In this paper, a new CPW (Coplanar Waveguide) fed printed UWB antenna integrated with a narrowband antenna is designed and analyzed for cognitive radio applications. The ultra-wideband (UWB) and narrowband (NB) antennas provide bandwidth from 2.2 GHz to 11GHz and from 4.8 GHz to 5.7 GHz respectively and reasonable isolation between the antennas. A prototype of the integrated antenna was fabricated and its performance was verified. The dimensions of the FR4 substrate are 40 × 48 × 1.6 mm3.The antenna represents good radiation characteristics, stable gain and good time domain manner to deliver the requirements of the current wireless communication standards. Also, two external tuning circuits were designed to show the ability of the narrowband antenna for reconfiguration.

This paper proposes a flexible distributed energy management system for the coordinated operation of networked microgirds (MGs). Each MGs are considered as distinct entities with local objectives to optimize their own operation costs and power exchanges. The networked MGs are connected by a common bus, which can exchange electrical powers in this way. A two-level algorithm is used to coordinate the operational planning of these MGs. The first level is for the economic operation of each microgrids and the second level is to optimize the power exchanges. The planning of the MGs is simulated by taking into account the power flow equations and voltage constraints in a multi-MG system in a 24-hour period. A penalty price is also defined to control the power exchanges among MGs. The results of simulation indicate that using the proposed energy management system increases the performance and improves the reliability in each of the MGs.

In this paper, design, simulation, Implementation and measuring of wide band quad-ridged horn antenna near constant gain is presented. These antennas designed for about 13dBi gain and 2-18GHz frequency band. For achieving good specifications, we divided it in two frequency band 2-6 and 6-18 GHz and used quad-ridged horn antenna. All antennas have two orthogonal vertical and horizontal polarization outputs. The radiation patterns are almost symmetrical. These type of antennas have many applications in wideband Monopulse radio direction finding and communication measuring. These antennas can use as: medium gain antennas, wideband antenna array and wideband reflector antenna’s feed. In this paper we discusses about wide band quad-ridged horn antenna, designing with reasonably constant beam width and gain, implementation, driving, adjusting and matching of antenna. Also mechanical tolerance affect in antennas output matching will explain. At the end two simulated and measured data compared with each other and show they are very close to each other. The designed antennas beam width stability compared with some similar references, and show that have better stability than them.

Speed, accuracy, and power consumption of electronic devices, are important parameters that should be considered in the design and manufacturing of these devices. In this paper, a new design of modified phase-locked loop, using Carbon Nanotube Field Effect Transistors, is proposed. Using a differential structure of the ring oscillator, the coupled noise of the power supply and the substrate is eliminated.  In addition, using active inductor in the oscillator delay cells will cause a marked increase in oscillation frequency. In the presented phase detector circuit, by using a new open loop structure, the detection speed increases significantly. This will remove the divider circuit on loop track. By removing the divider circuit, the noise of the loop will be reduced considrably. The designed circuit is implemented once in MOSFET technology using 0.18 micrometers process and once again in 32nm process of carbon nano-tube field effect transistors technology with 0.9 volt power supply. The center frequency in this process is 68.5 GHz. The value of power consumption is less than 150 nano-watts and the acquisition time is less than 10 picoseconds.

In Time modulated arrays (TMAs), a switch is used instead of a phase shifter, which reduces the area, complexity, power consumption and the overal cost of the array. The TMA uses the switch as a control element for array weighting for the purpose of beam forming and beam steering. To lower the IC cost, the IC is designed to be as compact as small as possible. Moreover, the inexpensive CMOS 180 nm technology of TSMC is used for IC fabrication. The designed SPDT switch has 1.85 dB loss at 33 GHz, more than 17 dB isolation in Ka-band, and its area is 0.086 mm2. Compared to other switches designed in CMOS180 nm, this work has the lowest loss and area (up to now), and covers Ka-band completely. Another critical element of an array is a power combiner/divider with minimum area. Because this array has 4 elements, it needs a 4-way power divider. Four switches and power divider form a TMA IC, which covers 26.5 to 37.6 GHz with an area of 0.7 by 1.48 mm2. The power consumption of the array is zero since all the elements are passive and do not consume any power.

Today, energy supplies and transportation are not traditionally affordable. So smart grids mean intelligent energy management and lower energy costs for consumers. Significant features of smart grids, scalability, resilient network distribution capability, lower network cost distribution, network flexibility and fault tolerance. All of these features appear in the concept of a micro-grid. The use of scattered products in micro energy networks has many environmental, economic and technical benefits. Optimization of the location and magnitude of generators in micro-grids plays an important role in reducing energy losses. Optimal clustering of micro-networks is also a major challenge in this regard. In this paper, we present a framework for clustering of small networks using Apollonius circular algorithm. Apollonius circles increase the precision of clustering with the help of geometric structure and high precision. Performance is equal to 5.38% for distance criterion and 16.15% for the system energy losses, and finally, 14.79% of the total annual cost is better than the past work done. Then, we have used the simulated annealing algorithm to compensate for the lack of power micro-grids and the stability of the entire network, which this action led to reducing energy losses in the amount of 26.54 kw in study grid.

:In this paper, a novel controller is presented with an optimal approach for asymptotic stabilizing of a class of nonlinear time-varying systems in presence of model uncertainties and external disturbances. The proposed controller has two nominal and robust parts and there are new ideas in designing of both of them. In the first part, a new ccontrol Lyapunov function is presented for the nominal controller design. The suggested structure of the proposed control Lyapunov function is different from the common versions. This function is designed in a way that a sliding surface equation is appeared in it directly and therefore, provides the possibility of combining the robust part (which is designed based on sliding mode control technique) with nominal one. This combination leads to a different sub-optimal control law where its discontinuous part switches based on the moment value of the sliding surface and the continuous terms will be designed based on the optimality approach. At the end of the paper, this controller is applied to a nonlinear time-varying inertia pendulum and the simulation results are given to confirm the performance and efficiency of proposed approach and verifying the theoretical achievements.

The short-and the long-term information in speech signal are useful for speech enhancement, especially if the speech signal is corrupted by both stationary and non-stationary noises. This paper proposes a new approach to provide long-term speech input for a deep denoising autoencoder by reducing the number of frequency sub-bands of the input data. This paper also proposes a two phase speech enhancement approach. The first phase performs short-term speech enhancement by using a deep denoising autoencoder. In the second phase, long-term speech enhancement denoising autoencoder is applied on the output of short-term enhanced speech data. The proposed models were evaluated on the Aurora-2 Speech recognition corpus and our results show significant improvements of 0.3 in PESQ score at lower SNR values. The proposed models were evaluated on the recognition task where the proposed method results in 4% reduction in word error rate for the multi-condition training when compared to the baseline MFCC front-end.

Environmental concerns, energy and economical-technical issues make modern power networks to use alternative approaches such as demand response (DR). The DR is an ability of system to contribute smart loads in dynamic regulation, continuously. This paper presents a new DR approach for frequency control of isolated microgrids. The proposed method is based on a generalized droop characteristic (GDC), changing controllable active and reactive loads through a set of special equations. To verify the control method, several scenarios are simulated in which the system frequency and voltage are studied. The simulation results are carried out in the presence of the proposed DR control loop in comparison with the conventional generation side controller. The results show proposed control methodology provides appropriate performance and improved stability.

This paper considers the work entitled “Dynamic Sliding Mode Control Design for Nonlinear Systems Using Sliding Mode Observer” that is published in Tabriz Journal of Electrical Engineering where the authors try to design a sliding mode control design with sliding mode observer for a class of nonlinear systems. In this paper, we first give a brief overview of the proposed approach of aforementioned paper to the observer design. For the convergence of the estimation error, there is a proposition that we will discuss the validity of its proof. Finally, with a change in dynamic error equations of observer, its stability is proven.

Feature selection is one of the important problems in classification that has an important role in increasing efficiency and there are different methods to solve it. Particle swarm optimization is one of the algorithms based on swarm intelligence that has been used in different contexts including feature selection and has shown good performance. Many studies have used particle swarm optimization for feature selection. In a research accomplished in the field, the authors have presented several different strategies for initialization of particles and several methods to update personal best and global best in particle swarm optimization for feature selection and have achieved good results. In this article we have presented a method for feature selection based on the mentioned research and our proposed fuzzy updating for one of the personal best or global best. k-nearest neighbor is used as the classifier. Experiments is performed on several datasets. According to the done simulations, the proposed method obtains good results in terms of accuracy and the number of feature in comparison with reference article.

Magnetic gears in comparison with mechanical type have a lot of features like high reliability, low vibration and acoustic noise, overload protection, input and output shafts insulation, and less repair and maintenance requirements. Having a semi-analytic model based on the magnetic equivalent circuit (MEC) compared with the finite element method can reduce the time needed in the preliminary stages of the design process. In this paper, a two-dimensional modeling of a coaxial magnetic gearbox based on a MEC is presented using the nodal analysis method. Using the proposed model, the magnetic potentials of the circuit nodes are first obtained and the magnetic field distribution, fluxes, inner and outer rotor torque are determined in different parts of the gear. In this modeling, a dynamical model of the gear is presented. Using this model, the torque-angle characteristic, torque ripple and pullout torque of the gear are extracted. In addition, the effect of the load torque variation on the MG dynamics is evaluated. Finally, in order to validate the proposed model, the model results are compared with the finite element analysis.

The video is a popular service among users which plays an important role in the networks traffic and has hugest volume of data compared to other types of communications. In recent years, the great willingness of users to watch live videos has attracted the researchers to the networks equipped with content saving devices in which the video content is saved in advance within the edge devices (small stations and smart devices) for fast delivery. In this paper, we have proposed a new method to send the video content based on the D2D connection and providing a multi-connection and multi-user opportunities. According to the random nature of the popularity of video content and the random demands of users in the network, the authors of the article use the random distribution of popularity among users to investigate the probability of sending the same content to some users simultaneously. In this method, the requests of some users are answered by one response. Extensive simulations results of the proposed method reveals the important effect of the random distribution of video content popularity and show that using multi-link D2D connections can cause significant improvements in the efficiency of the network in term of the network throughput.

One of the promising ideas to improve over CMOS constrains in the nano-scales is Quantum Cellular Automata (QCA). So far, a variety of logic circuits are designed based on QCA where usually the majority and the inverter gates are the basic building blocks from which more complicated circuits are developed. In this paper, first we propose an approach to minimize the number of the majority and inverter gates in a given circuit with multiple inputs/outputs (MIMO). In our proposal, which is based on Cartesian Genetic Programming (CGP), a QCA circuit is coded as a series of integer numbers that constitutes a genotype for CGP. Applying CGP operators then, outputs the optimum phenotype including the number and the type of gates along with their interconnections. As for the verification of this approach, we apply it to 27 logic circuits and the results are reported, which show better solutions (in majority of cases) compared to the competing approaches. In addition to a fewer number of gates, our approach may provide a way to design QCA circuits with less power dissipation and/or less occupied areas.

In this paper, we address the problem of frame synchronization and Carrier Frequency Offset (CFO) estimation for Continuous Phase Modulation (CPM) in frame-based transmission. We present an efficient algorithm to estimate the start of signal and CFO simultaneously. The state of art methods for frame synchronization mostly adopt the AWGN channel model and suffer from real-world multipath and frequency-selective channels to estimate the start of signal. By using spectral analysis in the estimation procedure over a specific length of the received signal, we propose a method which is robust to multipath channels. When the start of signal is detected, the CFO estimation is performed on the preamble part of the received frame in the frequency domain. Simulation results show that the proposed algorithm detects the start of signal at signal-to-noise ratios (SNRs) below 0dB with a probability not exceeding . We show that our algorithm outperforms the pervious methods in the frame synchronization even with short preamble lengths.

In this paper, an online optimal coordinated solution for the voltage regulation of a distribution smart grids including an on-load tap changer (OLTC) and multiple distributed generators (DG) is presented. The proposed strategy sets reactive power points of distributed generators as well as tap position of the OLTC hierarchically. In the first stage, a distributed sub-gradient method in order to find the optimal reactive powers for the DGs is implemented to minimize the power losses subject to voltage limits. If the first stage could not regulate voltage profile inside acceptable limits, in the second stage tap position of the OLTC will change optimally. The proposed solution is verified by studying suddenly load change and DGs’ active power output. An IEEE 123-bus unbalanced test system is used for the verification of the proposed method. Fast response, responsibility to different suddenly changes in the operating condition, and reduction in the number of needed taps are the results of this study. Moreover, analogous steady state results in comparison with another centralized method i.e. interior point algorithm demonstrate the ability and efficiency of the proposed solution.

Using nonlinear signal processing methods is critical in processing biological signals due to their nonlinear dynamics. Recurrence plots are one of these nonlinear methods that provide qualitative and graphical representation of inherent dynamic of signal. Reaching movement is one of the important skill movements during human life. Despite of nonlinear methods capability to analyze the electromyogram signals during reaching movement, these methods are less considered. Therefore, the current manuscript investigates the classification of reaching movements at different speeds in horizontal plane. To achieve this, some quantitative indicators of recurrence plot analysis and nonlinear quantifiers including Lyapunov exponent and Higuchi fractal dimension are used. Based on multivariate analysis of variance, most discriminative features in the separation of different speeds of reaching movement are selected. Results show Recurrence rate, determinism, laminarity and Higuchi fractal dimension are best indicators to describe the recorded signals. The accuracy of KNN is 96.67%, SVM is 100%, linear discriminant analysis is 100%, and decision tree is 90%.

In this paper the impact of the trap assisted tunneling mechanism on the subthreshold characteristics of the tunneling field effect transistors is investigated. It is shown that the trap assisted tunneling is the dominant charge transfer mechanism before the band to band tunneling starts. Employing a modified SRH formalism, we show that, at the room temperature and for the subthreshold voltages, the trap assisted tunneling current always dominates and degrades the switching characteristics of the device which is measured by the subthreshold swing. This approach is applicable to the double gate and the gate-all-around structures where the traps are located in the source-channel tunneling junction. The trap assisted tunneling strongly depends on the electric field and the temperature. The considered transistors in this research are based on the compound semiconductors of groups three and five of periodic table. The effects of various structural parameters and material systems on the trap assisted tunneling current are studied, too.

In this paper, a new high step-up DC-DC converter is proposed for renewable energy systems. The proposed converter is based on active-network and coupled inductors. Using the coupled inductors alongside active-network leads to high step-up voltage gain in low duty cycle of power switches in such a way that with the same duty cycle and turns ratio of coupled inductors, the voltage gain of the proposed converter is nearly two times more than other counterpart converters. Furthermore, the voltage stress of the semiconductor switches is very low and slightly dependent on the power switches duty cycle and with the same voltage gain, it is less than half of the voltage stress of the other counterpart converters. The steady state operation of the proposed converter is investigated under continuous conduction mode (CCM), discontinuous conduction mode (DCM) and boundary conduction mode (BCM) and also the voltage gain is calculated in CCM and DCM modes. Voltage stress across all semiconductor devices is also achieved in CCM mode. The simulation results confirm the validity of theoretical analysis as well as the proper performance of the proposed converter.

The most important issue in power system designing and operating is minimizing losses and costs. Unlike existing methods which use a large amount of data across the entire network to determine optimal dispatch of shunt capacitors, this paper describes a method for optimal switching of capacitors in subtransmision substations only by using local data including voltage magnitude on 20kV and 63kV busbars, outgoing/incoming reactive powers on 63kV lines, and reactive load of 20kV side of subtransmision transformer. The simulations are carried out for Alborz Province MV network in IRAN using DIgSILENT 2018. Simulation results show an acceptable accuracy to minimize power loss in 63kV network.

Adders are among the most practical and useful circuits in microprocessors. They could also be used in other arithmetic operators. Traditionally, they are fabricated using CMOS technology. However, CMOS has faced some challenges in the nanoscale regime such as reduced gate controllability and high leakage currents. In contrast, Quantum Cellular Automata (QCA) is a promising alternative for the challenges of the next generation digital circuits. Based on QCA idea, in this paper a Carry-Skip Adder (CSA) is designed, which as far as investigated, has not been previously presented in related works. As CSA adders are generally faster than ripple ones, our simulation results also confirm that the proposed CSA outperforms the state-of-the-art ripple and carry lookahead adders and produces the result three QCA clock cycles faster even in the worst-case scenario. In addition, the proposed QCA adder outperforms its CMOS counterpart in terms of speed and power consumption.

Due to the growing increase of generated images via cameras and various instruments, image processing has found an important role in most of practical usages including medical, security and driving. However, most of the available models has no considerable performance and in some usages the amount of error is very effective. The main cause of this failure in most of available models is the distribution mismatch across the source and target domains. In fact, the made model has no generalization to test data with different properties and distribution compared to the source data, and its performance degrades dramatically to face with new data. In this paper, we propose a novel approach entitled Sparse coding and ADAptive classification (SADA) which is robust against data drift across domains. The proposed model reduces the distribution difference across domains via generating a common subspace between the source and target domains and increases the performance of model. Also, SADA reduces the distribution mismatch across domains via the selection of the source samples which are related to target samples. Moreover, SADA adapts the model parameters to build an adaptive model to encounter with data drift. Our variety of experiments demonstrate that the proposed approach outperforms all stat-of-the-art domain adaptation methods.

One of the preeminent features of distribution network automation to enhance the reliability is self-healing ability in these networks. Self-healing ability of a network requires protective and control equipment. The main contribution of this paper is to provide a comprehensive model for the measurement and location of the aforementioned equipment, taking into account the arrangement and coordination between the components and the consideration of momentary and permanent faults in the form of convex programming. Planning follows the optimality of a function that consists of different parts. The first part of the objective function is to optimize the economic index, including the cost of installing and annual repairing of equipment and the cost of customer blackout time during the study period. The second and third parts of the objective function provide the optimality of mean indexes of system interruption duration and momentary interruptions frequency mean, respectively. On the other hand, by analyzing the sensitivity to the maximum initial investment and the sensitivity coefficients defined in the objective function that weigh the parts of the target function, a comprehensive analysis of the impact of the using the equipment above on the distribution network is provided. The problem has been solved by BONMIN solver using General Algebraic Modeling System (GAMS) optimization software.

In this paper, the problem of real time sensor and actuator fault diagnosis is studied in a satellite system fusing sensor information. Measurements of inertial sensors are fused with auxiliary sun, earth and star sensors as well as magnetometers and global positioning systems (GPS). All of these sensors are prone to faults, failures and, noises. Thrusters, as actuators, are also employed in satellite attitude control system and are subjected to different faults. In this paper, it is assumed that all sensors are calibrated and the only possible faults are hard faults (failures) and noises. Due to this fact that when a hard fault occurs in a sensor, the measurement model changes to a new one, interacting multiple models (IMMs) are employed for diagnosis of sensor faults. Unscented Kalman filters (UKFs) are used in IMMs due to nonlinear and Gaussian translational and attitude models. In order to reduce the number of parallel filters in the proposed IMM method, the translational and attitude subsystems are decoupled and separate IMMs are designed for each subsystem. Unknown input observers (UIOs) are used to estimate amplitude of faults in thrusters. The efficiency of the method is finally evaluated through simulation and compared with similar approaches.

One of the destructive factors in denotation scene details from the Synthetic Aperture radar images is the presence of speckle noise in it. Different method of image denoising have been proposed using the Sparse Representation (SR) Technique, which, eliminates the noise of the image properly by preserving details. Because of the Computational Complexity of these methods and the large dimensions of SAR images, their use in SAR images is challenging. This paper presents a new method in SAR image denoising by SR that reduce run time with preservation of image quality. In this method, the denoising performs in two step. Firstly, the image is filtered using a simple denoising method, and the removed details is then retrieved using the SR technique and added to the filtered image. By retrieving details from the heterogeneous regions of the image and using random sampling matrix in reconstruction image, the processing volume and the required memory in using SR technique are reduced. Simulation results show that this method, with preservation of image quality, has an operating time of about 0.2 of other methods.

There are two main challenges in control of hybrid systems which are to guarantee the closed-loop stability and reduce computational complexity. In this paper, we propose the exponential stability conditions of hybrid systems which are described in the Mixed Logical Dynamical (MLD) form in closed-loop with Model Predictive Control (MPC). To do this, it is proposed to use the decreasing condition of infinity norm based Lyapunov function instead of imposing the terminal equality constraint in the MPC formulation of MLD system. The exponential stability conditions have a better performance from both implementation and computational points of view. In addition, the exponential stability conditions of the equilibrium point of the MLD system do not depend on the prediction horizon of MPC problem which is the main advantage of the proposed method. On the other hand, by using the decreasing condition of the Lyapunov function in the MPC setup, the suboptimal version of the control signal with reduced complexity is obtained. In order to show the capabilities of the proposed method, the stabilization problem of the car suspension system is studied.

Series voltage compensation is used in low-voltage distribution system to compensate for voltage variations. The compensators are indeed series-connected converters which inject the missing voltage in series to the grid in case of voltage sag. In this paper, a switching algorithm for AC-AC converter based voltage compensator is proposed. As the bidirectional AC power electronic switches are used in the AC-AC converters, considering the switching dead-time, snubber circuits should be used in parallel with the switches to provide a current path during the dead-time and hence to reduce the dv/dt stresses on the switches. The snubber circuits increase the circuit elements and have their own power losses. Using the proposed switching algorithm, the snubber circuits could be eliminated since a current path is always (including the dead-time) guaranteed. In order to evaluate the proposed algorithm, the simulation studies and discussions are presented.

Lung nodules are the primary tissue of lung cancer. Designing a computer-aided diagnosis system can be used in order to enhance the accuracy of the radiologist in the detection and description of these tissues. The aim of this study is to provide an approach to detection of lung nodules on CT scan images. This study was conducted in two main stages of nodule segmentation and detection.  In the segmentation stage, combination procedures such as Fuzzy-Tsallis entropy and thresholding were used. In the nodule detection stage, intensity and geometric features are extracted and suspicious areas are determined by support vector machine. Using intensity features causes increasing true positive rate while using geometrical features causes decreasing false positive rate. To evaluate the proposed method, images of LIDC and Taba datasets were used. Classification sensitivity is 92%. The obtained results comparing to those reported by other articles, indicate the usefulness of the research.

Rule base of a Fuzzy Associative Classifier (FAC) is a collection of fuzzy associative rules that are often based on the system's quantitative data. However, due to the real-world complexities and uncertainties, classification in many practical circumstances remains a matter of art of decision-making that is strongly influenced by the knowledge, experience, and personal perspective of individuals. In this paper, we introduce the f-associative fuzzy classifier (f-FAC) in the framework of Extended Fuzzy Logic (FLe), which is more closely related to the way of thinking and reasoning of human beings. In the proposed structure, human knowledge and experience are considered by fuzzy validity concept in both phases of construction and deduction of FACs. In this classifier, the validity of the items and rules is determined by integrating the opinion of experts on the basis of wisdom of crowds and using perceptual computing. To evaluate the proposed approach, a real dataset of burn patients in Ahwaz are considered. f-FARC-HD is then implemented as an extension of FARC-HD associative classifier and is compared with the other approaches (associative classifier and non-associative classifier). Also, f-FARC-HD and FARC-HD are compared in different levels of noise. Results indicate that considering the concept of validity in the proposed extended approach, f-FARC-HD, leads to comparable accuracy, but at a considerably less complexity. Also, f-FARC-HD is less sensitive against noise.

Today, induction motors are widely used in the industry by electric drives. Vector control is one of the commonly used electric drives. Vector control has a good performance in heavy loads and the amount of rotor flux in these loads is the same as the nominal value. But in light loads, using vector control will result in a reduction in efficiency. In fact, in the light loads, the value of the rotor rated flux is not required. Motors are often used at a load other than the rated value. One of the factors that causes the motor to be placed in a load other than the rated load, is the oversized selection. In this paper, it will be tried to improve the induction motor efficiency, especially in light loads, by controlling the angle between the stator current and the rotor flux which is located on the d-axis (flux angle). In the proposed method, the value of the flux angle in light loads is controlled at a constant value, which is dependent on some of the motor parameters. The proposed method could be simply implemented, has a low computational burden and will considerably increase the efficiency of the induction motor in light loads.

Monte Carlo simulation method is widely used in reliability evaluation of distribution networks. The most important advantage of this method is their simplicity and flexibility to apply to any system. In contrast, large volumes of calculations and inaccurate results are the disadvantages of this method. In this paper, a new method for evaluating reliability indices in active networks is proposed. This method is a combination of Monte Carlo simulation method and analytical method. Unlike the simulation methods, it has a unique answer. Considering that, the purpose of this new method for reliability evaluation is filling gaps in the Monte Carlo simulation method, As a result, the Monte Carlo method will be examined in more detail. To prove the effectiveness of this method, evaluation of reliability indices for bus 2 of RBTS in an inactive network state and in active network state (modified RBTS Bus 2 and 4, including distributed generation resources and Energy storage) using new method and Monte Carlo method have been done and compared with each other. Results of these two methods show that the new method has accurate results and its implementation time is less than the Monte Carlo method.

This study presents a Pseudo noise sequence (PN) estimation algorithm using maximum likelihood method in low signal to noise ratio. The received signal samples are divided into temporal segments. Then correlation matrix is computed for eigenvalue estimation. Eigenvector related to largest eigenvalue of this matrix is chosen and de-noised by stationary wavelet transform to find asynchronous of sequence and chip rate. The estimation of PN sequence, is found through a maximum likelihood algorithm for delay estimation and interpolation filter. Simulation results are applied to evaluate the proposed method and compare with previous methods in terms of computational complexity and accuracy of the chip rate and the PN estimation. Furthermore, minimum number of required samples are investigated for true estimation accuracy measurement. The results indicated that, the proposed method presented 13% better accuracy of PN sequence estimation compared to other methods.

Nowadays the demand for photovoltaic (PV) systems has greatly increased due to their various advantages. In many applications for the purposes of reducing losses, increasing the efficiency and having the lower size and weight the transformer has been removed from the grid connected PV systems. In such situations, due to the absence of the galvanic isolation, the common mode voltage becomes unstable leading to flow of leakage current through the parasitic capacitor. The leakage current increases losses, deteriorates the quality of injected currents, causes the electromagnetic interference and finally presents personal safety problems. Therefore, it should be reduced to statutory limits which is defined by the VDE0126-1-1 standard. In the present paper attemps have been made to do so, using the single-vecror and double-vector model predictive control (MPCs) systems. In this approach, without using any extra hardware not only the leakage current is reduced, but the switching frequency and the THD index are also simultaneously minimized. The simulation results confirm the superior performance of the proposed method over other valuable methods.

The conventional routing protocols are not able to handle intermittent mobile networks, since because of deficiency of nodes’ density, mobility, instability of radio connections, most of the times no path exists among the source and destination nodes. Delay tolerant networks (DTN) is a solution in which communications become feasible in intermittent mobile networks by tolerating long delays. Routing methods in DTN use the idea of spreading packets among the mobile nodes for transporting information toward the destinations. In order to achieve a good performance, it is necessary to control the workload of the network by limiting the number of copies. In this paper, a novel method for packet copying process is proposed which improves the throughput significantly while controlling the workload of the network. The key idea behind the proposed method is to prioritize the buffered packets at each node in order to avoid excessive repetitions of packets and stop wasteful workload grow. The packets are prioritized based on the source nodes, the ages, and their remaining lifetimes. Our simulation results indicate that the proposed method can improve packet delivery ratio by 40 to 60 percent in comparison with Spray and Binary Wait, and Direct delivery routing methods.

Today, with the development of computer systems, malware has grown dramatically. Malware is defined as a program that is developed with malicious purpose, such as sabotaging the computer system, information theft or other malicious actions. Malware detection is a branch of computer security which attempts to analyze suspicious programs, detect malware and ultimately eliminate the threat. Opcode-based methods are commonly used in malware detection. Given that, all Opcode are not important for detecting malware, some of them can be ignored in the detection process. In this research, the proposed method is based on Opcode Analysis, but only some of the important and effective Opcodes will be considered for file detection. First, momentous Opcodes of file are identified and employed for generating images. Then, features are extracted from the images in order to accomplish the classification. The advantage of the proposed method is that images are created based on important Opcodes and detecting malware is converted into image classification. Therefore, the proposed method is more optimized compared to the previous methods and also has acceptable accuracy and less complexity.

In this paper an ultra-wideband power divider has been designed, simulated and fabricated. In this structure, the quarter-wave transformer in the conventional Wilkinson power divider, is replaced by an exponentially tapered microstrip line. Since the tapered line provides a consistent impedance transformation across all frequencies, very low amplitude ripple of 0.5dB peak-to-peak in the transmission coefficient and superior input return loss better than 15dB are achieved over an ultra-wide bandwidth. By optimizing the physical locations of the two additional standard resistors added along the tapered line, the output return loss and isolation are improved. The simulation results achieved by full wave analysis based on Finite Element Method (FEM) and the measured results confirm the good performance of the proposed circuit. The return loss of the output ports is better than 15dB and the isolation between the output ports is better than 20dB across the band 6-16GHz. Finally a comparison between ultra-wideband power dividers is provided. It is clear that the proposed divider in terms of the aforementioned important features, has a good performance related to the other ultra-wideband power dividers.

In this paper, a method is presented for the electrical rotor fault detection in wound rotor induction generators. The fault is a rotor electrical fault in induction generators employed for wind turbine applications. Due to the tower shadow effect, a stray fault signature is introduced in the generator current which may result in false fault detection. The method is based on the time-frequency analysis in which the frequency is transformed and the time averaging of the signal energy is obtained. The method is known as harmonics order tracking analysis. For reliable fault detection, statistic indices are used in post-processing that increase the ability to distinguish between the fault effect and tower shadow effect. The simulation results illustrate that the proposed method is effectively successful in discriminating these two effects. Finally, the harmonics order tracking analysis is evaluated using the experimental results.

Dou to penetration of stochastic resources in the microgrids, the need for new control and scheduling method is essential. Reconfiguration strategy can be considered as a practical solution for network performance improvement. Therefore, in this paper the scheduling of reconfigurable microgrid (RMG) in the normal and emergency conditions are analyzed. It is assumed that microgrid consists of several small neighboring microgrids, so in addition to the microgrid scheduling in the normal condition, the problem of neighboring microgrid management will be solved in the emergency condition. In the first condition, microgrid total cost minimization is considered as an objective while in the emergency condition, the microgrid divided to several neighboring microgrids and the proposed method tries to find the optimal structure for neighboring connection and minimizes the total load shedding, until the return to the normal condition. The results show the effectiveness of proposed method from the cost and load shedding minimization point of view.

In this paper, a high-gain low-cost reflectarray antenna is proposed. This antenna does not need radome. The exploited dielectric is the FR4 epoxy which is both low-cost and mechanically robust. Reflector of the proposed antenna consists of a layer of FR4, suspended above the ground plane by spacer, with its re-radiating elements on its interior side. Superiority of the suggested antenna over the similar previously reported design is shown. For the proposed design, sensitivity of the phase-delay characteristic, number of elements and gain to the FR4 thickness is studied. In addition, effect of design tolerance for the dielectric and the air gap on the antenna gain is investigated.