power consumption in wireless sensor networks. This algorithm deploys L MoreSensors in WSN work with batteries that have limited energy capacity. Therefore, reduction in power consumption is a very important issue. In this paper, we present a new routing algorithm to reduce power consumption in wireless sensor networks. This algorithm deploys Learning automata in each node to find a suitable path for routing data packets. In order to aim this goal the algorithm uses penalty based approach in learning automata and considers energy level of nodes and latency of packet delivery as well. Performance of our new developed algorithm has been compared with LABER and BEAR protocols in OMNET++ simulator. Simulation results show that, in a network with static nodes, energy consumption and control packets reduce significantly and network lifetime increases in comparison with two other protocols. Manuscript profile -
Open Access Article
292 - Simulation of Electrical Fault in Stator Winding of Permanent Magnet Synchronous Motor and Discriminating It from Other Possible Electrical Faults Using Probabilistic Neural Network
M. Taghipour-gorjikolaie S. M. Razavi M. A. Shamsi-NejadOne of the most common electrical faults in Permanent Magnet Synchronous Motor (PMSM) is inter-turn fault in stator winding. At the incipient steps it seems not dangerous and so light, but spreading this fault can leads to irreparable Consequences. In this paper, the in MoreOne of the most common electrical faults in Permanent Magnet Synchronous Motor (PMSM) is inter-turn fault in stator winding. At the incipient steps it seems not dangerous and so light, but spreading this fault can leads to irreparable Consequences. In this paper, the intelligent system is presented to protect PMSMs from this kind fault. At the first, intelligent protection system determine the condition of the motor (which can be: Normal, Phase-phase short circuit, Open circuit and Inter-turn fault conditions). If the system determines the faults then send an alarm to operator and also if the fault is inter-turn, it can determine the damaged phase. Obtaining results show that Probabilistic Neural Network can be the most reliable and robust protection system for PMSMs against internal faults, especially inter-turn faults. Manuscript profile -
Open Access Article
293 - Simultaneous Implementation of Time of Use Demand Response and Security Constraint Unit Commitment
M. Kia M. Setayesh-Nazar S. M. SepasianThe growing need of energy sources especially in industrial countries and the shortage of the fossil resources cause a great concern in many countries. Considering that in some periods of the day the energy price is increased, Demand side management is one of the soluti MoreThe growing need of energy sources especially in industrial countries and the shortage of the fossil resources cause a great concern in many countries. Considering that in some periods of the day the energy price is increased, Demand side management is one of the solutions that is implemented. The major change in demand side management is consideration of consumers' response to energy price variations. This paper investigates the effect of demand response implementation on cost reduction in stochastic security constraint unit commitment. Uncertainties in power system such as transmission lines and power plants outage is considered in the paper Considering that the simultaneous implementation of stochastic security constraint unit commitment and demand response is a complex and nonlinear problem that contain Continuous and discrete variables, the mixed integer programming is being used. Proposed method is simulated in simple 3 bud system and IEEE RTS 24 bus system and the results analyzed in the paper. Manuscript profile -
Open Access Article
294 - Classical Direct Torque and Flux Control (DTFC) for Line-Start Permanent Magnet Synchronous and Its Comparison with Induction Motors During Voltage Sag Conditions
M. Hosseinzadeh A. SadoughiThis study compares Direct Torque Flux Control (DTFC) performance of a three-phase Induction Motor (IM) and its equal Line-Start Permanent Magnet Synchronous Motor (LSPMSM). Simulation results of line-starting DTFC method of an IM and its equal LSPMSM (for both normal a MoreThis study compares Direct Torque Flux Control (DTFC) performance of a three-phase Induction Motor (IM) and its equal Line-Start Permanent Magnet Synchronous Motor (LSPMSM). Simulation results of line-starting DTFC method of an IM and its equal LSPMSM (for both normal and voltage sag conditions) is compared and analyzed. In addition, field weakening region is evaluated. The advantages of the discussed control strategy over line-starting are also investigated for LSPMSM. Manuscript profile -
Open Access Article
295 - Design of Wide Area SVC Robust Controller for Damping Inter-Area Oscillations of a Power System
سعید اباذری A. Arab Dardori M. Barkhordari Yazdi M. S. PayamIncreasing power transfer capability of existing transmission lines is one of the key issues in the power systems. Inter-area oscillations have effect on the power transfer capability and decrease the network efficiency. On the other hand, FACTS devices can be used to i MoreIncreasing power transfer capability of existing transmission lines is one of the key issues in the power systems. Inter-area oscillations have effect on the power transfer capability and decrease the network efficiency. On the other hand, FACTS devices can be used to increase the power transfer capability by damping the inter-area oscillations. This paper proposes a Linear Matrix Inequality (LMI) based robust controller design to generate an additional stabilizing signal for a Static VAR Compensator (SVC) in order to increase damping of the inter-area modes. Wide Area Measurement (WAM) has been employed by the controller which is designed based on the H∞ mixed-sensitivity synthesis method. The effectiveness of the method is investigated by a test system consisting of 16 numbers of generators, 68 buses and 5 areas. The results show good and robust performance of the controller in damping the oscillations. Manuscript profile -
Open Access Article
296 - Optimization of the Dynamic Response and the Input Current THD for PFC Rectifier Based on Boost Converter Using SPEA and NSGA-II Algorithms
H. Abolhasani S. M. R. RafieiIn single-stage single-phase power factor correction converters, the time of dynamic response and input current THD are in conflict with each other. The main purpose of this paper is to improve the dynamic response of the converter along with reducing its input current MoreIn single-stage single-phase power factor correction converters, the time of dynamic response and input current THD are in conflict with each other. The main purpose of this paper is to improve the dynamic response of the converter along with reducing its input current THD. To achieve these goals, two multi-objective optimization methods based on evolutionary algorithms including; SPEA and NSGA-II were used to design a PI compensator coefficients in the indirect current control technique for PFC rectifier. The integral and fractional-order PI compensators were designed, respectively. The obtained results showed the superiority of the fractional-order PI compensator. To investigate the optimization problem, the dynamic response to changes in load and reference voltage was considered. The comparison between the optimization algorithms showed that each algorithm may have better performance than the other one according to the used objective functions. It means that neither had an absolute superiority. Manuscript profile -
Open Access Article
297 - Control of Grid-Connected Inverter in Stationary Reference Frame with Harmonic Compensation Capability
M. Shahparasti M. Mohamadian A. Yazdian VarjaniDue to increasing number of inverter based distributed generation resources in electric power systems, improving the quality and performance of them are necessary. In this paper a new current scheme is presented to inject sinusoidal current to the grid with following gr MoreDue to increasing number of inverter based distributed generation resources in electric power systems, improving the quality and performance of them are necessary. In this paper a new current scheme is presented to inject sinusoidal current to the grid with following grid voltage conditions: sinusoidal voltage, distorted voltage and unbalance voltage. The proposed control scheme includes two sections: 1) Determination of sinusoidal reference current considering grid voltage condition; 2) current controller to track reference current. The proposed reference current determination algorithm in comparison with other algorithms, such as Park method is implemented easier and has faster dynamic response. The proposed current controller is implemented in the stationary reference frame and does not require the use of multiple controllers and coordinate transforms to compensate the harmonics. This control strategy needs tuning of only one variable, hence compared with other control methods requires less computational burden for practical implementation. Simulation results confirm the effectiveness of the proposed control method. Manuscript profile -
Open Access Article
298 - Application of Epsilon Variable-Multi Objective Genetic Algorithm for Multi-Objective Optimal Power Flow with TCSC
E. Afzalan M. JoorabianThis paper ε-multi objective genetic algorithm variable (εV-MOGA) to optimize cost of generation, emission and active power transmission loss of flexible ac transmission systems (FACTS) device-equipped power systems. In the proposed approach, optimal power flow problem MoreThis paper ε-multi objective genetic algorithm variable (εV-MOGA) to optimize cost of generation, emission and active power transmission loss of flexible ac transmission systems (FACTS) device-equipped power systems. In the proposed approach, optimal power flow problem is formulated as a multi-objective optimization problem. FACTS devices considered include thyristor controlled series capacitor (TCSC). The proposed approach has been examined and tested on the modified IEEE 57-bus test system. The results obtained from the proposed approach have been compared with those obtained from nondominated sorting genetic algorithm-II, multi-objective differential evolution. Manuscript profile -
Open Access Article
299 - Design of a High-Voltage Unity Power Factor Charger Based on Bi-directional Boost Converter with Electromagnetic Compatibility Filter
A. Skandarnezhad S. A. AbrishamifarHigh voltage chargers are being used in the equipments such as electrical vehicles, uninterruptible power supplies and aircrafts. The converter introduced here is based on bi-directional boost topology. The output voltage of batteries set is larger than the input source MoreHigh voltage chargers are being used in the equipments such as electrical vehicles, uninterruptible power supplies and aircrafts. The converter introduced here is based on bi-directional boost topology. The output voltage of batteries set is larger than the input source voltage amplitude, and this converter can transfer the energy both from the source to the batteries bank and vice versa. Input source voltage is sine wave and the output voltage is DC. Both conversion of AC-to-DC and DC-to-DC is performed in one stage and the control scheme of switches is based on hysteric control method to achieve the unity power factor. One can use the electrical equations presented here to define the converter and EMC filter elements value. Finally, simulation results performed on a typical converter show the control method authenticity and effectiveness of the analyses presented here. Also some suggestion for the future works is proposed. Manuscript profile -
Open Access Article
300 - Wind Farm Layout Optimization with Emphasis on the Wake Effect
A. Farajipoor F. Faghihi R. SharifiConstruction of wind farms rise for wind energy capture as a renewable energy around the world. The purpose of wind farm layout optimization, absorb maximum energy from wind farms. In this paper, a new hybrid algorithm is presented to maximize the expected energy output MoreConstruction of wind farms rise for wind energy capture as a renewable energy around the world. The purpose of wind farm layout optimization, absorb maximum energy from wind farms. In this paper, a new hybrid algorithm is presented to maximize the expected energy output. Considerations of algorithm wake loss, which is based on wind turbine location and wind direction. The proposed model is illustrated with a scenario of the wind speed and its direction distribution of windy sites and is compared with ant colony algorithm and evolutionary strategy algorithm in six steps layout. The results show that the combination of ant colony algorithm and genetic algorithm performs better than existing strategies based on maximum values of the expected energy output and wake loss. Manuscript profile -
Open Access Article
301 - BER Analysis of Decode–Amplify-Forward Protocol with n-th Best Relay Selection in Multi-Relay Cooperative Networks
E. Olfat A. OlfatSpatial diversity is one of the most effective techniques to combat fading in wireless channels that can be implemented through antenna arrays. In this paper the hybrid decode-amplify-forward protocol with best relay selection (HDAF-S)in a cooperative system with multip MoreSpatial diversity is one of the most effective techniques to combat fading in wireless channels that can be implemented through antenna arrays. In this paper the hybrid decode-amplify-forward protocol with best relay selection (HDAF-S)in a cooperative system with multiple parallel relays with independent non-identically channels is considered and tight upper and lower bounds on bit error rate (BER) of this protocol is derived. It is shown that the BER of this protocol outperforms the BER of amplify and forward (AF) protocol but cannot exceeds the performance of decode and forward (DF) protocol. Then through asymptotic analysis for high SNR regime, it is shown that the HDAF-S protocol achieves full diversity order. Then the BER performance of HDAF protocol with n-th best relay selection (HDAF-nS) in independent and identically distributed channels is analyzed and tight upper and lower bounds on the BER are derived. Asymptotic analysis shows that this protocol cannot achieve full diversity order and it is shown that the diversity order decreases as n increases. The analytical results are validated through simulations. Manuscript profile -
Open Access Article
302 - Face Detection Using Gabor Filters and Neural Networks
M. Mahlouji R. MohammadianIn this paper, a robust method for face detection from different views using a combination of Gabor filters and neural networks is presented. First, a mathematical equation of Gabor filter is expressed. Then, by examining 75 different filter banks, range of effective pa MoreIn this paper, a robust method for face detection from different views using a combination of Gabor filters and neural networks is presented. First, a mathematical equation of Gabor filter is expressed. Then, by examining 75 different filter banks, range of effective parameters values in Gabor filter generation is determined, and finally, the best value for them is specified. The neural network used in this paper is a feed-forward back-propagation multilayer perceptron network. The input vector of the neural network is obtained from the convolution the input image and a Gabor filter with angles π / 2 and the frequency π / 2 in the frequency domain. The proposed method has been tested on 550 image samples from Feret database with simple background and Markus Weber database with complex background, and detection accuracy of them is 98.4% and95%, respectively. Also, the face area has been detected using Viola-Jones algorithm, and then comparison between the results obtained from Viola-Jones algorithm and the proposed method is described. Manuscript profile -
Open Access Article
303 - A Formal Framework for Dynamic Reconfiguration in Adaptive Systems
J. Karimpour R. AlyariToday's advanced systems are expected to be able to adapt to environmental conditions and unpredictable situations. The first requirement for such systems is to adjust them according to customer needs, their own ability and operational environment and they should be abl MoreToday's advanced systems are expected to be able to adapt to environmental conditions and unpredictable situations. The first requirement for such systems is to adjust them according to customer needs, their own ability and operational environment and they should be able to answer when faced with problem and unexpected request. Software adaptation techniques try to cope, with adaptation contracts and reconfiguration capabilities. Also these reconfigurations should be performed out of the sight of client and sometimes during the operation so that prohibit system designers from direct involvement in the internal affairs of clients. Sometimes these adaptation techniques have an impressive role in reusing components for making new systems or improving old ones. Thins paper try to create a system that can be adapted to the environment and besides it also reduces the complexity problem. To do so, at first we use a formal model to represent the whole system and then, build a mathematical model called adaptor based on adaptation contract and client requests. After creation of the adaptor, the all configuration and transactions between the client and system are done through the adaptors and Adaptors are responsible for coordinating the internal system components. Also, to avoid complexity, the concept of hierarchical networks and services are used for building the networks of adaptors. Manuscript profile -
Open Access Article
304 - Using Context Dependent Information for Discriminative Spoken Term Detection
S. Tabibian Ahmad Akbari B. NasersharifSpoken Term Detection (STD) approaches can be divided into two main groups: Hidden Markov Model (HMM)-based and Discriminative STD (DSTD) approaches. One of the important advantages of HMM-based methods is that they can use context dependent (diphone or triphones) infor MoreSpoken Term Detection (STD) approaches can be divided into two main groups: Hidden Markov Model (HMM)-based and Discriminative STD (DSTD) approaches. One of the important advantages of HMM-based methods is that they can use context dependent (diphone or triphones) information to improve the whole STD system performance. On the other hand, lack of triphones information is one of the significant drawbacks of DSTD methods. In this paper, we propose a solution to overcome this drawback of DSTD systems. To this end, we modify the feature extraction part of an Evolutionary DSTD (EDSTD) system to consider triphones information. At first, we propose a monophone-based feature extraction part for the EDSTD system. Then, we propose an approach for exploiting triphones information in the EDSTD system. The results on TIMIT database indicate that the true detection rate of the triphone-based EDSTD (Tph-EDSTD) system, in false alarm per keyword per hour greater than two, is about 3% higher than that of the monophone-based EDSTD (Mph-SDSTD) system. This improvement costs about 36% degradation of the system response speed which is neglected. Manuscript profile -
Open Access Article
305 - Method of Flow Distribution Management in Systems Based on OpenFlow
M. Salehi M. R.The current architecture of data center networks is a combination of Ethernet switches and routers. However, this architecture cannot satisfy the requirements of these networks. Ethernet switches are flexible, have simple configuration, but are not scalable. Routers pro MoreThe current architecture of data center networks is a combination of Ethernet switches and routers. However, this architecture cannot satisfy the requirements of these networks. Ethernet switches are flexible, have simple configuration, but are not scalable. Routers provide better scalability and efficient use of bandwidth, but are costly. This architecture has a noticeable overhead configuration and maintenance. So, if we had a larger Layer 2 networks, number of routers and consequently the costs will be lessened. Many methods are presented for this purpose. In this paper introduce some main requirement center data networking and characteristic of proposed methods. Among of these methods, OpenFlow is preferred. But the control overhead of OpenFlow is high. One way to reduce the control overhead by separating big and small flows and letting the controller to control only the big flows. ECMP routing is a method that can be used for routing small flows. However OpenFlow does not support ECMP. In this paper, a new method based on OpenFlow is proposed to replace ECMP. The proposed method can achieve performance comparable to ECMP. Manuscript profile -
Open Access Article
306 - Automatic Reference Image Selecting for Histogram Matching in Image Enhancement
N. Samadiani H. HassanpourIn this paper, a method is proposed to automatically select reference image in histogram matching. Histogram matching is one of the simplest spatial image enhancement methods which improves contrast of the initial image based on histogram of the reference image. In the MoreIn this paper, a method is proposed to automatically select reference image in histogram matching. Histogram matching is one of the simplest spatial image enhancement methods which improves contrast of the initial image based on histogram of the reference image. In the conventional histogram matching methods, user should perform several experiments on various images to find a suitable reference image. This paper presents a new method to automatically select the reference image. In this method, images are converted from RGB to HSV, and the illumination (V) components are considered to select the reference image. The appropriate reference image is selected using a similarity measure via measuring the similarity between the histograms of the initial image and histograms of the images in the data base. Indeed, an image with similar histogram to the histogram of the original images is more appropriate to choose as the reference image for histogram matching. Results in this research indicate superiority of the proposed approach, compared to other existing approaches, in image enhancement via histogram matching. In addition, the user would have no concern in selecting an appropriate reference image for histogram matching in the proposed approach. This approach is applicable to both RGB and gray scale images. Manuscript profile -
Open Access Article
307 - High Rate Shared Secret Key Generation Using the Phase Estimation of MIMO Fading Channel and Multilevel Quantization
V. Zeinali Fathabadi H. Khaleghi Bizaki A. ShahzadiMuch attention has recently been paid to methods of shared secret key generation that exploit the random characteristics of the amplitude and phase of a received signal and common channel symmetry in wireless communication systems. Protocols based on the phase of a rece MoreMuch attention has recently been paid to methods of shared secret key generation that exploit the random characteristics of the amplitude and phase of a received signal and common channel symmetry in wireless communication systems. Protocols based on the phase of a received signal, due to the uniform distribution phase of fading channel, are suitable in both static and dynamic environments and, they have a key generation rate (KGR) higher than protocols based on received signal strength (RSS).In addition, previous works have generally focused on key generation protocol for single-antenna (SISO) systems but these have not produced a significant KGR. So in this paper to increase the randomness and key generation rate are used received signal phase estimations on multiple-antenna (MIMO) systems because they have the potential to present more random variables in key generation compared to SISO systems. The results of simulation show that the KGR of the proposed protocol is 4 and 9 times more than the KGR of a SISO system, when the numbers of transmitter and receiver antennas are the same and equal to 2 and 3, respectively. Also, the key generation rate will increase considerably, when to extract the secret key bits using multilevel quantization. Manuscript profile -
Open Access Article
308 - A New Criterion for Balancing Global Search and Local Search in Memetic Algorithm
Mehdi Rezapoor Mirsaleh M. R. MeybodiOne of the problems with traditional genetic algorithms is its premature convergence that makes them incapable of searching good solutions of the problem. A memetic algorithm (MA) which is an extension of the traditional genetic algorithm uses a local search method to e MoreOne of the problems with traditional genetic algorithms is its premature convergence that makes them incapable of searching good solutions of the problem. A memetic algorithm (MA) which is an extension of the traditional genetic algorithm uses a local search method to either accelerate the discovery of good solutions, for which evolution alone would take too long to discover, or to reach solutions that would otherwise be unreachable by evolution or a local search method alone. In this paper, a memetic algorithm based on learning automata (LA) and memetic algorithm, called LA-MA, is introduced. This algorithm is composed of two parts, genetic section and memetic section. Evolution is performed in genetic section and local search is performed in memetic section. The basic idea of LA-MA is to use learning automata during the process of searching for solutions in order to create a balance between exploration performed by evolution and exploitation performed by local search. To evaluate the efficiency of LA-MA, it has been used to solve two optimization problems: OneMax and graph isomorphism problems. The results of computer experimentations have shown that different versions of LA-MA outperform the others in terms of quality of solution and rate of convergence. Manuscript profile -
Open Access Article
309 - Automatic Detection of Grand-Mal Epileptic Seizure and Recognizing Normal Activities in Video by a Combination of Machine Vision and Machine Learning Techniques
A. Hakimi Rad N. Moghadam CharkariThe most relevant method to detect epileptic seizures is the electroencephalogram (EEG) based signal processing method which, due to the need for installing some electrodes on different places of the person's head, causes many movement problems. The aim of this research MoreThe most relevant method to detect epileptic seizures is the electroencephalogram (EEG) based signal processing method which, due to the need for installing some electrodes on different places of the person's head, causes many movement problems. The aim of this research is to automatically and intelligently detect grand-mal epileptic seizures and also to recognize normal activities of a person suffering from the disease by video surveillance. In this paper we have used the combination of machine vision and machine learning techniques to automatically detect grand-mal epileptic seizure when the person is lying on the ground or on the bed. After subtracting the background from video frame sequences and extracting the image silhouette, appropriate geometrical features have been extracted and fed to the multi-class support vector machine as the input for automatically classifying the videos and assigning proper activity label. All the implementations have been done on MATLAB R2011a. In this intelligent system the accuracy of detecting and recognizing activities is 90.21%. Using this system in addition to reducing the number of human observers is very helpful for the on time and constant detection of the condition. The need for just a conventional video camera and a computer system makes it affordable for people with different incomes. Because it needs not to be in contact with the person's body, there is no movement problem too. High accuracy verifies the optimal performance of the system. Manuscript profile -
Open Access Article
310 - Design of a CDS Backbone Based Wireless Mesh Network Energy Aware Routing Method for Maximizing Lifetime
A. Shafaroudi S. V. AzhariIn many applications, wireless mesh networks work by battery as a power source. In this scenario, routing method has a great impact on the network lifetime. In this research a new backbone based wireless mesh network routing method for maximizing lifetime has been prop MoreIn many applications, wireless mesh networks work by battery as a power source. In this scenario, routing method has a great impact on the network lifetime. In this research a new backbone based wireless mesh network routing method for maximizing lifetime has been proposed. This approach is compatible with the features provided by IEEE standard for wireless mesh networks. In this method, backbone routers are selected based on the maximum remaining energy. The proposed algorithm is compared with optimum and shortest path routing methods. Simulation results show acceptable increase in network lifetime in the proposed approach. Manuscript profile -
Open Access Article
311 - Reactive Power Management in the Presence of Wind Turbine Considering Uncertainty of Load and Generation
E. Moharamy S. EsmaeiliReactive power management is very important in power systems for the secure transmission of active power, especially when a part of system generation is provided by stochastic sources like wind energy. This paper presents a new algorithm for reactive power management in MoreReactive power management is very important in power systems for the secure transmission of active power, especially when a part of system generation is provided by stochastic sources like wind energy. This paper presents a new algorithm for reactive power management in the presence of wind generators and considering the stochastic nature of these sources and load simultaneously .In this regard, the proposed probabilistic algorithm, minimizes the overall cost function of the system considering the cost of each of the reactive power sources including wind generators. Besides economic issues, the voltage stability margin, having sufficient reactive power reserve in each area of voltage control and considering transmission congestion probability as technical aspects of the planning, have been investigated .Another advantage of this method compared to the previous one, is using of doubly-fed induction generator (DFIG) and its capability in providing reactive power considering the constraints of grid side and rotor side converters. The proposed optimization algorithm uses a multi objective function with different weighting coefficients. This algorithm is applied to minimize total reactive power, cost and losses and maximize voltage stability margin and reactive power reserve, simultaneously, meanwhile the probabilistic nature of wind and load forecasting inaccuracy is considered in this algorithm. The proposed method is implemented on the IEEE 30-bus test system and the simulation results demonstrate the effectiveness of proposed algorithm in real conditions for PMSMs against internal faults, especially inter-turn faults. Manuscript profile -
Open Access Article
312 - Modeling and Analysis of Tower Protection Performance in Order to Coordinate with Environmental Conditions Response and Security Constraint Unit Commitment
M. Yahyaabadi A. SadoughiرIn this paper, effective parameters on lightning performance of communication tower are analyzed. The effect of communication tower height, Influence of weather conditions and adjacent structures are investigated. A 3-D numerical analysis model based on charge simulati MoreرIn this paper, effective parameters on lightning performance of communication tower are analyzed. The effect of communication tower height, Influence of weather conditions and adjacent structures are investigated. A 3-D numerical analysis model based on charge simulation method is applied to calculate the probability of shielding failure and to determine the number of direct lightning strokes to antenna. The communication tower, lightning rod, downward descending leader and upward leaders are modeled by different shapes of charges. For each of the numerous points of all the space above the tower and for different values of lightning current, downward lightning leader is considered to be initiated, and it is distributed step by step until final jump. The electric field around the grounded objects is calculated and upward leader inception criterion is checked in each step. If this criterion were approved for a point, an upward leader would be initiated from that point and then the distribution of upward leader would continue. Upward leaders might be initiated from more than one point but only one of them could strike to downward leader. This process will continue for different conditions and in every situation all the results are analyzed and evaluated. Manuscript profile -
Open Access Article
313 - Lateral Stabilization of a Four Wheel Independent Drive Electric Vehicle Using a Three Layer Controller and Sliding Mode Control
H. Alipour M. Sabahi M. B. B. SharifiaIn this paper, a new controller, for lateral stabilization of four wheel independent drive type electric vehicles without mechanical differential, is proposed. The proposed controller has three levels includes high, medium and low control level. Desired vehicle dynamics MoreIn this paper, a new controller, for lateral stabilization of four wheel independent drive type electric vehicles without mechanical differential, is proposed. The proposed controller has three levels includes high, medium and low control level. Desired vehicle dynamics such as reference longitudinal speed and reference yaw rate are determined by higher level of controller. In this paper, a new sliding mode controller is proposed and its stability is proved by Lyapunov stability theorem. This sliding mode control structure is faster, more accurate, more robust, and with smaller chattering than common sliding mode controllers. Based on the proposed sliding mode controller, the medium control level is designed to determine the desired traction force and yaw moment. In the lower level controller, suitable wheel forces and torques are calculated by an optimal cost function minimizing. Finally, the effectiveness of the introduced controller is investigated through conducted simulations Manuscript profile -
Open Access Article
314 - Multi Objective Network Reconfiguration for Distribution System with Micro-Grids Power Exchange using Max-Min Fuzzy Method and Particle Swarm Optimization Algorithm
A. Fattahi Meyabadi H. SohrabianiA group of small generators and energy storages in the low or medium voltage distribution systems beside of consumers emerge to a new power system called micro grid. Micro grids are designed to have secure and economic operation isolated and connected to the network and MoreA group of small generators and energy storages in the low or medium voltage distribution systems beside of consumers emerge to a new power system called micro grid. Micro grids are designed to have secure and economic operation isolated and connected to the network and exchange electrical energy with distribution system. Hence, they may impact on planning and scheduling of distribution systems. In this case, network reconfiguration is a considerable issue after presenting of micro grids to the system. In the previous studies regarding to this issue, micro grid is considered as a distributed generation which should only produce electricity to the network. In this paper, micro grid is modeled as a power exchanger in the distribution network to study the effect of it on the network reconfiguration. For this purpose, reconfiguration is formulated as a multi objective optimization problem using max-min fuzzy method. In this problem, power loss reduction and load balancing among feeders are two independent objectives and voltage profile, lines congestion, radial network structure and load flow are equality and inequality constraints. Particle swarm algorithm is applied to solve the optimization problem and the reconfiguration over two 33 and 70 buses IEEE test network is shown. Results demonstrate that replacing traditional distribution systems by modern active networks and exchanging power with micro grids can lead to increase the reliability of system and more economic operation. Manuscript profile -
Open Access Article
315 - Improving the Performance of Grid-Connected Cascaded H-bridge Photovoltaic Inverters under Asymmetric Insolation Conditions
H. Iman-Eini M. Amini S. FarhangiIn recent years, solar energy has gained a great deal of attention. Hence, the photovoltaic (PV) systems which convert the solar energy into electricity should achieve high efficiency, low manufacturing cost, and high quality of electric power to attract the consumers. MoreIn recent years, solar energy has gained a great deal of attention. Hence, the photovoltaic (PV) systems which convert the solar energy into electricity should achieve high efficiency, low manufacturing cost, and high quality of electric power to attract the consumers. Although Cascaded H-Bride (CHB) inverter is a suitable choice for injection of PV power into grid, its control issues have not been completely solved. One of the main challenges in CHB inverter is low margin of stability when the H-bridge cells are under imbalance operating conditions. In this paper, a new MPPT algorithm is proposed for a CHB photovoltaic inverter. The proposed approach not only tracks the maximum point of distinct PV arrays under symmetric insolation, but also behaves well under asymmetric insolation conditions. The latter is achieved through shifting the operating point of PV arrays and using the modulation index of H-bridge cells as a degree of freedom. The usefulness and validity of new method is confirmed by simulation and experiments on a 7-level CHB photovoltaic inverter. Manuscript profile -
Open Access Article
316 - CMOS Low-Dropout Voltage Regulator with Controlled Pass Transistor
F. Qaraqanabadi A. SaberkariThis paper presents a low quiescent current low-dropout voltage regulator (LDO) with controlled pass transistor which can work either with on-chip or off-chip output capacitor. The pass transistor of the proposed LDO has lower width in low load condition and has higher MoreThis paper presents a low quiescent current low-dropout voltage regulator (LDO) with controlled pass transistor which can work either with on-chip or off-chip output capacitor. The pass transistor of the proposed LDO has lower width in low load condition and has higher width for moderate to heavy load current and the LDO topology transforms between a two-stage structure in low load current and a three-stage one in moderate to high load current. The proposed LDO topology is designed and simulated in HSPICE in a 0.35 µm CMOS process to provide a 2.8 V output voltage for a 3 V input voltage and is capable to deliver a stable output current in the range of 0-100 mA to the load with a 100 pF on-chip output capacitor while its quiescent current is only 7.5 µA. Without using the adaptively-controlled pass transistor, the maximum output variations of the LDO to the 0-100 mA load transient is 540 mV and its settling time is 11 µs, while using this technique decreases the output voltage variations and settling time to 280 mV and 6.5 µs, respectively. Manuscript profile -
Open Access Article
317 - Joint Blind Equalization and Decoding over Frequency Selective Channels in OFDM Systems Using Particle Filtering Joint Blind Equalization and Decoding over Frequency Selective Channels in OFDM Systems Using Particle Filtering
N. Ghasemi M. F. Sabahi A. R. ForouzanIn this paper a sequential algorithm is proposed for joint blind channel equalization and decoding for orthogonal frequency-division multiplexing (OFDM) in frequency selective channels. This algorithm offers a recursive method to sequentially calculate the posterior pro MoreIn this paper a sequential algorithm is proposed for joint blind channel equalization and decoding for orthogonal frequency-division multiplexing (OFDM) in frequency selective channels. This algorithm offers a recursive method to sequentially calculate the posterior probability for maximum a posteriori (MAP) detection. Recursive calculations are done along the indexes in each OFDM symbol using a particle filter. By defining an appropriate importance function, and a proper prior probability distribution function for the channel tap coefficients (and marginalizing it), an efficient method is presented for joint equalization and channel decoding in OFDM based systems. Performance of the proposed detector is evaluated using computer simulations and its bit error rate is compared with the trained turbo equalizer and a conventional particle filter-based method. The results show that the proposed method outperforms the previously presented particle filter-based method without a need for training data. Manuscript profile -
Open Access Article
318 - Performance Improvement of Generalized Spatial Modulation in Multipath Fading Channels
A. Rezvani R. Saadat J. AboueiSpatial Modulation(SM) is a novel method in use of multiple antenna systems. The main idea is based on information block mapping into two carrying units: a transmit symbol unit that is chosen from constellation members and second unit is the number of active antenna tha MoreSpatial Modulation(SM) is a novel method in use of multiple antenna systems. The main idea is based on information block mapping into two carrying units: a transmit symbol unit that is chosen from constellation members and second unit is the number of active antenna that shows the position of transmit antenna. The use of active antenna position as an extra source of transmit data increases the bandwidth efficiency. Also it doesn't have inter-antenna interference (IAI) and inter-channel interference (ICI) and it's caused to decrease the complexity in receiver side. So SM is a competitor in multiple antenna systems like V-BLAST and space-time coding. More recently generalized spatial modulation (GSM) is presented that use some active antennas instead an active antenna. When the symbol is sent from multiple antennas, it'll get a diversity gain. In this paper we show that by using different channel coding in GSM we can improve bit error rate (BER) without decrease in bandwidth efficiency between 15-40 percent. Manuscript profile -
Open Access Article
319 - A New Non-Isolated SEPIC Converter with High Gain and High Efficiency for Photovoltaic Application
M. Mahmoudi B. Mirzaeian Dehkordi M. NiroomandIn this paper, a new non-isolated SEPIC converter for photovoltaic application is introduced and analyzed. Regarding to low output voltage PV panel and high voltage application of PV systems, a high gain converter is designed. This converter has advantages such as high MoreIn this paper, a new non-isolated SEPIC converter for photovoltaic application is introduced and analyzed. Regarding to low output voltage PV panel and high voltage application of PV systems, a high gain converter is designed. This converter has advantages such as high output voltage gain while keeping the switch voltage stress equal to a regular SEPIC converter, improve the turn-on and turn-off transients of the switch and high efficiency. Also, switching losses and EMI noise are reduced by soft switching method. The MOSFET operates at zero-voltage-switching (ZVS) turn-off and near zero-current-switching (ZCS) turn-on. Manuscript profile -
Open Access Article
320 - Robust Tracking by Using Measure Theory
A. Zare A. Khaki-Sedigh A. VahidianThis paper presents two new approaches for robust step tracking in structure uncertain nonlinear systems. The problem is first restated as a non linear optimal control infinite horizon problem, then with a suitable change of variable, the time interval is transfer to th MoreThis paper presents two new approaches for robust step tracking in structure uncertain nonlinear systems. The problem is first restated as a non linear optimal control infinite horizon problem, then with a suitable change of variable, the time interval is transfer to the finite horizon [0 1). This change of variable, poses a time varying problem. This problem is then transfer to measure space, and it is shown that an optimal measure must be determined which is equivalent to a linear programming problem with infinite dimension. Then, using finite horizon approximations, the optimal control law is determined as a piece wise constant function. Simulations are provided to show the effectiveness of the proposed methodology Manuscript profile -
Open Access Article
321 - Optimum Design of Branch-Line Couplers with Impedance Matching
H. Horaizi J. Hamedfar -
Open Access Article
322 - Wavelet Detection of Partial Discharges in High Voltage Cables
B. Badrzadeh S. M. ShahrtashThis paper has proposed an on-line method of partial discharges (PDs) detection. Fundamental difficulty in PD measurement is that PD signal is so minute that can be easily contaminated by huge amount of noise and this makes PD detection rather obscure. Thus, noise reduc MoreThis paper has proposed an on-line method of partial discharges (PDs) detection. Fundamental difficulty in PD measurement is that PD signal is so minute that can be easily contaminated by huge amount of noise and this makes PD detection rather obscure. Thus, noise reduction algorithms have been extensively deployed to mitigate the noise. Among which, Digital Signal Processing (DSP) techniques are becoming more and more applicable. Compared by linear predictor and Least Mean Square (LMS), a wavelet-based noise reduction algorithm has been utilised. Some significant considerations in wavelet denoising such as selection of level of decomposition and reconstruction, mother wavelets, methods of signal extension,thresholding criterion have been discussed deeply. In order to prove the effectiveness of our algorithm, real data extracted from an 11 kV cable has been used Manuscript profile -
Open Access Article
323 - Modelling and Evaluation of Galloping in Overhead Transmission Lines
Ahmad Gholami Mohammad MirzaieOne of the main parameters for overhead lines designing is conductor oscillation that has a special role for determination of conductor’s gaps. One of the kinds of oscillations is galloping which creates economic losses for utilities. In this paper, a dynamic model of MoreOne of the main parameters for overhead lines designing is conductor oscillation that has a special role for determination of conductor’s gaps. One of the kinds of oscillations is galloping which creates economic losses for utilities. In this paper, a dynamic model of single conductor overhead lines that has vertical motion is investigated and according to applicable differential equations, this model is simulated for estimation of galloping amplitude. Also by using of control theories and mathematical approximation, a new electrical model is presented. Moreover by using of nonlinear control theory, system equivalent point has been determined and the amount of damper damping coefficient for decreasing of the oscillation amplitude has been evaluated. Manuscript profile -
Open Access Article
324 - An Improved Method for Adaptive Noise Cancellation of ECG Signals in very Difficult Conditions
Ahmad Ayatollahi S. H. SabzpooshanWe present a new adaptive noise cancellation method for ECG noise cancelling in very difficult conditions. This method is based on modified variable step size LMS algorithm. We show that the proposed algorithm is more efficient and the adaption speed is higher than conv MoreWe present a new adaptive noise cancellation method for ECG noise cancelling in very difficult conditions. This method is based on modified variable step size LMS algorithm. We show that the proposed algorithm is more efficient and the adaption speed is higher than conventional LMS Manuscript profile -
Open Access Article
325 - Blind Video Steganalysis by Semi-Supervised Approach for Motion Vectors Based Steganography Algorithms
Supervised learning algorithms are widely used in blind video steganalysis and the cost of generating labeled data in them is high. That is why only a limited number of steganography algorithms with accessible code can be used for the training the classifier. Therefore, MoreSupervised learning algorithms are widely used in blind video steganalysis and the cost of generating labeled data in them is high. That is why only a limited number of steganography algorithms with accessible code can be used for the training the classifier. Therefore, we cannot be sure about the effectiveness of steganalyzer in identifying non-accessible video steganography algorithms. On the other hand, using offline classification methods in the blind video steganalysis causes the learning process be time consuming and the system cannot be updated online. To solve this problem, we propose a new method for the blind video steganalysis by semi-supervised learning approach. In the proposed method, by eliminating the limitation of labeled training dataset, the classifier performance is improved for video steganography algorithms with non-accessible code. It is also proved that the proposed method, compared to common classification methods for the blind video steganalysis, has less time complexity and it is an optimal online technique. The simulation results on the standard database show that in addition to the above advantages, this method has appropriate accuracy and is comparable to common methods. Manuscript profile -
Open Access Article
326 - Blind Video Steganalysis by Semi-Supervised Approach for Motion Vectors Based Steganography Algorithms
J. Mortazavi Mehrizi M. Khademi H. Sadoghi YazdiSupervised learning algorithms are widely used in blind video steganalysis and the cost of generating labeled data in them is high. That is why only a limited number of steganography algorithms with accessible code can be used for the training the classifier. Therefore, MoreSupervised learning algorithms are widely used in blind video steganalysis and the cost of generating labeled data in them is high. That is why only a limited number of steganography algorithms with accessible code can be used for the training the classifier. Therefore, we cannot be sure about the effectiveness of steganalyzer in identifying non-accessible video steganography algorithms. On the other hand, using offline classification methods in the blind video steganalysis causes the learning process be time consuming and the system cannot be updated online. To solve this problem, we propose a new method for the blind video steganalysis by semi-supervised learning approach. In the proposed method, by eliminating the limitation of labeled training dataset, the classifier performance is improved for video steganography algorithms with non-accessible code. It is also proved that the proposed method, compared to common classification methods for the blind video steganalysis, has less time complexity and it is an optimal online technique. The simulation results on the standard database show that in addition to the above advantages, this method has appropriate accuracy and is comparable to common methods. Manuscript profile -
Open Access Article
327 - Blind Video Steganalysis by Semi-Supervised Approach for Motion Vectors Based Steganography Algorithms
J. Mortazavi Mehrizi M. Khademi H. Sadoghi YazdiSupervised learning algorithms are widely used in blind video steganalysis and the cost of generating labeled data in them is high. That is why only a limited number of steganography algorithms with accessible code can be used for the training the classifier. Therefore, MoreSupervised learning algorithms are widely used in blind video steganalysis and the cost of generating labeled data in them is high. That is why only a limited number of steganography algorithms with accessible code can be used for the training the classifier. Therefore, we cannot be sure about the effectiveness of steganalyzer in identifying non-accessible video steganography algorithms. On the other hand, using offline classification methods in the blind video steganalysis causes the learning process be time consuming and the system cannot be updated online. To solve this problem, we propose a new method for the blind video steganalysis by semi-supervised learning approach. In the proposed method, by eliminating the limitation of labeled training dataset, the classifier performance is improved for video steganography algorithms with non-accessible code. It is also proved that the proposed method, compared to common classification methods for the blind video steganalysis, has less time complexity and it is an optimal online technique. The simulation results on the standard database show that in addition to the above advantages, this method has appropriate accuracy and is comparable to common methods. Manuscript profile -
Open Access Article
328 - Content Based Image Retrieval by the Fusion of Short Term Learning Methods
B. Bagheri M. Pourmahyabadi H. Nezamabadi-pourContent based image retrieval (CBIR) contains a set of techniques to process the visual features of a query image, in order to retrieve images semantically similar to it, in a database. To improve the performance of image retrieval systems, relevance feedback tool can b MoreContent based image retrieval (CBIR) contains a set of techniques to process the visual features of a query image, in order to retrieve images semantically similar to it, in a database. To improve the performance of image retrieval systems, relevance feedback tool can be used. In this research, to increase the effectiveness of the image retrieval systems, the fusion of two (multiple) short term learning methods based on relevance feedback is proposed. In the proposed method, fusion is performed in three levels: fusion in ranks, fusion in retrieved images, and fusion in similarities. To evaluate the performance of the proposed method, a CBIR system with 10000 images of 82 different semantic groups is employed. The experimental results confirm the superior of suggested method in terms of retrieval precision. Manuscript profile -
Open Access Article
329 - Content Based Image Retrieval by the Fusion of Short Term Learning Methods
B. Bagheri M. Pourmahyabadi H. Nezamabadi-pourContent based image retrieval (CBIR) contains a set of techniques to process the visual features of a query image, in order to retrieve images semantically similar to it, in a database. To improve the performance of image retrieval systems, relevance feedback tool can b MoreContent based image retrieval (CBIR) contains a set of techniques to process the visual features of a query image, in order to retrieve images semantically similar to it, in a database. To improve the performance of image retrieval systems, relevance feedback tool can be used. In this research, to increase the effectiveness of the image retrieval systems, the fusion of two (multiple) short term learning methods based on relevance feedback is proposed. In the proposed method, fusion is performed in three levels: fusion in ranks, fusion in retrieved images, and fusion in similarities. To evaluate the performance of the proposed method, a CBIR system with 10000 images of 82 different semantic groups is employed. The experimental results confirm the superior of suggested method in terms of retrieval precision. Manuscript profile -
Open Access Article
330 - Semi-Supervised Learning Based on Extreme Learning
A. Mehrizi H. Sadoghi Yazdi S. J. Seyyed Mahdavi ChabokSemi-supervised learning with growing self-organizing map (GSOM) is used in many applications, such as clustering. The main challenges in the Semi-supervised GSOM are calculating parameters such as shape and structure of clustering layer, activation level, and weights o MoreSemi-supervised learning with growing self-organizing map (GSOM) is used in many applications, such as clustering. The main challenges in the Semi-supervised GSOM are calculating parameters such as shape and structure of clustering layer, activation level, and weights of classifier layer. Current approaches use initiative methods with a local look have trying to determine these parameters; which its effect, the results of these algorithms is highly dependent on the conditions. This paper studies a semi-supervised learning method based on GSOM and extreme learning for the first time. The proposed method, without the direct calculation of the GSOM parameters and using the extreme learning determines label of each data. Error resulted from the feedback system is used to optimize extreme learning and GSOM. In this paper, in addition to investigating the convergence analysis of the proposed method, sequential extreme learning is also provided for semi-supervised GSOM. Experiments conducted on online and partially labeled data show that the proposed method has a relative advantage in terms of accuracy on semi-supervised GSOM. Manuscript profile -
Open Access Article
331 - Learners Grouping in Adaptive Learning Systems Using Fuzzy Grafting Clustering
M. S. Rezaei Gh. A. MontazerQuality of adaptive and collaborative learning systems is related to appropriate specifying learners and accuracy of separation learners in homogenous and heterogeneous groups. In the proposed method for learners grouping, researchers effort to improving basic clusterin MoreQuality of adaptive and collaborative learning systems is related to appropriate specifying learners and accuracy of separation learners in homogenous and heterogeneous groups. In the proposed method for learners grouping, researchers effort to improving basic clustering methods by combination of them and improving methods. This work makes the complexity of grouping methods increased and quality of result’s groups decreased. In this paper, new method for selection appropriate clusters based on fuzzy theory is proposed. In this method, each cluster is defined as a fuzzy set and the corresponding clusters are determined. So the best cluster is selected among each corresponding clusters. The results of an empirical evaluation of the proposed method based on two criteria: “Davies-Bouldin” and “Purity and Gathering” indicate that this method has better performance than other clustering methods such as FCM, K-means, hybrid clustering method (HCM), evolutionary fuzzy clustering (EFC) and ART neural network. Manuscript profile -
Open Access Article
332 - Evaluation of Fuzzy-Vault-based Key Agreement Schemes in Wireless Body Area Networks Using the Fuzzy Analytical Hierarchy Process
M. Ebrahimi H. R. Ahmadi M. Abbasnejad AraWireless body area networks (WBAN) may be deployed on each person’s body for pervasive and real time health monitoring. As WBANs deal with personal health data, securing the data during communication is essential. Therefore, enabling secure communication in this area ha MoreWireless body area networks (WBAN) may be deployed on each person’s body for pervasive and real time health monitoring. As WBANs deal with personal health data, securing the data during communication is essential. Therefore, enabling secure communication in this area has been considered as an important challenge. Due to the WBAN characteristics and constraints caused by the small size of the nodes, selection of the best key agreement scheme is very important. This paper intends to evaluate different key agreement schemes in WBANs and find the best one. To achieve this goal, three schemes from existing research named OPFKA, PSKA and ECG-IJS are considered and a fuzzy analytical hierarchy process (FAHP) method is employed to find the best scheme. Manuscript profile -
Open Access Article
333 - A Distance-Based Method for Inconsistency Resolution of Models
R. Gorgan Mohammadi Ahmad Abdollahzadeh BarforoushModel driven approach to software engineering has been taken into consideration due to its impact on reducing complexities and improving the productivity in software development. Inconsistencies are considered as an important challenge in applying models. An inconsisten MoreModel driven approach to software engineering has been taken into consideration due to its impact on reducing complexities and improving the productivity in software development. Inconsistencies are considered as an important challenge in applying models. An inconsistency is occurred due to an undesired structural pattern in a model. The main drawback of current approaches to inconsistency resolution is not considering the difference between the repair and the spoiled model. This work presents a distance-based method for finding closest repair for the spoiled model. For this aim, models and metamodels are represented using directed graphs and graph transformation rules are employed for inconsistency resolution. A distance metric is defined based on the amount of changes in the graph corresponding to the model. Application of the proposed method to a set of BPMN models shows the improvement of the results. Manuscript profile -
Open Access Article
334 - Fault Detection by Integrating Canonical Variate Analysis and Independent Component Analysis Based on Local Outlier Factor
E. Tavasolipour M. T. Hamidi Beheshti A. RamezaniIn this paper a novel process monitoring scheme is proposed because of the importance of fault detection and identification in industrial processes. In this method, process dynamic and effect of outliers are considered concurrently. First, the proposed approach uses CVA MoreIn this paper a novel process monitoring scheme is proposed because of the importance of fault detection and identification in industrial processes. In this method, process dynamic and effect of outliers are considered concurrently. First, the proposed approach uses CVA method to implement the process dynamic. Then ICA method is performed for dimension reduction of data. The outliers elimination and control limit calculation are based on the Local Outlier Factor algorithm. This algorithm doesn’t consider a special distribution for process variables, thus conforming to data in real industrial processes. The proposed method is applied to fault detection in the Tennessee Eastman process. Results clearly indicate better performance of the proposed scheme compared to the alternative methods. Manuscript profile -
Open Access Article
335 - Separating Bichromatic Point Sets by Right Triangles
Z. Moslehi A. BagheriSeparating colored point sets is an interesting problem in computational geometry with application in machine learning and pattern recognition. In this problem, we are given a geometric shape C and two point sets P and Q of total size n as red and blue points, respectiv MoreSeparating colored point sets is an interesting problem in computational geometry with application in machine learning and pattern recognition. In this problem, we are given a geometric shape C and two point sets P and Q of total size n as red and blue points, respectively. Now, we must separate red and blue points by this shape such that all the blue points lie inside it and all the red points lie outside it. In the previous work, we have some algorithms for rectangle and wedge separability but we do not have any algorithm for separating by a triangle and separating by a triangle with a fixed angle such as right triangle. In this paper, we present an efficient algorithm for right triangle seprability. In this algorithm, we use sweep line technique and introduce some events and process them. So, we can report all separating right triangles in O(nlog n) time. Manuscript profile -
Open Access Article
336 - An Efficient Bread First Search Algorithm on CPU and GPU
P. Keshavarzi H. Deldari S. AbrishamiGraphs are powerful data representations used in enormous computational domains. In graph-based applications, a systematic exploration of graph such as a breath first search often is a fundamental component in the processing of the vast data sets. In this paper we prese MoreGraphs are powerful data representations used in enormous computational domains. In graph-based applications, a systematic exploration of graph such as a breath first search often is a fundamental component in the processing of the vast data sets. In this paper we presented a hybrid method that in each level of processing of graph chooses the best implementation of algorithms implemented on CPU or GPU, while avoid poor performance on low and high degree graphs. Our method shows improved performance over the current state-of-the-art implementation and our results proves it. Manuscript profile -
Open Access Article
337 - An Investigation on the Impacts of Renewable Energy Sources in the Generation Expansion Planning Framework from Social Welfare Perspective
H. Sadeghi M. Rashidinejad A. AbdollahiNowadays, it is clear to everyone that climate change has posed a huge threat to human welfare. Hence, the growth of demand for electricity as well as the dependence of power sector to the fossil fuel sources has converted the electrical energy sector into one of the mo MoreNowadays, it is clear to everyone that climate change has posed a huge threat to human welfare. Hence, the growth of demand for electricity as well as the dependence of power sector to the fossil fuel sources has converted the electrical energy sector into one of the most important areas suitable for applying the restrictions and implementation of the solutions provided to mitigate greenhouse gases. Enacting different incentive-based support schemes pursuing the promotion of renewable energy sources along with emission reduction in power generation sector is treated as one the main provided solutions. In this paper, from various points of view, such as environmental issues, power sector investors’ profit and the surplus of electricity consumers, the effect of renewable penetration rate growth under implementation of incentive-based policies is evaluated in a long-term generation expansion planning framework by employing the concept of Bergson-Samuelson social welfare function. To achieve this aim, first, a comprehensive generation expansion planning model, faced by a generation company, is proposed, as the effect of one on the most popular policies, namely emission trading system, is incorporated into the model. As a mixed integer nonlinear programming problem, the model is solved through two different scenarios using the GMAS optimization package. Then, regarding the obtained optimized expansion strategies, aforementioned viewpoints are assessed. Manuscript profile -
Open Access Article
338 - Design and Implementation of a Generator Fault Diagnosis Structure
Mohammad Zare Ernani A. AkbariGenerators failure and generators break down can cause high financial consequences. For this reason, several concepts for the condition monitoring of generators have been developed. The purpose of this article is to collect significant generator data in order to form a MoreGenerators failure and generators break down can cause high financial consequences. For this reason, several concepts for the condition monitoring of generators have been developed. The purpose of this article is to collect significant generator data in order to form a comprehensive analysis by analytical hierarchy process (AHP) method. The AHP is a multi-criteria analysis approach, where is used in order to combine the results of online diagnostic methods and draw conclusions on the most probable failure. A fault diagnosis structure has been designed and several comparison charts have been generated. This trend led to the running generator probable failure, to be revealed. In this paper the circumstances of design and implementation of the LEMS structure with two simulation results are described. Manuscript profile -
Open Access Article
339 - Exact Formulation and Modeling for Analytical Calculation of the Electrical and Mechanical Harmonic Behaviors of Doubly Fed Induction Generator in Wind Turbine
M. Nayeripour M. M. MansouriThis paper presents a new exact formulation which models all harmonics in Double Fed Induction Generator (DFIG). In this methodology, the harmonics which originate from rotor side converter, stator side and mechanical part are analyzed and their interactions are conside MoreThis paper presents a new exact formulation which models all harmonics in Double Fed Induction Generator (DFIG). In this methodology, the harmonics which originate from rotor side converter, stator side and mechanical part are analyzed and their interactions are considered and a new model is extracted based on frequency components in electrical and mechanical parts. The proposed method expands previous analytical approach and phase angle/amplitude of frequency components take to be account. Since this model is derived from time domain relations between frequency components, it can be used in normal and faulty conditions. The proposed model is evaluated by some case study in MATLAB/SIMULINK software. Manuscript profile -
Open Access Article
340 - Dual Loop Control of 400 Hz Inverter for Ground Power Units
M. Nouri H. Iman-EiniIn this paper dual-loop control method is proposed for control of 400 Hz inverter. Resonant controllers are used in the outer loop to regulate the amplitude of fundamental harmonic and to remove the unwanted harmonics. To avoid phase delay and bandwidth degradation, pro MoreIn this paper dual-loop control method is proposed for control of 400 Hz inverter. Resonant controllers are used in the outer loop to regulate the amplitude of fundamental harmonic and to remove the unwanted harmonics. To avoid phase delay and bandwidth degradation, proportional controller is used as the inner control loop. In this paper, hybrid digital design in discrete- and continuous-time domain is introduced to design the inner and outer control loops. To decouple the control system from the load current disturbances and to improve the dynamic performance, a feed-forward path is added to the dual-loop control structure. To reduce the noise of feed-forward path, a soft-derivative term is introduced which is optimized for 400 Hz frequency. To verify the system performance, several simulations have been carried out which shows satisfactory results under dynamic and steady state conditions. Finally, the experimental results of a 20 kVA hardware prototype is presented to confirm the validity of theoretical and simulation results. Manuscript profile -
Open Access Article
341 - A New Pulse Frequency Waveform Synthesizing Method Using IPT Frequency-Gain Characteristics
M. H. Ameri A. Yazdian Varjani M. MohamadianThe electrical connection between the load and source can be eliminated using inductive power transfer. Supplying AC Loads, such as V2G and single phase motors, is one of the many applications of IPT. To supply an AC load, the rectified output power of IPT should be del MoreThe electrical connection between the load and source can be eliminated using inductive power transfer. Supplying AC Loads, such as V2G and single phase motors, is one of the many applications of IPT. To supply an AC load, the rectified output power of IPT should be delivered to an inverter. The sequential dc/ac/dc/ac conversions cause IPT efficiency decreases. To make an output AC voltage with acceptable THD, the carrier frequency of the PWM method should be several times the reference frequency which increases the switching loss. In this paper based on IPT gain-frequency characteristics, a new pulse frequency waveform synthesizing method (PFWS) has been presented. This method eliminates secondary inverter switching losses. It is shown that besides loss reduction, synthesized sinusoidal waveform at secondary of IPT, causes the Total Switching Device Power (TSDP) of secondary converters decrease, therefore their lifetime increase. Simulated and experimental results of the developed laboratory model which verify and illustrate the operation of the proposed method are presented. Manuscript profile -
Open Access Article
342 - A New Unified Power Quality Conditioner based on Trans-Z-Source Inverter
M. Siahi Mohammad DavoodiUnified Power quality conditioner (UPQC) consists of back to back voltage source inverters. In UPQC combination of parallel and series active power filters are used to compensate for the nonlinear load current harmonics and voltage distortions, simultaneously. For appro MoreUnified Power quality conditioner (UPQC) consists of back to back voltage source inverters. In UPQC combination of parallel and series active power filters are used to compensate for the nonlinear load current harmonics and voltage distortions, simultaneously. For appropriate performance of both converters and bidirectional power flow, the DC link voltage should be at least 1.41 times larger than the line to line voltage in the high voltage part of the system; i.e. the parallel active filter. One of the determining factors for the cost of semiconductors is the maximum tolerable voltage stress. The voltage stress of the series converter increases when the DC link voltage is high. In order to overcome this deficiency, a Z-source network is added to the common structure of back to back invertors in the UPQC. It will reduce the applied DC voltage to the series active power filters significantly and decrease the cost of manufacturing. In this structure, an impedance source network is used in an AC/DC inverter to produce a buck-boost effect. Additionally, dead time has been eliminated through the use of a Z source network in the parallel active filter and thus its performance and reliability has increased impressively. In this paper, a comparison study has been conducted through necessary simulations for the performance evaluation of the common and proposed structures. The total switching device power has been used as a criteria to confirm the manufacturing cost reduction in the proposed structure. Manuscript profile -
Open Access Article
343 - Optimization Design of Interior Permanent Magnet Motor Based on Wide Flux Weakening Range and Reduction of Permanent Magnet Volume
M. Arehpanahi M. ArehpanahiAn interior permanent magnet motor is a good option for traction application related to the induction motor and switched reluctance motor because of high mechanical rigidity and low demagnetization risk. the design of this kind of motor is attractive for engineer despis MoreAn interior permanent magnet motor is a good option for traction application related to the induction motor and switched reluctance motor because of high mechanical rigidity and low demagnetization risk. the design of this kind of motor is attractive for engineer despise the implementation cost of them in high constant speed power range (CPSR) is high. in this paper using combination of two ideas i.e. non conventional air bridge and segmented permanent magnet a optimal design has been proposed. in this paper non conventional air bridge is used for reducing the permanent magnet volume. the genetic algorithm has been applied to the goal function. simulation results show the good performance of optimal design related the conventional design. Manuscript profile -
Open Access Article
344 - New Beamforming Algorithm for Cooperative Networks with Multiple Antenna Decode and Forward Relay
Mohammad Mohammadi Amiri A. OlfatIn this paper, a cooperative network consisting of one source, one relay, and one destination is considered. The source and the destination are both single-antenna systems, while the relay is equipped with N antennas and operates in decode-and-forward (DF) mode. We assu MoreIn this paper, a cooperative network consisting of one source, one relay, and one destination is considered. The source and the destination are both single-antenna systems, while the relay is equipped with N antennas and operates in decode-and-forward (DF) mode. We assume that there is no direct link between the source and the destination. We propose two beamforming methods at the relay to transmit the data to the destination. Beamforming is performed at the relay by the assumption of having two bit quantized information about the phase of all links between the relay and the destination. We derive an upper bound on bit error probability of the system and show that the proposed scheme achieves full diversity order. Simulation results illustrate that performance of the system in terms of bit error probability is better than some well-known scenarios and is close to some scenarios with ideal assumptions. Manuscript profile -
Open Access Article
345 - Object Transportation by a Multi-Robot Distributed System Using a Compound Architecture
T. Hekmatfar T. HekmatfarThis paper addresses the cooperative object transportation by a multi robot distributed system, which is a difficult problem due to path planning and robot cooperation challenges. In this problem, a number of robots should transport an object to a goal point safely whil MoreThis paper addresses the cooperative object transportation by a multi robot distributed system, which is a difficult problem due to path planning and robot cooperation challenges. In this problem, a number of robots should transport an object to a goal point safely while avoiding obstacles and utilizing a proper coordination and cooperation mechanism. The proposed method has a two-layer structure which benefits from both centralized and decentralized architectures. The global level takes advantage of full knowledge of environment to plan an optimal path using the new Optimally-Connect Random Tree (ORT) method, and the local level performs some local processes to reduce the system’s overall processing load and cost and increase its robustness. The required coordination between the robots is realized via radio communication, and for local path planning of the robots a combination of potential fields and TangentBug algorithms has been used. The proposed method has been implemented on multiple KUKA youBot mobile manipulators in the Webots simulation software, and its performance has been evaluated through various experimentations and the results of implementing and comparing the ORT and Rapidly-exploring Random Trees (RRT) showed the advantage of the proposed method. Manuscript profile -
Open Access Article
346 - Estimation of Causality Coefficients in Strategy Maps Using Gravitational Search-Based Learning of Fuzzy Cognitive Maps
A. Jahanbeigi A. Jahanbeigi M. RohaniMore than two decades ago, the balanced scorecard method was proposed to control and monitor the strategy of organizations. The most important outcome of this method is the strategy map. The causal relations among strategic goals (SGs) are established in this map which MoreMore than two decades ago, the balanced scorecard method was proposed to control and monitor the strategy of organizations. The most important outcome of this method is the strategy map. The causal relations among strategic goals (SGs) are established in this map which can help managers in decision making process. To have a precise strategy map, it is necessary to estimate the strengths of each causal relation correctly. So, the estimation of causal coefficients has attracted research interest in forming strategy maps. In this way, DEMATEL and Delphi are two well-known methods that are based on the experts’ opinion. However, these opinions are not exact in the complex business fields; so, the computational intelligence (CI) algorithms have been employed for more precise estimation of causality coefficients. In this study, the relations among SGs and their coefficients have been provided by the experts of a banking institution as the input of the proposed method. The main purpose of this study is to improve the precision of causal coefficients using a CI-based algorithm. For this purpose, the strategy map is decomposed into multiple fuzzy cognitive maps (FCMs) and then, the gravitational search algorithm (GSA) is employed for FCM training. In this way, two objective functions are used for determining the optimal value of causality coefficients. The first objective function is employed for reducing error in the prediction of SG realization percentages. The second objective function keeps causal coefficients in the intervals determined by the experts. Experimental results show that the total error of proposed model is lower than the expert-based model. In addition, GSA performs better than the following algorithms in finding the global optimum point in this real-world case study: particle swarm optimization and ant colony optimization. Manuscript profile -
Open Access Article
347 - Leaning the Structure of Bayesian Networks Using Learning Automata
M. R. Mollakhalili Meybodi M. R. MeybodiThe structure of a Bayesian network represents a set of conditional independence relations that hold in the domain. Learning the structure of the Bayesian network model that represents a domain can reveal in sights into its underlying causal structure. Automatically lea MoreThe structure of a Bayesian network represents a set of conditional independence relations that hold in the domain. Learning the structure of the Bayesian network model that represents a domain can reveal in sights into its underlying causal structure. Automatically learning the graph structure of a Bayesian network is a challenge pursued within artificial intelligence studies. In this paper, a new algorithm based on learning automata is proposed for learning the structure of the Bayesian networks. In this algorithm, automata is used as a tool for searching in structure’s space (DAG’s space) of the Bayesian networks. The mathematical behavior of the proposed algorithm is studied. Manuscript profile -
Open Access Article
348 - Multi-Human Face Detection Using Gabor Filters and Neural Networks in Internet Images
R. Mohammadian M. MahloujiThis paper presents a new method for multi human face detection from frontal view in internet images with complex background. The main goal is to reduce false acceptance error rate using feed forward back propagation multilayer perceptron neural network and Gabor energy MoreThis paper presents a new method for multi human face detection from frontal view in internet images with complex background. The main goal is to reduce false acceptance error rate using feed forward back propagation multilayer perceptron neural network and Gabor energy feature in the frequency domain. In the proposed method, the false acceptance error extremely decreased using a combination of three operations; introducing a new preprocessing algorithm to increase the quality of Gabor energy feature, performing two step monitoring on the input and output images, and utilizing three indexes of facial components recognition in Gabor energy output. In this paper, a new image database namely RFD is collected from internet images including 583 non repetitive face images and 9961 non face images with size of 192×168. The face detection accuracy of the proposed method on RFD images is 88.16% with false acceptance rate of 0.48% or 48 false acceptances only, while Viola-Jones algorithm has 124 false acceptances. Therefore, the false acceptance error of the proposed method has reduced by 2.5 times compared to that of Viola-Jones algorithm. Manuscript profile -
Open Access Article
349 - Fusion of Neural Networks Based on Negative Correlation Learning for Offline Handwritten Word Recognition
S. A. A. Abbaszadeh Arani E. KabirIn this study, an ensemble classification method, based on negative correlation learning, is used for holistic recognition of handwritten words with limited vocabulary. In this method, training data set, after preprocessing and feature extraction, is applied to the base MoreIn this study, an ensemble classification method, based on negative correlation learning, is used for holistic recognition of handwritten words with limited vocabulary. In this method, training data set, after preprocessing and feature extraction, is applied to the base Multilayer Perceptron classifiers. These classifiers are trained by negative correlation learning to make them diverse. Features extracted from a test input are applied to the base classifiers, which produce somehow diverse outputs. By combining these outputs, the final output of the system is obtained. For experiments, three feature sets based on zoning, gradient image and contour chain code are extracted from the images. In experiments, performed on 775 images of 31 Province centers from "Iranshahr" dataset, when gradient-based features were used to train 6 Multilayer Perceptron classifiers by negative correlation, by Fusion the outputs of these classifiers through voting, an average recognition rate of 96.10 percent is achieved. Manuscript profile -
Open Access Article
350 - Botnet Detection Based on Computing Negative Reputation Score by Use of a Clustering Method and DNS Traffic
R. Sharifnyay Dizboni A. Manafi MurkaniToday, botnets are known as one of the most important threats against Internet infrastructure. A botnet is a network of compromised hosts (bots) remotely controlled by a so-called botmaster through one or more command and control (C&C) servers. Since DNS is one of the m MoreToday, botnets are known as one of the most important threats against Internet infrastructure. A botnet is a network of compromised hosts (bots) remotely controlled by a so-called botmaster through one or more command and control (C&C) servers. Since DNS is one of the most important services on Internet, botmasters use it to resistance their botnet. By use of DNS service, botmasters implement two techniques: IP-flux and domain-flux. These techniques help an attacker to dynamically change C&C server addresses and prevent it from becoming blacklisted. In this paper, we propose a reputation system used a clustering method and DNS traffic for online fluxing botnets detection .we first cluster DNS queries with similar characteristics at the end of each time period. We then identify hosts that generate suspicious domain names and add them to a so-called suspicious group activity matrix. We finally calculate the negative reputation score of each host in the matrix and detect hosts with high negative reputation scores as bot-infected. The experimental results show that it can successfully detect fluxing botnets with a high detection rate and a low false alarm rate. Manuscript profile -
Open Access Article
351 - Classification of Hyperspectral Images Using Cluster Space Linear Discriminant Analysis and Small Training Set
M. Imani H. GhassemianThe hyperspectral images allow us to discriminate between different classes with more details. There are lots of spectral bands in hyperspectral images. On the other hand, the limited number of available training samples causes difficulties in classification of high dim MoreThe hyperspectral images allow us to discriminate between different classes with more details. There are lots of spectral bands in hyperspectral images. On the other hand, the limited number of available training samples causes difficulties in classification of high dimensional data. Since the gathering of training samples is hard and time consuming, feature reduction can considerably improve the performance of classification. So, feature extraction is one of the most important preprocessing steps in analysis and classification of hyperspectral images. Feature extraction methods such as LDA have not good efficiency in small sample size situation. A supervised feature extraction method is proposed in this paper. The proposed method, which is called cluster space linear discriminant analysis (CSLDA), without obtaining the label of testing samples and just with doing a clustering on testing data, finds the relationship between training and testing samples. Then, it uses the power of unlabeled samples together with training samples for estimation of within-class and between-class scatter matrices. The CSLDA improves the classification accuracy particularly in multimodal hyperspectral data. The experimental results on urban and agriculture hyperspectral images show the better performance of CSLDA compared to popular feature extraction methods such as LDA, GDA, and NWFE using limited number of training samples. Manuscript profile -
Open Access Article
352 - Onset Detection for Tar Solo Based on Pitch and Energy Features
B. Farrokhi E. KabirThis paper develops a new method of onset detection for the Tar, a traditional Iranian musical instrument. The proposed method is based on both types of pitch and energy features and an adaptive peak picking algorithm is utilized for primary onset detection. An improved MoreThis paper develops a new method of onset detection for the Tar, a traditional Iranian musical instrument. The proposed method is based on both types of pitch and energy features and an adaptive peak picking algorithm is utilized for primary onset detection. An improved template matching method is used to detect fundamental frequencies and finally, onsets are tagged based on primary onsets and fundamental frequencies. This step is especially useful to detect the reaz, repeatedly played notes with the same frequency and short durations. For the evaluation of the method, a data set with predetermined onsets was produced and the results were compared with an energy based method explained in terms of F measure. Manuscript profile -
Open Access Article
353 - Linearization of Power Amplifier with Method of the Modified Feed Forward
M. R. Motavalli Kasmaie M. R. Motavalli KasmaieThis paper offers a modified circuit for improving linearization of power amplifier with based on the model of the Feed Forward circuit amplifier. With the help of mathematical model for the single power amplifier, the circuit is simulated und a demonstrator is built an MoreThis paper offers a modified circuit for improving linearization of power amplifier with based on the model of the Feed Forward circuit amplifier. With the help of mathematical model for the single power amplifier, the circuit is simulated und a demonstrator is built and measured. it is used a complex Taylor series for modeling the power amplifier by the approximation of the amplitude transfer function and the level-dependence of the transmission-phase of the power amplifier and can be understood as a simplified form of Volterra series. In our proof of concept experiment, we verified the concept but also found that the adjustment of the circuit is critically dependent on the drive conditions and linearization is achieved only for a narrow range of drive power. The simulation of the total circuit is largely determined by the models for the transmission characteristics of the two power amplifiers. The new circuit in compare with the conventional Feed Forward amplifier, in addition a significant increase in efficiency to minimize the power of the distortion signal 3IMD for large driving amplitude (large signals). Manuscript profile -
Open Access Article
354 - Detection of Wind Aerodynamic Turbulence and Gear Tooth Breaks in Wind Turbine Gearboxes Using Wavelet Function
A. Ghabel A. Akbari ForodIn order to improve power quality, the detection and identification of factors involved in reducing power quality are paramount. One of the main factors in creating flicker and harmonics in the system connected to the wind turbines are wind aerodynamic turbulences and w MoreIn order to improve power quality, the detection and identification of factors involved in reducing power quality are paramount. One of the main factors in creating flicker and harmonics in the system connected to the wind turbines are wind aerodynamic turbulences and wind turbines mechanical errors. In this paper the mathematical equations of turbulence wind shadow and wind shear and mechanical equations of Gear Tooth Breaks in Wind Turbine Gearboxes have been evaluated accurately using the MATLAB simulation. The continued impact of the disturbances on the output parameters of the network is observed. Also, it is shown that these disturbances can be identified and classified properly by wavelet function. Manuscript profile -
Open Access Article
355 - Detection of Wind Aerodynamic Turbulence and Gear Tooth Breaks in Wind Turbine Gearboxes Using Wavelet Function
A. Ghabel A. Akbari ForodIn order to improve power quality, the detection and identification of factors involved in reducing power quality are paramount. One of the main factors in creating flicker and harmonics in the system connected to the wind turbines are wind aerodynamic turbulences and w MoreIn order to improve power quality, the detection and identification of factors involved in reducing power quality are paramount. One of the main factors in creating flicker and harmonics in the system connected to the wind turbines are wind aerodynamic turbulences and wind turbines mechanical errors. In this paper the mathematical equations of turbulence wind shadow and wind shear and mechanical equations of Gear Tooth Breaks in Wind Turbine Gearboxes have been evaluated accurately using the MATLAB simulation. The continued impact of the disturbances on the output parameters of the network is observed. Also, it is shown that these disturbances can be identified and classified properly by wavelet function. Manuscript profile -
Open Access Article
356 - 3D Finite Element Analysis of MV Three-Phase Transformer Mechanical Forces Effected by Inrush Current Based on a Novel Winding Structure
A. Nasiri A. Ranjbar F. Faghihi S. SoleymaniTransient mechanical force in transformer induced critical mechanical stress on windings and transformers in radial and axial directions. In this paper, impact of force’s within transient inrush current duration on MV three phase transformer with propose novelty windin MoreTransient mechanical force in transformer induced critical mechanical stress on windings and transformers in radial and axial directions. In this paper, impact of force’s within transient inrush current duration on MV three phase transformer with propose novelty winding configuration (S-P-S) to considered. In order to forces analysis, a 3-D model of three phase transformer developed by use Ansoft Maxwell V15.0. Magnetic vector potential, Magnetic flux density and electro-mechanical force’s of SPS-type and conventional-type of configuration windings and transformer calculated from a 3D finite element model. Based on the comparison and result analysis, proposed an optimal configuration for transformer winding in order to trade-off and minimization of electromechanical force’s in the transient inrush current state. Manuscript profile -
Open Access Article
357 - Optimal Power Flow in the Smart Distribution Grid Based on the Optimal Load Curtailment and Voltage Stability Index Improvement
S. Derafshi Beigvand H. AbdiSmart grid is the result of enabling consumers in the power system in order to play an effective role in the power system planning and operation processes. The communication, control, and measurement infrastructures create a two-way intelligent communication between use MoreSmart grid is the result of enabling consumers in the power system in order to play an effective role in the power system planning and operation processes. The communication, control, and measurement infrastructures create a two-way intelligent communication between users and the network which facilitates the effective implementation of demand response programs (DRPs) such as the direct load control (DLC). In this paper, optimal power flow as an important research topic in the power systems is presented based on DLC and a new voltage stability index. Simple calculations, voltage dependence, indirect dependence to the load and network topology, and also not reducing the network into a two-bus equivalent model, have made the proposed voltage stability index more applicable to real-time calculations considering the load pattern changes. In the proposed method, the optimal load curtailment in some selected loads of the network, with the aim of improving the voltage stability index of the weakest bus is evaluated. Finally, in order to show the effectiveness of the suggested method, it is applied to a 69-bus radial distribution network as an intelligent system. Manuscript profile -
Open Access Article
358 - Analytical Stator Design for Reducing the Cogging Torque in Surface-Mounted PM Motors
M. R. Alizadeh Pahlavani V. Zamani FaradonbeWe present an analytical method for the calculation of cogging torque in surface permanent-magnet (PM) motors. The cogging torque is calculated by integrating the Maxwell stress tensor inside the air gap. The stator design techniques are applied to reduce the cogging to MoreWe present an analytical method for the calculation of cogging torque in surface permanent-magnet (PM) motors. The cogging torque is calculated by integrating the Maxwell stress tensor inside the air gap. The stator design techniques are applied to reduce the cogging torque in SPM motors. The used techniques are stator dummy slots, teeth pairing and stator slot skewing. The direct search method is used to find the optimum geometry in the mentioned methods. Finally, the validity of the proposed model and the obtained results are verified with Finite Element Analysis. Manuscript profile -
Open Access Article
359 - Multi-Objective Optimization of Surface-Mounted PM Machines Using an Analytical Model for the Pole-Shifting Method
V. Zamani Faradonbe S. Taghipour BoroujeniIn the presented work an analytical model is developed for the pole-shifting method in the surface-mounted PM machine at no-load condition. The machine cogging torque and the harmonic spectrum of the air gap flux density are most no-load indexes of the machine performan MoreIn the presented work an analytical model is developed for the pole-shifting method in the surface-mounted PM machine at no-load condition. The machine cogging torque and the harmonic spectrum of the air gap flux density are most no-load indexes of the machine performance. It is shown that, although, the pole-shifting reduces the machine cogging torque; it destroyed the half-odd symmetry in the PMs and produces even harmonics in the air gap flux density. The even harmonics of the air gap flux density, results in undesired torque pulsations. Using the developed analytical model and the direct search method a multi-objective optimization is carried out for the machine cogging torque and the total harmonic distortion of the air gap flux density. Since, the considered variables are not in a same unite; a normalized technique is applied. Finally, the developed model and the obtained results are verified by finite element analysis. Manuscript profile -
Open Access Article
360 - Application of Wide-Area Synchrophasor Measurement System to Alleviate Blackouts by Rotor Angle Instability
S. Kiarostami S. KiarostamiIn this paper, a Wide-Area protection system to deal with rotor angle instabilities is proposed. Firstly, a system blackout model is developed and secondly the extreme contingencies that lead to large blackouts are extracted. Initiating events that ultimately lead to ro MoreIn this paper, a Wide-Area protection system to deal with rotor angle instabilities is proposed. Firstly, a system blackout model is developed and secondly the extreme contingencies that lead to large blackouts are extracted. Initiating events that ultimately lead to rotor angle instabilities are determined by artificial neural network (ANN). Coherent generators are detected by an algorithm using the data presented by phasor measurement units (PMUs). Based on identification of coherent generators, the power system is split into stable islands by disconnecting the weak interconnecting lines and load shedding. The performance of the proposed strategy is verified by simulations on the IEEE 39-bus sample power system. Manuscript profile -
Open Access Article
361 - Upper and Lower Bounds on ICI Power of FrFT-OFDM Systems in Frequency Selective Time Varying Channels
Z. Mokhtari M. SabbaghianIn this paper, we study the inter carrier interference (ICI) in fractional Fourier transform based orthogonal frequency division multiplexing (FrFT-OFDM) systems. In this analysis, we derive tight upper and lower bounds for ICI power of FrFT-OFDM systems in doubly dispe MoreIn this paper, we study the inter carrier interference (ICI) in fractional Fourier transform based orthogonal frequency division multiplexing (FrFT-OFDM) systems. In this analysis, we derive tight upper and lower bounds for ICI power of FrFT-OFDM systems in doubly dispersive channels. These bounds have considerably simpler expressions than the exact ICI formula. Thus, they provide deep and useful insight into the effect of Doppler frequency, symbol duration, channel delay spread, and angle of transform on the ICI power. This analysis confirms that in the special case of flat fast fading channels the FrFT-OFDM and Fourier transform based OFDM (FT-OFDM) systems exhibit analogous performance while in doubly dispersive channels FrFT-OFDM can achieve better performance than single carrier (SC) and FT-OFDM, if the angle of transform is selected accurately. Manuscript profile -
Open Access Article
362 - Asymptotically Optimal Online Solutions for Energy Harvesting Communication Systems
M. Mohassel Feghhi A. AbbasfarEnergy harvesting (EH) has emerged as a promising technique for green communications and it is a novel technique to prolong the lifetime of the wireless networks with replenishable nodes. In this paper, we investigate the online resource allocation for a large class of MoreEnergy harvesting (EH) has emerged as a promising technique for green communications and it is a novel technique to prolong the lifetime of the wireless networks with replenishable nodes. In this paper, we investigate the online resource allocation for a large class of objective functions in the EH communication systems, which are asymptotically optimal. It is shown that the solution is obtained by only considering the average EH pattern, irrespective of its stochastic dynamics. This optimal solution neither has the complexity of dynamic programming solutions, nor uses the non-causal knowledge about EH pattern. Also, some practical numerical examples for objective functions, which are utilized in communication systems, are considered and general results are derived for them. Moreover, simulation results validate our theoretical findings and show the accuracy of asymptotic theoretical curves for the transmission periods, which are used in practice. Manuscript profile -
Open Access Article
363 - Hexagonal-Circular Photonic Crystal Fiber with Low Chromatic Dispersion, Low Confinement Loss, and Low Nonlinearity
s. olyaee M. seifouri A. nikoosohbatPhotonic crystal fibers (PCFs) as waveguides with low dispersion, low confinement loss, and low nonlinearity can be used in optical telecommunication systems. In this paper, a hexagonal-circular photonic crystal fiber is proposed. In the first design, we present a hexag MorePhotonic crystal fibers (PCFs) as waveguides with low dispersion, low confinement loss, and low nonlinearity can be used in optical telecommunication systems. In this paper, a hexagonal-circular photonic crystal fiber is proposed. In the first design, we present a hexagonal PCF with 70 ps/nm.km dispersion at 1550 nm wavelength. The confinement loss and nonlinearity of this structure are respectively obtained as 0.6×10-12dB/cm and 8.988 W-1km-1. In the second design, by improving th e primary structure as hexagonal-circular PCF, the nearly zero dispersion is obtained. The simulation results show that the confinement loss and nonlinearity of the improved structure are 8×10-11 dB/cm and 7.956 W-1km-1, respectively. Manuscript profile -
Open Access Article
364 - Particle Filter with Adaptive Observation Model
Particle filter is an effective tool for the object tracking problem. However, obtaining an accurate model for the system state and the observations is an essential requirement. Therefore, one of the areas of interest for the researchers is estimating the observation fu MoreParticle filter is an effective tool for the object tracking problem. However, obtaining an accurate model for the system state and the observations is an essential requirement. Therefore, one of the areas of interest for the researchers is estimating the observation function according to the learning data. The observation function can be considered linear or nonlinear. The existing methods for estimating the observation function are faced some problems such as: 1) dependency to the initial value of parameters in expectation-maximization based methods and 2) requiring a set of predefined models for the multiple models based methods. In this paper, a new unsupervised method based on the kernel adaptive filters is presented to overcome the above mentioned problems. To do so, least mean squares/ recursive least squares adaptive filters are used to estimate the nonlinear observation function. Here, given the known process function and a sequence of observations, the unknown observation function is estimated. Moreover, to accelerate the algorithm and reduce the computational costs, a sparsification method based on approximate linear dependency is used. The proposed method is evaluated in two applications: time series forecasting and tracking objects in video. Results demonstrate the superiority of the proposed method compared with the existing algorithms. Manuscript profile -
Open Access Article
365 - Particle Filter with Adaptive Observation Model
H. Haeri H. Sadoghi YazdiParticle filter is an effective tool for the object tracking problem. However, obtaining an accurate model for the system state and the observations is an essential requirement. Therefore, one of the areas of interest for the researchers is estimating the observation fu MoreParticle filter is an effective tool for the object tracking problem. However, obtaining an accurate model for the system state and the observations is an essential requirement. Therefore, one of the areas of interest for the researchers is estimating the observation function according to the learning data. The observation function can be considered linear or nonlinear. The existing methods for estimating the observation function are faced some problems such as: 1) dependency to the initial value of parameters in expectation-maximization based methods and 2) requiring a set of predefined models for the multiple models based methods. In this paper, a new unsupervised method based on the kernel adaptive filters is presented to overcome the above mentioned problems. To do so, least mean squares/ recursive least squares adaptive filters are used to estimate the nonlinear observation function. Here, given the known process function and a sequence of observations, the unknown observation function is estimated. Moreover, to accelerate the algorithm and reduce the computational costs, a sparsification method based on approximate linear dependency is used. The proposed method is evaluated in two applications: time series forecasting and tracking objects in video. Results demonstrate the superiority of the proposed method compared with the existing algorithms. Manuscript profile -
Open Access Article
366 - Sentiment Analysis of Persian Documents using Optimal Transform Domain
A. Pourmasoumi H. Sadoghi Yazdi H. Ghaemi Z. DelkhastehWith development of web-based interactions such as social networks, personal blogs, surveys and user comments, sentiment analysis and opinion mining has become an important research domain in computer science. Up to now, many approaches have been proposed for analysis o MoreWith development of web-based interactions such as social networks, personal blogs, surveys and user comments, sentiment analysis and opinion mining has become an important research domain in computer science. Up to now, many approaches have been proposed for analysis of sense using machine learning and natural language processing techniques. In this paper, we used the distribution of words in the collection of documents as new criteria for analyzing sentiment. In proposed approach, we model an optimal transform domain over words distribution with two goals: maximizing spectral energy of class at low frequencies and maximizing spectral energy of at high frequencies. Using optimal transform domain, we can map data from frequency domain into Fourier domain and easily distinguish optimism and pessimism patterns. For this purpose, we use samples’ profiles of class which have low-frequency components. Assuming the contrast of the spectrum of two classes and, maximizing the spectral energy of class will be satisfied. We have performed this approach for English and Persian documents. Manuscript profile -
Open Access Article
367 - A Goal-Based Approach for the Holonification of Holonic Multi-Agent Systems
Ahmad Esmaeili N. Mozayani M. R. Jahed MotlaghHolonic structures are a hierarchical formation of holons that are developed and used for the purpose of restricting interaction domains, reducing uncertainty, or forming the high level goals of multi-agent systems, in such a way that the system benefits a high degree o MoreHolonic structures are a hierarchical formation of holons that are developed and used for the purpose of restricting interaction domains, reducing uncertainty, or forming the high level goals of multi-agent systems, in such a way that the system benefits a high degree of flexibility and dynamism in response to environmental changes. Although the holonic multi-agent systems are extensively used in modeling and solving complex problems, most of its prerequisites, like forming the body holons and dynamically controlling its structure, use very simple application-specific models. This is due to the immaturity of the research literatures in this field. In this article, an endeavor is made to propose a goal-based approach for the formation of holonic structures, using the concepts in social science and organizational theory. The use of concepts like role, skill, and goal structures, makes the proposed method possible to be used in wide range of applications. In order to demonstrate the capabilities of the method and also the way it can be applied in real world problems, a test bed based on the application of wireless sensor networks in object tracking is designed and presented. In this application, the sensors, which are distributed in the environment as simple agents, using holonic structures, are responsible for the track of any alien objects that enter and move in the environment. According to the empirical results of the simulations, the proposed holonic approach has provided successful performance in terms of tracking quality and energy consumption of the sensors. Manuscript profile -
Open Access Article
368 - A Novel Energy-Efficient Algorithm to Enhance Load Balancing and Lifetime of Wireless Sensor Networks
S. Abbasi-Daresari J. AboueiWireless senor networks (WSNs) are widely used for the monitoring purposes. One of the most challenges in designing these networks is minimizing the data transmission cost with accurate data recovery. Data aggregation using the theory of compressive sampling is an effec MoreWireless senor networks (WSNs) are widely used for the monitoring purposes. One of the most challenges in designing these networks is minimizing the data transmission cost with accurate data recovery. Data aggregation using the theory of compressive sampling is an effective way to reduce the cost of communication in the sink node. The existing data aggregation methods based on compressive sampling require to a large number of nodes for each measurement sample leading to inefficient energy consumption in wireless sensor network. To solve this problem, we propose a new scheme by using sparse random measurement matrix. In this scheme, the formation of routing trees with low cost and fair distribution of load on the network significantly reduces energy consumption. Toward this goal, a new algorithm called “weighted compressive data gathering (WCDG)” is suggested in which by creating weighted routing trees and using the compressive sampling, the data belong to all of nodes of each path is aggregated and then, sent to the sink node. Considering the power control ability in sensor nodes, efficient paths are selected in this algorithm. Numerical results demonstrate the efficiency of the proposed algorithm with compared to the conventional data aggregation schemes in terms of energy consumption, load balancing, and network lifetime. Manuscript profile -
Open Access Article
369 - Improving Q-Learning Using Simultaneous Updating and Adaptive Policy Based on Opposite Action
M. Pouyan S. Golzari A. Mousavi Ahmad HatamQ-learning is a one of the most popular and frequently used model-free reinforcement learning method. Among the advantages of this method is independent in its prior knowledge and there is a proof for its convergence to the optimal policy. One of the main limitations of MoreQ-learning is a one of the most popular and frequently used model-free reinforcement learning method. Among the advantages of this method is independent in its prior knowledge and there is a proof for its convergence to the optimal policy. One of the main limitations of this method is its low convergence speed, especially when the dimension is high. Accelerating convergence of this method is a challenge. Q-learning can be accelerated the convergence by the notion of opposite action. Since two Q-values are updated simultaneously at each learning step. In this paper, adaptive policy and the notion of opposite action are used to speed up the learning process by integrated approach. The methods are simulated for the grid world problem. The results demonstrate a great advance in the learning in terms of success rate, the percent of optimal states, the number of steps to goal, and average reward. Manuscript profile -
Open Access Article
370 - A Proposed Method of Decentralized Load Balancing Algorithm in Heterogeneous Cloud Environments
S. Hourali S. Jamali F. HouraliOne of the key strategies to improve the efficiency is load balancing. Choosing the appropriate VM to do any task, is function of various parameters such as the amount of required resources like CPU, memory, the size of VM resource, cost and maturity of VMs. In this pap MoreOne of the key strategies to improve the efficiency is load balancing. Choosing the appropriate VM to do any task, is function of various parameters such as the amount of required resources like CPU, memory, the size of VM resource, cost and maturity of VMs. In this paper, by considering each of these criteria and design objectives such as load balancing, reducing the rate of create new VM, and VM migration, we modeling the problem in terms of effective parameters in performance. Then, we solving this model by using the PROMETHEE method, which is one of the most widely used method for MADM problems. In this method, selecting the best VM occurs based on the value assigned to each of criteria which is calculated based on fuzzy logic. To evaluate the performance of this approach, the necessary simulations have been carried out on CloudSim simulator and shown that the proposed method has better performance compared to FIFO, DLB and WRR methods on average in terms of response time, rate of success tasks, load variation and rate of VM migration. Manuscript profile -
Open Access Article
371 - An Automated Approach for Detection of Vessel Borders and Hard Plaques in Intravascular Ultrasound Images
B. Mehran M. Yazdchi H. PourghasemSegmentation is necessary to determine the boundaries of the vessel. Intravascular ultrasound imaging (IVUS) is used for the diagnosis of coronary artery diseases. In this study, a new method is proposed for segmentation of IVUS images. First preprocessing is done to co MoreSegmentation is necessary to determine the boundaries of the vessel. Intravascular ultrasound imaging (IVUS) is used for the diagnosis of coronary artery diseases. In this study, a new method is proposed for segmentation of IVUS images. First preprocessing is done to convert images from Cartesian coordinates to polar coordinates, remove the catheter in images and speckle noise with Nonlinear Anisotropic Diffusion Filtering. Then, texture features of an image are extracted using Gabor filter, and the image segmentation and determining the vessels boundary will be discussed using active contour without edge for vector value model. Calcium plaques have been determined using phase clustering and the exact boundary of calcium plaques is extracted using active contour model. This method has been tested on thirty images, and the results of the image segmentation have been validated by an expert. The area diffusion between the internal border and the expert’s opinion is 0.4310.236, and the area diffusion between the external border and the expert’s opinion is 0.6530.723. Area diffusion of calcium plaque extracted by the proposed algorithm compared with virtual histology images has been achieved equal to 5.90 percent. Manuscript profile -
Open Access Article
372 - A Fault-Tolerant Routing Algorithm for 3D Networks-on-Chip
M. Taghizadeh Firoozjaee M. Taghizadeh Firoozjaee M. Taghizadeh FiroozjaeeThe performance of Networks-on-Chip is highly dependent to the incorporated routing algorithms. In recent years, many routing algorithms have been proposed for 2D and 3D Networks-on-Chip. In 3D integrated circuits, different devices are stacked through silicon via in wh MoreThe performance of Networks-on-Chip is highly dependent to the incorporated routing algorithms. In recent years, many routing algorithms have been proposed for 2D and 3D Networks-on-Chip. In 3D integrated circuits, different devices are stacked through silicon via in which the vertical connections are vulnerable to manufacturing process variations. Therefore, because of the high impact of faulty links or nodes on the performance of a Network-on-Chip, utilizing a fault-tolerant routing algorithm is of great importance especially for 3D Networks-on-Chip in which the vertical links are more vulnerable. In this paper, a new fault-tolerant routing algorithm called FT-ZXY is proposed to be used in 3D Networks-on-Chip. This routing method is capable of tolerating multiple vertical faulty links in addition to single horizontal faulty links without using any virtual channels thus incurs a very low hardware overhead. Experimental results reveal that the proposed routing algorithm has more reliability compared to the previous designs while incurs less latency and requires lower area and power overheads. Manuscript profile -
Open Access Article
373 - A New Method for Supply Reliability Assessment in Industrial Microgrids Considering Load Growth and Renewable Resources Uncertainty
S. Rahimi Takami R. Hooshmand A. Khodabakhshian A. KhodabakhshianDistributed Generation (DG) resources can effect a lot on the reliability parameters in industrial microgrids. So, reliability evaluation of industrial microgrids is presented in this paper using a proposed composite index in the presence of DG resources and demand resp MoreDistributed Generation (DG) resources can effect a lot on the reliability parameters in industrial microgrids. So, reliability evaluation of industrial microgrids is presented in this paper using a proposed composite index in the presence of DG resources and demand response (DR). This procedure of the reliability assessment is based on sequential Monte Carlo method with respect to the time varying load model. In this paper, wind and photovoltaic generations those are useful renewable generations are used. Since, the output power of these DGs depends on wind speed and solar radiation that are stochastic variables, therefore a number of scenarios have been considered in order to determine the output power per hour for each of them. According to the large number of generated scenarios, scenario reduction method is used based on two conditions that consist of power generation of DGs and load. Here the new composite index represents changes in the SAIFI, SAIDI and EENS indices per each KW of installed DGs. With considering to industrial load growth in the microgrid, a ten-year period is studied and the scheduling is performed in both islanding and grid connected operational modes. The concept of DR is also used in the islanding operational mode. To demonstrate the effectiveness of the proposed method, the approach is applied on a standard IEEE RBTS BUS2 system in the presence of DG resources and the results in different conditions are achieved. Manuscript profile -
Open Access Article
374 - Coordinated Framework for Reconfiguration and Direct Load Control to Meet the Challenges of Distribution Systems Operation
E. Hosseini Mohammad Sadegh Sepasian H. Arasteh V. VahidinasabThe basic approach of this paper is to improve the operational condition of distribution systems by the simultaneous utilization of system reconfiguration and direct load control programs. A Genetic Algorithm (GA) based algorithm is employed to find the optimal states o MoreThe basic approach of this paper is to improve the operational condition of distribution systems by the simultaneous utilization of system reconfiguration and direct load control programs. A Genetic Algorithm (GA) based algorithm is employed to find the optimal states of switches as well as the optimal incentives of the demand response programs. The concept of price elasticity of demand is utilized to illustrate the changes of electricity consumption pattern as a result of customers’ participation in Demand Response (DR). The objective function of the proposed model is network operation costs. In addition, voltage constraints, lines capacity limits and the related constraints of DR programs are considered in the optimization problem. Finally, the effectiveness of the proposed method in reducing operation costs is shown using the 33-bus distribution network. The simulation results show that the coordination of reconfiguration and DR can reduce the operation costs and load shedding requirements in addition to solving lines’ over loading problems. Manuscript profile -
Open Access Article
375 - Bidding Strategy of Virtual Power Plants in Energy and Ancillary Service Markets Considering Multiple Grid Supply Point
H. Nezamabadi M. SetayeshnazarIn this paper the optimal bidding strategy of virtual power plant (VPP) in a joint market of energy and spinning reserve service, coupled with reactive power market is investigated. The proposed bidding strategy model is non-equilibrium based on security-constrained pri MoreIn this paper the optimal bidding strategy of virtual power plant (VPP) in a joint market of energy and spinning reserve service, coupled with reactive power market is investigated. The proposed bidding strategy model is non-equilibrium based on security-constrained price-based unit commitment (SCPBUC), which considers the VPP supply-demand balancing and security constraints. The model is a non-convex mixed-integer nonlinear optimization problem with inter-temporal constraints. It is solved by mixed-integer nonlinear programming (MINLP), and the solution is a single optimal bidding profile for each of the energy, spinning reserve, and reactive power markets. Manuscript profile -
Open Access Article
376 - Designing an Applicable MIMO DC-DC Converter with Multivariable Controller for SMES System
M. R. Alizadeh Pahlavani S. Taghipour BroujeniIn modern power systems, utilization of renewable energy sources makes some difficulties for the power grid. One of these problems is shortage of electrical power during conditions which renewable energy sources cannot generate electrical power. For example, during shad MoreIn modern power systems, utilization of renewable energy sources makes some difficulties for the power grid. One of these problems is shortage of electrical power during conditions which renewable energy sources cannot generate electrical power. For example, during shading conditions, the output power of the PV array is negligible. Using SMES (Superconducting Magnetic Energy Storage) systems is one of the applicable solutions which has been proposed to solve mentioned problem. In SMES system, energy is stored at high power inductances and during critical conditions; this power can be delivered to the load. One of the important parts of SMES systems is Multi input - Multi Output (MIMO) DC-DC converter. In this paper, at first step, one topology has been designed for the MIMO DC-DC converter. This topology has remarkable advantages such as fewer electrical elements and better controllability than other topologies. In the second part of this paper, based on multivariable controller strategy, an efficient controller has been designed for the SMES system which can set the output voltages of DC-DC converter at predetermined values. The most important feature of proposed controller is its efficiency at different conditions which some of these conditions make serious problems for conventional controllers. Generally, the objective of this paper is designing one SMES systems with an appropriate controller, which can regulate the output voltages at different conditions. Manuscript profile -
Open Access Article
377 - Design and Implementation of a New Adaptive Sliding Mode for Current Control in Islanding Mode Operation
M. M. Ghanbarian M. Nayeripour A. H. RajaeiThis paper proposes a new modified adaptive sliding mode controller in order to control the inverters of DGS in the voltage and current (power) control modes in a microgrid. An observer is used to estimate the uncertain parameters in controller design and considering t MoreThis paper proposes a new modified adaptive sliding mode controller in order to control the inverters of DGS in the voltage and current (power) control modes in a microgrid. An observer is used to estimate the uncertain parameters in controller design and considering these estimated values, the controller is adapted to new condition. In the power management strategy, one of inverter controls the voltage and the other inverter controls the load current and balances the active power. Due to delays in startup power electronic converter and sliding mode controller, the result of controller implementation with classical controllers does not meet the requirement and so, considering these delays with adaptive controller, the performance will be improved considerably and the reference signal will be tracked with lower steady state error in comparison with classical sliding mode controller. Moreover, this controller reduces the total harmonic distortion and improves the rms and peak value tracking. Implementation of system using DSP/TMS320F28335 as well as MATLAB simulation validates the performance of system in different conditions. Manuscript profile -
Open Access Article
378 - Temperature Management in 3D Network-on-Chips Using Simulated Annealing-Based Task Migration
M. Mohebbi Moghaddam S. H. Mir Mohammadi S. H. Mir MohammadiCombination of 3D stacking and network-on-chip (NoC), known as 3D NoC, has several advantages such as reduced propagation delay, chip area and interconnect, and power consumption, and bandwidth increase. Despite these advantages, 3D stacking causes the increased power d MoreCombination of 3D stacking and network-on-chip (NoC), known as 3D NoC, has several advantages such as reduced propagation delay, chip area and interconnect, and power consumption, and bandwidth increase. Despite these advantages, 3D stacking causes the increased power density per chip area and subsequently increases the chip temperature. Temperature increase causes performance degradation and reliability reduction. Therefore, design of temperature management algorithms is essential for these systems. In this paper, we propose a task migration scheme for thermal management of 3D NoCs. The process of migration destinations for hot spots is an NP-complete problem which can be solved by using heuristic algorithms. To this end, we utilize a simulated annealing method in our algorithm. We consider migration overhead in addition to the temperature of the processing elements in migration destination selection process. Simulation results indicate up to 28 percentage peak temperature reduction, on average, for the benchmark that has the largest number of tasks. The proposed scheme has low migration overhead. Manuscript profile -
Open Access Article
379 - Determination of Private DG Energy Sourced Electricity Purchasing Price by DISCOs with Considering the Capacitor Placement and ENS Costs
B. Rezaei M. S. Ghazizadeh V. VahidinasabAfter the restructuring and privatization of the electricity industry, the main purpose of the DISCOs is to increase their income, according to the existing laws. The existence of private distributed generation (DG) units in the distribution network and the possibility MoreAfter the restructuring and privatization of the electricity industry, the main purpose of the DISCOs is to increase their income, according to the existing laws. The existence of private distributed generation (DG) units in the distribution network and the possibility to buy additional electricity of DG with a less price than the wholesale market, capacitor installation, payment of energy not supplied to customers, the cost of energy losses and voltage drop problem in the distribution network, has created opportunities and challenges for DISCOs that are looking for adopting a suitable strategy for higher profits. In this paper, as the first scenario, it is depicted that when there is no DG unit in the network the increasing in the DISCO’s income is achievable by optimal allocation of both fixed and switched capacitors. In the second scenario, this is done by determination of the maximum acceptable DG energy sourced electricity purchasing price with a known location, and in the third one, by determination of the purchase price from the DG while the locating has been done by the DISCO. Simulation studies are done on a 20kV 18-bus distribution network in Rasht city, and the results are presented at the end. Manuscript profile -
Open Access Article
380 - Optimal Operation of Energy Hub Using Model Predictive Control
Z. Hashemi A. Ramezani M. Parsa-MoghaddamEnergy hub (EH) concept is widely proposed for integrating different types of energy infrastructures. EH physically consists of some storage systems and converters receiving energy from multiple sources immediately from its upper grids and provides energy services for u MoreEnergy hub (EH) concept is widely proposed for integrating different types of energy infrastructures. EH physically consists of some storage systems and converters receiving energy from multiple sources immediately from its upper grids and provides energy services for ultimate consumers. In this paper a state space model for EH system is proposed. Due to the dynamic behavior loads and the price uncertainties, a Model Predictive Control approach is suggested for optimal performance. The proposed method is studied on a EH that consists of transformer, boiler, CHP, electrical and heat storages considering demand side management. Finally, the simulation results depicts to demonstrate the effectiveness of the proposed method for optimal operation of the EH. Manuscript profile -
Open Access Article
381 - Example-Based single Document Image Super Resolution Using Asynchronous Sequential Gradient Descent Algorithm
A. Abedi E. KabirIn this paper, a new method for resolution enhancement of single document images is presented. The proposed method is example based using an example set of low-resolution and high-resolution training patches. According to the Bayes rule, one function is considered as th MoreIn this paper, a new method for resolution enhancement of single document images is presented. The proposed method is example based using an example set of low-resolution and high-resolution training patches. According to the Bayes rule, one function is considered as the likelihood or data-fidelity term that measures the fidelity of the output high-resolution to the input low-resolution image. As well, three other functions are considered as the regularization terms containing the prior knowledge about the desired high-resolution document image. Three priors which are fulfilled by the regularization terms are bimodality of document images, smoothness of background and text regions, and similarity to the patches in the example set. By minimizing these four energy functions through the iterative procedure of asynchronous sequential gradient descent, the HR image is reconstructed. Instead of synchronous minimization of the linear combination of these functions, they are minimized in order and according to the gradual changes in their values and in the updating HR image. Therefore, determining the coefficients of the linear combination, which are variable for input images, is no longer required. In the experimental results on twenty document images with different fonts, at different resolutions, and with different amounts of noise and blurriness, the proposed method achieves significant improvements in visual image quality and in reducing the computational complexity. Manuscript profile -
Open Access Article
382 - Evaluation of Performance, Reliability and Security for Share-Data, Object-Oriented and Pipe and Filter Styles
H. Banki H. BankiA desirable software application should be able to provide the quality attributes required by the system, as well as the functional requirements. Software architecture styles have a significant effect on the quality attributes of the designed software as well as its spe MoreA desirable software application should be able to provide the quality attributes required by the system, as well as the functional requirements. Software architecture styles have a significant effect on the quality attributes of the designed software as well as its specification and decomposition.) The quantity evaluation and analysis of this effectiveness rate result in the selection of the most appropriate style for designing the architecture. In this paper, a method based on the Colored Petri Net is proposed to quantitatively evaluate three candidate attributes of the software architectural styles called the quality attributes, performance, reliability, and security in three candidate styles named shared-data, object-oriented, and pipe-and-filter software architectural styles. This method has not limitations of the previous-ones in evaluating the quality attributes. In this method, the candidate styles are firstly modeled by using the Colored Petri Net; then, considering the evaluation rules, CPN tools are used to analyze the networks and calculate the exact value of the candidate attributes. At the end, the best candidate style is chosen for implementation through ranking the styles in terms of the satisfaction level of the candidate quality attributes. To present a practical representation using the proposed methodology, the ATM system has been chosen as a case study. Manuscript profile -
Open Access Article
383 - A Novel Extended Mapping of Local Binary Pattern for Texture Classification
M. H. Shakoor M. H. ShakoorTexture classification is one of the important branches of image processing. The main point of texture classification is feature extraction. Local Binary Pattern (LBP) is one of the important methods that are used for texture feature extraction. This method is widely us MoreTexture classification is one of the important branches of image processing. The main point of texture classification is feature extraction. Local Binary Pattern (LBP) is one of the important methods that are used for texture feature extraction. This method is widely used because it has simple implementation and extracts high discriminative features from textures. Most of previous LBP methods used uniform patterns and only one feature is extracted from non-uniform patterns. In this paper, by extending non-uniform patterns a new mapping technique is proposed that extracts more discriminative features from non-uniform patterns. So in spite of almost all of the previous LBP methods, the proposed method extracts more discriminative features from non-uniform patterns and increases the classification accuracy of textures. The proposed method has all of the positive points of previous LBP variants. It is a rotation invariant and illumination invariant method and increase the classification accuracy. The implementation of proposed mapping on Outex dataset shows that proposed method can improve the accuracy of classifications significantly. Manuscript profile -
Open Access Article
384 - Weighted Multi-Level Fuzzy Min-Max Neural Network
R. Davtalab M. A. Balafar M. R. Feizi-DerakhshiIn this paper a weighted Fuzzy min-max classifier (WL-FMM) which is a type of fuzzy min-max neural network is described. This method is a quick supervised learning tool which capable to learn online and single pass through data. WL-FMM uses smaller size with higher weig MoreIn this paper a weighted Fuzzy min-max classifier (WL-FMM) which is a type of fuzzy min-max neural network is described. This method is a quick supervised learning tool which capable to learn online and single pass through data. WL-FMM uses smaller size with higher weight to manipulate overlapped area. According to experimental results, proposed method has less time and space complexity rather than other FMM classifiers, and also user manual parameters has less effect on the results of proposed method. Manuscript profile -
Open Access Article
385 - Integration of Systems in Ultra-Large-Scale Systems Using a Data-Centric Rich Services Approach
S. Shokrollahi F. Shams J. EsmaeiliAn Ultra-Large-Scale (ULS) system is generally considered as a system-of-systems that have many crosscutting concerns. As the size of a system-of-systems grows, and interoperability demands between the sub-systems are increased, achieving more scalable and dynamic integ MoreAn Ultra-Large-Scale (ULS) system is generally considered as a system-of-systems that have many crosscutting concerns. As the size of a system-of-systems grows, and interoperability demands between the sub-systems are increased, achieving more scalable and dynamic integration of sub-systems becomes a major challenge. In this integration, each sub-system has its own domain that may have independent policies. Over the last few years, the notion of Rich Services has emerged as a technique for facilitating integration of systems. In this paper, a Data-Centric Rich Services (DCRS) approach is proposed to improve the dynamicity, scalability, and security of Rich Services in a ULS system. In the proposed approach, a two-layer and data-centric middleware is presented to manage orchestration of Rich Services. The lower layer is a Data Distribution Service (DDS) middleware used for data-centric, publish-subscribe, real-time, and loosely-coupled communication among Rich Services. The upper layer is used for dynamic and secure configuration and reconfiguration of Rich Services. We also analyze the performance of our approach using simulation-based experiments. Manuscript profile -
Open Access Article
386 - Quantum-Logic Synthesis Using Improved Block-Based Approach
K. Marjoei M. Houshmand M. Saheb Zamani M. SedighiQuantum-logic synthesis refers to generating a quantum circuit for a given arbitrary quantum gate according to a specific universal gate library implementable in quantum technologies. Previously, an approach called block-based quantum decomposition (BQD) has been propos MoreQuantum-logic synthesis refers to generating a quantum circuit for a given arbitrary quantum gate according to a specific universal gate library implementable in quantum technologies. Previously, an approach called block-based quantum decomposition (BQD) has been proposed to synthesize quantum circuits by using a combination of two well-known quantum circuit synthesis methods, namely, quantum Shannon decomposition (QSD) and cosine-sine decomposition (CSD). In this paper, an improved block-based quantum decomposition (IBQD) is proposed. IBQD is a parametric approach and explores a larger space than CSD, QSD, and BQD to obtain best results for various synthesis cost metrics. IBQD cost functions for synthesis are calculated in terms of different synthesis cost metrics with respect to the parameters of the proposed approach. Furthermore, in order to find optimum results according to these functions, IBQD synthesis approach is defined as a constrained-optimization model. The results show that IBQD can lead to the minimum total gate cost among all the proposed approaches for the specific case of 4-qubit quantum circuit synthesis. Moreover, for the first time, the depth costs of the CSD, QSD, BQD, and IBQD synthesis approaches are evaluated and it is shown that IBQD makes a trade-off between the total gates and depth costs for the synthesized quantum circuits. Manuscript profile -
Open Access Article
387 - A Hybrid Access Control Model for CIM-Based SCADA System
P. Mahmoudi Nasr A. Yazdian VarjaniInsider attack is one of the most dangerous threats for the security of a critical infrastructure (CI). An insider attack occurs when an authorized operator misuses his/her permissions in order to perform malicious operations in the CI. Providing too many permissions fo MoreInsider attack is one of the most dangerous threats for the security of a critical infrastructure (CI). An insider attack occurs when an authorized operator misuses his/her permissions in order to perform malicious operations in the CI. Providing too many permissions for an operator may backfire when the operator abuses his/her privileges, either intentional or unintentional. Therefore, an access control model is required to provide necessary permissions in order to prevent malicious operations. In this paper, a hybrid access control model (HAC) has been proposed for CI applications which are monitored and controlled by a CIM (IEC-61970-301 common information model)-based supervisory control and data acquisition system. The proposed HAC is an extension of the mandatory and role-based access control models. In the proposed model, the permissions of an operator will be determined according to the predefined types of responsibilities, grid statuses, activation times of roles, security levels, and their periods of validity. A colored Petri-net is employed to simulate and illustrate the effectiveness of the proposed HAC. Manuscript profile -
Open Access Article
388 - Feature Extraction and Lexicon Expanded in Opinion Mining through Persian Reviews
E. Golpar-Rabooki S. Zarghamifar S. ZarghamifarOpinion mining deals with an analysis of user reviews for extracting their opinions, sentiments and demands in a specific area, which plays an important role in making major decisions in such areas. In general, opinion mining extracts user reviews at three levels of doc MoreOpinion mining deals with an analysis of user reviews for extracting their opinions, sentiments and demands in a specific area, which plays an important role in making major decisions in such areas. In general, opinion mining extracts user reviews at three levels of document, sentence and feature. Opinion mining at the feature level is taken into consideration more than the other two levels due to orientation analysis of different aspects of an area. In this paper, one method is introduced for a feature extraction. The recommended method consists of four main stages. First, opinion-mining lexicon for Persian is created. This lexicon is used to determine the orientation of users’ reviews. Second, the preprocessing stage includes unification of writing, tokenization, creating parts-of-speech tagging and syntactic dependency parsing for documents. Third, the extraction of features uses the method including dependency grammar based feature extraction. Fourth, the features and polarities of the word reviews extracted in the previous stage are modified and the final features' polarity is determined. To assess the suggested techniques, a set of user reviews in both scopes of university and cell phone areas were collected and the results of the method were compared with frequency-based feature extraction method. Manuscript profile -
Open Access Article
389 - A Reduced Switch Count Three-Phase AC/AC Converter with Six IGBTs
M. Heydari A. Yazdian VarjaniReducing the number of semiconductor switches in power electronic converters has been a continuing effort in recent years as a measure to enhance the system reliability and to decrease its size, weight, and component cost. For these reasons, a new reduced switch count t MoreReducing the number of semiconductor switches in power electronic converters has been a continuing effort in recent years as a measure to enhance the system reliability and to decrease its size, weight, and component cost. For these reasons, a new reduced switch count three-phase ac/ac converter is being proposed. Being realized by only six active switches and anti-parallel diodes, the proposed converter topology employs the minimum number of semiconductor devices amongst the converters of its kind. It also features unity power factor, regenerative operation, pulse width modulated output voltage, and sinusoidal input current. The reduced number of switches results in a simplified associated gate drive circuit as well as cooling system which, in turn, may cut the overall manufacture cost, especially in low voltage and low power applications. The modulation scheme of the new converter is developed, and a control algorithm is proposed for the converter’s rectifier side. Moreover, an analysis is performed on the dc link capacitor sizing for the purposes of reducing dc link voltage ripple, balancing the input current, and lowering its THD. The simulation and experimental results corroborate the transient and steady state performance of the proposed converter topology. Manuscript profile -
Open Access Article
390 - A New Method for under Voltage Load Shedding Using Voltage Sensitivity and Load Reactive Power
J. Modarresi E. Gholipour A. KhodabakhshianLoad shedding is the last line of defense for controlling and stabilizing of the power system in the occurrence of a disturbance. Determining the amount and location of the load shedding are issues that the power system operators always have faced In this paper, a new m MoreLoad shedding is the last line of defense for controlling and stabilizing of the power system in the occurrence of a disturbance. Determining the amount and location of the load shedding are issues that the power system operators always have faced In this paper, a new method is proposed for determining the location of under voltage load shedding (UVLS). The proposed method, unlike the previous UVLS methods, uses two different factors to determine the effective location of UVLS. Considering the load reactive power in the process of determination of the UVLS location leads to disconnecting more reactive power during the initial steps of UVLS. Therefore, less active power sheds by the UVLS. To verify the accuracy of the proposed method, the proposed UVLS method accompanied with the method which uses the sensitivity of voltage with respect to the active power are implemented in IEEE 118-bus test system and New England 39 bus system. The obtained results show the superiority of the proposed method. Manuscript profile -
Open Access Article
391 - A Control Strategy Presentation for DG Resources Power Injection in Order to Reduce Harmonic Distortion and Unbalanced Current Simultaneously Based on EMO-RLS Algorithm
F. Faghihi soodabeh Soleymani M. Mollazadeh ShahroudiIn this paper a control technique for renewable energy resources–grid interface is proposed based on extended multi output-recursive least square (EMO-RLS) algorithm considering active power management and harmonic, unbalanced and reactive current components elimination MoreIn this paper a control technique for renewable energy resources–grid interface is proposed based on extended multi output-recursive least square (EMO-RLS) algorithm considering active power management and harmonic, unbalanced and reactive current components elimination. The proposed method is evaluated via MATLAB/SIMULINK software. Firstly, an artificial three-phase unbalanced harmonic signal is generated. It will be transmitted to different estimators for their outputs comparison. The results indicate proper performance of the suggested structure for active harmonic symmetrical components analysis in comparison with the other traditional methods. Also, its dynamic operation in tracking of load current variations is evaluated employing EMO–RLS algorithm for control system of a DG source interface. It illustrates the active power injection to the grid is managed, as well as the harmonic, unbalance and reactive current components, are decreased simultaneously. Manuscript profile -
Open Access Article
392 - A Novel Directional Algorithm for Transmission Line Protection Based on Least Squares Optimization
S. Daniar S. DaniarDirectional protection is a crucial function in advanced transmission network relays. In this paper, a novel directional algorithm for transmission line protection is presented. Proposed algorithm responds to all kind of faults accurately without any dead zone. In this MoreDirectional protection is a crucial function in advanced transmission network relays. In this paper, a novel directional algorithm for transmission line protection is presented. Proposed algorithm responds to all kind of faults accurately without any dead zone. In this scheme, discrimination between internal and external faults will be done precisely even for close relay faults. The proposed algorithm utilizes a close form equation achieved by least squares optimization. Directional protection function is carried out based on proposed algorithm under various conditions such as current transformer saturation, power swing and source capacity changes. Moreover, variation on some parameters such as fault inception and fault resistance has only negligible effects on algorithm performance. Due to employing of low sampling frequency, hardware implementation of the proposed algorithm is not complicated. Algorithm performance is evaluated by applying the field data from Manesht 230kV substation located at Ilam province as well as extracted data form EMTP-RV simulations. Simulation results verify the speed and reliability of the proposed algorithm. Manuscript profile -
Open Access Article
393 - طراحی، بهینهسازی و تحلیل اجزای محدود موتور سنکرون آهنربای دایم نوع دیسکی
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Open Access Article
394 - Design, Optimization, and Finite Element Analysis of a Disk-Type Permanent Magnet Synchronous Motor
This paper proposes to design, optimization and finite element simulation of an axial-flux, super-high speed, permanent magnet motor. The target motor with 0.5 hp rated power at speed of 60,000 rpm is used in a special industrial application. Based on nominal specificat MoreThis paper proposes to design, optimization and finite element simulation of an axial-flux, super-high speed, permanent magnet motor. The target motor with 0.5 hp rated power at speed of 60,000 rpm is used in a special industrial application. Based on nominal specifications of the motor and using analytical relations of motor design, the design calculations, sizing and motor dimensions are investigated. Due to special application of the target motor that needs to the demanded torque with minimum current and copper losses, the dimensions and design specifications of motor is optimized via genetic algorithm based on a torque per ampere cost function. Optimization algorithm determines the optimum value of airgap, permanent magnet flux density, current density and turns number of stator windings. To demonstrate of analytical design and optimization results, using 3-D model of motor in Maxwell software, finite element analysis are carried out in Magneto-static and Transient modes. The FEM simulation results confirm the analytical design results. Moreover, they show the significant reduction in RMS current and copper loss at rated torque. There is a good agreement between the values of torque, motor efficiency, and flux density resulted from both methods. Manuscript profile -
Open Access Article
395 - Design, Optimization, and Finite Element Analysis of a Disk-Type Permanent Magnet Synchronous Motor
S. A. Seyedi Seadati A. Halvaei NiasarThis paper proposes to design, optimization and finite element simulation of an axial-flux, super-high speed, permanent magnet motor. The target motor with 0.5 hp rated power at speed of 60,000 rpm is used in a special industrial application. Based on nominal specificat MoreThis paper proposes to design, optimization and finite element simulation of an axial-flux, super-high speed, permanent magnet motor. The target motor with 0.5 hp rated power at speed of 60,000 rpm is used in a special industrial application. Based on nominal specifications of the motor and using analytical relations of motor design, the design calculations, sizing and motor dimensions are investigated. Due to special application of the target motor that needs to the demanded torque with minimum current and copper losses, the dimensions and design specifications of motor is optimized via genetic algorithm based on a torque per ampere cost function. Optimization algorithm determines the optimum value of airgap, permanent magnet flux density, current density and turns number of stator windings. To demonstrate of analytical design and optimization results, using 3-D model of motor in Maxwell software, finite element analysis are carried out in Magneto-static and Transient modes. The FEM simulation results confirm the analytical design results. Moreover, they show the significant reduction in RMS current and copper loss at rated torque. There is a good agreement between the values of torque, motor efficiency, and flux density resulted from both methods. Manuscript profile -
Open Access Article
396 - Improved Design of Axial Flux Permanent Magnet Synchronous Machines Using PSO Algorithm
M. R. Alizadeh Pahlavani Y. Shahbazi Ayat A. Vahedipaper present an improved design of Axial Flux Permanent Magnet (AFPM) synchronous machines using PSO algorithm that consider practical limits. At first sizing equations is provided and 20 kW AFPM machine is designed, and then output power density is improved using PSO Morepaper present an improved design of Axial Flux Permanent Magnet (AFPM) synchronous machines using PSO algorithm that consider practical limits. At first sizing equations is provided and 20 kW AFPM machine is designed, and then output power density is improved using PSO algorithm. A comparison between improved designed AFPM machine and a prototype constructed machine is performed. Improved machine has more output power density than constructed machine. Then magnetic flux density is calculated based on Maxwell equations analytically. Analytical results have good agreement with finite element method (FEM) results. Use of analytical method takes much less computational time than FEM dose. Manuscript profile -
Open Access Article
397 - Computation of the No-Load Magnetic Flux Density in an Axial Flux Permanent-Magnet Machine Using Semi-3D Analytical Method
M. R. Alizadeh Pahlavani Y. Shahbazi Ayat A. VahediThis paper presents a semi-3D analytical method for calculation of the no-load magnetic flux density in an axial flux permanent-magnet machine. This method is based on a 2-D analytical solution of magnetic field and using modulation function for considering machine’s ra MoreThis paper presents a semi-3D analytical method for calculation of the no-load magnetic flux density in an axial flux permanent-magnet machine. This method is based on a 2-D analytical solution of magnetic field and using modulation function for considering machine’s radial effect on magnetic field distribution. Modulation function is obtained analytical and by use of airgap and leakage permeances. This analytical method takes much less computational time than 3-D finite element method (FEM) does, and is, thus, useful for designing and optimization purposes. Finally, the accuracy of the presented analytical model is validated by comparing its results to corresponding finite-element analysis. Manuscript profile -
Open Access Article
398 - Reliable Transmission based on Imperfect Channel State Information by Optimum Combination of AMC and ARQ
M. Taki R. Mahin ZaeemIn this paper, a new scheme for completely reliable transmission of the information (with an error probability tends to zero) in a wireless communication link will be proposed in which to compensate the effects of fading and multipath, adaptive modulation and coding is MoreIn this paper, a new scheme for completely reliable transmission of the information (with an error probability tends to zero) in a wireless communication link will be proposed in which to compensate the effects of fading and multipath, adaptive modulation and coding is used. Obviously, by the practical forward error correction it is impossible to achieve error free communication. Removing the residual error is by an auto-forwarding system. Of course, if error correction coding capability is weak, number of retransmissions will be increased to the much needed and it severely undermines the system throughput. On the other hands, strong error correction capability needs high block length codes and high transmission power which are limited in practice. In this paper, a method for optimum combination of error correction and auto forwarding is provided. In this paper, link adaptation is based on imperfect channel state information. Numerical results demonstrate efficiency of designed method. Manuscript profile -
Open Access Article
399 - Reliable Transmission based on Imperfect Channel State Information by Optimum Combination of AMC and ARQ
M. Taki R. Mahin ZaeemIn this paper, a new scheme for completely reliable transmission of the information (with an error probability tends to zero) in a wireless communication link will be proposed in which to compensate the effects of fading and multipath, adaptive modulation and coding is MoreIn this paper, a new scheme for completely reliable transmission of the information (with an error probability tends to zero) in a wireless communication link will be proposed in which to compensate the effects of fading and multipath, adaptive modulation and coding is used. Obviously, by the practical forward error correction it is impossible to achieve error free communication. Removing the residual error is by an auto-forwarding system. Of course, if error correction coding capability is weak, number of retransmissions will be increased to the much needed and it severely undermines the system throughput. On the other hands, strong error correction capability needs high block length codes and high transmission power which are limited in practice. In this paper, a method for optimum combination of error correction and auto forwarding is provided. In this paper, link adaptation is based on imperfect channel state information. Numerical results demonstrate efficiency of designed method. Manuscript profile -
Open Access Article
400 - Improving Target Coverage in Visual Sensor Networks by Adjusting the Cameras’ Field-of-View and Scheduling the Cover sets Using Simulated Annealing
B. Shahrokhzadeh M. Dehghan M. R. ShahrokhzadehIn recent years, target coverage is one of the important problems in visual sensor networks. An efficient use of energy is required in order to increase the network lifetime, while covering all the targets. In this paper, we address the Maximum Lifetime with Coverage Sc MoreIn recent years, target coverage is one of the important problems in visual sensor networks. An efficient use of energy is required in order to increase the network lifetime, while covering all the targets. In this paper, we address the Maximum Lifetime with Coverage Scheduling (MLCS) problem that maximizes the network lifetime. We develop a simulated annealing (SA) algorithm that divides the sensors’ Field-of-View (FoV) to a number of cover sets that can cover all the targets and then applies a sleep-wake scheduling algorithm. On the other hand, we have to identify the best possible FoV of sensors according to the targets’ location using rotating cameras, to reduce the solution space and find a near-optimal solution. It also provides the balanced distribution of energy consumption by introducing a new energy and neighbor generating function as well as escaping from local optima. Finally, we conduct some simulation experiments to evaluate the performance of our proposed method by comparing with well-known solutions in the literature such as greedy algorithms. Manuscript profile -
Open Access Article
401 - Optimizing Quantum Circuits by One-Way Quantum Computation Model Based on Pattern Geometries
M. Eslamy M. Saheb Zamani M. Sedighi M. HoushmandA fundamentally quantum model of computation based on quantum entanglement and quantum measurement is called one-way quantum computation model (1WQC). Computations are shown by measurement patterns (or simply patterns) in this model where an initial highly entangled sta MoreA fundamentally quantum model of computation based on quantum entanglement and quantum measurement is called one-way quantum computation model (1WQC). Computations are shown by measurement patterns (or simply patterns) in this model where an initial highly entangled state called a graph state is used to perform universal quantum computations. This graph together with the set of its input and output qubits is called the geometry of the pattern. Moreover, some optimization techniques have been introduced to simplify patterns. Previously, the 1WQC model has been applied to optimize quantum circuits. An approach for parallelizing quantum circuits has been proposed which takes a quantum circuit and then produces the corresponding pattern after performing the proposed optimization techniques for this model. Then it translates the optimized 1WQC patterns back to quantum circuits to parallelize the initial quantum circuit by using a set of rewriting rules. To improve previous works, in this paper, a new automatic approach is proposed to optimize patterns based on their geometries instead of using rewriting rules by applying optimization techniques simultaneously. Moreover, the optimized pattern is translated back to a quantum circuit and then this circuit is simplified by decreasing the number of auxiliary qubits. Results show that the quantum circuit cost metrics of the proposed approach is improved as compared to the previous ones. Manuscript profile -
Open Access Article
402 - EBONC: A New Energy-Aware Clustering Approach Based on Optimum Number of Clusters for Mobile Wireless Sensor Networks
N. Norouzy N. Norouzy M. FazlaliThe energy constraint is one of the key challenges in wireless sensor networks that directly affects the network lifetime. Clustering the sensor nodes is one of the possible approaches to improving the energy efficiency by uniformly distributing the energy consumption a MoreThe energy constraint is one of the key challenges in wireless sensor networks that directly affects the network lifetime. Clustering the sensor nodes is one of the possible approaches to improving the energy efficiency by uniformly distributing the energy consumption among the nodes. The number of appropriate clusters plays an important role in the network throughput. A Large number of clusters imply that packets pass more hops to reach the destination, which results in higher energy consumption. In this paper, we devise an energy and location aware clustering scheme that tries to optimize the number of required clusters. Moreover, the cluster heads are chosen according to their energy levels. The devised scheme partitions the network into concentric circles and calculates the appropriate number of clusters to provide an energy efficient network. A gossiping approach is used to provide information exchange mechanism. The performance of the devised approach is compared with ASH scheme. The simulation results show the network lifetime is improved from 25% to 40% in difference network scenarios. Manuscript profile -
Open Access Article
403 - Classification and Phishing Websites Detection by Fuzzy Rules and Modified Inclined Planes Optimization
M. Abdolrazzagh-NezhadOne of the most important factors influencing the development of information technology on internet is steal the customer information. This security threat is known as phishing. With regarding to review and analysis of the published methods, lake of create the flexibili MoreOne of the most important factors influencing the development of information technology on internet is steal the customer information. This security threat is known as phishing. With regarding to review and analysis of the published methods, lake of create the flexibility to effective attribute selection in the procedure of phishing websites detection, non- dynamic behavior of classification algorithm on target websites and also no attention to reduce the amount of computation for the large number of websites are the main gaps of these methods. To achieve the above-mentioned objectives, a new dynamic mechanism is planned to flexible attribute reduction based on designing threshold change of assessment in this paper. Then inclined planes optimization algorithm is memorized based soft reducing the effect of the embedded memory though high iterations and 12 fuzzy rules are defined in a fuzzy inference system for intelligent dynamiting the algorithm. The experimental results of the proposed intelligent algorithm and the comparison the algorithms with the best available algorithms; demonstrate the ability of the modified inclined planes optimization algorithm to detect phishing websites and satisfy the above mentioned objectives. Manuscript profile -
Open Access Article
404 - Using Contour Information for Body Orientation Estimation in the Image
A. Sebti H. HassanpourPose and orientation of a person relative to the camera are the important and useful information in many applications, including surveillance systems. This information can be used in the behavior analysis of the person. Low quality of the recorded surveillance images, n MorePose and orientation of a person relative to the camera are the important and useful information in many applications, including surveillance systems. This information can be used in the behavior analysis of the person. Low quality of the recorded surveillance images, noisy data and cluttered backgrounds are some of the difficulties in this task. In the existing methods, histogram of orientation gradient (HOG) is used to estimate the orientation. The local properties of HOG is a weakness for orientation estimation. The edge surrounding the object, namely contour, is a useful information for orientation estimation. In this paper we present a general form of a contour. This hyper contour helps us to find the best contour which is matched to image of the person in a hierarchical fashion. These contours generated from a human 3D model. The matched contour as a high-level feature is combined with the low-level feature such as HOG, and considered as the final feature. The proposed feature is a linear combination of several types of contours with respect to different regions of the body. To show the impact of the proposed feature on orientation estimation, a support vector machine is trained on a hybrid feature space and then is evaluated on VIPeR dataset. The experimental results show that the accuracy of the orientation estimation is improved about 4% by using the extended feature. Manuscript profile -
Open Access Article
405 - Radon-Based Text and Script-Independent Gender Detection Using Symbolic Dynamic Filtering
K. Nouri K. Nouri Y. Akbari S. M. Razavi H. Ahmadi TorshiziIn this paper an automated system based on feature extraction of new techniques is presented to detect the gender from the scanned images (off-line) handwriting samples. In order to show the difference between examples of handwriting, in the first step Radon transform i MoreIn this paper an automated system based on feature extraction of new techniques is presented to detect the gender from the scanned images (off-line) handwriting samples. In order to show the difference between examples of handwriting, in the first step Radon transform is taken from the handwritten image, and then each handwriting sample features are extracted using symbolic dynamic filtering. Training and classification of extracted features from the samples are carried out by the multi-layer perceptron neural network. At the end, to determine the effectiveness of the proposed method, experiments are carried out on the Multi Script Handwritten Database (MSHD). In addition, two new challenges of text and script-independent gender detection are explored. Experiences show that the proposed method improves the detection rate compared to the previous works such as fractals, chain codes and textures. The best detection rate is able to achieve accuracy of 84.9% in experiences. Manuscript profile -
Open Access Article
406 - Robust and Fast Aerial and Satellite Image Matching based on Selective Scale and Rotation
M. Safdari P. Moallem M. SattariSIFT method is used to extract keypoints of the image in order to overcome the problems of matching between the satellite and aerial images, including: difference in scale, rotation, brightness intensity and the geometric shape. Unfortunately, SIFT method extracts sever MoreSIFT method is used to extract keypoints of the image in order to overcome the problems of matching between the satellite and aerial images, including: difference in scale, rotation, brightness intensity and the geometric shape. Unfortunately, SIFT method extracts several unfavorable keypoints of satellite and aerial images because of the turbulence and the environmental factors which leads to unreliable matching and increasing complexity. In order to improve the quality of the extracted specific areas and the run time of the algorithm, first the edges of the original images are extracted by Sobel operator and thresholding, then by using the SIFT method, keypoints are extracted from the edge image. After extracting keypoints, using the rBREIF method, that have stability dependence with respect to atmospheric turbulence and rotation, descriptor for every point of the extracted points is created. Then by applying the bilateral image matching and the RANSAC method that removes the unfavorable adaptive points, the correct matching between the satellite and aerial images are found using the suggested method. The results of the proposed method on the real images show the superiority of this method in term of the accuracy and speed, compared to the some well-known matching methods such as SIFT. Manuscript profile -
Open Access Article
407 - Automatic Error Detecting in Databases, Based on Clustering and Nearest Neighbor
M. ataeyan n. daneshpourData quality affects on companies decision making, so that decisions based on data without quality incur companies high costs. Data quality has various dimensions and accuracy is the most important of these dimensions. Error detection is needed for data cleaning. Due to MoreData quality affects on companies decision making, so that decisions based on data without quality incur companies high costs. Data quality has various dimensions and accuracy is the most important of these dimensions. Error detection is needed for data cleaning. Due to the huge volume of data, an automatic system is needed to perform this process without user interaction. In this paper an approach is proposed based on k-means clustering for error detection. Firstly data are clustered for each attribute. Then for each data in each cluster a method similar to k-nearest neighbor is used for detecting errors. The proposed method is able to detect multiple errors in one record. Also this approach is able to detect errors in fields with various attribute types. Experimental results show that this approach can detect 91% of errors in data on average. Also the proposed approach is compared with an automatic method which detects errors based on rule in various attribute types. Experimental results show that the proposed approach has on average 25%better performance to detect errors. Manuscript profile -
Open Access Article
408 - Optimal Economic Scheduling of Islanding Microgrid Considering Renewable Energy Sources (Wind Turbine and Photovoltaic System), Battery and Hydrogen Storage System in the Presence of the Demand Response Program
A. Mehdizadeh N. TaghizadeganMicrogrid (MG) supplied its local load with distributed energy resources at the low voltage system in distribution networks. Microgrid can be used in parts that are not allowed access to the electricity network with low investment cost. The used islanding MG in this res MoreMicrogrid (MG) supplied its local load with distributed energy resources at the low voltage system in distribution networks. Microgrid can be used in parts that are not allowed access to the electricity network with low investment cost. The used islanding MG in this research includes wind turbine and photovoltaic systems as renewable energy sources and hydrogen storage system (HSS). This paper proposes a new energy management strategy (EMS) for MG in the presence of the HSS considering the power uncertainties of renewable energy sources. The objective of proposed EMS is to minimize the operating costs of batteries, HSS and the costs associated with excess and undelivered energy considering the supplied load constraints. The considered technical constraints in this paper contain renewable energy sources limits and battery and HSS constraints. HSS includes electrolyzer (EL), hydrogen tanks and fuel cell (FC). Demand response program (DRP) is used to flat the load curve and optimal operation of MG. The proposed model on a MG is been implemented in GAMS software. The simulation results show that the operation cost of MG reduced by using of HSS and DRP. Manuscript profile -
Open Access Article
409 - Fault Location in Distribution Networks Using a Combination of Impedance Base Method and Voltage Sag
Mohammad Daisy R. DashtiLoad taps, laterals, and sub laterals are different branches of power distribution (PD) networks. In PD systems, reliability indices and their efficiency are improved using an accurate method in fault locating. In this paper, a new combined method for locating single, d MoreLoad taps, laterals, and sub laterals are different branches of power distribution (PD) networks. In PD systems, reliability indices and their efficiency are improved using an accurate method in fault locating. In this paper, a new combined method for locating single, double and three phase faults to ground is proposed in PD networks. In this article, for finding the possible fault locations, an impedance based fault-location algorithm is used. Then, for determining the faulty section, the new method is proposed using voltage sag matching algorithm. In this method, the possible fault locations are determined, after occurrence of single and double phase faults to ground, using an algorithm which is impedance based fault-location algorithm. Separately, the same fault is simulated in possible locations. Then, at the beginning of a feeder, the voltage is saved and the amplitude and angle of the voltage differences are determined and accordingly, an online data bank is generated. Then, the obtained and recorded amplitude and angle of the voltage differences (at the beginning of the feeder) is compared with that data bank, for the actual fault. By the matching value of each possible fault location, the real location of fault is determined. Compared to the other counterparts, the proposed method is more accurate in locating faults and less sensitive to the fault resistance. Manuscript profile -
Open Access Article
410 - Design of PSS and STATCOM Parameters Simultaneously Using Intelligent Method (BRGA)
A. Rajaee A. Khodabakhshian M. R. Esmaili M. MahmodiThis paper presents a new intelligent algorithm, named binary real genetic algorithm (BRGA) to design parameters of PSS and STATCOM controller simultaneously. The proposed algorithm has a strong search capability and high speed convergence to find the global optimum poi MoreThis paper presents a new intelligent algorithm, named binary real genetic algorithm (BRGA) to design parameters of PSS and STATCOM controller simultaneously. The proposed algorithm has a strong search capability and high speed convergence to find the global optimum points. The objective function used in this paper to be minimized is the time integral absolute error (ITAE). The objective will be minimizing the deviations of rotor speed () and the voltage of the bus in which STATCOM has been installed. The simulations are carried out on a two-area four-machine power system to show the superior performance of the proposed method, when compared with GA and PSO algorithms. Manuscript profile -
Open Access Article
411 - An Improved Grid Connected Transformerless Inverter with Proportional Resonant Controller
J. Fallah Ardashir M. Sabahi S. H. Hosseini E. Babaei G. GharehpetianThe grid tied PV systems without transformer have some benefits such as low cost, weight and size and also increases the overall efficiency. The galvanic connection between the grid and PV system causes leakage current in the transformerless inverter to flow through pa MoreThe grid tied PV systems without transformer have some benefits such as low cost, weight and size and also increases the overall efficiency. The galvanic connection between the grid and PV system causes leakage current in the transformerless inverter to flow through parasitic capacitors between the PV system and ground and causes personal safety problems, increases the output harmonic spectrum, and system losses. This paper introduces a modified single phase two stage transformerless inverter for grid connected photovoltaic systems with low leakage current. The neutral of the grid is directly connected to the negative terminal of PV panel that eliminates leakage current without complex control strategy. In this paper, a Proportional Resonant (PR) control strategy is used to control the injected current. The performance of the transformerless inverter is analyzed and its structure has been simulated in PSCAD/EMTDC and the obtained results tested experimentally. Manuscript profile -
Open Access Article
412 - Design and Manufacturing of a One Million Volt Residual Voltage Lightning Current Generator
Alireza Omidkhoda J. Jafari Behnam M. S. Mirghafourian A. Geraieli Hamidreza Sadegh MohammadiThe production of the lightning impulse current is very important for research and Standard quality control tests. Conduction of IEC standard type tests on metal-oxide high voltage surge arresters needs a lightning impulse current generator system that is able to produc MoreThe production of the lightning impulse current is very important for research and Standard quality control tests. Conduction of IEC standard type tests on metal-oxide high voltage surge arresters needs a lightning impulse current generator system that is able to produce both lightning impulse current and simultaneous several kV residual voltage. This paper describes the design and manufacturing of a one million volt residual voltage, 10 kA lightning current generator system and the innovation in design of an integrated high voltage air core reactor. Experimental laboratory tests show the good performance of the manufactured generator and its capability to perform standard type test on metal-oxide high voltage surge arresters. Manuscript profile -
Open Access Article
413 - Rotor Position Detection Algorithm with Mechanical Load Asymmetric Error Determination Ability in SR Motor Drive
E. Khiabani H. Moradi Cheshmeh-BeigiThis paper introduces a new sensorless rotor position detection technique with the mechanical load asymmetric error determines ability for switched reluctance motor drives. In presented paper combination of pulse injection technique and digital pulse position modulation MoreThis paper introduces a new sensorless rotor position detection technique with the mechanical load asymmetric error determines ability for switched reluctance motor drives. In presented paper combination of pulse injection technique and digital pulse position modulation are employed for control of SR motor. In this method, a single high-frequency pulse is injected in an idle phase to determine the rotor position and estimates the rotor position through analysis of the resultant current after voltage pulse injection. Since the number of injected pulses is constant, in terms of the proper functioning of the motor, output bit stream has a fixed length and is proportional to the mechanical load torque. In the event of mechanical failure as a result of fluctuations in the mechanical load, the number of bits according to the error rate will change, which counts the number of output bits detection circuit , errors in mechanical load is determined. Proposed method decrease the injuries caused by asymmetry error in mechanical load connected to the motor shaft. The proposed sensorless method has been simulated using Matlab-Simulink and implemented on an experimental setup in real time to validate its performance. The results obtained demonstrate the feasibility and practicability of the method. Manuscript profile -
Open Access Article
414 - Torque Ripple Reduction in Permanent-Magnetic BLDC Motor Using Optimum Design of Motor Structure
M. R. Alizadeh Pahlavani Y. Shahbazi Ayat A. VahediIn this paper instantaneous electromagnetic torque computation is done for axial flux permanent-magnet brushless DC (BLDC) motor using Lorentz force theorem. In this method, back electro motive force (EMF) and currents of phases should be defined. A novel method is pre MoreIn this paper instantaneous electromagnetic torque computation is done for axial flux permanent-magnet brushless DC (BLDC) motor using Lorentz force theorem. In this method, back electro motive force (EMF) and currents of phases should be defined. A novel method is presented for calculation of back EMF harmonics using analytical method (AM). The analytical results are compared with results obtained from the finite element method (FEM). A good agreement is between AM and FEM. Computational time in AM is much less than FEM. Finally, for torque ripple reduction, some motor geometric parameters are optimized using AM. Manuscript profile -
Open Access Article
415 - Identification and Contribution Evaluation of Interharmonic Sources in a Power System Using Adaptive Linear Neuron and Superposition and Projection Method
P. Sarafrazi H. R. MohammadiIn this paper a new method for identification of interharmonic producing loads in a power system is proposed which is capable of evaluating the contribution of each individual load in the point of common coupling. This method is based on using the superposition and proj MoreIn this paper a new method for identification of interharmonic producing loads in a power system is proposed which is capable of evaluating the contribution of each individual load in the point of common coupling. This method is based on using the superposition and projection method which needs the norton equivalent circuit of loads and supply network. Also in the proposed method, a two-stage adaptive linear neuron is used for determining the interharmonic components of a signal. The effectiveness of the proposed method has been shown through simulation studies in the MATLAB/SIMULINK software. The simulation results show the capability of the proposed method for identification and contribution evaluation of interharmonic sources in a power system. Manuscript profile -
Open Access Article
416 - A New Variance-Based Method for Solving Stochastic Graph Optimization Problem Using Learning Automata
M. R. Mollakhalili Meybodi M. R. MeybodiIn this paper, a new criterion is introduced for solving optimization problems on stochastic graphs- as a model of computer networks-by stochastic learning Automata. This proposed method, because of considering estimated variance of response of environment, can better a MoreIn this paper, a new criterion is introduced for solving optimization problems on stochastic graphs- as a model of computer networks-by stochastic learning Automata. This proposed method, because of considering estimated variance of response of environment, can better adaptation to changes of environment. As a result, the proposed method can produce better response to learning Automata actions. The proposed method, by entering a noise, can avoid learning Automata being stuck at a local optimum point. Our simulation shows that this proposed method can be improve the convergence rate of Automata-based algorithm. Manuscript profile -
Open Access Article
417 - Using the Capabilities of XML and Materialized Views in Creating a Near Real-Time Data Warehouse
S. M. Shafaei S. M. ShafaeiA major challenge in the field of platforms and applications is how to display and combine the results of real-time and static partitions, as well as reduce the response time of on-line analytical processing queries in a near real-time data warehouse. So appropriate con MoreA major challenge in the field of platforms and applications is how to display and combine the results of real-time and static partitions, as well as reduce the response time of on-line analytical processing queries in a near real-time data warehouse. So appropriate content in a near real-time data warehouse can be produced through a common interface for the results of queries. This article provides an architecture that includes an XML/XSLT interface approach to generate appropriate content and also creating materialized views in the client side. In this architecture, providing a model-based HTML output, distribution and composition of results, are presented. In addition, two parallel approaches for incorporating the results of real-time and static partitions of near real-time data warehouse architecture are proposed. In the proposed architecture, the fundamental role of XML and its related technologies, the production and maintenance of content in near real-time data warehouse is determined. The results show that response time of on-line analytical processing queries via materialized views in the server and client side is reduced. Introduced functions for selecting materialized views in the both of client and server sides improve the storage space. Manuscript profile -
Open Access Article
418 - Optimization of Adaptive Design of Wireless Sensor Networks Using Binary Quantum-Inspired Gravitational Search Algorithm
M. Mirhosseini F. Barani H. Nezamabadi-pourIn this paper, the binary quantum-inspired gravitational search algorithm is adapted to dynamically optimize the design of a wireless sensor network towards improving energy consumption and extending the lifetime of the network, so that the application-specific requirem MoreIn this paper, the binary quantum-inspired gravitational search algorithm is adapted to dynamically optimize the design of a wireless sensor network towards improving energy consumption and extending the lifetime of the network, so that the application-specific requirements and communication constraints are fulfilled. The proposed approach is applied on a wireless sensor network used in the application of precise agriculture to monitor environmental conditions. This algorithm would present an optimal design detecting operational mode of each sensor including cluster head, high signal range, low signal range and inactive modes taking into consideration the constraints of the network. The simulation results indicate the most performance of the proposed method in comparison with binary genetic algorithm and particle swarm optimization. Manuscript profile -
Open Access Article
419 - Fast Tracking Algorithm Robust Against Occlusion Using Divided Edge-Based Templates
P. Moallem R. AsgarianIn this paper a fast, reliable and robust algorithm against occlusion for visual tracking of a pre-defined target in sequence images based on adapting template of target edges with search space edges is presented. At first, target window is specified by user and then th MoreIn this paper a fast, reliable and robust algorithm against occlusion for visual tracking of a pre-defined target in sequence images based on adapting template of target edges with search space edges is presented. At first, target window is specified by user and then the proposed algorithm determines an appropriate model for the target by choosing the best edges of the target window. Moreover, to increase robustness against occlusion, target model has been divided into four equal divisions and by performing a logical AND between the template of each division edges and search space edges and then by counting its non-zero pixels, resemblance matrix for each division of target is obtained. In a case that values of the resemblance matrix are less than values of threshold matrix, the desired division is considered occluded and then by taking the effects of non-occluded divisions into account, the exact location of the target in each frame is determined. In the tracking values, in case of appropriate condition respect to background condition, the model of target edges is updated. Selecting dominant edges, multi dividing and updating the target template, has resulted in increasing the robustness of the algorithm against some vital challenges such as changing in ambient and target light, and occurring occlusion over target. The simplicity of this algorithm has provided the possibility of real-time implementation in OpenCV environment using C language, that achieves averagely to more than 60 frames per second for a computer with 2.6 GHz CPU and 4 GB RAM. Moreover, comparing the results of the proposed algorithm to other algorithms, revealed a higher speed and greater reliability. Manuscript profile -
Open Access Article
420 - Human Recognition via Finger Vein Images in Radon Space Using Common Spatial Patterns
H. Hassanpour A. GholamiOne of the most fitting biometric for identifying individuals is finger veins. In this paper, we study the human recognition via finger vein images that recognize persons at a high level of accuracy. First we use entropy based thresholding for segmentation and extractio MoreOne of the most fitting biometric for identifying individuals is finger veins. In this paper, we study the human recognition via finger vein images that recognize persons at a high level of accuracy. First we use entropy based thresholding for segmentation and extraction veins from finger vein images. The method extract veins as well, but the images are very noisy. That means in addition to the veins that appeared as dark lines, they have some Intersecting lines. Then we applied radon transformation to segmented images. The radon transform is not sensitive to the noise in the images due to its integral nature, so in comparison with other methods is more resistant to noise. This transform does not require the extraction of vein lines accurately, that can help to increase accuracy and speed. Then for extracting features from finger vein images, common spatial patterns are applied to the blocks of Radon Transform. In identification step two methods are used: Nearest Neighbor (1-NN) and Artificial Neural Network (MLP). Experiments conducted on sets of finger vein image database of Peking University show 99.6753 percent success rate in identifying individuals. Manuscript profile -
Open Access Article
421 - Symbolic Verification of Temporal Fuzzy Logic Properties on Fuzzy Program Graph
G. Sotudeh A. MovagharWe may investigate the correctness of dynamic fuzzy models by a combination of Modal Temporal Logics and Fuzzy Logic. So far Fuzzy-extended Kripke structure (FzKripke) and Fuzzy-extended Program Graph (FzPG) are introduced as two timed Fuzzy logic models. Meanwhile, a F MoreWe may investigate the correctness of dynamic fuzzy models by a combination of Modal Temporal Logics and Fuzzy Logic. So far Fuzzy-extended Kripke structure (FzKripke) and Fuzzy-extended Program Graph (FzPG) are introduced as two timed Fuzzy logic models. Meanwhile, a Fuzzy-extended Temporal Logic (FzCTL) is introduced. Although no verification technique is devised for verifying FzCTL properties of timed Fuzzy logic models, its applications in verification of Fuzzy Logic Circuits (i.e., Fuzzy Flip-Flops) are studied and elaborated. In this paper we introduce a symbolic approach to tackle the state space explosion problem in timed Fuzzy logic models with which models are simultaneously compressed and processed in the most compact representation possible yet. The applicability of this approach is also demonstrated through experiments on a case study concerning dynamic hazards in a Fuzzy D-Flip Flop. Performance measures like runtime and memory consumptions are also provided for different scenarios. Manuscript profile -
Open Access Article
422 - Key Concept Extraction Using FrameNet and Concept Chains
S. Mohammadi K. BadieDuring last years, many approaches have been presented for the automatic keyword or key phrase extraction. But there are a few approaches for the key concept or key point extraction and they are often based on the statistical methods. The key Concept extraction is a pr MoreDuring last years, many approaches have been presented for the automatic keyword or key phrase extraction. But there are a few approaches for the key concept or key point extraction and they are often based on the statistical methods. The key Concept extraction is a process to identify phrases referring to the concepts of the interests in an unstructured text. In this paper, a new approach has been proposed to the Key Concept Extraction (KCE) by using of FrameNet. This approach is based on the natural language processing methods. The FrameNet is used for shallow semantic parsing of the original texts. Then the concept chains are constructed. For each concept, a score vector with four elements is assigned. Three of them are based on the chains. As the final attempt, a set of concepts is extracted its score are greater than threshold. They contain the most important concept of the main text. The objective and the human-based subjective evaluation have been performed. Precision and recall criteria are investigated. The process of the automatic key concept extraction can be useful in the electronic document indexing, the digital libraries’ building, the categorizing, the text clustering and classifying, the summarizing and the searching. Manuscript profile -
Open Access Article
423 - The Effect of Granularity on the Design of Decimal Arithmetic Reconfigurable Units
S. Emami M. SedighiRecently, decimal arithmetic has received renewed attention in certain application domains such as financial computations. This is mostly due to the demand for more accurate decimal number representation and calculation in those applications. While decimal arithmetic ma MoreRecently, decimal arithmetic has received renewed attention in certain application domains such as financial computations. This is mostly due to the demand for more accurate decimal number representation and calculation in those applications. While decimal arithmetic may be implemented in software and hardware, the latter form offers higher speeds and better performance. Traditionally, hardware decimal units have been designed as application-specific specialized hardware modules. However, emerging designs have come with some degree of reconfigurablility. But there is no research on the effects of reconfigurability parameters, such as granularity and degree of flexibility, on the overall characteristics of decimal hardware modules .In this paper, it will be shown that bit-level granularity is not suitable for decimal reconfigurable adders. Instead, digit-level granularity will lead to superior designs. The synthesis results indicate that increasing granularity level provides an area improvement of %12 and power improvement of %13.4. Unlike adders, increasing the granularity of decimal multipliers has an adverse effect on their quality and may cause up to %75 increase in their area and power consumption. Manuscript profile -
Open Access Article
424 - Online Estimation of Transient Stability in a Two-Area Power System Based on Local and Wide-Area Measurements
M. Arabzadeh H. Seifi Mohammad Kazem Sheikh El EslamiTransient stability analysis (TSA) is one of the important issues in the power system operation. The common methods of TSA are typically based on offline simulations so that some preventive and corrective actions may be designed to be adopted in real time conditions. To MoreTransient stability analysis (TSA) is one of the important issues in the power system operation. The common methods of TSA are typically based on offline simulations so that some preventive and corrective actions may be designed to be adopted in real time conditions. To reduce the risk of these actions, in this paper a new method of transient stability estimation is proposed in which both local and wide-area measurements are used. According to the proposed method, the coherent generator groups of the two-area power system are initially identified and then the system is simplified based on the single machine equivalent (SIME) method. Thereafter, the equal area (EA) criterion is used to estimate the system transient stability. The innovation of this paper is the calculation of the acceleration area of SIME system based on the acceleration areas calculated locally in generator buses. The proposed method is applied on a10-mchine 39-bus test system and its results are presented by further explanation of its technical advantages. Manuscript profile -
Open Access Article
425 - Speed Control of Matrix Converter-Fed Five-Phase Permanent Magnet Synchronous Motors under Unbalanced Voltages
B. Yousefi S. Soleymani B. Mozafari S. A. GholamianFive-phase permanent magnet synchronous motors (PMSM) are often used for specific applications, in which the precise speed control of the motor by an appropriate driver design is important. The use of three-phase to five-phase matrix converter is a suitable technique fo MoreFive-phase permanent magnet synchronous motors (PMSM) are often used for specific applications, in which the precise speed control of the motor by an appropriate driver design is important. The use of three-phase to five-phase matrix converter is a suitable technique for constructing such a motor driver. Since the input voltages of such converters are directly supplied by input three-phase supply voltages, an imbalance in the voltages will cause problems such as unbalanced stator currents and electromagnetic torque fluctuations, making it inefficient to use such converters. In this paper, a new method is proposed to remove torque oscillator factors based on direct power control (DPC). In this way, a number of features including speed, torque, and flux of the motor will improve in terms of the above-mentioned conditions. Simulations are analyzed using Matlab/Simulink software. Manuscript profile -
Open Access Article
426 - An Efficient Method for Modulation Recognition of MPSK Signals in Fading Channels
S. HakimiAutomatic modulation recognition of digital signals is an essential for intelligent communication systems. Most automatic classifications of digital signal types deal with recognizing signals formats in presence of additive white Gaussian noise (AWGN) in channels. Howev MoreAutomatic modulation recognition of digital signals is an essential for intelligent communication systems. Most automatic classifications of digital signal types deal with recognizing signals formats in presence of additive white Gaussian noise (AWGN) in channels. However, real world communication environments, such as wireless communication channels, suffer from fading effects. There are few methods proposed to perform in fading channels. This paper presents a high efficient method for identification of M-array phase shift keying (MPSK) digital signal type. The proposed method is heuristic hybrid, formed by a multilayer perceptron (MLP) neural network as the classifier and the bees algorithm (BA) as the optimizer. An equalizer is also used to reduce channel effects. A suitable combination of higher order statistics, up to eighth, is considered as prominent characteristics of signals. Simulation results validate the high efficiency of the proposed technique in recognizing the types of digital signals even at low SNRs. Manuscript profile -
Open Access Article
427 - Design and Analysis of a Novel Robust and Fast Sliding-Mode Control with Multi-Slope Sliding Surface for Single-Phase Three Level NPC Inverters under Different Loads and Reduce the Output THD
B. Khajeh-Shalaly G. ShahgholianIn this paper control structure with robust performance in presence of parametric uncertainties of the converter in order to improve pure sinusoidal inverter in whole functional and loading conditions is rendered. The controller guarantees fast and accurate behavior of MoreIn this paper control structure with robust performance in presence of parametric uncertainties of the converter in order to improve pure sinusoidal inverter in whole functional and loading conditions is rendered. The controller guarantees fast and accurate behavior of the converter in order to increase the output voltage quality and reduce output harmonics. This controller by sliding performance and utilizing output voltage and capacitor current used in the control process, not only has exact output voltage tracking from reference but also has ability to reject the periodic disturbances due to loading. Also, it guides error states to zero rapidly and makes transient states of the converter as well as possible at error moments that is the same high spikes and loads in output current. Another characteristic of the proposed controller is, improved stability region under wide ranges of loading in different conditions. Accuracy of proposed controller on a single-phase three level NPC inverter which has high sensitivity in control in order to increase quality, decrease harmonics and THD output has been compared with a single-slope sliding mode controller with the sane loading conditions and reference. The simulations results are obtained by MATLAB. Manuscript profile -
Open Access Article
428 - An Adaptive Incremental Conductance MPPT Based on BELBIC Controller in Photovoltaic Systems
S. Azimi Sardari B. Mirzaeian Dehkordi M. NiroomandMany conventional incremental conductance (INC) methods are applied for maximum power point tracking (MPPT) of photovoltaic arrays. Where, the optimization step size determines the speed of MPPT. Fast tracking could be achieved with bigger increments but the system migh MoreMany conventional incremental conductance (INC) methods are applied for maximum power point tracking (MPPT) of photovoltaic arrays. Where, the optimization step size determines the speed of MPPT. Fast tracking could be achieved with bigger increments but the system might not operate properly at the MPP and might become oscillated at this point; therefore, there is a trade-off between the time needed to reach the MPP and the oscillation error. This article is to present an adaptive optimization step size in the INC to improve solar array performance. To adjust the MPP in the photovoltaic (PV) operation point, brain emotional learning based intelligent controller (BELBIC) is applied as an adaptive optimization step size in the INC. This would considerably increase the system's accuracy. The effectiveness of this proposed method is verified by comparing its simulation and experimental results with the conventional methods in different operating conditions. Manuscript profile -
Open Access Article
429 - Torque and Flux Ripple Elimination in DTC Control of PMSM Motors using Duty Cycle Control of Voltage Vectors
V. Ghasemian S. A. Gholamian S. M. MirimaniThis paper presents a novel method for controlling torque and stator flux ripples in DTC control of PMSM motor. In contrast to conventional duty ratio modulation methods which do not pay attention to stator flux condition, the proposed method controls both torque and st MoreThis paper presents a novel method for controlling torque and stator flux ripples in DTC control of PMSM motor. In contrast to conventional duty ratio modulation methods which do not pay attention to stator flux condition, the proposed method controls both torque and stator flux RMS ripples using minimization of a proper two variable (stator flux and torque) objective function. After realizing that, flux related machine specifications such as circular stator flux vector trajectory and current waveform quality will be developed. For this purpose, in addition to torque dynamics in any DTC control cycle, stator flux dynamics will be studied. Using this, the condition of both torque and stator flux at the end of an applied voltage vector of inverter is predicted. Then, standard deviation of torque RMS ripple and that of stator flux is studied in any control cycle and the normalized sum of these two deviations will be considered as the objective function. Finally, a proper switching instant during any control cycle is calculated for minimizing the objective function. The proposed method is validated by MATLAB simulation. Manuscript profile -
Open Access Article
430 - Performance Assessment of a WCDMA Based Radio-over-Fiber System with Near-Far Effect: Uplink Scenario
G. BaghersalimiIn this research the effect of a radio-over-fiber (RoF) subsystem on the total degradation (TD) performance of uplink wideband code division multiple access (WCDMA) is assessed in the presence of near-far effect. The study considers the use of pilot-aided channel estima MoreIn this research the effect of a radio-over-fiber (RoF) subsystem on the total degradation (TD) performance of uplink wideband code division multiple access (WCDMA) is assessed in the presence of near-far effect. The study considers the use of pilot-aided channel estimation to neutralize the optical subsystem nonlinearities for different channel conditions, estimation intervals, and near-far factors (NFF). The results demonstrate that the proposed equalization technique almost compensates for the joint impact of the optical subsystem nonlinearity and the near-far effect irrespective of spreading factor, large signal distortion, estimation interval, and user number. Manuscript profile -
Open Access Article
431 - A Novel Source/Drain side Double Recessed Gate 4H-SiC MESFET with n-Buried Layer in the Channel
S. M. Razavi Seyed-Hamid ZahiriA new structure named as source/drain sides-double recessed gate with N-buried layer in the channel (SDS-DRG) silicon carbide (SiC) based metal semiconductor field effect transistor (MESFET) is presented in this study. Important parameters such as short channel effect, MoreA new structure named as source/drain sides-double recessed gate with N-buried layer in the channel (SDS-DRG) silicon carbide (SiC) based metal semiconductor field effect transistor (MESFET) is presented in this study. Important parameters such as short channel effect, maximum DC trans-conductance, drain current and breakdown voltage of the proposed structure are simulated and compared with those of the source side-double recessed gate (SS-DRG) and drain side-double recessed gate (DS-DRG) 4H-SiC MESFETs. Our simulation results reveal that reducing the channel thickness under the gate at the SDS-DRG structure improves the maximum DC trans-conductance and reduces the short channel effects compared to SS-DRG and DS-DRG structures. Reducing the channel thickness under the gate at the drain side of the SDS-DRG structure is used to enhance the breakdown voltage in comparison with the SS-DRG structure. Also, N-buried layer with larger doping concentration in the SDS-DRG structure improves the saturated drain current compared to SS-DRG and DS-DRG structures. Manuscript profile -
Open Access Article
432 - A Multi-Frequency Miniaturized Microstrip Fractal Antenna
S. Jam A. MehboodiFor further and various applications of communication systems, we lead to using the overall of electromagnetic spectrum. Also, because of the developing f multiband wireless systems, antenna designers are enforced to design antennas matched to the operation in multi-ban MoreFor further and various applications of communication systems, we lead to using the overall of electromagnetic spectrum. Also, because of the developing f multiband wireless systems, antenna designers are enforced to design antennas matched to the operation in multi-band and multi-frequency. On the other hand, nowadays, the use of light-weight, simple, small and inexpensive antennas is an essential requirement for covering multi bands. In this paper, a microstrip antenna is designed and suggested fractal-based and utilized FR4 substrate with small size and light, and also ability to resonance in multi-frequency by increasing fractal repetitions and self-similarity property. Therefore, this proposed structure causes the antenna resonance in more frequencies, and also leads to miniaturization of its size. This antenna operates in 1-10 GHz range includes five frequency resonance for the most of convenient applications. Also, it has appropriate pattern and circular polarization which increases its applications. The antenna has been fabricated and there is a good agreement between measurement results and full wave simulation using HFSS software. Manuscript profile -
Open Access Article
433 - A Near Real-Time Data Warehouse Architecture Based on Ontology
Data warehouse does not provide external data that are required to dynamically build after design and create the data warehouse. Therefore, analysts conduct effective analysis to find a correlation between external data and data warehouse data, and in other cases requir MoreData warehouse does not provide external data that are required to dynamically build after design and create the data warehouse. Therefore, analysts conduct effective analysis to find a correlation between external data and data warehouse data, and in other cases requires a comparison both external data and data warehouse data together. The analyst forced to repeat some past repetitive situations. This includes creating terminology, measures and comparison. In this paper, for graduates of this problem, a real-time data warehouse architecture based on ontology is proposed. Furthermore, an algorithm to reduce the response time to users’ queries using materialized views and parallel processing is proposed. A case study to demonstrate how to create correlation between external data and data warehouse data is done and the results show the correlation between external data and data warehouse data is discovered. In experiments, using both direct and parent materialized views approaches in existing data warehouse architecture, reduce response time to users’ sequential, comparative and combination queries. Manuscript profile -
Open Access Article
434 - A Near Real-Time Data Warehouse Architecture Based on Ontology
S. M. Shafaei S. M. ShafaeiData warehouse does not provide external data that are required to dynamically build after design and create the data warehouse. Therefore, analysts conduct effective analysis to find a correlation between external data and data warehouse data, and in other cases requir MoreData warehouse does not provide external data that are required to dynamically build after design and create the data warehouse. Therefore, analysts conduct effective analysis to find a correlation between external data and data warehouse data, and in other cases requires a comparison both external data and data warehouse data together. The analyst forced to repeat some past repetitive situations. This includes creating terminology, measures and comparison. In this paper, for graduates of this problem, a real-time data warehouse architecture based on ontology is proposed. Furthermore, an algorithm to reduce the response time to users’ queries using materialized views and parallel processing is proposed. A case study to demonstrate how to create correlation between external data and data warehouse data is done and the results show the correlation between external data and data warehouse data is discovered. In experiments, using both direct and parent materialized views approaches in existing data warehouse architecture, reduce response time to users’ sequential, comparative and combination queries. Manuscript profile -
Open Access Article
435 - Presenting Technique for the Quantitative Evaluation of Image Color Reduction Algorithms by Explaining a Practical Sample
M. Fateh E. KabirIn color reduction algorithms the result will be evaluated based on visual or qualitative standards. Evaluation without considering the quantitative standard wouldn't be a complete and accurate evaluation and trends of viewer are very effective on the evaluation. In som MoreIn color reduction algorithms the result will be evaluated based on visual or qualitative standards. Evaluation without considering the quantitative standard wouldn't be a complete and accurate evaluation and trends of viewer are very effective on the evaluation. In some articles, the result will be evaluated with MSE. In this standard error the difference between the final images’ pixels color with first image will be considered as a failure in which is not a suitable technique for evaluating of color reduction methods. In images color reduction, if a color completely be replaced by a color closed to the original color it wouldn’t be considered as a failure. If these replacements don’t happen for all of those specific color pixels, then an error has happened in color reduction. The disintegration of the resulted colors from color reduction algorithm with desired colors should be considered in presenting the evaluation criteria since this will not be considered in MSE. In some of color reduction applications such as color reduction in the carpet cartoons, the final desired pixel color is specified and presenting the wrong color will be an error. Therefore, in such applications, the quantitative evaluation based on final color of each pixel is possible. By presenting criteria for quantitative evaluation, viewer trends wouldn't be considered in evaluation and the possibility of accurate comparison of color reduction algorithms would take place. In this article, we have presented a technique of quantitative evaluation for color reduction algorithms. When the final desired color for pixels are specified, this criteria would work out. To demonstrate the functionality of this quantitative evaluation technique, one of the applications of color reduction which is color reduction in carpet cartoons would be discussed. Several methods of color reduction would be evaluated based on proposed evaluation criteria and reference [42], had the lowest error. Manuscript profile -
Open Access Article
436 - A Parallel Bacterial Foraging Optimization Algorithm implementation on GPU
A. Rafiee S. M. MosaviBacterial foraging algorithm is one of the population-based optimization algorithms that used for solving many search problems in various branches of sciences. One of the issues discussed today is parallel implementation of population-based optimization algorithms on Gr MoreBacterial foraging algorithm is one of the population-based optimization algorithms that used for solving many search problems in various branches of sciences. One of the issues discussed today is parallel implementation of population-based optimization algorithms on Graphic Processor Units. Due to the low speed of bacterial foraging algorithm in the face of complex problem and also lack the ability to solve large-scale problems by this algorithm, Implementation on the graphics processor is a suitable solution to cover the weaknesses of this algorithm. In this paper, we proposed a parallel version of bacterial foraging algorithm which designed by CUDA and has ability to run on GPUs. The performance of this algorithm is evaluated by using a number of famous optimization problems in comparison with the standard bacterial foraging optimization algorithm. The results show that Parallel Algorithm is faster and more efficient than standard bacterial foraging optimization algorithm. Manuscript profile -
Open Access Article
437 - Precise Tracking of Moving Objects Using KLT, Sift and DBSCAN Algorithms
A. Karamiani A. KaramianiDetecting and tracking of moving objects is an important task in analyzing videos. In this paper, we propose a new method for tracking several concurrent moving objects of fixed camera. In the proposed method, at each stage, the location of moving objects in front of ca MoreDetecting and tracking of moving objects is an important task in analyzing videos. In this paper, we propose a new method for tracking several concurrent moving objects of fixed camera. In the proposed method, at each stage, the location of moving objects in front of camera view is obtained information between two current and previous frames. In each step, Sift’s edge points is obtained based on previous frame and to get the correspondence of these feature points by the use of KLT feature point correspondence algorithm on the current frame. Then having correspondent feature points between two sequence frames, we would estimate the distance by eliminating partial or fixed moving feature points related to moving objects. The classification of labeled features as moving objects is done using DBSCAN clustering algorithm into different clusters. By this method and on each moment, the situation of all existing moving objects in camera view which has got by one by one correspondence between these objects, is determined. The obtained results of the proposed method shows a high degree of accuracy and acceptable consuming time to track moving objects. Manuscript profile -
Open Access Article
438 - Green Routing Protocol Based on Sleep Scheduling in Mobile Ad-Hoc Network
Z. Movahedi A. KarimiOver recent years, green communication technology has been emerged as an important area of concern for communication research and industrial community. The reason of paying attention of this area is its effect on reducing environmental pollutions. According to recent re MoreOver recent years, green communication technology has been emerged as an important area of concern for communication research and industrial community. The reason of paying attention of this area is its effect on reducing environmental pollutions. According to recent research, a significant share of these pollutions is produced by the local area computer networks. A mobile ad-hoc network (MANET) is one of the widely used local area networks. The energy efficiency is important in MANETs not only from the green communication point of view, but also due to the network limitations in terms of battery lifetime. Of course, MANETs characterization such as distributed nature and lack of administration, nodes mobility, frequent topology changes and scare resources makes the greening trend a challenging task in such a context. In this paper, we propose and implement a green routing protocol for MANET which solves the idle energy consumption by allowing the necessary nodes and switching off the other un-utilized nodes. Simulation results show this can help to the 20 percentage of saving energy in the environment on average and also aware of the quality of service. Manuscript profile -
Open Access Article
439 - Model-Based Classification of Emotional Speech Using Non-Linear Dynamics Features
A. Harimi A. Ahmadyfard A. Shahzadi K. YaghmaieRecent developments in interactive and robotic systems have motivated researchers for recognizing human’s emotion from speech. The present study aimed to classify emotional speech signals using a two stage classifier based on arousal-valence emotion model. In this metho MoreRecent developments in interactive and robotic systems have motivated researchers for recognizing human’s emotion from speech. The present study aimed to classify emotional speech signals using a two stage classifier based on arousal-valence emotion model. In this method, samples are firstly classified based on the arousal level using conventional prosodic and spectral features. Then, valence related emotions are classified using the proposed non-linear dynamics features (NLDs). NLDs are extracted from the geometrical properties of the reconstructed phase space of speech signal. For this purpose, four descriptor contours are employed to represent the geometrical properties of the reconstructed phase space. Then, the discrete cosine transform (DCT) is used to compress the information of these contours into a set of low order coefficients. The significant DCT coefficients of the descriptor contours form the proposed NLDs. The classification accuracy of the proposed system has been evaluated using the 10-fold cross-validation technique on the Berlin database. The average recognition rate of 96.35% and 87.18% were achieved for females and males, respectively. By considering the total number of male and female samples, the overall recognition rate of 92.34% is obtained for the proposed speech emotion recognition system. Manuscript profile -
Open Access Article
440 - Speed up the Search for Proximity-Based Models
J. Paksima A. Zareh V. DerhamiOne of the main challenges in the proximity models is the speed of data retrieval. These models define a distance concept which is calculated based on the positions of query terms in the documents. This means that finding the positions and calculating the distance is a MoreOne of the main challenges in the proximity models is the speed of data retrieval. These models define a distance concept which is calculated based on the positions of query terms in the documents. This means that finding the positions and calculating the distance is a time consuming process and because it usually executed during the search time it has a special importance to users. If we can reduce the number of documents, retrieval process becomes faster. In this paper, the SNTK3 algorithm is proposed to prune documents dynamically. To avoid allocating too much memory and reducing the risk of errors during the retrieval, some documents' scores are calculated without any pruning (Skip-N). The SNTK3 algorithm uses three pyramids to extract documents with the highest scores. Experiments show that the proposed algorithm can improve the speed of retrieval. Manuscript profile -
Open Access Article
441 - Web Robot Detection Using Fuzzy Rough Set Theory
S. Rahimi J. HamidzadehWeb robots are software programs that traverse the internet autonomously. Their most important task is to fetch information and send it to the origin server. The high consumption of network bandwidth by them and server performance reduction, have caused the web robot de MoreWeb robots are software programs that traverse the internet autonomously. Their most important task is to fetch information and send it to the origin server. The high consumption of network bandwidth by them and server performance reduction, have caused the web robot detection problem. In this paper, fuzzy rough set theory has been used for web robot detection. The proposed method includes 4 phases. In the first phase, user sessions have identified using fuzzy rough set clustering. In the second phase, a vector of 10 features is extracted for each session. In the third phase, the identified sessions are labeled using a heuristic method. In the fourth phase, these labels are improved using fuzzy rough set classification. The proposed method performance has been evaluated on a real world dataset. The experimental results have been compared with state-of-the-art methods, and show the superiority of the proposed method in terms of F-measure. Manuscript profile -
Open Access Article
442 - Voltage Stability Improvement of Microgrids Using Local Control Optimization
V. Bahrami Foroutan M. H. Moradi Mohammad AbediniStability challenges in Microgrids (MGs) usually arise from low inertia of Distributed Generation (DG). In this paper, a voltage stability improvement method is proposed in order to improve MG operation. Voltage Stability Index (VSI) is applied to evaluate and improve v MoreStability challenges in Microgrids (MGs) usually arise from low inertia of Distributed Generation (DG). In this paper, a voltage stability improvement method is proposed in order to improve MG operation. Voltage Stability Index (VSI) is applied to evaluate and improve voltage stability of MGs including different types of DGs. A new hybrid optimization is introduced to find the optimal operation of autonomous MG and to improve VSI. Operational optimization is performed by finding optimal droop parameters of DGs and sitting wind DGs to reduce energy generation cost. Optimization is defined as a multi-objective function and a hybrid HS-GA algorithm is applied to solve the optimization problem. A new power flow formulation is also proposed in which the steady state frequency, reference frequency, droop coefficients and, reference voltage of droop based DGs are considered as optimization variables. Results of proposed approach are compared with other methods for 33 and 69-bus IEEE systems using MATLAB software. Results prove the efficiency of proposed approach for operational improvement of MGs. Manuscript profile -
Open Access Article
443 - Power Exchange Management for Multi-Area Systems Considering Participation of External Bus Players in Multiple Markets
علی کریمی H. SeifiIn recent years, there has been an increasing attention in energy exchange among the various countries or areas. One of the methods for energy exchange, with coordinated by the area operators, is participation of producers and consumers in other area markets directly. I MoreIn recent years, there has been an increasing attention in energy exchange among the various countries or areas. One of the methods for energy exchange, with coordinated by the area operators, is participation of producers and consumers in other area markets directly. In this paper, for multi-area power systems that there is a single market in each area (multiple markets structure), a mechanism for power exchange management is proposed. In the mentioned structure, the participation of external bus players in each market is possible. In the designed mechanism, the power exchange management is done by a proposed central coordinator entity. The coordinator performs the management of power exchange in an iterative decision-making process to maintain system security by using a technical approach. The simulation studies for a triple-market case in the standard three areas system (IEEERTS-96) are presented to validate the effectiveness of the proposed mechanism. Manuscript profile -
Open Access Article
444 - آنالیز عملکرد مبدل DC-DC کاهنده- افزاینده جدید با ضریب افزایندگی بالا برای کاربرد در سیستم خورشیدی
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Open Access Article
445 - Operational Analysis of the Buck Boost DC–DC Converter with High Step-Up Voltage Gain
M. R. Banaei H. A. Faeghi BonabIn some applications that we need a high voltage gain such as the photovoltaic cell and fuel cell, high step up dc-dc converters must be used, but conventional boost converter cannot provide the high voltage gain. For this reason, in this paper, a single switch transfor MoreIn some applications that we need a high voltage gain such as the photovoltaic cell and fuel cell, high step up dc-dc converters must be used, but conventional boost converter cannot provide the high voltage gain. For this reason, in this paper, a single switch transformerless high step-up buck boost dc-dc converter with reduced voltage stress on the semiconductors is proposed. The proposed converter has higher voltage gain in step-up mode in comparison with conventional boost and buck-boost converters. Reduced voltage stress on the active switch allows to choose lower voltage rating MOSFETs to reduce both switching and conduction losses. Low voltage stress on the diodes allows the use of Schottky rectifiers for alleviating the reverse-recovery current. The proposed converter can be operated in the continuous conduction mode (CCM) and the discontinuous conduction mode (DCM). In this paper, different operation modes of the proposed converter, calculation of the voltage gain, the currents that flow through the components, efficiency and capacitors voltage ripple are presented. To verify the operation of the proposed converter, simulation results via PSCAD software and experimental results are provided. Manuscript profile -
Open Access Article
446 - Exponential Stability Analysis of Discrete Linear Teleoperation Systems with Nonuniform Sampling
A. Aminzadeh Ghavifekr A. Rikhteghar Ghiasi M. A. Badamchizadeh F. HashemzadehTeleoperation systems have attracted more attention in processes that human operator’s availability is difficult. In this paper, using retarded functions, teleoperation systems have been modeled as a special case of Network Control Systems (NCS) with nonuniform sampling MoreTeleoperation systems have attracted more attention in processes that human operator’s availability is difficult. In this paper, using retarded functions, teleoperation systems have been modeled as a special case of Network Control Systems (NCS) with nonuniform sampling and network delays. It is assumed that slave and master robots are linear and continues-time systems and input-delay approach is used for the stability analysis. Using the proposed Lyapunov function, the sufficient conditions for the stability of discrete network-based teleoperation system is proposed. It will be represented that the proposed conditions are less conservative than previous recent researches. Also an upper bound of sampling time for discrete control signals is computed in a manner that does not disturb the stability conditions. To meet this condition the problem is defined as the convex optimization program and is represented by the LMI terms. In the simulation part, the behavior of the teleoperation system under the nonuniform sampling is represented and the effect of sampling time on the trade-off between the stability and transparency has been studied. Manuscript profile -
Open Access Article
447 - Band Engineered (Heterostructure) IMOS Device
H. Godazgar محمدكاظم مروج فرشي مرتضی فتحی پورA novel model for impact ionization metal-semiconductor (IMOS) device with an engineered bandstructure (heterostructure) has been proposed and simulated. The IMOS intrinsic, wherein the carrier generation is mainly due to impact ionization, controls the band to band tun MoreA novel model for impact ionization metal-semiconductor (IMOS) device with an engineered bandstructure (heterostructure) has been proposed and simulated. The IMOS intrinsic, wherein the carrier generation is mainly due to impact ionization, controls the band to band tunneling. In the proposed model, it is assumed the intrinsic region to be SixGe1−x (0.5≤x≤1) whose bandgap varies linearly from that of Si at the source edge to that of Si0.5Ge0.5 at the gate edge. Maximum gap difference of ΔEG=ΔEC=0.32 eV appears at the source /intrinsic region interface. As a consequence, the probability of band to band tunneling and hence the device dark current is reduced. The numerical result shows that the breakdown voltage and the dark current for the proposed heterostructure IMOS are respectively ~0.3 V and four times smaller than those of the homojunction Si0.5Ge0.5-IMOS, with the same dimensions. Manuscript profile -
Open Access Article
448 - Direct Torque Control of Low Voltage Three Phase Induction Motor Using Three-Level Ten-Switch Inverter
M. Shahparasti Mohammad FarziIn this paper a new topology of three-level inverters with ten-switch is proposed to control low voltage three phase induction motor. Ten-switch inverter is a reduced-switch-count three level inverter which compared to conventional topologies such as NPC, CHB and flying MoreIn this paper a new topology of three-level inverters with ten-switch is proposed to control low voltage three phase induction motor. Ten-switch inverter is a reduced-switch-count three level inverter which compared to conventional topologies such as NPC, CHB and flying capacitor has lower count of semiconductor switches. Thus, it enjoys from lower cost, lower volume and lower weight. In this paper, a direct torque control (DTC) scheme based on switching table is developed to control a ten switch inverter. Simulation results of controlling induction motor fed by a conventional two-level inverter, NPC and proposed 10 switch inverter are presented and they are compared together in different aspects. Results confirm the effectiveness of the proposed topology and its control method. Manuscript profile -
Open Access Article
449 - Sensorless Field Oriented Control of DFIGs Using a Rotor-Current-Based MRAS Observer under Grid Voltage Dip
A. Hasani R. KianinezhadThis paper proposes a new application of sensorless control method for doubly fed induction generator (DFIG) using rotor-current-based MRAS observer (RCMO) under grid voltage dip. MRAS means model reference adaptive system. In this paper the method of control of DFIG is MoreThis paper proposes a new application of sensorless control method for doubly fed induction generator (DFIG) using rotor-current-based MRAS observer (RCMO) under grid voltage dip. MRAS means model reference adaptive system. In this paper the method of control of DFIG is vector control VC (or field oriented control FOC). The position and speed of rotor are estimated by RCMO instead of measuring. DFIG is connected to a grid with a balanced voltage dip on PCC and is tested by large variation in rotor speed. Simulation results using MATLAB/Simulink are presented for a 2-MW DFIG. The simulation results show the decoupled control of active and reactive power of DFIG in three conditions: a) normal voltage of grid b) grid voltage dip c) huge variation at wind speed. The results show that the estimated speed of rotor and power produced in DFIG carefully follows the references. The conclusion of simulation results is that for decoupled control of active and reactive power of DFIG, application of RCMO method is favorable and acceptable under balanced voltage dips and variable speed wind as well as conventional VC. Manuscript profile -
Open Access Article
450 - Investigation of the Novel Attributes at AlGaN/GaN HEMT with a P-Layer in the Barrier at Source and Drain Side
S. M. Razavi Seyed-Hamid Zahiri S. E. HosseiniIn this work, novel gallium-nitride (GaN) high electron mobility transistor (HEMT) with a p-layer in the barrier at source and drain sides (SD-PL) is reported. Important parameters such as gate-source and gate-drain capacitances, maximum DC trans-conductance (gm), cut o MoreIn this work, novel gallium-nitride (GaN) high electron mobility transistor (HEMT) with a p-layer in the barrier at source and drain sides (SD-PL) is reported. Important parameters such as gate-source and gate-drain capacitances, maximum DC trans-conductance (gm), cut off frequency (fT), maximum lateral electric field, breakdown voltage, DC output conductance (go) and saturated drain current of the proposed structure are studied in details using two-dimensional and two-carrier device simulations. The simulation results of the proposed structure are compared with those of the source side p-layer in the barrier (S-PL), drain side p-layer in the barrier (D-PL) and conventional structures. According to the extracted results, the proposed structure improves the gate-source capacitance, maximum gm, cut off frequency and go compared to the D-PL structure. Also this new structure reduces the peak electric field at the gate corner near the drain and consequently increases the breakdown voltage significantly in comparison with the conventional structure. Increasing p-layer length (LP) and thickness (TP) in the SD-PL and S-PL structures, improves the breakdown voltage, gate-source capacitance, gate-drain capacitance and go. Manuscript profile -
Open Access Article
451 - Coordinated Fair Scheduling in LTE-Advanced Multi-Sector Cells
M. Abiri Mehri Mehrjoo R. Abaspour GhadiIn this paper, we propose a coordinated fair scheduling (CFS) scheme for LTE-Advanced networks where the cells are equipped with multiple sector antennas. To enhance the network spectral efficiency and throughput, the sectors use the same frequency bands. However, to re MoreIn this paper, we propose a coordinated fair scheduling (CFS) scheme for LTE-Advanced networks where the cells are equipped with multiple sector antennas. To enhance the network spectral efficiency and throughput, the sectors use the same frequency bands. However, to reduce the co-channel interference, the transmissions from the sectors to the users are coordinated. In other words, multiple sectors are allowed to transmit simultaneously, if the occurred co-channel interference is less than a threshold value. The scheduling scheme takes advantage of the user's diversity in space to transmit to the users with good channel conditions while maintaining fairness among the users using the alpha-fair criterion. Furthermore, a heuristic approach is proposed to reduce the computational complexity of the scheduling scheme. The performance of the proposed CFS scheme and the heuristic approach are evaluated using simulation results. The simulation results show that using coordinated fair scheduling improves system performance and increases cell throughput. Manuscript profile -
Open Access Article
452 - Identification and Contribution Evaluation of Interharmonic Sources in a Power System Using Adaptive Linear Neuron and Superposition and Projection Method
P. Sarafrazi H. R. MohammadiIn this paper a new method for identification of interharmonic producing loads in a power system is proposed which is capable of evaluating the contribution of each individual load in the point of common coupling. This method is based on using the superposition and proj MoreIn this paper a new method for identification of interharmonic producing loads in a power system is proposed which is capable of evaluating the contribution of each individual load in the point of common coupling. This method is based on using the superposition and projection method which needs the norton equivalent circuit of loads and supply network. Also in the proposed method, a two-stage adaptive linear neuron is used for determining the interharmonic components of a signal. The effectiveness of the proposed method has been shown through simulation studies in the MATLAB/SIMULINK software. The simulation results show the capability of the proposed method for identification and contribution evaluation of interharmonic sources in a power system. Manuscript profile -
Open Access Article
453 - Proposing a Density-Based Clustering Algorithm with Ability to Discover Multi-Density Clusters in Spatial Databases
A. Zadedehbalaei A. Bagheri H. AfsharClustering is one of the important techniques for knowledge discovery in spatial databases. density-based clustering algorithms are one of the main clustering methods in data mining. DBSCAN which is the base of density-based clustering algorithms, besides its benefits s MoreClustering is one of the important techniques for knowledge discovery in spatial databases. density-based clustering algorithms are one of the main clustering methods in data mining. DBSCAN which is the base of density-based clustering algorithms, besides its benefits suffers from some issues such as difficulty in determining appropriate values for input parameters and inability to detect clusters with different densities. In this paper, we introduce a new clustering algorithm which unlike DBSCAN algorithm, can detect clusters with different densities. This algorithm also detects nested clusters and clusters sticking together. The idea of the proposed algorithm is as follows. First, we detect the different densities of the dataset by using a technique and Eps parameter is computed for each density. Then DBSCAN algorithm is adapted with the computed parameters to apply on the dataset. The experimental results which are obtained by running the suggested algorithm on standard and synthetic datasets by using well-known clustering assessment criteria are compared to the results of DBSCAN algorithm and some of its variants including VDBSCAN, VMDBSCAN, LDBSCAN, DVBSCAN and MDDBSCAN. All these algorithms have been introduced to solve the problem of multi-density data sets. The results show that the suggested algorithm has higher accuracy and lower error rate in comparison to the other algorithms. Manuscript profile -
Open Access Article
454 - A Multi-Criteria Decision Making Mechanism for Data Offloading from Cellular Networks to Complementary Networks
M. Fallah Khoshbakht saleh Yousefi B. Ghalebsaz JeddiDue to proliferation of smart phones, data traffic in cellular networks has been significantly increasing, which has resulted in congestions in cellular networks. Data offloading to a complementary network such as Wi-Fi has been identified as a rational and cost-effecti MoreDue to proliferation of smart phones, data traffic in cellular networks has been significantly increasing, which has resulted in congestions in cellular networks. Data offloading to a complementary network such as Wi-Fi has been identified as a rational and cost-effective solution to these congestions. In this paper, a multi-criteria offloading (MCO) mechanism is proposed to select the best transfer mode among: cellular delivery, delay-tolerant offloading (DTO) to a complementary network, and peer-assisted offloading (PAO). The proposed MCO mechanism utilizes TOPSIS multi-criteria decision analysis method and a prediction model for the Wi-Fi connection pattern. The decision criteria include: the fraction of total users’ request satisfied by offloading, data transfer costs of cellular operator to users, data transfer bandwidth of users in both cellular and complementary networks, and total users’ power consumption. To evaluate the proposed mechanism various scenarios have been simulated, and the results show that the MCO mechanism can successfully take into account the preferences of the cellular operator and its users. Through simulations, the MCO mechanism demonstrated superior performance in comparison with other proposed solutions in the literature in terms of balancing the load on the network, reducing the cost of the cellular operator, and reducing energy consumption of the users. Manuscript profile -
Open Access Article
455 - A Novel Cascading Scheme to Improve Speed and Accuracy of a VMMR System
M. BiglariIn the last decade, many researches have been done on fine-grained recognition. The main category of the object is known in this problem and the goal is to determine the subcategory or fine-grained category. Vehicle Make and Model Recognition (VMMR) is a hard fine-grain MoreIn the last decade, many researches have been done on fine-grained recognition. The main category of the object is known in this problem and the goal is to determine the subcategory or fine-grained category. Vehicle Make and Model Recognition (VMMR) is a hard fine-grained classification problem, due to the large number of classes, substantial inner-class and small inter-class distance. Furthermore, improving system accuracy leads to increasing in processing time. As we can see the state-of-the-art machine vision tool like convolutional neural networks lacks in real-time processing time. In this paper, a method has been presented briefly for VMMR firstly. Secondly, a cascading scheme for improving both speed and accuracy of this VMMR system has been proposed. In order to eliminate extra processing cost, the proposed cascading scheme applies classifiers to the input image in a sequential manner. Some effective criterions for an efficient ordering of classifiers are proposed and finally a fusion of them is used in the cascade algorithm. For evaluation purposes, a new dataset with more than 5000 vehicles of 28 different makes and models has been collected. The experimental results on this dataset and comprehensive CompCars dataset show outstanding performance of our approach. Our cascading scheme results up to 80% increase in the system processing speed. Manuscript profile -
Open Access Article
456 - A Novel Cascading Scheme to Improve Speed and Accuracy of a VMMR System
M. Biglari ali Soleimani H. HassanpourIn the last decade, many researches have been done on fine-grained recognition. The main category of the object is known in this problem and the goal is to determine the subcategory or fine-grained category. Vehicle Make and Model Recognition (VMMR) is a hard fine-grain MoreIn the last decade, many researches have been done on fine-grained recognition. The main category of the object is known in this problem and the goal is to determine the subcategory or fine-grained category. Vehicle Make and Model Recognition (VMMR) is a hard fine-grained classification problem, due to the large number of classes, substantial inner-class and small inter-class distance. Furthermore, improving system accuracy leads to increasing in processing time. As we can see the state-of-the-art machine vision tool like convolutional neural networks lacks in real-time processing time. In this paper, a method has been presented briefly for VMMR firstly. Secondly, a cascading scheme for improving both speed and accuracy of this VMMR system has been proposed. In order to eliminate extra processing cost, the proposed cascading scheme applies classifiers to the input image in a sequential manner. Some effective criterions for an efficient ordering of classifiers are proposed and finally a fusion of them is used in the cascade algorithm. For evaluation purposes, a new dataset with more than 5000 vehicles of 28 different makes and models has been collected. The experimental results on this dataset and comprehensive CompCars dataset show outstanding performance of our approach. Our cascading scheme results up to 80% increase in the system processing speed. Manuscript profile -
Open Access Article
457 - An Efficient Routing Algorithm for Three-Dimensional Networks On-Chip with Partially Vertical Links
F. Vahdat Panah Ahmad patooghyThree-Dimensional Chips are made of stacking silicon layers which communicate with each other by Through-Silicon-Via (TSV) links. Manufacturing cost of Three-Dimensional chips is a function of the number of TSVs because the fabricating of a three-dimensional chip with f MoreThree-Dimensional Chips are made of stacking silicon layers which communicate with each other by Through-Silicon-Via (TSV) links. Manufacturing cost of Three-Dimensional chips is a function of the number of TSVs because the fabricating of a three-dimensional chip with fully vertical links is of high cost and high fabrication complexity. The packet routing strategies in the 3D NoCs with partially TSVs is more complex than that in the 2D NoCs. In this paper, we proposed a routing algorithm for the 3D NoCs with partial TSVs, which provides a dynamic routing with maximum adaptivity for packets by dividing the network into three groups of layers, rows and columns. This algorithm is independent of vertical channel's position but related to layer number of the current packet and based on the layer number, odd or even, uses a special turn strategy to route packets on rows and columns with odd or even numbers. The proposed routing algorithm mitigates deadlock and livelock with only two virtual. The experiments show that average packet latency in proposed algorithm is 32.8% smaller than that in Elevator_First which is a well-known algorithm for packet routing in 3D chips. Also, this improvement on average packet latency and network throughput will be more with increasing on network size and reduction on TSV number. Manuscript profile -
Open Access Article
458 - Analyzing the Optimization Problem of Resource Allocation in SIP Proxies and Providing an Overload Control Algorithm with Max-min Fairness
M. Jahanbakhsh S. V. Azhari V. GhasemkhaniSession Initiation Protocol (SIP) is an application layer protocol designed to create, manage, and terminate multimedia sessions in the IP multimedia subsystem (IMS). The widespread use of this protocol results in high traffic volume over SIP proxies, requiring delicate MoreSession Initiation Protocol (SIP) is an application layer protocol designed to create, manage, and terminate multimedia sessions in the IP multimedia subsystem (IMS). The widespread use of this protocol results in high traffic volume over SIP proxies, requiring delicate CPU allocation to flows. In this paper, we analyze the optimization problem of resource allocation in SIP proxies with two objective functions: maximizing total throughput and minimizing the least squares. Maximizing total throughput, prioritizes intra-domain flows over inter-domain ones, as the latter pass through two intermediate proxies. On the other hand, minimizing the least squares corresponds to a max-min fairness policy. Hence, we use round robin scheduling in proxies. In addition, we propose a SIP overload control algorithm that limits re-transmissions and prevents instability of proxies by controlling the length of SIP message backlog for each flow. This algorithm leads to better use of processing resources, in comparison with existing overload control algorithms. Manuscript profile -
Open Access Article
459 - Using Clustering and a Hybrid Method to Fill the Numeric Missing Values
A. M. SefidianEstimation of missing values is an important step in the preprocessing. In this paper, at two-step approach is proposed to fill the numeric missing values. In the first step, data is clustered. In the second step, the missing data in each cluster are estimated using a c MoreEstimation of missing values is an important step in the preprocessing. In this paper, at two-step approach is proposed to fill the numeric missing values. In the first step, data is clustered. In the second step, the missing data in each cluster are estimated using a combination of weighted k nearest neighbors and linear regression methods. The correlation measure is employed to determine the appropriate method for the filling of missing data in each cluster. The quality of estimated missing values is evaluated using the root mean squared error (RMSE) criterion. Effect of different input parameters on the error of estimated values is investigated. Moreover, the performance of the proposed method for the estimation purpose is evaluated on five datasets. Finally, the efficiency of the proposed method is compared to four different estimation methods, namely, Mean estimation, multi-layer perceptron (MLP) based estimation, fuzzy C-means (FCM) based approximation method, and Class-based K-clusters nearest neighbor imputation (CKNNI) method. Experimental results show that the proposed method produces less error in comparison to other compared methods, in most of the cases. Manuscript profile -
Open Access Article
460 - Observable Optimized Selective Hardening of Combinational Circuits against Soft-Error
R. Niaraki Asli H. SalemiDue to the shrinking of feature size, reduction in supply voltage and technology scaling, the sensitivity to radiation induced transient faults of digital systems has dramatically increased. Soft error causes transient distortion in circuit operation and is expected to MoreDue to the shrinking of feature size, reduction in supply voltage and technology scaling, the sensitivity to radiation induced transient faults of digital systems has dramatically increased. Soft error causes transient distortion in circuit operation and is expected to become very important in combinational logic with increment of the circuit frequency. In this paper, we introduce an optimized method for hardening of combinational logic circuits against soft errors. In this method, first we have found the most sensitive nodes of the circuit by observability computations. Next for optimizing power-delay product and area, the reliability of the circuit has been computed and the number of the necessary nodes for hardening will be identified. In the next step, three different hardening methods including time redundancy, Schmitt trigger and transistor feedback have been carried out on standard test circuits as our vehicles. The comparison of three method results show that the hardened circuits with Schmitt trigger have the most cumulative critical charge and the least power-delay product and lead to an optimum hardening. Moreover, the simulation results approve the optimized hardening is obtained from suitable selecting the number of required nodes considering observability concepts and reliability computations together with the best node hardening method. Monte-Carlo simulations also approve the performance of the proposed method against process variations. Manuscript profile -
Open Access Article
461 - Design of Quantum Reversible Ternary Multiplexer and Demultiplexer Circuits
M. Haghparast A. Taheri MonfaredMultiplexer and demultiplexer circuits are among the main circuits in designing the complicated hardware. Therefore, enhancing their performance is very important. In the last few years one of the cases that got the attention of the researchers is designing circuits wit MoreMultiplexer and demultiplexer circuits are among the main circuits in designing the complicated hardware. Therefore, enhancing their performance is very important. In the last few years one of the cases that got the attention of the researchers is designing circuits with low power. Using the reversible logic in designing the circuits can reduce power dissipation and power consumption. Using the ternary logic also leads to a better performance, reducing the power consumption and enhancing of fault tolerance in reversible circuits. In this paper, we have presented quantum reversible ternary multiplexer and demultiplexer circuits, we have used reversible ternary shift and controlled Feynman gates. Presented circuits in this paper have a better performance in compared to the previous designs. The improvements are reported. Manuscript profile -
Open Access Article
462 - Placement of AVRs and Reconfiguration of Distribution Networks Simultaneously and Robust Considering Load Uncertainty
M. R. Shakarami Y. Mohammadi Pour: In this paper, optimal locating for AVRs and reconfiguration of distribution networks were assessed simultaneously as an optimization problem. A new objective function was introducing which incorporated several electrical indices including real power losses, reactive More: In this paper, optimal locating for AVRs and reconfiguration of distribution networks were assessed simultaneously as an optimization problem. A new objective function was introducing which incorporated several electrical indices including real power losses, reactive power losses, reliability, voltage profile, voltage stability, and load capacity of lines (MVA). Various load levels were incorporated into the objective function to make sure that switch status in reconfiguration and AVR taps and locations would be robust against load variations. This paper also introduced a new method for calculating the load levels with respect to load uncertainty. It also considered all loads based on a voltage-dependent model. Several scenarios are defined to thoroughly assess the proposed approach. Integer particle swarm optimization algorithm (IPSO) was used to solve the mentioned optimization problem. The results obtained by the simulation of 33-bus and 69-bus standard IEEE .radial power distribution networks demonstrated the effectiveness of the proposed approach Manuscript profile -
Open Access Article
463 - Transmission Expansion Planning in a Deregulated Power System Using Multiobjective Differential Evolution Algorithm
f. rashidiTransmission lines are widely used for transferring electrical energy from power plants to loads, interconnecting load centers and improving reliability of power systems. Due to recent society developments, the need for electrical energy has increased which in turn requ MoreTransmission lines are widely used for transferring electrical energy from power plants to loads, interconnecting load centers and improving reliability of power systems. Due to recent society developments, the need for electrical energy has increased which in turn requires more investment in constructing additional electrical transmission lines. Power system restructuring and deregulation has increased uncertainties in transmission expansion planning and made investment in electrical transmission lines more complicated and less appealing for private parties. This paper proposes a new approach for transmission line expansion planning in deregulated networks. To do that, a multi objective programming problem which consists of various objective functions such as minimizing capital investment for constructing new transmission lines, minimizing congestion in transmission lines and maximizing the investment from private parties is suggested such that access to competitive, economic and reliable energy market is facilitated. To solve the proposed multi objective optimization problem, the Pareto differential evolution algorithm is used. Applying this algorithm to the proposed multi objective programming problem generates set of optimal plans that shows the best compromise between objective functions. The final plan, among the generated plans, is selected using a max-min fuzzy decision making. The proposed method is applied on the IEEE 24 bus test system and effectiveness of the proposed method is verified. Manuscript profile -
Open Access Article
464 - Optimal Sitting and Sizing of Renewable Energy Sources and Charging Stations Simultaneously Based on Improved GA-PSO Algorithm
M. Rezaei Mozafar M. Rezaei MozafarDue to the stochastic nature of renewable energy sources (RES) and electric vehicles (EV) load demand, large scale penetration of these resources in the power systems can stress the reliable network performance, such as reducing power quality, increasing power losses, a MoreDue to the stochastic nature of renewable energy sources (RES) and electric vehicles (EV) load demand, large scale penetration of these resources in the power systems can stress the reliable network performance, such as reducing power quality, increasing power losses, and voltage deviations. These challenges must be minimized by optimal planning based on the variable output from RES to meet the additional demand caused by EV charging. In this paper, a novel method for optimal locating and sizing of RES and EV charging stations simultaneously and managing vehicle charging process is provided. A multi-objective optimization problem is formulated to obtain objective variables in order to reduce power losses, voltage fluctuations, charging and demand supplying costs, and EV battery cost. In this optimization problem, the location and capacity of RES and EV charging stations are the objective variables. Coefficients which are dependent on wind speed, solar radiation, and hourly peak demand ratio for the management of the EV charging pattern in low load hours are introduced. GA-PSO hybrid improved optimization algorithm is used to solve the optimization problem in five different scenarios. The performance of the proposed method on IEEE 33-bus system has been investigated to validate the effectiveness of the novel GA-PSO method to optimal sitting and sizing of RES and EV charging stations simultaneously Manuscript profile -
Open Access Article
465 - A Generalized Relationship for Calculation of Critical Inductance in an n-Input Buck DC-DC Converter
critical inductance is one of the factors that decides continuous, boundary or discontinuous conduction mode of dc-dc converters. In applications like mining, the Continuous Conduction Mode (CCM) and consequently safety of converter can be guaranteed by proper selection Morecritical inductance is one of the factors that decides continuous, boundary or discontinuous conduction mode of dc-dc converters. In applications like mining, the Continuous Conduction Mode (CCM) and consequently safety of converter can be guaranteed by proper selection of inductance. So, calculation of critical inductance and proper sizing of inductor is an important issue in designing of dc-dc converters. In this paper, a non-isolated n-input buck dc-dc converter is introduced. Then, the operational modes and energy transfer process is investigated and discussed in detail. The critical inductance is calculated for 3 and 4-input versions. Using the inductive reasoning, a generalized relationship is proposed for calculation of critical inductance of converter with any number of inputs (n-input version). The proposed generalized relationship not only reduces the amount and time of calculation in design stage, but also presents a better view of performance of converter. The 3 and 5-input version of converter has been modeled and simulated in PSCAD/EMTDC software. Also, the 3-input version of converter has been practically implemented. The obtained simulation and experimental results confirm the validity of proposed generalized relationship for critical inductance calculation of n-input buck dc-dc converter. Manuscript profile -
Open Access Article
466 - A Generalized Relationship for Calculation of Critical Inductance in an n-Input Buck DC-DC Converter
K. Varesi S. H. Hosseini M. Sabahi E. Babaeicritical inductance is one of the factors that decides continuous, boundary or discontinuous conduction mode of dc-dc converters. In applications like mining, the Continuous Conduction Mode (CCM) and consequently safety of converter can be guaranteed by proper selection Morecritical inductance is one of the factors that decides continuous, boundary or discontinuous conduction mode of dc-dc converters. In applications like mining, the Continuous Conduction Mode (CCM) and consequently safety of converter can be guaranteed by proper selection of inductance. So, calculation of critical inductance and proper sizing of inductor is an important issue in designing of dc-dc converters. In this paper, a non-isolated n-input buck dc-dc converter is introduced. Then, the operational modes and energy transfer process is investigated and discussed in detail. The critical inductance is calculated for 3 and 4-input versions. Using the inductive reasoning, a generalized relationship is proposed for calculation of critical inductance of converter with any number of inputs (n-input version). The proposed generalized relationship not only reduces the amount and time of calculation in design stage, but also presents a better view of performance of converter. The 3 and 5-input version of converter has been modeled and simulated in PSCAD/EMTDC software. Also, the 3-input version of converter has been practically implemented. The obtained simulation and experimental results confirm the validity of proposed generalized relationship for critical inductance calculation of n-input buck dc-dc converter. Manuscript profile -
Open Access Article
467 - Optimal and Simultaneously Compensation of Active, and Reactive Powers in Power System Using of Plug in Electric Vehicle
f. rashidi H. Feshki FarahaniPlug in electric vehicles besides environment pollution reduction can help power system operation. One of the most important capabilities of them is providing activeand reactive power. This paper considers grid constraints, technical concerns and market price and propos MorePlug in electric vehicles besides environment pollution reduction can help power system operation. One of the most important capabilities of them is providing activeand reactive power. This paper considers grid constraints, technical concerns and market price and proposes a framework to allocate the PEV capacity such that operational cost paid by distribution system operator (DSO) to power provider of active and reactive power is minimized. For this purpose, an objective function is defined that includes the payment for each power provider. This objective function is minimized based on particle swarm optimization subject to grid and vehicles constraints. In this framework, the PEVs compete with generator to produce active and reactive power. In order to accelerate the optimization process and prevent the algorithm from being trapped in local optima, new heuristic approaches are included to the original PSO algorithm. To evaluate the effectiveness of the propose method, it is implemented on the low voltage with 134 customer and including the other power providers and the amount of each participants production and payment cost to each component is determined. Manuscript profile -
Open Access Article
468 - Analysis and Expansion of a Compact Model of Propagation Delay Time for Nano-CMOS NAND Gates in Response to Statistical Variability of Fabrication
H. Jooypa D. DidebanWith shrinking transistor dimensions into nano meter scale, electrical parameters of transistors become more sensitive against statistical or random variations. Moreover, accurate estimation of these variations using “atomistic simulators” is time consuming and not a co MoreWith shrinking transistor dimensions into nano meter scale, electrical parameters of transistors become more sensitive against statistical or random variations. Moreover, accurate estimation of these variations using “atomistic simulators” is time consuming and not a cost effective approach. In this paper for the first time, analytical models have been used to study the impacts of statistical variability of fabrication process on propagation delay time in a 35 nm CMOS NAND gate. With selecting appropriate set from analytical model’s parameters, the impact of statistical variability on the propagation delay time have been modeled and extended. Moreover, target analytical model has been benchmarked against statistical variability of fabrication process. The results obtained from extension of this model have been compared with the accurate atomistic simulations. It is observed that by applying different sets of parameters the maximum error of propagation delay time reaches to 8.7% against accurate atomistic simulations but by applying our proposed approach, Standard Deviation (SD) error of propagation delay is estimated to 2.4%. Also the SD error of propagation delay reaches to 9.9% when normal regenerated parameters have been used. Eventually using proposed algorithm which encompasses regenerated Gaussian parameters while taking the correlation factor into account, the SD error decreases to 1.6%. Manuscript profile -
Open Access Article
469 - A Game Framework for Congestion Management Based on Generators Re-Dispatching and Demand Response
Ali R. Reisi S. M. HosseinianThis paper proposes a new algorithm for addressing the congestion problem in the network through generation and demand rescheduling. A demand response market based programming is developed for demand rescheduling by capturing the benefit of retailers. In the proposed al MoreThis paper proposes a new algorithm for addressing the congestion problem in the network through generation and demand rescheduling. A demand response market based programming is developed for demand rescheduling by capturing the benefit of retailers. In the proposed algorithm two tasks are implemented by the ISO for controlling network security and spark prices. In the case of any network defect, generator re-dispatching is conducted by the ISO and in the case of any spark price, retailers’ demands in specific buses decrease via some economic signals, sent by the ISO. Having such economic signalsthe retailers then participate in a demand response trade with demand response aggregators (DRAs) to optimize their incomes and next to resubmit their demands to the ISO. A Stackelberg game is employed to capture the interplay among retailers, the leaders, and DRAs, the followers. Retailers choose their strategies, the amount and price of required demand response. Then, DRAs compete based on the retailers’ strategies to maximize their payoffs and to choose their strategies, the demand response sale amount. An IEEE bus test network with 14 buses is considered to demonstrate the feasibility of the proposed method. The paper demonstrates that the proposed method enables to alleviate the congestion problem while the retailers’ incomes increase. Manuscript profile -
Open Access Article
470 - Double-band Hysteresis Current Controller to Reduce Switching Losses of BLDC Drive and Its Comparison with Single-Band Hysteresis
H. Torkaman M. R. Hassanzadeh AghdamIn this paper, a double-band hysteresis current controller (DBHCC) as a new switching method in feeder inverter of a BLDC motor is proposed and implemented. Then, it is compared with the single-band hysteresis current controller (SBHCC). It has been shown that in the pr MoreIn this paper, a double-band hysteresis current controller (DBHCC) as a new switching method in feeder inverter of a BLDC motor is proposed and implemented. Then, it is compared with the single-band hysteresis current controller (SBHCC). It has been shown that in the proposed method, the average switching frequency of switches is reduced compared to SBHCC by preserving other advantages. Thus, switching losses are reduced and the lifetime of switches is increased. In addition, it has desirable effects on reducing electromagnetic interferences and noise. In addition, speed control, torque, current ripple and transient states are investigated in both states. Three-phase reference currents for hysteresis switching are obtained using a PI regulator and integrating with output signals from Hall-effect sensors. BLDC motors are used widely in the industry due to more advantages in comparison with others. In order to drive this motor, a three-level cascade half-bridge voltage source inverter with constant DC link for each phase is used. Simulation results are obtained and analyzed using MATLAB/Simulink environment. Manuscript profile -
Open Access Article
471 - Multi-Criteria Operation Optimization of Combined Cool, Heat and Power (CCHP) Generation Systems in a Microgrid
M. Setayeshnazar F. AmiriEnergy efficiency is one of the most important issues in the power system studies and many methods are used to improve power systems efficiency. Combined cool, heat and power (CCHP) systems are one of the most important technologies that can improve power system efficie MoreEnergy efficiency is one of the most important issues in the power system studies and many methods are used to improve power systems efficiency. Combined cool, heat and power (CCHP) systems are one of the most important technologies that can improve power system efficiency and these systems use their excess heat for supplying heat and cool loads. This paper presents a framework for optimal operation of CCHP systems in a microgrid. At first the unit cost functions are used to optimize operation of CCHP units. Then the algorithm determines the optimal operating strategy of microgrid units. A multi-criteria operation optimization method is proposed that uses primary energy consumption, pollution emissions and operating costs as criteria. The case study is performed for a nine bus microgrid and the results are compared with reference articles results and the advantage of the proposed method is investigated. Manuscript profile -
Open Access Article
472 - A Cloud-based Learnable Agent-oriented Approach to Control and improve Pacemaker Operation
H. Banki نگار مجمع A. MonadjemiThis paper aims to present a cloud-based learning agent-oriented approach for verification of the pacemaker behavior by monitoring and heart rate adjustment of an arrhythmic patient. In case of the pacemaker failure or inappropriate heart rate generation, the patient is MoreThis paper aims to present a cloud-based learning agent-oriented approach for verification of the pacemaker behavior by monitoring and heart rate adjustment of an arrhythmic patient. In case of the pacemaker failure or inappropriate heart rate generation, the patient is put at risk. Using the proposed approach, one can directs the pacemaker rate to correct one when it is incorrect. Using a learnable software agent, the proposed approach is able to learn un-predefined situations and operates accordingly. The proposed approach is cloud based meaning that it sends a message through cloud in case of a critical situation. After determining the patient heart rate by pacemaker, the proposed method verifies this rate against the predefined physician suggestion and automatically corrects it based on a reinforcement learning mechanism if there is some conflict. The proposed method was implemented and installed on a tablet as a patient mobile device for monitoring the pacemaker implanted in the patient chest. The contrast between results of our approach and expected results existing in the dataset showed our approach improved the pacemaker accuracy until 13.24%. The use of the software agent with reinforcement learning is able to play a significant role in improving medical devices in case of critical situations. Manuscript profile -
Open Access Article
473 - Efficient Multicast Routing in Reconfigurable Networks-on-Chip
F. Nasiri Ahmad KhademzadehSeveral routing algorithms have been presented for multicast and unicast traffic in MPSoCs. Multicast protocols in NoCs are used for clock synchronization, cache coherency in distributed shared memory on-chip multiprocessors, replication and barrier synchronization. Uni MoreSeveral routing algorithms have been presented for multicast and unicast traffic in MPSoCs. Multicast protocols in NoCs are used for clock synchronization, cache coherency in distributed shared memory on-chip multiprocessors, replication and barrier synchronization. Unicast routing algorithms are not useful for multicast. Indeed, when unicast routing algorithms are employed to realize multicast operation, high traffic, congestion and deadlock are imposed to the network. To prevent from these problems, Tree-based and path based techniques have been proposed for multicast in multicomputers (and recently NoCs). In this paper, we present a new multicast routing method to decrease power consumption and multicast message latency based on a reconfigurable NoC architecture. In this line, we benefit from simple switches in our reconfigurable architecture instead of routers; we then divide the network to smaller partitions to make better trees for conducting multicast packets. Our evaluation results reveal that, for both real and synthetic traffic loads, the proposed method outperforms the baseline tree-based routing method in a reconfigurable mesh, and reduces message latency by up to 51% and power consumption by up to 33%. Manuscript profile -
Open Access Article
474 - A Hybrid-Based Feature Selection Method for High-Dimensional Data Using Ensemble Methods
A. Rouhi H. Nezamabadi-pourNowadays, with the advent and proliferation of high-dimensional data, the process of feature selection plays an important role in the domain of machine learning and more specifically in the classification task. Dealing with high-dimensional data, e.g. microarrays, is as MoreNowadays, with the advent and proliferation of high-dimensional data, the process of feature selection plays an important role in the domain of machine learning and more specifically in the classification task. Dealing with high-dimensional data, e.g. microarrays, is associated with problems such as increased presence of redundant and irrelevant features, which leads to decreased classification accuracy, increased computational cost, and the curse of dimensionality. In this paper, a hybrid method using ensemble methods for feature selection of high dimensional data, is proposed. In the proposed method, in the first stage, a filter method reduces the dimensionality of features and then, in the second stage, two state-of-the-art wrapper methods run on the subset of reduced features using the ensemble technique. The proposed method is benchmarked using 8 microarray datasets. The comparison results with several state-of-the-art feature selection methods confirm the effectiveness of the proposed approach. Manuscript profile -
Open Access Article
475 - Next Hop Selection to Configuring the Route in LEAP Protocol Based on Fuzzy Logic in WSNs
Vahid Sattari-Naeini F. MovahhediSince in wireless sensor networks, selection of next hop is critical in attack avoidance and lowering the power consumption, a method based on fuzzy logic is proposed in this paper considering status and report transmission of the nodes. In this method, the next hop is MoreSince in wireless sensor networks, selection of next hop is critical in attack avoidance and lowering the power consumption, a method based on fuzzy logic is proposed in this paper considering status and report transmission of the nodes. In this method, the next hop is selected considering four factors, based on fuzzy logic system. These factors, indicating four optimized parameters; i.e., degree of node proximity to the shortest path, degree of node proximity to the sink, residual energy ratio of each node, and the number of false filtered messages. This method leads to an increase in energy level as well as maintaining security level in comparison with LEAP protocol. Meanwhile, it is possible to identify safe paths. Comparing with other related methods, it is shown that this method leads to significant reduction in energy consumption level and consequently the life-time of the network is increased. Meanwhile with selecting the appropriate next hop, packet drops are reduced as well. Manuscript profile -
Open Access Article
476 - Mobility-Aware and Fault-Tolerant Computation Offloading for Mobile Cloud Computing
R. Roostaei Z. MovahediNowadays, Internet of Things (IoT) has emerged as an important field in information and communication technologies. Despite the progress of networks and communication technologies, the development of IoT has encountered some challenges mainly with regard to computation MoreNowadays, Internet of Things (IoT) has emerged as an important field in information and communication technologies. Despite the progress of networks and communication technologies, the development of IoT has encountered some challenges mainly with regard to computation power, battery lifetime and memory of mobile devices. In order to overcome these challenges, mobile cloud computing has been raised which uses the cloud storage space and computation power to extend the capabilities of mobile devices. In this regard, some of application’s components are selected to be offloaded to the cloud in order to optimize the execution time and energy consumption of application. Since the mobility has an important effect on the acquired condition of the access network and the quality of the connection, the mobility should be considered while selecting components for offloading. Although a number of mobility-aware offloading approaches has been already proposed, these works suffer from the lack of an appropriate mobility-model, ignorance of the fault-tolerance capability and use of only coarse-grain offloading. In order to address these issues, we propose a mobility-aware offloading scheme which uses the user mobility Markov chain and the fault tolerance capability in order to optimize the offloading decision. Evaluation results show that our proposed method significantly outperforms the existing alternatives, reaching respectively up to 75 and 65 percent enhancement in terms of the execution time and the energy consumption. Manuscript profile -
Open Access Article
477 - Seam Carving Speed Improvement by Odd and Even Subimages Decomposition
F. Siar S. MozaffariSeam carving is one of content aware image retargeting techniques. In this method, a path of pixels with lowest energy, called seam, crossing from top to bottom or from left to right in an image is extracted. By removing or inserting seams, size of the image can be chan MoreSeam carving is one of content aware image retargeting techniques. In this method, a path of pixels with lowest energy, called seam, crossing from top to bottom or from left to right in an image is extracted. By removing or inserting seams, size of the image can be changed. Speed and quality are two main parameters in seam carving. In this paper a new method for speed enhancement of seam carving is proposed. The input image is decomposed into odd and even subimages and searching for seams is performed in parallel in these subimages. Compared to the original seam carving, the proposed method improves the speed at least by two times while maintain image’s quality unchanged. Previous seam searching algorithms can be utilized in our method or it can be combined with other parallel processing schemes. Finally, image quality of the proposed seam carving is improved. Manuscript profile -
Open Access Article
478 - Separating Bichromatic Point Sets by Fixed Angle Double Wedges
M. Maleki Shahrakiand A. Bagheri M. NayeriThe point-set covering is one of the important problems in computational geometry, which has many applications. In this problem, the given points should be covered by at least one geometric shape. A variant of the problem is the point-set separation, in which there are MoreThe point-set covering is one of the important problems in computational geometry, which has many applications. In this problem, the given points should be covered by at least one geometric shape. A variant of the problem is the point-set separation, in which there are at least two different kinds of points which are colored by different colors. The geometric shapes, which are called separators, should only cover the points of the same color. In this paper, separation of blue and red points by a double-wedge of a given angle θ is considered. The proposed algorithm reports all separator θ angle double-wedges in optimal time O(nlogn). Manuscript profile -
Open Access Article
479 - Adaptive Traffic Classification Algorithm for Live IPTV in EPON
M. Ahmadzadeh Bolghan Olia Mohammad Behdadfa M .R. NourifardIn this paper, An IPTV packet classification algorithm is introduced with adaptive adjustment property and the objective of reducing packet loss ratio in Ethernet passive optical networks. The proposed algorithm, improves weight allocation for WRR scheduling using prope MoreIn this paper, An IPTV packet classification algorithm is introduced with adaptive adjustment property and the objective of reducing packet loss ratio in Ethernet passive optical networks. The proposed algorithm, improves weight allocation for WRR scheduling using proper classification and prioritization of arriving packets to OLT. Based on simulation results with NS2 simulator, the packet loss ratio of proposed algorithm, shows a 65% reduction compared to existing methods which leads to perceptible user quality of experience improvement. Manuscript profile -
Open Access Article
480 - Evaluation of Resonance Existence in Optimal Allocation of Capacitors in Distribution Networks
M. Ayoubi R. Hooshmand M. Torabian EsfahaniOne of the most important problems in power networks is the presence of resonance at some of the buses which leads to an unwanted increase in voltage and current and damage to equipment. Since with installing a capacitor bank in the network, frequency characteristic of MoreOne of the most important problems in power networks is the presence of resonance at some of the buses which leads to an unwanted increase in voltage and current and damage to equipment. Since with installing a capacitor bank in the network, frequency characteristic of the system is changed and resonance is increased, it is necessary to consider this point in allocation of capacitors in the network. In this paper, a new index for evaluating the resonance is presented. Applying the proposed resonance index, a new two-step method for optimal placement of capacitors in a harmonic system is provided. In the first step, a sensitivity analysis is used, then in the second step, the objective function considering technical constraints is optimized using a fuzzy technique. The proposed method is implemented with the MSPSO algorithm on the IEEE 18-bus network. The results show the efficiency of this method in comparison with other methods. Manuscript profile -
Open Access Article
481 - Two New Switching Methods to Speed Control of Induction Motor with Eleven Levels Inverter
M. S. Orfi Yegane N. Ghaffarzadeh Mohammad SarviBy using usual industrial switching methods, two new multicarrier PWM (MCPWM) methods are proposed in this paper to improve the output voltage characteristics for eleven levels diode-clamped inverter. DC component and Even harmonic orders of the output voltage are total MoreBy using usual industrial switching methods, two new multicarrier PWM (MCPWM) methods are proposed in this paper to improve the output voltage characteristics for eleven levels diode-clamped inverter. DC component and Even harmonic orders of the output voltage are totally eliminated in the proposed VFCBOD and COOD methods by applying the phase shift in the carrier wave (carrier-based); so total harmonic distortion (THD) and torque ripple are reduced. By using the both proposed methods, the number of pulses per cycle equally are distributed and increased the lifetime of the switches. In this paper, a full bridge has been series with each phase of eleven levels diode-clamped inverter to change the polarity of the voltage to produce more switching patterns to generate the specified voltage levels. Then, by determining suitable switching patterns, the inverter can be driven with the least of switches when there is a failure and finally increased the reliability of the whole system. Manuscript profile -
Open Access Article
482 - Predictive Control of Modular Multilevel Converters Using Sphere Decoding Algorithm
H. Shafaiyeh Hiag R. Mahboobi Esfanjani Mohammad HejriModular Multilevel Converters, by increasing the number of voltage levels the quality of output waveform is improved and the semiconductor switches tolerate low voltage values. However, design of switching strategy in these complicated circuits is challenging. In this p MoreModular Multilevel Converters, by increasing the number of voltage levels the quality of output waveform is improved and the semiconductor switches tolerate low voltage values. However, design of switching strategy in these complicated circuits is challenging. In this paper, based on sphere decoding algorithm, a predictive controller with finite control set is proposed to regulate load current while minimizing both capacitor voltage variations and circulating currents. The suggested scheme decreases the computational burden of optimization stage which is considerable for long prediction horizons and modular converters with high number of voltage levels. The suggested scheme is simulated for a practical modular multilevel converter to demonstrate its performance compared to some rival methods. Manuscript profile -
Open Access Article
483 - Optimum Design of Out-runner PM BLDC Motor with High Torque Density for Flywheel Applications as Energy Storages: Design, FEA and Fabrication
O. Safdarzadeh H. Torkaman Mohammad Mahdavy FakhrOptimum design of electrical motors may be considered as a complex optimization problem due to the wide variety of mechanical, electrical, electromagnetics parameters, although recently it can be accomplished utilizing heuristic optimization algorithms. In this paper op MoreOptimum design of electrical motors may be considered as a complex optimization problem due to the wide variety of mechanical, electrical, electromagnetics parameters, although recently it can be accomplished utilizing heuristic optimization algorithms. In this paper optimum design of an out-runner PM BLDC motor for flywheel energy storage applications is performed. The optimization utilized particle swarm optimization (PSO) algorithm to achieve maximum torque density. Accordingly, the motor design equations are employed in the fitness function of the algorithm. Based on the random initial values and respecting the designs constraints, the optimum design is achieved. Effectiveness of the algorithm results are verified by finite element analysis (FEA) and motor operating parameters are obtained and analyzed. Finally, the prototype of the motor is fabricated and experimental results are demonstrated to show the applicability of the model and analysis. Manuscript profile -
Open Access Article
484 - Reducing OFF-State Current in Nano-Scale Double Gate Junctionless Field Effect Transistor (DGJL-FET) Using Doping Engineering of Channel Region
S. Kalantari M. VadizadehScaling the channel length leads to the increased leakage current of double gate junctionless field effect transistor (DGJL-FET) and, as a result, the increased power consumption in OFF-state. The present paper proposes a new structure for reducing the leakage current i MoreScaling the channel length leads to the increased leakage current of double gate junctionless field effect transistor (DGJL-FET) and, as a result, the increased power consumption in OFF-state. The present paper proposes a new structure for reducing the leakage current in DGJL-FET, which is called modified DGJL-FET. In this structure, the channel doping under the gate is the same as the drain and source doping but higher than the mid-channel doping. The simulation results indicated that reducing the thickness of the doped layer under the gate, D, resulted in the reduced OFF-state current. For the proposed device with 10 nm channel length, the OFF-state current is less than that in the regular DGJL-FET by two orders of magnitude. Performance of the regular DGJL-FET and modified DGL-FET for different channel lengths is compared based on the IOFF/ION ratio, sub-threshold slope (SS), and intrinsic gate delay. For modified DGJL-FET, the mid-channel doping and Dare considered as additional parameters for improving the device’s performance in nanometer regime. The simulation results indicated that in the proposed device with channel length of 15 nm, values of SS and IOFF/ION ratio are improved compared to the regular DGJL-FET by 14% and 106 orders of magnitude, respectively. Manuscript profile -
Open Access Article
485 - Design, Simulation and Fabrication of Compact Microstrip Coupler with Performance Improvement and Harmonic Suppression
T. Barati Kashantoui S. RoshaniIn this paper a novel branch line coupler (BLC) with size reduction and performance improvement at 2.4 GHz is proposed. The proposed branch line coupler suppresses the second harmonic with 38.55 dB attenuation level. The scattering parameters of the proposed BLC are giv MoreIn this paper a novel branch line coupler (BLC) with size reduction and performance improvement at 2.4 GHz is proposed. The proposed branch line coupler suppresses the second harmonic with 38.55 dB attenuation level. The scattering parameters of the proposed BLC are given as follows: S11= -67.67 dB, S12= -2.95 dB, S13= -3.09 dB and S14= -49.78 dB. The bended line structures and open-ended stubs are used in design process. The proposed BLC has 45.4% size reduction compare to the conventional one. The proposed device fabricated on RT/Duroid 5880 substrate. Manuscript profile -
Open Access Article
486 - A New State Estimator in Distribution Systems
S. Sabzebin F. KarbalaeiDue to the lack of measurement in distribution systems, state estimation has particular importance. Different methods are presented to improve the accuracy of system state with limited measurements. In this paper a new state estimator in distribution systems are offered MoreDue to the lack of measurement in distribution systems, state estimation has particular importance. Different methods are presented to improve the accuracy of system state with limited measurements. In this paper a new state estimator in distribution systems are offered. This estimator bases on backward forward load flow estimates system state with adjusting load consumption at each step. Voltage measurements in slack bus, loads and zero injection measurements are inputs of estimator. This estimator is compared with weight least square estimator and its results are shown. The estimator calculates voltage magnitude with less error and also faster than WLS estimator. 85-bus system is presented in this paper. Manuscript profile -
Open Access Article
487 - Performance Analysis of Three Phase Four Leg Boost Rectifier with One Cycle Control Under Unbalanced Loads
M. ArehpanahiHarmonic pollution of source currents and poor power factor are the main challenges of rectifiers. In this paper using one cycle control strategy, rectifiers can be operated at unity power factor. For performance analysis of this method harmonic injection and unbalanced MoreHarmonic pollution of source currents and poor power factor are the main challenges of rectifiers. In this paper using one cycle control strategy, rectifiers can be operated at unity power factor. For performance analysis of this method harmonic injection and unbalanced load applied to the source side considered. Simulation results show that combination of three phase four leg rectifier with one cycle control can be improved power factor and harmonic pollution reduction especially in nonlinear and unbalanced loads in the source side. Manuscript profile -
Open Access Article
488 - Investigation of Fundamental Mode of Ferroresonance for Transformer considering the Inverse JA Hysteresis Model
B. Rezaeealam M. Mikhak BeyranvandSevere saturation of the magnetic core is the most influential factor in ferroresonance that leads to distorted currents and voltages. , modeling the nonlinear behavior of the magnetic core is the most important challenge in ferroresonance study. In this paper, finite e MoreSevere saturation of the magnetic core is the most influential factor in ferroresonance that leads to distorted currents and voltages. , modeling the nonlinear behavior of the magnetic core is the most important challenge in ferroresonance study. In this paper, finite element method in conjunction with the inverse Jiles-Atherton (JA) hysteresis model of the steel core, is employed for modeling of a single-phase transformer accurately. Then, ferroresonance is studied by inserting different capacitors in series with the unloaded transformer, and the corresponding variation of copper losses and iron losses are obtained and discussed. Ferroresonance affects the shape of the hysteresis loop that necessitates the retuning of the parameters of the JA hysteresis model. The numerical results agree well with the experimental ones. Manuscript profile -
Open Access Article
489 - Handover Management between Femtocell and Macrocell Using Geo-Based Spectral Clustering
T. Bahraini M. Zamiri H. Sadoghi YazdiAvailable techniques in handover management in cellular communication networks can’t keep unnecessary events and delay decision at a low level state. The main purpose of this paper is to provide the intelligence method which is able to minimize the number of unnecessary MoreAvailable techniques in handover management in cellular communication networks can’t keep unnecessary events and delay decision at a low level state. The main purpose of this paper is to provide the intelligence method which is able to minimize the number of unnecessary events and allowing the necessary requests to occur and so improves the overall network performance. In order to achieve such a goal, in the proposed method, we have used the geographical knowledge from building maps with spectral clustering in the area covered by femtocell. Therefore, we require to develop the spectral clustering based on geographical information. The experimental results on real dataset and performed simulations indicate that the superiority of the proposed method in allocating the user to appropriate cell and acceptable ability to manage the handover in heterogeneous layer of femtocell-macrocell. Manuscript profile -
Open Access Article
490 - How to Identify Requirements under Uncertainty for Self-Adaptive Software Systems Development
R. Moeinfar Ahmad Abdollahzadeh Barforoush S. M. HashemiOne key challenge in software systems development is changing requirements at development phases or run-time. This might happen as the result of uncertainty in stakeholder requirements. Uncertain requirements drive a flexible and therefore adaptable architecture to mana MoreOne key challenge in software systems development is changing requirements at development phases or run-time. This might happen as the result of uncertainty in stakeholder requirements. Uncertain requirements drive a flexible and therefore adaptable architecture to manage risks at run-time. Modeling uncertainty to adapt architecture automatically is an effective solution when requirements change. In order to evaluate requirements and handle uncertainty by modeling and self-managing, it is advantageous to quantify requirements, computationally. This study besides understanding the sources of uncertainty, investigates how to quantify requirements and quality attributes. Subsequently, decision making at all software development phases will be based on numerical analysis that leads to autonomic software development. Manuscript profile -
Open Access Article
491 - Geometrical Self-Organizing Map Classifier Based on Active Learning for Steganalysis in the Video Environment by Spending at Least a Label
H. Sadoghi Yazdi A. Mohiaddini M. KhademiClassifier is one of the three blocks of a video steganalysis that needs labeled for training. In the blind video steganalysis, due to the lack of access to steganography algorithms, it is difficult to label. In this paper, the semi supervised growing self-organizing ma MoreClassifier is one of the three blocks of a video steganalysis that needs labeled for training. In the blind video steganalysis, due to the lack of access to steganography algorithms, it is difficult to label. In this paper, the semi supervised growing self-organizing map classifier has been used to reach the minimum label. For this purpose, a concept called the geometric redundancy of the lower-layer nodes of the semi supervised self-organizing network has been used. It has been shown that this redundancy will create repetitive patterns of the network, so deleting such nodes is possible. Proven due to the existence of one-to-one correspondence between nodes and labels. Reducing nodes leads to a reduction in the number of labels required. The basic point is the need for a geometric redundancy among a number of nodes, which is a conception of abstraction, is the formation of a group by them. Therefore, the proposed algorithm is based on identifying categories and integrating their members. The classifier obtained on this basis has been named a geometric self-organizing map classifier .It is proven that this classifier can achieve the minimum amount of optimal label. The simulation results show a remarkable superiority over the previous algorithms. Manuscript profile -
Open Access Article
492 - An Efficient Hybrid Routing Protocol in Underwater Wireless Sensor Networks
J. Tavakoli N. MoghimUnderwater Wireless Sensor Network (UWSN) is a kind of sensor networks that their operational fields have been developed under water in recent decades, although these networks deal with lots of challenges due to lack of the GPS1. These networks encounter researchers wit MoreUnderwater Wireless Sensor Network (UWSN) is a kind of sensor networks that their operational fields have been developed under water in recent decades, although these networks deal with lots of challenges due to lack of the GPS1. These networks encounter researchers with many challenges by some limitations like high propagation delay, low bandwidth, high bit error rate, movement, limited battery and memory. In comparison with terrestrial sensor networks, sensors in the UWSN consume energy more because they use acoustic technology to communicate. Motivation of this research is proposing a routing protocol for underwater systematic settings with a limited energy. The settled sensor nodes in underwater cannot communicate directly with nodes near surface, so they need prepared multi hop communications with a proper routing plan. In wireless sensor networks, node clustering is a common way to organize data traffic and to decrease intra-network communications along with scalability and load balance improvement plus reducing of overall energy consumption of system. Therefore, in this article a fuzzy clustering routing protocol with data aggregation and balanced energy consumption for UWSNs is proposed. Simulation results show that in the proposed protocol, energy consumption becomes more uniformly distributed in the network and average of the nodes' energy usage and number of routing packets decreases and finally, packet delivery ratio and throughput are improved in the network in comparison with DABC3 and IDACB4 algorithms. Manuscript profile -
Open Access Article
493 - The Effect of Topic Pattern of Teen Users’ Search Behavior on Query Recommendation
H. Ghasemzadeh Mohammad Ghasemzadeh A. ZarehTeenager users apply a limited vocabulary when they proceed to look for their desired materials. Another important issue is that teenagers often click mostly on the first items presented in the list of the search results. This research shows that, in order to amend and MoreTeenager users apply a limited vocabulary when they proceed to look for their desired materials. Another important issue is that teenagers often click mostly on the first items presented in the list of the search results. This research shows that, in order to amend and compensate these issues, we can extract and suggest a more appropriate query to the teenager user. This can be accomplished by discovering the relevant subject patterns from the behavior of the teenage user according to his or her previous search quarries and based on the already found patterns. In the proposed method, the topic patterns of the user are discovered based on the popularity of the clicks and the most relevant topics from the search logs which are generally massive. Afterwards, by using the binary classification method, the closest query to the query given by the user would be specified. Then, by filtering the subject navigation noise via extraction of the subject patterns of the teen user’s clicks, a user model with a higher accuracy can be obtained. We evaluated performance of the proposed method using the Alteryx and Weka tools, over the AOL search log, which includes about twenty million sample search transactions from six hundred and fifty different users. The results obtained from the experiments indicate that the queries presented by the proposed system are closer to the target user's query, and consequently, leads to achievement of more related results. Manuscript profile -
Open Access Article
494 - Adaptive Educational Hypermedia Web Pages Recommending Based on Learning Automata and User Feedback for Resource-Based Learning
Mohammad Tahmasebi Faranak Fotouhi-Dgazvini M. EsmaeiliPersonalized recommender systems and search engines, are two effective key solutions to overcome the information overloading problem. They use the intelligent techniques on users’ interactions to extract their behavioral patterns. These patterns help in making a persona MorePersonalized recommender systems and search engines, are two effective key solutions to overcome the information overloading problem. They use the intelligent techniques on users’ interactions to extract their behavioral patterns. These patterns help in making a personalized environment to deliver accurate recommendations. In the technology enhanced learning (TEL) field and in particular resource-based learning, recommendation systems have attracted growing interest. Specially, they are an important module of Adaptive Educational Systems that deliver the appropriate learning objects to their users. Gray-sheep users are a challenge in these systems. They have a little similarity with their peers. So the recommendations to others are not suitable for them. To overcome this problem, we propose the idea of accommodating the user’s learning style to web page features. The user's learning style will be computed according to Felder-Silverman theory. On the other hands, the necessary implicit and explicit meta data will be extracted from OCW web pages. By matching the extracted information, the system delivers the appropriate educational links to user. The user can compare the proposed links, based of our algorithm, to the output of Lucene algorithm. A user’s opinion about every web page as a recommended result would be submitted to the system. The system uses a learning automata algorithm and user’s feedback to deliver best recommendations. The system has been evaluated by a group of engineering students to evaluate its accuracy. Results show that the proposed method outperforms the general search algorithm. This system can be used at formal and informal learning and educational environments for Resource-based learning. Manuscript profile -
Open Access Article
495 - A New BGP-based Load Distribution Approach in Geographically Distributed Data Centers
A. Esmaeili B. BakhshiToday, hosting services in geographically distributed data centers is very common among service provider companies, because of more efficiency of energy consumption, high availability of the system, and providing quality of service. Load distribution is the main issue i MoreToday, hosting services in geographically distributed data centers is very common among service provider companies, because of more efficiency of energy consumption, high availability of the system, and providing quality of service. Load distribution is the main issue in the geographical data centers. On the one hand, there are several architectures to distribute load between different clusters, e.g., central load balancer, DNS-based systems, and IGP based schemes; one the other hand, the optimum traffic load balancing between clusters is a very challengeable issue. The proposed solutions have different facilities to distribute incoming traffic; nevertheless, they are vulnerable in terms of propagation delay, centralized load balancer failure, and maintaining connections. In this paper, a new architecture based on BGP and Anycast routing protocols in SDN based data centers is proposed to distribute traffic loads between clusters. Simulation result shows improvement in comparison to the existing techniques. Manuscript profile -
Open Access Article
496 - A New EPC-C1G2 Based Anti-Collision Algorithm to Address Tags’ Starvation in RFID Systems
A. Abbasian M. SafkhaniIn this paper, we present a new EPC-C1G2 standard based anti-collision algorithm to solve the problem of tags’ starvation in RFID systems. Non deterministic identification of tags in the collisions lots, leads to tags’ starvation phenomenon. In this paper, to address th MoreIn this paper, we present a new EPC-C1G2 standard based anti-collision algorithm to solve the problem of tags’ starvation in RFID systems. Non deterministic identification of tags in the collisions lots, leads to tags’ starvation phenomenon. In this paper, to address this problem, we use the position of the first different value bits that are the first different bits in the tags’ 16-bit random number (or RN16).In fact, the reader in facing with collision slots, earns the position of the first different-value bit in RN16 and uses it to deterministic identification of tags. Unlike recent anti-collision algorithms, which in them it is assumed that tags send information synchronous or asynchronous, in the proposed anti-collision algorithm in order to obtain the position of the first different-value bit there is not any assumption on synchronous or asynchronous sending information by tags. Based on simulation which is done, the average time of identification for 200 to 2000tags in the proposed anti-collision algorithm relative to average time of identification in EPC-C1G2, BIS and ERN2 anti-collision algorithms is less than 0.92, 0.71, and 0.42 second, respectively. Manuscript profile -
Open Access Article
497 - Multipath Error Mitigation of Low-Cost GPS Receiver Using PSO-SVM and GA-SVM Hybrid Methods
Mohammad S. E. Abadi M. H. Refan A. DameshghiOne of the major errors that affect GPS accurately is the multi-path effect of each receiver. Multi-paths is receiving an antenna signal from more than one path, multi-path effect is a major source of unknown error in positioning and is not eliminated by differential me MoreOne of the major errors that affect GPS accurately is the multi-path effect of each receiver. Multi-paths is receiving an antenna signal from more than one path, multi-path effect is a major source of unknown error in positioning and is not eliminated by differential methods. This effect is largely dependent on the environment specific to each receiver and it is low-frequency effect. The geometry between GPS satellites and the specific location of each receiver is repeated on astronomical days, the multi-path effects tend to behave similarly on consecutive days. In this paper, a method for extracting the multi-path effects behavior was applied to the GPS-code observations, multi-path error mitigation increases the accuracy of positioning. In the proposed method, the residual signal is generated based on the dual difference (DD) and is used as the input of the proposed algorithm. Support Vector Machine (SVM) is used for multi-path approximation. To determine the basic parameters of SVM and its kernel function, particle optimization algorithms (PSO) and genetic algorithm (GA) were used. In order to evaluate the accuracy of the proposed method, simulation and experimental based on two stations (reference and user) and two low-cost receivers were designed. The proposed methods were tested based on practical data. The experiments showed that the multi-path error of the receiver of the user's station decreased by 70% in the static test based on the RMS criterion. Models of this paper have been compared with some recent models presented in the context of multi-path error reduction. The results showed that the proposed model had better performance than other methods. The result is high accuracy and stability in positioning results. Three-dimensional position accuracy improved by about 56% after using the proposed method, reaching 1.60 m. Manuscript profile -
Open Access Article
498 - LMI Robust Control Design for SIDO Boost Converter Based on SFG Modelling Method
M. Abbasi Mohammad Reza Alizadeh Pahlavani Ahmad AfifiA robust control design process based on a linear Matrix Inequalities (LMI) for a Single Inductor Multi Output (SIMO) boost converter has been presented in this paper. Considering complicated multi-stages operation of SIDO converter, Signal Flow Graph (SFG) modelling wa MoreA robust control design process based on a linear Matrix Inequalities (LMI) for a Single Inductor Multi Output (SIMO) boost converter has been presented in this paper. Considering complicated multi-stages operation of SIDO converter, Signal Flow Graph (SFG) modelling was used to predict all behavior of the converter. Using the SFG model, nonlinearities and uncertainties was modelled as a convex polytope for LMI design constraints. This method guarantees a certain perturbation rejection level and a region of pole location. The derived parameters from LMI were applied on state-feedback coefficients in Matlab/Simulink to show the validity of the presented LMI method. Finally, the obtained results have been compared with a conventional PI controller. Manuscript profile -
Open Access Article
499 - Torque Ripple Reduction Technique in SRM for Low Speed Range by Employing Fuzzy Logic for Dynamic Controlling of TSF
H. Moradi Cheshmeh-Beigi E. NouriIn this paper, in order to reduce torque ripple for low speed range in non-commutation region, instead of exciting by a DC current, a adjustable current according to rotor position is injected. Also, to reduce torque ripple in commutation region the modified torque shar MoreIn this paper, in order to reduce torque ripple for low speed range in non-commutation region, instead of exciting by a DC current, a adjustable current according to rotor position is injected. Also, to reduce torque ripple in commutation region the modified torque sharing function (TSF) method has been used. In the proposed method, TSF is modified by a feedback from the motor speed and applying it to a fuzzy controller according to speed value. In the proposed method, motor speed, torque error, and torque error derivative are used as fuzzy controller inputs, which Turn-On and overlap angles between the phases are changed as a function of motor speed. Also reference torque of adjacent phase is modified as a function of torque error and torque error derivative. In this method, TSF is modified dynamically and momentary. The exact simulation based on Matlab/Simulink for a 3-phase 6/4 SRM are carried out to verify the effectiveness of the proposed novel method for 0 to 1500rpm speed range. Manuscript profile -
Open Access Article
500 - Identification of Coherent Machines Based on Slow Coherency
S. H. Adeli A. RabieeTo study the stability of dynamic systems, it is neither practical nor necessary to model the entire interconnected system in details. In more specific application, such as dynamic security assessment and system control design, reduced order models of the entire system, MoreTo study the stability of dynamic systems, it is neither practical nor necessary to model the entire interconnected system in details. In more specific application, such as dynamic security assessment and system control design, reduced order models of the entire system, or part of it, are needed to satisfy computational or design constraints. In this paper, a dynamic reduction method based on coherency concept is developed and slow coherency identification is used to identify coherency machine. Despite its simplicity, the proposed method provides an effective approach to recognize coherence generators. Furthermore, a new clustering method is suggested in this paper to improve acceleration of coherence machines identification. Finally, the accuracy of proposed method is evaluated by time domain simulation and compared with other methods. The obtained results indicate that the new proposed grouping method works more quickly than the other methods in the area, concluding that, without loss of accuracy, it can be readily used in dynamic studies of power systems. Manuscript profile -
Open Access Article
501 - Nonlinear Analysis of Jitter Transfer in Charge Pump Phase-Locked loops regarding Channel Length Modulation Effect
H. Dehbovid H. Adarang M. B. TavakoliDue to the nonlinear behavior caused by the charge pump, charge pump phase-locked loops (CPPLLs) are nonlinear systems. In an ideal charge pump, the applied current is constant; however, in practice, it is not constant due to the transistor's non-ideal effects. In this MoreDue to the nonlinear behavior caused by the charge pump, charge pump phase-locked loops (CPPLLs) are nonlinear systems. In an ideal charge pump, the applied current is constant; however, in practice, it is not constant due to the transistor's non-ideal effects. In this paper, regarding the transistor's channel length modulation effect (CLM) on charge pump’s current, the non-linear differential equation of the system is obtained and shows that the phase lock loop is a nonlinear system with memory and Voltaire Series expansion can be used to analyze it. As a result, a method for estimating a jitter transfer with a second-order filter is proposed. System level simulation is used to validate the analytical results with particular emphasis on the jitter transfer characteristics. The effect of different loop parameters has also been studied. The experiments all show excellent conformance between analytical equations and simulation results. Manuscript profile -
Open Access Article
502 - The Effect of MIMO Channel Estimator in the Precoder Design of Wireless Sensor Networks
H. Rostami A. FalahatiOne of the most important applications of wireless sensor networks was to estimate the unknown phenomenon. The cooperative activities of wireless sensors and scattered information of sensor nodes over network are used to decentralized estimation. Precoder design done on MoreOne of the most important applications of wireless sensor networks was to estimate the unknown phenomenon. The cooperative activities of wireless sensors and scattered information of sensor nodes over network are used to decentralized estimation. Precoder design done on the sensor nodes in order to provide an optimal estimate of the actual amount. Precoder design is an optimization problem. Since the channel is wireless link on the wireless sensor networks. Therefore, assuming the access of full channel state information isn't correct in this network. Since the perfect channel state information is required in the precoder design process, so the effects of the channel estimation investigated on precoder design process. On the issue of channel estimation, channel estimated by using of the known training sequence method with LS and MMSE criteria. Since power restriction is the key subject in the wireless sensor networks, therefore in this study power restriction considered in the channel estimation and precoder design problem. Manuscript profile -
Open Access Article
503 - Covariance Matrix Design for SINR Enhancement in Presence of Signal-Dependent Interferers
M. Bolhasani S. Imani S. A. GhorashiIn this paper, the problem of covariance matrix design to increase signal-to-interference-plus-noise ratio (SINR) in receiver for multiple-input multiple-output (MIMO) radars is considered. Our goal is to design a covariance matrix which can suppress more interferers co MoreIn this paper, the problem of covariance matrix design to increase signal-to-interference-plus-noise ratio (SINR) in receiver for multiple-input multiple-output (MIMO) radars is considered. Our goal is to design a covariance matrix which can suppress more interferers compared to phased array radar and recent covariance matrix design methods. It can also result in a better SINR level compared to conventional MIMO radars. In this paper, maximum SINR of the proposed covariance matrix is calculated in closed form. Simulation results show that our proposed covariance matrix in addition to achieve better SINR performance, can suppress more interferers compared to phased array radar and recent covariance matrix design methods, by using waveform diversity with the same number of antennas. Simulation results also validate analytical achievements that presented in this paper. Manuscript profile -
Open Access Article
504 - Improving the Power System State Estimation Algorithm Based on the PMUs Placement and Voltage Angle Relationships
A. R. Sedighi M. Sayaf M. R. TabanTo optimize the operation of power systems, monitoring of network state variables is important. Because these variables play an important role in improving economic efficiency, network reliability and analyze system status.Therefore, state estimation algorithm have been MoreTo optimize the operation of power systems, monitoring of network state variables is important. Because these variables play an important role in improving economic efficiency, network reliability and analyze system status.Therefore, state estimation algorithm have been used to determine an accurate estimate of state variables with limited measurements. Since modern measuring devices, such as PMUs, in addition to the measurement of electrical quantities are able to measure bus voltage angle,in this paper, a new method is proposed to obtain a more accurate estimate of all network variable. The proposed algorithm determines number and location of the measuring devices (PMUs) in such a way that state variables and electrical quantities can be obtained in the most accurate estimate. Increasing the state estimation calculations accuracy is due to the use of the derivatives of the buses voltage angle equations along with the state estimation relations. Finally, the calculation of the state estimation is performed using the least squared weighted method (WLS). The calculations performed on the IEEE 14 bus network are done using MATLAB and MATPOWER software. The results show that the proposed method has been successful in increasing the accuracy of estimating state variables and reducing the number and proper location of PMUs . Manuscript profile -
Open Access Article
505 - Design of Floating-Point Multipliers with Normal and Fault-Tolerant Operations Using Reduced-Precision Computin
M. Mohajer M. Taghizadeh FiroozjaeeMultiplication is one of the important computations required for different signal processing applications especially regarding voice and image. However, the multipliers as digital circuits are susceptible to different environmental effects such as noises. In this paper, MoreMultiplication is one of the important computations required for different signal processing applications especially regarding voice and image. However, the multipliers as digital circuits are susceptible to different environmental effects such as noises. In this paper, a new approach is proposed for designing a 32-bit floating-point multiplier which can operate in two operational modes, normal and fault-tolerant, dependent to the environmental conditions. In the fault-tolerant mode, by reducing the normal precision and accepting a negligible error in the output, a portion of preliminary circuit is released which is used for redundant computations in order to detect or correct errors. This way, two multiplier architectures with error detection or correction capability are proposed that have a beneficial reliability against different types of permanent and transient faults. The implementation results show that in the fault-tolerant mode, maintaining 13 bits instead of 23 bits for the mantissa will be enough to achieve an error detecting multiplier, and maintaining 11 bits will be enough to achieve an error correcting multiplier with acceptable area and power overheads (from 12% to 26%) while their precisions are enough for most applications. Manuscript profile -
Open Access Article
506 - Analyzing and Designing a Domain Specific Language to Describe Structure and Movement of Linkages
A. nourollah N. BehzadpourThis research has been prepared in the field of linkage structures and their movements. A linkage is a set of line segments that can be interconnected via their ends, which exhibits numerous usages in modeling robot arms. To date, various domain-specific languages have MoreThis research has been prepared in the field of linkage structures and their movements. A linkage is a set of line segments that can be interconnected via their ends, which exhibits numerous usages in modeling robot arms. To date, various domain-specific languages have been introduced in the field of robot movements. In spite that some of the capabilities of these languages combined with general-purpose languages can be used to describe and create the movements of these linkages and their structures, yet they cannot be considered domain-specific languages for explaining the linkages and their movements. The domain-specific languages are programs that raise the level of abstraction, the ability to understand better, accelerating the development and requires less effort to learn relevant knowledge that will provide the same advantages. So like all software, have levels such as analysis, design, implementation, testing, maintenance and support. Therefore, in this paper, we attempt to analyze and design a domain-specific language and describe and create linkage movements and their structures. By using this domain specific language, there is no limit to the definition of simple linkages in terms of it’s number. Also, by defining the modules and their sequential and parallel combinations, the final movements of the linkages are generated, and by using the features of the language, the terms needed to start or terminate each final movements are defined. Applying this kind of attitude to specific general-purpose modeling, in addition to providing ease in defining the structure of linkages and diversity in their initial definition, allows for the coordination and collaboration of multiple robots to perform a single task and then implemented in the next step. Manuscript profile -
Open Access Article
507 - Power Control and Subchannel Allocation in OFDMA Macrocell-Femtocells Networks
H. Davoudi M. RastiHeterogeneous networks, including macrocell and femtocell, cause to increase network capacity. Also, they improve quality of offers services to users in cellular networks. Common subchannel allocation among different tier users, make cross-tier interference among users. MoreHeterogeneous networks, including macrocell and femtocell, cause to increase network capacity. Also, they improve quality of offers services to users in cellular networks. Common subchannel allocation among different tier users, make cross-tier interference among users. Since macrocell users have priority to femtocell ones, presence of femtocell users should not prevent macrocell users to access minimum quality-of-service. In this paper, a power control and subchannel allocation scheme in downlink transmission an orthogonal frequency division multiple access (OFDMA) based two tier of macrocell and femtocell is proposed, aiming the maximization of femtocell users total data rate, in which the minimum QOS for all macrocell users and femtocell delay-sensitive users is observed. In macrocell tier, two different problems are considered. The first problem aim to maximizing the total threshold of tolerable cross-tier interference for macrocell users and the second problem’s goal is minimizing the macrocell’s total transmission power. For the femtocell tier, maximizing the users total data rate is the objective. Hungrian method, an assignment optimization method, is used for solving the first problem in macrocell tier. Moreover, in order to solve the second problem a heuristic method for subchannel allocation is proposed and dual Lagrange method is used for power control. In addition, in order to solve the problem for femtocell tier, a heuristic method is used for subchannel allocation. Subsequently, a dual Lagrange method which is one of the convex optimization problem solver is used, so that we can control the power. Finally, an extend simulations are performed to validate the performance of the proposed method. Manuscript profile -
Open Access Article
508 - Hyper Spherical Search Optimization Algorithm Based on Chaos Theory
Mohammad Kalantari S. Sohrabi H. Rashidy Kanan H. KaramiA Hyper Spherical Search (HSS) optimization algorithm based on chaos theory is proposed that resolves the weakness of the standard HSS optimization algorithm including the speed of convergence and the sequential increment in the number of algorithm iterations to achieve MoreA Hyper Spherical Search (HSS) optimization algorithm based on chaos theory is proposed that resolves the weakness of the standard HSS optimization algorithm including the speed of convergence and the sequential increment in the number of algorithm iterations to achieve the optimal solution. For this, in the particle initiation and search steps of the proposed algorithm, random values used in the standard algorithm are replaced with the values of two mappings, Chebyshev and Liebovitch, that makes the results of the proposed algorithm definite and decreases their standard deviation. The simulation results on the standard benchmark functions show that the proposed algorithm not only has faster convergence, but also acts as a more accurate search algorithm to find the optimal solution in comparison to standard hyper spherical search algorithm and some other optimization algorithms such as genetic, particle swarm, and harmony search algorithm. Manuscript profile -
Open Access Article
509 - Proposing a New Method for Acquiring Skills in Reinforcement Learning with the Help of Graph Clustering
M. Davoodabadi Farahani N. MozayaniReinforcement learning is atype of machine learning methods in which the agent uses its transactions with the environment to recognize the environment and to improve its behavior.One of the main problems of standard reinforcement learning algorithms like Q-learning is t MoreReinforcement learning is atype of machine learning methods in which the agent uses its transactions with the environment to recognize the environment and to improve its behavior.One of the main problems of standard reinforcement learning algorithms like Q-learning is that they are not able to solve large scale problems in a reasonable time. Acquiring skills helps to decompose the problem to a set of sub-problems and to solve it with hierarchical methods. In spite of the promising results of using skills in hierarchical reinforcement learning, it has been shown in some previous studies that based on the imposed task, the effect of skills on learning performance can be quite positive. On the contrary, if they are not properly selected, they can increase the complexity of problem-solving. Hence, one of the weaknesses of previous methods proposed for automatically acquiring skills is the lack of a systematic evaluation method for each acquired skill. In this paper, we propose new methods based on graph clustering for subgoal extraction and acquisition of skills. Also, we present new criteria for evaluating skills, with the help of which, inappropriate skills for solving the problem are eliminated. Using these methods in a number of experimental environments shows a significant increase in learning speed. Manuscript profile -
Open Access Article
510 - Data Offloading to Femtocell with In-Band Full Duplex Deployment
Mohammad Mollashahi M. Mehrjoo M. AbiriIn order to increase throughput and spectral efficiency in a heterogeneous network including a macro and a femtocell, we propose a combined offloading with In-Band Full Duplex (IBFD) scheme in this paper. Traffic offloading to the femtocell is deployed to transmit netwo MoreIn order to increase throughput and spectral efficiency in a heterogeneous network including a macro and a femtocell, we propose a combined offloading with In-Band Full Duplex (IBFD) scheme in this paper. Traffic offloading to the femtocell is deployed to transmit network users traffic to a macrocell base station in the uplink. In other words, all or a part of the traffic is offloaded to the femtocell and then transmitted to the macrocell, while the rest of traffic is transmitted to the macrocell directly. In the femtocell, we deploy and investigate IBFD technology, i.e., simultaneous transmit and receive traffic in one frequency band. Furthermore, in order to improve throughput of the network, we propose several scheduling schemes to transmit traffic. Finally, optimal number and position of users who use IBFD or do not use it, are determined. We propose a heuristic solution to find optimal position of IBFD users. Simulation results verify the network throughput improvement and power consumption reduction. Manuscript profile -
Open Access Article
511 - Scheduling of Modules in Fog Computing by Knapsack-Based Symbiotic Organisms Search
D. Rahbari M. NickrayWireless sensor networks have limitations such as processing power, storage resources, and time delay in data transfer to the cloud. The cloud computing by the development of cloud-based services to the edge of the network reduces traffic and delays, so these types of n MoreWireless sensor networks have limitations such as processing power, storage resources, and time delay in data transfer to the cloud. The cloud computing by the development of cloud-based services to the edge of the network reduces traffic and delays, so these types of networks are used in many systems, such as medical care, wearable devices, transportation systems and smart cities. Task scheduling techniques in fog computing are considered to be NP-hard issues. Applications require resources to run. Network fog devices are close to the sensors and the cloud and have the required processing power to run the applications. Each fog device can be used to run resource allocation policies. In this paper, we present an optimized Knapsack-based method optimized by symbiotic organism search to allocate resources appropriately to tasks in fog network. The proposed method is simulated in the iFogsim as a developed library from Cloudsim for fog computing. The results indicate improvement in energy consumption, resource consumption, and execution cost of the network. The proposed method is better than FCFS and Knapsack methods. Manuscript profile -
Open Access Article
512 - A Self-Learning Single Image Super-Resolution by Considering Consistency in Adjacent Pixels
M. Habibi A. Ahmadyfard H. hassanpourIn this paper, we propose a self-learning single image super-resolution. In our proposed method, adjacent pixels information in smooth area is used. Low and high-resolution pyramids are built by applying up-sampling and down-sampling techniques on input image, as traini MoreIn this paper, we propose a self-learning single image super-resolution. In our proposed method, adjacent pixels information in smooth area is used. Low and high-resolution pyramids are built by applying up-sampling and down-sampling techniques on input image, as training data. In training phase, we apply support vector regression (SVR) to model the relationship between the pair of low and high-resolution images. For each patch in the low-resolution image, sparse representation is extracted as a feature vector. In this paper, in order to reduce the edge blurring effects, we first separate edge pixels from non-edge pixels. In the smooth area, because of the similar colors around the each pixel, the center pixel value is determined by considering the reconstructed adjacent pixels. Experimental results show that the proposed method is quantitatively and qualitatively outperform the competitive super-resolution approaches. Manuscript profile -
Open Access Article
513 - Cell Association Combined with Interference Management in Heterogeneous Cellular Networks Using a Distributed Algorithm
Maryam Chinipardaz Seyed Majid NoorhosseiniDue to the growing demand of cellular networks, the need to increase the capacity of these networks has always been a challenge. Heterogeneous cellular networks using small base stations alongside macro base stations are low cost and effective solutions for this problem MoreDue to the growing demand of cellular networks, the need to increase the capacity of these networks has always been a challenge. Heterogeneous cellular networks using small base stations alongside macro base stations are low cost and effective solutions for this problem. However the differences between the various BSs in heterogeneous networks have created new challenges in terms of cell association and interference management compared with the traditional cellular networks. Therefore, the design of new and efficient methods for allocating cells and resources in these networks is an open research topic. This paper addresses the need for an efficient solution to simultaneously allocating cells and subbands in order to prevent interference for all users. The protocol interference model and its modeling methods in cellular networks have been studied. After modeling the system, the problem is formulated as an integer optimization problem. Then, by reformulating the problem and using a one-level dual decomposition, an algorithm with efficient complexity with near-optimal answers is attained. Thereafter, a distributed protocol is presented in which each user and each base station would only require local information for making decisions. The simulation results confirm the effectiveness of the proposed solution. Manuscript profile -
Open Access Article
514 - Performance Analysis of Subband Adaptive Algorithms over Distributed Networks Based on Incremental Strategy
Mohammad S. E. Abadi A. R. Danaee M. S. ShafieeThis paper presents the problem of distributed estimation in an incremental network based on the family of normalized subband adaptive algorithms (NSAAs). The distributed NSAA (dNSAA), the distributed selective partial update NSAA (dSPU-NSAA), the distributed dynamic se MoreThis paper presents the problem of distributed estimation in an incremental network based on the family of normalized subband adaptive algorithms (NSAAs). The distributed NSAA (dNSAA), the distributed selective partial update NSAA (dSPU-NSAA), the distributed dynamic selection NSAA (dDS-NSAA), and the dSPU-DS-NSAA are introduced in a unified way. The dNSAAs have better convergence speed than distributed normalized least mean square (dNLMS) algorithm especially for colored Gaussian input of the nodes. In comparison with dNSAA, the dSPU-NSAA, and dDS-NSAA have lower computational complexity and close performance to dNSAA. Also by combination of these algorithms, the dSPU-DS-NSAA is established which is computationally efficient. In addition, a unified approach for mean-square performance analysis of each individual node is presented. This approach can be used to establish a performance analysis of classical distributed adaptive algorithms as well. The theoretical expressions for transient, and steady-state performance analysis of the various dNSAAs are introduced. The validity of the theoretical results, and the good performance of these algorithms are demonstrated by several computer simulations. Manuscript profile -
Open Access Article
515 - Statistical Analysis and Modeling of CMRR and PSRR Random Variations in a Nano-CMOS Transconductance Amplifier
B. Mahboubi D. DidebanWith advancement of integrated circuit technology and aggressive scaling into nanometer regime, statistical variability in device electrical characteristics caused by discreteness of charge and fabrication process variations has significantly increased. These variations MoreWith advancement of integrated circuit technology and aggressive scaling into nanometer regime, statistical variability in device electrical characteristics caused by discreteness of charge and fabrication process variations has significantly increased. These variations in turn result in fluctuations in output characteristics of important analog building blocks and in particular, amplifiers. In this paper, with the aid of Monte-Carlo simulations for a transconductance amplifier and using 1000 different compact models of MOSFET transistors in 35nm technology node, statistical variations of important circuit parameters are investigated and analyzed based on their statistical distributions. Moreover, statistical correlations between circuit parameters are extracted. Analysis of statistical variations for circuit parameters and their correlations has a direct impact on reduction of cost and time of a design and thus, is of great amount of significance. Manuscript profile -
Open Access Article
516 - Implementation of Pulse Width Modulation Technique for Achieving Increased Voltage Gain and Balanced Voltage Stress in the A-Source Inverter
F. Zohrabi E. Abiri A. RajaeiThe Z-source converter was first introduced as a buck-boost dc-ac single-stage inverter in 2003. Different structures of impedance source inverters have been introduced for improving the performance of power inverters. Due to their specific structure, these inverters us MoreThe Z-source converter was first introduced as a buck-boost dc-ac single-stage inverter in 2003. Different structures of impedance source inverters have been introduced for improving the performance of power inverters. Due to their specific structure, these inverters use shoot-through state in order to increase the output voltage. Therefore, in addition to improving the reliability of systems, they create a single-stage dc-ac inverter capable of reducing and increasing voltage at the same time. Recently, a three-winding network called the A-source network has been introduced. A new Pulse Width Modulation method has been proposed to improve the voltage gain and reduce switching losses. In this new method, duty cycle of the switch is controlled using the third harmonic injection and the new reference voltages in the three-phase A-source inverter. The proposed modulation method reduces the switching losses and increases voltage gain without adding any additional hardware to the inverter structure. In this method, the buck-boost single-stage structure of the inverter is maintained. In this paper, the proposed method is partially analyzed and compared to the conventional Pulse Width Modulation methods. In this method, the third harmonic injection is used to increase the modulation index to 1.15 and thereby reduce the switching losses. The simulation of the proposed and conventional methods and analyzes, demonstrated the ability of the proposed system. Manuscript profile -
Open Access Article
517 - Overcurrent Relay Coordination Using Improved Hyper-Spherical Search Algorithm Considering Different Relay Characteristics and Pickup Current
A. Hassani Ahangar H. Nafisi H. Karami G. GharehpetianMinimization of the discrimination time between the backup and main overcurrent relay is one of the most critical issue in relay coordination of power system. Determination of time setting multipliers (TSMs) using evolutionary algorithms has been studied in previous pap MoreMinimization of the discrimination time between the backup and main overcurrent relay is one of the most critical issue in relay coordination of power system. Determination of time setting multipliers (TSMs) using evolutionary algorithms has been studied in previous papers. In this paper, TSM, various characteristics of the overcurrent relays and pickup currents are simultaneously considered to improve coordination of main and backup overcurrent relays. Furthermore, the coordination problem can also be considered as an optimization problem which can be solved using artificial intelligent methods. Recently, a novel optimization algorithm, called hyper-sphere search (HSS) algorithm, has been introduced. In this paper, Improved HSS (IHSS) is introduced. Based on the problems mentioned in this paper, the IHSS algorithm is more appropriate for obtaining the characteristics of the overcurrent relays, pickup currents and their TSMs. The result of IHSS is compared with HSS algorithm which has been used in previous studies. The simulation results on the test network show the efficiency of using IHSS and considering pickup currents in term of better relays coordination. Manuscript profile -
Open Access Article
518 - Optimal Operation of AC Microgrid in the Presence of Plug-in Electric Vehicles under Demand Side Managemen
A. Mehdizadeh N. Taghizadegan J. SalehiIn the recent years, integrations of renewable energy sources as well as plug-in electric vehicles are increased in the AC microgrid. Also, demand side management can be used to manage peak load in order to improve optimal performance of AC microgrid. Therefore, this pa MoreIn the recent years, integrations of renewable energy sources as well as plug-in electric vehicles are increased in the AC microgrid. Also, demand side management can be used to manage peak load in order to improve optimal performance of AC microgrid. Therefore, this paper proposes optimal operation of AC microgrid in the presence of plug-in electric vehicles under demand side management. The proposed model describes optimal operation of microgrid including the exchange power with the upstream grid, the production of DG units including wind turbines, battery storage, diesel generators, charging and discharging of electric vehicles and the manner of participation of large industrial consumers and aggregators of small consumers in demand side management that minimize the operation cost of microgrid. The proposed formulation is considered the mathematical model of various energy sources in a microgrid and the AC load flow constraints and the bus voltage and feeder current limitations has been considered.In the proposed model, charge and discharge management of plug-in electric vehicles and demand side management are simultaneously proposed to reduce operation cost of AC microgrid subject to technical and economic constraints. A 33-bus microgrid is used as test system in order to investigate effects of plug-in electric vehicles and demand side management on optimal operation of AC microgrid. The proposed model is formulated via mixed-integer non-linear programming which is solved using CPLEX solver under GAMS optimization software. Manuscript profile -
Open Access Article
519 - Close Loop Identification for Combustion System by Recurrent Adaptive Neuro-Fuzzy Inference System and Network with Exogenous Inputs
E. Aghadavoodi G. ShahgholianBoiler-turbine is a multi-variable and complicated system in steam power plants including combustion, temperature and drum water level. Selecting control loops as a unique loop in order to identify and control the boiler as a whole unit is a difficult and complicated ta MoreBoiler-turbine is a multi-variable and complicated system in steam power plants including combustion, temperature and drum water level. Selecting control loops as a unique loop in order to identify and control the boiler as a whole unit is a difficult and complicated task, because of nonlinear time variant dynamic characteristics of the boiler. It is necessary to identify each control group in order to accomplish a realistic and effective model, appropriate for designing an efficient controller. Both the effective and efficient performance of the identified model during the load change is of major importance. Here, not all parts of the system should be considered as a unit part, if determining and effective and realistic model is sought. The combustion loop of the 320 MW steam power plant of Islam Abad, Isfahan is the subject. Due to the sensitivity and complexity of the system, with respect to its nonlinear and closed loop characteristics, the identification of the system is conducted through intelligent procedures like recurrent adaptive neuro-fuzzy inference system (RANFIS) and nonlinear autoregressive model with exogenous input (NARX). The comparisons of the findings with actual data collected from the plant are presented and the accuracy of the procedures is determined. Manuscript profile -
Open Access Article
520 - Design of Parity Preserving Reversible Signed Multiplier Circuit
M. Haghparast A. BolhassaniOne of the major challenges and constraints in designing very large integrated circuits is the power dissipation of transistors. Reversible logic is one of the new paradigm in reducing the power consumption of digital circuits in the quantum computing field. In this pap MoreOne of the major challenges and constraints in designing very large integrated circuits is the power dissipation of transistors. Reversible logic is one of the new paradigm in reducing the power consumption of digital circuits in the quantum computing field. In this paper, an improved design of a parallel 5-bit parity preserving reversible signed multiplier circuit is presented. Reversible circuit designs with parity preserving property are an important issue for the implementation of fault tolerant systems in nanotechnology area. To design of the proposed multiplier, the reversible full adder circuit using 5×5 reversible HBF block with low quantum cost, and the 4×4 reversible HBL gate, with parity preserving property are proposed. The structure of the multiplier circuit consists of two parts of the partial product generation (PPG) and multi-operand addition (MOA). This structure is based on Baugh-Wooley and Wallace-Tree algorithms, which results in improved speed of operation in a 5-bit multiplier for signed digits. The proposed circuits are optimized based on important evaluation issues such as quantum cost, garbage outputs and constant inputs, and also are compared with the existing circuits. The main goal is to reduce the quantum cost, the number of constant inputs and garbage outputs in the design of the proposed multiplier circuit. The results of the final evaluation and comparison shows that the proposed multiplier in this study is improved by 26% in quantum cost, 9% in garbage outputs and 9% in constant inputs relative to the best existing designs. Manuscript profile -
Open Access Article
521 - Design, Simulation and Implementation of a Compact, 6-Way Wilkinson Power Divider Using Composite Lines
M. Heydari S. RoshaniIn this paper a novel compact 6-way Wilkinson power divider coupler (WPD) using composite lines is proposed, simulated and fabricated. The proposed structure consists of a 2-way divider and two 3-way dividers. The applied dividers have equal division ratios. In the pro MoreIn this paper a novel compact 6-way Wilkinson power divider coupler (WPD) using composite lines is proposed, simulated and fabricated. The proposed structure consists of a 2-way divider and two 3-way dividers. The applied dividers have equal division ratios. In the proposed structure long quadrature wavelength lines are replaced with small composite lines, which results in size reduction and harmonics suppression. Moreover for improved output ports isolations a resistor and a capacitor are used together. The designed device correctly works on 5.1 GHz Manuscript profile -
Open Access Article
522 - A Load Balancing Scheme by D2D-Based Relay Communications in Heterogeneous Networks Signals
shahriar gholami mehrabadi yasser attar izi soroush akhlaghiHeterogeneous networks have been regarded as an integral part of fifth generation communication networks in order to respond to the unprecedented growth of required data rates. In such networks, the existence of a variety of cells with base stations of varying capacitie MoreHeterogeneous networks have been regarded as an integral part of fifth generation communication networks in order to respond to the unprecedented growth of required data rates. In such networks, the existence of a variety of cells with base stations of varying capacities and transmit powers has enabled the repeated use of available bandwidth. Moreover, the excess load on the central base station can be directed to the sub-cell base stations. In the current work, a novel approach is proposed for such a load balancing problem in which some nodes previously connected to the main base station can be served by sub-cells through the use of some D2D relays. This will increase the overall network capacity, improve the quality of service (QoS) of cell edge users, and increase covered users. In this design, the maximization of the capacity of D2D links is formulated as an optimization problem which is not convex in general. To tackle this, the main problem is divided into two sub-problems of optimal resource allocation and user-relay pairing problems with much lower complexity. Simulation results demonstrate the superiority of the proposed method over existing works addressed in the literature. Manuscript profile -
Open Access Article
523 - Design of a New Observer for Unknown and Variable Input Time-Delay Estimation in Linear SISO Systems
Hadi Chahkandi Nejad mohsen Farshad Ramazan HavangiIn this paper, a novel observer is designed for online time delay estimation, in SISO linear systems, with variable and unknown time-delay in control input. It is clear that Laplace transfer function of a delayed system includes a time-delay operator (exponential and no MoreIn this paper, a novel observer is designed for online time delay estimation, in SISO linear systems, with variable and unknown time-delay in control input. It is clear that Laplace transfer function of a delayed system includes a time-delay operator (exponential and non-rational). In this article, it is assumed that the only unknown and variable parameter in the system is the system’s time-delay. For designing the proposed observer, first, a Pade approximation is used for exponential operator of time delay to rationalize the system transfer function. Therefore, the new transfer function, which is an approximation of the main transfer function of the system, will include a time-variant delay parameter. After rewriting a state space realization of the mentioned transfer function and considering time delay parameter as an extra state variable, a system with nonlinear state equations will be formed. Eventually, using a Kalman filter, the systems states, such as system time-delay, are estimated. Finally, simulations results show rather desirable performance of the proposed estimator in dealing with unknown and variable time-delays. Manuscript profile -
Open Access Article
524 - A Distributed Solution for Mixed Big Data Clustering
M. Mahmoudi نگین دانشپورDue to the high-speed of information generation and the need for data-knowledge conversion, there is an increasing need for data mining algorithms. Clustering is one of the data mining techniques, and its development leads to further understanding of the surrounding env MoreDue to the high-speed of information generation and the need for data-knowledge conversion, there is an increasing need for data mining algorithms. Clustering is one of the data mining techniques, and its development leads to further understanding of the surrounding environments. In this paper, a dynamic and scalable solution for clustering mixed big data with a lack of data is presented. In this solution, the integration of common distance metrics with the concept of the closest neighborhood, as well as a kind of geometric coding are used. There is also a way to recover missing data in the dataset. By utilizing parallelization and distribution techniques, multiple nodes can be scalable and accelerated. The evaluation of this solution is based on speed, precision, and memory usage criteria compared to other ones. Manuscript profile -
Open Access Article
525 - A New Memetic Model based on the Fixed Structure Learning Automata
M. Rezapoor Mirsaleh M. R. MeybodiMemetic algorithm (MA) is a kind of evolutionary algorithms (EAs) that searches the problem solving space using local search and global search. The balance between global search and local search is one of the key issues in this algorithm. In this paper a new model is pr MoreMemetic algorithm (MA) is a kind of evolutionary algorithms (EAs) that searches the problem solving space using local search and global search. The balance between global search and local search is one of the key issues in this algorithm. In this paper a new model is proposed, called GALA2. This model is combined of genetic algorithm (GA) and object migration automata (OMA), which is a kind of fixed-structure learning automaton. In the proposed model, global search is performed by genetic algorithm and local learning is performed by learning automata. In this model, the Lamarckian and Baldwinian learning models have been used to increase the convergence rate and avoidance of premature convergence, simultaneously. In this evolutionary model, chromosomes are represented by object migration automata for the purpose of using positive effects of evolution and local learning. In order to show the superiority of the proposed model, GALA2 is used to solve the graph isomorphism problem. Manuscript profile -
Open Access Article
526 - Identifying Primary User Emulation Attacks in Cognitive Radio Network Based on Bayesian Nonparametric Bayesian
K. Akbari J. AboueiCognitive radio as a key technology is taken into consideration widely to cope with the shortage of spectrum in wireless networks. One of the major challenges to realization of CR networks is security. The most important of these threats is primary user emulation attack MoreCognitive radio as a key technology is taken into consideration widely to cope with the shortage of spectrum in wireless networks. One of the major challenges to realization of CR networks is security. The most important of these threats is primary user emulation attack, thus malicious user attempts to send a signal same as primary user's signal to deceive secondary users and prevent them from sending signals in the spectrum holes. Meanwhile, causing traffic in CR network, malicious user obtains a frequency band to send their information. In this thesis, a method to identify primary user emulation attack is proposed. According to this method, primary users and malicious users are distinguished by clustering. In this method, the number of active users is recognized in the CR network by clustering. Indeed, by using Dirichlet process mixture model classification based on the Bayesian Nonparametric method, primary users are clustered. In addition, to achieve higher convergence rate, Chinese restaurant process method to initialize and non-uniform sampling is applied to select clusters parameter. Manuscript profile -
Open Access Article
527 - Introducing a Fog-Based Algorithm for Routing in Wireless Sensor Networks
E. Mirzavand Borujeni D. Rahbari M. NickrayWireless sensor networks (WSNs) consist of thousands of small nodes. The small and inexpensive parts of these nodes have led to their widespread use in various fields. However, these networks have constraints on energy consumption, processing resources, and storage whic MoreWireless sensor networks (WSNs) consist of thousands of small nodes. The small and inexpensive parts of these nodes have led to their widespread use in various fields. However, these networks have constraints on energy consumption, processing resources, and storage which have caused many studies to find solutions to reduce these constraints. In recent years, with the advent of the concept of Fog computing, many new and effective solutions are represented for routing in wireless sensor networks. Since in WSNs it is important to save alive nodes and reduce the energy consumption of nodes, fog computing is useful for this purpose. In most WSN routing protocols, the best way to send data to cluster heads and the base station is the major part of their studies. In the new protocols, the Fog computing have been used to find the best way. In these methods, we have seen decreasing energy consumption and increasing network lifetime. In this paper, we represent a fog-based algorithm for routing in WSNs. According to the simulation results, the proposed protocol improved energy consumption by 9% meanwhile the number of alive nodes is increased by 74%, compared to the reviewed method. Manuscript profile -
Open Access Article
528 - Visual Distractors Detecting in Images Using Weighted Two Phase Test Sample Sparse Representation Method
F. Sabouri F. yaghmaeeThe image observer usually wants to receive the message and the main subject of the image in the shortest time. Hence, assuming there is useful information in the salient regions, the human vision system unconsciously guides visual attention towards them. This assumptio MoreThe image observer usually wants to receive the message and the main subject of the image in the shortest time. Hence, assuming there is useful information in the salient regions, the human vision system unconsciously guides visual attention towards them. This assumption is not always correct in practice, and in some cases, salient regions merely cause visual distractions. Therefore, in different applications, a mechanism is needed to identify these regions. To prevent from distracting observer’s attention from the main subject, these regions are eliminated. Furthermore, neglecting these regions could be of considerable assistance to the methods that function base on salient regions recognition. So, in this paper, Based on the methods of the class imbalance challenge each segment of training images in the dataset is a partition to 9 classes according to the relevant mask in the dataset, that the number of each class is proportional to its disturbance intensity. Then, segment-based features are extracted and determining the class of each segment is determined according to WTPTSSR method, which is based on the Sparse Coding and Representation system.Finally, in order to precisely analyzing the proposed method and comparing it to other approaches, four analysis criteria with different performances are presented. According to results, despite being time-consuming, the proposed method has a higher accuracy than the previous ones. Manuscript profile -
Open Access Article
529 - A Novel Link Prediction Approach on Social Networks
S. Rezavandi Shoaii H. ZareNowadays the network science has been attracted many researchers from a wide variety of different fields and many problems in engineering domains are modelled through social networks measures. One of the most important problems in social networks is the prediction of ev MoreNowadays the network science has been attracted many researchers from a wide variety of different fields and many problems in engineering domains are modelled through social networks measures. One of the most important problems in social networks is the prediction of evolution and structural behavior of the networks that is known as link prediction problem in the related literature. Nowadays people use multiple and different social networks simultaneously and it causes to demonstrate a new domain of research known as heterogenous social networks. There exist a few works on link prediction problem on heterogenous networks. In this paper, first a novel similarity measure for users in heterogenous networks is defined. Then a novel link prediction algorithm is described through a supervised learning approach which is consisted by the generated features from the introduced similarity measures. We employ the standard evaluation criteria for verification of the proposed approach. The comparison of the proposed algorithm to the other well-known earlier works showed that our proposed method has better performance than the other methods based on testing on several network datasets. Manuscript profile -
Open Access Article
530 - An Improved Grid-Based K-Coverage Technique Using Probabilistic Sensing Model for Wireless Sensor Networks
Abdolreza Vaghefi Mahdi MollamotalebiCoverage of an area, with one or multiple sensors, is one of the fundamental challenges in wireless sensor networks. Since a sensor life span is limited and reliable data is of great importance, sensitive applications like fire\leakage alarm systems, intrusion detection MoreCoverage of an area, with one or multiple sensors, is one of the fundamental challenges in wireless sensor networks. Since a sensor life span is limited and reliable data is of great importance, sensitive applications like fire\leakage alarm systems, intrusion detection, etc. need multiple sensors to cover the region of interest, which is called K-coverage. Most of the studies that have been carried out on K-coverage evaluation have used binary sensing model. In this paper, we propose a grid-based K-coverage evaluation technique using probabilistic sensing model to increase evaluation accuracy and decrease evaluation time. The proposed technique is implemented using NS-2 simulator, and its results are compared to probabilistic perimeter-based and binary grid-based techniques. The results indicate that the proposed technique improved accuracy by 14% and 24% compared to the mentioned techniques respectively. It also shows 7% decrease in evaluation time compared to probabilistic perimeter-based technique. Manuscript profile -
Open Access Article
531 - Semi-Supervised Metric Learning in Stratified Space by Accurate Exploiting of Prior Knowledge
Z. Karimi S. Shiry Ghidary R. RamezaniSemi-supervised metric learning has attracted increasing interest in recent years. They enforce smoothness label assumption on the manifold. However, they suffer from two challenges: (1) since data in each class lies on one manifold and the similarity between classes le MoreSemi-supervised metric learning has attracted increasing interest in recent years. They enforce smoothness label assumption on the manifold. However, they suffer from two challenges: (1) since data in each class lies on one manifold and the similarity between classes leads the intersection between manifolds, the smoothness assumption on the manifold is violated in intersecting regions. (2) 1NN classifier, which is applied for predicting the label of classes in metric learning methods, is suffered from the rare of labeled data and has not suitable accuracy. In this paper, a novel method for learning semi-supervised metric in the stratified space has been proposed that exploit the prior knowledge, which is the smoothness assumption on each manifold, more accurate than existing methods. In the metric learning stage, it doesn’t apply smoothness assumption on the intersecting regions and in the classification stage, labeled data in the interior regions of manifolds are extended based on the smoothness assumption. The different behavior of the Laplacian of piecewise smooth function on stratified space is exploited for the distinction of the intersecting regions from interior regions of manifolds. The results of experiments verify the improvement of the classification accuracy of the proposed method in the comparison with other methods. Manuscript profile -
Open Access Article
532 - Improvement in Electrical Characteristics of Silicon on Insulator Junctionless Field Effect Transistor (SOI-JLFET) Using the Auxiliary Gate
M. VadizadehSilicon on insulator junctionless field effect transistor (SOI-JLFET) includes a single type doping at the same level in the source, channel, and drain regions. Therefore, its fabrication process is easier than inversion mode SOI-FET. However, SOI-JLFET suffers from hig MoreSilicon on insulator junctionless field effect transistor (SOI-JLFET) includes a single type doping at the same level in the source, channel, and drain regions. Therefore, its fabrication process is easier than inversion mode SOI-FET. However, SOI-JLFET suffers from high subthreshold slope (SS) as well as high leakage current. As a result, the SOI-JLFET device has limitation for high speed and low power applications. For the first time in this study, use of the auxiliary gate in the drain region of the SOI-JLFET has been proposed to improve the both SS and leakage current parameters. The proposed structure is called "SOI-JLFET Aug". The optimal selection for the auxiliary gate work function and its length, has improved the both SS and ION/IOFF ratio parameters, as compared to Regular SOI-JLFET. Simulation results show that, SOI-JLFET Aug with 20nm channel length exhibits the SS~71mV/dec and ION/IOFF~1013. SS and ON-state to OFF-state current (ION/IOFF) ratio of SOI-JLFET Aug are improved by 14% and three orders of magnitudes, respectively, as compared to the Regular SOI-JLFET. The SOI-JLEFT Aug could be good candidate for digital applications. Manuscript profile -
Open Access Article
533 - Robust Scheduling of a Smart Microgrid Connected to the Grid Considering Air Pollution in the Presence of Controllable Loads
amin namvar NAVID TAGHIZADEGAN KALANTARIThe microgrid is a set of local energy producers and consumers that can be utilized with low cost and high reliability. In this paper, a robust multi-objective model is proposed to reduce operating costs and carbon emissions in which a smart grid utilizes a wind turbine MoreThe microgrid is a set of local energy producers and consumers that can be utilized with low cost and high reliability. In this paper, a robust multi-objective model is proposed to reduce operating costs and carbon emissions in which a smart grid utilizes a wind turbine and micro-turbine to feed its connected loads. The microgrid also uses a battery to store electrical energy in off-peak hours and to deliver energy in on-peak hours. On the other hand, it is connected to the main grid and can exchange energy with it. Consumers connected to this microgrid are divided into two groups. The first group is uncontrollable loads with certain load pattern and the second group is controllable loads that have certain energy consumption but can be controlled by the operating time. The proposed model is a mixed-integer linear programming problem and is simulated with the CPLEX solver in GAMS software. The results show that when the price of electricity is low, the loads are often supplied by grid electricity, and when the price of electricity is high, they are often fed by micro-turbines, batteries, and wind turbines. Manuscript profile -
Open Access Article
534 - Flashover Voltage Assessment of Polymeric Insulators with Different Profiles under Fan-Shaped and Longitudinal Non-Uniform Pollutions and Environment Humidity Effects
mehrdad ghorbani pashakolaei Mohammad Mirzaie seyyed meysam seyyedbarzegarThe deposited pollution on the insulaters surface in overhead Transmission Lines and also its characteristic is one of the effective factors on insulators electrical behavior. The pollution on insulators surface is Non-uniform due to the wind direction. So, less contam MoreThe deposited pollution on the insulaters surface in overhead Transmission Lines and also its characteristic is one of the effective factors on insulators electrical behavior. The pollution on insulators surface is Non-uniform due to the wind direction. So, less contamination is in the same direction wind. Also, the pollution is different throughout the insulators length and in near high and low voltage electrodes. Therefore, the deposited contamination on insulators is non-uniform and can be considered two forms of longitudinal and Fan-shaped non-uniform pollutions. In this paper, the influence of uniform pollution and also the effect of three states for pollution expansion (%15, %25, %35) and four states non-uniform contamination degree (1.5, 3, 6, 13) with longitudinal and Fan-shaped, under different humidities, on the flashover voltage different 20 kV silicon rubber insulators, have been studied. According to the obtained results from laboratory tests, the increase of non-uniformity contamination degree has significant effect on the behavior of the insulators under different non-uniform pollution, so that the flashover voltage has decreased between 8.8 to 42.21 percent in all the insulators. Manuscript profile -
Open Access Article
535 - Human Activity Recognition using Switching Structure Model
Mohammad Mahdi Arzani M. Fathy Ahmad AkbariTo communicate with people interactive systems often need to understand human activities in advance. However, recognizing activities in advance is a very challenging task, because people perform their activities in different ways, also, some activities are simple while MoreTo communicate with people interactive systems often need to understand human activities in advance. However, recognizing activities in advance is a very challenging task, because people perform their activities in different ways, also, some activities are simple while others are complex and comprised of several smaller atomic sub-activities. In this paper, we use skeletons captured from low-cost depth RGB-D sensors as high-level descriptions of the human body. We propose a method capable of recognizing simple and complex human activities by formulating it as a structured prediction task using probabilistic graphical models (PGM). We test our method on three popular datasets: CAD-60, UT-Kinect, and Florence 3D. These datasets cover both simple and complex activities. Also, our method is sensitive to clustering methods that are used to determine the middle states, we evaluate test different clustering, methods. Manuscript profile -
Open Access Article
536 - Design and Simulation of a Biosensor Based on 2D Photonic Crystalnano-Ring Resonator
فریبرز پرندین Farsad HeidariIn this paper, a biosensor based on a photonic crystal is designed. This sensor has two adjacent circular nano-rings that allow coupling between the waveguides and the nano-ring resonator. A number of dielectric rods have been used to design the sensor, which are locate MoreIn this paper, a biosensor based on a photonic crystal is designed. This sensor has two adjacent circular nano-rings that allow coupling between the waveguides and the nano-ring resonator. A number of dielectric rods have been used to design the sensor, which are located in the water environment. Circular ring resonators have also been used between the input and output waveguides. Also, in order to increase the optical restriction and improve the coupling performance of waveguides and nano-ring resonator, the input and output paths have been used closed end. In the proposed structure, which has a small dimension, the sensing rod is selected so that is has a high quality factor. The simulation results show that the designed biosensor has a high quality factor and by attaching the biomolecule to it, the displacement of the resonant wavelength is well formed. Another feature of the proposed structure is that all dielectric rods have the same radius, which makes it easier to construct the sensor. Manuscript profile -
Open Access Article
537 - A Hybrid Method for Transmission Cost Allocation Based on Effect of Transmission Facilities in System Reliability and Merchant Value
Hassan Esmaili علی کریمیWith the advent of electricity markets and the creation of a competitive environment in power systems, proper allocation of transmission cost among network users (consumers and producers) is essential to help the investment of transmission network, effectively. In this MoreWith the advent of electricity markets and the creation of a competitive environment in power systems, proper allocation of transmission cost among network users (consumers and producers) is essential to help the investment of transmission network, effectively. In this paper, a hybrid method for transmission cost allocation based on the effect of transmission facilities in system reliability and their merchant value is proposed. In the proposed method, first, the users' benefit in the electricity market and in other words, the merchant benchmark in cost allocation has considered. Second, cost allocation considering the effect of facilities in system reliability which are consist of factors of system security and adequacy and the benefit of users with these factors is done. For the implementation of the proposed method, the capacity of all facilities includes lines and transformers are divided into four sections consist of merchant capacity, contingency capacity for maintaining security, future capacity for maintaining adequacy and invalid capacity. The numerical results in a 3-bus and the IEEE 30-bus test system are presented to demonstrate the effectiveness of the proposed method and compare to other methods. Manuscript profile -
Open Access Article
538 - A New Method to Detect Line-to-Ground Faults in DC Microgrids Using Instantaneous Power Changes
Said Abbasi N. GhaffarzadehWith the increasing of sensitive loads such as data centers, the use of DC microgrids has increased. Line to ground fault is the most common type of fault in this type of microgrid, which causes various damages to the DC microgrid. One of the most important challenges i MoreWith the increasing of sensitive loads such as data centers, the use of DC microgrids has increased. Line to ground fault is the most common type of fault in this type of microgrid, which causes various damages to the DC microgrid. One of the most important challenges in operating a DC microgrid is the lack of effective protection against this faults type. In this paper, by using local measurements such as voltage and current at the beginning of each line, the instantaneous power changes in them are computed and a new protection scheme that is not based on any communication line is presented. The proposed protection scheme has good accuracy and speed of operation and is able to detect line-to-ground faults in DC microgrids with high-speed. The accuracy and precision of the protection scheme has been tested under different conditions. Manuscript profile -
Open Access Article
539 - A Multigate Scheme to Improve CORPL under Traffic Load in Cognitive Radio Based Smart Grids with Mesh Topology
S. A. Hashemian V. TabatabvakiliThe conventional power grid has several drawbacks and a new powerful smart grid perspective has been recently introduced. The smart grid principle, allowing to efficiently manage an electrical grid network, needs to exploit a communication network for interconnecting t MoreThe conventional power grid has several drawbacks and a new powerful smart grid perspective has been recently introduced. The smart grid principle, allowing to efficiently manage an electrical grid network, needs to exploit a communication network for interconnecting the Smart Grid devices. An increasing interest is toward wireless communications due to their higher flexibility. Within this context cognitive radio (CR) techniques has been introduced aiming to exploit more efficiently the radio spectrum resources. In neighborhood area network (NAN), mesh grids can be considered as one of possible network topologies. In such networks no base station is required and data will be sent to gateway by means of nodes themselves. Hence, routing is one of the main issues in such networks. Routing in such networks should be done by a protocol which maximizes throughput against cognitive radio drawbacks and Packets delay in such protocol needs to be minimum and suitable for smart grids applications. CORPL has been introduced as a routing protocol to meet some of these goals. In this paper by CORPL functionality would be evaluated under burst and poisson traffic. It will be shown that by increasing active nodes, CORPL functionality would be decreased. Then average upper limit for delay would be mathematically modeled and to reduce that a multigate scheme would be introduced. Manuscript profile -
Open Access Article
540 - Design and Construction of High-Current Line-Commutated Rectifier Based on Parallel Thyristors
M. Shahparasti Mohammad Farzi M. Arefian R. Asad M. Sharei-pourThis paper presents the process of designing and manufacturing a high-current line-commutated rectifier, which consists of six high current valves. Every valve is constructed through the parallelization of the four thyristors. The design of the physical structure, the p MoreThis paper presents the process of designing and manufacturing a high-current line-commutated rectifier, which consists of six high current valves. Every valve is constructed through the parallelization of the four thyristors. The design of the physical structure, the placement of busbars, and the arrangement of parallel thyristors are made using an innovative technique so that the current flows equally between them. To ensure equal flow distribution, in addition to the design of hardware structure and the use of suitable methods for simultaneous and accurate triggering of parallel thyristors, a new control technique based on the temperature measurement of each thyristor is proposed. Finally, the experimental results of a 170V, 4000A rectifier are presented to verify the proposed hardware design and control method. Manuscript profile -
Open Access Article
541 - Reliability Modeling of PV Farm Using Markov Model
V. Khaligh H. MonsefUtilization of photovoltaic units in power networks and their participation in the power supply has increased in recent years. Total world capacity of PV units has grown exponentially from 1.5 GW in 2000 to about 300 GW in 2016. This paper presents an analytical method MoreUtilization of photovoltaic units in power networks and their participation in the power supply has increased in recent years. Total world capacity of PV units has grown exponentially from 1.5 GW in 2000 to about 300 GW in 2016. This paper presents an analytical method for evaluating the reliability of large photovoltaic farms with regard to the changes in input power and reliability indices of unit components. The proposed method is not only capable of estimating the annual energy production of the photovoltaic units, but also able to calculate the system reliability indices. With Markov approach, Frequency and Duration method is utilized in order to model a photovoltaic farm similar to the multistate conventional units. Probability, frequency and transition rate of each state is obtained using the statistical data of solar radiation as well as operational characteristics of a photovoltaic unit. Due to the large number of solar radiation and PV modules operational states, k-means clustering algorithm is used for data classification. This analytical method is applied to the RBTS to demonstrate the effectiveness of developed approach. Capacity credit using LOLF index, is more than what obtained in the case of LOLE index. This observation can be explained through the variable nature of solar radiation in comparison with conventional units. Hence there is a need to obtain a model which reflects the frequency based reliability indices of PV systems. Manuscript profile -
Open Access Article
542 - Winding Losses Calculation in Multi-Winding Traction Transformer Using a Semi-Numerical Method
D. Azizian G. GharehpetianNowadays, multi-winding transformers are widely used in power systems, especially in traction networks and steel producing companies. The multi-winding transformers have special geometry. They encounter with serious problems and difficulties in design procedure in compa MoreNowadays, multi-winding transformers are widely used in power systems, especially in traction networks and steel producing companies. The multi-winding transformers have special geometry. They encounter with serious problems and difficulties in design procedure in comparison with conventional two-winding transformers. Considering the importance of windings losses (and the generated heat), the current research firstly focuses on thermal calculations in this type of transformers, also introduces a semi-numerical technique for electromagnetic analysis of split-winding traction system transformer. Combining finite element and analytical methods, the windings losses distribution due to eddy currents is calculated and the modeling results are validated using the experimental results. As shown, the introduced semi-numerical method is a powerful technique for electromagnetic modeling and winding losses calculations in split-winding transformers. Also, the winding losses of the split-winding transformer are discussed and compared to the conventional two-winding transformer results. Finally, the relation between the winding losses and frequency is studied in this paper. Manuscript profile -
Open Access Article
543 - A DC-DC Interleaved Converter Based on Buck Topology with High Step-Down Conversion Ratio
M. Ghanbari M. R. YazdaniHigh step-down conversion ratio cannot be achieved by the conventional buck converter. Also, the switch voltage stress is another drawback of the regular buck converter for high input voltages. In this paper, a DC-DC switching converter using interleaved method is propo MoreHigh step-down conversion ratio cannot be achieved by the conventional buck converter. Also, the switch voltage stress is another drawback of the regular buck converter for high input voltages. In this paper, a DC-DC switching converter using interleaved method is proposed based on the buck topology to achieve a high step-down conversion ratio. In the structure of this converter, a coupled inductor is used without need of another auxiliary winding. After presenting key waveforms and analysis of the proposed converter, the conversion ratio curves are offered. Moreover, simulation waveforms of a 240 W converter prototype with the input voltage of 150 V and the output voltage of 24 V are shown to verify the theoretical analysis. Manuscript profile -
Open Access Article
544 - Algebraic Stability Analysis and Stabilization by Proportional Controllers: Critical Inflection Point in Phase Diagram
kh. Neshat M. S. TavazoeiThis paper deals with algebraic stability analysis and investigating the existence of proportional stabilizing controllers on the basis of frequency response data. Firstly, it is shown that using the available results in this subject may yield in inconsistent subsequenc MoreThis paper deals with algebraic stability analysis and investigating the existence of proportional stabilizing controllers on the basis of frequency response data. Firstly, it is shown that using the available results in this subject may yield in inconsistent subsequences in the cases that there is a critical inflection point in phase diagram of the open-loop/process transfer function. Then, to solve this inconsistency problem some modifications are proposed. Finally, conditions for ensuring the existence of critical inflection point in phase diagram of a dynamical system are analytically found. Manuscript profile -
Open Access Article
545 - Design and ُSimulation of a New High CMRR, High Bandwidth and Low Power Current Mode Instrumentation Amplifier Based on FDCCII
S. Ahmadi S. J. AzhariIn this paper a novel topology of CMIA based on FDCCII is proposed. Due to benefiting from current mode signal processing, unlike the most of the previously reported IAs, the proposed FDCCII based structure doesn't need well-matched resistors or active blocks to obtain MoreIn this paper a novel topology of CMIA based on FDCCII is proposed. Due to benefiting from current mode signal processing, unlike the most of the previously reported IAs, the proposed FDCCII based structure doesn't need well-matched resistors or active blocks to obtain high CMRR and inherently can improve CMRR, bandwidth, power consumption and it has better frequency performances. On the other side, unlike other current mode types of this group, using fully differential structure decreases the mismatch effect in electronic blocks. Both of these advantages significantly reduced the structure size and power consumption while improving bandwidth and CMRR and makes it an excellent and an unbeatable choice for integration. In the proposed circuit, CMRR as the most important property of IA has been greatly improved by using a current subtracting stage. The CMIA has been designed using 0.18 um CMOS Technology under ±1 V supply voltages and the performance of the CMIA has been verified using HSPICE software in transistor level. The CMIA has achieved voltage CMRR of 227.4 dB, voltage CMRR bandwidth of 8.98 KHz, differential voltage gain bandwidth of 9.08 MHz and output offset voltage of 2.23 uV and the IA’s power dissipation is only 348 uW Manuscript profile -
Open Access Article
546 - A New Statistical-Physical UTD Based Channel Model for Calculating Channel Capacity in Mobile Urban Areas
Ali TajvidyIn urban areas, wireless communications suffer from severe fading due to reflections and diffraction of waves from buildings and mobility of receivers. Hence, in design of wireless networks, we need a model to predict propagation channels, in order to determine communic MoreIn urban areas, wireless communications suffer from severe fading due to reflections and diffraction of waves from buildings and mobility of receivers. Hence, in design of wireless networks, we need a model to predict propagation channels, in order to determine communication methods between transmitters and receivers. Most of current mobile wireless communication models are based on measurements. In this paper, we want to introduce a new statistical physical model in which buildings are considered as a fixed part of the model and the phenomena of diffraction and reflection are modeled using the uniform theory of diffraction (UTD).On the other hand, the receiver in this model is considered as a car. The position of this car is predicted using the Poisson point process (PPP). We can predict channel capacity in urban areas, taking into account the density of traffic and urban traffic by using this model. Furthermore, in order to validate the proposed model, we compared the results of this model with a statistical model based on measurements and there is a good agreement between them. Manuscript profile -
Open Access Article
547 - A Method to Get WSN Nodes Data by Web Clients through IoT Gateway Based on CoAP Protocol
M. R. Nikseresht H. Haj Seyyed Javadi Mahdi MollamotalebiThe advancement of technology in the area of wireless sensor networks and the ability to use the Internet Protocol in small objects with limited resources (such as sensors) has changed the Internet landscape. How to communicate and how to exchange information is one of MoreThe advancement of technology in the area of wireless sensor networks and the ability to use the Internet Protocol in small objects with limited resources (such as sensors) has changed the Internet landscape. How to communicate and how to exchange information is one of the challenges of the Internet world of things. 6LoWPAN and CoAP standards for using web protocols in low-loss and low-power sensor networks (LLNs) are presented. The 6LoWPAN / CoAP protocol stack allows access to the sensor network through web protocols. This will facilitate the development of applications on the sensor network and access to them by the Internet. Each layer stack of the 6LoWPAN / CoAP protocol imposes overhead on interchange messages, and data overload in multichannel networks exacerbates energy consumption. In this paper, a method for reducing the overhead imposed on small and medium packets in multi-step networks based on 6LoWPAN / CoAP is presented using the scheduling and aggregation of CoAP packets on sensor nodes. In order to achieve the research objectives, measures such as the classification of CoAP requests / responses in terms of network priority (maximum allowed delay detection), scheduling and aggregation of incoming messages on sensor nodes (based on the maximum allowed delay of each), and opening messages aggregated in the destination , It has been done. The evaluation results of the proposed method indicate a reduction of energy consumption and network traffic for applications such as monitoring, in multi-step networks based on the 6LoWPAN/ CoAP protocol stack. Manuscript profile -
Open Access Article
548 - Sustainable Tree-Based Scheduling in Solar Powered Wireless Mesh Networks
H. Barghi S. V. AzhariIn many applications of wireless mesh networks, due to the lack of access to a permanent source of energy and the use of battery and energy harvesting equipment, energy sustainable design is very important. Duty-cycle adjustment, putting the node into sleep mode in some MoreIn many applications of wireless mesh networks, due to the lack of access to a permanent source of energy and the use of battery and energy harvesting equipment, energy sustainable design is very important. Duty-cycle adjustment, putting the node into sleep mode in some parts of the working period, is a method for energy saving and sustainability assurance. In this case, to exchange data between neighboring nodes, protocols for sleep scheduling are needed. In some applications of these networks, such as video surveillance applications, it is necessary to collect data from different parts of the network. Tree topology is a good option for these applications. A simple method for coordinating sleep in a tree topology is the TIME-SPLIT algorithm, at which the working time of each node is evenly divided among its children. The proposed TIME-SPLIT scheduling algorithm does not consider the node energy limitations. In this paper, we have added the nodes duty-cycle constraint in the TIME-SPLIT algorithm to guarantee energy sustainability in tree-based wireless mesh networks. In situations where the energy status of the children is different, equal division of time leads to network inefficiency. To improve network efficiency and throughput, we provide two scheduling algorithms that take into account the conditions of the children's energy and traffic. In the first proposed algorithm, the time division is performed in relation to the duty-cycle of the children of each node. In the second algorithm, the time division is dynamically and in proportion to the traffic of the children, and the connection acceptance is more precisely performed based on its energy consumption during its lifespan. The simulation results performed by the NS3 network simulator show that in energy and tree structure imbalance conditions, where children of a node have different energy or sub tree, the proposed methods significantly (more than about 60%) increase the network’s total delivered traffic. Manuscript profile -
Open Access Article
549 - A Pattern-Matching Method for Estimating WCET of Multi-Path Monotonic Loops
Mehdi Sakhaei-nia S. parsaPattern matching is one of possible methods proposed for estimating the WCET of the loops. If the loop matches with the proposed pattern, the number of iterations is calculated using an equation. In fact, the derivation of counter values for all iterations is thus avoid MorePattern matching is one of possible methods proposed for estimating the WCET of the loops. If the loop matches with the proposed pattern, the number of iterations is calculated using an equation. In fact, the derivation of counter values for all iterations is thus avoided. A shortcoming of pattern matching methods is its excessive dependence upon patterns. It is dependent upon location, frequency and how to change in value of the counter and structure and place of counter tester. In order to reduce dependence upon patterns, loop flow can be modeled in two sets of symbolic expressions indicating iteration conditions and changes in value of counters. Based upon these expressions, the number of possible values that could be assigned to the loop control variables during the loop execution is computed as the worst-case estimation of the number of loop iterations. But the estimate presented in this method is greater than the actual value and there is overestimation. In this paper, the variables whose values are equal on the different paths and this value is accounted as an iteration, are detected and are considered in the estimations. This will reduce the overestimation. The evaluations are showed that the proposed method is effective and efficient and has less overestimation. Manuscript profile -
Open Access Article
550 - Incremental Opinion Mining Using Active Learning over a Stream of Documents
F. NoorbehbahaniToday, opinion mining is one the most important applications of natural language processing which requires special methods to process documents due to the high volume of comments produced. Since the users’ opinions on social networks and e-commerce websites constitute a MoreToday, opinion mining is one the most important applications of natural language processing which requires special methods to process documents due to the high volume of comments produced. Since the users’ opinions on social networks and e-commerce websites constitute an evolving stream, the application of traditional non-incremental classification algorithm for opinion mining leads to the degradation of the classification model as time passes. Moreover, because the users’ comments are massive, it is not possible to label enough comments to build training data for updating the learned model. Another issue in incremental opinion mining is the concept drift that should be supported to handle changing class distributions and evolving vocabulary. In this paper, a new incremental method for polarity detection is proposed which with the application of stream-based active learning selects the best documents to be labeled by experts and updates the classifier. The proposed method is capable of detecting and handling concept drift using a limited labeled data without storing the documents. We compare our method with the state of the art incremental and non-incremental classification methods using credible datasets and standard evaluation measures. The evaluation results show the effectiveness of the proposed method for polarity detection of opinions. Manuscript profile -
Open Access Article
551 - Reduce Dimensions of CDF Steganalysis Approach Using a Graph Theory Based Feature Selection Method
S. Azadifar S. H. Khasteh M. H. EdrisiThe steganalysis purpose is to prevent the pursuit of steganography methods for your goals. In steganography, in order to evaluate new ideas, there should be known steganalysis attacks on them, and the results should be compared with other existing methods. One of the m MoreThe steganalysis purpose is to prevent the pursuit of steganography methods for your goals. In steganography, in order to evaluate new ideas, there should be known steganalysis attacks on them, and the results should be compared with other existing methods. One of the most well-known steganalysis methods is CDF method that used in this research. One of the major challenges in the image steganalysis issue is the large number of extracted features. High-dimensional data sets from two directions reduce steganalysis performance. On the one hand, with the increase in the dimensions of the data, the volume of computing increases, and on the other hand, a model based on high-dimensional data has a low generalization capability and increases probability of overfitting. As a result, reducing the dimensions of the problem can both reduce the computational complexity and improve the steganalysis performance. In this paper, has been tried to combine the concept of the maximum weighted clique problem and edge centrality measure, and to consider the suitability of each feature, to select the most effective features with minimum redundancy as the final features. The simulation results on the SPAM and CC-PEV data showed that the proposed method had a good performance and accurately obtained about 96% in the detection of data embedding in the images, and this method is more accurate than the previously known methods. Manuscript profile -
Open Access Article
552 - Enhancing Speed, Area and Power Consumption of Carry Select Adders Using a New Grouping Structure
A. Mohammad Nezhad M. Taghizadeh FiroozjaeeDesign of low-cost and high-speed datapath is very important for current computing systems. The adders are the essential parts of datapaths in computing systems. Among different types of adders, the carry select adder (CSeA) has a high speed while having the area overhe MoreDesign of low-cost and high-speed datapath is very important for current computing systems. The adders are the essential parts of datapaths in computing systems. Among different types of adders, the carry select adder (CSeA) has a high speed while having the area overhead, as well. A factor influencing the speed of this adder is the incorporated grouping structure dependent to its components' delay. In this paper, at first, the delay and area of different existing CSeA architectures are reduced by utilizing a fast and small multiplexer. Then, a new grouping structure is proposed for more delay reduction based on a delay analysis. Implementation and experimental results show that applying the proposed grouping and modifications on different CSeA architectures leads to a high delay reduction in the add operation compared to the best existing grouping structure. For example, the amount of delay reduction in the investigated 32-bit CSeA architectures is more than 33%. In addition, the average reduction of power-delay-product criterion for 32-bit and 64-bit CSeAs utilizing the proposed grouping equals45% and 35%, respectively, compared to the CSeAs incorporating the current best grouping. Manuscript profile -
Open Access Article
553 - An Improvement in Microblog Hashtag Recommendation Based on Topic Vector
Mir Saman Tajbakhsh J. BagherzadehStatic contents defined in Web 1.0 were replaced with structured user generated contents by means of Web 2.0. Wikis, Blogs, Social Networks, and Social Bookmarking Systems are some of the examples where users can generate and publish contents. Generating contents by use MoreStatic contents defined in Web 1.0 were replaced with structured user generated contents by means of Web 2.0. Wikis, Blogs, Social Networks, and Social Bookmarking Systems are some of the examples where users can generate and publish contents. Generating contents by users leads to creation of heterogeneous data which makes computation and algorithms hard to be applied. Web 2.0 benefits hashtags (tags) in order to solve the heterogeneous problem of the contents in which users can label their contents with hashtags. This technique cannot help in microblogging systems such as Twitter because of number of characters in each tweet (140 characters per tweet) and leads the tags or words be truncated or be used in heterogeneous form. In the current paper, a novel method is introduced based on Latent Dirichlet Allocation which can be used for numericalization tweets in a vector namely topic vector (TV). Additionally, TV is used for modeling users’ taste which can improve hashtag recommendation. The proposed method has been tested on 8396744 real tweets in English. The top 1 to 5 hashtags are recommended for each tweet and results show precision more than 20% and recall more than 45%. The improvement applied by TV shows that the most precision is increased from 3% to 32%, and recall from 21% to 46% to the best method tested by the authors. Manuscript profile -
Open Access Article
554 - Energy-Aware Scheduling for Real-Time Unicore Mixed-Criticality Systems
S. H. Sadeghzadeh yasser sedaghatIntegrated modular avionics (IMA) has significantly evolved avionic industry. In this architecture, tasks with different criticality have been integrated into a share hardware in order to reduce the size, weight, power consumption and cost so they commonly use the resou MoreIntegrated modular avionics (IMA) has significantly evolved avionic industry. In this architecture, tasks with different criticality have been integrated into a share hardware in order to reduce the size, weight, power consumption and cost so they commonly use the resources. The industry’s interest in integrating tasks has resulted in introducing mixed-criticality systems. Real time and assurance of executing critical tasks are considered of the two basic needs for these kinds of systems. However, integration of critical and non-critical tasks makes some problems for scheduling executing tasks. On the other hand, reducing energy consumption is another important need as these devices run by batteries. Therefore, the present study aims at satisfying the above mentions needs (real time scheduling and reducing energy consumption) by introducing an innovative energy- aware scheduling approach. The proposed algorithm guarantees executing critical tasks as well as reducing energy consumption by dynamic voltage and frequency scaling (DVFS). The results of simulation showed that energy consumption of the proposed algorithm improved up to 14% in comparison with the similar approaches. Manuscript profile -
Open Access Article
555 - Analyzing the Effect of Heterogeneous Cache Hierarchy in Data Center Processors
Adnan Nasri M. Fathy Ali BroumandniaThis paper focuses on the effect of heterogeneous cache hierarchy in data center processors in the dark silicon era. For extreme-scale high performance computing systems, system-wide power consumption has been identified as one of the key constraints. As energy consumpt MoreThis paper focuses on the effect of heterogeneous cache hierarchy in data center processors in the dark silicon era. For extreme-scale high performance computing systems, system-wide power consumption has been identified as one of the key constraints. As energy consumption becomes a key issue for operation and maintenance of cloud data centers, cloud computing providers are becoming significantly concerned. Emerging non-volatile memory technologies are favorable replacement for conventional memory. Here, we employ a nonvolatile memory called spin-transfer torque random access memory (STT-RAM) as an on-chip L2 cache to obtain lower energy compared to conventional L2 caches, like SRAM. High density, fast read access, near-zero leakage power and non-volatility make STT-RAM a significant technology for on-chip memories. In order to decrease memory energy consumption, it is required to address both the leakage and dynamic energy. Previous studies have mainly studied specific schemes based on common applications and do not provide a thorough analysis of emerging scale-out applications with multiple design options. Here, we discuss different outlooks consisting of performance and energy efficiency in cloud processors by running CloudSuite benchmarks as one of scale-out workloads. Experiment results on the CloudSuite benchmarks show that using STT-RAM memory compare to SRAM memory as last level cache, consumes less energy in L2 cache, around 59% at maximum. Manuscript profile -
Open Access Article
556 - Human Action Recognition in Still Image of Human Pose using Multi-Stream neural Network
Roghayeh Yousefi K. FaezToday, human action recognition in still images has become one of the active topics in computer vision and pattern recognition. The focus is on identifying human action or behavior in a single static image. Unlike the traditional methods that use videos or a sequence of MoreToday, human action recognition in still images has become one of the active topics in computer vision and pattern recognition. The focus is on identifying human action or behavior in a single static image. Unlike the traditional methods that use videos or a sequence of images for human action recognition, still images do not involve temporal information. Therefore, still image-based action recognition is more challenging compared to video-based recognition. Given the importance of motion information in action recognition, the Im2flow method has been used to estimate motion information from a static image. To do this, three deep neural networks are combined together, called a three-stream neural network. The proposed structure of this paper, namely the three-stream network, stemmed from the combination of three deep neural networks. The first, second and third networks are trained based on the raw color image, the optical flow predicted by the image, and the human pose obtained in the image, respectively. In other words, in this study, in addition to the predicted spatial and temporal information, the information on human pose is also used for human action recognition due to its importance in recognition performance. Results revealed that the introduced three-stream neural network can improve the accuracy of human action recognition. The accuracy of the proposed method on Willow7 action, Pascal voc2012, and Stanford10 data sets were 91.8%, 91.02%, and 96.97%, respectively, which indicates the promising performance of the introduced method compared to state-of-the-art performance. Manuscript profile -
Open Access Article
557 - Improving Security of LSBM Steganography Using of Genetic Algorithm, Mmulti-Key and Blocking
vajiheh sabeti Sepide faiazi hadise shirinkhahBy increasing the precision of steganalysis attacks in discovering methods of steganography, the need to improve the security of steganographic methods is felt more than ever. The LSBM is one of the simplest methods of steganography, which have been proposed relatively MoreBy increasing the precision of steganalysis attacks in discovering methods of steganography, the need to improve the security of steganographic methods is felt more than ever. The LSBM is one of the simplest methods of steganography, which have been proposed relatively successful attacks for its discovery. The main purpose of this paper is to provide a method for improving security of LSBM. The choice of the sequence of pixels to embed and how to modify them varies in LSBM-based methods. In most existing methods some of these decisions are made at random. In the proposed method in this paper, a multi-key idea in the first step and a genetic algorithm in the second step are used to make better decisions. In the proposed method, as MKGM, the image is blocked and GLSBM is executed for each block with different keys and finally the block with the least histogram change compared to the original block is included in the stego image. The GLSBM method is the same as the LSBM method except that the genetic algorithm is used to decide whether to increase or decrease non-matching pixels. Comparison of the image quality criteria and the accuracy of the attacks in the detection of the proposed method show that these criteria are improved compared to the original LSBM method. Manuscript profile -
Open Access Article
558 - Design and Fabrication of a Miniaturized Gysel Power Divider with Harmonic Suppression Feature Using Low-Pass Filter
In this article, by replacing lowpass filter in Gysel power divider configuration, a power divider with 9 harmonic suppression capability at 930 MHz has been designed analyzed and fabricated. To provide a step by step analysis, the basic resonator of the proposed lowpas MoreIn this article, by replacing lowpass filter in Gysel power divider configuration, a power divider with 9 harmonic suppression capability at 930 MHz has been designed analyzed and fabricated. To provide a step by step analysis, the basic resonator of the proposed lowpass filter has been firstly investigated and the location of the first transmission zero of it has been calculated, then, its stopband is extended by using rectangular suppressor. After replacing the designed filter in Gysel configuration, the final circuit has been fabricated and measured. The measured results indicate that the final circuit has 79% size reduction in comparison with a conventional Gysel power divider. Moreover, first port return loss, the second port return loss, the isolation and insertion loss are 16.5, 17, 36, 3.14 dB, respectively. Manuscript profile -
Open Access Article
559 - Scheduling of IoT Application Tasks in Fog Computing Environment Using Deep Reinforcement Learning
Pegah Gazori Dadmehr Rahbari Mohsen NickrayWith the advent and development of IoT applications in recent years, the number of smart devices and consequently the volume of data collected by them are rapidly increasing. On the other hand, most of the IoT applications require real-time data analysis and low latency MoreWith the advent and development of IoT applications in recent years, the number of smart devices and consequently the volume of data collected by them are rapidly increasing. On the other hand, most of the IoT applications require real-time data analysis and low latency in service delivery. Under these circumstances, sending the huge volume of various data to the cloud data centers for processing and analytical purposes is impractical and the fog computing paradigm seems a better choice. Because of limited computational resources in fog nodes, efficient utilization of them is of great importance. In this paper, the scheduling of IoT application tasks in the fog computing paradigm has been considered. The main goal of this study is to reduce the latency of service delivery, in which we have used the deep reinforcement learning approach to meet it. The proposed method of this paper is a combination of the Q-Learning algorithm, deep learning, experience replay, and target network techniques. According to experiment results, The DQLTS algorithm has improved the ASD metric by 76% in comparison to QLTS and 6.5% compared to the RS algorithm. Moreover, it has been reached to faster convergence time than QLTS. Manuscript profile -
Open Access Article
560 - A New and Robust AMP Algorithm for Non IID Matrices Based on Bayesian Theory in Compressed Sensing
F. Ansari Ram M. Khademi Abbas Ebrahimi moghadam H. Sadoghi YazdiAMP is a low-cost iterative algorithm for recovering signal in compressed sensing. When the sampling matrix has IID zero-mean Gaussian elements, the convergence of AMP is analytically guaranteed. But for other sampling matrices, especially ill-conditioned matrices, the MoreAMP is a low-cost iterative algorithm for recovering signal in compressed sensing. When the sampling matrix has IID zero-mean Gaussian elements, the convergence of AMP is analytically guaranteed. But for other sampling matrices, especially ill-conditioned matrices, the recovery performance of AMP degrades and even may be diverged. This problem limits the use of AMP in some applications such as imaging. In this paper, a method is proposed for modifying the AMP algorithm based on Bayesian theory for non-IID matrices. Simulation results show better robustness properties of the proposed algorithm for non-IID matrices in comparison with previous works. In other words, the proposed method has more precision in recovery, and converges with less iterations. Manuscript profile -
Open Access Article
561 - An Intelligent Novel Hybrid Live Video Streaming Method in Mesh-Based Peer-to-Peer Networks
Naghmeh Farhadian behrang barekatain Majid Haroni Behzad Soleimani NeysianiLack of an efficient video frame delivery method due to high delay in Pull method and large number of duplicated frames in Push method, as the two main content delivery methods among peers, has been a strong motivator for introducing hybrid methods based on these two ba MoreLack of an efficient video frame delivery method due to high delay in Pull method and large number of duplicated frames in Push method, as the two main content delivery methods among peers, has been a strong motivator for introducing hybrid methods based on these two basic approaches for live video streaming in mesh-based peer-to-peer networks. Recent studies show that these hybrid methods suffer from inherent challenges of the two basic approaches because they are just a sequential or parallel execution of them. In this regard, this research introduces AMIN, a novel hybrid method for intelligently exchanging video frames among peers. Using AMIN, contrary to Pull, each peer sends its buffer map status (BMS) to its two-hop neighbors and the peer who receives the BMS will immediately check which video frames it can send to that peer instead of requesting missed video frames in its buffer from it. In addition, contrary to Push and because of BMS, peers do not blindly send video frames to their neighbors. Simulation results show that video quality considerably increases in peers, while End-to-End delay, received delay and the number of duplicated frames decrease in comparison with two basic methods as well as another recent similar approach. Manuscript profile -
Open Access Article
562 - Priority-Based Task Scheduling Using Fuzzy System in Mobile Edge Computing
Entesar Hosseini Mohsen Nickray SH. GH.Mobile edge computing (MEC) are new issues to improve latency, capacity and available resources in Mobile cloud computing (MCC). Mobile resources, including battery and CPU, have limited capacity. So enabling computation-intensive and latency-critical applications are i MoreMobile edge computing (MEC) are new issues to improve latency, capacity and available resources in Mobile cloud computing (MCC). Mobile resources, including battery and CPU, have limited capacity. So enabling computation-intensive and latency-critical applications are important issue in MEC. In this paper, we use a standard three-level system model of mobile devices, edge and cloud, and propose two offloading and scheduling algorithms. A decision-making algorithm for offloading tasks is based on the greedy Knapsack offloading algorithm (GKOA) on the mobile device side, which selects tasks with high power consumption for offloading and it saves energy consumption of the device. On the MEC side, we also present a dynamic scheduling algorithm with fuzzy-based priority task scheduling (FPTS) for prioritizing and scheduling tasks based on two criteria. Numerical results show that our proposed work compared to other methods and reduces the waiting time, latency and system overhead. Also, provides the balance of the system with the least number of resources. And the proposed system reduces battery consumption in the smart device by up to 90%. The results show that more than 92% of tasks are executed successfully in the edge environment. Manuscript profile -
Open Access Article
563 - Grayscale Images Deblurring Using Robust Optimization Problem in Uncertainty Conditions in Blurring Model Parameters
Zeinab Mohammadi Ebrahim Daneshifar Abbas Ebrahimi moghadam M. KhademiNowadays, one of the most important issues in the field of image processing is image de-blurring. De-blurring of an image can be achieved via two different approaches; blind de-blurring and non-blind de-blurring. In blind de-blurring, the kernel by which the blur has oc MoreNowadays, one of the most important issues in the field of image processing is image de-blurring. De-blurring of an image can be achieved via two different approaches; blind de-blurring and non-blind de-blurring. In blind de-blurring, the kernel by which the blur has occurred is assumed unknown, while in non-blind de-blurring, this kernel is given. In blind de-blurring, the blurring kernel must be estimated in order to sharpen the corrupted image. This may increase the computational cost of the de-blurring process. Non-blind image de-blurring is an ill-posed problem with linear reverse issues. Therefore, we develop optimization problems in order to estimate the original sharp images. Usually, non-blind de-blurring methods assume that the blurring kernel is error-free, however, in practice our knowledge of the PSF is uncertain. Hence, in this paper, we use a semi-blind method for de-blurring the blurred image that is robust to this uncertainty. The proposed robust optimization model is followed by a filter for image de-blurring that can attain the solution with lowest possible error in the worst case scenarios, that is, the maximum uncertainty about the blurring kernel. Based on the simulation results, our proposed semi-blind model yields more than 4 dB PSNR improvements compared to conventional blind image de-blurring methods. Manuscript profile -
Open Access Article
564 - A New Multiport DC-DC Converter Based on T-Source for PV-Battery Applications
saber zare A. Rajaei M. R. Kheyrati Mohammad MardanehA new structure of multi-port DC-DC converter is proposed which is based on T-Source converter. It can be used for hybrid renewable energy applications. Two input ports includes a solar panel and battery. The main advantages of the converter are including; high voltag MoreA new structure of multi-port DC-DC converter is proposed which is based on T-Source converter. It can be used for hybrid renewable energy applications. Two input ports includes a solar panel and battery. The main advantages of the converter are including; high voltage gain, continuous input current, independent mode operation of input ports, and high efficiency. Different switching modes are discussed in the relations for steady state operation of the converter are derived. A prototype of the converter is provided and several tests are performed which validates the simulations and theoretical predictions of the converter. Manuscript profile -
Open Access Article
565 - Performance Improvement of Switched Reluctance Motor with a Modified Segmental Rotor
babak allahverdinejad H. Torkaman arash allahyariIn this paper, a segmental SRM and its performance optimization via making some changes on its rotor is investigated. These changes not only reduce the torque ripple, but also increase the efficiency of the motor. Motor has two types of poles on its stator: main and aux MoreIn this paper, a segmental SRM and its performance optimization via making some changes on its rotor is investigated. These changes not only reduce the torque ripple, but also increase the efficiency of the motor. Motor has two types of poles on its stator: main and auxiliary. The auxiliary poles make the flux path shorter and eliminate flux inversion on stator. Different types of notches on rotor structure are examined and the best one is chosen. For simulations, finite element method is utilized. Manuscript profile -
Open Access Article
566 - Traffic Patterns Detection in Video Surveillance Using Optical Flow and Topic Model
Amin Moradi Asadollah Shahbahrami Alireza AkoshidehResearch in the field of video surveillance systems has been improving because of the increasing need for intelligent monitoring, control and management. Given the large amount of data on these intelligent transportation systems, extracting patterns and automatically la MoreResearch in the field of video surveillance systems has been improving because of the increasing need for intelligent monitoring, control and management. Given the large amount of data on these intelligent transportation systems, extracting patterns and automatically labeling them is a challenging task. In this paper, a topic model was used to detect and extract traffic patterns at intersections so that visual patterns are transformed into visual words. The input video is first split into clips. Then, the flow characteristics of the clips, which are based on abundant local motion vector information, are computed using optical flow algorithms and converted to visual words. After that, with a non-probabilistic topic model, the traffic patterns are extracted to the designed system by a group sparse topical coding method. These patterns represent visible motion that can be used to describe a scene by answering a behavioral question such as: Where does a vehicle go? The results of the implementation of the proposed method on the QMUL video database show that the proposed method can correctly detect and display meaningful traffic patterns such as turn left, turn right and crossing a roundabout. Manuscript profile -
Open Access Article
567 - A Distributed Method for Extracting Persian-English Chunks
Seyedeh Sara Mirmobin Mohammad Ghasemzadeh Amin NezaratThis research is in the field of machine translation and in relation to extraction of Persian-English chunks from bilingual corpus by Spark. In this regard, the most important challenge is that the operation must be carried out on large corpus; therefore, it requires di MoreThis research is in the field of machine translation and in relation to extraction of Persian-English chunks from bilingual corpus by Spark. In this regard, the most important challenge is that the operation must be carried out on large corpus; therefore, it requires distributed computing along with big data analysis techniques and tools. When translating text, we are usually confronted with chunks that we need to find the corresponding chunks of each one in the target language and insert it in our translation; this is accomplished by locating it in a corpus that contain the chunks and their corresponding translations. The existing methods, perform this operations in a non-distributed way, therefore while they run slowly, they cannot use a very large corpus. To overcome this shortcoming, in this research a distributed method has been presented, which also takes distance between the sections of chunks into account. The proposed method extracts all possible chunks from the input sentences in the monolingual corpus and uses the correlation coefficient to translate those chunks using the bilingual corpus. We implemented the proposed algorithm in a platform consisting of a computing cluster with sixty-four GB of memory and a twenty-four-core processor in Spark. The incorporated experimental data was a Persian and an English monolingual corpus along with an English-Persian bilingual corpus, each of which containing 100,000 sentences. Experimental results show that run time could greatly be reduced, and the quality of translation is also significantly improved. Manuscript profile -
Open Access Article
568 - Economic Evaluation of Integrated Operation of Electricity and Gas Networks in Khorasan Province
Vahid khaligh Azam Ghezelbash Hassan AbnikiToday, optimal operation and expansion planning have gained great attention in electricity industry optimizations and coordination of electricity and gas networks is one of the main goals in this procedure. In this study, decentralized operation of electricity and gas n MoreToday, optimal operation and expansion planning have gained great attention in electricity industry optimizations and coordination of electricity and gas networks is one of the main goals in this procedure. In this study, decentralized operation of electricity and gas networks is modeled on a real-world case study in Khorasan province of Iran. This modeling is from the perspective of two independent operators who seek to minimize the operation cost of their subordinating network, considering technical constraints. In this way, the amount of gas consumption in gas and electricity networks is considered as a common variable and it is compared using different methods as ADMM, ATC and centralized. Moreover, operating cost is compared in all three different methods. Finally, scenarios of increased load and second fuel have also been investigated using the obtained model. Manuscript profile -
Open Access Article
569 - Global Hybrid Modeling and Control of a DC-DC Buck-Boost Converter via Mixed Logical Dynamical Systems
Mohammad HejriThis paper presents a new model for a DC-DC buck-boost converter considering its all controlled and uncontrolled switching phenomena in both continuous and discontinuous conduction modes. The proposed model is developed based on hybrid systems theory using mixed-logical MoreThis paper presents a new model for a DC-DC buck-boost converter considering its all controlled and uncontrolled switching phenomena in both continuous and discontinuous conduction modes. The proposed model is developed based on hybrid systems theory using mixed-logical dynamical (MLD) systems, and an improved version of these systems called as extended mixed-logical dynamical (EMLD) Systems. Compared to the existing MLD and EMLD models of the DC-DC converters, the proposed model contains fewer numbers of integer variables and inequalities, and, as a result, leads to the less complexity and solution time of the mixed integer optimization problems arising from the corresponding hybrid model predictive controllers. The advantage of the proposed modeling and control method is evaluated via the comparison of the existing MLD models and hybrid predictive controllers as well as classic proportional-integral (PI) controllers. Moreover, the theoretical challenges for the closed-loop stability proof are discussed and in this regard some future research outlines and ideas are introduced. The steady state and transient performance of the closed-loop control system over a wide range of the operation points show the satisfactory operation of the proposed modeling and control scheme for the DC-DC buck-boost converter. Manuscript profile -
Open Access Article
570 - Optimal Strategy Determination of Preventive Maintenance Scheduling in the Presence of Demand Response Resources
V. Sharifi M. Rashidinejad A. Abdollahi M. Mollahassani-pourIn this paper, a new method is proposed for maintenance scheduling of generation units in a competitive electricity market environment. The problem of productive maintenance scheduling is one of the most important problems in the restructured power system due to its imp MoreIn this paper, a new method is proposed for maintenance scheduling of generation units in a competitive electricity market environment. The problem of productive maintenance scheduling is one of the most important problems in the restructured power system due to its impact on the safety and emission of pollutants and producers' profits. In order to consider producers' risk, productive maintenance scheduling has been modeled from the producer's point of view using non-cooperative game theory, which is used to achieve an optimal Nash equilibrium strategy. On the other hand, the independent system operator seeks to achieve a level of appropriate reliability and pollution reduction. In this paper, load response programs are one of the options for influencing energy policy decision-making. Also, the coordination procedure has been used to coordinate producers' maintenance programs with reliability-pollution maintenance program. The proposed model has been implemented on the IEEE-RTS Modified 24 Bus. The results indicate the effectiveness of the proposed method. Manuscript profile -
Open Access Article
571 - Lifetime Estimation of Distribution Transformers in Present of Harmonic Loads: Case Study of Ilam Distribution Transformers
A. Moradkhani M. H. Parhizgari D. BagheriOne of the main components of distribution systems is transformer, and their failure will cause irreparable damage in power systems and distribution companies. These failures are to increase the losses of the transformers due to the increase of harmonics, especially the MoreOne of the main components of distribution systems is transformer, and their failure will cause irreparable damage in power systems and distribution companies. These failures are to increase the losses of the transformers due to the increase of harmonics, especially the current harmonics. These losses increase the temperature of transformers and reduced the lifetime of distribution transformers. In this paper evaluated losses and lifetime in the presence of harmonic loads in Ilam distribution transformers. Technical and practical assessments of the presence of harmonic loads and their effect on the lifetime of transformers have been investigated. According to the obtained results the useful lifetime of some transformers from 30 years to 17 years are decreased. Manuscript profile -
Open Access Article
572 - Economic Load Dispatch in Power Plants, Taking into Account Environmental Pollutants and System Security Indices Using Multi-Objective Harmony Search Algorithm
H. Sharifi محمود اوکاتی صادقPublic sensitivity to environmental issues in the economic dispatch is also impressive. In this case it is necessary to consider the costs of pollution in the economic dispatch. Before the introduction of the concept of power system security, the subject of economic loa MorePublic sensitivity to environmental issues in the economic dispatch is also impressive. In this case it is necessary to consider the costs of pollution in the economic dispatch. Before the introduction of the concept of power system security, the subject of economic load dispatch normally focused on economic aspects rather than security of the system. Today, with the expansion of the power grid and system load, combination of stability and economic load dispatch indices has become a critical necessity. This article will consider the issue of solving the economic dispatch of power plants considering the emissions and security indices of the network. Using penalty functions, system security indices are added to the objective function of economic load dispatch problem. Since fuel costs and emission reduction targets are relatively contrasting, problem solving of economic load dispatch and emission reduction leads to a multi-objective optimization problem. Given the complexity of objective functions and necessity of the considering the practical constrains of power plants operation and security indices reveal more than ever the need to use efficient methods to optimize. In this article Multi Objective Harmony Search algorithm (MOHS) has been used to solve the problem. The results show that MOHS algorithm is excellent for convergence and accuracy compared to other employed methods. The proposed testing system used to solve the problem is IEEE test system with 10 power generation units, 39 bus and 46 transmission line. Manuscript profile -
Open Access Article
573 - Probabilistic Modeling of Fast Charging Station Load Demand for Public Electric Vehicles
Hossein Yousefi Meghdad Tourandaz Kenari Mohammad Sadegh SepasianConsidering economic and environmental factors, it is expected that the number of plug-in electric vehicles (PEVs) will be increased, rapidly. The high penetration of EVs, can affect the power system. Therefore, in recent years, various studies have paid their attention MoreConsidering economic and environmental factors, it is expected that the number of plug-in electric vehicles (PEVs) will be increased, rapidly. The high penetration of EVs, can affect the power system. Therefore, in recent years, various studies have paid their attention to the impacts of PEVs charging on the network. In this paper, a probabilistic model based on the queueing theory is extracted using Monte Carlo simulation for modeling EV charging station load. It is assumed that the vehicles are the taxis of Amol city in Mazandaran province. Required data such as the time of arrival and the state of charge of the battery before charging, were collected and extracted using three methods from intra-city taxis in the city of Amol. To obtain the demand load of EV charging, the traffic-based behavior of drivers is needed. This behavior is stochastic. Therefore, its related variables will not be deterministic and must be evaluated using probabilistic methods. Manuscript profile -
Open Access Article
574 - Design and Implementation of Brushless DC Motor Drive Using Current Source Inverter Based on Space Vector Modulation Strategy
S. Paksaz A. Halvaei NiasarToday, the brushless DC motors (BLDCs) have been widely used in industry due to their unique advantages. These motors are generally fed from voltage source inverters (VSIs). These inverters have a very simple structure, but have problems such as unwanted short circuit a MoreToday, the brushless DC motors (BLDCs) have been widely used in industry due to their unique advantages. These motors are generally fed from voltage source inverters (VSIs). These inverters have a very simple structure, but have problems such as unwanted short circuit across dc-bus and using bulky capacitor in the dc-bus. Using the current source inverters (CSI) is one of the ways to reduce the mentioned problems in VSI-BLDC motor drives. In this paper, the space vector modulation (SVM) strategy is employed for switching in CSI-BLDC motor drive in order to reduce the switching losses, minimize current and torque ripple and increase the reliability of the drive. The BLDC motor drive model is implemented in the Proteus simulator software and the motor behavior is simulated at different speeds. In order to confirm the simulation results, an experimental setup system is designed, implemented and tested. Manuscript profile -
Open Access Article
575 - Low Phase-Noise and Strong Start-Up Condition Voltage Controlled Oscillator for K Band Applications
مصطفی کاتبی A. Nasri S. Toofan H. ZolfkhaniThis paper presents a voltage controlled oscillator (VCO) based on a cross-coupled pair and Colpitts structures for K-band applications. By employing cross-coupled pair and Colpitts structures, the dc power consumption and phase noise was reduced. By using inductors bet MoreThis paper presents a voltage controlled oscillator (VCO) based on a cross-coupled pair and Colpitts structures for K-band applications. By employing cross-coupled pair and Colpitts structures, the dc power consumption and phase noise was reduced. By using inductors between cross-coupled pair and Colpitts structures, the effective transconductance was enhanced and robust the start-up condition. In order to cover a wide frequency tuning range, a capacitor bank was used. The VCO has been designed and simulated in TSMC 0.18 µm CMOS technology. Simulation results showed that the simulated phase noise of center frequency (24.25 GHz), at 1-MHz offset frequency is-120 dBc/Hz and the figure of merit is -195.67 dBc/Hz. The covering frequency range and tuning range of this VCO are 1.4 GHz and 5.7%, respectively. The occupied area of the layout is 335 µ2m and the power consumption of this VCO was 15.92 mW from 1.5 V supply voltage. Manuscript profile -
Open Access Article
576 - New Decentralized Observers for a Large Scale Nonlinear Interconnected Systems
A. Varvani Farahani M. MontazeriIn this paper, a new decentralized observer scheme based on combination of two large scale interconnected subsystems is proposed. It discusses design problem of flow measurement by partial differential equation (PDE) observer for state estimation of a quasi linear syste MoreIn this paper, a new decentralized observer scheme based on combination of two large scale interconnected subsystems is proposed. It discusses design problem of flow measurement by partial differential equation (PDE) observer for state estimation of a quasi linear system without external disturbance and without measurement noise. The measurement system is decomposed into two subsystems according to their locations, condensate and gas pipes, such that each subsystem has interconnection with other. By using matrix form Navier Stocks equations and Lyapunov technique, inequality at each subsystem, a Lyapunov-based design of PDE observer is developed such that the resulting estimation error system is exponentially stable and presented in terms of standard linear matrix inequalities (LMIs). The first mean value theory for integrals is used in the observer design development. The proposed method may be used as a backup for existing systems in the operation field or as a main system for new established plants. Manuscript profile -
Open Access Article
577 - Attribute Reduction Based on Rough Set Theory by Soccer League Competition Algorithm
M. Abdolrazzagh-Nezhad Ali AdibiyanIncreasing the dimension of the databases have involved the attribute reduction as a critical issue in data mining that it searches to find a subset of attributes with the most effectiveness on the hidden patterns. In the current years, the rough set theory has been con MoreIncreasing the dimension of the databases have involved the attribute reduction as a critical issue in data mining that it searches to find a subset of attributes with the most effectiveness on the hidden patterns. In the current years, the rough set theory has been considered by researchers as one of the most effective and efficient tools to the reduction. In this paper, the soccer league competition algorithm is modified and adopted to solve the attribute reduction problem for the first time. The ability to escape the local optimal, the ability to use the information distributed by players in the search space, the rapid convergence to the optimal solutions, and the low algorithm’s parameters were the motivation of considering the algorithm in the current research. The proposed ideas to modify the algorithm consist of utilizing the total power of fixed and saved players in calculating the power of each team, considering the combination of continuous and discrete structures for each player, proposing a novel discretization method, providing a hydraulic analysis appropriate to the research problem for evaluating each player, designing correction in Imitation and Provocation operators based on the challenges in their original version. The proposed ideas are performed on small, medium and large data sets from UCI and the experimental results are compared with the state-of-the-art algorithms. This comparison shows that the competitive advantages of the proposed algorithm over the investigated algorithms. Manuscript profile -
Open Access Article
578 - Text Generation by a GAN-based Ensemble Approach
Ehsan Montahaie Mahdieh Soleymani BaghshahText generation is one of the important problems in Natural Language Processing field. The former methods for text generation that are based on language modeling by the teacher forcing approach encounter the problem of discrepancy between the training and test phases an MoreText generation is one of the important problems in Natural Language Processing field. The former methods for text generation that are based on language modeling by the teacher forcing approach encounter the problem of discrepancy between the training and test phases and also employing an inappropriate objective (i.e., Maximum Likelihood estimation) for generation. In the past years, Generative Adversarial Networks (GANs) have achieved much popularity due to their capabilities in image generation. These networks have also attracted attention for sequence generation in the last few years. However, since text sequences are discrete, GANs cannot be easily employed for text generation, and new approaches like Reinforcement Learning and approximation have been utilized for this purpose. Furthermore, the instability problem of GANs training causes new challenges. In this paper, a new GAN-based ensemble method is proposed for sequence generation problem. The idea of the proposed method is based on the ratio estimation which enables the model to overcome the problem of discreteness in data. Also, the proposed method is more stable than the other GAN-based methods. It also should be noted that the exposure bias problem of teacher forcing approach does not exist in the proposed method. Experiments show the superiority of the proposed method to previous GAN-based methods for text generation. Manuscript profile -
Open Access Article
579 - Nonvolatile and Low-Power Spintronic Full-Adder for Realization of Process in Memory
A . Amirany kian Jafari رامین رجاییAs technology nodes shrink below 90 nm, high static power consumption has become one of the biggest problems of CMOS based circuits due to the exponential leakage current of transistors. Spintronic devices such as magnetic tunnel junction (MTJ) due to their fascinating MoreAs technology nodes shrink below 90 nm, high static power consumption has become one of the biggest problems of CMOS based circuits due to the exponential leakage current of transistors. Spintronic devices such as magnetic tunnel junction (MTJ) due to their fascinating features such as low static power consumption, non-volatility, high endurance, compatibility with CMOS transistors and high-density fabrication are one of the promising candidate for designing hybrid MTJ/CMOS circuits and overcoming high static power consumption of CMOS based circuits. In this paper, a fully nonvolatile and low power hybrid MTJ/CMOS full-adder circuit for Realization of Process in Memory is proposed. The simulation results show that all the proposed circuit is at least 50% faster than all previous counterparts, the power output delay is 39% lower than the previous design, and does not impose high hardware overhead. Manuscript profile -
Open Access Article
580 - Blind Two-Channel Speech Source Separation Based on Localization
Hassan Alisufi M. Khademi Abbas Ebrahimi moghadamThis paper presents a new method for blind two-channel speech sources separation without the need for prior knowledge about speech sources. In the proposed method, by weighting the mixture signal spectrum based on the location of the speech sources in terms of distance MoreThis paper presents a new method for blind two-channel speech sources separation without the need for prior knowledge about speech sources. In the proposed method, by weighting the mixture signal spectrum based on the location of the speech sources in terms of distance to the microphone, the speech sources are separated. Therefore, by forming an angular spectrum by generalized cross-correlation function, the speech sources in the mixture signal are localized. First, by creating an angular spectrogram by generalized cross-correlation function, the speech sources in the mixture signal are localized. Then according to the location of the sources, the amplitude of the mixture signal spectrum is weighted. By multiplying the weighted spectrum by the values obtained from the angular spectrograms, a binary mask is constructed for each source. By applying the binary mask to the amplitude of the mixture signal spectrum, the speech sources are separated. This method is evaluated on SiSEC database and the measurement tools and criteria contained in this database are used for evaluation. The results show that the proposed method is comparable in terms of the criteria available in the database to the competing ones, has lower computational complexity. Manuscript profile -
Open Access Article
581 - Optimal and Sub-optimal Transmitter-Receiver Design in Dense Wireless Sensor Networks and the Internet of Things
Farzad H. Panahi Fereidoun H. Panahi Zahra Askarizadeh ArdestaniWith the rapid development of new technologies in the field of internet of things (IoT) and intelligent networks, researchers are more interested than ever in the concept of wireless sensor networks (WSNs). The emergence of these densely structured networks in recent ye MoreWith the rapid development of new technologies in the field of internet of things (IoT) and intelligent networks, researchers are more interested than ever in the concept of wireless sensor networks (WSNs). The emergence of these densely structured networks in recent years has raised the importance of the use of telecommunications technologies, such as ultra-wideband (UWB) technology with high reliability, industrial applications, and appropriate communication security. However, there are still numerous concerns about the extent of inter-network interference, particularly owing to undesired spectral discrete lines in this technology. As a result, it is necessary to provide an optimal solution to eliminate interference and control the power spectrum, and then design the optimal transmitter-receiver structures while considering high sensitivities to the synchronization problem in WSNs based on UWB technology. These goals are pursued in the present study by employing the optimal spectral strategy in the signal model, the structure of the transmitter sensor, and then constructing the optimal or sub-optimal receiver sensor structures, the results of which indicate improved communication performance in WSNs. Manuscript profile -
Open Access Article
582 - Modeling of K-250 Compressor Using NARX and Hierarchical Fuzzy Model
Adel Khosravi Abbas Chatraei G. Shahgholian Seyed-Mohamad KargarDue to the increasing use of compressors in the industry, it is important to determine a mathematical model for the compressor to design a control system, analysis and simulation of the computer. Also, in recent years, smart modeling such as neural network and fuzzy net MoreDue to the increasing use of compressors in the industry, it is important to determine a mathematical model for the compressor to design a control system, analysis and simulation of the computer. Also, in recent years, smart modeling such as neural network and fuzzy network have been considered by researchers for their more realistic performance, and their types have been used for modeling. Smart methods have high capability to communicate between input and output data. In this paper, modeling of K-250 compressor at Isfahan smelter company based on smart models of fuzzy neural network is presented. The Nonlinear Auto Regressive With exogenous input (Narx) and hierarchical fuzzy network are presented. For modeling, the system has been tested and the input and output data of the compressor using compressor sensors and image processing are used to convert the data into the required data in the modeling, then the above algorithms of the compressor model will be achieved with the help of software, MATLAB. The results of modeling Which NARX performed better than hierarchical fuzzy. Among the two models presented in this paper, the NARX model shows a better response than the hierarchical fuzzy network in all cases and in all aspects of the performance criteria. Manuscript profile -
Open Access Article
583 - Optimizing the Selection and Composition of QoS-Aware Web Services by Considering Dependency, Conflict, and Correlation between Web Services
mahdi farzandway F. ShamsToday, the continuous changes in customer requirements are the main challenges faced by enterprises. Service-oriented architecture is considered as a practical solution to solve this problem for service-oriented enterprises. In the service-oriented architecture, selecti MoreToday, the continuous changes in customer requirements are the main challenges faced by enterprises. Service-oriented architecture is considered as a practical solution to solve this problem for service-oriented enterprises. In the service-oriented architecture, selection and composition of services to quickly respond to complex customer requirements is available to service-oriented enterprises. Enterprises use ready-to-use and outsourced services to respond more quickly to the complex and changing needs of customers. One of the emerging technologies in this area is web services. By expanding the desire of enterprises to use web services, overtime web services providers increased. For this reason, Web services with the same functionality and different qualities were expanded. Therefore, the issue of choosing a web service with the best quality for enterprises is important. On the other hand, enterprises with only one web service cannot meet the complex requirements of customers; therefore, they need to composite multiple web services together. In addition, with the increase of web services with different functions, correlation, dependency and conflict between Web services also expand in their composition. But so far, there is no way to choose the best web services based on the quality of service(QoS) and also their composition does not violate the dependency, conflict and correlation between web services. In this paper, we try to make use of previous methods that consider dependency or conflict or correlation in simple modes of web services composition. We will improve all these methods in a comprehensive approach and support complex situations that may arise from the composition of web services and find the suitable composite web service by considering dependency, conflict, and correlation between Web services. Manuscript profile -
Open Access Article
584 - A Non-Parametric Proximity-Based Method for Outlier Detection
Y. Salehi نگین دانشپورThe detection of outliers is a task in data mining and machine learning and it’s an important step in data preprocessing. In this paper, in order to detect proximity-based outliers, a non-parametric method is proposed called NPOD. The proposed method is a combination of MoreThe detection of outliers is a task in data mining and machine learning and it’s an important step in data preprocessing. In this paper, in order to detect proximity-based outliers, a non-parametric method is proposed called NPOD. The proposed method is a combination of distance-based and density-based methods and has the ability to detect outliers in both local and global scenarios. This method does not require to determine any parameters of neighborhood radius, the threshold of existing points in the neighborhood radius, and the nearest neighbor parameters. In order to detect outliers, a new method of scoring is presented. Experimental results on the UCI datasets show that this algorithm, in spite of being non-parametric, has comparable results with previous methods. Also in some cases, it has the best performance. Manuscript profile -
Open Access Article
585 - Automatic Image Annotation by Block Principal Pivoting
H. Rikabi N. Soufi H. Sadoghi Yazdi A. H. TaheriniaImage annotation systems are responsible for describing the content of the images by assigning tags to them. The purpose of this research is to improve the accuracy and speed of image annotation system. Recently, with the growing of images, the image annotation process MoreImage annotation systems are responsible for describing the content of the images by assigning tags to them. The purpose of this research is to improve the accuracy and speed of image annotation system. Recently, with the growing of images, the image annotation process is based on the basics of images instead of themselves. One of these new methods is the implementation of the non-negative matrix algorithm (NMF) on the features of the images. In the proposed method, for the first time, in order to increase the speed and efficiency of the7 system, we use a method that called the block principal pivoting for the NMF solution. This method has ability to add online new class of data to its knowledge and knowledge learning in a compact form. Moreover, the ability to train based on received data without having to be re-processed. In the training phase, the matrix of the coefficients and the base of the input images are obtained using the Block Principal Pivoting method. Then, at the test phase for the input image, by extracted features of the image and the coefficients obtained from the training phase, the coefficient of belonging to the test image is calculated to each of the classes of training images. Then, this coefficient while searching among the teaching images for assigning the label to test image increases the accuracy of the algorithm. This search is done by the KNN method on the base of the images. To test the proposed method, we used two databases Corel5K and real animal data (derived from 500px) and, finally, compared with existing methods, which we found in the Corel5K database at a precision of 50.20 and real data was 62.89. Precision have been increased considerably. Manuscript profile -
Open Access Article
586 - Control and Power Management of Combined Wind-Microturbine Generation System in Stand-Alone Applications
Ahmad Reza Atapoor محسن رحیمی Allahyar AkhbariThis paper deals with the performance investigation and control of a combined wind-microturbine generation system at off-grid and stand-alone applications. As the novelty, in this paper, the wind turbine does not always work at the MPPT mode, and depending on the availa MoreThis paper deals with the performance investigation and control of a combined wind-microturbine generation system at off-grid and stand-alone applications. As the novelty, in this paper, the wind turbine does not always work at the MPPT mode, and depending on the available wind power and load demand, two operation modes for the wind turbine are defined: power control mode (MPPT mode) and voltage control mode. At the conditions that the available wind power is less than the load demand, the wind turbine operates at the MPPT mode and microtubule provides the rest of the load power. Once the available wind power goes beyond the load demand, the microturbine can not absorb the additional power, and wind turbine works at load following mode. In this mode, the wind turbine power is less than the available wind power and is identical to the load demand, and the microturbine power is negligible. At the end, by performing simulations at the Matlab-Simulink environment, performance of the study system at different operating conditions is investigated. Manuscript profile -
Open Access Article
587 - Improved Realization of Controlled Unitary Gates in the One-Way Quantum Computation Model Using the Extended Measurement Calculus
M. Houshmand M. hooshmandIn one-way quantum computation model (1WQC), the quantum correlations in an entangled state, called a cluster state or graph state, are used to perform universal quantum computations using single-qubit measurements. In 1WQC, the computations are shown by measurement pat MoreIn one-way quantum computation model (1WQC), the quantum correlations in an entangled state, called a cluster state or graph state, are used to perform universal quantum computations using single-qubit measurements. In 1WQC, the computations are shown by measurement patterns or simply patterns. The synthesis problem in the 1WQC model is defined as extracting the pattern from a given arbitrary unitary matrix. The important criteria in evaluating measurement patterns in the 1WQC model, are the size, the depth and the number of entanglements of the pattern. In this paper, a new approach is proposed to synthesize controlled-unitary U gates where U is a single-qubit gate. To this end, for the first time, the idea of applying the extended measurement calculus, which utilizes the measurements in different Bloch sphere planes, is used in the synthesis of the 1WQC model. Some optimizations are proposed for this method and a new approach is presented to synthesize controlled-U gates for the 1WQC model which improves the evaluation criteria of size, depth and the number of entanglements in this model as compared to the best previous result by 9.1%, 30% and 18.1%, respectively. Manuscript profile -
Open Access Article
588 - A Lightweight Intrusion Detection System Based on Two-Level Trust for Wireless Sensor Networks
M. sadeghizade O. R. MarouziWireless sensor networks (WSNs) are one of the useful and attractive technologies that have received much attention in recent years. These networks have been used in a variety of applications, due to their ease of use and inexpensive deployment. Due to the criticality o MoreWireless sensor networks (WSNs) are one of the useful and attractive technologies that have received much attention in recent years. These networks have been used in a variety of applications, due to their ease of use and inexpensive deployment. Due to the criticality of most applications of these networks, security is considered as one of the essential parameters of the quality of service (QoS), and thus Intrusion Detection System (IDS) is considered as a fundamental requirement for security in these networks. This paper provides a trust-based IDS to protect the WSN against all network layer and routing attacks based on the features extracted from them. Through simulations, the proposed IDS has been evaluated with all performance criteria. The results show that the proposed IDS, in comparison with existing works, which often focuses on a specific attack, covers all network layer and routing attacks in WSNs, and also, due to high detection accuracy, low false alarms rate, and low energy consumption is considered as a desirable and lightweight IDS for WSNs. Manuscript profile -
Open Access Article
589 - Improve Identity-based Encryption Algorithm and Its Productivity in Providing Privacy of Cloud-Based Electronic Health Systems
M. Alipour Sh. Bakhtiari Chehelcheshmeh Sh. HeidarianIn this paper, a new method of identity-based encryption is first presented, and it is shown that there is less computational overhead than previous methods. In this regard, the proposed identity-based encryption method is simulated, and the results are compared with th MoreIn this paper, a new method of identity-based encryption is first presented, and it is shown that there is less computational overhead than previous methods. In this regard, the proposed identity-based encryption method is simulated, and the results are compared with the superior representatives of the identity-based encryption. Then, a cloud-based electronic health system (EHS) is proposed using the re-encryption proxy and the identity-based encryption method presented in this paper. In addition to providing confidentiality and enhancing accessibility, the system has a lower running time in the phases of setup, private key generation, encryption, re-encryption key generation, and decryption — this resulting in lower costs and overhead of the cryptographic process in the Electronics health system. Manuscript profile -
Open Access Article
590 - An On-Chip Detection Mechanism to Detect Scan-Based Attack in Crypto-Chips
F. Jamali Zavareh H. BeitollahiSince the advent of cryptographic chips, the side channel attacks have become a serious threat to cryptographic algorithms and security systems. The side channel attacks use weaknesses in the chip implementation instead of using the computational weaknesses of the algor MoreSince the advent of cryptographic chips, the side channel attacks have become a serious threat to cryptographic algorithms and security systems. The side channel attacks use weaknesses in the chip implementation instead of using the computational weaknesses of the algorithms. The scan chain that is widely used in the chip test is one of these side channels. To avoid an attack using a scan chain, one can remove the scan chain after the construction test, but this method makes it impossible to test the post-construction and updating the circuit. Therefore, in addition to preserving the testability of the scan chain, it is necessary to look for a method to prevent the side channel attacks. In this article, a method is proposed to identify the attacker and prevent his scan-based attacks. In this way, by the user authorization, the corresponding output will be generated and the attacker's access to sensitive information is prevented. The proposed method, with an area overhead of less than 1%, power overhead around 1% and a negligible delay overhead retains testability and can prevent differential and signature-based scan attacks better than previous state-of-the-art techniques. Manuscript profile -
Open Access Article
591 - Robot Path Planning using Clonal Selection Algorithm
S.A. daneshnia S. Golzari A. Harifi A. A. RezaeePath planning of mobile robot is one of the most important topics in mobile robotic discussion. The aim of this study is to find a continuous path from an initial position to the final target; So that, it should be free of collision and optimal or near to optimal. Since MorePath planning of mobile robot is one of the most important topics in mobile robotic discussion. The aim of this study is to find a continuous path from an initial position to the final target; So that, it should be free of collision and optimal or near to optimal. Since path planning problem of robot is one type of optimization problems, the evolutionary algorithms can be used to solve this problem. Nowadays, clonal selection algorithm is frequently used to solve the problems because of having valuable computational characteristics. But very little attempts have been done in the field of using this method to solve robot path planning problem. Few accomplished attempts are actually a kind of improved genetic algorithm. In this research, an efficient method for robot path planning in the presence of obstacles is designed using all the features of the clonal selection algorithm. The proposed method is evaluated in various environments with different runs in terms of the proposed path length criteria and the number of generations needed to generate the path. Based on the results of experiments, the proposed method shows better performance than the genetic algorithm in all environments and all the evaluation parameters. Especially, by increasing the number of obstacles vertices and also concave obstacles, the proposed method shows much more efficient performance than the genetic algorithm. Also, comparing the performance of the proposed method with the BPSO algorithm (presented in another study) indicates the superiority of path planning algorithm based on the clonal selection. Manuscript profile -
Open Access Article
592 - High Performance Computing via Improvement of Random Forest Algorithm Using Compression and Parallelization Techniques
Naeimeh Mohammad Karimi Mohammad Ghasemzadeh Mahdi Yazdian Dehkordi Amin NezaratThis research seeks to promote one of the widely being used algorithms in machine learning, known as the random forest algorithm. For this purpose, we use compression and parallelization techniques. The main challenge we address in this research is about application of MoreThis research seeks to promote one of the widely being used algorithms in machine learning, known as the random forest algorithm. For this purpose, we use compression and parallelization techniques. The main challenge we address in this research is about application of the random forest algorithm in processing and analyzing big data. In such cases, this algorithm does not show the usual and required performance, due to the needed large number of memory access. This research demonstrates how we can achieve the desired goal by using an innovative compression method, along with parallelization techniques. In this regard, the same components of the trees in the random forest are combined and shared. Also, a vectorization-based parallelization approach, along with a shared-memory-based parallelization method, are used in the processing phase. In order to evaluate its performance, we run it on the Kaggle benchmarks, which are being used widely in machine learning competitions. The experimental results show that contribution of the proposed compression method, could reduce 61% of the required processing time; meanwhile, application of the compression along with the named parallelization methods could lead to about 95% of improvement. Overall, this research implies that the proposed solution can provide an effective step toward high performance computing. Manuscript profile -
Open Access Article
593 - Performance Improvement of Heterogeneous Networks with Backhaul Constraint through Decoupled Uplink and Downlink Access Policy
a. j. Zolfa Zeinalpour-Yazdi Aliakbar tadaion taftOne of the major challenges in the heterogeneous networks, where different base stations with different capabilities serve users, is the access policy for establishing a communication link between the user and its serving node. To overcome this challenge in a heterogene MoreOne of the major challenges in the heterogeneous networks, where different base stations with different capabilities serve users, is the access policy for establishing a communication link between the user and its serving node. To overcome this challenge in a heterogeneous network which also suffers from the backhaul constraint, a special kind of “decoupled uplink and downlink access” policy is proposed in this paper, which let users to be served by different base stations in uplink and downlink communications. More precisely, in order to efficiently utilize the system resources, increase the users’ throughput, and guarantee the users’ fairness, a special load balancing association policy is considered in the uplink transmission and a problem which maximizes the weighted sum of users’ effective rates is solved. Simulation results show that using this association policy for the considered scenario, significantly improves the load balancing index, energy efficiency, and also users’ effective rate compared to the scenario which considers the criterion of the maximum received power of the downlink connection for both uplink and downlink transmissions. In addition we propose an algorithm which further improves the load balancing considering the backhaul constraint of the base stations and evaluate its efficiency. Manuscript profile -
Open Access Article
594 - Robust Optimal Stable Fuzzy Controller Design for Stabilization of Electric Vehicle Speed, in Presence of Parametric Uncertainties and External Disturbances
Mohammad Veysi M. Shasadeghi M. R. SoltanpourIn electric vehicle’s nonlinear dynamic equations, some parameters has uncertainty such as the coefficient of rolling resistance, drag coefficient, armature resistance and field winding resistance. Design of a controller that is robust in the presence of these parametri MoreIn electric vehicle’s nonlinear dynamic equations, some parameters has uncertainty such as the coefficient of rolling resistance, drag coefficient, armature resistance and field winding resistance. Design of a controller that is robust in the presence of these parametric uncertainties and also in presence of external disturbances, and on the other hand simultaneously satisfies the optimality criteria, is a challenging issue. In practical applications, in addition to the above problem, the computational load of the control input should also be considered and provide a rational interaction between the controller's desirable performance and the calculations volume. In the present paper, a robust optimal stable fuzzy controller based on the parallel distributed compensation is designed, using Takagi-Sugeno fuzzy model of electric vehicle. The stabilizer feedback gains of fuzzy model, the upper bound of the uncertainties, the upper bound of the disturbances effect, and the upper bound of the cost function are obtained completely offline, through the solving of a minimization problem based on the linear matrix inequality. Therefore, the calculation volume of the control input is extremely low. This allows the practical implementation of the proposed controller. The favorable performance of the proposed controller is demonstrated in five-step simulations. Manuscript profile -
Open Access Article
595 - Harmonic Voltage Reduction by using Droop Controller in Inverters Parallel Operation
B. Fani M. Moazzami E. FarhoodiMicrogrid technology makes possible coordination and effective use of different energy resources for supplying loads. In order to have synchronous operation between inverter resources during the occurrence of islanding condition, the use of droop controller structure wo MoreMicrogrid technology makes possible coordination and effective use of different energy resources for supplying loads. In order to have synchronous operation between inverter resources during the occurrence of islanding condition, the use of droop controller structure would be beneficial. In this paper, the conventional droop controller is modified to divide proportional power between resources and cause accurate voltage setting in output resources. By providing a model for connected inverter to the nonlinear load, a harmonic droop controller has been designed. By droop controller related to each harmonic, the harmonic voltages are calculated and add to the reference voltage. Therefore the quality of the output voltage is improved. Then the inverter voltage control loop would be modified with resistance impedance in the presence of non-linear loads, so that, in combination with harmonic droop controller, THD of output voltage considerably reduced. Simulation results show the ability of suggested method in reduction of harmonic voltages in inverters parallel operation. Manuscript profile -
Open Access Article
596 - Optimal Design of Six-Phase Radial Flux Permanent Magnet Synchronous Generator for Small Scale Wind Turbine Applications
M. E. Moazzen S. A. GholamianThis paper presents optimal design of a six-phase permanent magnet synchronous generator (PMSG) for use in direct drive wind turbines. High Dimensions and manufacturing cost and low efficiency are the disadvantages of generators connected to wind turbines without gearbo MoreThis paper presents optimal design of a six-phase permanent magnet synchronous generator (PMSG) for use in direct drive wind turbines. High Dimensions and manufacturing cost and low efficiency are the disadvantages of generators connected to wind turbines without gearbox because of their low nominal speed. Therefore, the main purpose of this paper is to optimize the design of the PMSG based on the reduction of losses and the construction cost of the generator. For this purpose, the relations governing the design of the radial flux PMSG have been introduced and then a design algorithm has been extracted. Subsequently, by defining a multi-objective optimization problem and using the particle swarm optimization (PSO) algorithm, the optimum design variables are determined in a suitable range and the minimum losses and construction cost of the generator are obtained. The optimal design has been verified by using finite element analysis. Manuscript profile -
Open Access Article
597 - Investigation and Analysis of a Soft Switching Multi-Input Converter for Renewable Energy Sources
B. Mazaheri Tehrani M. Khorram Dashti B. Raeisi احسان اديبRenewable energy sources cannot provide load power continuously which is an important challenge in applying these sources. Therefore, usually several renewable sources; such as, solar cells and fuel cells are applied simultaneously. A converter can be applied for each s MoreRenewable energy sources cannot provide load power continuously which is an important challenge in applying these sources. Therefore, usually several renewable sources; such as, solar cells and fuel cells are applied simultaneously. A converter can be applied for each source which results in high implementation cost. Therefore, multi input converters are used to reduce cost and volume of the system. In this paper, a new soft switching multi input converter is proposed. In this converter by applying one additional switch, soft switching is achieved for all main switches. The proposed converter is analyzed and design considerations are discussed. Manuscript profile -
Open Access Article
598 - Balancing the DC Bus Voltage of a Cascaded H-Bridge Converter with Adaptive Carrier Phase Shift Method
M. Rahali Asl M. Saradarzadeh A. R. NamadmalanThe cascaded H-bridge converter is one of the useful multilevel converters for high power applications. The unbalancing of cells DC bus voltages is a major issue in this topology especially when the capacitors are charged from the grid, which mainly is caused by the dif MoreThe cascaded H-bridge converter is one of the useful multilevel converters for high power applications. The unbalancing of cells DC bus voltages is a major issue in this topology especially when the capacitors are charged from the grid, which mainly is caused by the different losses of cells. In this paper a new method is proposed for balancing the cells DC bus voltages without need to measure the cells current. This method is named as “adaptive carrier phase shift”, which is based on the phase shift pulse width modulation. The balancing between the cells DC bus voltages is achieved by measuring the voltages and changing the carrier phase shift. This method is analyzed mathematically and is used to balance a 7-level cascaded H-bridge STATCOM. The feasibility and appropriate function of balancing method is investigated by the simulation studies in the MATLAB/Simulink software. Manuscript profile -
Open Access Article
599 - Selection of an Optimal Equipment Maintenance Strategy Using an Inspection Maintenance Model
M. Samadi H. SeifiReliability centered maintenance is a tool for managing the maintenance of deteriorating assets. The basis of this method is the identification of failure mode of equipment, deterioration process, and maintenance scheduling to reduce the risk of failure and maintenance MoreReliability centered maintenance is a tool for managing the maintenance of deteriorating assets. The basis of this method is the identification of failure mode of equipment, deterioration process, and maintenance scheduling to reduce the risk of failure and maintenance costs. One of the maintenance methods used in reliability-based maintenance is inspection-based maintenance. In inspection-based maintenance, a decision about the type of maintenance is made after an inspection and determination of the deterioration status of equipment. In this paper, a model for annual maintenance scheduling of network equipment is provided. The scheduling problem is formulated as a probabilistic model with binary variables as inspection times and the optimal maintenance strategy is determined. This model is implemented on a transformer and sensitivity analysis is performed to analyze the effect of inspection and outage cost. Manuscript profile -
Open Access Article
600 - Advanced Spatial Modulation
A. Abbasfar H. TafreshianIn this paper, we present a new scheme named advanced spatial modulation for multiple input multiple output (MIMO) systems. Advanced spatial modulation achieves more spectral efficiency than ordinary spatial modulation with using power divider and set the phase of activ MoreIn this paper, we present a new scheme named advanced spatial modulation for multiple input multiple output (MIMO) systems. Advanced spatial modulation achieves more spectral efficiency than ordinary spatial modulation with using power divider and set the phase of active transmit antennas. Using Power divider enable us to have more than one active antenna in a time slot with only one RF-chain in transmitter. Additionally, we can allocate more spatial bits with map information bits into the phase of the transmit antenna. Then, the performance of the proposed system is simulated and is compared with ordinary spatial modulation and some MIMO techniques such as orthogonal space time block code and V-BLAST. Manuscript profile -
Open Access Article
601 - Design and Simulation of a RGW-Based Microwave (15-18 GHz) Power Divider/Combiner and Its Application to High Power SSPA
A. Karimi Nobandegani S. E. HosseiniIn this paper, a 1:8 Ku-band(15-18 GHz) power divider/combiner based on Ridge Gap Waveguide(RGW) technology is designed and simulated which can be extended to arbitrary 1:N power divider/combiners. In the proposed structure a piece of metal and T-junctions with multisec MoreIn this paper, a 1:8 Ku-band(15-18 GHz) power divider/combiner based on Ridge Gap Waveguide(RGW) technology is designed and simulated which can be extended to arbitrary 1:N power divider/combiners. In the proposed structure a piece of metal and T-junctions with multisection impedance matching are used. Return loss of the simulated power divider is better than -10 dB at 15-18 GHz frequency band. Also the insertion loss from input to each output is almost -9dB which was expected. Also difference between phases of the insertion loss from input port to each output port is less than 0.9 degree.. Manuscript profile -
Open Access Article
602 - Outage Power Cost Calculation and Optimal Interruption Allocation to the Customers
Mahdi Khajeh Rezaei Gh. yousefi Ebrahim ShayestehIn power systems operation, interruptions occur due to various reasons such as faults and inadequacy of generation. Load shedding allocation with respect to operation costs and security, customers’ type and their behavior is the main challenge of this paper. In this res MoreIn power systems operation, interruptions occur due to various reasons such as faults and inadequacy of generation. Load shedding allocation with respect to operation costs and security, customers’ type and their behavior is the main challenge of this paper. In this research a new procedure for load shedding allocation with respect to the “load shedding history” of each customer is presented. In this research a new coefficient, called endurance coefficient, is introduced. The customers declare their dependency to electricity via sending their endurance coefficients to the power system operator (ISO).A new method is proposed in this paper in which the customers get paid according to the mentioned coefficient, if load shedding occurs. For validation of the proposed method, different scenarios on IEEE RTS 24-bus test grid is studied and numerical results show effectiveness of the proposed method. Manuscript profile -
Open Access Article
603 - Design and Analysis of an Improved LMS/Newton Adaptive Algorithm for Acoustic Echo Cancellation
Mehdi BekraniSome of important issues in acoustic echo cancellation (AEC) using adaptive filters are the sparseness of the acoustic path impulse responses and strong dependency of the convergence performance of adaptive algorithm to the eigenvalue spread of the input signal correlat MoreSome of important issues in acoustic echo cancellation (AEC) using adaptive filters are the sparseness of the acoustic path impulse responses and strong dependency of the convergence performance of adaptive algorithm to the eigenvalue spread of the input signal correlation matrix. These issues result in a performance degradation of the adaptive AEC systems. In this paper, to improve the performance of the LMS/Newton adaptive algorithm in AEC, the matrix inverse computation is modified. To this end, the matrix inversion lemma is employed such that the contribution of the matrix inverse in the weight update is initially high and as a result, the dependency of the adaptive algorithm to the eigenvalue spread is low during the initial convergence. In addition, for the step-size adjustment, an improved proportionate method is applied such that during the convergence, the contribution of those weights having higher amplitudes in the adaptation process is gradually varied to become identical at the end of convergence. The proposed adaptive proportionate method, results in both convergence rate and steady-state performance improvement for identification of sparse acoustic impulse responses. Simulation results using a colored speech-like signal shows the steady-state misalignment of the proposed algorithm is typically 6.5 dB lower than that of the LMS/Newton algorithm. Moreover, the convergence of the proposed algorithm is typically 3.6 sec faster than that of the PNLMS algorithm, to achieve a misalignment of -17 dB. Theoretical misalignment analyses in the transient and steady state are presented and verified with simulation results. Manuscript profile -
Open Access Article
604 - Feed Locating and Beamforming in Collocated MIMO Antenna Using Characteristic Mode Theory
Mostafa Parvin J. ahmadi-Shokouh Hamideh DashtiKhavidakiIn this paper, a procedure for feed placement in a collocated Multiple Input Multiple Output (MIMO) antenna is presented based on characteristic mode theory. The orthogonality of characteristic currents is used to determine optimal feed locations in the presented antenn MoreIn this paper, a procedure for feed placement in a collocated Multiple Input Multiple Output (MIMO) antenna is presented based on characteristic mode theory. The orthogonality of characteristic currents is used to determine optimal feed locations in the presented antenna. First, characteristic mode analysis is done to determine the resonance modes of the antenna; Then the optimal feed locations are determined to excite these orthogonal modes. Moreover, we modify the shape of the radiation pattern of the antenna by changing amplitude excitation of these modes. It is observed that only by changing amplitudes of the antenna modes and their composition at the desired frequency, the shape and the beam width of the antenna pattern is changed. Manuscript profile -
Open Access Article
605 - Coordinated Scheduling of Electricity and Natural Gas Networks Considering the Effect of PtG Units on Handling Electric Vehicles’ Uncertainties
Iman Goroohi Sardou Ali MobasseriGas-fueled power plants are considerably effective in power system operation during peak hours due to their high up and down ramping rates. By increasing the penetration of gas-fueled power plants in power systems and development of new technologies, such as power-to-ga MoreGas-fueled power plants are considerably effective in power system operation during peak hours due to their high up and down ramping rates. By increasing the penetration of gas-fueled power plants in power systems and development of new technologies, such as power-to-gas (ptg) units, coordinated scheduling of both electricity and natural gas (NG) networks has attracted systems researchers’ attention. The NG volume generated by ptg units are stored in storages to directly supply the NG demands, or to sell in NG markets. If necessary, the stored NG volumes are reconverted into electricity which may be a suitable replacement for batteries and storages in electricity network in long term. In this paper, a mixed integer linear programming (MILP) model is proposed for stochastic coordinated scheduling of electricity and NG networks with ptg units, considering uncertainties of charging and discharging available capacities of vehicle to grid (v2g) stations. A test network integrating modified 24-bus IEEE electricity network and Belgium gas network including nine power stations (three of them are gas-fueled), three v2g stations, and three ptg stations is studied to evaluate the effectiveness of the proposed model. Simulation results demonstrate the effectiveness of ptg units in handling the uncertainties of v2g stations charging and discharging. Besides, the effectiveness of coordinated scheduling of both electricity and NG networks in comparison with independent scheduling of both networks is demonstrated. Manuscript profile -
Open Access Article
606 - A Survey on Inversion over Prime and Binary Fields
Reza Roohghalandari Hatameh Mosanaei Boorani s. bayat sarmadiPublic key cryptography is one of the common cryptosystems mainly because it does not have key agreement issue. One important operation in these cryptosystems is inversion. Therefore, improving its performance gains significant attention. In this paper, inversion operat MorePublic key cryptography is one of the common cryptosystems mainly because it does not have key agreement issue. One important operation in these cryptosystems is inversion. Therefore, improving its performance gains significant attention. In this paper, inversion operation over binary and prime fields are surveyed considering time and area complexity. Moreover, the implementation results on FPGA and ASIC platforms are investigated and analyzed. Manuscript profile -
Open Access Article
607 - User Experience Improvement in Mobile Application Using Information Architecture
FATEMEH ZAHRA GHAZIZADEH sh. VafadarUser experience is an important issue in the success of commercial mobile applications. Information architecture is a discipline which can be used to design user interface in order to achieve desirable user experience based on user and content analysis. In this research MoreUser experience is an important issue in the success of commercial mobile applications. Information architecture is a discipline which can be used to design user interface in order to achieve desirable user experience based on user and content analysis. In this research, the impact of information architecture on the software usability is evaluated by a quantitative approach. By selecting a mobile application, logging the users’ interaction automatically, and analyzing the log, usage problems are discovered. Afterward, navigation system is redesigned by using information architecture. Then, the usability of the new version of the application is evaluated. In this experience, 8 metrics are measured in 11 functionalities for each version of the application. Comparing the results show that among 88 measurements, 74 have been improved, 10 have been decreased and 4 have been unchanged. The most improved metrics are time to reach to the functionality, user extra activities and function finding. Manuscript profile -
Open Access Article
608 - Calculation of the Dimensions and Speed of the Car from the Video Received from the Uncalibrated Camera
R. Asgarian Dehkordi H. KhosraviIn this paper, a fully automated method for calibrating the camera and obtaining dimensions and speed of vehicles is presented. In this method, at first, vanishing points and the focal length of the camera are obtained, according to the directions of the cars in the ini MoreIn this paper, a fully automated method for calibrating the camera and obtaining dimensions and speed of vehicles is presented. In this method, at first, vanishing points and the focal length of the camera are obtained, according to the directions of the cars in the initial frames. After detecting moving vehicles, their 3D bounding box are created using the vanishing points. In order to deal with the perspective, the bounding box of each vehicle is projected on a hypothetical road and then to have their real dimensions in meter, the metric coefficient (pixel-to-meter conversion) is obtained. This calculates the coefficient; a dominant car is detected and according to its metric dimensions, the pixel to meter coefficient is computed. Projecting the vehicle on the road surface and the use of the metric coefficient provides the possibility of expressing the actual speeds and dimensions of the vehicles in each frame. However, it may have some errors. To increase the accuracy of the results, these parameters are aggregated along the vehicle's path, and some histograms are made up for the speed and dimensions of each vehicle. Then the maximum of these histograms is reported as new values of speed and dimensions for each vehicle. This will improve the accuracy. Creating histograms for each vehicle requires tracking of the car in multiple frames. For this purpose, a fast algorithm is presented. Comparing the results of the proposed method with previous methods indicates higher processing speed and better response. The average error of dimension estimation is 1.4%, and the error of speed estimation is 1.1 km/h. The average processing speed for testing videos in MATLAB is about 3.5 frames per second. Manuscript profile -
Open Access Article
609 - Design of an Efficient XOR Circuit in Nanomagnetic Logic
Samira Sayedsalehi Z. Azadi MotlagThe aim of this paper is to suggest new and efficient designs for XOR circuits based on nanomagnetic logic technology in order to implementation of nanomagnetic computational circuits such as adders, subtractors and multipliers. Nanomagnetic logic due to its properties MoreThe aim of this paper is to suggest new and efficient designs for XOR circuits based on nanomagnetic logic technology in order to implementation of nanomagnetic computational circuits such as adders, subtractors and multipliers. Nanomagnetic logic due to its properties such as very high speed, low power consumption, scalability and working on room temperature is a suitable alternative for conventional transistor technology. First, nanomagnetic majority gates are introduced then two efficient designs with minimum area, minimum number of nanomagnetic elements and lowest delays for XOR circuits are proposed based on a three-input minority gate and a five-input majority gate. Basic elements in these designs are out-of-plane nanomagnetic cells made of Co/Pt, due to relative advantages of this alloy. Clocking field which is an external uniform magnetic field is required for proper performance of these proposed circuits. MagCAD tool was used for implementation of these designs, and the accuracy of operation of these circuits was proved by applying Modelsim simulator. According to the results of this simulation, it is shown that the proposed single layer and multilayer three-input XOR gates have improvement in comparison to the state-of-art design in number of gates 50% and 25%, in delay 80% and 80%, and in the number of elements 23% and 21%, respectively. Manuscript profile -
Open Access Article
610 - High Speed and Low Static Power Scan Cell Design in CMOS 22 nm
P. Zakian R. Niaraki AsliOne of the popular methods in design for testability (DFT) is scan design which leads on increase observability and controllability in circuit nodes. In this paper, we present a scan cell design which decreases the number of transistors, improves PDP and decreases energ MoreOne of the popular methods in design for testability (DFT) is scan design which leads on increase observability and controllability in circuit nodes. In this paper, we present a scan cell design which decreases the number of transistors, improves PDP and decreases energy usage. The first proposed design is an optimized version of integrated low power gating scan cell, and the main idea of this design is reducing leakage current in the part of the circuit which is not used. Also, this design has the ability of reducing the propagation delay due to decreasing output parasitic capacitance. In the second proposed design, the scan cell is designed for controlling in pull down part of the inverter at slave latch so that static power consumption is diminished when current path is cut in unnecessary position. Simulations are carried out in 22 nm PTM technology CMOS by Hspice software. The results show that the proposed designs are superior to the previous designs considering propagation delay which is decreased, and enhanced static power consumption. Manuscript profile -
Open Access Article
611 - Analysis and Evaluation of the Effect of Design Parameters on Timing Parameters and Power Consumption of Static Flip-Flop in 16 nm Technology Node
E. Mahmoodi Morteza GholipourFlip-flop is one of the important elements in the digital circuit’s design, which its performance affects the speed and power of the system. In this paper, appropriate simulations are used to obtain the timing parameters of the static flip-flop and investigate the effec MoreFlip-flop is one of the important elements in the digital circuit’s design, which its performance affects the speed and power of the system. In this paper, appropriate simulations are used to obtain the timing parameters of the static flip-flop and investigate the effect of the width of different transistors on these parameters. Then, the effects of the supply voltage and manufacturing process parameters variation on the performance of the flip-flop are investigated. The widths of transistors are determined based on the desired energy-delay product (EDP) and power-delay product (PDP) for these two cases separately. Then, the effect of voltage variations on the increase of EDP and PDP are investigated compared to the base flip-flop. We used a static D-type flip-flop in our simulations. The simulations were performed using the HSPICE in 16 nm technology node at 1 GHz frequency. Manuscript profile -
Open Access Article
612 - Improved BIRCH Clustering by Chemical Reaction Optimization Algorithm to Health Fraud Detection
M. Abdolrazzagh-Nezhad M. KheradWith regard to the scale of the financial transactions and the extent of the healthcare industry, it is one of the ideal systems for fraud. Therefore, suitable identifying fraud data is still one of the challenges facing the healthcare providers, although there are seve MoreWith regard to the scale of the financial transactions and the extent of the healthcare industry, it is one of the ideal systems for fraud. Therefore, suitable identifying fraud data is still one of the challenges facing the healthcare providers, although there are several fraud detection algorithms. In the paper, the BIRCH clustering algorithm, as one hierarchical clustering algorithm, is hybridized with a chemical reaction optimization algorithm (CRO). The BIRCH with linear time complexity is able for clustering large scale data and identifying their noises and the CRO, as one of new meta-heuristic algorithm inspired by the chemical reactions in the real world, explores the search space with a dynamic population size based on four reactions such as on-wall ineffective collision, decomposition, inter-molecular ineffective collision and synthesis. Due to the improved BIRCH-CRO removes the internal clustering process of the classic BIRCH and determines the optimal values of its main parameters, it causes that the computational time decreases and accuracy and precision of detecting fraud data increase since its experimental results is compared with the exist unsupervised algorithms. Also, the proposed fraud detection algorithm has the ability to perform on online data and large scale data, and given the obtained results, it provides a proper performance. Manuscript profile -
Open Access Article
613 - Using Combined Classifier Based on the Separation of Conventional and Unconventional Samples to Diagnose Breast Cancer
amin rezaeipanah hesam vaghebinBreast cancer is one of the most common types of cancers in women and in recent years there has been a significant increase in the number of people with this disease. With the increasing spread of science, data mining has become one of the most widely used areas for imp MoreBreast cancer is one of the most common types of cancers in women and in recent years there has been a significant increase in the number of people with this disease. With the increasing spread of science, data mining has become one of the most widely used areas for improving therapeutic systems. In this paper, the diagnosis of breast cancer is performed in two steps. In the first step, an improved genetic algorithm is used to identify the desirable features in the prediction of this disease, and in the second stage, conventional and Unconventional samples are identified to increase the accuracy and create the final classification model. For classification work, a comparison between two decision tree and Support vector machine model is used to show the results of the superiority of the Support vector machine model. The results of the experiments reported the accuracy of breast cancer diagnosis on WBCD, WDBC and WPBC data sets are 99.26%, 98.55% and 98.45%, respectively. Manuscript profile -
Open Access Article
614 - Investigating the Absorption Performance of Ink-Jet Printed Microwave Transmission Line at S Band
Mohammad Momeni-Nasab سیدمنصور بیدکی Mohsen Hadizadeh Masoud MovahhediInk-jet printing technology is one of the most promising printing techniques enabling fabrication of conductive patterns in a one-step and direct process. In this study, a microwave transmission line is fabricated on RO4003C substrate using water-based reactive inks and MoreInk-jet printing technology is one of the most promising printing techniques enabling fabrication of conductive patterns in a one-step and direct process. In this study, a microwave transmission line is fabricated on RO4003C substrate using water-based reactive inks and ink-jet printing technique. The fabricated transmission line structure includes an ink-jet printed silver line, a dielectric layer, and a continuous metallic ground plate. The conductivity of the printed line is measured using Four-point probe method. The electromagnetic wave absorption rate of the printed transmission line is simulated according to the measured conductivity, which proves a good agreement with the measured absorption rate at S band (2-4 GHz frequency range). Manuscript profile -
Open Access Article
615 - Robust Human Physical Activity Recognition Using Smartphone Sensors
Mahdi Yazdian Dehkordi Zahra Abedi Nasim KhaniHuman physical activity recognition using gyroscope and accelerometer sensors of smartphones has attracted many researches in recent years. In this paper, the performance of principle component analysis feature extraction method and several classifiers including support MoreHuman physical activity recognition using gyroscope and accelerometer sensors of smartphones has attracted many researches in recent years. In this paper, the performance of principle component analysis feature extraction method and several classifiers including support vector machine, logestic regression, Adaboost and convolutional neural network are evaluated to propose an efficient system for human activity recognition. The proposed system can improve the classification accuracy in comparison with the state of the art researches in this field. The performance of a physical activity recognition system is expected to be robust on different smartphone platforms. The quality of smartphone sensors and their corresponding noises vary considerably between different smartphone models and sometimes within the same model. Therefore, it is beneficial to study the effect of noise on the efficiency of the human activity recognition system. In this paper, the robustness of the investigated classifiers are also studied in various level of sensor noises to find the best robust solution for this purpose. The experimental results, which is provided on a well-known human activity recognition dataset, show that the support vector machine with averaged accuracy of 96.34% perform more robust than the other classifiers on different level of sensor noises. Manuscript profile -
Open Access Article
616 - A New Approach to Count or Optimize Point Set Triangulation in the Plane Based on MIS
A. nourollah Zahra RezayatThe triangulation of the given point set on the 2D-plane is the planar straight-line embedding of the graph whose vertices is exactly and set of its edges is maximal (with the most edge). Two important issues are being explored in this area. a) In how many ways can MoreThe triangulation of the given point set on the 2D-plane is the planar straight-line embedding of the graph whose vertices is exactly and set of its edges is maximal (with the most edge). Two important issues are being explored in this area. a) In how many ways can the given set of points be triangulated? b) Which triangulation is optimal based on the given particular feature? The first problem is an open problem, and except in special cases where it has a closed relation, a polynomial time algorithm for it has not been presented in general. The second problem is NP-HARD when the goal is to find a triangulation whose total edge length is the smallest (MWT). So research has been done to provide heuristic, meta heuristic, or approximation algorithms for it. In this paper, a method is presented in which by constructing the intersection graph obtained from all the line segments obtained from all pairs of points of and then algorithms for generating all maximal independent sets (MIS) of the intersection graph is introduced. Furthermore, an algorithm is introduced for counting the number of maximal independent sets. This approach in which constructing intersection graph and converting any triangulation problem to the maximal independent set problem is a new approach for triangulation problem in both cases (a) and (b). Considering difficulties to design algorithms for problems (a) and (b) because of its geometric natures, all the algorithms that have been proposed so far for problems (a) and (b) can be used to solve the triangulation problems in both cases by the approach proposed in this article. The proposed approach of converting triangulation problem to the MIS problem is a new approach that has never been reported to solve counting the number of triangulations or minimum weight triangulation. Furthermore a heuristic estimation algorithm will be introduced to estimate average number of triangulations on the given point set and the algorithm implementation shows its outputs is near to exact values for some instances. Manuscript profile -
Open Access Article
617 - Evaluating Schottky-Barrier-Type GNRFETs-Based Static Flip-Flop Characteristic under Manufacturing Process Parameters Variations
Erfan Abbasian Morteza GholipourGraphene nanoribbon field-effect transistors (GNRFETs) have emerged as encouraging replacement candidate for traditional silicon-based transistor in next-generation technology. Since GNRFETs’ channel is about a few nanometers, impact of manufacturing process variations MoreGraphene nanoribbon field-effect transistors (GNRFETs) have emerged as encouraging replacement candidate for traditional silicon-based transistor in next-generation technology. Since GNRFETs’ channel is about a few nanometers, impact of manufacturing process variations on circuits’ performance is very large. In this paper, impact of manufacturing process variations such as oxide thickness, channel length, and number of dimer lines on schottky-barrier-type GNRFETs (SB-GNRFETs)-based static flip-flop characteristics such as delay, power, and energy-delay-product (EDP) is evaluated and analyzed. Furthermore, Monte-Carlo (MC) simulations have been performed for statistical analysis of these variations. With change in the oxide thickness from its nominal value to 1.15 nm, the propagation delay and EDP are increased by 31.57% and 60.62%, respectively. Also, the channel length variation has the least effect on flip-flop characteristic. The propagation delay and EDP are increased by 315.48 % and 204.79%, respectively, when the number of dimer lines increases by one from its nominal value. The results obtained from MC simulations show that the oxide thickness variations lead to spread of 2.46, 1.57 and 2.39 times higher than the number of dimer lines variations in histogram distribution of flip-flop characteristic. Manuscript profile -
Open Access Article
618 - Analysis and Design of a Low Power Analog to Digital Converter Using Carbon Nano-Tube Field Effect Transistors
Saeedeh Heidari D. DidebanNowadays, analog to digital (A/D) converters are indistinguishable parts of system on chip (soC) structures because they omit the distance between analog real data and digital logic world. Due to this fact and ever increasing trend for using portable instruments, the fi MoreNowadays, analog to digital (A/D) converters are indistinguishable parts of system on chip (soC) structures because they omit the distance between analog real data and digital logic world. Due to this fact and ever increasing trend for using portable instruments, the figures of merit for design of these converters such as speed, power and occupied area are improved. Different methods are proposed to improve the performance of these converters. In this paper, we design a fast and low power ADC using carbon nano-tube field effect transistor (CNTFET) and then its performance is comprehensively compared with a MOSFET based counterpart at the same technology node. The performance is studied two encoders: ROM and Fat tree. The obtained results are presented using HSPICE simulator at 0.9 V power supply. The simulated data from CNTFET based converter shows significant improvements in delay and power compared with its CMOS based counterpart. The power and delay obtained from CNTFET based converter using ROM encoder are improved by 92.5% and 54% with respect to the same parameters obtained from CMOS based design while the improvements using a Fat tree encoder in CNTFET converter reaches 93% and 72% in comparison with CMOS conventional design. Manuscript profile -
Open Access Article
619 - Space Time Code Design in Phased-MIMO Radars to Achieve High Resolution in Board and Velocity
Roholah Vahdani Hossein Khaleghi Mohsen Fallah JoshaghaniIn this paper, space-time codes for MIMO radar are used to achieve high resolution at target range and speed. The two-dimensional ambiguity function is known as a tool to compare radar performance in terms of resolution. A space-time code can be designed based on minimi MoreIn this paper, space-time codes for MIMO radar are used to achieve high resolution at target range and speed. The two-dimensional ambiguity function is known as a tool to compare radar performance in terms of resolution. A space-time code can be designed based on minimizing the distance between the actual target parameters in range, speed and angle. For this purpose, high resolution can be achieved by analyzing the ambiguity function and narrowing it down as much as possible. In this paper, the ambiguity function with two variables of amplitude and speed mismatch is considered and a new criterion to achieve high resolution performance in this field is proposed. In this case, by optimizing the proposed cost functions, the optimal space-time code is extracted. The proposed design can also be extended to phased-MIMO radar. The simulation results also show that our proposed scheme has a very narrow ambiguity function around the origin, while it has a performance very close to the optimal state in terms of target identification probability. Manuscript profile -
Open Access Article
620 - Variational Bayesian inference in Noise Removal from Hyperspectral Images Using Cluster-Based Latent Variables
T. Bahraini Abass Ebrahimi moghadam M. Khademi H. Sadoghi YazdiRemoving noise from hyperspectral images is an inevitable step to improve the quality of these types of images. Many methods have been proposed by researchers in this field. Most of these methods do not address simultaneous spatial-spectral similarities. When the noise MoreRemoving noise from hyperspectral images is an inevitable step to improve the quality of these types of images. Many methods have been proposed by researchers in this field. Most of these methods do not address simultaneous spatial-spectral similarities. When the noise removal method applies data globally without regard to spatial-spectral similarities, it usually has a negative effect on low-level pixels; when in the spectral data, a large number of pixels have little noise and a small number of pixels are destroyed by the high level of noise. In this paper, we first extract spatial-spectral similarities in images by defining cluster-based latent variables. In the following, a low-rank matrix factorization method based on these latent variables is proposed to eliminate the noise of hyperspectral images and to improve the resistance to noise (as compared to other methods). The performance of the proposed method is compared visually with six new methods on real noise-contaminated images. For quantitative comparison, the same experiments are done on clean images combined with six types of simulated noise. The simulation results show that by applying latent variables in the Bayesian inference framework, the performance of the noise removal method is improved and the proposed method performs better than the other methods. Manuscript profile -
Open Access Article
621 - Scheduling of Scientific Workflow Applications in Multi-Cloud Environment Using Cuckoo Search Algorithm
S. Mohammad Latif PourKarimi Somayeh AbdiMulti-cloud environments consist of the considerable variety of resources where the cost of scheduling workflow applications can be significantly reduced in such environments and the resource limitationsimposed by commercial cloud providers can bealso overcome. Accordin MoreMulti-cloud environments consist of the considerable variety of resources where the cost of scheduling workflow applications can be significantly reduced in such environments and the resource limitationsimposed by commercial cloud providers can bealso overcome. Accordingly, this study addresses the scheduling of scientific workflowapplications in a multi-cloud environment under a deadline with the aim of minimizing costs. In this paper,an algorithm for scheduling of workflow applications in multi-cloud environment is presented using the cuckoo search algorithm which is one of the most popular meta-heuristic methods. The Cuckoo Search Algorithm is able to search the solution space in a short time and find solutions in the vicinity of the optimal global solution that is close to it. The results show that the proposed approach of this research has better performance in comparison with other meta- heuristic approach in terms of cost reduction. Moreover, the obtained solutions of the proposed meta- heuristic algorithm are in a desirable degree close to the global optimal solutions of mathematical model. Manuscript profile -
Open Access Article
622 - A Task Scheduling and Mapping Approach to Enhance the Main Design Challenges of Multiprocessor Systems on Chip
حمیدرضا زرندیIn this paper, a static task scheduling and mapping heuristic approach to optimize execution time, reliability, power and temperature of multiprocessor systems on chip is presented. This method is proposed based on the list scheduling approach and utilized task replicat MoreIn this paper, a static task scheduling and mapping heuristic approach to optimize execution time, reliability, power and temperature of multiprocessor systems on chip is presented. This method is proposed based on the list scheduling approach and utilized task replication, dynamic voltage and frequency scaling, and adding cooling slacks to improve reliability, power consumption and temperature to expand the design space and explore the solution set more efficiently. Due to the existing trade-offs among the considered parameters and their optimization, the optimization process is complicated and our proposed method is used the Pareto front generation technique. Moreover, our proposed method, models the objectives comprehensively to consider their dependency. Several experiments are performed to demonstrate the performance and capability of the proposed method in joint optimization of the parameters and extracting the proper solution set. Compared to the previous research, our proposed method outperforms them in optimizing the considered design parameters and its results is 19% better averagely than an efficient studied heuristic method. Manuscript profile -
Open Access Article
623 - Design, Development and Fabrication of Two-Parameter Synthetic Short-Circuit Test for VCB Using Nnetwork-Connected Current Circuit
Alireza Omidkhoda J. Jafari Behnam M. S. Mirghafourian Abdolah Geraiely H. Kazemi Karegar Hamidreza Sadeg mohamadiOne of the main tests of power circuit breaker is to evaluate their breaking capability. Direct test requires a high power source capacity but using the synthetic method and supplying current and voltage from two separated sources, allows to significant power reduction. MoreOne of the main tests of power circuit breaker is to evaluate their breaking capability. Direct test requires a high power source capacity but using the synthetic method and supplying current and voltage from two separated sources, allows to significant power reduction. This paper presents the design, development and fabrication of a synthetic circuit for testing vacuum circuit breaker using distribution network as current circuit. The development and construction of this equipment has made possible to perform short circuit breaking test on VCB according to international standards. Laboratory measurements show good conformity between design and fabrication. Manuscript profile -
Open Access Article
624 - Preventive and Probabilistic-Possibilistic Scheduling of Microgrid against the Natural Phenomena in the Presence of Electric Vehicles
Amirhossein Nasri A. Abdollahi M. RashidinejadThis paper proposes a preventive and probabilistic–possibilistic framework for day-ahead scheduling of Electric Vehicles (EVs) parking lot and distributed generation in a microgrid. The suggested scheduling is performed in normal and emergency conditions when a natural MoreThis paper proposes a preventive and probabilistic–possibilistic framework for day-ahead scheduling of Electric Vehicles (EVs) parking lot and distributed generation in a microgrid. The suggested scheduling is performed in normal and emergency conditions when a natural phenomenon appears and the microgrid is disconnected from the upstream network. Furthermore, the uncertainty of EVs number in a parking lot is considered by Z-number as a probabilistic-possibilistic model. Moreover, the uncertainties of photovoltaic units generation, wind turbine output power, market price, and load demand are modeled by Monte Carlo as a probabilistic method. Furthermore, natural phenomena occurrences are modeled by considering multifarious scenarios according to when the phenomenon unfolds and how much it takes. In the suggested framework, the operation of parking lots is based on the uncertainty and EVs charging/discharging schedule. The operational cost in normal condition and load shedding cost in addition to operational cost are considered as the objective functions of the proposed structure. To evaluate the performance of the suggested structure, the modified 33-bus IEEE distribution network is employed. Manuscript profile -
Open Access Article
625 - A Novel High-Efficiency Soft-Switching Structure for Induction Heatin
Mohamad Reza Banaei sajad gabeli sani khalil monfarediIn this paper, a novel structure and a control method to improve the performance of inductive heating circuits is proposed. In the presented structure, with the combination of the performance of a half-bridge resonant converter with voltage-boost capability, the reducti MoreIn this paper, a novel structure and a control method to improve the performance of inductive heating circuits is proposed. In the presented structure, with the combination of the performance of a half-bridge resonant converter with voltage-boost capability, the reduction in output efficiency at low power and at high power is compensated to an acceptable level. The use of the low number of switches and diodes, the use of the high-quality capacitors with low capacities, good quality of the input current and also high power factor ensures the proper operation of the proposed converter. The switching of high frequency switches in the proposed structure is carried out as soft-switching where resulting in very low switching losses. In this converter, the design of the input filter in order to prevent the effects of electromagnetic interference has been prepared. Finally, to demonstrate the proposed structure operation, the simulation and experimental results are presented. Manuscript profile -
Open Access Article
626 - Modeling and Reliability Evaluation of Magnetically Controlled Reactor based on the Markov Process Technique
M. Haghshenas R. HooshmandControlled reactors as one of the flexible AC transmission systems play an important role in the availability and reliability of power systems.However, in the conventional reliability assessment of power systems, reactive power is considered only as a constraint for the MoreControlled reactors as one of the flexible AC transmission systems play an important role in the availability and reliability of power systems.However, in the conventional reliability assessment of power systems, reactive power is considered only as a constraint for the network, and so far no precise model for assessing the reliability of reactors has been provided. In this paper, a new reliability model based on Markov process is proposed for a magnetically controlled reactor (MCR). In the modeling process, first the MCR structure is divided into two distinct parts, and then the extracted Markov models are combined based on frequency/duration technique.Since temperature changes play a significant role in changing the failure rate of electrical equipment, the effect of temperature changes in accordance with the MIL-217F standard has been considered in the proposed model and its impact on the probability of MCR operating modes has been evaluated. The simulation results have shown that in normal temperature conditions, the control system and at high temperatures, reactor windings can have the greatest impact on the availability of MCR. Comparison of reliability indices at different temperatures has shown that under different temperature conditions, different components will affect the availability of MCR. Therefore, in this condition, the measures needed to improve the reliability of the reactor can be different. This fact highlights the importance of considering the effect of operating temperature on reliability assessment as well as planning for preventive maintenance to improve the performance of reactive power sources. Manuscript profile -
Open Access Article
627 - Stability Analysis of Doubly-Fed Induction Generator Wind Turbine Systems Using Modal Analysis
Ahmad Jafari G. Shahgholian M. ZamanifarIn this paper, the modal analysis of a grid connected doubly-fed induction generator (DFIG) using small signal stability analysis is presented and effect of variation in system parameters such as mutual inductance, stator resistance, line reactance, shaft stiffness and MoreIn this paper, the modal analysis of a grid connected doubly-fed induction generator (DFIG) using small signal stability analysis is presented and effect of variation in system parameters such as mutual inductance, stator resistance, line reactance, shaft stiffness and wind speed on the eigenvalues, stability and damping ratio of different modes of system are studied. This analysis shows that which parameters variation can deviate the system from normal working conditions as well as which parameters variation can improve the system behavior. For evaluating the stability and different controllers design, the simulation results show the effects of parameters variations. Manuscript profile -
Open Access Article
628 - Coordinated Expansion Planning of Gas and Electricity Networks Considering N-1 Security Criterion
V. Khaligh M. Oloomi BuygiPlanning for the coordinated expansion of generation units, taking into account the fuel needed, has always attracted the attention of power industry planners. Failure to coordinated expansion of electricity and gas networks will result in excessive investment and, in s MorePlanning for the coordinated expansion of generation units, taking into account the fuel needed, has always attracted the attention of power industry planners. Failure to coordinated expansion of electricity and gas networks will result in excessive investment and, in some cases, defects in power supply. Therefore, there is a need to a model coordinating the expansion of electricity and gas networks, while taking into account the technical constraints. In this study, centralized expansion of gas and electricity networks is modeled by considering N-1 security criterion in gas network. This modeling is from the perspective of a central investor who, considering the technical constraints, seeks to minimize the total cost of investment and operation of the electricity and gas networks. The results of the gas network investment problem indicate that there is a need to increase pipeline capacity in some areas. In the proposed case study, the investment cost of the gas network is $19 million, while the total cost of investment and operation of the gas network is $37.19 billion. On the other hand, in the electricity grid, new power plants need to be installed in the designated areas. The results also indicate that the capacity of the F-H transmission line should be increased. Moreover, considering the N-1 criterion for gas pipeline outages, the power grid would prefer to install about 3200 MW of new generation units all around the grid thereby boosting the power network against pipeline outages. However, 2400 MW of new generating units would be adequate when N-1 criterion is omitted. Manuscript profile -
Open Access Article
629 - Grid Impedance Estimation of Low Voltage Grids Using Signal Processing Techniques for Frequency Range of 2 kHz – 150 kHz
M. M. AlyanNezhadi H. Hassanpour F. ZareIn this paper, the impedance of low voltage grids in frequency range of 2 kHz - 150 kHz is estimated using rectangular pulse injections and signal processing techniques. The grid impedance is defined as division of voltage signal to current signal in frequency domain. I MoreIn this paper, the impedance of low voltage grids in frequency range of 2 kHz - 150 kHz is estimated using rectangular pulse injections and signal processing techniques. The grid impedance is defined as division of voltage signal to current signal in frequency domain. In noisy condition, the accuracy of impedance estimation is directly dependent to energy of injected signal. The injection signal must has sufficient energy in the frequency range of estimation for an accurate impedance estimation. In the proposed method, several injection signals with different widths are selected with the Genetic algorithm. The grid responses to the injected signals are measured and then denoised for an accurate impedance estimation. When the measurement duration is low, the whole transient state of the grid is not measured; hence the impedance estimation is not accurate. Therefore, in this paper a method is proposed for determining the best measurement duration for impedance estimation using Time-Frequency distributions. The proposed method is applied on several simulated grids and the results show the ability and accuracy of the proposed method in grid impedance estimation. Manuscript profile -
Open Access Article
630 - A Model-Based Approach for Improving Power Transformer Differential Protection
Zahra Kazemi Mohammad Mohammadpour E. FarjahIn this paper, a new algorithm based on Kalman Filter (KF) is proposed for improving the reliability of power transformer differential protection. The three-phase currents of the transformer at the energization side are first estimated by KF. Three residual signals whic MoreIn this paper, a new algorithm based on Kalman Filter (KF) is proposed for improving the reliability of power transformer differential protection. The three-phase currents of the transformer at the energization side are first estimated by KF. Three residual signals which are the differences between the measured (by current transformers) and estimated (by KF) are defined and considered as the decision criteria to discriminate the fault and inrush conditions. During the transformer energization, the residual signals are almost zero. However, in fault conditions, the residual signals exceed a determined threshold value and a trip command will be subsequently issued. The performance of the proposed method is verified using simulations in MATLAB and PSCAD software. Manuscript profile -
Open Access Article
631 - Design of a Fully Integrated Low Voltage, High Efficiency Capacitive, DC-DC Converter for Energy Harvesting Applications
A. Hassanzadeh F. AlirezaeiIn this paper, a low voltage boost DC-DC converter has been presented. The circuit can be used for increasing the output voltage of miniature low voltage generators such as TEG, solar and piezoelectric. The converter is fully integrated and works with low voltages as lo MoreIn this paper, a low voltage boost DC-DC converter has been presented. The circuit can be used for increasing the output voltage of miniature low voltage generators such as TEG, solar and piezoelectric. The converter is fully integrated and works with low voltages as low as 200 mV, and the output voltage can reach 1 V. Body biasing has been used to handle low input voltages. The output power density is 50 µW/mm2, and the converter uses 5 cross coupled stages with 76% efficiency. The maximum total efficiency of the converter for 6 µA load is 52%. The converter uses 0.2 mm2 of chip area using 90 nm technology. Manuscript profile -
Open Access Article
632 - Parity Check Matrix Estimation of k/n Convolutional Coding in Noisy Environment Based on Walsh-Hadamard Transform
Mohammad khaksar H. Khaleghi BizakiBlind estimation of Physical layer transmission parameters, is one of the challenges for smart radios to adapt itself to network standards. These parameters could be transmission rate, modulation and coding scheme that is used for combating with channel errors. Therefor MoreBlind estimation of Physical layer transmission parameters, is one of the challenges for smart radios to adapt itself to network standards. These parameters could be transmission rate, modulation and coding scheme that is used for combating with channel errors. Therefore, Channel Coding Estimation, including code parameters, parity check matrix and generator matrix estimation, is one the interesting research topics in the context of software radios. Algebraic methods like Euclidean methods and Rank-based methods are usually performed on intercepted received sequence to estimate the code. Poor efficiency in a high error probability environment is the main drawback of this methods. Transform-based methods, like Walsh-Hadamard transform is one of the methods that could solve channel coding estimation problem. In this paper, new algorithm based on Walsh-Hadamard Transform is proposed that could reconstruct the parity check matrix of convolutional code with general k/n rate in a high error probability environments (BER>0.07), that has much better performance compared to other methods. This algorithm exploits algebraic properties of convolutional code in order to form k-n equation for estimation of k-n rows of the parity check matrix and then use Walsh-Hadamard transform to solve these equations. Simulation results verified excellent performance of the proposed algorithm in high error probability environments compared to other approaches. Manuscript profile -
Open Access Article
633 - Proposing an Intelligent Method for Design and Optimization of Double tail Comparator
Sadegh Mohammadi-Esfahrood Seyed-Hamid ZahiriThe performance of an Analog/Digital (A/D) converter, various aspects like general architecture of the converter, architecture of the building blocks or design of the blocks can be improved. The comparator block is a fundamental block in data converters. Due to contradi MoreThe performance of an Analog/Digital (A/D) converter, various aspects like general architecture of the converter, architecture of the building blocks or design of the blocks can be improved. The comparator block is a fundamental block in data converters. Due to contradicting design purposes, circuit constraints and necessities, design of comparators and obtaining best circuit performance are complicated and challenging. Such challenges in circuit design necessitate presenting approaches which not only satisfy all the objectives but also, they are cost effective in terms of time and cost. One of the approaches which has recently attracted attentions is the heuristic algorithms based intelligent Methods. Inclined Planes system Optimization algorithm (IPO) is a novel heuristic algorithm inspired by dynamic movement of the objects on frictionless inclined planes. But despite its remarkable ability for exploration and exploitation of the search space, its standard model has complex relationships with many structural parameters that often confuse the user in choosing the effective values for them. In this paper, IPO algorithm is simplified to present a heuristic algorithm (called SIPO) and its efficiency in optimization of 10 standard benchmarks has been evaluated. Then, a multi-objective version of the proposed algorithm (called MOSIPO) for design and optimization of double tail comparator is presented and its efficiency in optimization of double tail comparator has been evaluated and compared with popular multi-objective intelligent methods. The results clearly demonstrate the improved performance and superiority of SIPO and MOSIPO compared to the other methods. Manuscript profile -
Open Access Article
634 - SAHAR: An Architecture to Strengthen the Control Plane of the Software-Defined Network Against Denial of Service Attacks
mehran shetabi Ahmad AkbariSoftware-defined network (SDN) is the next generation of network architecture thatby separating the data plane and the control plane enables centralized control with the aim of improving network management and compatibility. However, due to the centralized control polic MoreSoftware-defined network (SDN) is the next generation of network architecture thatby separating the data plane and the control plane enables centralized control with the aim of improving network management and compatibility. However, due to the centralized control policy, this type of network is prone to Inaccessibility of control plane against a denial of service (DoS) attack. In the reactive mode, a significant increase in events due to the entry of new flows into the network puts a lot of pressure on the control plane. Also, the presence of recurring events such as the collection of statistical information from the network, which severely interferes with the basic functionality of the control plane, can greatly affect the efficiency of the control plane. To resist attack and prevent network paralysis, this paper introduces a new architecture called SAHAR, which consists of a control box consisting of a coordinator controller, a primary flow setup controller, and one or more (as needed) secondary flow setup controller(s). Assigning monitoring and managing tasks to the coordinator controller reduces the load of flow setup controllers. In addition, dividing the incoming traffic between the flow setup controllers by the coordinator controller distributes the load at the control plane. Thus, by assigning the traffic load resulting from a denial-of-service attack to one or more secondary flow setup controller(s), the SAHAR architecture can prevent the primary flow setup controller from impairment and resist DoS attacks. Tests show that SAHAR performs better in the face of a DoS attack than existing solutions. Manuscript profile -
Open Access Article
635 - Wireless Powered Communication System Design with Nonlinear Energy Harvester
مهرنوش میرحاج مریم مسجدی محمدفرزان صباحیIn this paper, a wireless powered communication network (WPCN) is considered, in which the hybrid access point (HAP) and the users are equipped with multiple antennas.In the downlink phase, an energy HAP transfers the energy signal to the users and in the uplink phase, MoreIn this paper, a wireless powered communication network (WPCN) is considered, in which the hybrid access point (HAP) and the users are equipped with multiple antennas.In the downlink phase, an energy HAP transfers the energy signal to the users and in the uplink phase, users apply the harvested energy to transfer their information to the HAP using spatial division multiple access (SDMA) technology. By considering the nonlinear behavior of energy harvester in system design and aiming to maximize the sum of the rates, we propose an optimal method for designing energy pre-coding matrices, user information pre-coding matrices, and time devoted to the downlink and uplink phases. For this purpose, we rewrite the problem as a convex optimization problem by appropriate change of variables and propose a method to solve it. The simulation results show that in practical scenarios, employing the nonlinear energy harvesting model in the system design could reduce the transmitted energy, increase and the sum rate of the users. Manuscript profile -
Open Access Article
636 - Cautious Classification of Hyper Rectangular, Hyper Circular, and Hyper Oval with a Maximum Symmetric Margin Relative to the Data Edge
Yahya Forghani M. Hejazi H. Sadoghi YazdiA robust classification model is a non-standard model for classifying learning based on an uncertain data set. An incautious model is said to have any meaningless answer to any classification model in its possible set of possible solutions. The optimal answer for a caut MoreA robust classification model is a non-standard model for classifying learning based on an uncertain data set. An incautious model is said to have any meaningless answer to any classification model in its possible set of possible solutions. The optimal answer for a cautious robust classification model for a training data set may not be the hyper-page, in which case it will not be possible to classify the data at the test stage. In this paper, incautious robust classification models are introduced and their problems are investigated and then by changing the loss function of a robust classifier, a cautious robust classification model is presented to prevent incautious. The proposed cautious model is standardized and solutions are provided to reduce the training time and test time. In the experiments, the proposed model was compared with some incautious robust models to classification incomplete training data set, and complete definitive training data set. The results showed that in the incomplete data set, the proposed model had less training time and error rate than incautious models. Also, in the complete definitive data set, the proposed model training time and test time were less than incautious models. The results approved that adding caution to a robust classifier is efficient. Manuscript profile -
Open Access Article
637 - Quality of Service Aware Service Composition Method Using Biogeography-Based Optimization (BBO) Algorithm
S. Saligheh B. ArastehFast development in the utilization of cloud computing leads to publishing more cloud services on the cloud environment. The single and simple services cannot satisfy the users’ real-world complex requirements. To create a complex service, it is necessary to select and MoreFast development in the utilization of cloud computing leads to publishing more cloud services on the cloud environment. The single and simple services cannot satisfy the users’ real-world complex requirements. To create a complex service, it is necessary to select and compose a set of simple services. Therefore, it is essential to embed a service composition system in cloud computing environment. Service composition is one of the important NP-hard problems in the service-oriented computings. In this paper, a biogeography-based optimization algorithm is used to create the optimal composite-services. The proposed method was simulated and executed on five different scenarios with different number of tasks and candidate services. The throughput of the proposed method, genetic algorithm and particle swarm optimization algorithm are respectively 0.9997, 0.9975 and 0.9994; furthermore, the reliability of these methods are respectively 0.9993, 0.9980 and 0.9982. The results of simulations indicate that the proposed method outperforms the previous methods in the same conditions in terms of throughput, successability, reliability, response time, and stability. Manuscript profile -
Open Access Article
638 - Efficient Document Partitioning for Load Balancing between Servers Using Term Frequency of Past Queries
Reyhaneh Torab Sajjad ZarifzadehThe main goal of web search engines is to find the most relevant results with respect to the user query in a shortest possible time. To do so, the crawled documents have to be partitioned between several servers in order to use their aggregate retrieval and processing p MoreThe main goal of web search engines is to find the most relevant results with respect to the user query in a shortest possible time. To do so, the crawled documents have to be partitioned between several servers in order to use their aggregate retrieval and processing power. The search engines use different policies for efficient partitioning of documents. In this paper, we propose a new document partitioning method that intends to balance the load between servers to reduce the response time of queries. The idea is to weigh each term based on its daily frequency in log of past queries. We then assign a weight to each document via summing the weight of its substituent terms. The weight of a document approximates the likelihood of its presence in future search results. Finally, the documents are partitioned between servers in a way that the sum of document weights in each server becomes roughly equal. Our evaluation results show that the proposed method is able to balance the load by about 20% better than former algorithms, especially in the peak of search engine traffic. Manuscript profile -
Open Access Article
639 - Family of Variable Step-Size Affine Projection Adaptive Algorithms in Diffusion Distributed Networks
Mohammad S. E. Abadi E. HeydariDistributed processing uses local computations at each node and communications among neighboring nodes to solve the problems over the entire network. Diffusion is one of the methods for performing distributed networks. This paper presents a novel Variable Step-Size Diff MoreDistributed processing uses local computations at each node and communications among neighboring nodes to solve the problems over the entire network. Diffusion is one of the methods for performing distributed networks. This paper presents a novel Variable Step-Size Diffusion Affine Projection Algorithm (VSS-DAPA) to improve the performance of the Diffusion Affine Projection Algorithm (DAPA) in distributed networks. The variable step-size of each node is obtained by minimizing the Mean-Square Deviation (MSD) in that node. In comparison with Diffusion Affine Projection Algorithm (DAPA), the VSS-DAPA algorithm has faster convergence speed and lower steady-state error. To reduce the computational complexity of VSS-DAPA, the Variable Step-Size Selective Regressors Diffusion Affine Projection Algorithm (VSS-SR-DAPA), the Variable Step-Size Dynamic Selection of Diffusion Affine Projection Algorithm (VSS-DS-DAPA) and Variable Step-Size Selective Partial Update Diffusion Affine Projection Algorithm (VSS-SPU-DAPA) are proposed. Simulation results show the good performance of proposed algorithms in convergence speed and steady-state error. Manuscript profile -
Open Access Article
640 - Propose a New Clustering Algorithm for Data Transmission in Wireless Sensor Networks by Using Apollonius Circle
Sh. Pourbahrami E. Khaledi Alamdari L. Mohammad KhanliWireless sensor networks, as an up-to-date technology, are one of the fastest growing technologies in the world today. Since these networks are used in military and agricultural environments as well as for observation of inaccessible environments, these networks need to MoreWireless sensor networks, as an up-to-date technology, are one of the fastest growing technologies in the world today. Since these networks are used in military and agricultural environments as well as for observation of inaccessible environments, these networks need to be organized to achieve goals such as successful and timely sending of data to the main station. Clustering of wireless sensor networks is one of the most widely used methods for organizing these networks. Various ways to cluster these networks are provided, most of which are aimed at preventing energy loss and increasing the lifetime of sensor nodes. The thesis attempts to present a new geometric method for clustering the nodes of wireless sensor networks. In this geometric method, Apollonius circle is used to draw the abstract shape of the clusters and to assemble the nodes around the cluster head. Due to the high accuracy that it has in determining the fit of node distances, this circle can accurately assign nodes to cluster heads and prevent large single-node clusters or faraway nodes. In this algorithm, a main station, a number of nodes are used as a cluster header and a number of nodes as routers. The goal is to find the most accurate cluster heads and create clusters of high coverage in the network. The proposed method is implemented in MATLAB software and comparison of the results obtained from the view of successful data transmission, clustering accuracy, network lifetime and number of coverage areas, is showing accuracy of this method compared to optimal Leach algorithms and K-means presented in this field. Manuscript profile -
Open Access Article
641 - An Efficient Approach to Reduce Energy Consumption in Internet of Things Routing
M. Asgari M. Fathy Mohammad Shahverdy M. Soheili NayerThe Internet of Things (IOT) is a new concept in the area of monitoring information transmission and remote control of things, existents and equipment that has been able to adapt itself with different industries and substructures easily. The information transmission wit MoreThe Internet of Things (IOT) is a new concept in the area of monitoring information transmission and remote control of things, existents and equipment that has been able to adapt itself with different industries and substructures easily. The information transmission with regard to the non-homogenous environment of internet of things has been a challengeable topic and use of routing methods by considering the limitations of processing, calculating, saving and communicating has been known as a necessary issue. Various algorithms with special applications have been already introduced in the domain of internet of things and wireless sensor networks that each one somehow has been successful in achieving the routing goals. Some proposed protocols in this field have used a tree structure for gathering the network information. These methods in selecting the parent or children of graph are affected by important challenges depending on the type of application. In this paper, at first, a general classification of advantages and defects of recent methods has been done in the domain of routing the internet of things and then a routing method service quality awareness in routing based on fuzzy system has been suggested. The results of simulations and assessment express that the suggested method in the tests of energy productivity, delay ratio and data delivery ratio have better performance than the recent methods. Manuscript profile -
Open Access Article
642 - SDDNA: Sign-Digit Coding for Mapping Digital Data in DNA Data Storage
میثم اللهی رودپشتی S. AlinezhadDue to the explosive increment of data in recent application, available data storage cannot respond to this volume of data, for this reason molecular memory have been suggested in recent research. DNA is molecular data storage that can store a large amount of data in a MoreDue to the explosive increment of data in recent application, available data storage cannot respond to this volume of data, for this reason molecular memory have been suggested in recent research. DNA is molecular data storage that can store a large amount of data in a limited space with high endurance. Storing data in low volumes can be provided using appropriate mapping. In this paper, a new method for mapping digital data to DNA have been proposed with the aim of simple coding, omitting the decoding faults, increasing the speed of coding and storing digital data and sign-digit with sufficient compression. Studies show that the proposed method can guarantee long-term retrieval of information from DNA compared to previous methods. It also uses less compression to store digital data as compared to the previous methods. Manuscript profile -
Open Access Article
643 - Diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD) based on Variable Length Evolutionary Algorithm
M. Ramzanyan Hussain Montazery KordyThe methods used today to investigate brain connections to diagnose brain-related diseases are the imaging method of resting magnetic resonance imaging. In this paper, a new method is proposed using an evolutionary variable-length algorithm to select the appropriate fea MoreThe methods used today to investigate brain connections to diagnose brain-related diseases are the imaging method of resting magnetic resonance imaging. In this paper, a new method is proposed using an evolutionary variable-length algorithm to select the appropriate features to improve the accuracy of the diagnosis of healthy and patient-to-patients with attention deficit hyperactivity disorder based on analysis of rs-fMRI images. The characteristics examined are the correlation values between the time series signals of different regions of the brain. Selection of the variable-length property were based on the honey bee algorithm in order to overcome the problem of feature selection in algorithms with fixed-length vector lengths. The Mahalanubis distance has been used as a bee algorithm evaluation function. The efficiency of the algorithm was evaluated in terms of the value of the evaluation function in the first degree and the processing time in the second degree. The results obtained from the significantly higher efficiency of the variable-length bee algorithm than other methods for selecting the feature. While the best result of the overall categorization accuracy among the other methods with the 26 selected characteristics of the PSO algorithm is 76.61%, the proposed method can achieve a total classification accuracy of 85.32% by selecting 25 features. The nature of the data is such that the increase in the number of attributes leads to a greater improvement in the accuracy of the classification so that by increasing the length of the characteristic vector to 35 and 45, classification accuracy was 91.66% and 95.57% respectively. Manuscript profile -
Open Access Article
644 - Reduction of Magnetic Core Losses in Forward Converter for Driving Magnetron Lamp
Mohamad Reza Banaei ابوالفضل نصیریIn this study, a forward converter with phased shifted active clamp is presented for the driving of magnetron lamp (4 kV, 300 mA, 1000 ±40 W).The presented converter is of a boost and high-gain type. To reduce the voltage stress, the active clamp structure is used. In a MoreIn this study, a forward converter with phased shifted active clamp is presented for the driving of magnetron lamp (4 kV, 300 mA, 1000 ±40 W).The presented converter is of a boost and high-gain type. To reduce the voltage stress, the active clamp structure is used. In addition, using the clamp switch phase shifted method, while the maximum flux density of the transformer core retains power, it is possible to increase the time the main key is turned on. Thus, with the same nucleus, the possibility of increasing power transmission is created. Therefore, in the same power, the volume, weight and price of the core used should be reduced.Also, a series resonance circuit provides soft switching conditions. Maximum and average power supply power is controlled for minimum losses. The power supply delivers about 1 kW with an average power of about 250 W by adjusting the time the converter is enabled. Other advantages of the proposed circuit include simply power circuit, reduction of the number of switching elements and reduction of switching losses. The design results have been simulated and verified by PSCAD software. Manuscript profile -
Open Access Article
645 - Anomaly Detection in the Car Trajectories Using Sparse Reconstruction
Reyhane Taghizade Abbas Ebrahimi moghadam M. KhademiIn traffic control and vehicle registration systems a big challenge is achieving a system that automatically detects abnormal driving behavior. In this paper a system for detection of vehicle anomalies proposed, which at first extracts spatio-temporal features form clus MoreIn traffic control and vehicle registration systems a big challenge is achieving a system that automatically detects abnormal driving behavior. In this paper a system for detection of vehicle anomalies proposed, which at first extracts spatio-temporal features form clusters then creates dictionary from these features. This classification stage consists of processes such as, optimized clustering with the bee mating algorithm and sparse processing on spatiotemporal features derived from the training data. Finally the trained classifier is applied to the test data for anomaly detection. The distinction of this study from previous research is using new method of pre-processing to create a dictionary matrix and anomaly detection based on evaluation of matrix that related to each class dependency, which leads to higher accuracy of the proposed method compared to other leading methods. To evaluate the proposed method, UCSD database and video sequences recorded from vehicle traffic on Vakilabad Boulevard at the north side of Ferdowsi University of Mashhad are used and the performance of the proposed method is compare to other competing methods in this field. By analyzing the evaluation standards, we find that the proposed method performance is better than other methods. Manuscript profile -
Open Access Article
646 - Reactive Power Compensation using optimal capacitor allocation in the Distribution Network in the Presence of Wind Power Plant Based on Information Gap Decision Theory
M. Ramezani mahboobeh etemadizadehThe presence of uncertain parameters in the power system has created many challenges for designers andoperators of the system including the problem of capacitors in the presence of wind power plants. The answer depends on the amount of load and output power of the wind MoreThe presence of uncertain parameters in the power system has created many challenges for designers andoperators of the system including the problem of capacitors in the presence of wind power plants. The answer depends on the amount of load and output power of the wind power plant that has uncertain values. In this paper, the information gap based decision theory method is used model the uncertainty in load and output power of the wind power plant. The objective function includes the cost of capacitive banks and energy losses, used to of load Flow based on unscented transformation for calculate energy losses. A genetic algorithm is used to optimize the above problem. Finally, the efficiency of the proposed method has been investigated by carrying out numerical studies on the IEEE 33-bus network. Manuscript profile -
Open Access Article
647 - Hybrid Beamforming in MIMO Systems via Matrix Decomposition
MIMO systems, and particularly massive MIMO systems, achieve high spectral efficiency by using a large number of antennas. An important issue in these systems is beamforming. In fully digital baseband beamforming, an RF chain is required for each antenna, which leads to MoreMIMO systems, and particularly massive MIMO systems, achieve high spectral efficiency by using a large number of antennas. An important issue in these systems is beamforming. In fully digital baseband beamforming, an RF chain is required for each antenna, which leads to high cost and power consumption. In analog beamforming, only one RF chain is used and beamforming is performed by using phase shifters. This method does not provide optimal spectral efficiency and thus, analog-digital hybrid methods for beamforming are considered. In this paper, a hybrid beamforming method is proposed in which the required number of RF chains is much less than fully digital method. The precoder and receiver filter are designed by maximizing the spectral efficiency. To this end, the optimal beamforming matrix (which contains the right singular vectors of the channel matrix) is approximated by the product of two analog and digital beamforming matrices. This approximation is improved by an iterative method. The criterion for the proximity of the two matrices is considered to be the Frobenius norm of their differences. In the receiver, the design of the hybrid beamforming is performed in a similar way, using the mean squares error criterion. Also, to improve the method, a gradient-based algorithm is proposed to further reduce the error. The simulation results show the performance superiority of the proposed method over similar methods as well as its less complexity. Manuscript profile -
Open Access Article
648 - Joint Power-Location Optimization in Cooperative Airborne Relay Networks for 5G+
H. Amiri Mohamadreza Zahabi وحید مقدادیFuture cellular networks 5G+ promise high data rates, ubiquitous services everywhere and flexibility. Cooperative airborne relay networks (CARNs) is a promising system architecture that enables network coverage extension and reliability enhancement. This article determi MoreFuture cellular networks 5G+ promise high data rates, ubiquitous services everywhere and flexibility. Cooperative airborne relay networks (CARNs) is a promising system architecture that enables network coverage extension and reliability enhancement. This article determined the optimum relay location and allocate optimal power to minimize the average symbol error rate (ASER) of an aerial platform CRS with amplify-and-forward relaying protocol (AF-CRS) in the Nakagami-m fading channel. To achieve this goal, the ASER for the AF-CRS in the Nakagami-m channel for different modulations is calculated firstly. Then, we consider three scenarios. First, the optimal location of the AF relay with a given power allocation for the source and relay is determined. Second, the problem of optimizing power allocation for different relay locations is solved. Eventually, an algorithm for joint optimizing the power-location that leads to more efficient system operation is proposed. Also, we investigate the effect of the path-loss exponent, channel fading parameter, and relay altitude on the optimal relay location in the CARS. Finally, Simulations and numerical results are presented, that confirm the theoretical achievements and simulations show a more than 1 dB gain for the optimized system versus the non-optimized system. Manuscript profile -
Open Access Article
649 - Improved Semi-Quantum Direct Communication Protocol
Z. rashidi M. hooshmandUnlike classical cryptography, where security is based on computational complexity, quantum cryptography has unconditional security, which is based on physical constraints. So far, the semi-quantum version of many of the problems of secure quantum communication protocol MoreUnlike classical cryptography, where security is based on computational complexity, quantum cryptography has unconditional security, which is based on physical constraints. So far, the semi-quantum version of many of the problems of secure quantum communication protocols has been proposed. In this study, we examined semi-quantum protocols that allow users to access a secret message directly without distributing the key. An important factor used to analyze the performance of secure quantum direct communication protocols is efficiency. In this study, the proposed semi-quantum secure communication protocol against various quantum attacks has been investigated. In the proposed scheme for decoding the confidential message by the receiver, a sequence of single photons is required, which is first generated by the controller. The proposed protocol has a yield of 50%, which is higher than the previous protocol, which has a yield of 66.6%. Manuscript profile -
Open Access Article
650 - Distributed Control Scheme Based on Model Predictive Control for Supplying Power in an Isolated DC Microgrid
Arash Abedi Behrooz Rezaie Alireza Khosravi مجید شهابیIn this paper, a control scheme is presented for an isolated DC microgrid including wind turbine connected to permanent magnet synchronous generator, electrical energy storage unit, and variable electrical loads. Energy sources are connected to a common bus through DC b MoreIn this paper, a control scheme is presented for an isolated DC microgrid including wind turbine connected to permanent magnet synchronous generator, electrical energy storage unit, and variable electrical loads. Energy sources are connected to a common bus through DC buck and buck-boost converters. The local distributed controllers are located in the first control layer. These controllers are designed based on a Lyapunov stability analysis and thereby its stability is guaranteed. Moreover, the current and voltage, injected to the network, are adjusted by controlling the switching functions of the converters. The decentralized secondary controllers determine the contribution of the local units for supplying the local loads. In this control layer, a model predictive controller for the wind generation unit as well as a proportional-integral controller for preserving the bus voltage are proposed to determine the reference currents for the local controllers. In addition to the practical simplicity, complete isolation of the secondary controllers, minimum requirements to data transfer, and providing a control structure without any need to change in development plan are the important advantages of the proposed control scheme. The performance of the controllers is investigated and verified using the simulations in MATLAB software performed for different cases. Manuscript profile -
Open Access Article
651 - A Feature Selection Algorithm in Online Stream Dataset Based on Multivariate Mutual Information
Maryam Rahmaninia Parham MoradiToday, in many real-world applications, such as social networks, we are faced with data streams which new data is appeared every moment. Since the efficiency of most data mining algorithms decreases with increasing data dimensions, analysis of the data has become one of MoreToday, in many real-world applications, such as social networks, we are faced with data streams which new data is appeared every moment. Since the efficiency of most data mining algorithms decreases with increasing data dimensions, analysis of the data has become one of the most important issues recently. Online stream feature selection is an effective approach which aims at removing those of redundant features and keeping relevant ones, leads to reduce the size of the data and improve the accuracy of the online data mining methods. There are several critical issues for online stream feature selection methods including: unavailability of the entire feature set before starting the algorithm, scalability, stability, classification accuracy, and size of selected feature set. So far, existing methods have only been able to address a few numbers of these issues simultaneously. To this end, in this paper, we present an online feature selection method called MMIOSFS that provides a better tradeoff between these challenges using Mutual Information. In the proposed method, first the feature set is mapped to a new feature using joint Random variables technique, then the mutual information of new feature with the class label is computed as the degree of relationship between the features set. The efficiency of the proposed method was compared to several online feature selection algorithms based on different categories. The results show that the proposed method usually achieves better tradeoff between the mentioned challenges. Manuscript profile -
Open Access Article
652 - Semi-Supervised Ensemble Using Confidence Based Selection Metric in Nnon-Stationary Data Streams
shirin khezri jafar tanha ali ahmadi arash SharifiIn this article, we propose a novel Semi-Supervised Ensemble classifier using Confidence Based Selection metric, named SSE-CBS. The proposed approach uses labeled and unlabeled data, which aims at reacting to different types of concept drift. SSE-CBS combines an accurac MoreIn this article, we propose a novel Semi-Supervised Ensemble classifier using Confidence Based Selection metric, named SSE-CBS. The proposed approach uses labeled and unlabeled data, which aims at reacting to different types of concept drift. SSE-CBS combines an accuracy-based weighting mechanism known from block-based ensembles with the incremental nature of Hoeffding Tree. The proposed algorithm is experimentally compared to the state-of-the-art stream methods, including supervised, semi-supervised, single classifiers, and block-based ensembles in different drift scenarios. Out of all the compared algorithms, SSE-CBS outperforms other semi-supervised ensemble approaches. Experimental results show that SSE-CBS can be considered suitable for scenarios, involving many types of drift in limited labeled data. Manuscript profile -
Open Access Article
653 - Investigating the Influence of Number of Carbon Atoms Along the Width of Graphene Nanoribbon on the current of a Graphene Single Electron Transistor
D. Dideban Vahideh KhademhosseiniA single electron transistor is a nanoscale device comprised of three metallic electrodes and one island or quantum dot. The island can made of carbon nano materials like a graphene nanoribbon. The number of carbon atoms along the width of the graphene nanoribbon affect MoreA single electron transistor is a nanoscale device comprised of three metallic electrodes and one island or quantum dot. The island can made of carbon nano materials like a graphene nanoribbon. The number of carbon atoms along the width of the graphene nanoribbon affect on the speed of transistor operation and coulomb blockade region. In this research, the current for a single electron transistor utilizing a graphene nanoribbon island is modeled. The impact of several parameters on the transistor current is investigated including the number of carbon atoms along the width, length of nanoribbon, and the applied gate voltage. The modeling results show that increasing the number of carbon atoms along the width of the nanoribbon results in reduced coulomb blockade region. Moreover, reducing the length of nanoribbon and increasing the applied gate voltage cause a decrease in the zero current range of the transistor. Increasing the number of atoms along the width of three islands also gives a boost in the electron tunneling region and thus, the transistor performance will be improved. Manuscript profile -
Open Access Article
654 - Controller Design and Asymptotic Stability Analysis of a Buck Converter with a Cascade Control Structure Using Singular Perturbation Theory
Sajad Azarastemal Mohammad HejriThis paper presents the theoretical proof for the closed-loop asymptotic stability of a DC-DC buck converter based on singular perturbation theory. Due to the two-time scales structure of this converter with fast and slow dynamics, a cascade control structure is used to MoreThis paper presents the theoretical proof for the closed-loop asymptotic stability of a DC-DC buck converter based on singular perturbation theory. Due to the two-time scales structure of this converter with fast and slow dynamics, a cascade control structure is used to control it. This controller has two control loops: an outer loop to control the output voltage based on the proportional-integral control and an inner loop to control the inductor current based on the sliding mode control. The controllers in the loops are designed based on perturbation theory to meet the constraints of the converter and ensure the asymptotic stability of the closed-loop system over a wide range of initial conditions. For validation, the proposed control design method is simulated for a typical buck converter in the MATLAB-SIMULINK environment. The simulation results show that by properly selecting the PI controller coefficients in the outer loop, the problem requirements are met, and the asymptotic stability of the closed-loop system is guaranteed in a wide range of the converter initial conditions. Furthermore, the system robustness against load uncertainty and input disturbances as well as the voltage reference tracking are evaluated, and the proposed structure is compared with a PI-PI structure. Manuscript profile -
Open Access Article
655 - A Traffic-Aware Packet Classification Method to Reduce Memory Accesses
Saeid Asadrooz Mohammad Nassiri M. A.Packet classification plays a critical role in improving the performance of many network devices including routers, firewalls and intrusion detection systems. Due to the increasing number of classification rules, high traffic volume and high bandwidth network links, des MorePacket classification plays a critical role in improving the performance of many network devices including routers, firewalls and intrusion detection systems. Due to the increasing number of classification rules, high traffic volume and high bandwidth network links, designing an efficient packet classifier becomes more challenging. Packet classification algorithms that use static data structure do not consider the pattern of the incoming traffic in optimizing their search mechanism. Therefore, we use some statistical characteristics of the incoming traffic to propose a traffic aware data structure. Since most Internet traffic volume belong to long-live flows, the majority of the packets are matched to the rules in a few sub trees. To take the advantage of this feature, AVL tree data structure is served for storing classification rules where the upper and lower limits of the rule-set are used as nodes. Our evaluation have shown that with increasing the skewness of data packets, the average number of memory accesses are significantly decreased compared to the basic case. Finally, evaluation results show that the traffic-aware packet classification with high frequency rules can decrease more than 40% of the average number of memory accesses and consequently the lookup time. Manuscript profile -
Open Access Article
656 - Synthesis and Implementation of Reversible Circuits Using all-optical Switch of Mach-Zehnder Switch (MZI)
yasser Sohrabi M. hooshmand Mohammad boloukian Maryam MoosaviVLSI technology is currently dealing with a serious challenge, as the exponential growth of density in VLSI and CMOS chips has reached its limit. Power dissipation in VLSI chip refers to heat generation, which is a real barrier against traditional CMOS technology. Irrev MoreVLSI technology is currently dealing with a serious challenge, as the exponential growth of density in VLSI and CMOS chips has reached its limit. Power dissipation in VLSI chip refers to heat generation, which is a real barrier against traditional CMOS technology. Irreversible logic leads to problems such as energy dissipation, heat generation, information loss and slow computations. We need a new technology for solving these problems. Using reversible logic can help solve this problem. In next generation of optical computers, electrical circuits and wires will be replaced by several optical fibers and these systems will be more efficient because they will be cheaper, lighter, and more compact without interference. Based on optical computations, several optical switches have been proposed for future applications. One of these switches is the Mach-Zehnder switch. Its behavior and the reversible circuits, which can be made with this switch is studied in this article. Finally, we introduce and design three new all-optical reversible gates named NFT, SRK and MPG, which are effective in designing all-optical reversible logical circuits such as flip-flops and other all-optical reversible sequential circuits. We also simulate one all-optical reversible circuits implemented with Mach-Zehnder switch and provide simulation challenges and solutions to overcome these challenges. Manuscript profile -
Open Access Article
657 - A Thermal Equivalent Circuit for Thermal Analysis of Power Transformers under Harmonic Loads
m. mikhak B. Rezaeealam m. jafarboland v. ebrahimian m. asgariThe majority of the power transformers failures are caused by the thermal stresses under abnormal operating conditions, such as harmonic loads. Therefore, it is of great interest to determine the temperature distribution inside the power transformers. In this paper, a n MoreThe majority of the power transformers failures are caused by the thermal stresses under abnormal operating conditions, such as harmonic loads. Therefore, it is of great interest to determine the temperature distribution inside the power transformers. In this paper, a new thermal equivalent circuit is presented by which the temperature in different regions of the transformer is estimated under harmonic loads. Also, the three-dimensional Finite Element (FE) Model of the power transformer is developed to calculate the power losses in each part of the transformer that are considered as the heat sources in the proposed equivalent circuit. The computed hotspot and average oil temperatures are compared with those obtained from IEEE Std C57.91 method, thereby the accuracy of the proposed method for calculating the temperature rise due to harmonic loads, is investigated. Finally, derating of the power transformer is discussed under harmonic loads. Manuscript profile -
Open Access Article
658 - Adaptive Non-singular Terminal Sliding Mode Control Based On Disturbance Observer for the Microelectromechanical Vibratory Gyroscope Contro
M. R. SoltanpourIn this paper, an adaptive non-singular terminal sliding mode control based on disturbance observer is proposed for detection process and control of the micro-electromechanical vibratory gyroscope stimulation process. For this purpose, the dynamical equations of the vib MoreIn this paper, an adaptive non-singular terminal sliding mode control based on disturbance observer is proposed for detection process and control of the micro-electromechanical vibratory gyroscope stimulation process. For this purpose, the dynamical equations of the vibrational gyroscope system are initially expressed. In the following, the dynamical equations of this system are transmitted to the domain of state-space equations and then to the domain of tracking error. After that, the dynamic structure of the finite time disturbance observer is presented. Then, the design of the adaptive non-singular terminal sliding mode control based on finite time disturbance observer is expressed. The proposed strategy carries out the control of the stimulation process in the presence of structured and un-structured uncertainties existing in the dynamic equations of the microelectromechanical vibrational gyroscope system, and performs the detection process through only an adaptive law. The mathematical proof shows that the closed-loop system with the proposed control, and in the presence of the existing uncertainties, has the finite time global asymptotic stability. The presence of a disturbance observer in the proposed control structure will weaken the role of un-structured uncertainties in the gyroscope control process and reduce the control input amplitude. In order to evaluate the proposed control performance, simulations in 3 steps are implemented on the electromechanical vibrational gyroscope system. Simulation results confirm the desired performance of the proposed control. Manuscript profile -
Open Access Article
659 - A New Non-Isolated Buck-Boost DC-DC Converter with Wide Voltage Conversion Range
M. Heydari h. khoramikia Seyed Mohammad DehghanIn this paper, a new wide-input-wide-output non-isolated buck-boost DC-DC converter is presented. The proposed converter has continuous current and is able to buck and boost the input voltage with shorter duty-cycles of the power switch compared to conventional buck-boo MoreIn this paper, a new wide-input-wide-output non-isolated buck-boost DC-DC converter is presented. The proposed converter has continuous current and is able to buck and boost the input voltage with shorter duty-cycles of the power switch compared to conventional buck-boost converters. A smaller duty cycle for a given voltage gain translates to lower current ripple of the inductors, reduced conduction losses, alleviated voltage stresses of the semiconductor switches and improved overall efficiency. The proposed converter also benefits from a simpler structure and control scheme. In this paper, the steady state operation of the proposed converter is investigated under both continuous conduction mode (CCM). The simulation and experimental results confirm the validity of theoretical analysis as well as the proper performance of the proposed converter. Manuscript profile -
Open Access Article
660 - A Reduced Data Transfer Scheme in Distributed Secondary Control of Microgrid Using Aperiodic Sampling Method
Mohyedin Ganjian-Abukheili مجید شهابی Qobad ShafieeThe steady state error in voltage amplitude and frequency and improper reactive power sharing are main disadvantages of droop control in primary level of control of distributed resources (DERs) in microgrid. Secondary control can compensate these problems. In contrary t MoreThe steady state error in voltage amplitude and frequency and improper reactive power sharing are main disadvantages of droop control in primary level of control of distributed resources (DERs) in microgrid. Secondary control can compensate these problems. In contrary to centralize control, distributed secondary control may bring merits such as reliability, flexibility and scalability improvement. The distributed secondary control is usually implemented using consensus algorithm whose communication network is very important. Communication network is usually modeled continuously with a constant transfer rate. In this paper, the consensus algorithm with communication network are implemented in discrete domain because of discrete nature of them. Two aperiodic data transfer strategies state dependent and state independent are also proposed for releasing communication network burden where data rate is not fixed. Time delay as a non-desirable effect is evaluated. The proposed method applied on an islanded microgrid, and simulation results show the effectiveness of the proposed method. Manuscript profile -
Open Access Article
661 - Coordinated Design of Power System Stabilizer and Variable Impedance Devices to Increase Damping of Inter-Area Modes Using Genetic Algorithm
m. zamani G. ShahgholianPower system stabilizer (PSS) does not have a significant impact on inter-area modes and FACTS devices are used to damping these modes and to enhance power system stability. In this article, an objective function based on different and variable weight coefficients accor MorePower system stabilizer (PSS) does not have a significant impact on inter-area modes and FACTS devices are used to damping these modes and to enhance power system stability. In this article, an objective function based on different and variable weight coefficients according to eigenvalues condition is proposed and optimization parameters of power system stabilizer and variable impedance parameters include static VAR compensator (SVC) and thyristor controlled series capacitor (TCSC), (Including amplifying gain rate and time constant of phase-compensating blocks) is done using genetic algorithm in harmony. Also, in the process of optimization, the location of the FACTS devices and the control signal are considered as optimization parameters. Simulation results on IEEE 68-bus system show improvement damping of inter-area modes using the proposed method. Manuscript profile -
Open Access Article
662 - Multi-Stage Restoration of Electrical Distribution Networks
s. ghasemi A. Khodabakhshian R. HooshmandThe purpose of distribution networks restoration is to re-energize the out-of-service loads after fault occurrence which is accomplished by changing the status of network switches and considering the network constraints. In this paper a multi-stage restoration method b MoreThe purpose of distribution networks restoration is to re-energize the out-of-service loads after fault occurrence which is accomplished by changing the status of network switches and considering the network constraints. In this paper a multi-stage restoration method by the help of the modified decision-making tree algorithm is proposed to maximize the restored loads and also to minimize switching operations. The main stages of this method include initial restoration, reconfiguration and optimal load shedding. To reduce the search space, the network switches are categorized into different sets which avoid having any inappropriate result space. The proposed method is tested on two IEEE 69-bus and 119-bus distribution networks. The simulation results confirm the accuracy and efficiency of the proposed method in distribution network restoration. Manuscript profile -
Open Access Article
663 - Optimal Allocation of Battery Energy Storage in Distribution Network for Maximum Profitability
mohammad rasol jannesar mohsen kalantar A. R. SedighiIn this paper, the optimal allocation of battery energy storage in the distribution network is performed for peak shaving and maximizing profitability. To this end, indicator shave been introduced using hourly load information, feeder upgrade cost and electricity sales MoreIn this paper, the optimal allocation of battery energy storage in the distribution network is performed for peak shaving and maximizing profitability. To this end, indicator shave been introduced using hourly load information, feeder upgrade cost and electricity sales price to various tariffs. Then, using the Analytic Hierarchy Process (AHP), the indicators are weighted and a suitable feeder is indicated for installing energy storage. Then, to achieve the maximum possible peak shaving and maximize profit, an economic objective function is defined to determine the optimal sizing and charge-discharge of the energy storage. The objective function includes the investment and operating cost of battery energy storage and the profits of energy arbitrage, deferring facility investment, environmental issues, and reducing the upstream access cost. Appropriate constraints are considered according to the peak shaving, range of battery power and energy capacity as well as balance in the amount of charge and discharge. Due to the nonlinearity of the objective function, the components involved in the nonlinearity of the objective function are determined according to the heuristic algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Tabu Search (TS)) and then the objective function is solved by the Interior-point linear programming. The results provide the most suitable battery type and optimization method among the introduced batteries and methods while fulfilling the objectives. Manuscript profile -
Open Access Article
664 - Robust Optimal Control of Lateral Vehicle’s Dynamics with Adaptive Dynamic Programming Approach
Mohammad Reza Satouri Abolhassan Razminia Arash MarashianLateral vehicle’s control with constant longitudinal velocity using adaptive dynamic programming, backstepping and zero-sum games theory is investigated in this paper. The nonlinear dynamics is considered and the steering torque is chosen to be the control input instead MoreLateral vehicle’s control with constant longitudinal velocity using adaptive dynamic programming, backstepping and zero-sum games theory is investigated in this paper. The nonlinear dynamics is considered and the steering torque is chosen to be the control input instead of the steering angle. At first, a subsystem is created by augmenting the lateral vehicle’s dynamics with lane keeping ones considering the steering angle as the control input and the road curvature as a disturbance. Utilizing adaptive dynamic programming, neural networks and zero-sum games theory, the optimal control law is obtained and then, the results exerted on the second subsystem which is the dynamics of the steering angle and a control law is captured for which using the backstepping control method. Finally, performance of the proposed algorithm is demonstrated by applying it on a typical vehicle model. Manuscript profile -
Open Access Article
665 - State Estimation of Nonlinear Systems Using Gaussian-Sum Cubature Kalman Filter Based-on Spherical Simplex-Radial Rule
Mohammad Amin Ahmadpour Kahkak بهروز صفری نژادیانIn this paper, a new algorithm of Gaussian sum filters for state estimation of nonlinear systems is presented. The proposed method consists of several parallel Cubature Kalman filters each of which is implemented according to the simplex spherical-radial rule. In this m MoreIn this paper, a new algorithm of Gaussian sum filters for state estimation of nonlinear systems is presented. The proposed method consists of several parallel Cubature Kalman filters each of which is implemented according to the simplex spherical-radial rule. In this method, the probability density function is the sum of the weights of several Gaussian functions. The mean value, covariance, and weight coefficients of these Gaussian functions are calculated recursively over time, and each of the Cubature Kalman filters are responsible for updating one of these functions. Finally, the performance of the proposed filter is investigated using two nonlinear state estimation problems and the results are compared with conventional nonlinear filters. The simulation results show the appropriate accuracy of the proposed algorithm in state estimation of nonlinear systems. Manuscript profile -
Open Access Article
666 - An Adaptive Multi-Objective Clustering Algorithm based on Auction_Prediction for Mobile Target Tracking in Wireless Sensor Network
Roghieh Alinezhad Sepideh Adabi arash SharifiOne of the applications of sensor networks is to track moving target. In designing the algorithm for target tracking two issues are of importance: reduction of energy consumption and improvement of the tracking quality. One of the solutions for reduction of energy consu MoreOne of the applications of sensor networks is to track moving target. In designing the algorithm for target tracking two issues are of importance: reduction of energy consumption and improvement of the tracking quality. One of the solutions for reduction of energy consumption is to form a tracking cluster. Two major challenges in formation of the tracking cluster are when and how it should be formed. To decrease the number of messages which are exchanged to form the tracking cluster an auction mechanism is adopted. The sensor’s bid in an auction is dynamically and independently determined with the aim of establishing an appropriate tradeoff between network lifetime and the accuracy of tracking. Furthermore, since the tracking cluster should be formed and activated before the target arrives to the concerned region (especially in high speed of target), avoidance from delay in formation of the tracking cluster is another challenge. Not addressing the mentioned challenge results in increased target missing rate and consequently energy loss. To overcome this challenge, it is proposed to predict the target’s position in the next two steps by using neural network and then, simultaneously form the tracking clusters in the next one and two steps. The results obtained from simulation indicate that the proposed algorithm outperforms AASA (Auction-based Adaptive Sensor Activation). Manuscript profile -
Open Access Article
667 - Feature Selection and Cancer Classification Based on Microarray Data Using Multi-Objective Cuckoo Search Algorithm
kh. Kamari f. rashidi a. KhaliliMicroarray datasets have an important role in identification and classification of the cancer tissues. In cancer researches, having a few samples of microarrays in cancer researches is one of the most concerns which lead to some problems in designing the classifiers. Mo MoreMicroarray datasets have an important role in identification and classification of the cancer tissues. In cancer researches, having a few samples of microarrays in cancer researches is one of the most concerns which lead to some problems in designing the classifiers. Moreover, due to the large number of features in microarrays, feature selection and classification are even more challenging for such datasets. Not all of these numerous features contribute to the classification task, and some even impede performance. Hence, appropriate gene selection method can significantly improve the performance of cancer classification. In this paper, a modified multi-objective cuckoo search algorithm is used to feature selection and sample selection to find the best available solutions. For accelerating the optimization process and preventing local optimum trapping, new heuristic approaches are included to the original algorithm. The proposed algorithm is applied on six cancer datasets and its results are compared with other existing methods. The results show that the proposed method has higher accuracy and validity in comparison to other existing approaches and is able to select the small subset of informative genes in order to increase the classification accuracy. Manuscript profile -
Open Access Article
668 - Improving the Architecture of Convolutional Neural Network for Classification of Images Corrupted by Impulse Noise
Mohammad Momeny M. Agha Sarram A. M. Latif R. SheikhpourImpulse noise is one the common noises which reduces the performance of convolutional neural networks (CNNs) in image classification. Preprocessing for removal of impulse noise is a costly process which may have a destructive effect on the training and validation of the MoreImpulse noise is one the common noises which reduces the performance of convolutional neural networks (CNNs) in image classification. Preprocessing for removal of impulse noise is a costly process which may have a destructive effect on the training and validation of the convolutional neural networks due to insufficient improvement of noisy images. In this paper, a convolutional neural network is proposed which is robust to impulse noise. Proposed CNN classify images corrupted by impulse noise without any preprocessing for noise removal. A noise detection layer is placed at the beginning of the proposed CNN to prevent the processing of noisy values. The ILSVRC-2012 database is used to train the proposed CNN. Experimental results show that preventing the impact of impulse noise on the training process and classification of CNN can increase the accuracy and speed of the network training. The proposed CNN with error of 0.24 is better than other methods in classification of noisy image corrupted by impulse noise with 10% density. The time complexity of O(1) in the proposed CNN for robustness to noise indicates the superiority of the proposed CNN. Manuscript profile -
Open Access Article
669 - Using Evolutionary Clustering for Topic Detection in Microblogging Considering Social Network Information
E. Alavi H. Mashayekhi H. Hassanpour B. Rahimpour KamiShort texts of social media like Twitter provide a lot of information about hot topics and public opinions. For better understanding of such information, topic detection and tracking is essential. In many of the available studies in this field, the number of topics must MoreShort texts of social media like Twitter provide a lot of information about hot topics and public opinions. For better understanding of such information, topic detection and tracking is essential. In many of the available studies in this field, the number of topics must be specified beforehand and cannot be changed during time. From this perspective, these methods are not suitable for increasing and dynamic data. In addition, non-parametric topic evolution models lack appropriate performance on short texts due to the lack of sufficient data. In this paper, we present a new evolutionary clustering algorithm, which is implicitly inspired by the distance-dependent Chinese Restaurant Process (dd-CRP). In the proposed method, to solve the data sparsity problem, social networking information along with textual similarity has been used to improve the similarity evaluation between the tweets. In addition, in the proposed method, unlike most methods in this field, the number of clusters is calculated automatically. In fact, in this method, the tweets are connected with a probability proportional to their similarity, and a collection of these connections constitutes a topic. To speed up the implementation of the algorithm, we use a cluster-based summarization method. The method is evaluated on a real data set collected over two and a half months from the Twitter social network. Evaluation is performed by clustering the texts and comparing the clusters. The results of the evaluations show that the proposed method has a better coherence compared to other methods, and can be effectively used for topic detection from social media short texts. Manuscript profile -
Open Access Article
670 - Bug Detection and Assignment for Mobile Apps via Mining Users' Reviews
Maryam Younesi Abbas Heydarnoori F. GhanadiIncreasing the popularity of smart phones and the great ovation of users of mobile apps has turned the app stores to massive software repositories. Therefore, using these repositories can be useful for improving the quality of the program. Since the bridge between users MoreIncreasing the popularity of smart phones and the great ovation of users of mobile apps has turned the app stores to massive software repositories. Therefore, using these repositories can be useful for improving the quality of the program. Since the bridge between users and developers of mobile apps is the comments that users write in app stores, special attention to these comments from developers can make a dramatic improvement in the final quality of mobile apps. Hence, in recent years, numerous studies have been conducted around the topic of opinion mining, whose intention was to extract and exert important information from user's reviews. One of the shortcomings of these studies is the inability to use the information contained in user comments to expedite and improve the process of fixing the software error. Hence, this paper provides an approach based on users’ feedback for assigning program bugs to developers. This approach builds on the history of a program using its commit data, as well as developers' ability in fixing a program’s errors using the bugs that developers have already resolved in the app. Then, by combining these two criteria, each developer will get a score for her appropriation for considering each review. Next, a list of developers who are appropriate for each bug are provided. The evaluations show that the proposed method would be able to identify the right developer to address the comments with a precision of 74%. Manuscript profile -
Open Access Article
671 - Optimal Resource Allocation in Multi-Task Software-Defined Sensor Networks
S. A. Mostafavi M. Agha Sarram T. SalimianUnlike conventional wireless sensor networks which are designed for a specific application, Software-Defined Wireless Sensor Networks (SDSN) can embed multiple sensors on each node, defining multiple tasks simultaneously. Each sensor node has a virtualization program wh MoreUnlike conventional wireless sensor networks which are designed for a specific application, Software-Defined Wireless Sensor Networks (SDSN) can embed multiple sensors on each node, defining multiple tasks simultaneously. Each sensor node has a virtualization program which serves as a common communication infrastructure for several different applications. Different sensor applications in the network can have different target functions and decision parameters. Due to the resource constraints of sensor network nodes, the multiplicity and variety of tasks in each application, requirements for different levels of quality of service, and the different target functions for different applications, the problem of allocating resources to the tasks on the sensors is complicated. In this paper, we formulate the problem of allocating resources to the sensors in the SDSN with different objective functions as a multi-objective optimization problem and provide an effective solution to solve it. Manuscript profile -
Open Access Article
672 - DRSS-Based Localization Using Convex Optimization in Wireless Sensor Networks
Hassan Nazari M. R. Danaee M. SepahvandLocalization with differential received signal strength measurement in recent years has been very much considered. Due to the fact that the probability density function is known for given observations, the maximum likelihood estimator is used. This estimator can be asym MoreLocalization with differential received signal strength measurement in recent years has been very much considered. Due to the fact that the probability density function is known for given observations, the maximum likelihood estimator is used. This estimator can be asymptotically represented the optimal estimation of the location. After the formation of this estimator, it is observed that the corresponding cost function is highly nonlinear and non-convex and has a lot of minima, so there is no possibility of achieving the global minimum with Newton method and the localization error will be high. There is no analytical solution for this cost function. To overcome this problem, two methods are existed. First, the cost function is approximated by a linear estimator. But this estimator has poor accuracy. The second method is to replace the non-convex cost function with a convex one with the aid of convex optimization methods, in which case the global minimum is obtained. In this paper, we proposed new convex estimator to solve cost function of maximum likelihood estimator. The results of the simulations show that the proposed estimator has up to 20 percent performance improvement compared with existing estimators, moreover, the execution time of proposed estimator is 30 percent faster than other convex estimators. Manuscript profile -
Open Access Article
673 - The Extraction of Fetal ECG from Abdominal Recordings Using Sparse Representation of ECG Signals
Parya Tavoosi قاسم عازمی پگاه زرجامone of the most prevalent causes for mortality of infants is cardiac failure. Recordings of heart electrical activities by Electrocardiogram (ECG) are a safe method to detect abnormal arrhythmia in time and reduce cardiac failure in newborns. However, the non-invasive e Moreone of the most prevalent causes for mortality of infants is cardiac failure. Recordings of heart electrical activities by Electrocardiogram (ECG) are a safe method to detect abnormal arrhythmia in time and reduce cardiac failure in newborns. However, the non-invasive extraction of fetal ECG (fECG) from the maternal abdominal is quite challenging, since the fECG signals are often corrupted by some electrical noises from other sources such as: maternal heart activity, uterine contractions, and respiration, in addition to instrumental noises. Among such signals, the maternal heart signal (due to high amplitude) has the most disruptive effect and the fetal brain signal (due to low amplitude) has the least effect on distortion of the fetal heart signal. In this paper, a new method for extracting fECG signals from multichannel abdominal recordings is proposed. The proposed method uses Compressive Sensing (CS)to reduce the computational complexity and fast Independent Component Analysis (fICA) algorithm to estimate the sources. Also, for finding sparse representations of the acquired ECG signals, two dictionaries namely: discrete cosine transformation and discrete wavelet transform are deployed here. The proposed method is then implemented and its performance is tested using the well-known and publicly available database used in 2013 Physionet Challenge. The performance results are compared with that of the best performing existing methods. The results show that the proposed method based on CS and ICA outperforms the existing detection methods with a Mean Minimum Square Error (MMSE) of 171.65, and therefore can be used for non-invasive and reliable extraction fECG from abdominal recordings. Manuscript profile -
Open Access Article
674 - Write Error Rate Reduction Based on Thermal Effect and Dual-Vdd
حمیدرضا زرندی Sh. JalilianWrite Error (WER) is one of the most drawbacks of STT-MRAM based memories. This problem usually occurred because of thermal instability and process variation. Although some methods have been proposed for WER reduction, they often did not consider the thermal effect of M MoreWrite Error (WER) is one of the most drawbacks of STT-MRAM based memories. This problem usually occurred because of thermal instability and process variation. Although some methods have been proposed for WER reduction, they often did not consider the thermal effect of MTJ and had significant overhead. Therefore, proposing a new method in a lower layer of abstraction with the minimum penalty is essential. In this regard, a write driver core has been proposed, which uses two distinct ways according to the state of writing data based on the thermal feature of MTJ cell and by Dual-Vdd method. Simulation results show 11.38% write latency reduction without area and power penalty. Manuscript profile -
Open Access Article
675 - Computing Colored Average Degree of Graphs in Sublinear Time
Mohammad Ali Abam محمدرضا بهرامیGraphs are common data structures which widely used for information storage and retrieval. Occasionally some vertices of a graph contain specific features or information, which we value in their effect. We consider modeling this effect formally, and we devise two super- MoreGraphs are common data structures which widely used for information storage and retrieval. Occasionally some vertices of a graph contain specific features or information, which we value in their effect. We consider modeling this effect formally, and we devise two super-fast algorithms to approximate the colored average degree. In the first method, we assume the information of each vertex is available; hence, the provided algorithm works with a 2+ϵ approximation factor. Eventually, we waive this assumption and find another algorithm with the same approximation factor, which computes the answer in the sublinear expected time. Manuscript profile -
Open Access Article
676 - Improving On-Off Current Ratio (Ion/Ioff) in Schottky-Barrier-Type Graphene Nanoribbon FETs
Morteza GholipourSchottky-barrier-type graphene nanoribbon transistors (SB-GNRFET), despite their prominent characteristics compared to conventional transistors, have a relatively high off-current and a low Ion/Ioff ratio. In this paper, a new structure of SB-GNRFET is presented in whic MoreSchottky-barrier-type graphene nanoribbon transistors (SB-GNRFET), despite their prominent characteristics compared to conventional transistors, have a relatively high off-current and a low Ion/Ioff ratio. In this paper, a new structure of SB-GNRFET is presented in which the gate of the transistor is divided into two parts. A constant voltage is connected to the gate located on the drain side, and the gate located on the source side is the main gate of the transistor. The proposed SB-GNRFET is simulated using non-equilibrium Green functions-based numerical simulator under different geometric and physical characteristics and in biases. The simulation results show Ion/Ioff ratio improvement of up to 6.7-fold at VDS = 0.8 V. At this voltage the ratio has increased from 1.2 in the normal SB-GNRFET transistor to 8.01 in the new transistor and the off current has been reduced from 5 µA to 0.7 µA. Also at VDS = 0.6 V, as the supply voltage, the Ion/Ioff ratio increased from 3.97 to 15.8 and the off current decreased from 0.63 µA to 0.16 µA. Manuscript profile -
Open Access Article
677 - Comprehensive Optimal Management System of Distributed Resources Using Dynamic Neural Network in Modeling of Electricity Consumption Uncertainty for Grid-Connected Microgrids
Mohammad Veysi محمدرضا سلطانپور jafar Khalilpour hadi niaeiIn this paper, to enhance the optimal planning for power management of micrigrids, a strategy is proposed using power sharing through coordination between microgrids and the neighborhood system, which has no additional costs for generating units. The uncertainty values MoreIn this paper, to enhance the optimal planning for power management of micrigrids, a strategy is proposed using power sharing through coordination between microgrids and the neighborhood system, which has no additional costs for generating units. The uncertainty values of electrical consumers are modeled by dynamic neural network, considering the implementation process and high accuracy of forecasting. In another view, to supply the electrical energy of microgrid, diesel generator, renewable energies such as solar energy and wind energy and so, battery energy storage are used, in addition to the upstream grid connection. As well as, using of the reliability factors, along with a detailed assessment of current costs will improve the performance of microgrid. Hence, the loss of power supply probability (LPSP) and loss of load expectations (LOLE) are expressed as factors for assessing the accuracy of current costs. The proposed model is implemented in GAMS and MATLAB environment and the simulation results clearly demonstrate the desired performance of the proposed algorithm, and leads to gaining revenue for the under-study system. Manuscript profile -
Open Access Article
678 - H∞ Robust Stability Augmentation System Design by Genetic Optimal Coefficient for HUAV MIMO Model with Coupled Dynamics
zahra salamati zahra nejati alireza farajiNowadays, Unmanned helicopters are used widely in many applications because they have high maneuverability and can take off and landing in many areas, and its stability has special importance. Without stability augmentation system (SAS), the helicopter is not maneuverab MoreNowadays, Unmanned helicopters are used widely in many applications because they have high maneuverability and can take off and landing in many areas, and its stability has special importance. Without stability augmentation system (SAS), the helicopter is not maneuverable. Stability augmentation system or SAS design for helicopter decreases disturbances effects and improve performance. In this paper a robust SAS is designed for nonlinear dynamic model of ANCL helicopter in hover mode, this model is unstable, multivariable, under-actuated with coupling between dynamics Due to specific characteristics for liner model of the system in this paper, some filters are designed for input signals of actuators for decoupling of system dynamics in closed loop system, so these loops will become decoupled. PI controller is conventional to design of SAS in small helicopters, so PI coefficients are designed robustly for each decoupled control loop and this is designed by H_∞ Robust problem and optimized by genetic algorithm. Finally, obtained controllers are simulated for nonlinear model helicopter in hover mode that results show robustness against of nonlinear model uncertainty and disturbances. Manuscript profile -
Open Access Article
679 - Robust Persian Isolated Digit Recognition Based on LSTM and Speech Spectral Features
شیما طبیبیانOne of the challenges of isolated Persian digit recognition is similar pronunciation of some digits such as "zero and three", "nine and two" and "five, seven and eight". This challenge leads to the high substitution errors and reduces the recognition accuracy. In this p MoreOne of the challenges of isolated Persian digit recognition is similar pronunciation of some digits such as "zero and three", "nine and two" and "five, seven and eight". This challenge leads to the high substitution errors and reduces the recognition accuracy. In this paper, a combined solution based on short-term memory (LSTM) and hidden Markov model (HMM) is proposed to solve the mentioned challenge. The proposed approach increases the recognition rate of Persian digits on average 2 percent and in the best case 8 percent in comparison to the HMM-based approach. In the following of this work, due to the intensification of the mentioned challenge in noisy conditions, the robust recognition of Persian digits with similar pronunciation was considered. In order to increase the robustness of the LSTM-based recognizer, robust features extracted from the speech spectrum such as spectral entropy, burst degree, bisector frequency, spectral flatness, first formant and autocorrelation-based zero crossing rate were used. Using these features, while reducing the number of features for recognizing similar Persian digits from 39 coefficients to a maximum of 4 and a minimum of 1 coefficient, on average improved the robustness of the isolated digit recognizer in different noisy conditions (30 different situations resulting from five noise types of white, pink, babble, factory and car noises and six signal-to-noise ratios of -5, 0, 5, 10, 15 and 20 decibels) by 10%, 13%, 15% and 13% compared to the HMM-based, LSTM-based, deep belief network-based recognizers with Mel-Cepstrum coefficients and a convolutional neural network-recognizer with Mel Spectrogram features. Manuscript profile -
Open Access Article
680 - Green Cloud Computing with Reduced Energy Consumption in Live Migration Prioritizing Services
Mohammad Rostami Salman GoliToday, the rapid growth in cloud computing resources usage has increased energy consumption in data centers. Green cloud computing goal is to decrease the energy consumption of data centers. In the meantime, service aggregation is a good method to reduce energy consumpt MoreToday, the rapid growth in cloud computing resources usage has increased energy consumption in data centers. Green cloud computing goal is to decrease the energy consumption of data centers. In the meantime, service aggregation is a good method to reduce energy consumption in these systems. Existing aggregation methods with unnecessary migration, the unbalanced workload of hosts, and ignoring the relationship between services may reduce the quality of service and increase energy consumption. Therefore, in this study, by migrating the necessary services based on priority (including the number of children, the level and communication cost of each service), from hosts with the unbalanced workload to hosts that contain partner services, the productivity of available resources is improved and the energy consumption is decreased. Live services migration based on prioritizing and minimizing the number of migrations can also lead to response time decrease and system efficiency increase. The proposed method can lead to an 11.79% decrease in energy consumption, a 12.15% reduction in the number of service migrations, and a 1.55% increase in the number of hosts that have been shut down. Manuscript profile -
Open Access Article
681 - Sliding Mode Control Applied in Two-wheeled Self-Balancing Robot System in Presence of Structured and Un- Structured Uncertainties in Dynamical Equations and Without the Need for Kinematic Equations
M. R. Soltanpour R. GholamiIn this paper, we proposed solutions for controlling the two-wheel self-balancing robot system in the presence of uncertainties in dynamical equation and without the need for kinematic equations. For this purpose, the dynamical equations of this system are initially tra MoreIn this paper, we proposed solutions for controlling the two-wheel self-balancing robot system in the presence of uncertainties in dynamical equation and without the need for kinematic equations. For this purpose, the dynamical equations of this system are initially transmitted to the domain of error, then these equations are divided into two independent subsystems, one of which is an under-actuated system and the other is fully actuated system. In order to control the under-actuated subsystem, two completely different sliding mode controllers are proposed that are able to provide this subsystem in the presence of structured and un-structured uncertainties with global asymptotic stability. Subsequently, in order to control the fully under-actuated subsystem, a sliding mode control is proposed to provide this subsystem in the presence of existing uncertainties with global asymptotic stability. Since these two subsystems are completely independent of each other, their global asymptotic stability proofs prove the global asymptotic stability of the closed-loop system. The separation of two-wheeled self-balancing robot sub-systems eliminates the need to use the kinematic equations, and this causes the presence of structured uncertainties to have no effect on the accuracy of tracing the closed-loop system state variables. Finally, to evaluate the performance of the proposed controllers and compare their performance results, three-stage simulations are implemented on the two-wheeled self-balancing robot system. Mathematical proofs and simulation results show the desired performance of the proposed solutions. Manuscript profile -
Open Access Article
682 - An Intelligent Approach for OFDM Channel Estimation Using Gravitational Search Algorithm
F. Salehi mohammad hassan majidi N. NedaThe abundant benefits of Orthogonal Frequency-Division Multiplexing (OFDM) and its high flexibility have resulted in its widespread applications in many telecommunication standards. One important parameter for improving wireless system’s efficiency is the accurate estim MoreThe abundant benefits of Orthogonal Frequency-Division Multiplexing (OFDM) and its high flexibility have resulted in its widespread applications in many telecommunication standards. One important parameter for improving wireless system’s efficiency is the accurate estimation of channel state information (CSI). In the literatures many techniques have been studied in order to estimate the CSI. Nowadays, the techniques based on intelligent algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO) have attracted attention of researchers. With a very low pilot overhead, these techniques are able to estimate the channel frequency response (CFR) properly only using the received signals. Unfortunately each of these techniques suffers a common weakness: they have a slow convergence rate. In this paper, a new intelligent and different method has been presented for channel estimation using gravitational search algorithm (GSA). This method can achieve accurate channel estimation with a moderate computational complexity in comparison with GA and PSO estimators. Furthermore, with higher convergence rate our proposed method is capable of providing the same performance as GA and PSO. For a two-path fast fading channel, simulation results demonstrate the robustness of our proposed scheme according to the bit error rate (BER) and the mean square error (MSE). Manuscript profile -
Open Access Article
683 - Proposing a Robust Method Against Adversarial Attacks Using Scalable Gaussian Process and Voting
Mehran Safayani Pooyan Shalbafan Seyed Hashem Ahmadi Mahdieh Falah aliabadi Abdolreza MirzaeiIn recent years, the issue of vulnerability of machine learning-based models has been raised, which shows that learning models do not have high robustness in the face of vulnerabilities. One of the most well-known defects, or in other words attacks, is the injection of MoreIn recent years, the issue of vulnerability of machine learning-based models has been raised, which shows that learning models do not have high robustness in the face of vulnerabilities. One of the most well-known defects, or in other words attacks, is the injection of adversarial examples into the model, in which case, neural networks, especially deep neural networks, are the most vulnerable. Adversarial examples are generated by adding a little purposeful noise to the original examples so that from the human user's point of view there is no noticeable change in the data, but machine learning models make mistakes in categorizing the data. One of the most successful methods for modeling data uncertainty is Gaussian processes, which have not received much attention in the field of adversarial examples. One reason for this could be the high computational volume of these methods, which limits their used in the real issues. In this paper, a scalable Gaussian process model based on random features has been used. This model, in addition to having the capabilities of Gaussian processes for proper modeling of data uncertainty, is also a desirable model in terms of computational cost. A voting-based process is then presented to deal with adversarial examples. Also, a method called automatic relevant determination is proposed to weight the important points of the images and apply them to the kernel function of the Gaussian process. In the results section, it is shown that the proposed model has a very good performance against fast gradient sign attack compared to competing methods. Manuscript profile -
Open Access Article
684 - A New High Speed Easily Expandable Digital Multiplication Algorithm without Pipeline
ebrahim hosseini Morteza MousazadehThis paper proposes a new high speed low power algorithm for unsigned digital multiplier without pipeline which could be easily expanded to a wider number of bits. The blocks of multiplier works in parallel which significantly increase the speed of multiplier. In propos MoreThis paper proposes a new high speed low power algorithm for unsigned digital multiplier without pipeline which could be easily expanded to a wider number of bits. The blocks of multiplier works in parallel which significantly increase the speed of multiplier. In proposed algorithm, the input bits of multiplier, are divided into smaller groups of bits which multiplication of these groups are in parallel and simultaneously. This division continues until the minimum number of input bits which is 2×2. In calculating the product of each category, the proposed algorithm is used, which leads to acceleration of the product of each category.The final result will be obtained from the sum of these smaller categories.Modified tree adder have been used to add smaller groups, which can increase the multiplication speed. Multipliers with input bit lengths of 64, 32, 16, 8, 4, and 2 have been implemented using the proposed algorithm in 180 nm and 90 nm technology, which its delay and power consumption with bit length of 32 in 180 nm are 3.05 ns and 40 mW respectively. In 90 nm technology and with the 32 bit length the delay is 1.53 nm and power consumption is 9.7 mW. Also, using the proposed method, it is estimated that the delay of 128×128 bits multiplier in the 180 nm and 90 nm technology are equal to 5.4ns and 2.5ns, respectively. According to the results and in comparison with other works reported in the articles and in the same process, without increasing the power consumption and with a silicon area of 1.5 times, the proposed multiplication speed has increased more than 2 times. Manuscript profile -
Open Access Article
685 - A Transfer Learning Algorithm to Improve the Convergence Rate and Accuracy in Cellular Learning Automata
Seyyed Amir Hadi Minoofam Azam Bastanfard M. R. KeyvanpourCellular learning automaton is an intelligent model as a composition of cellular automaton and learning automaton. In this study, an extended algorithm of cellular learning automata is proposed based on transfer learning as the TL-CLA algorithm. In this algorithm, trans MoreCellular learning automaton is an intelligent model as a composition of cellular automaton and learning automaton. In this study, an extended algorithm of cellular learning automata is proposed based on transfer learning as the TL-CLA algorithm. In this algorithm, transfer learning is used as an approach for computation deduction and minimizing the learning cycle. The proposed algorithm is an extended model based on merit function and attitude vector for transfer learning. In the TL-CLA algorithm, the value of the merit function is computed based on the local environment, and the value of the attitude vector is calculated based on the global environment. When these two measures get the threshold values, the transfer of action probabilities causes the transfer learning from the source CLA to the destination CLA. The experimental results show that the proposed TL-CLA model leads to increment the convergence accuracy as 2.7% and 2.2% in two actions and multi-action standard environments, respectively. The improvements in convergence rate are also 8% and 2% in these two environments. The TL-CLA could be applied in knowledge transfer from learning one task to learning another similar task Manuscript profile -
Open Access Article
686 - New Structure of Wind-PV Farm with Improved Performance under Voltage and Frequency Fault Conditions
Mehrdad Tarafdar Hagh Farshid Najaty MazgarIn this paper a new structure for wind – PV farm is proposed. The PV arrays and DC loads are capable to connect to the proposed structure. In the proposed structure each DFIG wind turbine is connected to the AC grid through its stator windings and has a connection to a MoreIn this paper a new structure for wind – PV farm is proposed. The PV arrays and DC loads are capable to connect to the proposed structure. In the proposed structure each DFIG wind turbine is connected to the AC grid through its stator windings and has a connection to a common DC link via its rotor side converters. The proposed structure uses a high power grid side converter and an energy storage system for entire wind – PV farm. The converter power loss decrease and lifetime increase of power switches are some advantages of the proposed structure under normal operation conditions. The proposed structure with the coordinated power control of DFIG wind turbines, the ESS and PV arrays improves the low voltage ride-through capability under-voltage fault conditions and enhances the frequency response of the wind farm under frequency faults. The proposed structure is simulated in MATLAB/ Simulink software and the results are presented. Furthermore, an experimental setup is provided to test the operation of the proposed structure. Manuscript profile -
Open Access Article
687 - Propose a Proper Algorithm for Incremental Learning Based on Fuzzy Least Square Twin Support Vector Machines
Javad Salimi Sartakhti Salman GoliSupport Vector machine is one of the most popular and efficient algorithms in machine learning. There are several versions of this algorithm, the latest of which is the fuzzy least squares twin support vector machines. On the other hand, in many machine learning applica MoreSupport Vector machine is one of the most popular and efficient algorithms in machine learning. There are several versions of this algorithm, the latest of which is the fuzzy least squares twin support vector machines. On the other hand, in many machine learning applications input data is continuously generated, which has made many traditional algorithms inefficient to deal with them. In this paper, for the first time, an incremental version of the fuzzy least squares twin support vector algorithm is presented. The proposed algorithmis represented in both online and quasi-online modes. To evaluate the accuracy and precision of the proposed algorithmfirst we run our algorithm on 6 datasets of the UCI repository. Results showthe proposed algorithm is more efficient than other algorithms (even non-incremental versions). In the second phase in the experiments, we consider an application of Internet of Things, and in particular in data related to daily activities which inherently are incremental. According to experimental results, the proposed algorithm has the best performance compared to other incremental algorithms. Manuscript profile -
Open Access Article
688 - Improving Energy Consumption in Wireless Sensor Networks Using Shuffled Frog Leaping Algorithm and Fuzzy Logic
Shayesteh TabatabaeyWireless sensor networks consist of thousands of sensor nodes with limited energy. Energy efficiency is a fundamental challenge issue for wireless sensor networks. Clustering sensor nodes in separate categories and exchanging information through clusters is one of the w MoreWireless sensor networks consist of thousands of sensor nodes with limited energy. Energy efficiency is a fundamental challenge issue for wireless sensor networks. Clustering sensor nodes in separate categories and exchanging information through clusters is one of the ways to improve energy consumption. This paper presents a new cluster-based routing protocol called SFLCFBA. The proposed protocol biologically uses fast and effective search features inspired by the Shuffled Frog Leaping algorithm, which acts based on the Frog food behavior to cluster sensor nodes. The proposed protocol also uses fuzzy logic to calculate the node fitness, based on the two criteria of distance to the sink and the remaining energy of the sensor node or power of battery level. IEEE 802.15.4 Protocol and NODIC Protocol with the proposed methodology and OPNET Simulator were simulation and the results in terms of energy consumption, end to end delay, signal to noise ratio, the success property data and throughput were compared with each other. The results of the simulation showed that the proposed method outperforms the IEEE 802.15.4 Protocol and NODIC Protocol due to the use of the criteria listed. Manuscript profile -
Open Access Article
689 - A Dynamic Sequential Approach Using Deep Learning to Improve the Performance of Biometrics Match on Card Systems
Mohammad Sabri Mohammad Moin Farbod RazzaziNowadays, the threats such as terrorism and cybercrime are extremely increased, therefore, the identity authentication process is very substantial for the national security of a country. In this paper, we propose a novel multimodal authentication system with sequential MoreNowadays, the threats such as terrorism and cybercrime are extremely increased, therefore, the identity authentication process is very substantial for the national security of a country. In this paper, we propose a novel multimodal authentication system with sequential structure based on deep learning. In the proposed method, feature vectors are extracted automatically through deep network with an end to end architecture. A multi biometric system using two fingerprint and a face is implemented and evaluated. The results demonstrate that, the authentication is done by fingerprints in 91.42% cases and only for 8.58% cases the face modal is required. In addition, the proposed method is more accurate than first and second fingerprint by 35% and 30% at FMR=0.001, respectively. As a result, we augmented the accuracy of the system and at the same time reduced the acquisition and matching time. This conducts to the improvement of user convenience and security of the service provider, simultaneously. The achievements of this work can be used to increase the effectiveness of authentication process and can play an important role in the acceptability of real world applications. Manuscript profile -
Open Access Article
690 - Convolutional Neural Networks for Sentiment Analysis in Persian Social Media
M. Rohanian M. Salehi A. Darzi وحید رنجبرWith the social media engagement on the rise, the resulting data can be used as a rich resource for analyzing and understanding different phenomena around us. A sentiment analysis system employs these data to find the attitude of social media users towards certain entit MoreWith the social media engagement on the rise, the resulting data can be used as a rich resource for analyzing and understanding different phenomena around us. A sentiment analysis system employs these data to find the attitude of social media users towards certain entities in a given document. In this paper we propose a sentiment analysis method for Persian text using Convolutional Neural Network (CNN), a feedforward Artificial Neural Network, that categorize sentences into two and five classes (considering their intensity) by applying a layer of convolution over input data through different filters. We evaluated the method on three different datasets of Persian social media texts using Area under Curve metric. The final results show the advantage of using CNN over earlier attempts at developing traditional machine learning methods for Persian texts sentiment classification especially for short texts. Manuscript profile -
Open Access Article
691 - Energy Efficiency in Secrecy Multi-Antenna Two-Way Relay Networks
F. B. soroush akhlaghipaper investigates the energy-efficiency in secrecy two-way relay networks. It is assumed that in the presence of several multi-antenna amplify-and-forward relays and a single eavesdropper, two single-antenna users exchange their confidential messages during two hops. I Morepaper investigates the energy-efficiency in secrecy two-way relay networks. It is assumed that in the presence of several multi-antenna amplify-and-forward relays and a single eavesdropper, two single-antenna users exchange their confidential messages during two hops. In the first hop, both users send their messages to the relay nodes and during the second hop, the relays send the received signal to the users by using the beamforming matrix, to minimize the received information by the eavesdropper .In this way, using two beamforming strategies, named as Null-Space Beamforming (NSBF) and Information Leakage Alignment Beamforming (ILABF), the secrecy energy efficiency that is the ratio of total secrecy sum-rate to the total power consumption of the network is calculated. It is shown that the aforementioned problem is non-convex so it will be converted to the convex form, using the Semi-Definite Relaxation (SDR). This problem has not closed-form and is solved using the interior point method.In numerical results, it is observed that by using the information leakage alignment beamforming (ILABF) method, energy efficiency is allocated more value than the null-space beamforming (NSBF) approach that was used in previous studies. Manuscript profile -
Open Access Article
692 - An Efficient Approach for Resource Allocation in Fog Computing Considering Request Congestion Conditions
Samira Ansari Moghaddam سميرا نوفرستي مهري رجاييCloud data centers often fail to cope with the millions of delay-sensitive storage and computational requests due to their long distance from end users. A delay-sensitive request requires a response before its predefined deadline expires, even when the network has a hig MoreCloud data centers often fail to cope with the millions of delay-sensitive storage and computational requests due to their long distance from end users. A delay-sensitive request requires a response before its predefined deadline expires, even when the network has a high load of requests. Fog computing architecture, which provides computation, storage and communication services at the edge of the network, has been proposed to solve these problems. One of the fog computing challenges is how to allocate cloud and fog nodes resources to user requests in congestion conditions to achieve a higher acceptance rate of user requests and minimize their response time. Fog nodes have limited storage and computational power, and hence their performance is significantly reduced due to high load of user requests. This paper proposes an efficient resource allocation method in fog computing that decides where (fog or cloud) to process the requests considering the available resources of fog nodes and congestion conditions. According to the experimental results, the performance of the proposed method is better compared with existing methods in terms of average response time and percentage of failed requests. Manuscript profile -
Open Access Article
693 - Proposing a Novel Write Circuit to Reduce Energy and Delay of Writing Operations in STT-MRAM Memories Using the Temperature Method
امیرمحمد حاجی صادقی حمیدرضا زرندی Sh. JalilianWith the advancement of technology and the shrinking dimensions of transistors in CMOS technology, several challenges have arisen. One of the main concerns in using CMOS-based memory is the high power consumption of this type of memory. Therefore, new and non-volatile m MoreWith the advancement of technology and the shrinking dimensions of transistors in CMOS technology, several challenges have arisen. One of the main concerns in using CMOS-based memory is the high power consumption of this type of memory. Therefore, new and non-volatile memories were introduced to address the shortcomings of conventional volatile memory. One of the emerging non-volatile technologies is STT-MRAM memory, an effective and efficient alternative to conventional memory such as SRAMs due to low leakage power, high density, and short access time. The positive features of STT-MRAMs make it possible to use them at different memory hierarchy levels, especially the cache level. However, STT-MRAMs suffer from high write energy. In this paper, we present a new write circuit using the temperature method; in addition to improving the high write energy, write delay is also improved. The proposed circuit lead to 22.5% and 18.62% improvement in energy and writing delay, respectively, compared to the existing methods. Manuscript profile -
Open Access Article
694 - Resource Management in Multimedia Networks Using Software-Defined Network Technology
Ahmadreza MontazerolghaemNowadays, multimedia networks on the Internet have become a low-cost and efficient alternative to PSTN. Multimedia transfer applications on the Internet are becoming more and more popular. This connection consists of two phases: signaling and media. The signaling phase MoreNowadays, multimedia networks on the Internet have become a low-cost and efficient alternative to PSTN. Multimedia transfer applications on the Internet are becoming more and more popular. This connection consists of two phases: signaling and media. The signaling phase is performed by SIP proxies and the media phase by network switches. One of the most important challenges in multimedia networks is the overload of SIP proxies and network switches in the signaling and media phases. The existence of this challenge causes a wide range of network users to face a sharp decline in the quality of service. In this article, we model the routing problem in multimedia networks to deal with the overload. In this regard, we present a technology-based method of software-based networks and a mathematical programming model in multimedia networks. The proposed method is simulated under various scenarios and topologies. The results investigate that the throughput and resource consumption has improved. Manuscript profile -
Open Access Article
695 - A New Method for Performance Evaluation of Wind Turbines and Wind Farms Using Extended Capacity Factor – Case Study of Manjil Wind Farm
Hamed Delkhosh Mostafa ParnianiNowadays, with the increasing share of wind power in electrical energy sector, performance evaluation indices are of great importance. Such indices can lead to optimal utilization of invested capital and effective development of existing wind farms. Despite having some MoreNowadays, with the increasing share of wind power in electrical energy sector, performance evaluation indices are of great importance. Such indices can lead to optimal utilization of invested capital and effective development of existing wind farms. Despite having some of the required characteristics, the capacity factor based on traditional definition has some limitation. This study aims to extend the concept of capacity factor and presents a comprehensive formulation in order to calculate this index using measured and simulated data for one turbine, all turbines connected to a feeder or a busbar, and all turbines of a wind farm. This formulation also provides a framework for calculating the capacity factor in various time periods (annual, seasonal, monthly, etc.) and different time slots (all hours, special hours, hourly, etc.). As a case study, performance of the installed wind turbines in Manjil wind farm is investigated over an operation period using both measured and simulated data. Performance evaluation of the farm is also carried out with a newer variable speed type. Moreover, capacity factors of the feeders, busbars, and the entire farm are calculated using the turbines simulated data as well as measured data of the feeders over an operation period, and various results of exploring the obtained capacity factors are presented. Numerical results demonstrate the effectiveness of newly presented method for the performance evaluation of wind turbines and wind farms based on extended concept of capacity factor. Manuscript profile -
Open Access Article
696 - A Hybrid Long-Term Probabilistic Net Load Forecasting Approach Considering Renewable Energies Power in Smart Grids
Mohsen Jahantigh majid moazzamiWith the growth and integration of distributed generation resources in smart grids, net load forecasting is of significant importance. A hybrid optimization method is proposed in this paper for probabilistic net load forecasting using neighborhood component analysis and MoreWith the growth and integration of distributed generation resources in smart grids, net load forecasting is of significant importance. A hybrid optimization method is proposed in this paper for probabilistic net load forecasting using neighborhood component analysis and solving regression problem with the aid of mini-batch LBFGS method. Net load forecasting is suggested in this paper trough forecast combination via adaptive network-based fuzzy inference system. The structure includes a combination of several long-term forecasts, including forecasts of load, the generation of a solar station, and the generation of a wind farm with wind turbines equipped with doubly-fed induction generator. Also, the net load forecasting and the relationship between errors of load, wind and solar predictions are studied in this paper. The simulation results of the proposed method and its comparison with Tao and quantile regression models show that mean absolute percentage error of load forecasting, and the forecasts of solar and wind generations improved by 0.947%, 0.3079% and 0042%, respectively which result to a decrease in net load forecasting error. Manuscript profile -
Open Access Article
697 - Non-Isolated DC / DC Converter with High Voltage Gain and Appropriate Efficiency in High Transfer Power with New Soft Switching Structure
Omid sharifiyana majid dehghani Ghazanfar Shahgholian S.M. Mehdi Mirtalaei Masoud JabbariOne of the main limitations of using renewable energies for electricity generation is the low output voltage of power plants with renewable energies. Therefore, the design of a converter with higher gain voltage and higher efficiency is important in the use of renewable MoreOne of the main limitations of using renewable energies for electricity generation is the low output voltage of power plants with renewable energies. Therefore, the design of a converter with higher gain voltage and higher efficiency is important in the use of renewable energies. In this paper, a new topology that simultaneously has the structure of a boost converter can minimize switching losses by conventional soft switching methods and is also able to reduce voltage stress on diodes and switches Keep to an acceptable level. A simple boost converter can Increase the output voltage significantly by adding a parallel branch by generating a series resonance and enables zero voltage switching at the same time. Suggested converter without adding active element to converter with simple non-isolated structure at 500 watts and 385 volts it has a voltage gain factor of about 10.8 and efficiency of over 93%. The results show the performance simulation of the proposed converter for different performance modes. Manuscript profile -
Open Access Article
698 - Presenting a Multi-Criteria QoS-Aware Fault Tolerant Routing Algorithm for Network-On-Chips
Alireza Mahjoub Fatemeh Vardi Roya RadNetwork-on-chip is a router-based paradigm that determines the path of packet passing from the source to destination by a routing pattern through simplified protocols of the public data communication network. Sometimes, it is impossible to send packets from source to de MoreNetwork-on-chip is a router-based paradigm that determines the path of packet passing from the source to destination by a routing pattern through simplified protocols of the public data communication network. Sometimes, it is impossible to send packets from source to destination due to the communication problems caused by network elements in NoC such as routers and faulty links. In most cases, fault-tolerant algorithms select a reliable path using definite criteria. Therefore, in this paper, a reliable path is selected using a multi-criteria decision making technique through an adaptive approach according to the density status received from the adjacent nodes along with the path length so that when a failure occurs, a reliable path with similar QoS features is replaced by rating different paths among network nodes. The weight path selection strategy in NoCs to detect the minimal output port and multi-criteria decision making approach with VIKOR method has improvement over the basic routing algorithm in terms of delay and throughput. The algorithm hardware overhead has a reasonably low cost that maintains scalability for large scale On-Chip networks implementations. Manuscript profile -
Open Access Article
699 - Performance Improvement of Polynomial Neural Network Classifier using Whale Optimization Algorithm
Mahsa Memari A. Harifi a. KhaliliPolynomial neural network (PNN) is a supervised learning algorithm which is one of the most popular models used in real applications. The architectural complexity of polynomial neural network in terms of both number of partial descriptions (PDs) and number of layers, le MorePolynomial neural network (PNN) is a supervised learning algorithm which is one of the most popular models used in real applications. The architectural complexity of polynomial neural network in terms of both number of partial descriptions (PDs) and number of layers, leads to more computation time and more storage space requirement. In general, it can be said that the architecture of the polynomial neural networks is very complex and it requires large memory and computation time. In this research, a novel approach has been proposed to improve the classification performance of a polynomial neural network using the Whale Optimization Algorithm (PNN-WOA). In this approach, the PDs are generated at the first layer based on the combination of two features. The second layer nodes consists of PDs generated in the first layer, input variables and bias. Finally, the polynomial neural network output is obtained by sum of weighted values of the second layer outputs. Using the Whale Optimization Algorithm (WOA), the best vector of weighting coefficients will be obtained in such a way that the PNN network reach to the highest classification accuracy. Eleven different dataset from UCI database has been used as input data of proposed PNN-WOA and the results has been presented. The proposed method outperforms state-of-the-art approaches such as PNN-RCGA, PNN-MOPPSO, RCPNN-PSO and S-TWSVM in most cases. For datasets, an improvement of accuracy between 0.18% and 10.33% can be seen. Also, the results of the Friedman test indicate the statistical superiority of the proposed PNN-WOA model compared to other methods with p value of 0.039. Manuscript profile -
Open Access Article
700 - Design and Implementation of High Impedance Fault Relay Based on Harmonic Analysis Algorithm for Ahvaz 33 kV Distribution Network
مهدي منادي S. Gh. Seifossadat R. Kianinezhad Mohammad BaharipoorOver current relays that are used commonly in distribution system can't detect high impedance fault. Therefore for that purpose it is necessary to design special algorithms. In this paper, a method based on harmonic analysis is presented. In this technique, the proposed MoreOver current relays that are used commonly in distribution system can't detect high impedance fault. Therefore for that purpose it is necessary to design special algorithms. In this paper, a method based on harmonic analysis is presented. In this technique, the proposed relay, after fault occurs, extracts the required harmonic and according designed algorithm, occurrence of fault is reported. Software of this relay for different scenarios of high impedance faults was tested; also its hardware of relay in laboratory tests could correctly identify events. Manuscript profile -
Open Access Article
701 - A Frequency-Hopping Based Pulse Width Modulator for Spur Reduction in Switching Buck Converters
Reza Inanlou Omid ShoaeiThis paper presents an EMI reduction technique for switched-mode buck converters. To achieve this, the frequency hopping concept is utilized in asynchronous pulse width modulators (APWM) performing the power conversion with controlling the on-off time of the power switc MoreThis paper presents an EMI reduction technique for switched-mode buck converters. To achieve this, the frequency hopping concept is utilized in asynchronous pulse width modulators (APWM) performing the power conversion with controlling the on-off time of the power switches. The modulator has an oscillatory behavior; such that its oscillation frequency depends on its internal loop delay. Making use of this property and randomly changing the loop delay between 8 distinct random values, its self-oscillation frequency is also changed between 8 different values. As a result, a spur-free spectrum is achieved at the output of the converter. To verify the usefulness of the proposed method, a model-based behavioral simulation was done using MATLAB-SIMULINK. The main advantage of the proposed method over previous works is that the switching frequency controlling mechanism is fully digital. Besides, it can be readily done without causing any disturbance in the carrier signal. Manuscript profile -
Open Access Article
702 - Autonomous Controlling System for Structural Health Monitoring Wireless Sensor Networks
Sahand Hashemi Seyyed Amir Asghari Mohammad Reza Binesh MarvastiNowadays, office, residential, and historic buildings often require special monitoring. Obviously, such monitoring involves costs, errors and challenges. As a result of factors such as lower cost, broader application, and ease of installation, wireless sensor networks a MoreNowadays, office, residential, and historic buildings often require special monitoring. Obviously, such monitoring involves costs, errors and challenges. As a result of factors such as lower cost, broader application, and ease of installation, wireless sensor networks are frequently replacing wired sensor networks for structural health monitoring. Depending on the type and condition of a structure, factors such as energy consumption and accuracy, as well as fault tolerance are important. Particularly when wireless sensor networks are involved, these are ongoing challenges which, despite research, have the possibility of being improved. Using the Markov decision process and wake-up sensors, this paper proposes an innovative approach to monitoring stable and semi-stable structures, reducing the associated cost and error over existing methods, and according to the problem, we have advantages both in implementation and execution. Thus, the proposed method uses the Markov decision process and wake-up sensors to provide a new and more efficient technique than existing methods in order to monitor the health of stable and semi-stable structures. This approach is described in six steps and compared to widely used methods, which were tested and simulated in CupCarbon simulation environment with different metrics, and shows that the proposed solution is better than similar solutions in terms of a reduction of energy consumption from 11 to 70%, fault tolerance in the transferring of messages from 10 to 80%, and a reduction of cost from 93 to 97%. Manuscript profile -
Open Access Article
703 - Assessment of Demand Side Resources Potential in Presence of Cooling and Heating Equipment Using Data Mining Method Based Upon K-Means Clustering Algorithm
fatemeh sheibani M. Mollahassani-pour هنگامه کشاورزUnder the smart power systems, determining the amount of Demand Response Resources(DRRs) potential is considered as a crucial issue due to affecting in all energy policy decisions. In this paper, the potential of DRRs in presence of cooling and heating equipment are ide MoreUnder the smart power systems, determining the amount of Demand Response Resources(DRRs) potential is considered as a crucial issue due to affecting in all energy policy decisions. In this paper, the potential of DRRs in presence of cooling and heating equipment are identified using k-means clustering algorithm as a data mining technique. In this regard, the energy consumption dataset are categorized in different clusters by k-means algorithm based upon variations of energy price and ambient temperature during peak hours of hot (Spring and Summer) and cold (Autumn and Winter) periods. Then, the clusters with the possibility of cooling and heating equipment’s commitment are selected. After that, the confidence interval diagram of energy consumption in elected clusters is provided based upon energy price variations. The nominal potential of DRRs, i.e. flexible load, will be obtained regarding the maximum and minimum differences between the average of energy consumption in upper and middle thresholds of the confidence interval diagram. The energy consumption, ambient temperature and energy price related to BOSTON electricity network over a six-year horizon time is utilized to evaluate the proposed model. Manuscript profile -
Open Access Article
704 - Improving the Transient Stability of Grid Connected Converter During Severe Voltage Drop by Virtual Impedance
Omid Abdoli E. Gholipour R. HooshmandWith the rise in the penetration of inverter based distributed energy sources, grid codes say that converters should not be disconnected during the fault. These sources should also help the grid by reactive power injection. Power system grids are resistive inductive and MoreWith the rise in the penetration of inverter based distributed energy sources, grid codes say that converters should not be disconnected during the fault. These sources should also help the grid by reactive power injection. Power system grids are resistive inductive and the converter may be unstable during the fault. Converters use phase locked loop (PLL) to synchronize with the grid. PLL is not able to be stable during severe voltage drop, so converters cannot ride through the fault and should be disconnected. In this paper a novel method based on virtual impedance is proposed to maintain the synchronization during severe voltage drop. This method needs grid impedance estimation and virtually connects the converter to a point that has a stronger connection. By this novel method, during voltage drop, the converter stays connected to the grid and injects reactive power. Simulation results in MATLAB verify the ability of proposed method in improving the transient stability of converter. Manuscript profile -
Open Access Article
705 - Model Predictive Control of Permanent Magnet Synchronous Machine Based on Finite and Continuous Control Sets in Two Functional Quarters
ehsan ghasemi madani Mohammad Reza Alizadeh Pahlavani Arash Dehestani KolagarIn this paper, two schemes of model predictive control (MPC) method, named finite control set model predictive control (FCS-MPC) and dead-beat model predictive control (DB-MPC) as a continuous control set model predictive control (CCS-MPC) are applied and compared to co MoreIn this paper, two schemes of model predictive control (MPC) method, named finite control set model predictive control (FCS-MPC) and dead-beat model predictive control (DB-MPC) as a continuous control set model predictive control (CCS-MPC) are applied and compared to control the current of a permanent magnet synchronous machine in energy recovery mode for the use of electric vehicles. The FCS-MPC strategy selects the optimal voltage vector and applies the control pulses directly to the inverter without using any modulators. In other side, DB-MPC is implemented through space vector pulse width modulation (SVPWM). The performance and results of both types of control strategies are extracted and compared using MATLAB Simulink software. The comparisons are made mainly in steady state and transient modes. Both control strategies are applied to a permanent magnet synchronous machine with the same parameters and with the same operating mode. The results show that the current steady state fluctuation is further reduced in the DB-MPC strategy and the transient state response is faster in the FCS-MPC strategy. Manuscript profile -
Open Access Article
706 - Improving Age Estimation of Dental Panoramic Images Based on Image Contrast Correction by Spatial Entropy Method
Masoume Mohseni Hussain Montazery Kordy Mehdi EzojiIn forensic dentistry, age is estimated using dental radiographs. Our goal is to automate these steps using image processing and pattern recognition techniques. With a dental radiograph, the contour is extracted and features such as apex, width and tooth length are dete MoreIn forensic dentistry, age is estimated using dental radiographs. Our goal is to automate these steps using image processing and pattern recognition techniques. With a dental radiograph, the contour is extracted and features such as apex, width and tooth length are determined, which are used to estimate age. Optimizing the resolution of radiographic images is an important step in contour extraction and age estimation. In this article, the aim is to improve the image resolution in order to extract the appropriate area and proper segmentation of the tooth, which makes it possible to estimate age better. In this model, due to the low resolution of radiographic images, in order to increase the accuracy of extracting the desired area of each tooth (ROI), the image resolution increases using spatial entropy based on the spatial distribution of pixel brightness, along with another increasing resolution method, like the Laplacian pyramids. Increasing the resolution of the image leads to the extraction of appropriate ROI and the removal of unwanted areas. The database used in this study is 154 adolescent panoramic radiographs, of which 73 are male and 81 are female. This database is prepared from Babol University of Medical Sciences. The results show that by using fixed tooth segmentation methods and only by applying the proposed effective method to improve image resolution, the extraction of appropriate ROI increased from 66% to 78% which shows a good improvement. The extracted ROI is then delivered to the segmented block and the contour extracted. After contour extraction, age is estimated. The age estimation using the proposed method is closer to the manual age estimate compared to the method that does not use the proposed algorithm to increase the image resolution. Manuscript profile -
Open Access Article
707 - Design and Implementation of Fuzzy Sliding Mode Controller for Motion Control of an Electric Shake Table Using Adaptive Extended Kalman Filter
Nima rajabi Ramazan HavangiIn this paper, Design of a fuzzy sliding mode controller (FSMC) with adaptive extended Kalman filter (AEKF) for controlling a shake table system with electric actuator and ball-screw mechanism. Due to the uncertainties regarding the model parameters and the noise of the MoreIn this paper, Design of a fuzzy sliding mode controller (FSMC) with adaptive extended Kalman filter (AEKF) for controlling a shake table system with electric actuator and ball-screw mechanism. Due to the uncertainties regarding the model parameters and the noise of the data of the two encoder and accelerometer sensors, there are many problems in controlling this system. Therefore, it is crucial to employ a non-precise model-based controller and a nonlinear adaptive filter. The fuzzy sliding mode control and Extended Kalman filter are a good way to control this system. In sliding mode control, chattering at the control input is inevitable. In this paper, a simple fuzzy inference mechanism is used to reduce the undesirable phenomenon of chattering by correctly estimating the upper bound of uncertainty. In the following, a recursive method is used to determine the system and measurement noise covariance matrices. The data of the two encoder and accelerometer sensors are combined in the adaptive extended Kalman filter and the results in noise elimination and parameter estimation are investigated. Linear speed feedback available through the Kalman filter is used to stabilize and control the closed loop system. The end is examined to check the performance of the control structure provided by the seismic table test. The results show that the proposed method is very effective. Manuscript profile -
Open Access Article
708 - Spatio-Temporal Prediction of Vegetation Dynamics Based on Remote Sensing Data Using Deep Learning
Elham Zangeneh H. Mashayekhi Saeed GharacheloUnderstanding and analyzing spatial-temporal data changes is very important in various applications, including the protection and development of natural resources. In the past studies, Markov process and comparison-based methods were mainly used to predict the changes o MoreUnderstanding and analyzing spatial-temporal data changes is very important in various applications, including the protection and development of natural resources. In the past studies, Markov process and comparison-based methods were mainly used to predict the changes of vegetation indices, whose accuracy still needs improvement. Although time series analysis has been used to predict some indices, the method to extract these indices from remote sensing data and model their sequences with deep learning is rarely observed. In this article, a method for predicting changes in plant indices based on deep learning is presented. The research data includes Landsat satellite images from 2000 to 2018, related to four seasons in the north and east of Shahrood city in Semnan province. The time span of the extracted images makes it possible to predict changes in vegetation cover. Vegetation indices extracted from the data set are NDVI, SAVI and RVI. After performing atmospheric corrections on the images, the desired indicators are extracted and then the data is converted into a time series. Finally, the modeling of the sequence of these data is performed by the Short-Long-Term Memory (LSTM) network. The results of the experiments show that the deep network is able to predict future values with high accuracy. The amount of the model error without additional data is 0.03 for the NDVI index, 0.02 for the SAVI index, and 0.06 for the RVI index. Manuscript profile -
Open Access Article
709 - Optimal Placement of Energy Storage Systems Taking into Account the Uncertainties of Renewable Energy Generation, Load and Electricity Prices
NAVID TAGHIZADEGAN KALANTARI Yousef Fonooni Morteza Ahangari HassasOne of the main goals of distribution network operators is to reduce the cost of operating the network and improve profit. In this paper, the problem of siting and determining the size of energy storage batteries are studied. The constituent components of the objective MoreOne of the main goals of distribution network operators is to reduce the cost of operating the network and improve profit. In this paper, the problem of siting and determining the size of energy storage batteries are studied. The constituent components of the objective function of the placement problem include the profit from the operation of the distributed generation unit, the profit from the reduction of grid power losses, the cost of installing an energy storage system, and the profit from the reduction of energy purchased from the upstream network. The model used for positioning is based on the probabilistic behavior of solar radiation, energy consumers, and electricity market operators. To model the stochastic nature of the output power of solar power plants, the probability density function has been used, and to model the load and price of electricity, the scenario method has been used. The simulations were performed using MATLAB software. The proposed method can manage the generation of solar power plants using the siting and management of charge and discharge of batteries. Manuscript profile -
Open Access Article
710 - Investigation of Leakage Current and Surface Temperature of 230 kV Composite Insulator Under the Influence of Moisture and Contamination Conditions
Saman Mohammadnabi Khosrow RahmaniAs moisture condenses on the surface of the contaminated insulators, the electrical conductivity of the insulator surface increases, resulting in a leakage current on the surface and causing the insulators to fail. Condensation of moisture on the insulator surface occur MoreAs moisture condenses on the surface of the contaminated insulators, the electrical conductivity of the insulator surface increases, resulting in a leakage current on the surface and causing the insulators to fail. Condensation of moisture on the insulator surface occurs due to the mechanism of radiation cooling, mainly in the early mornings of winters. In this case, the temperature of the insulator surface is lower than the dew point. In this paper, a sample of real fine dust collected from the dust center and chemical analysis and measurement of electrical conductivity in the wet state were performed. By simulating a 230-kV contaminated composite insulator in COMSOL Multiphysics software, the magnitude of leakage current was obtained and verified by an experimental test. Also, using heat transfer governing relations, the temperature of the insulator surface during the leakage current flow, was determined and compared with the images captured by the thermo-vision camera during the test. The results show that the leakage current and the surface temperature of the insulator increase with increasing the conduction and thickness of the contamination layer and consequently the probability of insulator failure also increases. Experimental testing shows that simulation of insulators with finite elements-based commercial software can be a reliable method for pre-analysis of insulators. Manuscript profile -
Open Access Article
711 - Non-Fragile Adaptive Sliding-Mode Observer Design for a Class of Fractional-Order Pseudo-Linear Systems with State Delay
مجيد پرويزيان خسرو خانداني وحيد جوهري مجدIn recent years, fractional order systems and fractional order control have increasingly attracted the attention of researchers in various fields of science and engineering. On the other hand, numerous control approaches have been extended in order to be utilized in fra MoreIn recent years, fractional order systems and fractional order control have increasingly attracted the attention of researchers in various fields of science and engineering. On the other hand, numerous control approaches have been extended in order to be utilized in fractional order systems. Despite this fact, few research studies have been devoted to generalizing integer order observers to fractional order ones. Since the applications of fractional order systems are increasing, developing fractional order observers seems to be essential. In this paper the problem of non-fragile adaptive sliding mode observer design for a class of fractional-order nonlinear systems with time delay is addressed. First, the states of the fractional-order pseudo-linear time-delay system with matched nonlinearity are estimated employing the sliding mode control method. Then the state estimation problem of fractional order systems with mismatched nonlinearity has been investigated. The asymptotic stability of the estimation error dynamics is proven by employing the Lyapunov stability analysis method for fractional order systems. The sufficient stability conditions are derived in the form of Linear Matrix Inequalities (LMIs). Eventually, the effective performance of the proposed approach in this paper has been corroborated through simulation of a numerical example and also a case study of a fractional order economic system. Manuscript profile -
Open Access Article
712 - Providing lightweight mutual group authentication of Internet of Things
reza sarabi miyanaji sam jabbehdari nasser modiriThe Internet of things is becoming the largest computing platform and we are seeing an increase in the number of devices in this environment. In addition, most Things in this infrastructure have the computational power and memory constraints. They cannot perform complex MoreThe Internet of things is becoming the largest computing platform and we are seeing an increase in the number of devices in this environment. In addition, most Things in this infrastructure have the computational power and memory constraints. They cannot perform complex computational operations. These limitations have been ignored in most traditional authentication methods. Meanwhile, in the new methods of authentication of this environment, not much attention has been paid to the issue of scalability. Therefore, the need for a lightweight, scalable authentication is felt. In this paper, a lightweight authentication protocol is presented in which things are placed in different groups. In each group, a group manager node is considered and as an agent, it performs authentication on behalf of other members. Therefore, Authentication is done in groups, which makes the proposed protocol highly scalable. The proposed method reduces the computational cost of nodes and servers and provides privacy through node anonymity. In addition, it has forward-looking privacy without the use of asynchronous encryption and key agreement. The AVISPA tool has been used to confirm the security of the proposed method. In our method, the computation time of the node and server in authentication has been decreased by 7.8% and 3.5%, respectively, compared with reviewing protocols. Manuscript profile -
Open Access Article
713 - Measuring and Modeling Satellite Reaction Wheel Disturbances Using Acceleration and Force Sensors
Arman Sehat nia F. Hashemzadeh Hamid Guchi eskandarThe reaction wheel is one of the most sensitive devices used in spacecraft, which is easily disturbed. Nowadays, maintaining the status of the satellite and the ability to control it, is one of the most important issues due to the costly design and construction of such MoreThe reaction wheel is one of the most sensitive devices used in spacecraft, which is easily disturbed. Nowadays, maintaining the status of the satellite and the ability to control it, is one of the most important issues due to the costly design and construction of such projects. To improve this process, identifying and modeling perturbations and analyzing their effects on system parameters to spot the defects, are very important. As a result, accurate identification and estimation of perturbations on reaction wheels through studying the effect of input uncertainty on the system state variables is necessary to reveal the internal condition of the spacecraft and identify its defects. For this reason, in this paper, a new observer is designed to estimate the uncertain perturbation and the system state vector. In this regard, by considering the dynamics of variable micro-turbulence with wheel imbalance time, we obtain the proposed observer’s design matrices at any time by performing a series of linear matrix inequality (LMI) calculations that converge and stabilize the estimation error based on Lyapuanv theorem. Then, the results are presented in a series of simulations in MATLAB software included the characteristic of estimated uncertain inputs and state vector of micro-turbulence model, in section four. Manuscript profile -
Open Access Article
714 - Detecting Human Activities Based on Motion Sensors in IOT Using Deep Learning
Abbas Mirzaei fatemeh farajiControl of areas and locations and motion sensors in the Internet of Things requires continuous control to detect human activities in different situations, which is an important challenge, including manpower and human error. Permanent human control of IoT motion sensors MoreControl of areas and locations and motion sensors in the Internet of Things requires continuous control to detect human activities in different situations, which is an important challenge, including manpower and human error. Permanent human control of IoT motion sensors also seems impossible. The IoT is more than just a simple connection between devices and systems. IoT information sensors and systems help companies get a better view of system performance. This study presents a method based on deep learning and a 30-layer DNN neural network for detecting human activity on the Fordham University Activity Diagnostic Data Set. The data set contains more than 1 million lines in six classes to detect IoT activity. The proposed model had almost 90% and an error rate of 0.22 in the evaluation criteria, which indicates the good performance of deep learning in activity recognition. Manuscript profile -
Open Access Article
715 - Modeling a Proposed Nanoscale SOI-Junctionless for Improvement of Steady-State and Frequency Characteristics
Mohammad Kazem AnvarifardIn this paper in order to improve the electrical performance of nanoscale SOI-junctionless, a targeted modification has been performed. The proposed structure has been aimed to reduce the OFF current and self-heating effect. To reduce the self-heating effect, the buried MoreIn this paper in order to improve the electrical performance of nanoscale SOI-junctionless, a targeted modification has been performed. The proposed structure has been aimed to reduce the OFF current and self-heating effect. To reduce the self-heating effect, the buried oxide thickness has been reduced into the half and a part of it has been replaced by a buffer layer. Increase in the thermal conduction and making an extra depletion layer in the buffer layer/channel region interface are led to improvement of the electrical performance in the terms of DC and AC. In the proposed method, which is based on the energy band modification, the parameters such as IOFF, ION/IOFF, subthreshold swing, lattice temperature, voltage gain, transconductance, parasitic capacitances, power gains, cut-off frequency, maximum oscillation frequency and minimum noise figure have been improved. Also, a designing consideration for the role of buffer layer on the proposed device has been performed. Comparing structures under the study simulated by the SILVACO showed the electrical performance superiority for the proposed device. Manuscript profile -
Open Access Article
716 - A Semi-Central Method to Improve Energy Saving in Real Wireless Sensor Networks Using Clustering and Mobile Sinks
Fatemeh Sadeghi Sepideh Adabi Sahar AdabiApplying a hierarchical routing approach based on clustering technique and mobile sink has a great impact on reducing energy consumption in WSN. Two important issues in designing such an approach are cluster head selection and optimal allocation of mobile sinks to criti MoreApplying a hierarchical routing approach based on clustering technique and mobile sink has a great impact on reducing energy consumption in WSN. Two important issues in designing such an approach are cluster head selection and optimal allocation of mobile sinks to critical regions (i.e., regions those have low remaining energy and thus, high risk of energy hole problem). The limited number of mobile sinks should be utilized due to a high cost. Therefore, allocating the limited number of mobile sinks to the high amount of requests received from the critical regions is categorized as a NP-hard problem. Most of the previous studies address this problem by using heuristic methods which are carried out by sensor nodes. However, this type of solutions cannot be implemented in real WSN due to the sensors’ current technology and their limited processing capability. In other words, these are just theoretical solutions. Consequently, a semi-central genetic algorithm based method using mobile sink and clustering technique is proposed in order to find a trade-off between reduction of computation load on the sensors and increasing accuracy. In our method, lightweight computations are separated from heavyweight computations. While, the former computations are carried out by sensors, the latter are carried out by base station. Following activities are done by the authors: 1) cluster head selection by using effective environmental parameters and defining cost function of cluster membership, 2) mathematical modeling of a region’s chance to achieve mobile sink, and 3) designing a fitness function to evaluate the fitness of each allocation of mobile sinks to the critical regions in genetic algorithm. Furthermore, in our activities minimizing the number and length of messages are focused. In summary, the main distinguishing feature of the proposed method is that it can be implemented in real WSN (due to separation of lightweight computations from heavyweight computations) with respect to early mentioned objectives. The simulation results show the better performance of the proposed method compared to comparison bases. Manuscript profile -
Open Access Article
717 - A New Algorithm Based on Distributed Learning Automata for Solving Stochastic Linear Optimization Problems on the Group of Permutations
mohammadreza mollakhalili meybodi masoumeh zojajiIn the present research, a type of permutation optimization was introduced. It is assumed that the cost function has an unknown probability distribution function. Since the solution space is inherently large, solving the problem of finding the optimal permutation is com MoreIn the present research, a type of permutation optimization was introduced. It is assumed that the cost function has an unknown probability distribution function. Since the solution space is inherently large, solving the problem of finding the optimal permutation is complex and this assumption increases the complexity. In the present study, an algorithm based on distributed learning automata was presented to solve the problem by searching in the permutation answer space and sampling random values. In the present research, in addition to the mathematical analysis of the behavior of the proposed new algorithm, it was shown that by choosing the appropriate values of the parameters of the learning algorithm, this new method can find the optimal solution with a probability close to 100% and by targeting the search using the distributed learning algorithms. The result of adopting this policy is to decrease the number of samplings in the new method compared to methods based on standard sampling. In the following, the problem of finding the minimum spanning tree in the stochastic graph was evaluated as a random permutation optimization problem and the proposed solution based on learning automata was used to solve it. Manuscript profile -
Open Access Article
718 - Performance Evaluation of TMDFET-based SRAM Memory Cell Compared to Si-MOSFET Technology
فرزانه ایزدی نسب Morteza GholipourTransition metal dichalcogenides FETs (TMDFETs) are among the emerging devices that have been considered by researchers in recent years. In this paper, the effect of parameter variations, temperature and power supply on the performance of TMDFET transistors has been inv MoreTransition metal dichalcogenides FETs (TMDFETs) are among the emerging devices that have been considered by researchers in recent years. In this paper, the effect of parameter variations, temperature and power supply on the performance of TMDFET transistors has been investigated in comparison with Si-MOSFET technology. The results indicate that TMDFET is less sensitive to these variations compared to Si-MOSFET devices. By selecting the appropriate transistors size ratios, the performance of the TMDFET-based conventional 6-transistor static random access memory cell is evaluated in comparison with the Si-MOSFET in 16nm technology. Simulations are performed at room temperature, 0.7 V supply voltage and the same conditions for both TMDFET and Si-MOSFET devices. The results of the simulations show that TMDFET-based SRAM cell has 29.44% more WTP, corresponding to more writing ability, 49.49% more WTI×WTV, corresponding to higher writing noise margin, and 29.48% lower read delay. In other words, a TMDFET-based SRAM cell performs better than Si-MOS-SRAM in terms of write ability, static read margin, and read delay. Manuscript profile -
Open Access Article
719 - testDesign Decentralized Controller for a Group of Cooperative Robot to Pushing a Box in Presence of Network Constraints
میلاد مرادی سید محمد مهدی Seyyed M. Mehdi DehghanThe problem of pushing objects by a group of cooperative robots has many applications on land and sea level and due to its importance, it has become a standard problem for evaluating various theories of robot cooperation. In this case, each robot produces distributed co MoreThe problem of pushing objects by a group of cooperative robots has many applications on land and sea level and due to its importance, it has become a standard problem for evaluating various theories of robot cooperation. In this case, each robot produces distributed control force to push the object in the desired direction. The proposed methods for distributed control of an object on a time-varying path require information about the position of the robots relative to the object. The problem of the lack of sufficient knowledge of each robot of how the robots are positioned relative to the body can be solved by proposing a consensus issue on positional moments. In this case, the robots must reach a consensus on these moments by exchanging information through the communication network between them. The effect of communication network between robots on the process of reaching consensus and the effect of delay in consensus on the results of control of object on the desired path is the subject of this article. In this paper, the appropriate control law for achieving consensus in the absence of full connection between all bots, delay and the probability of data loss in the communication network is presented. The maximum allowable network delay is also specified to prevent the instability of object motion control. The simulation results show the capability of the proposed method for controlling the velocity of the object on the desired variable path and show the effect of network constraints on the performance of the controller. Manuscript profile -
Open Access Article
720 - Design and Simulation of a New Micro-Displacement Sensor Based on Negative Refraction Photonic Crystal
K. FasihiIn this paper, design and simulation of a new micro-displacement sensor based on photonic crystal fixed and movable segments is presented. It has been shown that using negative refraction photonic crystal in the fixed segment, the transmitted power is concentrated on th MoreIn this paper, design and simulation of a new micro-displacement sensor based on photonic crystal fixed and movable segments is presented. It has been shown that using negative refraction photonic crystal in the fixed segment, the transmitted power is concentrated on the entrance of the movable segment, and the sensor specifications are improved. Based on the FDTD simulation results, the sensitivity, the operational displacement range and the regression coefficient of the proposed sensor are 1.1 (a-1), 0.35a and 0.99848, respectively. The simulation results show that the proposed sensor has a good performance and could well be used in micro-displacement measuring systems. Manuscript profile -
Open Access Article
721 - Reliable and Energy Efficient Deployment Optimization of Internet of Things Applications in Cloud and Fog Infrastructure by Using Cuckoo Search Algorithm
Yaser Ramzanpoor میرسعید حسینی شیروانیDeployment applications of internet of things (IoT) in fog infrastructure as cloud complementary leads effectively computing resource saving in cloud infrastructure. Recent research efforts are investigating on how to better exploit fog capabilities for execution and su MoreDeployment applications of internet of things (IoT) in fog infrastructure as cloud complementary leads effectively computing resource saving in cloud infrastructure. Recent research efforts are investigating on how to better exploit fog capabilities for execution and supporting IoT applications. Also, the distribution of an application’s components on the possible minimum number of fog nodes for the sake of reduction in power consumption leads degradation of the service reliability level. In this paper, a hybrid meta-heuristic algorithm based on cuckoo search algorithm is presented for static deployment the components of IoT applications on fog infrastructure in the aim of trade-off between efficient power usage, reduction in the effect of one point of failure and boosting the application reliability against failure. The results of simulations show that the proposed approach in this paper reduces the power consumption of fog network and meets the quality of service requirement of IoT application with the high reliability level. Manuscript profile -
Open Access Article
722 - Multi-Objective Optimization Solution for Virtual Machine Placement Problem in Cloud Datacenters with Minimization of Power Consumption and Resource Dissipation Perspectives by Simulated Annealing Algorithm
Mirsaeid Hosseini ShirvaniNowadays, cloud computing industry has been transformed to a new supply chain between cloud service providers and service requesters. To this end, cloud service provisioning in datacenters is procured via virtualization platforms in which it can potentially increase the MoreNowadays, cloud computing industry has been transformed to a new supply chain between cloud service providers and service requesters. To this end, cloud service provisioning in datacenters is procured via virtualization platforms in which it can potentially increase the utilization of computing resources at infrastructure level. Inefficient virtual machine placement (VMP) schemes lead lower system utilization, increase of resource dissipation, and high rate of power consumption. Therefore, this paper formulates VMP problem on physical machines of cloud datacenters to a multi-objective optimization problem with minimization of both power consumption and resource dissipation perspectives which is computationally NP-Hard. Since the most meta-heuristic algorithms are designed for continuous optimization problems and are also susceptible to get stuck in local optimum, to figure out this combinatorial problem an optimization algorithm based on simulated annealing algorithm commensurate with discrete search space of stated problem is extended, so that the possibility of getting stuck in local optimum is reduced. To validate the proposed approach, several scenarios are introduced and conducted. Reported results from simulation of different scenarios show that the proposed approach outperforms against other existing approaches in terms of reduction in power consumption, resource dissipation, and the number of active server in use. Manuscript profile -
Open Access Article
723 - Numeric Polarity Detection based on Employing Recursive Deep Neural Networks and Supervised Learning on Persian Reviews of E-Commerce Users in Opinion Mining Domain
Sepideh Jamshidinejad Fatemeh Ahmadi-Abkenari Peiman BayatOpinion mining as a sub domain of data mining is highly dependent on natural language processing filed. Due to the emerging role of e-commerce, opinion mining becomes one of the interesting fields of study in information retrieval scope. This domain focuses on various s MoreOpinion mining as a sub domain of data mining is highly dependent on natural language processing filed. Due to the emerging role of e-commerce, opinion mining becomes one of the interesting fields of study in information retrieval scope. This domain focuses on various sub areas such as polarity detection, aspect elicitation and spam opinion detection. Although there is an internal dependency among these sub sets, but designing a thorough framework including all of the mentioned areas is a highly demanding and challenging task. Most of the literatures in this area have been conducted on English language and focused on one orbit with a binary outcome for polarity detection. Although the employment of supervised learning approaches is among the common utilizations in this area, but the application of deep neural networks has been concentrated with various objectives in recent years so far. Since the absence of a trustworthy and a complete framework with special focuses on each impacting sub domains is highly observed in opinion mining, hence this paper concentrates on this matter. So, through the usage of opinion mining and natural language processing approaches on Persian language, the deep neural network-based framework called RSAD that was previously suggested and developed by the authors of this paper is optimized here to include the binary and numeric polarity detection output of sentences on aspect level. Our evaluation on RSAD performance in comparison with other approaches proves its robustness. Manuscript profile -
Open Access Article
724 - An Intelligent Vision System for Automatic Forest Fire Surveillance
Mohammad Sadegh Kayhanpanah Behrooz KoohestaniFighting forest fires to avoid their potential dangers as well as protect natural resources is a challenge for researchers. The goal of this research is to identify the features of fire and smoke from the unmanned aerial vehicle (UAV) visual images for classification, o MoreFighting forest fires to avoid their potential dangers as well as protect natural resources is a challenge for researchers. The goal of this research is to identify the features of fire and smoke from the unmanned aerial vehicle (UAV) visual images for classification, object detection, and image segmentation. Because forests are highly complex and nonstructured environments, the use of the vision system is still having problems such as the analogues of flame characteristics to sunlight, plants, and animals, or the smoke blocking the images of the fire, which causes false alarms. The proposed method in this research is the use of convolutional neural networks (CNNs) as a deep learning method that can automatically extract or generate features in different layers. First, we collect data and increase them according to data augmentation methods, and then, the use of a 12-layer network for classification as well as transfer learning method for segmentation of images is proposed. The results show that the data augmentation method used due to resizing and processing the input images to the network to prevent the drastic reduction of the features in the original images and also the CNNs used can extract the fire and smoke features in the images well and finally detect and localize them. Manuscript profile -
Open Access Article
725 - Efficient Recognition of Human Actions by Limiting the Search Space in Deep Learning Methods
m. koohzadi N. MoghadamThe efficiency of human action recognition systems depends on extracting appropriate representations from the video data. In recent years, deep learning methods have been proposed to extract efficient spatial-temporal representations. Deep learning methods, on the other MoreThe efficiency of human action recognition systems depends on extracting appropriate representations from the video data. In recent years, deep learning methods have been proposed to extract efficient spatial-temporal representations. Deep learning methods, on the other hand, have a high computational complexity for development over temporal domain. Challenges such as the sparsity and limitation of discriminative data, and highly noise factors increase the computational complexity of representing human actions. Therefore, creating a high accurate representation requires a very high computational cost. In this paper, spatial and temporal deep learning networks have been enhanced by adding appropriate feature selection mechanisms to reduce the search space. In this regard, non-online and online feature selection mechanisms have been studied to identify human actions with less computational complexity and higher accuracy. The results showed that the non-linear feature selection mechanism leads to a significant reduction in computational complexity and the online feature selection mechanism increases the accuracy while controlling the computational complexity. Manuscript profile -
Open Access Article
726 - A New Data Clustering Method Using 4-Gray Wolf Algorithm
Laleh Ajami Bakhtiarvand Zahra BeheshtiNowadays, clustering methods have received much attention because the volume and variety of data are increasing considerably.The main problem of classical clustering methods is that they easily fall into local optima. Meta-heuristic algorithms have shown good results in MoreNowadays, clustering methods have received much attention because the volume and variety of data are increasing considerably.The main problem of classical clustering methods is that they easily fall into local optima. Meta-heuristic algorithms have shown good results in data clustering. They can search the problem space to find appropriate cluster centers. One of these algorithms is gray optimization wolf (GWO) algorithm. The GWO algorithm shows a good exploitation and obtains good solutions in some problems, but its disadvantage is poor exploration. As a result, the algorithm converges to local optima in some problems. In this study, an improved version of gray optimization wolf (GWO) algorithm called 4-gray wolf optimization (4GWO) algorithm is proposed for data clustering. In 4GWO, the exploration capability of GWO is improved, using the best position of the fourth group of wolves called scout omega wolves. The movement of each wolf is calculated based on its score. The better score is closer to the best solution and vice versa. The performance of 4GWO algorithm for the data clustering (4GWO-C) is compared with GWO, particle swarm optimization (PSO), artificial bee colony (ABC), symbiotic organisms search (SOS) and salp swarm algorithm (SSA) on fourteen datasets. Also, the efficiency of 4GWO-C is compared with several various GWO algorithms on these datasets. The results show a significant improvement of the proposed algorithm compared with other algorithms. Also, EGWO as an Improved GWO has the second rank among the different versions of GWO algorithms. The average of F-measure obtained by 4GWO-C is 82.172%; while, PSO-C as the second best algorithm provides 78.284% on all datasets. Manuscript profile -
Open Access Article
727 - Search Engine for Structured Event Retrieval from News Sources
A. mirzaeiyan s. aliakbaryAnalysis of published news content is one of the most important issues in information retrieval. Much research has been conducted to analyze individual news articles, while most news events in the media are published in the form of several related articles. Event detect MoreAnalysis of published news content is one of the most important issues in information retrieval. Much research has been conducted to analyze individual news articles, while most news events in the media are published in the form of several related articles. Event detection is the task of discovering and grouping documents that describe the same event. It also facilitates better navigation of users in news spaces by presenting an understandable structure of news events. With rapid and increasing growth of online news, the need for search engines to retrieve news events is felt more than ever. The main assumption of event detection is that the words associated with an event appear in the same time windows and similar documents. Accordingly, in this research, we propose a retrospective and feature-pivot method that clusters words into groups according to semantic and temporal features. We then use these words to produce a time frame and a human readable text description. The proposed method is evaluated on the All The News dataset, which consists of two hundred thousand articles from 15 news sources in 2016 and compared to other methods. The evaluation shows that the proposed method outperforms previous methods in terms of precision and recall. Manuscript profile -
Open Access Article
728 - Energy-Aware Data Gathering in Rechargeable Wireless Sensor Networks Using Particle Swarm Optimization Algorithm
Vahideh Farahani Leili Farzinvash Mina Zolfy Lighvan Rahim Abri LighvanThis paper investigates the problem of data gathering in rechargeable Wireless Sensor Networks (WSNs). The low energy harvesting rate of rechargeable nodes necessitates effective energy management in these networks. The existing schemes did not comprehensively examine t MoreThis paper investigates the problem of data gathering in rechargeable Wireless Sensor Networks (WSNs). The low energy harvesting rate of rechargeable nodes necessitates effective energy management in these networks. The existing schemes did not comprehensively examine the important aspects of energy-aware data gathering including sleep scheduling, and energy-aware clustering and routing. Additionally, most of them proposed greedy algorithms with poor performance. As a result, nodes run out of energy intermittently and temporary disconnections occur throughout the network. In this paper, we propose an energy-efficient data gathering algorithm namely Energy-aware Data Gathering in Rechargeable wireless sensor networks (EDGR). The proposed algorithm divides the original problem into three phases namely sleep scheduling, clustering, and routing, and solves them successively using particle swarm optimization algorithm. As derived from the simulation results, the EDGR algorithm improves the average and standard deviation of the energy stored in the nodes by 17% and 5.6 times, respectively, compared to the previous methods. Also, the packet loss ratio and energy consumption for delivering data to the sink of this scheme is very small and almost zero Manuscript profile -
Open Access Article
729 - Construction of Scalable Decision Tree Based on Fast Data Partitioning and Pre-Pruning
سميه لطفي Mohammad Ghasemzadeh Mehran Mohsenzadeh Mitra MirzarezaeeClassification is one of the most important tasks in data mining and machine learning; and the decision tree, as one of the most widely used classification algorithms, has the advantage of simplicity and the ability to interpret results more easily. But when dealing wit MoreClassification is one of the most important tasks in data mining and machine learning; and the decision tree, as one of the most widely used classification algorithms, has the advantage of simplicity and the ability to interpret results more easily. But when dealing with huge amounts of data, the obtained decision tree would grow in size and complexity, and therefore require excessive running time. Almost all of the tree-construction algorithms need to store all or part of the training data set; but those algorithms which do not face memory shortages because of selecting a subset of data, can save the extra time for data selection. In order to select the best feature to create a branch in the tree, a lot of calculations are required. In this paper we presents an incremental scalable approach based on fast partitioning and pruning; The proposed algorithm builds the decision tree via using the entire training data set but it doesn't require to store the whole data in the main memory. The pre-pruning method has also been used to reduce the complexity of the tree. The experimental results on the UCI data set show that the proposed algorithm, in addition to preserving the competitive accuracy and construction time, could conquer the mentioned disadvantages of former methods. Manuscript profile -
Open Access Article
730 - Design and Implementation of a Compact, Microstrip Coupler with Harmonics Suppression Using T-Shaped and Stepped-Impedance Resonators
sonhan roshany Somayeh karimi Saeed RoshaniIn this paper a novel compact microstrip coupler using T-shaped and stepped impedance resonators is proposed, simulated and fabricated. In the proposed structure long quadrature wavelength lines are replaced with small resonators, which results in size reduction and ha MoreIn this paper a novel compact microstrip coupler using T-shaped and stepped impedance resonators is proposed, simulated and fabricated. In the proposed structure long quadrature wavelength lines are replaced with small resonators, which results in size reduction and harmonics suppression. The proposed coupler correctly works at 1 GHz and suppresses 2nd up to 7th unwanted harmonics. Moreover the designed coupler reduces the circuit size more than 65% compared to the conventional coupler. Manuscript profile -
Open Access Article
731 - Server Based QoE Improvement for Streamed Video Content in Cloud Architecture
seyed hassan nabavi Mohammad behdadfar Mohammad Reza noorifardOne of the new solutions playing an important role in improving multimedia delivery quality, is applying cloud based networks. In this paper, a new cloud based scheme is proposed for improving user quality of experience in video adaptive streaming services over HTTP. In MoreOne of the new solutions playing an important role in improving multimedia delivery quality, is applying cloud based networks. In this paper, a new cloud based scheme is proposed for improving user quality of experience in video adaptive streaming services over HTTP. In proposed solution, a server side look ahead window algorithm and a client side HTTP-GET request transmission algorithm are applied. Using both algorithms concurrently at server side and client side, results in reducing buffer overflow probability which leads to prevent playout stall. Manuscript profile -
Open Access Article
732 - A POI Recommendation Model According to the Behavior Pattern of Users Based on Friends List Using Deep Learning
sadaf safavi mehrdad jalaliThe rapid growth of Location-based Social Networks (LBSNs) is a great opportunity to provide personalized recommendation services. An important task to recommend an accurate Point-of-Interests (POIs) to users, given the challenges of rich contexts and data sparsity, is MoreThe rapid growth of Location-based Social Networks (LBSNs) is a great opportunity to provide personalized recommendation services. An important task to recommend an accurate Point-of-Interests (POIs) to users, given the challenges of rich contexts and data sparsity, is to investigate numerous significant traits of users and POIs. In this work, a novel method is presented for POI recommendation to develop the accurate sequence of top-k POIs to users, which is a combination of convolutional neural network, clustering and friendship. To discover the likeness, we use the mean-shift clustering method and only consider the influence of the most similarities in pattern’s friendship, which has the greatest psychological and behavioral impact rather than all user’s friendship. The new framework of a convolutional neural network with 10 layers can predict the next suitable venues and then select the accurate places based on the shortest distance from the similar friend behavior pattern. This approach is appraised on two LBSN datasets, and the experimental results represent that our strategy has significant improvements over the state-of-the-art techniques for POI recommendation. Manuscript profile -
Open Access Article
733 - Provide an Energy-aware Markov Based Model for Dynamic Placement of Virtual Machines in Cloud Data Centers
mehdi rajabzadeh Abolfazl Toroghi Haghighat Amir Masoud RahmaniThe use of energy-conscious solutions is one of the important research topics in the field of cloud computing. By effectively using virtual machine placement and aggregation algorithms, cloud suppliers will be able to reduce energy consumption. In this paper, a new mode MoreThe use of energy-conscious solutions is one of the important research topics in the field of cloud computing. By effectively using virtual machine placement and aggregation algorithms, cloud suppliers will be able to reduce energy consumption. In this paper, a new model is presented that seeks to achieve the desired results by improving the algorithms and providing appropriate methods. Periodic monitoring of resource status, proper analysis of the data obtained, and prediction of the critical state of the servers using the proposed Markov model have reduced the number of unnecessary migrations as much as possible. The combination of genetic algorithm and simulated annealing in the replacement section along with the definition of the adsorbent Markov chain has resulted in better and faster performance of the proposed algorithm. Simulations performed in different scenarios in CloudSim show that compared to the best algorithm compared, at low, medium and high load, energy consumption has decreased significantly. Violations of service level agreements also fell by an average of 17 percent. Manuscript profile -
Open Access Article
734 - Performance and Security Enhancement in Multi-band Uplink NOMA Networks with Selection of the Users and Energy Harvesting
Maryam NajimiIn this paper, uplink secure transmission in a non-orthogonal multiple access (NOMA) network is investigated by selection of the users for data transmission to the base station (BS) and also jammers with the capability of energy harvesting. In fact, each frame has two p MoreIn this paper, uplink secure transmission in a non-orthogonal multiple access (NOMA) network is investigated by selection of the users for data transmission to the base station (BS) and also jammers with the capability of energy harvesting. In fact, each frame has two phases. In the first phase, jammers harvest energy from BS and in the second phase, the selected users transmit their data to BS using NOMA technique while selected jammer emits the artificial noise for confusing the eavesdropper. In fact, the problem is maximizing the secrecy throughput by selection of the users for uplink data transmission to BS in each frequency channel and suitable jammers to make the artificial noise for eavesdropper with constraints on the secrecy outage probability (SOP) and connection outage probability (COP). The problem is solved based on the convex optimization methods and Karush-Kuhn-Tucker (KKT) conditions. An algorithm is proposed for solving the problem and the system performance is evaluated. Simulation results present that the proposed algorithm has the better performance for the throughput and security of the network in comparison with the benchmark algorithms in different situations and scenarios. Manuscript profile -
Open Access Article
735 - An Approximate Binary Tree-Based Solution to Speed Up the Search for the Nearest Neighbor in Big Data
Hosein Kalateh M. D.Due to the increasing speed of information production and the need to convert information into knowledge, old machine learning methods are no longer responsive. When using classifications with the old machine learning methods, especially the use of inherently lazy class MoreDue to the increasing speed of information production and the need to convert information into knowledge, old machine learning methods are no longer responsive. When using classifications with the old machine learning methods, especially the use of inherently lazy classifications such as the k-nearest neighbor (KNN) method, the operation of classifying large data sets is very slow. Nearest Neighborhood is a popular method of data classification due to its simplicity and practical accuracy. The proposed method is based on sorting the training data feature vectors in a binary search tree to expedite the classification of big data using the nearest neighbor method. This is done by finding the approximate two farthest local data in each tree node. These two data are used as a criterion for dividing the data in the current node into two groups. The data set in each node is assigned to the left and right child of the current node based on their similarity to the two data. The results of several experiments performed on different data sets from the UCI repository show a good degree of accuracy due to the low execution time of the proposed method. Manuscript profile -
Open Access Article
736 - Sub-Region Analytical Modeling of the Outer-Rotor Surface-Mounted Permanent Magnet Synchronous Machine
Armin Solhroshan Mohammad Reza Alizadeh Pahlavani Arash Dehestani KolagarIn this paper, the sub-region method is used to analyze the outer-rotor permanent magnet synchronous machine. In this method, based on hypotheses such as geometry, electrical and magnetic characteristics, the machine is divided into four sub-regions of groove, groove op MoreIn this paper, the sub-region method is used to analyze the outer-rotor permanent magnet synchronous machine. In this method, based on hypotheses such as geometry, electrical and magnetic characteristics, the machine is divided into four sub-regions of groove, groove opening, air gap and magnet. Based on Maxwell's equations and considered assumptions, the governing partial differential equations for each sub-region are presented and solved analytically. In this paper, after calculating the air-gap flux density caused by the armature winding current and magnets with three patterns of radial, parallel and Halbach magnetization, the other main quantities of the machine are calculated accordingly. To validate the analytical model, the results obtained from MATLAB software are compared with the values obtained from the finite element method. Manuscript profile -
Open Access Article
737 - Deep Extreme Learning Machine: A Combined Incremental Learning Approach for Data Stream Classification
Javad Hamidzadeh Mona MoradiStreaming data refers to data that is continuously generated in the form of fast streams with high volumes. This kind of data often runs into evolving environments where a change may affect the data distribution. Because of a wide range of real-world applications of dat MoreStreaming data refers to data that is continuously generated in the form of fast streams with high volumes. This kind of data often runs into evolving environments where a change may affect the data distribution. Because of a wide range of real-world applications of data streams, performance improvement of streaming analytics has become a hot topic for researchers. The proposed method integrates online ensemble learning into extreme machine learning to improve the data stream classification performance. The proposed incremental method does not need to access the samples of previous blocks. Also, regarding the AdaBoost approach, it can react to concept drift by the component weighting mechanism and component update mechanism. The proposed method can adapt to the changes, and its performance is leveraged to retain high-accurate classifiers. The experiments have been done on benchmark datasets. The proposed method can achieve 0.90% average specificity, 0.69% average sensitivity, and 0.87% average accuracy, indicating its superiority compared to two competing methods. Manuscript profile -
Open Access Article
738 - Reduction of Electrical Losses of Flying-Capacitor Modular Multilevel Converter (FC-MMC) in Electric Drive Application
Ahmad Bagheri H. Iman-EiniThe flying-capacitor modular multilevel converter (FC-MMC) has been introduced as a hardware development of the conventional MMC with the aim of reducing the cell capacitor ripple voltage in the application of electrical drive at low speeds. The capacitor ripple voltage MoreThe flying-capacitor modular multilevel converter (FC-MMC) has been introduced as a hardware development of the conventional MMC with the aim of reducing the cell capacitor ripple voltage in the application of electrical drive at low speeds. The capacitor ripple voltage of the cells in this converter is reduced only by injecting high frequency circulating current between the arms. In the conventional control method of this converter, the circulating current component is injected with the aim of complete elimination of the voltage ripple at low frequencies, which leads to an unnecessary increase of the current amplitude in the converter arms. In this paper, the converter control system is modified by finding the relationship between the cell capacitor voltage ripple and the high frequency circulating current amplitude. Then, by injecting the appropriate amplitude of the circulating current, the voltage ripple is controlled in an acceptable range. It is shown that by partial compensation (instead of full elimination of the voltage ripple), in addition to reducing the amplitude of the arm currents, the losses of the electrical system are significantly reduced. The results of simulations and experiments confirm the successful performance of the proposed method. Manuscript profile -
Open Access Article
739 - Improving Register File Access Latency Tolerance in GPUs by Value Reproduction
Rahil Barati Mohammad Sadrosadati حمید سربازی آزادLarge register files reduce the performance and energy overhead of memory accesses by improving the thread-level parallelism and reducing the number of data movements from the off-chip memory. Recently, the latency-tolerant register file (LTRF) is proposed to enable hig MoreLarge register files reduce the performance and energy overhead of memory accesses by improving the thread-level parallelism and reducing the number of data movements from the off-chip memory. Recently, the latency-tolerant register file (LTRF) is proposed to enable high-capacity register files with low power and area cost. LTRF is a two-level register file in which the first level is a small fast register cache, and the second level is a large slow main register file. LTRF uses a near-perfect register prefetching mechanism that warp registers are prefetched from the main register file to the register file cache before scheduling the warp and hiding the register prefetching latency by the execution of other active warps. LTRF specifies the working set of the warps by partitioning the control flow graph into several prefetch subgraphs, called register-interval. LTRF imposes some performance overhead due to warp stall during the register prefetching. Reducing the number of register-intervals can greatly mitigate this overhead, and improve the effectiveness of LTRF. A register-interval is a subgraph of the control flow graph (CFG) where it has to be a single-entry subgraph with a limited number of registers. We observe that the second constrain contributes more in reducing the size of register-intervals. Increasing the number of registers inside the register-interval cannot address this problem as it imposes huge performance and power overhead during the register prefetching process. In this paper, we propose a register-interval-aware re-production mechanism at compile-time to increase register-interval size without increasing the number of registers inside it. Our experimental results show that our proposal improves the effectiveness of LTRF by 29%, and LTRF’s performance by about 18% (about 30% improvement over baseline GPU architecture). Moreover, our proposal reduces GPU energy and power consumption by respectively 38% and 15%, on average. Manuscript profile -
Open Access Article
740 - Design and Simulation of a Lable-Free Nano Biosensor for Detecting Molecules via Nanotube Junctionless Field Effect Transistor
Zahra AhangariBiosensors have various applications especially in medical diagnosis. In this paper, nanotube junctionless transistor is employed for label-free detection of biomolecules. The proposed device works based on dielectric modulated principle. In this transistor, the gate vo MoreBiosensors have various applications especially in medical diagnosis. In this paper, nanotube junctionless transistor is employed for label-free detection of biomolecules. The proposed device works based on dielectric modulated principle. In this transistor, the gate voltage is responsible for controlling the drain current and in case of gate capacitance variation, the drain current can be modulated. A nanogap is embedded in the gate insulator region for immobilization of biomolecules. Since each individual biomolecule has its specific dielectric constant, the accumulation of different biomolecule in the nanogap changes the dielectric constant of the nanogap, which eventually leads to the variation of gate capacitance and the drain current. Threshold voltage variation and drain current modulation are considered as two measures for detecting biomolecules and determining the biosensor’s sensitivity. The proposed device has two internal and external gates with low static power consumption as well as simpler low temperature fabrication process. One of the main advantages of the proposed device is its high selectivity and sensitivity, especially for biomolecules with low dielectric constant. Impact of critical physical and structural design parameters on the operation of the biosensor are thoroughly investigated. Gate workfunction and channel doping density are two critical parameters that affect the sensitivity of the biosensor and as a consequence, optimum values should be determined for them. Due to the low power consumption and high sensitivity, this sensor can be considered as a potential candidate for applications in nanoscale regime. Manuscript profile -
Open Access Article
741 - Evaluation of the Progression of Boxwood Blight Disease in the Forests of Northern Iran Using Satellite Image Processing Techniques
marzieh ghavidel Peiman Bayat Mohammadebrahim farashianiIn recent years, boxwood dieback has become one of the essential concerns of practitioners and managers of the natural resources of the country. To control the expansion of the factors contributing to the dieback of box trees, the early detection and preparation of dist MoreIn recent years, boxwood dieback has become one of the essential concerns of practitioners and managers of the natural resources of the country. To control the expansion of the factors contributing to the dieback of box trees, the early detection and preparation of distribution maps are required. Assessment data can play an important role in this regard. The combination of high-resolution and low-spectrum panchromatic images with low resolution is used for evaluating the extent of destruction. Also, spectral and textural features are considered simultaneously in images extracted from Landsat 8 satellite. Finally, by extracting effective features from the candidate description space with the help of genetic algorithm and using the appropriate classification in the form of simultaneous application of fuzzy clustering and maximum similarity classification of area resulted in good accuracy in 2014-2018. The coefficients obtained from the models confirm their model validation for future estimates and the possibility it usage to assess the extent of the affected areas and the evolution of progress for all regions. Manuscript profile -
Open Access Article
742 - Optimal Robust Controller Design for the Electrical Vehicle Charging Process in the Presence of Uncertainty
mahsa karami roohollah barzamini reza sharifiWireless power transmission technology with titles such as contactless power transmission, magnetic coupling power transfer, etc.are known and in fact, this method safely and reliably transmits power in such a way that does not require a mechanical connection between th MoreWireless power transmission technology with titles such as contactless power transmission, magnetic coupling power transfer, etc.are known and in fact, this method safely and reliably transmits power in such a way that does not require a mechanical connection between the source and the load. In this method, power transmission is done wirelessly using resonance induction coupling. By operating the transducer in the resonant mode, it will be possible to transfer a significant amount of power over an air distance of a few tens of centimeters, while the system efficiency is high and the voltage and current stress of the transducer are reasonable. In this paper, by presenting a method based on robust control and meta-heuristic algorithms, we improve the charging process of electric vehicles by considering uncertainty conditions. The simulation results show the better performance of the proposed controller compared to other controllers. Also, in this paper, the effect of connecting the charging station of electric vehicles to the distribution network is investigated by considering the optimal charging and discharging scheduling systems to maximize the economic profit of the vehicles and the charging station. In the proposed method, the best program for charging and discharging cars in order to maximize their profit is extracted based on genetic algorithm. According to the simulation results, optimal charging and discharging planning has reduced the value of losses to the total network energy to load the station in some trains, so that network targets such as losses and voltage deviation index are minimized and voltage stability index is maximized. In this study, minimization of losses, voltage deviation as well as maximization of voltage stability index have been investigated and the optimal location of the station has been obtained by considering these goals along with the profit of the station and vehicles. Finally, according to the results, with the planning of charging and discharging cars, in addition to providing the required charge, the profit of the station and cars has also increased. Manuscript profile -
Open Access Article
743 - A Prediction-Based Load Distribution Approach for Software-Defined Networks
Hossein Mohammadi سیداکبر مصطفویSoftware-defined networking is a new network architecture which separates the control layer from the data layer. In this approach, the responsibility of the control layer is delegated to the controller software to dynamically determine the behavior of the entire network MoreSoftware-defined networking is a new network architecture which separates the control layer from the data layer. In this approach, the responsibility of the control layer is delegated to the controller software to dynamically determine the behavior of the entire network. It results in a flexible network with centralized management in which network parameters can be well controlled. Due to the increasing number of users, the emergence of new technologies, the explosive growth of network traffic, meeting the requirements of quality of service and preventing underload or overload of resources, load balancing in software-based networks is of substantial importance. Load imbalance increases costs, reduces scalability, flexibility, efficiency, and delay in network service. So far, a number of solutions have been proposed to improve the performance and load balancing in the network, which take into account different criteria such as power consumption and server response time, but most of them do not prevent the system from entering the load imbalance mode and the risks of load imbalance. In this paper, a predictive load balancing method is proposed to prevent the system from entering the load imbalance mode using the Extreme Learning Machine (ELM) algorithm. The evaluation results of the proposed method show that in terms of controller processing delay, load balance and response time, it performs better than CDAA and PSOAP methods. Manuscript profile -
Open Access Article
744 - Low-Error and Variation-Aware Approximate Full Adders for Imprecision-Tolerant Applications
Mohammad Mirzaei سيامك محمديIn imprecision-tolerant applications such as image processing and machine learning, imprecision can be tolerated because of the nature of the application itself or the limitation of human senses. By using the approximate computation in these applications, significant po MoreIn imprecision-tolerant applications such as image processing and machine learning, imprecision can be tolerated because of the nature of the application itself or the limitation of human senses. By using the approximate computation in these applications, significant power, delay, or area reductions can be achieved. In this paper, two approximate full adders and an approximate adder, with low error are proposed. The effects of die-to-die (D2D) process variation on the threshold voltage of approximate circuits have been evaluated. For evaluating the accuracy and the variability, these approximate full adders have been used and analyzed in the ripple carry adder structure, image Sharpening and image Smoothing algorithms. In terms of power-delay-product (PDP), accuracy, and area for uniformly distributed inputs, the proposed approximate full adder 1, exhibits the best performance, and the proposed approximate full adder 2 and the proposed approximate adder, show the best peak-signal-to-noise ratio (PSNR) for real images. Manuscript profile -
Open Access Article
745 - Broadband Printed Microstrip Antenna Loaded by Wideband AMC Structure for MIMO Systems
حسین ملک پور شهرکی Ali AbolmasoumiIn this paper, a wideband printed antenna over an artificial magnetic conductor (AMC) surface is introduced which can be utilized for wireless applications such as WLAN, WiMAX, and multiple-input multiple-output (MIMO) systems. In the proposed structure, a planar AMC su MoreIn this paper, a wideband printed antenna over an artificial magnetic conductor (AMC) surface is introduced which can be utilized for wireless applications such as WLAN, WiMAX, and multiple-input multiple-output (MIMO) systems. In the proposed structure, a planar AMC surface as the antenna ground plane is used to direct the radiation pattern of the antenna, and enhancing the impedance bandwidth. The proposed antenna design is composed of a pair of printed microstrip elements fed by an E-shape feed line for coupling the elements. The bandwidth of the designed antenna includes from 4.94 GHz to 6.9 GHz with a return loss of less than -10dBforlinear polarization in C-band. The rhombic-shape AMC unit cell indicates the bandwidth of 5.24-7.15 GHz for the ±90˚ reflection phase. By adding the AMC surface into the printed antenna, a wideband structure with acceptable miniaturization and gain enhancement to 7.25 dBi is achieved. The simulated results of the antenna’s impedance properties are performed by using full-wave simulators of HFSS and CST. Also, two-element array of the proposed design are investigated for different polarizations. Based on the obtained results, the operating bandwidth includes the frequency range from5.18GHz to 6.81 GHz and the isolation between the array elements is less than -22 dB. For this purpose, the antenna arrays can be applied for MIMO systems. Manuscript profile -
Open Access Article
746 - Hierarchical Control for Accurate Power Sharing and Circulation Current Reduction in Resistive AC Microgrids Using Adaptive Virtual Impedance and Distributed Communication Links
Masoud Esmaili Mohammad HejriThis paper presents an efficient method based on the adaptive virtual impedance and distributed communication link with a hierarchical control system in the resistive AC islanding micrigrids for accurate power sharing and circulating current reduction. In existing metho MoreThis paper presents an efficient method based on the adaptive virtual impedance and distributed communication link with a hierarchical control system in the resistive AC islanding micrigrids for accurate power sharing and circulating current reduction. In existing methods, the adaptive virtual resistance can take negative values and violate the assumption of feeders’ resistive dominance based on which the droop controller is designed, and as a result, deteriorate its performance. Besides, the negative virtual resistance, with a reduction in the system overall damping, can reduce the stability margin and lead to side effects on the closed-loop system performance, especially during transients. In the proposed method, the problems associated with the negative virtual resistance are removed via the intelligent implementation of a new distributed communication link among microgrid inverters. The advantages of the proposed method include: circulating current elimination, accurate power sharing among distributed generators proportional to their rated capacities, prevention of voltage and frequency deviations from their reference values in point of power coupling (PCC) bus, guarantee of the resistive or inductive dominance of the feeder impedance in various operating points, decoupling between active and reactive powers, and as a result, guarantee of a desirable performance for droop controller in different operating points, performance and stability improvement, and finally using a simple, one-sided and a low bandwidth communication link instead of the complex, two-sided, and centralized communication system. Simulation results in MATLAB/SIMULINK environment demonstrate that the proposed control strategy has obviated effectively the shortcomings of the conventional droop and adaptive virtual impedance controllers. Manuscript profile -
Open Access Article
747 - A Novel Method Based on Non-Negative Matrix Factorization for Dimensions Reduction
Mehdi Hosseinzadeh Aghdam مرتضی آنالویی Jafar TanhaMachine learning has been widely used over the past decades due to its wide range of applications. In most machine learning applications such as clustering and classification, data dimensions are large and the use of data reduction methods is essential. Non-negative mat MoreMachine learning has been widely used over the past decades due to its wide range of applications. In most machine learning applications such as clustering and classification, data dimensions are large and the use of data reduction methods is essential. Non-negative matrix factorization reduces data dimensions by extracting latent features from large dimensional data. Non-negative matrix factorization only considers how to model each feature vector in the decomposed matrices and ignores the relationships between feature vectors. The relationships between feature vectors provide better factorization for machine learning applications. In this paper, a new method based on non-negative matrix factorization is proposed to reduce the dimensions of the data, which sets constraints on each feature vector pair using distance-based criteria. The proposed method uses the Frobenius norm as a cost function to create update rules. The results of experiments on the data sets show that the proposed multiplicative update rules converge rapidly and give better results than other algorithms. Manuscript profile -
Open Access Article
748 - A Patient Identification and Authentication Protocol to Increase Security
Afsaneh Sharafi Sepideh Adabi Ali Movaghar Salah Al-MajedToday, with the ever-expanding IoT, information technology has led the physical world to interact more with stimuli, sensors, and devices. The result of this interaction is communication "anytime, anywhere" in the real world. A research gap that can be felt in addition MoreToday, with the ever-expanding IoT, information technology has led the physical world to interact more with stimuli, sensors, and devices. The result of this interaction is communication "anytime, anywhere" in the real world. A research gap that can be felt in addition to providing a multi-layered and highly secure protocol (a protocol that simultaneously performs authentication) and at the same time has a low computational burden. Therefore, in the field of health and treatment and for the purpose of remote monitoring of patients with physical and mental disabilities (such as patients with cerebral palsy and spinal cord amputation) there is an urgent need for a very safe protocol. The protocol we propose in this study is a two-layer protocol called "Identification-Authentication" which is based on EEG and fingerprint. Also, our authentication step is the modified Diffie-Hellman algorithm. This algorithm needs to be modified due to a security problem (the presence of a third person) that the proposed method is able to authenticate the patient with very high accuracy and high speed by receiving the patient's fingerprint and EEG signal. The proposed protocol was evaluated using data from 40 patients with spinal cord injury. The implementation results show more security of this protocol, Validity of the proposed protocol is checked and the processing time of authentication stage is decrease to 0.0215 seconds. Manuscript profile -
Open Access Article
749 - Double Recycling Folded Cascode Op-Amp Using Feed-Forward Capacitor Coupling Driving
Mohammad R. Ali Ali Khamesi NaeiniA double recycling Op-Amp based on a simple recycling folded cascode Op-Amp is presented. The proposed Op-Amp has significantly improved performance compared to a recycling folded cascode. In the proposed Op-Amp, those cascode output current sources of recycling folde MoreA double recycling Op-Amp based on a simple recycling folded cascode Op-Amp is presented. The proposed Op-Amp has significantly improved performance compared to a recycling folded cascode. In the proposed Op-Amp, those cascode output current sources of recycling folded cascode that still have a constant value have been considered and have taken on a dynamic state through capacitive couplings in the path created between the input and output of the amplifier. DC gain, unity-gain bandwidth, and slew rate have been improved compared to the previous amplifier at the same power consumption. Simulation results using the 0.18μm CMOS technology show a DC gain enhancement of 6dB, 35% improvement in slew rate, and almost a 30% increase the bandwidth compared to the traditional recycling folded cascode Op-Amp. Also, smaller input-referred noise is achieved. Simulated results of proposed circuit show the values of SR, power consumption and DC gain are about 93.5 V/µs, 1.02mW and 68.3 dB respectively. Manuscript profile -
Open Access Article
750 - Outlier Detection in High Dimensional Data Using Entropy-Based Locally Relevant Subspace Selection
Mahboobeh Riahi Madvar Ahmad Akbari B. NasersharifOne of the challenges of high dimensional outlier detection problem is the curse of dimensionality which irrelevant dimensions (features) lead to hidden outliers. To solve this problem, some dimensions that contain valuable information to detect outliers are searched to MoreOne of the challenges of high dimensional outlier detection problem is the curse of dimensionality which irrelevant dimensions (features) lead to hidden outliers. To solve this problem, some dimensions that contain valuable information to detect outliers are searched to make outliers more prominent and detectable by mapping the dataset into the subspace which is constituted of these relevant dimensions/features. This paper proposes an outlier detection method in high dimensional data by introducing a new locally relevant subspace selection and developing a local density-based outlier scoring. First, we present a locally relevant subspace selection method based on local entropy to select a relevant subspace for each data point due to its neighbors. Then, each data point is scored in its relevant subspace using a density-based local outlier scoring method. Our adaptive-bandwidth kernel density estimation method eliminates the slight difference between the density of a normal data point and its neighbors. Thus, normal data are not wrongly detected as outliers. At the same time, our method underestimates the actual density of outlier data points to make them more prominent. The experimental results on several real datasets show that our local entropy-based subspace selection algorithm and the proposed outlier scoring can achieve a high accuracy detection rate for the outlier data. Manuscript profile -
Open Access Article
751 - A New Heuristic for Deadlock Detection in Safety Analysis of Software Systems
عین الله پیراThe safety analysis of software systems, especially safety-critical ones, should be performed exactly because even a minor failure in these systems may result in disaster consequences. Also, such analysis must be done before implementation, i.e. the design step and in t MoreThe safety analysis of software systems, especially safety-critical ones, should be performed exactly because even a minor failure in these systems may result in disaster consequences. Also, such analysis must be done before implementation, i.e. the design step and in the model level. Model checking is an exact and mathematical-based way that gets a model of a system and analyzes it through exploring all reachable states of the model. Due to the complexity of some systems and their models, this way may face the state space explosion problem, i.e. it cannot explore all available states. A solution to solve this problem in these systems is that model checking tries to refute them, instead of verifying them, by finding errors such as deadlock (if available).Although, a heuristic has been previously proposed to find a deadlock in the model's state space and it has been applied in several simple heuristic search and evolutionary algorithms, its detection speed has been low. In this paper, we propose a novel heuristic to detect a deadlock in the model's state space, and test and compare its detection speed by applying it in several simple heuristic search algorithms such as iterative deepening A*, beam search, and evolutionary algorithms such as genetic, particle swarm optimization, and Bayesian optimization. Comparison results confirm that the new heuristic can detect a deadlock in less time than the previous heuristic. Manuscript profile -
Open Access Article
752 - Mutual Continuous Lightweight Authentication Based on Node Prioritization Using Traffic Rates for Internet of Things
reza sarabi miyanaji sam jabbehdari nasser modiriToday, billions of devices are connected via the Internet of Things, often through insecure communications. Therefore, security and privacy issues of these devices are a major concern. Since devices in IoT are typically resource-constrained devices, the security solutio MoreToday, billions of devices are connected via the Internet of Things, often through insecure communications. Therefore, security and privacy issues of these devices are a major concern. Since devices in IoT are typically resource-constrained devices, the security solutions of this environment in terms of processing and memory must be secure and lightweight. However, many existing security solutions are not particularly suitable for IoT due to high computation. So there is a need for a lightweight authentication protocol for IoT devices. In this paper, a mutual lightweight authentication protocol between nodes with limited resources and IoT servers is introduced that uses node prioritization based on traffic rates. This scheme is light due to the use of lightweight XOR and Hash operations. The proposed is resistant to cyber-attacks such as eavesdropping attack, and replay attack. The proposed is also secure using the AVISPA tool in the Dolev-Yao threat model. The security risks of this scheme are low compared to other lightweight methods. In addition, the proposal is compared with existing authentication schemes reduces the computational cost, protects privacy through anonymity of nodes, and provides forward secrecy. In our method, the execute time of authentication is reduced by 15% compared to the other methods. Manuscript profile -
Open Access Article
753 - Analysis of Slew Rate and Settling Time in Two Stage CMOS Operational Amplifiers with Cascode Compensation
hannane Gholamntaj habib Adarang seyed saleh Mohseni seyed saleh GhoreishiSlew rate and settling time are the important parameters in opamps with feedback. In this paper, the slew rate and settling time of the fully differential two stages folded cascade architecture amplifier with cascade compensation is analyzed. An important characteristic MoreSlew rate and settling time are the important parameters in opamps with feedback. In this paper, the slew rate and settling time of the fully differential two stages folded cascade architecture amplifier with cascade compensation is analyzed. An important characteristic of the proposed analytical model is that the behavior of the transistors is examined in detail after applying the step in the input, and it is shown that the settling time as well as slew rate would depend on the size of the input step. The performed analysis can be beneficial for design and manual calculations in integrated circuits. Moreover, circuit level simulation is used to validate the analytical results with particular emphasis on slew rate and settling time. Simulations results show excellent conformance between the analytical equations and the simulation results. Manuscript profile -
Open Access Article
754 - Detection and Mitigation of a Combined Cyber Attack on Automatic Generation Control
Tina Hajiabdollah H. Seifi Hamed DelkhoshRecent advances in power system monitoring and control require communication infrastructure to send and receive measurement data and control commands. These cyber-physical interactions, despite increasing efficiency and reliability, have exposed power systems to cyber a MoreRecent advances in power system monitoring and control require communication infrastructure to send and receive measurement data and control commands. These cyber-physical interactions, despite increasing efficiency and reliability, have exposed power systems to cyber attacks. The Automatic Generation Control (AGC) is one of the most important control systems in the power system, which requires communication infrastructure and has been highly regarded by cyber attackers. Since a successful attack on the AGC, not only has a direct impact on the system frequency, but can also affect the stability and economic performance of the power system. Therefore, understanding the impact of cyber attacks on AGC and developing strategies to defend against them have necessity and research importance. In most of the research in the field of attack-defense of AGC, the limitations of AGC in modeling such as governor dead band and communication network transmission delay have been ignored. On the other hand, considering two cyber attacks on the AGC and proposing a way to defend against them simultaneously, have not been considered. In this paper, while using the improved AGC model including governor dead band and communication network transmission delay, the effect of two attacks - data injection attack (FDI) and delay attack which are the most important cyber attacks on AGC - has been investigated. Also, the simultaneous effect of these two attacks is discussed as a combined cyber attack. The Kalman filter-based three-step defense method has been proposed to detect, estimate and mitigate the impact of the attacks and its effectiveness has been tested on the two-area AGC system. Manuscript profile -
Open Access Article
755 - Iranian Dastgah Music Recognition Based on Notes Sequence Extraction and Use of LSTM Networks
سینا غضنفری پور M. Khademi Abbas Ebrahimi moghadamIranian "Dastgah" music classification by computer is a very interesting yet complex and challenging topic for those who are interested in Iranian Dastgah music. The aforementioned problem is important, firstly, due to its many applications in different areas such as co MoreIranian "Dastgah" music classification by computer is a very interesting yet complex and challenging topic for those who are interested in Iranian Dastgah music. The aforementioned problem is important, firstly, due to its many applications in different areas such as composing and teaching music, and secondly, because of the needs of ordinary people to computer to detect the Dastgah. This paper presents a method for recognition of the genre (Dastgah) and subgenre (sub-Dastgah) of Iranian music based on sequential note extraction, hierarchical classification, and the use of LSTM networks. In the proposed method, the music track is first classified into one of the three general categories. The first category includes only "Mahour" Dastgah, the second category includes "Shour" and "Nava", and the third category includes "Homayoun", "Segah" and "Chahargah". Then, for each category, depending on its type, a different number of classifiers are applied until one of the 6 Dastgah and 11 sub-Dastgah of Iranian music are recognized. This research is not limited to any particular style of playing or instruments, it is also not affected by neither the speed nor the techniques of player. The labeled tracks in the "Arg" database, which is created for this research, are solo. However, some of them are also played by percussion instruments (such as the Tombak) along with melodic instruments. The results show that recognition of 6 main Dastgah and 11 sub-Dastgah have been approved by an average accuracy of 74.5% and 66.35%, respectively, which is more promising compared to other few similar studies. Manuscript profile -
Open Access Article
756 - Robust Finite-Time Chattering Free Sliding Mode Adaptive Impedance controller in Remote Control System in Presence of Random Delay
Abolfazl Kamali Ardakani Hadi SafdarkhaniRemote control of robots is one of the most relevant and practical fields in robotics. Most of the control structures of remote operation systems seek to achieve transparency and stability at the same time, which the simultaneous achievement of the both, considering the MoreRemote control of robots is one of the most relevant and practical fields in robotics. Most of the control structures of remote operation systems seek to achieve transparency and stability at the same time, which the simultaneous achievement of the both, considering the uncertainty and disturbances in the system and random delay in the communication channel is very challenging. So far, many researchers have used position, speed, force or impedance information to provide various control methods, but none of these methods have achieved complete transparency and robust stability in the presence of random delay and uncertainties and disturbances and compromises between them should be made. In this paper, using a new method, a control structure including sliding mode control, adaptive control and impedance control is presented. This method has been simulated by Simulink of MATLAB software and it has been shown that this method is able to establish ideal transparency and ensure robust stability in the system with disturbances and uncertainties in the presence of random delay in the network. Manuscript profile -
Open Access Article
757 - A Two-Step Stochastic Linear Programming Approach for Microgrid Resources and Energy Storage Management with Real-Time Pricing Program Using Salp Swarm Optimization Algorithm
Mohsen Sarami مجيد معظمي غضنفر شاهقلیانIntegrating renewable resources to provide local load has created a concept called microgrid. With the widespread introduction of microgrids, energy management and system utilization and resources in the electricity market are important tasks of microgrid management. In MoreIntegrating renewable resources to provide local load has created a concept called microgrid. With the widespread introduction of microgrids, energy management and system utilization and resources in the electricity market are important tasks of microgrid management. In this paper, the problem of microgrid utilization is modeled taking into account economic, technical and uncertainties related to power consumption, wind speed and solar radiation in electricity market conditions. One of the most important issues in the electricity market is the discussion of the participation of units in real price conditions. In this paper, a framework for the exploitation of electricity and the consumption of controllable loads through integrated utilization of distributed energy sources of uncertainty is presented from a consumer perspective. The optimization problem is a two-step stochastic linear programming that minimized the cost of microgrid operation and expected cost of consumers considering the consumer’s requirement for controllable loads in the desire time interval and distribution company constraints that solved by using Salp swarm optimization algorithm. RBT and IBR tariffs are employed for modeling retail power market for better reflection of wholesale price volatility and avoid of the concurrent use of consumers. In this method price announced to the consumers by retailers only is limited specific later hours instead of the entire operation period. In this condition any timing of controllable loads need to price forecasting, while this forecasting have some uncertainties. These uncertainties are modeled using Monte Carlo method for stochastic price variable scenario generation. MATLAB software is employed for simulation and verification of the proposed method. Manuscript profile -
Open Access Article
758 - Robust Planning of False Data Injection Attack on Electricity Markets in Smart Grids
Hamed Badrsimaei R. Hooshmand Soghra NobakhtianFalse data injection attack (FDIA) is a destructive cyber threat to the economic performance of electricity markets in smart grids. A cyber attacker can make a huge financial profit by implementing an FDIA through penetrating the virtual transactions of the electricity MoreFalse data injection attack (FDIA) is a destructive cyber threat to the economic performance of electricity markets in smart grids. A cyber attacker can make a huge financial profit by implementing an FDIA through penetrating the virtual transactions of the electricity markets and manipulating electricity prices. In this paper, a new approach to planning an absolutely stealthily FDIA is presented with the aim of achieving maximum financial profit from the perspective of a cyber attacker participating in virtual transactions from two markets of day-ahead (DA) and real-time (RT). A common hypothesis in studies of FDIAs against electricity markets is that the attacker has complete information about the smart grid. But the fact is that the attacker has limited resources and can hardly access all the network information. This paper proposes a robust approach in designing an attack strategy under incomplete network information conditions. In particular, it is assumed that the attacker has uncertainties about the network modeling matrices. The validity of the proposed method is evaluated based on the IEEE 14-bus standard system using the Matpower tool. Numerical results confirm the relative success of the proposed attack in cases of varying degrees of incomplete information. Manuscript profile -
Open Access Article
759 - Stochastic Planning of Resilience Enhancement for Electric Power Distribution Systems against Extreme Dust Storms
M. Haghshenas R. Hooshmand M. GholipourResilience in power systems refers to the system's ability to withstand severe disturbances with a low probability of occurrence. Because in recent years extreme dust storms have caused severe damage to Iran's electricity industry, especially in the south and southwest, MoreResilience in power systems refers to the system's ability to withstand severe disturbances with a low probability of occurrence. Because in recent years extreme dust storms have caused severe damage to Iran's electricity industry, especially in the south and southwest, in this paper proposed a new scenario-based stochastic planning model for enhancement of power distribution systems resilience against extreme dust storms. In proposed model, in the first stage, the investment costs to improve the distribution system resilience against extreme dust storms are minimized due to the financial constraints, and in the second stage, the expected operating costs in dust storm conditions are minimized due to the operating constraints. Because network's insulation equipment are major cause of distribution system vulnerabilities in the dust storms, measures in the planning stage include replacement of porcelain insulators with silicon-rubber type, installation of automatic tie switches and installation of emergency generators. In the second stage, the measures are divided into preventive actions and corrective actions, and coordination between stages 1 and 2 is implemented in such a way that the results of each stage depend on the decision variables of the other stage. The simulation results for IEEE 33-bus test system and a 209 bus radial distribution network located in Khuzestan province, Iran, confirm the efficiency of the proposed model in different financial conditions. Manuscript profile -
Open Access Article
760 - Detection and Recovery of Corrupted Images After High Rate of Tampering Attacks
Faranak Tohidi Mohammad Reza HooshmandaslIn recent years, illegally copying digital images and even manipulating them, without great loss of quality and at a low cost has been made possible. Watermarking has recently been developed as one of the methods to detect that tampering has occurred and even enable som MoreIn recent years, illegally copying digital images and even manipulating them, without great loss of quality and at a low cost has been made possible. Watermarking has recently been developed as one of the methods to detect that tampering has occurred and even enable some recovery of the original images. However, there are still many issues to resolve in providing an effective watermark that can detect and recover a wide range of manipulations. Furthermore, the accuracy of detecting and the capability of the recovery of the original images by existing methods are still not at an acceptable level. These problems are more critical when certain high-rate manipulation attacks occur. In this paper, a watermarking method will be introduced that not only is able to detect any tampering, but also can successfully recover the original images in high quality, even at high tampering rates. In this method, Singular Value Decomposition (SVD) is used to detect tampering and Optimal Iterative Block Truncation Coding (OIBTC) has also been applied to recover lost data. This paper proposes a powerful way to increase detection sensitivity while increasing watermark resistance for the effective recovery of corrupted images. The results prove the superiority of the proposed method over current methods.92% of tasks are executed successfully in the edge environment. Manuscript profile -
Open Access Article
761 - Load Balancing in Fog Nodes using Reinforcement Learning Algorithm
niloofar tahmasebi pouya Mehdi-Agha SarramFog computing is an emerging research field for providing cloud computing services to the edges of the network. Fog nodes process data stream and user requests in real-time. In order to optimize resource efficiency and response time, increase speed and performance, task MoreFog computing is an emerging research field for providing cloud computing services to the edges of the network. Fog nodes process data stream and user requests in real-time. In order to optimize resource efficiency and response time, increase speed and performance, tasks must be evenly distributed among the fog nodes. Therefore, in this paper, a new method is proposed to improve the load balancing in the fog computing environment. In the proposed algorithm, when a task is sent to the fog node via mobile devices, the fog node using reinforcement learning decides to process that task itself, or assign it to one of the neighbor fog nodes or cloud for processing. The evaluation shows that the proposed algorithm, with proper distribution of tasks between nodes, has less delay to tasks processing than other compared methods. Manuscript profile -
Open Access Article
762 - Detector Design & Power Allocation of Frequency Diverse Phased Multi Input Multi Output Radar within Nonhomogeneous Environments
Hamid Reza Fotoohi Firouzabad Seyed Mehdi Hosseini Andargoli Hossein Ghanei Yakhdan J. AboueiIn recent years, Phased-Multiple-Input, Multiple-Output radars (PMRs) have attracted great interest. PMR can combine the advantages of both MIMO radar and phased array radar. Here, PMR transmits orthogonal signals from all subarrays to provide both waveform frequency di MoreIn recent years, Phased-Multiple-Input, Multiple-Output radars (PMRs) have attracted great interest. PMR can combine the advantages of both MIMO radar and phased array radar. Here, PMR transmits orthogonal signals from all subarrays to provide both waveform frequency diversity and high coherent processing gain. In this paper dealt with detector design in the presence of heterogeneous clutter based on the unknown scattering coefficients for PMR. Then, detection probability and false-alarm probability are computed based on the derived optimum detector. At the end, the power allocation problem is investigated analytically. The numerical simulations show that obtained optimal detector is joint spatial-temporal filter, which, the clutters are effectively weakened in PMR. Furthermore, simulation results illustrate that proposed power allocation algorithm improve detection performance of PMR in comparison with PR and equal power PMR. Manuscript profile -
Open Access Article
763 - Sum Rate and Energy Efficiency Maximization in a Cognitive Radio Network with a Successive Relay Primary User
elahe maddah Mohammad lariIn this paper, we propose a cognitive radio network which consists of a number of secondary users and one primary user. The primary user utilized a successive relay performance. The successive relaying technique creates a full duplex relay performance by two half duplex MoreIn this paper, we propose a cognitive radio network which consists of a number of secondary users and one primary user. The primary user utilized a successive relay performance. The successive relaying technique creates a full duplex relay performance by two half duplex relays, which improves spectral efficiency. In the presence of secondary users, we use successive relay technique in the primary user to ensure its acceptable performance. Also, the sum rate of secondary users is increased. The challenges of this network are inter-relay interference and inter user interference. The interference alignment method is utilized to eliminate the interferences in the successive relay technique and in the cognitive radio network. Besides, the minimum transmitted power of the primary user is derived to guarantee its quality of service requirement. Two power allocations algorithms are proposed to maximize the sum rate of secondary users and the energy efficiency of the network. In both power allocations algorithms, satisfying the quality of service of the primary user is considered. The closed-form solutions of these algorithms are studied. The fractional programing approach was employed to solve the energy efficiency optimization in two steps. Manuscript profile -
Open Access Article
764 - Angle Robust Reflective Subtractive Color Filter Using Titanium Dioxide Metasurface and Aluminum Mirrors
Zahra NasehiRecently, color filters have been used for high quality resolution color imaging and printing in subwavelength scale. In this paper, a reflective subtractive color filter with excellent color contrast has been demonstrated. In the proposed filter, titanium dioxide nanoc MoreRecently, color filters have been used for high quality resolution color imaging and printing in subwavelength scale. In this paper, a reflective subtractive color filter with excellent color contrast has been demonstrated. In the proposed filter, titanium dioxide nanocuboids have been integrated with aluminum mirrors at the top and bottom of them. Due to the creation of magnetic dipole in titanium dioxide nanocuboids, a resonance occurs in the visible spectrum, which the resonance wavelength could be tuned over the whole visible range through the adjustment of the nanocuboid side size. By utilizing aluminum patches on both sides of the nanocuboids, the efficiency of more than 70% and the bandwidth of less than 35 nm have been attained. The proposed filter exhibits high incident angular tolerance such that by increasing the incident light angle from 0 to 60 degree, the resonance wavelength has very poor variation and maintains the same bandwidth and efficiency. Also, the proposed filter is polarization-independent due to its symmetric geometry. These advantages facilitate the function of the suggested filter in imaging and displays with high brightness. Manuscript profile -
Open Access Article
765 - Proposing a New High-Gain Switched-Capacitor Pulsed-Power Converter Using Low Input Voltage Source
sogand nikkhah Mohammad Rezanejad Reza khosraviIn this paper a new topology of pulsed-power converter to generate high-voltage pulses by low-input source is proposed. The proposed high step-up converter can generate high output voltage with few number of elements and stages. This converter which is based on switch-c MoreIn this paper a new topology of pulsed-power converter to generate high-voltage pulses by low-input source is proposed. The proposed high step-up converter can generate high output voltage with few number of elements and stages. This converter which is based on switch-capacitor structure is self-balanced and can be used in portable pulsed power supply. To show the validity of the proposed converter operation, a prototype of the proposed topology in the laboratory was constructed. The results show proper operation of the converter. Manuscript profile -
Open Access Article
766 - A Step towards All-Optical Deep Neural Networks: Utilizing Nonlinear Optical Element
Aida Ebrahimi Dehghan Pour S. K.In recent years, optical neural networks have received a lot of attention due to their high speed and low power consumption. However, these networks still have many limitations. One of these limitations is implementing their nonlinear layer. In this paper, the implement MoreIn recent years, optical neural networks have received a lot of attention due to their high speed and low power consumption. However, these networks still have many limitations. One of these limitations is implementing their nonlinear layer. In this paper, the implementation of nonlinear unit for an optical convolutional neural network is investigated, so that using this nonlinear unit, we can realize an all-optical convolutional neural network with the same accuracy as the electrical networks, while providing higher speed and lower power consumption. In this regard, first of all, different methods of implementing optical nonlinear unit are reviewed. Then, the impact of utilizing saturable absorber, as the nonlinear unit in different layers of CNN, on the network’s accuracy is investigated, and finally, a new and simple method is proposed to preserve the accuracy of the optical neural networks utilizing saturable absorber as the nonlinear activating function. Manuscript profile -
Open Access Article
767 - An Intelligent Overload Controller Using in Next Generation Networks
مهدی خزائیSIP is considered as a signaling protocol for IP multimedia subsystem (IMS) and IMS is introduced as the next generation networking platform. Unlike positive features such as text-based, IP-based, data-independent, support mobility and end-to-end, SIP lacks a proper ove MoreSIP is considered as a signaling protocol for IP multimedia subsystem (IMS) and IMS is introduced as the next generation networking platform. Unlike positive features such as text-based, IP-based, data-independent, support mobility and end-to-end, SIP lacks a proper overload control mechanism. Hence, this challenge will cause the widespread users of next generation networks to loss quality of service. IMS is a complex network consisting of subsystems, interacting with each other. As a result, multi-agent systems can be a useful tool to solve the IMS overload. Therefore, each IMS server is considered as an intelligent agent with learning and negotiation ability with other agents while maintaining autonomy therefore, the overload is eliminated by communication and knowledge transferred between agents. In this paper, multi-agent system and their properties presents a hop-by-hop elimination-based method which simulation results show performance improvement compared to known methods. Manuscript profile -
Open Access Article
768 - Design and Simulation of an ESIW H-plane Horn Antenna with High Gain and Improved Bandwidth
سید حسین حقیرالسادات محمدحسن نشاطيIn this paper by using the radiation slots, the half power beam width (HPBW) of the SIW horn antenna is reduced in E-plane and the radiation pattern is improved. In addition to keeping the dimensions of the structure constant, these slots can have a significant effect o MoreIn this paper by using the radiation slots, the half power beam width (HPBW) of the SIW horn antenna is reduced in E-plane and the radiation pattern is improved. In addition to keeping the dimensions of the structure constant, these slots can have a significant effect on the characteristics of the antenna. Also placing the reflector plate at a suitable distance from aperture and slots leads to improve side lobe levels (SLLs) and front to back ration (FTBR). Then, to improve the impedance matching and increase the bandwidth of the antenna, the dielectric of the structure is completely removed and non-radiation slots added to the upper and lower plate of the antenna. Removing the insulation, increasing the bandwidth of the antenna compared to a conventional SIW horn and adding radiation slots significantly improves the gain of the antenna. The simulation results shows that the proposed antenna in this paper covers the frequency range of 27.2 GHz to 28.3 GHz and its gain changes between 10.1 dBi to 15.3 dBi with 98% radiation efficiency in this range. Finally, in order to increase the gain of the antenna, a two-dimensional array of the proposed antenna with suitable feeding structure is designed in the H-plane. Manuscript profile -
Open Access Article
769 - A New Measure for Partitioning of Block-Centric Graph Processing Systems
Masoud Sagharichian Morteza Alipour LangouriBlock-centric graph processing systems have received significant attention in recent years. To produce the required partitions, most of these systems use general-purpose partitioning methods. As a result, the performance of them has been limited. To face this problem, s MoreBlock-centric graph processing systems have received significant attention in recent years. To produce the required partitions, most of these systems use general-purpose partitioning methods. As a result, the performance of them has been limited. To face this problem, special partitioning algorithms have been proposed by researchers. However, these methods focused on traditional partitioning measures like the number of cutting-edges and the load-balance. In return, the power of block-centric graph processing systems is due to unique characteristics that are focused on the design of them. According to basic and important characteristics of these systems, in this paper two new measures are proposed as partitioning goals. To the best of our knowledge, the proposed method is the first work that considers the diameter and size of the high-level graph as optimization factors for partitioning purposes. The evaluation of the proposed method over real graphs showed that we could significantly reduce the diameter of the high-level graph. Moreover, the number of cutting-edges of the proposed method are very close to Metis, one of most popular centralized partitioning methods. Since the number of required supersteps in block-centric graph processing systems mainly depends on the diameter of the high-level graph, the proposed method can significantly improve the performance of these systems. Manuscript profile -
Open Access Article
770 - Finding the Cause of Metal Oxide Surge Arresters' Failures in Mountainous Areas of Khuzestan Province; Engineering Experiences of Analyzing Field Results in a Very Large 33 kV Network
Elaheh Mashhour Seyed Hamidreza AlemohammadThis paper presents the findings of a practical study to detect the degradation factors of metal-oxide surge arresters in a distribution network in the mountainous region of Izeh, which experiences two warm and temperate climates annually. The surge arresters have defec MoreThis paper presents the findings of a practical study to detect the degradation factors of metal-oxide surge arresters in a distribution network in the mountainous region of Izeh, which experiences two warm and temperate climates annually. The surge arresters have defected in both periods when the network operating conditions and weather conditions are completely different. However, the appearance of the defected surge arresters in these periods is different. In this paper, by simulating the network, its permanent and transient state behaviors are analyzed. Based on the results and environmental conditions, the appropriate arresters' specifications for the network are obtained and compared with existing arresters. By considering different scenarios for ground resistance of arresters, the changes in energy absorbed by arresters are evaluated and the results are compared with those obtained in the practical reduction of ground resistance of some of arresters. By adding several arresters to the network, changes in the absorbed energy of arresters are investigated. Based on the research findings, the causes of arresters' failures in both warm and temperate periods are investigated. Finally, the findings of this research are validated by comparing the simulation results with field events, and some solutions are presented to overcome the problems. Manuscript profile -
Open Access Article
771 - Novel AI-Based Metaheuristic Optimization Approaches for Designing INS Navigation Systems
علی محمدی Farid Sheikholeslam Mehdi EmamiSoft computing techniques in engineering sciences have covered a large amount of research. Among them is the design and optimization of navigation systems for use in land, sea, and air transportation systems. Therefore, in this paper, an attempt is made to take advantag MoreSoft computing techniques in engineering sciences have covered a large amount of research. Among them is the design and optimization of navigation systems for use in land, sea, and air transportation systems. Therefore, in this paper, an attempt is made to take advantage of novel approaches of intelligent metaheuristic optimization for designing integrated navigation systems. For this purpose, the inclined planes system optimization algorithm with several modified and new versions have been used along with two well-known methods of genetic algorithm and particle swarm optimization. Considerations are made on an INS/GNSS problem with IMU MEMS inertia measurement modules. Process and measurement noise covariance matrices are considered as design variables and the sum of mean-squares-error as an objective function in the form of a single-objective minimization problem. Outputs are presented in terms of statistical and performance indicators such as runtime, fitness, convergences, angular-velocity accuracy, latitude, longitude, altitude, roll, pitch, yaw, and routing along with the ranking of algorithms. The overall assessment indicated the correctness of the performance and the relative superiority of the IPO and IIPO over the competitors and competitive performance of the assumed algorithms in comparison with the volume of considerations and calculations of the base problem. Manuscript profile -
Open Access Article
772 - Generation of Persian sentences By Generative Adversarial Network
Nooshin riahi Sahar JandaghyText generation is a field of natural language processing. Text generation enables the system to produce comprehensive, .grammatically correct texts like humans. Applications of text generation include image Captioning, poetry production, production of meteorological re MoreText generation is a field of natural language processing. Text generation enables the system to produce comprehensive, .grammatically correct texts like humans. Applications of text generation include image Captioning, poetry production, production of meteorological reports and environmental reports, production of business reports, automatic text summarization, .With the appearance of deep neural networks, research in the field of text generation has change to use of these networks, but the most important challenge in the field of text generation using deep neural networks is the data is discrete, which has made gradient inability to transmit. Recently, the use of a new approach in the field of deep learning, called generative adversarial networks (GANs) for the generation of image, sound and text has been considered. The purpose of this research is to use this approach to generate Persian sentences. In this paper, three different algorithms of generative adversarial networks were used to generate Persian sentences. to evaluate our proposed methods we use BLEU and self-BLEU because They compare the sentences in terms of quality and variety. Manuscript profile -
Open Access Article
773 - Design, Simulation and Implementation of Compact and Wideband Microwave Filter Using Semi-Hexagonal Cavity by Substrate Integrated Waveguide (SIW) Technology
m.h. n. Rasoul RahmaniIn this paper, a compact wideband microwave filter in X band using substrate integrated waveguide technology is designed, simulated and implemented. At first, the structure of hexagonal and semi-hexagonal microwave resonators is studied and their resonate modes, resonan MoreIn this paper, a compact wideband microwave filter in X band using substrate integrated waveguide technology is designed, simulated and implemented. At first, the structure of hexagonal and semi-hexagonal microwave resonators is studied and their resonate modes, resonance frequencies and field distribution inside these resonators are investigated. Then, a second order Chebyshev filter is designed by coupling matrix of two semi-hexagonal cavities with center frequency of 10 GHz and fractional bandwidth of 20%. The first designed filter based on theoretical modeling is simulated by a full wave simulator and the geometrical parameters of the structure are adjusted for the required response. A prototype of the designed filter is implemented by TLY031 substrate and its characteristics are successfully measured. The results show that the measured results agree well with those obtained by simulation. The center frequency of the implemented filter is 8.7 GHz and it provides 27.3% bandwidth, with maximum insertion loss of 2.1 dB. Manuscript profile -
Open Access Article
774 - Damping Controller Design Based on Identified Model Using Wide-Area Phasor Measurements Data
Azin Atarodi Hemin GOLPIRA Hassan BevraniContinuous changes besides increasing complexities of modern power systems cause emergence of new challenges in modeling of power systems. Nowadays, with development of wide-area monitoring systems, data from the overall system can be used to identify and estimate model MoreContinuous changes besides increasing complexities of modern power systems cause emergence of new challenges in modeling of power systems. Nowadays, with development of wide-area monitoring systems, data from the overall system can be used to identify and estimate model for power systems. This paper focuses on power system stabilizer tuning using the derived measurements-based model. The derived low-order model includes dynamic characteristics of inter-area dominant modes and can be used to design the damping controller and evaluate its effectiveness in power system studies. The controller can be reinterpreted as power system stabilizer and may be designed in two different methods of i) robust and ii) Ziegler-Nichols. The numerical results show the effectiveness of this approach in improving the small signal stability behavior of two-area 4-machine system using measured data, obtained from time domain simulation in MATLAB software. Manuscript profile -
Open Access Article
775 - Provide a Personalized Session-Based Recommender System with Self-Attention Networks
Azam Ramazani A. ZarehSession-based recommender systems predict the next behavior or interest of the user based on user behavior and interactions in a session, and suggest appropriate items to the user accordingly. Recent studies to make recommendations have focused mainly on the information MoreSession-based recommender systems predict the next behavior or interest of the user based on user behavior and interactions in a session, and suggest appropriate items to the user accordingly. Recent studies to make recommendations have focused mainly on the information of the current session and ignore the information of the user's previous sessions. In this paper, a personalized session-based recommender model with self-attention networks is proposed, which uses the user's previous recent sessions in addition to the current session. The proposed model uses self-attention networks (SANs) to learn the global dependencies among all session items. First, SAN is trained based on anonymous sessions. Then for each user, the sequences of the current session and previous sessions are given to the network separately, and by weighted combining the ranking results from each session, the final recommended items are obtained. The proposed model is tested and evaluated on real-world Reddit dataset in two criteria of accuracy and mean reciprocal rank. Comparing the results of the proposed model with previous approaches indicates the ability and effectiveness of the proposed model in providing more accurate recommendations. Manuscript profile -
Open Access Article
776 - Introducing Intelligent Mutation Method Based on PSO Algorithm to Solve the Feature Selection Problem
Mahmoud Parandeh Mina Zolfy Lighvan jafar tanhaToday, with the increase in data production volume, attention to machine learning algorithms to extract knowledge from raw data has increased. Raw data usually has redundant or irrelevant features that affect the performance of learning algorithms. Feature selection alg MoreToday, with the increase in data production volume, attention to machine learning algorithms to extract knowledge from raw data has increased. Raw data usually has redundant or irrelevant features that affect the performance of learning algorithms. Feature selection algorithms are used to improve efficiency and reduce the computational cost of machine learning algorithms. A variety of methods for selecting features are provided. Among the feature selection methods are evolutionary algorithms that have been considered because of their global optimization power. Many evolutionary algorithms have been proposed to solve the feature selection problem, most of which have focused on the target space. The problem space can also provide vital information for solving the feature selection problem. Since evolutionary algorithms suffer from the pain of not leaving the local optimal point, it is necessary to provide an effective mechanism for leaving the local optimal point. This paper uses the PSO evolutionary algorithm with a multi-objective function. In the proposed algorithm, a new mutation method that uses the particle feature score is proposed along with elitism to exit the local optimal points. The proposed algorithm is tested on different datasets and examined with existing algorithms. The simulation results show that the proposed method has an error reduction of 20%, 11%, 85%, and 7% in the Isolet, Musk, Madelon, and Arrhythmia datasets, respectively, compared to the new RFPSOFS method. Manuscript profile -
Open Access Article
777 - Increasing Image Quality in Image Steganography Using Genetic Algorithm and Reversible Mapping
Saeed TorabiTorbati مرتضی خادمی عباس ابراهیمی مقدمOne of the evaluation methods for image steganography is preserving cover image quality and algorithm imperceptibility. Placing hidden information should be done in such a way that there is minimal change in quality between the cover image and the coded image (stego ima MoreOne of the evaluation methods for image steganography is preserving cover image quality and algorithm imperceptibility. Placing hidden information should be done in such a way that there is minimal change in quality between the cover image and the coded image (stego image). The quality of the stego image is mainly influenced by the replacement method and the amount of hidden information or the replacement capacity. This can be treated as an optimization problem and a quality function can be considered for optimization. The variables of this function are the mappings applied to the cover image and the hidden information and location of the information. In the proposed method, by genetic algorithm and using the two concepts of targeted search and aimless search, the appropriate location and state for placement in the least significant bits of the cover image are identified. In this method, hidden information can be extracted completely and without error. This feature is important for management systems and cloud networks that use steganography to store information. Finally, the proposed method is tested and the results are compared with other methods in this field. The proposed method, in addition to maintaining the stego image quality, which is optimized based on PSNR, has also shown good performance in examining histogram and NIQE statistical criteria. Manuscript profile -
Open Access Article
778 - Semi-Supervised Self-Training Classification Based on Neighborhood Construction
mona emadi jafar tanha Mohammadebrahim Shiri Mehdi Hosseinzadeh AghdamUsing the unlabeled data in the semi-supervised learning can significantly improve the accuracy of supervised classification. But in some cases, it may dramatically reduce the accuracy of the classification. The reason of such degradation is incorrect labeling of unlabe MoreUsing the unlabeled data in the semi-supervised learning can significantly improve the accuracy of supervised classification. But in some cases, it may dramatically reduce the accuracy of the classification. The reason of such degradation is incorrect labeling of unlabeled data. In this article, we propose the method for high confidence labeling of unlabeled data. The base classifier in the proposed algorithm is the support vector machine. In this method, the labeling is performed only on the set of the unlabeled data that is closer to the decision boundary from the threshold. This data is called informative data. the adding informative data to the training set has a great effect to achieve the optimal decision boundary if the predicted label is correctly. The Epsilon- neighborhood Algorithm (DBSCAN) is used to discover the labeling structure in the data space. The comparative experiments on the UCI dataset show that the proposed method outperforms than some of the previous work to achieve greater accuracy of the self-training semi-supervised classification. Manuscript profile -
Open Access Article
779 - Probabilistic Evaluation of Multi-Chamber Arresters Protection Performance for Reduction of Lighting Failures in Overhead Distribution Lines
Ramezan Ali NaghizadehA sophisticated and accurate probabilistic computational procedure for the calculation of lightning failures and evaluation of MCA performance for reduction of failures is implemented in this paper. Calculation of induced overvoltage caused by indirect lightning is impl MoreA sophisticated and accurate probabilistic computational procedure for the calculation of lightning failures and evaluation of MCA performance for reduction of failures is implemented in this paper. Calculation of induced overvoltage caused by indirect lightning is implemented based on the Agarwal method with consideration of lossy ground. The Monte Carlo method with backward scenario reduction is implemented to take into account the uncertainty of lightning flash parameters including peak current and front time with the distance of the striking point from the distribution line with applying a proper model for simulation of MCA in ATP-EMTP software. A link is developed between MATLAB and ATP-EMTP software to simulate the numerous generated scenarios and analyze the output results. Different conditions including the insulation strength of the line, the earth conductivity, and the shielding factor of the adjacent objects to the line are also taken into account in calculations. The results are presented in a proper way to make them useful for the determination of lightning-related failure rates and also accurate evaluation of the effectiveness of MCA installation in different conditions of distribution feeders. Manuscript profile -
Open Access Article
780 - Fault Tolerant Control of DFIG Wind Turbine Back-to-Back Converter Based on Developed Sliding Mode Method
mehrnoosh Kamarzarrin Mohammad Hossein Refan پرویز امیریFault detection and tolerable control of wind turbine increases its reliability and availability. One of the electrical components of the wind turbine with a high error rate is the power converter. In this paper, a new method for fault tolerant (FT) control of the wind MoreFault detection and tolerable control of wind turbine increases its reliability and availability. One of the electrical components of the wind turbine with a high error rate is the power converter. In this paper, a new method for fault tolerant (FT) control of the wind turbine back-to-back converter based on Dual Feed Induction Generator (DFIG) is presented. When a open circuit fault occurs in each of the IGBTs of the wind turbine converter, the performance of the converter is distorted and part of the current signal of each leg of the converter is lost. The classical controller cannot completely correct this change in current behavior, and for this reason, it has an abnormal performance. As a result, power generation will be accompanied by many fluctuations. In order to compensate, a new method based on sliding mode control is presented in this article. First, when an error occurs, the fault detection system identifies the faulty leg, and after reconfiguring the hardware, the proposed control system based on sliding mode control replaces the classic control system and switching operation. The fault detection method presented in this article is based on artificial neural network and it was developed based on matching with the functional parameters of the wind turbine. The proposed FT method is evaluated using a hardware simulator in a laboratory loop with a 90 kW DFIG generator. The experimental results show the proper accuracy of the fault detection method and on the other hand, the proposed FT method was able to compensate the open circuit fault of the IGBT. Manuscript profile -
Open Access Article
781 - Evaluation of the Effect of Transformer Oil Parameters on the Transformer Health Index Using Curve Estimation Method
Morteza Saeid Hamed Zeinoddini-MeymandTransformers are one of the most expensive and important equipment in power systems that are under the influence of electrical, thermal and chemical reactions The transformer health index is a standard that is used to evaluate the condition and determine the remaining l MoreTransformers are one of the most expensive and important equipment in power systems that are under the influence of electrical, thermal and chemical reactions The transformer health index is a standard that is used to evaluate the condition and determine the remaining life of the transformer by using laboratory data and field inspections. The purpose of this article is to determine the relationships between electrical, physical, chemical parameters of oil, dissolved gases in oil and transformer health index. One of the advantages of using the regression method in the analysis of transformer data compared to other methods for determining the transformer health index is determining the influence of the parameters that have the greatest impact on each other. In this article, Curve Estimation Regression method is used and the results are drawn by drawing graphs by SPSS statistical software to analyze the parameters. To carry out the simulations, the laboratory data of some transformers have been considered. Manuscript profile -
Open Access Article
782 - Neural-Fuzzy Network and Z-Source Converter Adaptive Controller for Control the Power of the Hybrid Network Consisting of Doubly-Fed Induction Generator and Solar Cel
ali akbar habibi borzou yousefi abdolreza noori shirazi Mohammad rezvaniRenewable energies outfitted with low latency assets as wind turbines and photovoltaic exhibits give significant adverse consequences through power framework dynamic protections. For this issue, in view of fostering a high voltage direct current (HVDC) interface, a vers MoreRenewable energies outfitted with low latency assets as wind turbines and photovoltaic exhibits give significant adverse consequences through power framework dynamic protections. For this issue, in view of fostering a high voltage direct current (HVDC) interface, a versatile Neuro-Fuzzy-based damping regulator is introduced in this paper for working on unique execution of low inertia resources associated with power frameworks. The created power framework comprises of various age sources including seaward and inland wind turbines (WTs), photovoltaic exhibits (PVs) and limited doubly fed induction generators (DFIGs) which are incorporated together through an interconnected framework. For this situation, thinking about various functional and innovative conditions, damping execution of proposed ANFIS plot is assessed. The proposed plot is a non-model-based regulator which utilizes the benefits of both neural and fluffy rationales together for giving a quick and secure design of damping regulator through continuous recreations. To research ANFIS plot through genuine cases, considering a commonplace microgrid comprises of various low-latency assets (for example WT, PV, DFIG), the framework damping exhibitions through hamper occasions are assessed. Recreation results demonstrate viability and effectiveness of the proposed plot for damping dynamic motions of low inertia resources with high damping proportions with respect to extreme issue occasions. Manuscript profile -
Open Access Article
783 - Improvement of the Sharpness and Brightness of Dim Images Using the Retinax Approach and Nonlinear Conversion
maryam ghasemi Morteza Khademi Abbas Ebrahimi moghadamImages captured in low light conditions are unsuitable for human and machine vision due to low brightness and sharpness and high noise, and have a negative effect on their performance. Much research has been done to improve such images. The methods proposed so far to so MoreImages captured in low light conditions are unsuitable for human and machine vision due to low brightness and sharpness and high noise, and have a negative effect on their performance. Much research has been done to improve such images. The methods proposed so far to solve this problem greatly improve such images. One of these methods is the RETINEX-based method, which modifies low-light images, but because the initial structure of this method is complex and inefficient, researchers have developed other methods such as SSR, MSR, and MSRCR. To solve the problem, they have presented this approach. These methods, in turn, have problems such as abnormal images and amplification of noise. In the continuation of the work done, the field of optimization has been used, which shows better performance than the previous works. In this research, by obtaining the optimal brightness component, using nonlinear conversion and applying smoothing filter and reducing noise on the image as a post-processing step, these weaknesses are largely eliminated. By applying the proposed method, the resulting images look more natural and their information is more preserved. Subjective and objective criteria such as EI, SSIM, PSNR and IMMSE were used to evaluate the proposed method. The simulation results show the superiority of the proposed method over the competing methods. Manuscript profile -
Open Access Article
784 - Improving Robotic Arm Control via Model Reference Adaptive Controller Using EMG Signals Classification
Mahsa Barfi Hamidreza Karami Elham Farahi Fatemeh ّّFaridi Seyed Manouchehr Hosseini PilangorgiThe purpose of designing and manufacturing prosthetic organs is to create their maximum behavioral similarity to human organs. The aim of this paper is to improve the robotic arm control via Model Reference Adaptive System (MRAS) based on Lyapunov theory using EMG data MoreThe purpose of designing and manufacturing prosthetic organs is to create their maximum behavioral similarity to human organs. The aim of this paper is to improve the robotic arm control via Model Reference Adaptive System (MRAS) based on Lyapunov theory using EMG data classification. In this paper, human arm is modeled with a robot with two degrees of freedom. The proposed control method is MRAS. The outcome of this research is a robotic arm with MRAS, using the classification of electromyogram (EMG) data recorded from human arm movements, results in proper tracking of the reference signal, less overshoot and steady-state error compared to the conventional PI controller. For this purpose, using two electrodes, EMG data is collected from the anterior deltoid and middle deltoid muscles of the arm of five female athletes and by performing two movements of abduction and flexion of the arm. Then, after eliminating noise, integral of absolute value (IAV), zero crossing (ZC), variance (VAR) and median frequency (MF) are extracted. Then, classification is done by linear discriminant analysis (LDA) method to detect movements based on data characteristics. Finally, the proposed controller and model are designed according to the EMG characteristics to achieve the proper control response and the appropriate command signal is sent to the controller to perform the corresponding movement. The results and the values of the obtained errors show the conformity of the model and controller behavior with the predefined movement pattern. Manuscript profile -
Open Access Article
785 - Improving IoT Botnet Anomaly Detection Based on Dynamic Feature Selection and Hybrid Processing
Boshra Pishgoo Ahmad akbari aziraniThe complexity of real-world applications, especially in the field of the Internet of Things, has brought with it a variety of security risks. IoT Botnets are known as a type of complex security attacks that can be detected using machine learning tools. Detection of the MoreThe complexity of real-world applications, especially in the field of the Internet of Things, has brought with it a variety of security risks. IoT Botnets are known as a type of complex security attacks that can be detected using machine learning tools. Detection of these attacks, on the one hand, requires the discovery of their behavior patterns using batch processing with high accuracy, and on the other hand, must be operated in real time and adaptive like stream processing. This highlights the importance of using batch/stream hybrid processing techniques for botnet detection. Among the important challenges of these processes, we can mention the selection of appropriate features to build basic models and also the intelligent selection of basic models to combine and present the final result. In this paper, we present a solution based on a combination of stream and batch learning methods with the aim of botnet anomaly detection. This approach uses a dynamic feature selection method that is based on a genetic algorithm and is fully compatible with the nature of hybrid processing. The experimental results in a data set consisting of two known types of botnets indicate that on the one hand, the proposed approach increases the speed of hybrid processing and reduces the detection time of the botnets by reducing the number of features and removing inappropriate features, and on the other hand, increases accuracy by selecting appropriate models for combination. Manuscript profile -
Open Access Article
786 - Analysis of SettlingTime in Charge Pump Phase-Locked loops regarding Non-ideal Effect
hadi dehbovid habib Adarang hamidreza rabieePhase locked loops (PLL) are widely used in telecommunication systems. Frequency characteristics and settling time are the two most important features of PLLs. In phase lock loops, several nonlinear factors can be considered, one of which is the nonlinear behavior of th MorePhase locked loops (PLL) are widely used in telecommunication systems. Frequency characteristics and settling time are the two most important features of PLLs. In phase lock loops, several nonlinear factors can be considered, one of which is the nonlinear behavior of the phase detector. In fact, load pump phase locking loops (CPPLL) are nonlinear systems due to the nonlinear behavior generated by the load pump. Although the applied current is fixed in an ideal load pump, this is not fixed in practice because of the non-ideal behavior of the transistors. In this paper, considering the channel length modulation (CLM) effect caused by the drain-source voltage of MOSFET transistor, a more accurate model is presented for the phase detector. By investigating the non-linear differential equation dominating the system and using the step-response approximation for the transient time analysis, new equations are obtained for the settling time and overshooting. In order to check the validity of the specified non-linear equations, the simulation was conducted in MATLAB Simulink. Moreover, in order to better assess the proposed method, the performance of a PLL subjected to the transistor’s drain-source voltage has been simulated and the effect of the different loop parameters, such as the loop’s resistor and current has been investigated. The final results showed the appropriate accordance of the analytical equations with the simulation results. Manuscript profile -
Open Access Article
787 - Determination of Available Transfer Capability by Combined Method of Newton-Raphson-Seydel and Holomorphic Load Flow with Improved Matrix Calculations
Mostafa EidianiThis paper first demonstrates that high direct current lines will undoubtedly be the backbone of the future transmission network. The Newton Raphson Seydel alternating load flow equations are then combined with the direct current line equations. This paper employed matr MoreThis paper first demonstrates that high direct current lines will undoubtedly be the backbone of the future transmission network. The Newton Raphson Seydel alternating load flow equations are then combined with the direct current line equations. This paper employed matrix techniques to increase the speed of solving problems as the dimensions of the equations get larger. Furthermore, the holomorphic load flow does not require an initial estimate to run the load flow, and if a solution exists, the precise answer is calculated. The initial guess of Newton Raphson Seydel was calculated using this approach. In this paper, we describe a novel approach that can compute the available transfer capability in small and large networks with sufficient accuracy and speed by combining these methods. The simulation in this paper uses five networks: 39 IEEE buses, 118 IEEE buses, 300 IEEE buses, 145 Iowa state buses, and 1153 East Iran buses network. In addition, four approaches were employed for comparison: continuous power flow, the general minimum residual method, Newton Raphson Seydel classical method, and the standard holomorphic power flow method. The results of the simulations suggest that the proposed strategy is acceptable. Manuscript profile -
Open Access Article
788 - Performance Enhancement of Unfalsified Adaptive Control Using the Model Reference
Mojtaba Nouri ManzarUnfalsified adaptive control is a new approach in supervisory control that ensures the selection of a stabilizing controller from a control set based on the system input-output data. A prerequisite for ensuring stability is the existence of a pre-designed controller set MoreUnfalsified adaptive control is a new approach in supervisory control that ensures the selection of a stabilizing controller from a control set based on the system input-output data. A prerequisite for ensuring stability is the existence of a pre-designed controller set that contains a stabilizing controller. The supervisor selects the controller based on the cost function calculated with the system input-output data. In this method, the control system performance is restricted to the controllers of the control set. In this paper, the controller set update is performed by introducing the concept of performance falsification along with the stability falsification of the active controller. To falsify the performance of the controller set, the structure of the model reference is proposed to evaluate the performance of the control system. In case of performance falsification, a new controller is designed and added to the controller set based on system data and without using any model. To design the controller, a linear matrix inequality problem is solved. In this paper, no system model is used, and the presented method is completely model-free and data-oriented. The simulation results show the performance improvement of the proposed method compared to other methods in a standard robust adaptive benchmark system. Manuscript profile -
Open Access Article
789 - Multi-Label Feature Selection Using a Hybrid Approach Based on the Particle Swarm Optimization Algorithm
َAzar Rafiei Parham Moradi Abdolbaghi GhaderzadehMulti-label classification is one of the important issues in machine learning. The efficiency of multi-label classification algorithms decreases drastically with increasing problem dimensions. Feature selection is one of the main solutions for dimension reduction in mul MoreMulti-label classification is one of the important issues in machine learning. The efficiency of multi-label classification algorithms decreases drastically with increasing problem dimensions. Feature selection is one of the main solutions for dimension reduction in multi-label problems. Multi-label feature selection is one of the NP solutions, and so far, a number of solutions based on collective intelligence and evolutionary algorithms have been proposed for it. Increasing the dimensions of the problem leads to an increase in the search space and consequently to a decrease in efficiency and also a decrease in the speed of convergence of these algorithms. In this paper, a hybrid collective intelligence solution based on a binary particle swarm optimization algorithm and local search strategy for multi-label feature selection is presented. To increase the speed of convergence, in the local search strategy, the features are divided into two categories based on the degree of extension and the degree of connection with the output of the problem. The first category consists of features that are very similar to the problem class and less similar to other features, and the second category is similar features and less related. Therefore, a local operator is added to the particle swarm optimization algorithm, which leads to the reduction of irrelevant features and extensions of each solution. Applying this operator leads to an increase in the convergence speed of the proposed algorithm compared to other algorithms presented in this field. The performance of the proposed method has been compared with the most well-known feature selection methods on different datasets. The results of the experiments showed that the proposed method has a good performance in terms of accuracy. Manuscript profile -
Open Access Article
790 - Fixed-Time Consensus of Fractional-Order Single Integrator Multi-Agent Systems
Hossein Zamani وحيد جوهري مجد Khosro KhandaniThe problem of consensus in fractional order single-integrator multi-agent systems has been studied in this paper. The effect of memory is considered using the Riemann-Liouville fractional derivative in the dynamics of the agents. In order to achieve convergence among t MoreThe problem of consensus in fractional order single-integrator multi-agent systems has been studied in this paper. The effect of memory is considered using the Riemann-Liouville fractional derivative in the dynamics of the agents. In order to achieve convergence among the agents, a fractional order control protocol based on the error signal between neighboring agents is proposed. Using Lyapunov's stability theorem, a Lyapunov function is introduced that shows that the agents converge over a specified settling time and the upper bound of the settling time is obtained. The merit of the proposed bound for the settling time is that it is independent of the initial conditions. Finally, some simulations are provided to confirm the introduced method. Manuscript profile -
Open Access Article
791 - Integrated Modeling of Bidirectional Solid-State Transformers: Rectifier, DC to DC Converter and Inverter Stages
hamed molla-ahmadian morteza shafiei javid khorasani: One of the new and growing equipment in modern power networks is solid state or power electronic transformer. These types of transformers are based on power semiconductor switches and high frequency transformers. Compared to traditional transformers, it has several ca More: One of the new and growing equipment in modern power networks is solid state or power electronic transformer. These types of transformers are based on power semiconductor switches and high frequency transformers. Compared to traditional transformers, it has several capabilities such as the ability to operate with input voltage variations in amplitude and frequency, automatic regulation of output voltage and input power factor correction. The investigated transformer has the ability to transfer power in both directions and has three stages, including the rectifier, the middle stage and the inverter stage. This transformer has a large number of semiconductor switches and its modeling, analysis, design and simulation is difficult and complex. In particular, real-time simulation of these transformers with conventional models is not possible. In these cases, the use of averaging theory seems to be the appropriate solution. In this paper, the averaging theory is applied to a solid-state transformer and its modeling is done in a simple and powerful way with the ability to study real-time, transient and steady states performance. The proposed modeling includes differential equations and equivalent circuits and offers an integrated transformer model with the ability to study the interaction between stages as a part of power system. The presented models are used in simulation of smart grids, DC microgrids and connection of distributed generation sources to the grid, as well as analysis and design of solid-state transformer behavior in areas such as renewable energies and electrical transportation. In addition to the proposed modeling, the closed-loop control structure has been implemented for all three stages. Transformer simulation is performed by implementing differential equations in SIMULINK/MATLAB software and verified the proposed model. Manuscript profile -
Open Access Article
792 - Regional Power-Aware Routing for Partially-Connected 3D Network-on-Chip
Mitra Moalemnia HadiShahriar ShahhoseiniNetwork-on-chip provides an efficient communication platform for Systems-on-chip. The static power consumption is an important issue in these networks. Switching the power supply on virtual channels during idle time is a common method for reducing the network power cons MoreNetwork-on-chip provides an efficient communication platform for Systems-on-chip. The static power consumption is an important issue in these networks. Switching the power supply on virtual channels during idle time is a common method for reducing the network power consumption. The traffic load at the network level and non-continuous idle period of virtual channel have caused the sources to be switched on and off continuously, which leads to increase in power consumption and other overheads. This will be more important, in partially connected 3D chip networks in which a limited number of vertical connections has been used. In this paper, a routing algorithm is proposed who employs an appropriate policy for packet distribution, and reduces the load distribution in the network and creates a continuous idle time for the resources, result in suitable power management in the network. In this routing scheme the network is divided to north and south region and some restriction applied in usage of elevators in each region and try to increase the utilization of the used resources as well as the ideal time of low traffic paths. The simulation results, derived by BookSim, show the proposed method improve the network power consumption by 18% to 30% comparing previous algorithms, and the network delay has been reduced by 32%. Manuscript profile -
Open Access Article
793 - High Level Synthesis of Decimal Arithmetic on Coarse Grain Reconfigurable Architectures
Samaneh EmamiThe increasing capabilities of integrated circuits and the complexity of applications have led hardware design methods and tools to higher levels of abstraction and high-level synthesis is one of the key steps in increasing the level of abstraction. In recent years, ext MoreThe increasing capabilities of integrated circuits and the complexity of applications have led hardware design methods and tools to higher levels of abstraction and high-level synthesis is one of the key steps in increasing the level of abstraction. In recent years, extensive research has been conducted on the design of decimal arithmetic reconfigurable architectures. Since, on the one hand, the effective use of these architectures depends on the existence of appropriate algorithms and tools to implement the design on the hardware, and on the other hand, research on the development of these algorithms has been very limited, this paper will present methods for the automated synthesis of decimal arithmetic circuits on a coarse-grained reconfigurable architecture. The platform chosen to execute the proposed algorithms is the DARA coarse-grained reconfigurable architecture, which is optimized for decimal arithmetic. The algorithms proposed for resource allocation of synthesis include a heuristic method and an ILP algorithm. The results show that, as expected, for the limited architectural dimensions used, the ILP algorithm performs significantly (about 30%) better than the heuristic algorithm. Manuscript profile -
Open Access Article
794 - Multi-Objective Logic Synthesis of Quantum Circuits
Arezoo Rajaei Mahboobeh Houshmand Seyyed Abed HosseiniQuantum computing is a new method of information processing that is based on the concepts of quantum mechanics and leads to strange and powerful events in the quantum field. The logic synthesis of quantum circuits refers to the process of converting a given quantum gate MoreQuantum computing is a new method of information processing that is based on the concepts of quantum mechanics and leads to strange and powerful events in the quantum field. The logic synthesis of quantum circuits refers to the process of converting a given quantum gate into a set of gates that can be implemented in quantum technologies. The most famous logic synthesis methods are CSD and QSD. The main goal of this study is to present a multi-objective logical synthesis method combining the above two methods in the quantum circuit model with the aim of optimizing the evaluation criteria. In this proposed method, the solution space is created from different combinations of CSD and QSD decomposition methods. The created solution space is a space with a very large exponential size. Then, using a bottom-up approach of multi-objective dynamic programming, a method is presented to search only a part of the entire solution space to find circuits with the optimal Pareto costs. The obtained results show that this method creates a balance between the evaluation criteria and produces many optimal Pareto solutions that can be selected according to different quantum technologies. Manuscript profile -
Open Access Article
795 - A Semi-Intelligent Method for Charging Electric Vehicles in Unbalanced Four-Wire Distribution Networks
Saeed Zolfaghari MoghaddamThe growing penetration of electric vehicles (EVs) in distribution networks (DNs) has posed many challenges for electricity distribution companies, such as: increasing the amount of voltage drop, network losses and the number of outages due to the overload. To overcome MoreThe growing penetration of electric vehicles (EVs) in distribution networks (DNs) has posed many challenges for electricity distribution companies, such as: increasing the amount of voltage drop, network losses and the number of outages due to the overload. To overcome this, it is recommended to use coordinated charging methods. However, these methods require telecommunication, measurement and processing infrastructure with high costs and can only be implemented in smart grids. In this paper, a semi-intelligent method for charging EVs is presented that does not require complex infrastructure. This method, using a simple and inexpensive local automation system, charges EVs in the off-peak periods of the DN and thus improves its parameters. Since the EVs are charged at the low tariff time intervals, the proposed method will also benefit the EV owners. To achieve real results, four-wire DN is considered to model the effect of neutral conductor. To confirm the effectiveness of the proposed method, it is compared with different uncontrolled charging methods. A standard 19 bus test system is used for simulations. Manuscript profile -
Open Access Article
796 - A Content-Based Image Retrieval System Using Semi-Supervised Learning and Frequent Patterns Mining
Maral KolahkajContent-based image retrieval, which is also known as query based on image content, is one of the sub-branches of machine vision, which is used to organize and recognize the content of digital images using visual features. This technology automatically searches the imag MoreContent-based image retrieval, which is also known as query based on image content, is one of the sub-branches of machine vision, which is used to organize and recognize the content of digital images using visual features. This technology automatically searches the images similar to the query image from huge image database and it provides the most similar images to the users by directly extracting visual features from image data; not keywords and textual annotations. Therefore, in this paper, a method is proposed that utilizes wavelet transformation and combining features with color histogram to reduce the semantic gap between low-level visual features and high-level meanings of images. In this regard, the final output will be presented using the feature extraction method from the input images. In the next step, when the query images are given to the system by the target user, the most similar images are retrieved by using semi-supervised learning that results from the combination of clustering and classification based on frequent patterns mining. The experimental results show that the proposed system has provided the highest level of effectiveness compared to other methods. Manuscript profile -
Open Access Article
797 - Synchronverter with the Capability of Damping Enhancement for the Suppression of Power and Frequency Oscillations in Inverter-Based Micro-Grids
kambiz Mehrdadian Seyed Mohammad AzimiNowadays, due to the advances made in power electronics and the desire to use renewable energy resources, micro-grids have been developed considerably. One of the challenging operation modes of Micro-grids is named islanded mode, where the control of power and frequency MoreNowadays, due to the advances made in power electronics and the desire to use renewable energy resources, micro-grids have been developed considerably. One of the challenging operation modes of Micro-grids is named islanded mode, where the control of power and frequency is a challenging problem. Many distributed energy resources are operated based on electronic power converters and these converters have no inertia unlike synchronous generators, as a result, the issue of power and frequency control in micro-grids is considered as a serious problem. This issue will cause severe frequency fluctuations following to power changes which can lead to system instability. In this paper, first a sample micro-grid is simulated and modeled in synchronous reference frame then using the idea of inertia in synchronous machines, a novel control method with the capability of damping enhancement during system transients is proposed. The control scheme utilizes the idea of virtual inertia injection during the power and frequency fluctuations based on the synchronverter model. Finally, the effectiveness of the proposed method is verified using a set of the time domain simulations carried out in Matlab/Simulink software in an inverter based multi-source micro-grid operating in the island mode, and the results are compared with the vector control method implemented in the rotating reference frame under different scenarios. Manuscript profile -
Open Access Article
798 - Maintaining Confidentiality and Integrity of Data and Preventing Unauthorized Access to DICOM Medical Images
Mohammad Soltani Hassan Shakeri Mahboobeh HoushmandWith the development of telecommunication and communication technologies, especially wireless communications, information cryptography is one of the communication necessities. Today, cryptographic algorithms are used to increase security and prevent DICOM medical images MoreWith the development of telecommunication and communication technologies, especially wireless communications, information cryptography is one of the communication necessities. Today, cryptographic algorithms are used to increase security and prevent DICOM medical images from unauthorized access. It should be noted that changes in DICOM medical images will cause the doctor to misdiagnose the patient's treatment process. In this paper, a type of hybrid cryptographic algorithms is designed. In the proposed algorithm, DNA encryption algorithm is used to encrypt DICOM images and patient biometric information such as fingerprint or iris image is used to make digital signature and validate DICOM medical images. The designed encryption algorithm is resistant to brute force attacks and the entropy of the encrypted DICOM images is above 7.99. Manuscript profile -
Open Access Article
799 - Integrated Fault Estimation and Fault Tolerant Control Design for Linear Parameter Varying System with Actuator and Sensor Fault
Hooshang Jafari Amin Ramezani Mehdi ForouzanfarFault occurrence in real operating systems usually is inevitable and it may lead to performance degradation or failure and requires to be meddled quickly by making appropriate decisions, otherwise, it could cause major catastrophe. This gives rise to strong demands for MoreFault occurrence in real operating systems usually is inevitable and it may lead to performance degradation or failure and requires to be meddled quickly by making appropriate decisions, otherwise, it could cause major catastrophe. This gives rise to strong demands for enhanced fault tolerant control to compensate the destructive effects and increase system reliability and safety in the presence of faults. In this paper, an approach for estimation and control of simultaneous actuator and sensor faults is presented by using integrated design of a fault estimation and fault tolerant control for time-varying linear systems. In this method, an unknown input observer-based fault estimation approach with both state feedback control and sliding mode control was developed to assure the closed-loop system's robust stability via solving a linear matrix inequality formulation. The presented method has been applied to a linear parameter varying system and the simulation results show the effectiveness of this method for fault estimation and system stability. Manuscript profile -
Open Access Article
800 - Energy Management of Micro-Grids and Their Harmonic Compensation Through Shunt Active Filter Based on Multi-Agent Systems
Mohammad-Reza Salehi Rad Mohammad Mollaie EmamzadehIn this paper, a new energy management strategy is presented by using shunt active power filter (SAPF) in a multi-agent structure. This strategy is applied to a micro-grid connected to the grid and includes the problem of harmonic compensation. By examining the advantag MoreIn this paper, a new energy management strategy is presented by using shunt active power filter (SAPF) in a multi-agent structure. This strategy is applied to a micro-grid connected to the grid and includes the problem of harmonic compensation. By examining the advantages and disadvantages of shunt active power filters and passive filters, as well as their efficiency in the multi-agent structure for power micro-grids, the reason for using shunt active power filters in the proposed method has been determined. Also, the performance of these filters for compensating current harmonics has been compared by examining the FFT results. In the used micro-grid, wind turbine generator and solar cell generator are used as renewable energy sources (RES) and two fuel cells are used to compensate for sudden and unplanned changes in the production power of these two generators. The energy management unit manages the active and inactive state of the two fuel cells according to the production power and consumption power of the micro-grid in such a way that the power exchanged between the micro-grid and the main grid is limited within an acceptable range. The simulation results show that the proposed method using local continuous controllers (in each agent) and central discrete controller (energy management system) has been able to perform well and while providing the required power of the micro-grid, at the same time, it performs the current harmonics compensation issue correctly. Manuscript profile -
Open Access Article
801 - Design and Simulation of a Low Power and High-Speed CMOS Double-Tail Comparator
Akbar Heidaritabar habib Adarang seyed saleh Ghoreishi Reza YousefiThe need for low power and high-speed ADC pushes for dynamic comparators to reduce power consumption and maximize speed. This paper presents an analysis of delay, speed, and comparator considerations, and analytical expressions are derived. Using the equation expression MoreThe need for low power and high-speed ADC pushes for dynamic comparators to reduce power consumption and maximize speed. This paper presents an analysis of delay, speed, and comparator considerations, and analytical expressions are derived. Using the equation expressions, we can understand the design of comparators and make trade-offs. Based on the presented analysis, a new dynamic comparator is proposed by modifying the circuit of the conventional tail comparator for high speed and low power at small supply voltages without complicating the circuit design, resulting in a remarkable reduction in delay time and incremental speed. Simulation results in a 180 nm CMOS technology confirm the analysis results. It is shown that the proposed conventional tail comparator reduces power consumption and increases speed. The simulation results show that the proposed comparator operates up to 2.5GHz with a delay of 69ps and consumes only 329 μW at a supply voltage of 1.2 V and an offset standard deviation of 7.8 mW. Manuscript profile -
Open Access Article
802 - A Two-Level Method Based on Dynamic Programming for Partitioning and Optimization of the Communication Cost in Distributed Quantum Circuits
zohreh davarzani maryam zomorodi-moghadam M. HoushmandNowadays, quantum computing has played a significant role in increasing the speed of algorithms. Due to the limitations in the manufacturing technologies of quantum computers, the design of a large-scale quantum computer faces many challenges. One solution to overcome t MoreNowadays, quantum computing has played a significant role in increasing the speed of algorithms. Due to the limitations in the manufacturing technologies of quantum computers, the design of a large-scale quantum computer faces many challenges. One solution to overcome these challenges is the design of distributed quantum systems. In these systems, quantum computers are connected to each other through the teleportation protocol to transfer quantum information. Since quantum teleportation requires quantum resources, it is necessary to reduce the number of that. The purpose of this paper is to present a distributed quantum system considering the two goals of balanced distribution of qubits and minimizing the number of teleportation protocols in two levels. In the first level, by presenting a dynamic programming algorithm, an attempt has been made to distribute qubits in a balanced manner and reduce the number of connections between subsystems. According to the output partitioning obtained from the first level, in the second level and in the stage of implementation of global gates, when one of the qubits of this gate is teleported from the home to the desired destination, this qubit may be able to be used by a number of global gates, observing the precedence restrictions and as a result it reduces the number of teleportations. The obtained results show the better performance of the proposed algorithm. Manuscript profile -
Open Access Article
803 - SQ-PUF: A Resistant PUF-Based Authentication Protocol against Machine-Learning Attack
Abolfazl Sajadi Bijan AlizadehPhysically unclonable functions (PUFs) provide hardware to generate a unique challenge-response pattern for authentication and encryption purposes. An essential feature of these circuits is their unpredictability, meaning that an adversary cannot sufficiently predict fu MorePhysically unclonable functions (PUFs) provide hardware to generate a unique challenge-response pattern for authentication and encryption purposes. An essential feature of these circuits is their unpredictability, meaning that an adversary cannot sufficiently predict future responses from previous observations. However, machine learning algorithms have been demonstrated to be a severe threat to PUFs since they are capable of accurately modeling their behavior. In this work, we analyze PUF security threats and propose a PUF-based authentication mechanism called SQ-PUF, which can provide good resistance to machine learning attacks. In order to make it harder to simulate or predict, we obfuscated the correlation between challenge-response pairs. Experimental results show that, unlike existing PUFs, even with a large data set, the SQ-PUF model cannot be successfully attacked with a maximum prediction accuracy of 53%, indicating that this model is unpredictable. In addition, the uniformity in this model remains almost the same as the ideal value in A-PUF. Manuscript profile -
Open Access Article
804 - One Analytical Method Based on Winding Function Theory and Magnetic Equivalent Circuit Model for Electromagnetic Analysis of Induction Motors under Healthy Condition and Broken-Rotor Bar Fault
Farhad Rezaee-Alam Abdolsamad Hamidi Vahid NaeiniIn this paper, one hybrid analytical model (HAM) based on winding function theory (WFT) was presented for cage-rotor induction motors (CRIMs), which helps from the magnetic equivalent circuit (MEC) for considering the effect of slots and magnetic saturation in stator an MoreIn this paper, one hybrid analytical model (HAM) based on winding function theory (WFT) was presented for cage-rotor induction motors (CRIMs), which helps from the magnetic equivalent circuit (MEC) for considering the effect of slots and magnetic saturation in stator and rotor cores. A non-linear MEC model is used to calculate the magneto motive force (MMF) drops in iron parts of stator and rotor for every operating point under the healthy condition and broken-rotor bar (BRB) fault. The distribution of MMF drop in stator and rotor is separately expressed in terms of the distribution of equivalent virtual currents and the virtual winding function. The inductances are then calculated using WFT while considering the effect of slots and magnetic saturation. To model the starting of no-load CRIM, the system of electrical and mechanical differential equations is solved using the finite difference method (FDM) under the healthy condition and BRB fault. Hague's solution and one simple conformal mapping (CM) are used to calculate and analysis of air-gap magnetic field. To verify the proposed model, some analytical results are compared with the corresponding results obtained through finite element method (FEM). Manuscript profile -
Open Access Article
805 - Distributed Target Tracking by Solving Average Consensus Problem on Sensor Network Measurements
Iman Maghsudlu Meysam r. Danaee Hamid ArezumandIn this paper, a new algorithm is presented to drastically reduce communication overhead in distributed (decentralized) single target tracking in a wireless sensor network. This algorithm is based on a new approach to solving the average consensus problem and the use of MoreIn this paper, a new algorithm is presented to drastically reduce communication overhead in distributed (decentralized) single target tracking in a wireless sensor network. This algorithm is based on a new approach to solving the average consensus problem and the use of distributed particle filters. For the algorithm of this paper, unlike the common algorithms that solve an average consensus problem just to approximate the global likelihood function to calculate the particle importance weights in distributed tracking, a new model for observation is presented based on the Gaussian approximation, which only solves the problem Consensus is applied to the mean on the received observations of the nodes in the network (and not to approximate the global likelihood function). These innovations significantly reduce the exchange of information between network nodes and as a result uses much less energy resources. In different scenarios, the efficiency of the proposed algorithm has been compared with the centralized algorithm and the distributed algorithm based on the graph, and the simulation results show that the communication overhead of the network is greatly reduced in exchange for an acceptable drop in tracking accuracy by using our proposed algorithm. Manuscript profile -
Open Access Article
806 - Stock Price Movement Prediction Using Directed Graph Attention Network
Alireza Jafari Saman HaratizadehPrediction of the future behavior of the stock market has always attracted researchers' attention as an important challenge in the field of machine learning. In recent years deep learning methods have been successfully applied in this domain to improve prediction perfor MorePrediction of the future behavior of the stock market has always attracted researchers' attention as an important challenge in the field of machine learning. In recent years deep learning methods have been successfully applied in this domain to improve prediction performance. Previous studies have demonstrated that aggregating information from related stocks can improve the performance of prediction. However, the capacity of modeling the stocks relations as directed graphs and the power of sophisticated graph embedding techniques such as Graph Attention Networks have not been exploited so far for prediction in this domain. In this work, we introduce a framework called DeepNet that creates a directed graph representing how useful the data from each stock can be for improving the prediction accuracy of any other stocks. DeepNet then applies Graph Attention Network to extract a useful representation for each node by aggregating information from its neighbors, while the optimal amount of each neighbor's contribution is learned during the training phase. We have developed a novel Graph Attention Network model called DGAT that is able to define unequal contribution values for each pair of adjacent nodes in a directed graph. Our evaluation experiments on the Tehran Stock Exchange data show that the introduced prediction model outperforms the state-of-the-art baseline algorithms in terms of accuracy and MCC measures. Manuscript profile -
Open Access Article
807 - Software Evaluation of Reducing the Number of Switching States and Removing the Weight Factor in the Predictive Current Control of Six-Phase Induction Motor
Peyman Mirzaeipour esmaeel rokrok Mohsen Saniei Syed Qudrat Allah seifosadatThe simple and accurate design of the flux weighting coefficient for the predictive current control (PCC) algorithm is an important issue that can be seen in all predictive controllers. It should be said that predictive current control is a promising method to obtain fa MoreThe simple and accurate design of the flux weighting coefficient for the predictive current control (PCC) algorithm is an important issue that can be seen in all predictive controllers. It should be said that predictive current control is a promising method to obtain fast torque response with a simple and flexible structure, but its development to multi-phase drives can lead to dissatisfaction. In this article, due to the challenge of computing load of PCC algorithm, the weighting coefficient removal method is used and finally modified predictive current control (VV-PCC) without weighting coefficient is used for six-phase induction motor drive. Different operating conditions such as startup, sudden loading and different speeds have been investigated. As a result, choosing a switching state in PCC leads to high x-y currents, this problem requires a small number of repetitions with the proposed VV-PCC method based on removing the weighting factor, because the number of switching states has increased from 49 to 13, and finally It will reduce copper losses and improve power quality. The results and validation of the mentioned cases are presented using MATLAB software. Manuscript profile -
Open Access Article
808 - A New Parallel Method to Verify the Packets Forwarding in SDN Networks
Rozbeh Beglari Hakem BeitollahiThe rise of Software-Defined Networking (SDN) has revolutionized network management, offering greater flexibility and programmability. However, ensuring the accuracy of packet forwarding remains paramount for maintaining network reliability and security in SDN environme MoreThe rise of Software-Defined Networking (SDN) has revolutionized network management, offering greater flexibility and programmability. However, ensuring the accuracy of packet forwarding remains paramount for maintaining network reliability and security in SDN environments. Unlike traditional IP networks, SDN separates the control plane from the data plane, creating new challenges for securing data transmission. Existing verification methods designed for IP networks often cannot be directly applied to SDN due to this architectural difference. To address the limitations of existing verification methods in SDN networks, new approaches are necessary. This research proposes a novel parallel method for verifying packet forwarding, building upon concepts from DYNAPFV. The proposed approach aims to overcome specific limitations of existing methods (including DYNAPFV), such as scalability issues, slow verification times. Simulations demonstrate significant improvements compared to DYNAPFV. The proposed parallel method achieves a 92% reduction in time required to identify malicious nodes within the network. The results also reveal a trade-off between security and verification time. As the probability of packet integrity confirmation increases from 0.8 to 0.99, system security strengthens, but the time to detect malicious switches also increases. Manuscript profile -
Open Access Article
809 - Finite-Control-Set Model Predictive Control of an Active Front-End Rectifier with Dynamic References and Comparison with MPDPC Method
Ayyoub Keshvari Mohammad Reza Alizadeh Pahlavani Arash Dehestani KolagarIn this paper, a finite-control-set model predictive control method is presented for closed loop control of an active front-end rectifier. The method used has a discrete-time function and does not require any additional modulators. The interesting point in the control a MoreIn this paper, a finite-control-set model predictive control method is presented for closed loop control of an active front-end rectifier. The method used has a discrete-time function and does not require any additional modulators. The interesting point in the control algorithm is how to control the dynamic references. The control strategy is able to provide proper references for source active power and DC voltage, without the need for additional control loops. In order to better understand the performance, the proposed control method is compared with the model predictive direct power control (MPDPC) method. The results obtained using Matlab/Simulink software show that the proposed method, while having all the capabilities of the MPDPC method, including proper tracking of active power and DC voltage and low current THD, by removing the PI controller and its related disadvantages, it has better stability and faster transient response. Manuscript profile -
Open Access Article
810 - Social Networks Embedding Based on the Employment of Community Recognition and Latent Semantic Feature Extraction Approaches
Mohadeseh Taherparvar Fateme Ahmadi abkenari Peyman bayatThe purpose of embedding social networks, which has recently attracted a lot of attention, is to learn to display in small dimensions for each node in the network while maintaining the structure and characteristics of the network. In this paper, we propose the effect of MoreThe purpose of embedding social networks, which has recently attracted a lot of attention, is to learn to display in small dimensions for each node in the network while maintaining the structure and characteristics of the network. In this paper, we propose the effect of identifying communities in different situations such as community detection during or before the process of random walking and also the effect of semantic textual information of each node on network embedding. Then two main frameworks have been proposed with community and context aware network embedding and community and semantic feature-oriented network embedding. In this paper, in community and context aware network embedding, the detection of communities before the random walk process, is performed through using the EdMot non-overlapping method and EgoNetSplitter overlapping method. However, in community and semantic feature-oriented network embedding, the recognition of communities during a random walk event is conducted using a Biterm topic model. In all the proposed methods, text analysis is examined and finally, the final display is performed using the Skip-Gram model in the network. Experiments have shown that the methods proposed in this paper work better than the superior network embedding methods such as Deepwalk, CARE, CONE, and COANE and have reached an accuracy of nearly 0.9 and better than other methods in terms of edge prediction criteria in the network. Manuscript profile -
Open Access Article
811 - Optimum Design and Full-Wave Analysis of Broad-Band Metamaterial Absorbers in the Visible Light Spectrum
Mortaza Nazari Amir Habibzadeh-Sharif Mohammad EskandariIn this paper, optimum design, numerical simulation and full-wave analysis of two broad-band metamaterial absorbers have been presented in the infrared, visible light, and ultraviolet frequencies of the sunlight spectrum. These planar absorbers consist of two conductive MoreIn this paper, optimum design, numerical simulation and full-wave analysis of two broad-band metamaterial absorbers have been presented in the infrared, visible light, and ultraviolet frequencies of the sunlight spectrum. These planar absorbers consist of two conductive layers and an intermediate insulating layer. The simulations results obtained by the finite integration technique have shown that performance of the designed absorbers is independent of the incident wave polarization and its elevation and azimuth angles. The proposed absorbers have an absorption of more than 92% in the visible light range. Therefore, these absorbers can be used to harvest the energy of sunlight Manuscript profile -
Open Access Article
812 - Community Detection in Complex Dynamic Networks Based on Graph Embedding and Clustering Ensemble
Majid Mohammadpour Seyedakbar Mostafavi وحید رنجبرSpecial conditions of wireless sensor networks, such as energy limitation, make it essential to accelerate the convergence of algorithms in this field, especially in the distributed compressive sensing (DCS) scenarios, which have a complex reconstruction phase. This pap MoreSpecial conditions of wireless sensor networks, such as energy limitation, make it essential to accelerate the convergence of algorithms in this field, especially in the distributed compressive sensing (DCS) scenarios, which have a complex reconstruction phase. This paper presents a DCS reconstruction algorithm that provides a higher convergence rate. The proposed algorithm is a distributed primal-dual algorithm in a bidirectional incremental cooperation mode where the parameters change with time. The parameters are changed systematically in the convex optimization problems in which the constraint and cooperation functions are strongly convex. The proposed method is supported by simulations, which show the higher performance of the proposed algorithm in terms of convergence rate, even in stricter conditions such as the small number of measurements or the lower degree of sparsity. Manuscript profile -
Open Access Article
813 - Thermal Side Reaction on Lithium-Ion Battery in Fast Charging Mode with Multi-Stage Constant Current and Voltage Control CC-CV Charging Vechnique
Sohaib Azhdari رحمت اله میرزاییLithium-ion batteries are extensively used in fast charging stations because of their high density of energy storage and power. It is critical to know how to charge lithium batteries since their structure is very sensitive to heat. When using fast charging techniques fo MoreLithium-ion batteries are extensively used in fast charging stations because of their high density of energy storage and power. It is critical to know how to charge lithium batteries since their structure is very sensitive to heat. When using fast charging techniques for charging batteries, considerable heat is generated. This heat is caused by the ohmic losses of the battery and its internal reactions. While fast charging reduces the charging time of the battery, it may damage its structure. There are various methods of fast charging. Each has its advantages and limitations. By applying changes to the multi-stage constant current charging method, in addition to reducing the charging time, attempts were made to prevent damage to the battery. This improved method can deal with cases where temperature effects are removable, such as when there is a ventilation system. It minimizes charging time as much as possible. Manuscript profile -
Open Access Article
814 - Energy-saving Method in GPON Using Optimal Point Based on Gradient Descent
AliAkbar Nikoukar Hamidreza Goudarzi ali iloon kashkoolyDoze and sleep mechanisms are the most common energy-saving solution in GPON networks. Sleep duration is the critical value in the energy-saving domain, and it will affect the QoS metrics with inappropriate value. In this paper, a new energy-saving mechanism is proposed MoreDoze and sleep mechanisms are the most common energy-saving solution in GPON networks. Sleep duration is the critical value in the energy-saving domain, and it will affect the QoS metrics with inappropriate value. In this paper, a new energy-saving mechanism is proposed using an optimal point based on gradient descent that calculates sleep duration and keeps QoS metrics acceptable. The historical value of average delay and packet, drop ratio, ONU buffer, and bandwidth request parameters are used as input, and the sleep duration value is calculated. The simulation results show that the proposed method saves up to 17% energy in GPON and keeps the network’s QoS in an acceptable domain. Manuscript profile -
Open Access Article
815 - Improving Precision of Recommender Systems using Time-, Location- and Context-aware Trust Estimation Based on Clustering and Beta Distribution
Samaneh Sheibani Hassan Shakeri Reza SheybaniCalculation and applying trust among users has become popular in designing recommender systems in recent years. However, most of the trust-based recommender systems use only one factor for estimating the value of trust. In this paper, a multi-factor approach for estimat MoreCalculation and applying trust among users has become popular in designing recommender systems in recent years. However, most of the trust-based recommender systems use only one factor for estimating the value of trust. In this paper, a multi-factor approach for estimating trust among users of recommender systems is introduced. In the proposed scheme, first, users of the system are clustered based on their similarities in demographics information and history of ratings. To predict the rating of the active user into a specific item, the value of trust between him and the other users in his cluster is calculated considering the factors i.e. time, location, and context of their rating. To this end, we propose an algorithm based on beta distribution. A novel tree-based measure for computing the semantic similarity between the contexts is utilized. Finally, the rating of the active user is predicted using weighted averaging where trust values are considered as weights. The proposed scheme was performed on three datasets, and the obtained results indicated that it outperforms existing methods in terms of accuracy and other efficiency metrics. Manuscript profile -
Open Access Article
816 - Proposing a Detection and Mitigation Approach for DDoS Attacks on SDN-Based IoT Networks
fatemeh MotieShirazi Seyedakbar MostafaviInternet of Things (IoT) is a network of objects on which objects can communicate with other objects. The Internet of Things is currently constantly under numerous attacks due to technical, legal and human problems. One of the most important of these attacks is the Deni MoreInternet of Things (IoT) is a network of objects on which objects can communicate with other objects. The Internet of Things is currently constantly under numerous attacks due to technical, legal and human problems. One of the most important of these attacks is the Denial of Service (DoS) attack, in which normal network services are out of service and it is impossible for objects and users to access the server and other resources. Existing security solutions have not been able to effectively prevent interruption attacks in Internet of Things services. Software-oriented network (SDN) is a new architecture in the network based on the separation of the control and data plane of the network. Programmability and network management capability by SDN can be used in IoT services because some IoT devices send data periodically and in certain time intervals. SDN can help reduce or prevent the data flood caused by IoT if properly deployed in the data center. In this article, a method to detect DDoS attacks in Internet of Things based on SDN is presented and then an algorithm to reduce DDoS attacks is presented. The proposed method is based on the entropy criterion, which is one of the most important concepts in information theory and is calculated based on the characteristics of the flow. In this method, by using two new components on the controller to receive incoming packets and considering the time window and calculating entropy and flow rate, a possible attack is detected in the network, and then based on the statistics of the flow received from the switches, the certainty of the attack is determined. Compared to the existing methods, the proposed method has improved 12% in terms of attack detection time and 26% in terms of false positives/negatives. Manuscript profile -
Open Access Article
817 - Video Summarization Using a Clustering Graph Neural Networks
Mahsa RahimiResketi Homayun Motameni Ebrahim Akbari Hossein NematzadehThe increase of cameras nowadays, and the power of the media in people's lives lead to a staggering amount of video data. It is certain that a method to process this large volume of videos quickly and optimally becomes especially important. With the help of video summar MoreThe increase of cameras nowadays, and the power of the media in people's lives lead to a staggering amount of video data. It is certain that a method to process this large volume of videos quickly and optimally becomes especially important. With the help of video summarization, this task is achieved and the film is summarized into a series of short but meaningful frames or clips. This study tried to cluster the data by an algorithm (K-Medoids) and then with the help of a convolutional graph attention network, temporal and graph separation is done, then in the next step with the connection rejection method, noises and duplicates are removed, and finally summarization is done by merging the results obtained from two different graphical and temporal steps. The results were analyzed qualitatively and quantitatively on three datasets SumMe, TVSum, and OpenCv. In the qualitative method, an average of 88% accuracy rate in summarization and 31% error rate was achieved, which is one of the highest accuracy rates compared to other methods. In quantitative evaluation, the proposed method has a higher efficiency than the existing methods. Manuscript profile -
Open Access Article
818 - Design of a Secondary Controller Based on Distributed Cooperative Control of Distributed Generators (DGs) with Multi-Agent Systems Approach Considering DoS Cyber Attacks
Abdollah Mirzabeigi Ali Kazemy Mehdi Ramezani Seyed Mohammad AzimiToday, in many control methods, neighboring system information is used for better control and synchronization between different units, and therefore, in the access and transmission of information through communication links, problems such as disruption, uncertainty, noi MoreToday, in many control methods, neighboring system information is used for better control and synchronization between different units, and therefore, in the access and transmission of information through communication links, problems such as disruption, uncertainty, noise, delay, and cyber-attacks occur. In this paper, the effect of the Denial of Service (DoS) cyber-attack on the microgrid in island mode is investigated and a cooperative distributed hierarchical controller is designed with the presence of this cyber-attack. Distributed Generations (DGs) have been analyzed with the help of multi-agent systems and the communication network between them using graph theory. The effects of the DoS cyber-attack on the model of DGs are mathematically formulated and in proving the stability and synchronization of frequency and voltage, the suitable Lyapunov function is presented and the stability analysis of DGs against these cyber-attacks is performed and the stability and synchronization conditions of DGs are proved. To confirm the proposed theoretical issues, a case study model is simulated despite the DoS attack on the communicative links in Matlab Simulink, and the results show the performance of the designed controller in different conditions. Manuscript profile -
Open Access Article
819 - Ontology Matching Based on Maintaining Local Similarity of Information Using Propagation Technique
NazarMohammad Parsa Asieh GhanbarpourIn recent years, ontologies, as one of the most important components of the semantic web, have expanded in various fields. The problem of ontology matching has been raised with the aim of creating a set of mappings between entities of ontologies. This problem is classif MoreIn recent years, ontologies, as one of the most important components of the semantic web, have expanded in various fields. The problem of ontology matching has been raised with the aim of creating a set of mappings between entities of ontologies. This problem is classified as an NP-hard problem. Therefore, greedy methods have been proposed to solve it in different ways. Selecting the appropriate lexical, structural and semantic similarity criteria and using an effective combination method to obtain the final mapping is one of the most important challenges of these methods. In this paper, an automatic method of matching ontologies is proposed to provide a one-to-one mapping set. This method detects primary mappings based on a new lexical similarity criterion, which is accordance with the descriptive essence of entities and combining this similarity with semantic similarity obtained from external semantic sources. By locally propagating the score of initial mappings in the class hierarchy graph, structurally matching entities are identified. In this method, property matching is examined in a separate step. In the final step, the mapping filter is applied in order to maintain the consistency of the final mapping set. In the evaluation section, comparing the performance of the lexical similarity measure compared to other proposed textual similarity measures, indicates the efficiency of this measure in the problem of ontology matching. In addition, the results of the proposed matching system compared to the results of the set of participating systems in the OAEI competitions shows this system in the second place and higher than many complex matching systems. Manuscript profile -
Open Access Article
820 - Presenting a Network-on-Chip Mapping Approach Based on Harmony Search Algorithm
Zahra Bagheri Fatemeh Vardi Alireza MahjoubIn network-on-chip implementation, mapping can be considered as an important step in application implementation. The tasks of an application are often represented in the form of a core graph. The cores establish a link between themselves using a communication platform a MoreIn network-on-chip implementation, mapping can be considered as an important step in application implementation. The tasks of an application are often represented in the form of a core graph. The cores establish a link between themselves using a communication platform and often the network on the chip. For finding proper mapping for an application, developers have proposed various algorithms. In most cases, due to the complexity, exact search methods are used to find the mapping. However, these methods are suitable for networks with small dimensions. As the size of the network increases, the search time also increases exponentially. This article, from the perspective of a heuristic approach, uses the harmony search method to decide when to connect cores to routers. Our approach uses an improved version of the harmony search algorithm with a focus on reducing power consumption and delay. Algorithm complexity analysis reveals a more appropriate solution compared to similar algorithms with respect to application traffic pattern. Compared to similar methods, the algorithm achieves 39.98% less delay and 61.11% saving in power consumption. Manuscript profile -
Open Access Article
821 - Increase of Image Sharpness Using Visual Saliency
Mina Vafaei Jahan Abbas Ebrahimi moghadam Morteza KhademiIncreasing the sharpness of the image, in many cases, refers to strengthening its high frequency components and increasing the sharpness at the edges. In the existing models of increasing clarity, it is assumed that the sensitivity of the human visual system is the same MoreIncreasing the sharpness of the image, in many cases, refers to strengthening its high frequency components and increasing the sharpness at the edges. In the existing models of increasing clarity, it is assumed that the sensitivity of the human visual system is the same in the whole scene, and the effects of visual attention caused by visual salience are not included in these models. Various studies have shown that visual sensitivity is higher in places that attract more attention. Therefore, increasing image clarity based on visual attention can cause greater perceived clarity in the image. In this article, a model for increasing image sharpness is proposed, which uses the relationship between the map of high frequency image components and visual salience to determine the optimal value of image sharpness. By using a non-linear function, the proposed model expresses the optimal sharpness value for an image according to its visual prominence. Determining the parameters of the nonlinear function in the form of a modeled optimization problem, the solution of which leads to finding the optimal sharpness value automatically. The results show that the proposed method has a more effective performance than the other compared methods if the appropriate values of the control parameters are selected. Manuscript profile -
Open Access Article
822 - Designing Quadrature VCO in a Wide Range Frequency
Amir Hossein Mahdavi Hossein Miar Naimi Mohsen JavadiThe 5G network has been created to solve the limitation of communication coverage in large areas. One of the challenges of the 5G is the construction of quadrature oscillators in a wide range of high frequencies. Phase error and amplitude imbalance cause a decrease in t MoreThe 5G network has been created to solve the limitation of communication coverage in large areas. One of the challenges of the 5G is the construction of quadrature oscillators in a wide range of high frequencies. Phase error and amplitude imbalance cause a decrease in the image rejection ratio (IRR), which affects the communication error vector magnitude (EVM). The quadrature phases are generated by a one-stage poly-phase filter (PPF) whose resistors consist of four N-type MOSFETs in triode mode, each of its four gate ends is set by a voltage. The feedback circuit constantly adjusts the center frequency of the PPF according to the input frequency by changing the resistance of the MOSFETs. In this research, the circuit is simulated in the advanced design system software environment in the frequency range of 2 to 6 GHz with a central frequency of 4 GHz, which has reduced the quadrature phase error to less than 1 to 9 degrees. Then, the governing mathematical equations of the circuit were extracted and the network function of the circuit was designed in the Simulink MATLAB environment. The main advantage of the Simulink method is the high speed of simulation. Manuscript profile -
Open Access Article
823 - Spam Detection in Twitter by Ensemble Learning Approach
Maryam Fasihi Mohammad Javad shayegan zahra hosieni zahra sejdehToday, social networks play a crucial role in disseminating information worldwide. Twitter is one of the most popular social networks, with 500 million tweets sent on a daily basis. The popularity of this network among users has led spammers to exploit it for distributi MoreToday, social networks play a crucial role in disseminating information worldwide. Twitter is one of the most popular social networks, with 500 million tweets sent on a daily basis. The popularity of this network among users has led spammers to exploit it for distributing spam posts. This paper employs a combination of machine learning methods to identify spam at the tweet level. The proposed method utilizes a feature extraction framework in two stages. In the first stage, Stacked Autoencoder is used for feature extraction, and in the second stage, the extracted features from the last layer of Stacked Autoencoder are fed into the softmax layer for prediction. The proposed method is compared and evaluated against some popular methods on the Twitter Spam Detection corpus using accuracy, precision, recall, and F1-score metrics. The research results indicate that the proposed method achieves a detection of 78.1%. Overall, the proposed method, using the majority voting approach with a hard selection in ensemble learning, outperforms CNN, LSTM, and SCCL methods in identifying spam tweets with higher accuracy. Manuscript profile -
Open Access Article
824 - A Fast and Lightweight Network for Road Lines Detection Using Mobile-Net Architecture and Different Loss Functions
Pejman Goudarzi milad Heydari Mehdi HosseinpourBy using the line detection system, the relative position of the self-driving cars compared to other cars, the possibility of leaving the lane or an accident can be checked. In this paper, a fast and lightweight line detection approach for images taken from a camera ins MoreBy using the line detection system, the relative position of the self-driving cars compared to other cars, the possibility of leaving the lane or an accident can be checked. In this paper, a fast and lightweight line detection approach for images taken from a camera installed in the windshield of cars is presented. Most of the existing methods consider the problem of line detection in the form of classification at the pixel level. These methods despite having high accuracy, suffer from two weaknesses of having the high computational cost and not paying attention to the general lines content information of the image (as a result, they cannot detect if there is an obstacle). The proposed method checks the presence of lines in each row by using the row-based selection method. Also, the use of Mobile-net architecture has led to good results with fewer learning parameters. The use of three different functions as cost functions, with different objectives, has resulted in obtaining excellent results and considering general content information along with local information. Experiments conducted on the TuSimple video image collection show the suitable performance of the proposed approach both in terms of efficiency and especially in terms of speed. Manuscript profile -
Open Access Article
825 - Reactive Power management in Distribution Network Considering uncertainties in the Presence of Discrete and Continuous Reactive Power Compensator Equipment
mahboobeh etemadizadeh maryam Ramezani H. FalaghiThe increasing rate of distributed generation resources expansion into power systems and the random nature of these resources have altered the operation and design of these networks, and reactive power management in distribution networks belongs to this category. The us MoreThe increasing rate of distributed generation resources expansion into power systems and the random nature of these resources have altered the operation and design of these networks, and reactive power management in distribution networks belongs to this category. The use of these resources in distribution networks is not without challenges and the lack of optimal management of reactive power may not bring economic efficiency for the network. Energy storage systems have the potential to solve this problem. Therefore, in this article, reactive power management in a microgrid connected to the main grid, taking into account distributed generation sources, energy storage systems and discrete reactive power compensating equipment, including capacitor banks, taking into account uncertainty in network load and Wind and solar power generation has been done. Finally, the efficiency of the method is demonstrated by numerical examinations on the distribution networks of 33 and 69 IEEE buses and in the GAMS optimization software. Manuscript profile -
Open Access Article
826 - Distributed Primal-Dual Algorithm with Variable Parameters and Bidirectional Incremental Cooperation
Ghanbar AzarniaSpecial conditions of wireless sensor networks, such as energy limitation, make it essential to accelerate the convergence of algorithms in this field, especially in the distributed compressive sensing (DCS) scenarios, which have a complex reconstruction phase. This pap MoreSpecial conditions of wireless sensor networks, such as energy limitation, make it essential to accelerate the convergence of algorithms in this field, especially in the distributed compressive sensing (DCS) scenarios, which have a complex reconstruction phase. This paper presents a DCS reconstruction algorithm that provides a higher convergence rate. The proposed algorithm is a distributed primal-dual algorithm in a bidirectional incremental cooperation mode where the parameters change with time. The parameters are changed systematically in the convex optimization problems in which the constraint and cooperation functions are strongly convex. The proposed method is supported by simulations, which show the higher performance of the proposed algorithm in terms of convergence rate, even in stricter conditions such as the small number of measurements or the lower degree of sparsity. Manuscript profile -
Open Access Article
827 - Semantic Word Embedding Using BERT on the Persian Web
shekoofe bostan Ali-Mohammad Zare-Bidoki mohamad reza pajohanUsing the context and order of words in sentence can lead to its better understanding and comprehension. Pre-trained language models have recently achieved great success in natural language processing. Among these models, The BERT algorithm has been increasingly popular MoreUsing the context and order of words in sentence can lead to its better understanding and comprehension. Pre-trained language models have recently achieved great success in natural language processing. Among these models, The BERT algorithm has been increasingly popular. This problem has not been investigated in Persian language and considered as a challenge in Persian web domain. In this article, the embedding of Persian words forming a sentence was investigated using the BERT algorithm. In the proposed approach, a model was trained based on the Persian web dataset, and the final model was produced with two stages of fine-tuning the model with different architectures. Finally, the features of the model were extracted and evaluated in document ranking. The results obtained from this model are improved compared to results obtained from other investigated models in terms of accuracy compared to the multilingual BERT model by at least one percent. Also, applying the fine-tuning process with our proposed structure on other existing models has resulted in the improvement of the model and embedding accuracy after each fine-tuning process. This process will improve result in around 5% accuracy of the Persian web ranking. Manuscript profile -
Open Access Article
828 - Wide Area out of Step Prediction of Interconnected Power System Using Decision Tree C5.0 Based on WAMS Data
Soheil RanjbarThis paper presents a new method for Out-of-Step detection in synchronous generators based on Decision Tree theory. For distinguishing between power swing and out-of-step conditions a series of input features are introduced and used for decision tree training. For gener MoreThis paper presents a new method for Out-of-Step detection in synchronous generators based on Decision Tree theory. For distinguishing between power swing and out-of-step conditions a series of input features are introduced and used for decision tree training. For generating input training samples, a series of measurements are taken under various faults including operational and topological disturbances. The proposed method is simulated over 10 machines 39-bus IEEE test system and the simulation results are prepared as input-output pairs for decision tree induction and deduction. The merit of proposed out-of-step protection scheme lies in adaptivity and robustness of input features under different input scenarios Manuscript profile -
Open Access Article
829 - Identification of Transfer Function Parameters of Brushless DC Motor Using Particle Swarm Algorithm
Ahmad Shirzadi Arash Dehestani Kolagar Mohammad Reza Alizadeh PahlavaniSo far, comprehensive and extensive studies have been conducted on the brushless DC motor (BLDC), and a part of these studies focuses on the estimation of the parameters of the transfer function of this motor. Estimation of BLDC motor transfer function parameters is ess MoreSo far, comprehensive and extensive studies have been conducted on the brushless DC motor (BLDC), and a part of these studies focuses on the estimation of the parameters of the transfer function of this motor. Estimation of BLDC motor transfer function parameters is essential to study motor performance and predict its behavior. Therefore, an efficient, accurate and reliable parameter estimation method is needed. In this article, the problem of estimating the parameters of the transfer function of the inverter-fed BLDC motor set has been solved using particle swarm algorithms (PSO). The results of using this algorithm have been compared with the results of other optimization algorithms. The comparison of these results has shown that the PSO algorithm is an efficient, accurate and reliable method for solving the transfer function parameter estimation problem. Manuscript profile -
Open Access Article
830 - Machine Learning-Based Security Resource Allocation for Defending against Attacks in the Internet of Things
Nasim Navaei Vesal HakamiNowadays, the Internet of Things (IoT) has become the focus of security attacks due to the limitation of processing resources, heterogeneity, energy limitation in objects, and the lack of a single standard for implementing security mechanisms. In this article, a solutio MoreNowadays, the Internet of Things (IoT) has become the focus of security attacks due to the limitation of processing resources, heterogeneity, energy limitation in objects, and the lack of a single standard for implementing security mechanisms. In this article, a solution will be presented for the problem of security resources allocating to deal with attacks in the Internet of Things. Security Resource Allocation (SRA) problem in the IoT networks refers to the placement of the security resources in the IoT infrastructure. To solve this problem, it is mandatory to consider the dynamic nature of the communication environments and the uncertainty of the attackers' actions. In the traditional approaches for solving the SRA, the attacker works over based on his assumptions about the system conditions. Meanwhile, the defender collects the system's information with prior knowledge of the attacker's behavior and the targeted nodes. Unlike the mentioned traditional approaches, this research has adopted a realistic approach for the Dynamic Security Resources Allocation in the IoT to battle attackers with unknown behavior. In the stated problem, since there is a need to decide on deploying several security resources during the learning periods, the state space of the strategies is expressed in the combinatorial form. Also, the SRAIoT problem is defined as a combinatorial-adversarial multi-armed bandit problem. Since switching in the security resources has a high cost, in real scenarios, this cost is included in the utility function of the problem. Thus, the proposed framework considers the switching cost and the earned reward. The simulation results show a faster convergence of the weak regret criterion of the proposed algorithms than the basic combinatorial algorithm. In addition, in order to simulate the IoT network in a realistic context, the attack scenario has been simulated using the Cooja simulator. Manuscript profile -
Open Access Article
831 - An Algorithm for Optimal Control of a Class of Linear Time Varying Systems with Computational Time Reduction and Increasing Its Speed Approach in Engineering Problems
Mehdi Yousefi Tabari Zahra Rahmani Ali Vahidian Kamyad Seyed Jalil SadatiTime-delay systems have been very much considered in the last few decades. Many of these time-delay systems appear in different systems and branches of science such as engineering, chemistry, physics, disease models. The presence of delay makes the analysis and control MoreTime-delay systems have been very much considered in the last few decades. Many of these time-delay systems appear in different systems and branches of science such as engineering, chemistry, physics, disease models. The presence of delay makes the analysis and control of such systems much more complicated. In fact, the application of Pontryagin’s maximum principle to the optimal control problems with time-delay results in boundary value problem involving both delay and advance terms. In this paper, we consider a time-delay optimal control problems. The first section, using the Pontryagin's maximum principle for optimal control problems with time delay, the necessary optimality conditions for this problem, are obtained. Then a new algorithm is proposed to solve this problem numerically. This algorithm is based on an approximation for derivatives and linear interpolation for delayed arguments. Finally, the resulting equations becomes a linear programming problem that can be solved numerically. The efficiency of the proposed method is evaluated by solving several numerical examples. Manuscript profile -
Open Access Article
832 - Designing a Secure Consensus Algorithm for Use in Blockchain
Hosein Badri Masumeh SafkhaniBlockchain technology eliminates the need for a central authority. This system consists of a distributed ledger with a chain of blocks that records every network transaction. This ledger is replicated by every node in the network. We require a mechanism that provides co MoreBlockchain technology eliminates the need for a central authority. This system consists of a distributed ledger with a chain of blocks that records every network transaction. This ledger is replicated by every node in the network. We require a mechanism that provides consensus for the entire network, known as "consensus algorithm," in order for the state of this ledger to be the same for all nodes of the network at any given time. In this work, we will suggest a novel consensus algorithm that protects the blockchain platform from four common attacks. These attacks include the Sybil, Denial of Service, 51%, and Eclipse attacks. Due to its multiple control parameters, generic and all-purpose character, immunity to different attacks, and acceptable execution speed, our suggested algorithm can be used to build secure blockchain-based systems in a variety of applications. Manuscript profile -
Open Access Article
833 - Stabilizing and Synchronizing the Islanded Microgrid with the Presence of Sensor and Actuator Fault and Cyber-Attack with Secondary Controller Design
Abdollah Mirzabeigi Ali Kazemy Mehdi Ramezani Seyed Mohammad AzimiIn many microgrid control methods, the output information of sensors and actuators of neighbouring distributed generators (DGs) is used to stabilize and synchronize voltage and frequency. Many problems such as disturbances, uncertainty, unmodeled dynamics, cyber-attacks MoreIn many microgrid control methods, the output information of sensors and actuators of neighbouring distributed generators (DGs) is used to stabilize and synchronize voltage and frequency. Many problems such as disturbances, uncertainty, unmodeled dynamics, cyber-attacks, noise, time delay, and measurement errors cause invalid data problems and errors in the system. Better microgrid control depends on the quality of data measured or sent from the output of sensors and actuators. In this paper, according to the advantages of the Cooperative distributed hierarchical control, it is used for control and synchronization in the islanded microgrid with the presence of sensor and actuator error. To synchronize DGs with multi-agent systems and communication channels, it is modeled with graph theory. To stabilize and synchronize, sensor and actuator error in the DG model is mathematically formulated. In the proof of stability and synchronization, the appropriate Lyapunov candidate is presented and the conditions of stability and synchronization are proved. Finally, to show the effectiveness of the designed controller in solving communication channel problems and verifying the presented theory, a case study is simulated in the MATLAB/Simulink software environment with the presence of error and cyber-attack of sensors and actuators. Manuscript profile -
Open Access Article
834 - Multi-Objective Economic-Environment Scheduling of Microgrids in the Presence of Hybrid Electric Vehicles and Demand Response to Smooth the Distribution Nodal Prices
ali mirzaei NAVID TAGHIZADEGAN KALANTARI Sajad Najafi RavadaneghToday, with the growing demand for hybrid electric vehicles in microgrids, electricity supply, environmental issues, and rescheduling are among the challenges of microgrids that must be solved and suitable solutions provided. To overcome these challenges, this paper int MoreToday, with the growing demand for hybrid electric vehicles in microgrids, electricity supply, environmental issues, and rescheduling are among the challenges of microgrids that must be solved and suitable solutions provided. To overcome these challenges, this paper introduces a new multi-objective optimization model, which in the first objective, minimizes the total operation cost of the microgrid, and in the second objective, improves the reliability index by reducing the amount of energy not supplied. Due to these two objectives, a multi-objective evolutionary seagull optimization algorithm is used to find the optimal global solutions. In this regard, hybrid electric vehicles and demand response programs are used to smooth out distribution nodal prices and reduce CO2 emissions. The 69-bus distribution network has been used to evaluate the efficiency of the proposed method. Manuscript profile -
Open Access Article
835 - Data-Driven Sliding Mode Control Based on Projection Recurrent Neural Network for HIV Infection: A Singular Value Approach
Ashkan Zarghami mehdi Siahi Fereidoun Nowshiravan RahatabadIn the present study, drug treatment of HIV infection is investigated using a Data-Driven Sliding Mode Control (DDSMC) combined with a Projection Recurrent Neural Network (PRNN). The major objective is to establish the control law that eliminates the need for HIV infect MoreIn the present study, drug treatment of HIV infection is investigated using a Data-Driven Sliding Mode Control (DDSMC) combined with a Projection Recurrent Neural Network (PRNN). The major objective is to establish the control law that eliminates the need for HIV infection mathematical formulae and ensures that the physical limits of the actuator are reached. This is accomplished by creating the concepts of model-free adaptive control, in which the relation between input and output is described using local dynamic linearized models based on quasi-partial derivatives. To determine the DDSMC law, a performance index is first defined based on the fulfillment of a discrete-time exponential reaching condition. By turning this index into a quadratic programming problem, the dynamics of the PRNN are extracted based on projection theory. The closed-loop system is explicitly determined using the optimizer output equation and the closed-loop stability analysis is evaluated using the singular value approach. The simulation results reveal that the proposed algorithm has robust performance in conducting the state variables of HIV infection to the healthy equilibrium point in the face of model uncertainty and external disturbances when compared to one of the newest control techniques. Manuscript profile -
Open Access Article
836 - Identification of Cancer-Causing Genes in Gene Network Using Feedforward Neural Network Architecture
مصطفی اخوان صفار abbas ali rezaeeIdentifying the genes that initiate cancer or the cause of cancer is one of the important research topics in the field of oncology and bioinformatics. After the mutation occurs in the cancer-causing genes, they transfer it to other genes through protein-protein interact MoreIdentifying the genes that initiate cancer or the cause of cancer is one of the important research topics in the field of oncology and bioinformatics. After the mutation occurs in the cancer-causing genes, they transfer it to other genes through protein-protein interactions, and in this way, they cause cell dysfunction and the occurrence of disease and cancer. So far, various methods have been proposed to predict and classify cancer-causing genes. These methods mostly rely on genomic and transcriptomic data. Therefore, they have a low harmonic mean in the results. Research in this field continues to improve the accuracy of the results. Therefore, network-based methods and bioinformatics have come to the aid of this field. In this study, we proposed an approach that does not rely on mutation data and uses network methods for feature extraction and feedforward three-layer neural network for gene classification. For this purpose, the breast cancer transcriptional regulatory network was first constructed. Then, the different features of each gene were extracted as vectors. Finally, the obtained vectors were given to a feedforward neural network for classification. The obtained results show that the use of methods based on multilayer neural networks can improve the accuracy and harmonic mean and improve the performance compared to other computational methods. Manuscript profile -
Open Access Article
837 - Multi-Objective Predictive Control of Two-Motor Drive System with Five-Leg Inverter
Reza Mohammadi Nik Mohammad Reza Alizadeh Pahlavani Arash Dehestani KolagarDual-motor drive systems have been widely favored due to many advantages, including reduced dimensions and cost. In this paper, a model-based predictive control (MPC) method for a dual-motor drive system fed by a five-leg inverter (FLI) is introduced. Among the advantag MoreDual-motor drive systems have been widely favored due to many advantages, including reduced dimensions and cost. In this paper, a model-based predictive control (MPC) method for a dual-motor drive system fed by a five-leg inverter (FLI) is introduced. Among the advantages of the MPC method, the independent and fast tracking of reference control variables and the elimination of cascade control structures dependent on the modulator for multi-motor systems can be mentioned. PI loops have disadvantages such as delayed time response, as well as design limitations of PI coefficients due to the FLI structure. In this paper, using the predictive control method based on the multi-objective model proportional to speed and current (MOMPC), the PI control loops have been removed. One of the challenges of this structure is how to allocate the DC link voltage to the motors. For this purpose, by defining the duty cycle corresponding to the steady-state voltage of the motors, the DC link voltage of the inverter is shared between the motors. In addition, by using this method, the control objectives of two motors become independent from each other, which reduce the torque ripple and current ripple of the motors. Manuscript profile -
Open Access Article
838 - Bounded Delays in Switching Signal for Switched Affine Systems
Arman Sehatnia F. Hashemzadeh Mahdi BaradaranniaIn this article, the consequence of the presence of delay in the switch signal for switched affine systems is investigated. First, based on the principles of stability, the process of extracting the switch law as the only control input is examined, then by presenting th MoreIn this article, the consequence of the presence of delay in the switch signal for switched affine systems is investigated. First, based on the principles of stability, the process of extracting the switch law as the only control input is examined, then by presenting the practical stability issue for switched systems, more realistic view of these systems is proposed. The main focus of the article will be on the effect of delay in the transmission of switching signal information. The presence of limited delay in switching signal is usually caused by high volume of switching law calculations or any cyber attacks. In this paper, the practical Lyapunov stability results related to the states before and after the presence of delay in switching signal for a linear switched affine system are compared analytically and simulated. The results of the comparison of these modes show that when the value of delay in switching signal increases, the ultimate limit of the error for system states becomes larger, and this means a decrease in the convergence of the system states. In this regard, the results implemented for a DC-DC power converter and the necessary comparisons are presented in the last chapter. Manuscript profile -
Open Access Article
839 - Design of New Ternary Flip Flops Using CNTFET in Nanotechnology
katayoun rahbari seyed ali hosseinoiUsing multi-valued logic can reduce chip interconnections, which can have a direct effect on chip area and interconnections power consumption. In recent years, due to the ability of Nano electronics in the design of multi-level circuits, research in this field has flour MoreUsing multi-valued logic can reduce chip interconnections, which can have a direct effect on chip area and interconnections power consumption. In recent years, due to the ability of Nano electronics in the design of multi-level circuits, research in this field has flourished. The sequential circuits, flip-flops are important components of processors and VLSI circuits. In this paper, for the first time, a ternary flip-flop with a pulse generator has been proposed, and also a ternary binary-decode flip-flop and the first flip-flop using a buffer have been introduced. Then these flip-flops are compared with themselves and previous circuits. Also, these flip-flops have been used in the design of the ternary counter. The simulation results with HSPICE software show the correct performance of the proposed circuits. There is a 20% improvement in delay and a reduction in the number of transistors in the STI pulse generator flip-flop model, 30% in the SP flip-flop, and 30% in the buffer flip-flop. Also, in the comparison table, the advantages and disadvantages of each have been examined. Manuscript profile -
Open Access Article
840 - Friendship Selection Based on Social Features in Social Internet of Things
Mohammad Mahdian S.Mojtaba MatinkhahThe Social Internet of Things (SIoT) network is the result of the union of the Social Network and the Internet of Things network; wherein, each object tries to use the services provided by its friends. In this network, to find the right friend in order to use the right MoreThe Social Internet of Things (SIoT) network is the result of the union of the Social Network and the Internet of Things network; wherein, each object tries to use the services provided by its friends. In this network, to find the right friend in order to use the right service is demanding. Great number of objects' friends, in classical algorithms, causes increasing the computational time and load of network navigation to find the right service with the help of friendly objects. In this article, in order to reduce the computational load and network navigation, it is proposed, firstly, to select the appropriate object friend from a heuristic approach; secondly, to use an adapted binary cuckoo optimization algorithm (AB-COA) which tries to select the appropriate friendly object to receive the service according to the maximum response capacity of each friendly object, and finally, adopting the Adamic-Adar local index (AA) with the interest degree centrality criterion so that it represents the characteristics of the common neighbors of the objects are involved in the friend selection. Finally, by executing the proposed algorithm on the Web-Stanford dataset, an average of 4.8 steps was obtained for reaching a service in the network, indicating the superiority of this algorithm over other algorithms. Manuscript profile -
Open Access Article
841 - LSBB Voltage Level Shifter based on Body Biasing
Reza Darvish khalilabadi amir bavafa toosiDesigners of modern digital and analog systems have been using multiple voltage levels in one circuit to increase performance. To convert voltage levels in high-performance circuits, it is necessary to use voltage level shifter (LS) circuits with high speed and low powe MoreDesigners of modern digital and analog systems have been using multiple voltage levels in one circuit to increase performance. To convert voltage levels in high-performance circuits, it is necessary to use voltage level shifter (LS) circuits with high speed and low power consumption. In this article, a high-performance LS circuit called LSBB (Level Shifter based on Body Biasing) is presented. LSBB consists of three parts: body biasing, current mirror circuit, and pull-up and pull-down circuit. The main idea of this design is to use the biasing circuit to depend on the base of the body of the transistors of the input stages to the VDDL voltage. This dependence leads to changes in the threshold voltage and as a result changes in the delay and power consumption to increase the performance of the circuit. Implementation in 180 nm TSMC technology and simulation with VDDL equal to 0.4 V, VDDH equal to 1.8 V and input frequency 1 MHz indicates the correct operation and high-performance of the proposed circuit, the delay values are 21.9 nS, the power consumption is 129 nW and the PDP equal to 2825 nW*nS confirms the high-performance of LSBB. Manuscript profile -
Open Access Article
842 - Design and Implementation of Model-Free Predictive Current and Speed Control of Surface Permanent Magnet Synchronous Motor using a Robust Nonlinear Disturbance Observer Against of Variation of Parameters and Disturbances
Mohammad Bagher SepahKar Abolfazl Halvaei NiasarIn the drive control of permanent magnet synchronous motors (PMSMs), the control system must be designed to work in different conditions and against of changes in motor parameters and unknown disturbances. In order to enhance the drive performance of PMSM motor, the mod MoreIn the drive control of permanent magnet synchronous motors (PMSMs), the control system must be designed to work in different conditions and against of changes in motor parameters and unknown disturbances. In order to enhance the drive performance of PMSM motor, the model-predictive control independent of current and speed model (MFPCSC) is proposed in this article. This method only uses the input and output of the system and does not involve the motor parameters in the drive control, and it is robust to the changes of the motor parameters. The conventional model-independent predictive control method requires setting several control parameters. To improve the performance of the drive system of this motor and make it robust to changes in parameters and disturbances, the proposed MFPCSC method is designed based on the nonlinear disturbance observer (NDO). This observer can estimate system disturbances with more accuracy and stability, and the amount of calculations is small. The simulation and practical test results of the proposed MFPCSC method combined with the NDO show that the proposed control method has high robustness to parameter changes, favorable transient response, small output ripple, and improved transient characteristics, and can accurately and stably estimate system disturbances. Manuscript profile -
Open Access Article
843 - Optimization of Initial States for Adiabatic Quantum Computing in a Quantum Algorithm
Arash Karimkhani Amir Ghal’eIn any adiabatic quantum computation, there exist an initial state that must be used in the corresponding quantum algorithm. In this paper, the relation between an initial state and allowed energy level of an implemented generalized Deutsch’s algorithm is investigated. MoreIn any adiabatic quantum computation, there exist an initial state that must be used in the corresponding quantum algorithm. In this paper, the relation between an initial state and allowed energy level of an implemented generalized Deutsch’s algorithm is investigated. To study the generalized Deutsch’s algorithm, a compacted form for the output states of the algorithm is obtained. It has been shown that one can prepare the initial states in such a way that control the minimum of energy. By using numerical methods, the minimum values of allowed energy levels for the initial state are obtained. Also, to study the dynamics of the system is chosen. The corresponding Hamiltonian for the algorithm is obtained and it has been shown that one of the energy levels describes a binding state. Manuscript profile -
Open Access Article
844 - Design and Collection of Speech Data as the First Step of Localization the Intelligent Diagnosis of Autism in Iranian Children
Maryam Alizadeh Shima tabibianAutism Spectrum Disorder is a type of disorder in which, the patients suffer from a developmental disorder that manifests itself by symptoms such as inability to social communication. Thus, the most apparent sign of autism is a speech disorder. The first part of this pa MoreAutism Spectrum Disorder is a type of disorder in which, the patients suffer from a developmental disorder that manifests itself by symptoms such as inability to social communication. Thus, the most apparent sign of autism is a speech disorder. The first part of this paper reviews research studies conducted to automatically diagnose autism based on speech processing methods. According to our review, the main speech processing approaches for diagnosing autism can be divided into two groups. The first group detects individuals with autism by processing their answers or feelings in response to questions or stories. The second group distinguishes people with autism from healthy people because of the accuracy of recognizing their spoken utterances based on automatic speech recognition systems. Despite much research being conducted outside Iran, few studies have been conducted in Iran. The most important reason for this is the lack of rich data that meet the needs of autism diagnosis based on the speech processing of suspected people. In the second part of the paper, we discuss the process of designing, collecting, and evaluating a speaker-independent dataset for autism diagnosis in Iranian children as the first step in the localization of the mentioned field. Manuscript profile -
Open Access Article
845 - Combination of Instance Selection and Data Augmentation Techniques for Imbalanced Data Classification
Parastoo Mohaghegh Samira Noferesti Mehri RajaeiMohaghegh, S. Noferesti*, and M. Rajaei Abstract: In the era of big data, automatic data analysis techniques such as data mining have been widely used for decision-making and have become very effective. Among data mining techniques, classification is a common method fo MoreMohaghegh, S. Noferesti*, and M. Rajaei Abstract: In the era of big data, automatic data analysis techniques such as data mining have been widely used for decision-making and have become very effective. Among data mining techniques, classification is a common method for decision making and prediction. Classification algorithms usually work well on balanced datasets. However, one of the challenges of the classification algorithms is how to correctly predicting the label of new samples based on learning on imbalanced datasets. In this type of dataset, the heterogeneous distribution of the data in different classes causes examples of the minority class to be ignored in the learning process, while this class is more important in some prediction problems. To deal with this issue, in this paper, an efficient method for balancing the imbalanced dataset is presented, which improves the accuracy of the machine learning algorithms to correct prediction of the class label of new samples. According to the evaluations, the proposed method has a better performance compared to other methods based on two common criteria in evaluating the classification of imbalanced datasets, namely "Balanced Accuracy" and "Specificity". Manuscript profile -
Open Access Article
846 - Implementation of Comparator with Four-Level Input and Three-level output Based on Carbon Nano Tube Field Effect Transistor Technology
Ebrahim Farahi Gonbari موسی یوسفی Khalil MonfarediDue to the increase of processing data, processing systems should be designed to occupy less space. The enlargement of the processing systems has caused the growth of the data size, on the other hand, the problems of miniaturization of metal-oxide semiconductor field ef MoreDue to the increase of processing data, processing systems should be designed to occupy less space. The enlargement of the processing systems has caused the growth of the data size, on the other hand, the problems of miniaturization of metal-oxide semiconductor field effect transistor MOSFET have faced many problems for the designers of processing circuits, the idea of replacing binary processing circuits with multi-valued level processing circuits. It reduces connections between systems and reduces space consumption. Because the implementation of multi-level processing circuits with MOSFET technology is very complicated and problematic, a suitable alternative for MOSFET is carbon nanotube field effect transistor (CNTFET) technology, which has many advantages such as the possibility of making transistors It has a different threshold voltage, which reduces design challenges in the implementation of multi-level systems. In this article, the structure of the transistor level of single-digit quaternary and multi-digit comparators is presented. Transistor level circuits are presented along with circuit techniques. The simulation results also show that the amount of propagation delay and power consumption in the single-digit quaternary comparator is 17.3 picoseconds and 4.59 microwatts, respectively, and the PDP index of this comparator is 79.2 aJ. All simulation results of proposed comparators in this article have been obtained using carbon nanotube field effect transistors and 32 nm technology in HSPICE software. Manuscript profile -
Open Access Article
847 - Analysis and Implementation of a Step-Down DC-DC Converter with a New Control Method to Reduce Converter Losses
Mohamad Reza Banaei sajad gabeli saniA step-down converter based on buck and buck-boost converters with a loss reduction technique is proposed in this paper. Utilizing non-electrolytic capacitors in the implementation of the proposed converter has resulted in an increase in circuit life and a reduction in MoreA step-down converter based on buck and buck-boost converters with a loss reduction technique is proposed in this paper. Utilizing non-electrolytic capacitors in the implementation of the proposed converter has resulted in an increase in circuit life and a reduction in weight and volume. This paper compares the proposed converter to other buck converters. To increase the output efficiency of the converter in comparison to other structures, a new method based on determining the working duty-cycles has been employed to reduce the losses of the converter, resulting in an increase in the converter's output efficiency. In order to demonstrate the differences in efficiency between the proposed method and the conventional method, the efficiency of the converter has been calculated using real-world conditions and the output loss results have been compared. In addition, the proposed converter has a common ground with the input source and has a suitable reduction gain. Finally, this converter has been implemented as a PCB and tested with 100 watts of output power. Manuscript profile -
Open Access Article
848 - Design and Implementation of an Optimized Controller by TLBO Algorithm on a Twin-Rotor System
Mostafa Yazdani Khosro KhandaniIn this research, a new intelligent control design using Teaching-Learning-Based-Optimization (TLBO) algorithm to optimize PID controller coefficients is presented. This method has been applied on the twin rotor system which has been constructed in Control Engineering L MoreIn this research, a new intelligent control design using Teaching-Learning-Based-Optimization (TLBO) algorithm to optimize PID controller coefficients is presented. This method has been applied on the twin rotor system which has been constructed in Control Engineering Lab at Arak University. The purpose of controlling the twin rotor system is to stabilize the system in the zero degree horizontal position. After modeling and obtaining the state space description, the PID controller is designed and implemented on the system. In this study, by reviewing meta-heuristic optimization methods such as particle swarm optimization algorithm, genetic algorithm, colonial competition algorithm and differential evolution algorithm, the optimization results were compared with the above-mentioned meta-heuristic methods. With the optimization performed by the teaching and learning algorithm, the stability and faster performance of the system compared to other meta-heuristic methods can be seen. The merit of TLBO is that it does not have control parameters, which makes it convenient to employ. The simulation results of the PID controller for a twin rotor system show the effectiveness of the proposed methods. Manuscript profile