Iranian Journal of Electrical and Electronic Engineering

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Microarray technology is a new and powerful tool for concurrent monitoring of large number of genes expressions. Each microarray experiment produces hundreds of images. Each digital image requires a large storage space. Hence, real-time processing of these images and transmission of them necessitates efficient and custom-made lossless compression schemes. In this paper, we offer a new architecture for lossless compression of microarray images. In this architecture, we have used a dedicated hardware for separation of foreground pixels from the background ones. By separating these pixels and using pipeline architecture, a higher lossless compression ratio has been achieved as compared to other existing methods

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Almost all of electric utility companies are planning to improve their management automation system, in order to meet the changing requirements of new liberalized energy market and to benefit from the innovations in information and communication technology (ICT or IT). Architectural design of the utility management automation (UMA) systems for their IT-enabling requires proper selection of IT choices for UMA system, which leads to multi-criteria decision-makings (MCDM). In response to this need, this paper presents a model-based architectural design-decision methodology. The system design problem is formulated first then, the proposed design method is introduced, and implemented to one of the UMA functions–feeder reconfiguration function (FRF)– for a test distribution system. The results of the implementation are depicted, and comparatively discussed. The paper is concluded by going beyond the results and fair generalization of the discussed results finally, the future under-study or under-review works are declared.

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A new heterodyne nano-displacement with error reduction is presented. The main errors affecting the displacement accuracy of the nano-displacement measurement system including intermodulation distortion error, cross-talk error, cross-polarization error and phase detection error are calculated. In the designed system, a He-Ne laser having three-longitudinal-mode is considered as the stabilized source. The free spectral range of the 35cm laser cavity is about 435-MHz at 632.8-nm wavelength, which a secondary beat frequency equal to 300-kHz is produced by combining the reference and measurement beams. The resolution of the displacement measurement resulting from intermodulation distortion, cross-talk and cross-polarization errors is limited to 18-pm. Also, the phase detection uncertainty causes an error of only 5.9-pm in the displacement measurement. Furthermore, frequency-path models of two- and three-longitudinal-mode laser interferometers are modeled as the ac interference, ac reference, dc interference and optical power terms. A comparison study between two- and three-longitudinal-mode laser interferometers confirms that the performance of the designed system is considerably improved.

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This paper presents a novel implementation of an electromagnetically coupled patch antenna using air gap filled substrates to achieve the maximum bandwidth. We also propose an efficient modeling technique using the FDTD method which can substantially reduce the simulation cost for modeling the structure. The simulated results have been compared with measurement to show the broadband behavior of the antenna and the accuracy of the proposed modeling technique. The measured results show a 16% of VSWR<2 bandwidth which is considerable considering the inherent bandwidth limitations in microstrip antenna technology.

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Artificial neural network (ANN) has application in communication engineering in diverse areas such as channel equalization, channel modeling, error control code because of its capability of nonlinear processing, adaptability, and parallel processing. On the other hand, wavelet transform (WT) with both the time and the frequency resolution provides the exact representation of signal in both domains. Applying these signal processing tools for channel compensation and noise reduction can provide an enhanced performance compared to the traditional tools. In this paper, the slot error rate (SER) performance of digital pulse interval modulation (DPIM) in diffuse indoor optical wireless (OW) links subjected to the artificial light interference (ALI) is reported with new receiver structure based on the discrete WT (DWT) and ANN. Simulation results show that the DWT-ANN based receiver is very effective in reducing the effect of multipath induced inter-symbol interference (ISI) and ALI.

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In this article, perfectly matched layer (PML) for the boundary treatment and an efficient compact two dimensional finite-difference frequency-domain (2-D FDFD) method were combined to model photonic crystal fibers (PCF). For photonic crystal fibers, if we assume that the propagation constant along the propagation direction is fixed, three-dimensional hybrid guided modes can be calculated by using only a two-dimensional mesh. An index-guiding PCF with an array of air-holes surrounding the silica core region has special characteristics compared with conventional single-mode fibers (SMFs). Using this model, the fundamental characteristics of single mode photonic crystal fibers (SMPCFs) such as confinement loss, bending loss, effective mode area and chromatic dispersion are numerically investigated. The results revealed that low confinement loss and zero-flattened chromatic dispersion can be obtained by varying the air-holes diameter of each ring along the PCF radius. In this work, an especial PCF with nearly zero-flattened dispersion (1.3 ps/nm/km) over a wide wavelength range which covers O, E, S, C, L and U telecommunication wavelength bands and low confinement loss (0.06 dB/km at 1.55μm) is designed. Macro-bending loss performance of the designed PCF is also studied and it is found that the fiber shows low bending losses for the smallest feasible bending radius of 5 mm. Also, it is revealed that the temperature sensitivity of PCFs is very low in compared with the conventional fibers.

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The aim of this study is to introduce a new methodology for isolation of ectopic rhythms of ambulatory electrocardiogram (ECG) holter data via appropriate statistical analyses imposing reasonable computational burden. First, the events of the ECG signal are detected and delineated using a robust wavelet-based algorithm. Then, using Binary Neyman-Pearson Radius test, an appropriate classifier is designed to categorize ventricular complexes into "Normal + Premature Atrial Contraction (PAC)" and "Premature Ventricular Contraction (PVC)" beats. Afterwards, an innovative measure is defined based on wavelet transform of the delineated P-wave namely as P-Wave Strength Factor (PSF) used for the evaluation of the P-wave power. Finally, ventricular contractions pursuing weak P-waves are categorized as PAC complexes however, those ensuing strong P-waves are specified as normal complexes. The discriminant quality of the PSF-based feature space was evaluated by a modified learning vector quantization (MLVQ) classifier trained with the original QRS complexes and corresponding Discrete Wavelet Transform (DWT) dyadic scale. Also, performance of the proposed Neyman-Pearson Classifier (NPC) is compared with the MLVQ and Support Vector Machine (SVM) classifiers using a common feature space. The processing speed of the proposed algorithm is more than 176,000 samples/sec showing desirable heart arrhythmia classification performance. The performance of the proposed two-lead NPC algorithm is compared with MLVQ and SVM classifiers and the obtained results indicate the validity of the proposed method. To justify the newly defined feature space (σi1, σi2, PSFi), a NPC with the proposed feature space and a MLVQ classification algorithm trained with the original complex and its corresponding DWT as well as RR interval are considered and their performances were compared with each other. An accuracy difference about 0.15% indicates acceptable discriminant quality of the properly selected feature elements. The proposed algorithm was applied to holter data of the DAY general hospital (more than 1,500,000 beats) and the average values of Se = 99.73% and P+ = 99.58% were achieved for sensitivity and positive predictivity, respectively.

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In this study, a new long-duration holter electrocardiogram (ECG) major events detection-delineation algorithm is described which operates based on the false-alarm error bounded segmentation of a decision statistic with simple mathematical origin. To meet this end, first three-lead holter data is pre-processed by implementation of an appropriate bandpass finite-duration impulse response (FIR) filter and also by calculation of the Euclidean norm between corresponding samples of three leads. Then, a trous discrete wavelet transform (DWT) is applied to the resulted norm and an unscented synthetic measure is calculated between some obtained dyadic scales to magnify the effects of low-power waves such as P or T-waves during occurrence of arrhythmia(s). Afterwards, a uniform length window is slid sample to sample on the synthetic scale and in each slid, six features namely as summation of the nonlinearly amplified Hilbert transform, summation of absolute first order differentiation, summation of absolute second order differentiation, curve length, area and variance of the excerpted segment are calculated. Then all feature trends are normalized and superimposed to yield the newly defined multiple-order derivative wavelet based measure (MDWM) for the detection and delineation of ECG events. In the next step, a α-level Neyman-Pearson classifier (which is a false-alarm probability-FAP controlled tester) is implemented to detect and delineate QRS complexes. To show advantages of the presented method, it is applied to MIT-BIH Arrhythmia Database, QT Database, and T-Wave Alternans Database and as a result, the average values of sensitivity and positive predictivity Se = 99.96% and P+ = 99.96% are obtained for the detection of QRS complexes, with the average maximum delineation error of 5.7 msec, 3.8 msec and 6.1 msec for P-wave, QRS complex and T-wave, respectively showing marginal improvement of detection-delineation performance. In the next step, the proposed method is applied to DAY hospital high resolution holter data (more than 1,500,000 beats including Bundle Branch Blocks-BBB, Premature Ventricular Complex-PVC and Premature Atrial Complex-PAC) and average values of Se=99.98% and P+=99.97% are obtained for QRS detection. In summary, marginal performance improvement of ECG events detection-delineation process in a widespread values of signal to noise ratio (SNR), reliable robustness against strong noise, artifacts and probable severe arrhythmia(s) of high resolution holter data and the processing speed 163,000 samples/sec can be mentioned as important merits and capabilities of the proposed algorithm.

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The design process of a superconducting current limiter (SFCL) requires simulation and definition of its electrical, magnetic and thermal properties in form of equivalent circuits and mathematical models. However, any change in SFCL parameters: dimension, resistance, and operating temperature can affect the limiting mode, quench time, and restore time. In this paper, following the simulation of electrical and thermal behavior of resistive and inductive SFCLs and investigation on their performance variation responded to change parameters, the best design cases will be selected by using multiple criteria decision making (MCDM) techniques. As a case study, to evaluate proposed MCDM approaches in design of superconducting fault current limiter, a model in which a SFCL is located at an outgoing feeder in a 20 kV distribution substation will be considered and best designs will be presented for both resistive and inductive type.

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We report the simulation results for impact of nonlinear Kerr effect on band structures of a ‎two dimensional photonic crystal (2D-PhC) with no defect, a PhC based W1-waveguide ‎‎(W1W), and also Coupled-Cavity Waveguides (CCWs). All PhC structres are assumed to a ‎square lattice of constant a made of GaAs rods of radius r=0.2a, in an air background. The ‎numerical simulation was performed using the nonlinear finite difference time domain ‎‎(NFDTD) technique. To study the impact of Kerr effect on the photonic band structures, E-‎polarized lights of peak input intensities 0.5 GW-cm−2≤I≤25 GW-cm−2 have been used. The ‎numerical results have shown that as the input light intensity increases, the band edges for all ‎PhC waveguide structures considered experience red shifts. These numerical results for CCWs ‎also show that the larger the light input intensity, the smaller is the corresponding maximum ‎light group velocity.‎

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This paper presents the results of Persian handwritten word recognition based on Mixture of Experts technique. In the basic form of ME the problem space is automatically divided into several subspaces for the experts, and the outputs of experts are combined by a gating network. In our proposed model, we used Mixture of Experts Multi Layered Perceptrons with Momentum term, in the classification Phase. We produce three different Mixture of Experts structure. Experimental result for proposed method show an error rate reduction of 6.42 % compare to the mixture of MLPs experts. Comparison with some of the most related methods indicates that the proposed model yields excellent recognition rate in handwritten word recognition.

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Differential Power Analysis (DPA) implies measuring the supply current of a cipher-circuit in an attempt to uncover part of a cipher key. Cryptographic security gets compromised if the current waveforms obtained correlate with those from a hypothetical power model of the circuit. As FPGAs are becoming integral parts of embedded systems and increasingly popular for cryptographic applications and rapid prototyping, it is imperative to consider security on FPGAs as a whole. During last years, there has been a large amount of work done dealing with the algorithmic and architectural aspects of cryptographic schemes implemented on FPGAs, however, there are only a few articles that assess their vulnerability to such attacks which, in practice, pose far a greater danger than algorithmic attacks. This paper first demonstrates the vulnerability of the Advanced Encryption Standard Algorithm (AES) implemented on a FPGA and then presents a novel approach for implementation of the AES algorithm which provides a significantly improved strength against differential power analysis with a minimal additional hardware overhead. The efficiency of the proposed technique was verified by practical results obtained from real implementation on a Xilinx Spartan-II FPGA.

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This paper presents a nonlinear analytical model for micromechanical silicon ring resonators with bulk-mode vibrations. A distributed element model has been developed to describe the dynamic behavior of the micromechanical ring resonator. This model shows the nonlinear effects in a silicon ring resonator focusing on the effect of large amplitudes around the resonance frequency, material and electrical nonlinearities. Through the combination of geometrical and material nonlinearities, closed-form expressions for third-order nonlinearity in mechanical stiffness of bulk-mode ring resonators are obtained. Using the perturbation method and the method of harmonic balance, the expressions for describing the effect of nonlinearities on the resonance frequency and stability are derived. The results, which show the effect of varying the AC drive voltage, initial gap, DC applied voltage and the quality factor on the frequency response and resonant frequencies, are discussed in detail. The nonlinear model introduces an appropriate method in the field of bulk-mode ring resonator design for achieving sufficient power handling and low motional resistance.

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Nowadays, the Fuzzy C-Means method has become one of the most popular clustering methods based on minimization of a criterion function. However, the performance of this clustering algorithm may be significantly degraded in the presence of noise. This paper presents a robust clustering algorithm called Bilateral Weighted Fuzzy CMeans (BWFCM). We used a new objective function that uses some kinds of weights for reducing the effect of noises in clustering. Experimental results using, two artificial datasets, five real datasets, viz., Iris, Cancer, Wine, Glass and a speech corpus used in a GMM-based speaker identification task show that compared to three well-known clustering algorithms, namely, the Fuzzy Possibilistic C-Means, Credibilistic Fuzzy C-Means and Density Weighted Fuzzy C-Means, our approach is less sensitive to outliers and noises and has an acceptable computational complexity.

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This paper presents the design and a new low-cost process for fabrication of a second-order micromechanical filter using UV-LIGA technology. The micromechanical filter consists of two identical bulk-mode ring resonators, mechanically coupled by a flexural-mode beam. A new lumped modeling approach is presented for the bulk-mode ring resonators and filter. The validity of the analytical derivation is investigated using the finite element method by ANSYS software. The new low-cost fabrication process is used to achieve a high aspect ratio of 16 with 3 μm gap spacing. The rigid graphite serves as a low-cost primary substrate and plating base of nickel as structural material. The fabrication process needs only three UV-lithography steps with Mylar masks to fabricate the main structure and pattern the printed circuit board as a secondary substrate. The frequency response of the fabricated filter is characterized as a function of the DC-bias voltage using a fully differential drive and sense interface circuit. The experimental results demonstrates micromechanical filter with center frequency in the vicinity of 10.31 MHz and percent bandwidth less than 0.3% using a DC-bias voltage of 60 V. The detailed fabrication process can be applied as an appropriate low-cost alternative to X-ray LIGA and silicon-based micromechanical filters.

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This paper presents modeling and control of a hybrid distributed energy sources including photovoltaic (PV), fuel cell (FC) and battery energy storage (BES) in a microgrid which provides both real and reactive power to support an unbalanced utility grid. The overall configuration of the microgrid including dynamic models for the PV, FC, BES and its power electronic interfacing are briefly described. Then controller design methodologies for the power conditioning units to control the power flow from the hybrid power plant to the unbalanced utility grid are presented. In order to distribute the power between power sources, the neuro-fuzzy power controller has been developed. Simulation results are presented to demonstrate the effectiveness and capability of proposed control strategy.

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This study focuses on one of the most effective type of capacity markets named Capacity Subscription (CS) market which is predicted to be widely used in the upcoming smart grids. Despite variant researches done about the mechanism and structure of capacity markets, their performances have been rarely tested in the presence of network constraints. Considering this deficiency, we tried to propose a new method to determine capacity prices in the network considering the transmission line flow limitations named Local capacity Prices (LP). This method is quite new and has not been tried before in any other similar researches. The philosophy of the proposed method is to determine capacity prices considering each consumer share of total peak demand. The first advantage of LP is that the consumers who benefit from the transmission facilities and are the responsible for transmission congestions, pay higher capacity prices than those whom their needed electricity is prepared locally. The second advantage of LP is that consumers connected to the same bus do not have to pay same capacity price due to their different shares of total peak demand. For more clarification, two other different methods named Branches Flow limit as a Global Limit (BFGL) and Locational Capacity Prices (LCP) are proposed and compared to the LP method in order to show LP method efficiency. The numerical results obtained from case studies show that the LP method follows more justice market procedure which results in more efficient capacity prices in comparison to BFGL and LCP methods.

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In this article, three new green's functions are presented for a narrow strip line (not a thin wire) inside or on a homogeneous dielectric, supposing quasi-TEM dominant mode. These functions have no singularity in contrast to so far presented ones, so that they can be used easily to determine the capacitance matrix of multi-layer and single-layer homogeneous coupled microstrip lines. To obtain the green’s functions, the Laplace’s equation is solved analytically in Fourier integral or Fourier series expressions, taking into account the boundary conditions including the narrow strip. The validity and accuracy of three presented green’s functions are verified by some examples.

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Microgrid (MG) is one of the important blocks in the future smart distribution systems. The scheduling pattern of MGs affects distribution system operation. Also, the optimal scheduling of MGs will be result in reliable and economical operation of distribution system. In this paper, an operational planning model of a MG which considers multiple demand response (DR) programs is proposed. In the proposed approach, all types of loads can participate in demand response programs which will be considered in either energy or reserve scheduling. Also, the renewable distributed generation uncertainty is covered by reserve prepared by both DGs and loads. The novelty of this paper is the demand side participation in energy and reserve scheduling, simultaneously. Furthermore the energy and reserve scheduling is proposed for day-ahead and real-time. The proposed model was tested on a typical MG system in connected mode and the results show that running demand response programs will reduce total operation cost of MG and cause more efficient use of resources.

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One of the related problems of OCR systems is discrimination of fonts in machine printed document images. This task improves performance of general OCR systems. Proposed methods in this paper are based on various fractal dimensions for font discrimination. First, some predefined fractal dimensions were combined with directional methods to enhance font differentiation. Then, a novel fractal dimension was introduced in this paper for the first time. Our feature extraction methods which consider font recognition as texture identification are independent of document content. Experimental results on different pages written by several font types show that fractal geometry can overcome the complexities of font recognition problem.