Search

High Efficiency Video Coding (HEVC) is considered the last standard for video compression with about 50% additional compression compared to the previous standard i.e. H264/AVC, while maintaining image quality. The significant increase in performance of this standard has been achieved with high computational complexity. In this standard, the intra prediction unit is one of the parts that although it greatly improves performance, it significantly increases its computational complexity due to the increase in the number of prediction modes. In this paper, a method has been proposed to reduce the number of intra prediction modes in HEVC by which the computational complexity of compression at this stage can be reduced as much as possible. The proposed method determines the predominant mode of 4 × 4 blocks, and the details in each larger block, and accordingly, by applying the appropriate filters and selecting the most likely mode, the number of candidate modes to select the best mode is reduced. The simulation results showed that on average the proposed method can reduce the compression time by 45% while increasing the bit rate by 0.69%. [ABSTRACT FROM AUTHOR]

Under unbalanced grid condition, in a Doubly-Fed Induction Generator (DFIG), voltage, current, and flux of the stator become asymmetric. Therefore, active-reactive power and torque will be oscillating. In DFIG controlling Rotor Side Converter (RSC) aims to eliminate power and torque oscillations. However, simultaneous elimination of the power and torque oscillations is not possible. Also, Grid Side Converter (GSC) aims to regulate DC-Link voltage. In this paper, in order to regulate DC-Link voltage, an Extended State Observer (ESO) based on a Generalized ProportionalIntegral (GPI) controller, is employed. In this controlling method, DC-Link voltage is controlled without measuring the GSC current, and due to using the GPI controller, the improved dynamic response is resistant against voltage changes, and the settling time is reduced. To improve the transient stability and Low Voltage Fault Ride Through (LVRT) capability of DFIG, Statistic Fault Current Limiter (S-FCL) and Magnetic Energy Storage Fault Current Limiter (MES-FCL) are proposed in this paper. The proposed FCL does not only limit the fault current but also fasten voltage recovery. The simulations are implemented by MATLAB software in the synchronous positive and negative sequence reference (d-q). [ABSTRACT FROM AUTHOR]

In this paper, we use a nonlinear hierarchical model predictive control (MPC) to stabilize the Segway robot. We also use hardware in the loop (HIL) simulation in order to model the delay response of the wheels' motor and verify the control algorithm. In Two-Wheeled Personal Transportation Robots (TWPTR), changing the center of mass location and value, the nonlinearity of the equations, and the dynamics of the system are topics complicating the control problem. A nonlinear MPC predicts the dynamics of the system and solves the control problem efficiently, but requires the exact information of the system models. Since model uncertainties are unavoidable, the time-delay control (TDC) method is used to cancel the unknown dynamics and the unexpected disturbances. When TDC method is applied, the results show that the maximum required torque for engines is reduced by 7%, and the maximum displacement of the robot has dropped by 44% around the balance axis. In other words, robot stability has increased by 78%. Due to the cost of implementing control in practice, this research runs the HIL simulation for the first time. Use of this simulation helps in implementing the control algorithms without approximation, and also the system response can be discussed in a more realistic way. [ABSTRACT FROM AUTHOR]

Nowadays, sea wave energy is widely regarded as an energy source that is clean, renewable and highly available for power extraction. The subject of extracting the maximum power from sea waves in Iran is of great importance due to access to the Caspian Sea and the Persian Gulf. Moreover, there is a need for resources with no air pollution besides providing a part of the country's power demand without costly infrastructure, so this research field is highly interesting although has rarely been addressed so far. The main purpose of this paper is to use an appropriate control strategy to improve the performance of point absorbers. In this scheme, to consider high uncertainty in the parameters of the power take-off system in different atmospheric conditions and improve controller performance, a new improved black hole algorithm is introduced to tune fuzzy controller parameters. The proposed method is then implemented for tuning the fuzzy controller parameters in order to obtain the maximum power capture of wave energy converters. Compared to particle swarm optimization and conventional black hole algorithm, the results of the proposed method indicate enhancements in reference velocity tracking and absorbed power. Finally, some simulations are performed and the proposed controller is implemented for the wave spectrum of the Persian Gulf waters, so the performance of the proposed controller is evaluated. [ABSTRACT FROM AUTHOR]

This paper proposes the Variable Latency Speculative (VLS) Multiply-Accumulate (MAC) architectures. The proposed VLS architectures, unlike conventional MAC with fixed latencies, consists of two short and long data paths and a circuit is used to select a suitable path with minimum overhead. Two methods are considered to design the proposed VLS MAC. The first one considers the general structure of the VLS MAC with integrating the result vectors of multiplier with the accumulator, and the second method uses a novel VLS 4:2 compressor design. To investigate the proposed VLS MACs performance, all architectures have been synthesized using a CMOS 90 nm technology library, for operand lengths 8, 16 and 32 bits. Obtained results show that the proposed MAC architectures provide a variety of trade-offs in the power-delay-area space that outperform the existing designs that use only the integration technique. Moreover, the VLS MAC with the proposed VLS 4:2 compressor, in the short data path, has a delay equal to MAC with previously proposed approximate 4:2 compressor with an error recovery module. In comparison to MAC with the approximate 4:2 compressor, on average, the VLS MAC with the proposed VLS 4:2 compressor resulted in 11.26% and 13.59% lower area and power consumption. [ABSTRACT FROM AUTHOR]

With the expansion of human activities, the volume of waste and hazardous waste produced has increased dramatically. Increasing the volume of waste has created challenges such as transportation hazards, cleanup, disposal, energy consumption, and most important environmental problems. The difficulty of unsafe waste control is one of the critical studies topics. Finding the optimal location of hazardous waste disposal is one of the issues that, if done properly, can significantly reduce the aforementioned challenges. The increasing volume of information, the complexity of multivariate decision criteria, have led to the lack of conventional methods for finding the optimal location. Machine learning methods have proven to be effective and superior in many areas. In this paper, a new method based on machine learning for finding the optimal location of hazardous waste disposal is presented. In the proposed method, after applying clustering in the separation of the desired areas, the gray wolf algorithm optimization is used to find the optimal location of waste disposal. In order to apply the gray wolf optimization algorithm, a multivariate target function is defined. Cluster centers as were chosen as location of waste disposal. Proposed method is performed on collected data from the study area in Iran, Tehran province. Proposed clustering method is evaluated and compared with some metaheuristics algorithm. The simulation results of the proposed method show cost reduction in finding the desired locations compared to similar researches. Also, Xi and Separation index was used for evaluation of the proposed clustering method to select the best location. The number of best locations using Xi and Separation index claim the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Mobile Wireless Sensors Networks (MWSNs) are used in several applications presenting difficult/dangerous environment and/or requiring the movement of sensors after initial deployment. Optimizing the use of the limited energy resource in a MWSN is a key challenge for researchers to maintain longer network survival. This paper attempts to provide an energy-efficient data routing solution for large MWSNs. The aim of this work is to propose a cluster-based scheduling protocol for MWSN. The network is firstly divided into an optimal number of clusters according to sensors connectivity. Secondly, a sleep scheduling algorithm is proposed to save the energy consumption by turning off the overlapped nodes in the sensing field. This method is distributed among sensor nodes in each cluster. It is based on the perimeter coverage level of mobile sensor nodes to schedule their activities according to their weights. The weight is used to balance the energy consumption for all sensor nodes in a cluster. The proposed approach ranges from sensors deployment and their organization to their operational mode. Experimental results demonstrate that the proposed cluster-based scheduling algorithm, based on the perimeter coverage of sensors, provides higher energy efficiency and longer lifetime coverage for MWSNs as compared to other protocols. [ABSTRACT FROM AUTHOR]

Conversation and assurance issues play a crucial function when talking regarding to the wise grid. This paper presents opportunities of testing power framework assurance transfers and correspondence standards for smart supply. In this paper, a depiction in the Smart Grid lab hardware and the key protection devices has been presented. Further employ cases and the possibilities by dynamically setting up devices and program interaction are demonstrated. Ideas for the mix of checked and controllable decentralized vitality sources are demonstrated, and the network capacity and Quality of Services (QoS) are tested and evaluated. By implementing adaptive modulation scheme, the served users were increased by 10% at heavy Traffic Load (TL). [ABSTRACT FROM AUTHOR]

This paper is treated with optimum energy management in a DC/AC Microgrid (MG) containing hybrid power sources to supply the load within cost minimization. In this hybrid electrical networks, energy sources are exploited as DC and AC manner, in which the Independent System Operator (ISO) should provide a practical coordination between them in order to procure the demand load optimally. This paper presents a framework that all available resources are formulated mathematically in hybrid microgrid with full constraints along with Demand Response (DR) programs implementation. The network under consideration can operate both in grid-tied and autonomous modes to manage power exchanging. Uncertainty and intermittent of Photovoltaic (PV) with Maximum Power Point Tracker (MPPT) equipped, Wind Turbine (WT), Energy Storage Systems (ESS) and DR programs are also considered to achieve the optimal control and operation. The ESSs are capable to connect both DC and AC links and the State of Charge (SOC) is maintained within permissible range. The proposed DG control framework and operation scheduling has facilitated the energy management of renewables using dynamic programing approach. A 24-hour time horizon simulation and discussion through three scenarios verified on a IEEE 33 bus distribution network, is done to represent the effectiveness of proposed energy management strategy to keep the whole hybrid grid stable. [ABSTRACT FROM AUTHOR]

The Electric transit buses (ETBs) are the main source for public transit to get the cleaner environment. The ETBs have gained popularity around the globe since the last decade. The ETBs are 14 % of the total transit buses around the world. The ETBs are heavy EVs and need more power to charge the high capacity batteries. The batteries used in these buses have the energy capacities between 80 kWh to 550 kWh. Such high capacity batteries take more to get charged. In order to increase the adoption of ETBs, a suitable number of high power dc charging infrastructures need to be installed in various main cities of the nations. The ETBs can operate with battery alone or fuel cell or combination of these two. Such ETBs are named as battery electric transit bus (BETB), fuel cell electric transit bus (FCETB) and hybrid electric transit bus (HETBs). As of 2020, out of total ETBs around the globe, 70 % are HETBs, 20 % are FCETBs and 10 % are BETBs. In this paper, the key parameters and comparison among these three batteries are shown. The major EV market holders are China, US, Europe and japan. The charging protocol used in the US and Europe is combined charging system. The charger capacity has reached up to 500 kW as of 2020. With such high power chargers it takes only less than half an hour to charge the high power batteries. [ABSTRACT FROM AUTHOR]

This paper focuses on introducing a transformerless DC/DC converter with low total switching device power in dual working modes including step-up and step-up/down modes. The proposed converter is analysed in terms of the continuous conduction mode, steady state, and efficiency with the replacement of parasitic resistance effects. The proposed converter in the step-up mode has a high voltage gain ratio and a continuous input current. Then, the other working mode of the proposed converter with relevant DC/DC converters is compared. By this comparison, the proposed converter has a high voltage gain ratio. Also, the converter characteristics such as voltage stress on power switches and charge pump capacitors are in a good condition in this mode. Finally, the experimental results from a laboratory made prototype and the obtained waveforms from the simulation in PLECS are presented for validation such as higher voltage gain ratio, lower total switching device power and better efficiency. [ABSTRACT FROM AUTHOR]

In this paper, the Electromagnetic Band-Gap (EBG) structures have been used to decrease the mutual coupling between two wideband quad-ridge horn antennas. The EBG structure is a small sheet with a length of 6 cm and a width of 10.6 cm, and it was placed vertically between the horn antennas, providing us with a very compact system. Full-wave CST simulations have been carried out to simulate the whole structure. A two-layer EBG structure has provided a 17 dB isolation over the 20-40 GHz frequency range. Moreover, to verify the proposed structure, EBG layers have been fabricated and measured. The S parameter and far-field measurements of the horn antennas were conducted to investigate the isolation and radiation patterns of the antennas. The measurement results were perfectly comparable with the simulations. Moreover, because of the standalone characteristic of the designed EBGs, this structure can be used as an add-on unit to decrease the E-plane mutual coupling of any two antennas. [ABSTRACT FROM AUTHOR]

In a parallel transmission line, fault line, fault location, and classification have been identified separately. Since fault location takes more calculation time, it is unfit for protection purposes. Thus, this paper presented a new scheme that estimates the faulted line, fault location, and type of fault in a parallel transmission line, with the help of Phasor Measurement Units (PMU) and the Artificial Intelligence Technique. The proposed scheme uses phasors of Positive Sequence Voltage (PSV) and Positive Sequence Current (PSC) to detect the faulted line in a parallel transmission line. Further, the Artificial Neural Network (ANN) models have been designed to estimate the fault distance on a faulted line and classify the fault types. The PSV and PSC obtained from PMUs are selected as inputs because they have a negligible mutual coupling effect on the parallel transmission lines. The IEEE 9 bus system and the IEEE 30 bus system have been considered test cases to validate the proposed scheme. The proposed scheme is also validated by hardware in the loop on an OPAL-RT real-time simulator (OP RTS 5700). The results show that the proposed scheme identifies the fault line, fault distance, and type of fault regardless of its location on a parallel transmission line. Besides this, the proposed scheme has a quick response time, making it suitable for wide-area backup protection applications. [ABSTRACT FROM AUTHOR]

In this paper, a new hybrid low-power and area efficient Carry Look-Ahead Adder in CNFET technology based on the full-swing Gate Diffusion Input (GDI) technique is proposed. The proposed CLA design in GDI logic style, not only decreases the circuit area effectively but also decreases the power consumption and delay parameters as well. The proposed design is simulated in HSPICE using the CNFET model parameters. Finally, the simulation results justify a good improvement in the circuit performance parameters such as power consumption, delay, chip size area and power-delay product (PDP) for the proposed CLA circuit. [ABSTRACT FROM AUTHOR]

Penetration of distributed generation resources including wind power and solar photovoltaic units in distribution system has been increased, and it is important to examine their impact on the distribution systems' operation in term of reliability. In this paper, the multi-objective dynamic feeder reconfiguration is introduced as an efficient approach for providing an energy management schedule in the distribution grid considering energy loss and energy not supplied as the objective functions in the presence of renewable energy sources and capacitor units. In addition, the effect of uncertainty related to power demand is considered in the evaluations. To this end, an enhanced particle swarm optimization algorithm is provided in this paper, the proposed approach is applied to the 33-node testing system. [ABSTRACT FROM AUTHOR]

In this paper, a novel lossless snubber is introduced that provides ZVS conditions for both On and Off instant of converter switches. On one hand, the energy of the snubber is optimally transmitted to the output so that no significant losses are imposed on the converter. Since the converter diodes are switched off as ZCS, the reverse recovery problem is reduced. In this paper, the proposed snubber circuit is applied to a conventional boost converter and an 80W sample is constructed in the laboratory to prove the performance and theoretical analysis. Furthermore, in order to confirm the effectiveness of the proposed snubber on the reduction of Electromagnetic Interference (EMI), the EMI value of the boost converter with the proposed snubber has been compared with the conventional boost converter, which shows a decrease of 10dBμV. [ABSTRACT FROM AUTHOR]

In the recent days, the main challenge for the electrical power system is an economical storage technology. Energy storage is essential for the future Smart Grid (SG) to smooth out the fluctuating output of Renewable Energy Resources (RERs). Even though many good storage technologies are available but either they are not economical or they are not efficient. Several research studies are analyzed the application of energy storage with respect to voltage support, peak shaving, frequency stability, renewable firming, transmission upgrade deferral, and a host of other uses. RERs are dependent on the climate conditions for the power output. Therefore, an efficient storage technology is an important part for the reliability of electric power system. This paper compares different storage technologies available, i.e. hydrogen storage, batteries, superconducting magnet energy storage, fly wheels, compressed air energy storage, pumped hydro energy storage, etc. This paper details the necessity of storage techniques to help the RERs power output in the SG to meet the energy demands of the future. [ABSTRACT FROM AUTHOR]

Brushless DC motors face many challenges and complexities which could be considered as sensor-based or sensorless schemes for detecting the position of the rotor, and end in a variety of results. A brushless DC motor sensorless control system is developed in this paper and a sensorless technique which is based on a hysteresis comparator and a potential start-up method with a high starting torque has been suggested. In addition, the phase delay of the back EMFs, in case of passing low-pass filters, could be compensated by the hysteresis comparator which prevents multiple output transitions from ripple or noise in the terminal voltage. The rotor position is aligned at standstill for maximum starting torque without additional sensors and motor parameter information. Where, by modulating the pulse width of the switching devices during alignment, the stator current could be easily adjusted. In this paper, the simulation and the experimental results has been provided for validating the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the design and optimization of a cascaded common source four-stage millimeter wave amplifier in a 130 nm CMOS technology has been presented. First, Pi-shaped wideband impedance matching networks (IMNs) were used in the Input/Output Impedance Matching Networks (IOIMNs) and inter-stages. Next, single stubs were converted to symmetrical double stubs in the IOIMNs, and an ultra-wideband inductor replaced each stub. Ultra-wideband inductors were also used in series in the inter-stage IMNs to achieve a higher gain in the wider frequency bandwidth. Then, the impedance matrices of IOIMNs and inter-stage were calculated using Planar Circuit Analysis (PCA), which is based on the planar waveguide model and Segmentation/Desegmentation Methods (SDSMs). Finally, by optimizing the length and characteristic impedance of each segment of microstrip line in the IMNs through using an intelligent optimization algorithm in MATLAB, the excellent IMNs were designed, which resulted in an amplifier with S11min = −25.3dB, S22min = −20.6 dB, and S21max = 30.5 dB in the frequency range of 57- 64 GHz. With this design method, in addition to incorporating the effect of discontinuities, the fringing fields at the edges of the microstrip as well as the conductor and dielectric losses, the effect of dispersion would be minimized by choosing a substrate whose thickness is much smaller than the wavelength and its relative permittivity is low. [ABSTRACT FROM AUTHOR]

Grey Wolf optimizer is a well-known metaheuristic technique but it faces the problem of premature convergence, trapping in local optima and poor balance between exploration and exploitation. Hence, various modifications have been proposed over past few years. One such modification is modelling the prey position as dynamic in nature as shown in GWOLF. However, still it has been observed that to get better solution, GWOLF needs to be modified too, hence an improved version of GWO (IGWO) is proposed. IGWO has the advantage of both GWO and GWOLF. In this paper, IGWO is used to solve Dynamic Economic Dispatch (DED) problem. IGWO is having a better balance between exploitation and exploration for the complex problem such as Dynamic Economic Dispatch (DED) taking into account of valve-point effect, transmission losses and ramp-rate limits with and without Electric Vehicles (EVs). The efficiency of the algorithm is demonstrated on solving different DED problems for 5 generator and 15 generator test systems with and without losses along with different charging profile distribution of electric vehicles. The results showcased by IGWO is compared with the other algorithm. The results obtained by IGWO algorithm adopted in solving dynamic economic dispatch problem is giving competitive results as compared to the results given by other algorithm present in literature. [ABSTRACT FROM AUTHOR]

DGs and capacitor banks are installed to optimize the performance of many distribution networks. Typically, the problem of optimizing the overall performance of the distribution network is examined with multi-objective purposes. Network optimization purposes are usually varied and sometimes contradictory. Therefore, the problem search space is very large due to the variety of purposes. This paper presents a modified Pareto local search function for optimal placement of DGs and capacitor banks. To limit the search space and find Pareto points, a new combination method including Pareto chart and a weight function has been used. The optimal operation of the distribution network is performed by three single objective functions related to the voltage stability index, voltage profile of buses and power loss. In this method, a modified per-unit system is presented to align single objective functions and their weighting coefficients. The network is studied with three different loads. So that, the network is examined in the final stage by increasing the load and reaching bus voltage stability margins. The particle swarm optimization method is applied to solving placement problems. In addition, locating and sizing DG and capacitor banks, tap setting of on load tap changer transformer is adjusted by the proposed method. To show the effectiveness of the purposed method, simulations are applied to 69 bus radial system. The results indicated the favorable advantage of the proposed method to improve the overall performance of the distribution network. [ABSTRACT FROM AUTHOR]

The 4-moduli set residue number system (RNS), {2n + 3,2n - 3,2n + 1, 2n - 1}, with a wide dynamic range, has recently been proposed as a balanced 4-moduli set for utilizing the cases that demand fast calculations such as deep learning and implementation of asymmetric cryptographic algorithms. Up to now, only an unsigned reverse converter has been designed for this moduli set. Thus, there is a need for two separate units, a sign detection circuit, and a comparator to use this set in cases requiring sign and comparison. Nevertheless, the existence of these components demands high hardware that makes the implementation of the RNS impractical. Therefore, this paper presents the design of a sign detection circuit and a signed reverse converter that can overcome this problem by reusing the hardware. To achieve an integrated hardware design, first, we optimized the previous unsigned reverse converter for this 4-moduli set and next, we derived an approach from the structure of the reverse convertor for detecting signs and recognizing comparators. Finally, using the sign signals extracted from the reverse converter, we change reverse convertor into a unit that perform sign detection and comparison. The simulation has been conducted using ISE Design Suite 14.7 tool and the Spartan6 family technology. Empirical results show that, the proposed multifunctional unit has an approximately identical performance with respect to delay and area compared to the previous reverse converter. Besides, the proposed signed reverse converter relies on a 46% and 28% reduction in area and delay compared to the previous unsigned reverse converter which uses a comparator and also a multiplexer to detect a sign in the output. [ABSTRACT FROM AUTHOR]

One of the most significant handicaps and disadvantages for the proper operation of the polymer membrane in a PEMFC fuel cell energy system is the distribution of water. In this paper, we propose a mathematical model for defining the static and dynamic characteristics of energy behaviour (voltage, electricity, and relative humidity) for various input operating parameters (hydrogen, oxygen, water flow rates, temperature and current). This energy phenomenon is used in a wide range of operating conditions to ensure the exploitation of the energy produced, which will be modeled by a recent practicable and achievable graphical formalism, the Macroscopic Energy Representation (MER), which is used because of its simplicity which feasibility, and is based on the action/reaction principle and controlled by a simple inversion method. This behavior is designed to deduce and recommend an energy management plan for the PEMFC system that takes into account the various states of flooding and drought and contributes to an optimal humidity level for the system's implementation. The simulation results show that to operate correctly for this model, the Relative Humidity must be in the neighborhood of 100% for the device to be effective. [ABSTRACT FROM AUTHOR]

Matched Field Processing (MFP) is one of the most famous algorithms for source detection and underwater localization. Traditional MFP relies on a match between the received signal at the hydrophone array and a replica signal, which is constructed using Green's Function, then by scanning the space in range and depth to provide an estimation of source position in shallow water and deep water. Different environment models relying on Green's function exist for constructing the replica signal; this includes normal modes in a shallow water waveguide, the Lloyd-Mirror Pattern, and the Image model. Using the proposed estimation algorithm, here, an analytical Lloyd-Mirror model is developed based on the reflection from the target surface for a case where a target is located in the source signal propagation path. So, in this paper, a new underwater acoustic target localization algorithm using the generalized Lloyd-Mirror Pattern is presented. This idea is verified using an acoustic data from a 2019 underwater communication trial in Grand Passage, Nova Scotia, Canada. [ABSTRACT FROM AUTHOR]

To moderate global warming, conventional fossil fuels are depleted. As the population increased with the rising standard of living and industrial growth, the global environment is affected and cause the greenhouse gases occurrence, which are frequently increased by unlimited use of fossil fuels. The generation of electric power loads increases the power demand on the basics of modern power technology development. Several benefits can be attained by installing the distribution generation with the quality and reliability of power delivered. However, the global energy problem can be resolved by renewable energy sources as an alternative energy generation. Technological developments in the last decade have increased the use of renewable energy sources. In worldwide, several renewable energy sources are used to attain their own power demand. The photovoltaic (PV) generation is the essential renewable energy source to serve the increasing electrical loads. The fastest-growing PV system has the naturally available energy sources of robust evolution with elegant benefits. The foremost objective of this paper is to examine the performance of the PV system with various Maximum Power Point Tracking (MPPT) algorithms. The solar irradiance and temperature make it complex to track the MPPT of PV systems. This review is about various MPPT algorithms like online, offline, and hybrid methods. The selected algorithms from each discussion are simulated in MATLAB/Simulink environment to match their performance in footings of the dynamic response and efficiency of the PV system under the variations of solar irradiance and temperature. An explanation and discussion of the PV system are achieved with the study of different types of MPPT algorithms of PV systems. [ABSTRACT FROM AUTHOR]

Today, due to the advent of the powerful photo editing software packages, it has become relatively easy to create forgery images. Recognizing the correctness of digital images becomes important when those images are used as evidence in legal, forensic, industrial, and military applications. One of the most common ways to forge images is copy move forgery, in which one part of the image is copied and pasted in another part of the same image. So far, various methods have been proposed for detecting copy move forgery, but these methods are not able to detect copy move forgery with different challenges of noise, rotation, scale, and detection of symmetrical images with high accuracy. In this paper, an enhanced hybrid method based on local and frequency feature extraction is presented for image copy move forgery detection, which has a very high resistance to above challenges, both individually and simultaneously and has provided good identification accuracy. In this method, the combination of Discrete Wavelet Transform, Scale Invariant Feature Transform and Local Binary Pattern are used simultaneously. The forged area is chosen in such a way that at least both methods used in this proposed method have consensus about the forgery of that area. Various experiments and analyses on the MICC database show that the proposed methods, despite the above challenges, have reached the accuracy of 98.81% both separately and simultaneously, which shows significant improvement compared to other methods used in this field. [ABSTRACT FROM AUTHOR]

In this paper, a Zero-Voltage Transition (ZVT) non-isolated high step-up multi-input DC-DC converters is proposed which employs an auxiliary cell and diode-capacitor multiplier. The auxiliary cell has only one switch and is suitable for high step converters with diode-capacitor multiplier. In the proposed converter, all semiconductor devices operate under fully soft switching condition. The main switches turn on and turn off under Zero Voltage Switching (ZVS) condition whereas the auxiliary switch turns on under Zero Current Switching (ZCS) condition and turns off under zero Voltage and Zero Current Switching (ZVZCS) condition. Also, ZCS condition at turn-off is provided for all diodes to eliminate reverse recovery issue. The structure of the proposed converter includes two boost cells, one diode-capacitor multiplier cell, and one ZVT auxiliary circuit. Soft switching conditions for all main switches are provided by only one auxiliary circuit. The proposed converter has high step-up conversion gain without any coupled inductor. Soft switching conditions, continuous current of input sources, high efficiency, expansion capability of input sources, returning the energy of the auxiliary circuit to the diode-capacitor multiplier and low-voltage stress on switches are the main advantages of the proposed converter. The steady-state analysis of the converter and operation modes are discussed. A 160-W prototype of the proposed converter is designed and implemented. Experimental results confirm that the theoretical and the efficiency of the proposed converter reaches 96.4% at the nominal load. [ABSTRACT FROM AUTHOR]

In this paper, electromagnetic (EM) scatterings from electrically large Perfect Electric Conductor (PEC) and Perfect Magnetic Conductor (PMC) targets coated with Uniaxial Electric Anisotropic Medium (UEAM) layer are evaluated and compared. The effect of the coating layer’s parameters including εu, εv and the thickness (d) are studied. It is shown that radar cross section (RCS) of a PMC with UEAM coating is less than that of PEC with the same coating. In some cases, about 20 dB reduction in RCS has been obtained for UEAM coated PMC plate. [ABSTRACT FROM AUTHOR]

One of the essential pieces of equipment in the power system is the Automatic Voltage Regulator (AVR) or synchronous generator excitation. The system's goal is to maintain the terminal voltage of the synchronous generator at the desired level. AVR is inherently uncertain. Hence, the proposed controller should be able to handle the problem. In this paper, Fractional Order Fuzzy PID (FOFPID) controller has been employed to control the system. To enhance the controller's performance, the Grasshopper Optimization Algorithm (GOA) is used to tune the controller's parameters. Unlike other methods, the FOFPID controller gains are not constant and alter in different operating conditions. The robustness of the controller has been investigated, and the comparative results show that the proposed controller has a better performance against other methods. [ABSTRACT FROM AUTHOR]

Palestine has a large number of remote small communities with no electricity services and the probability of connecting them with local grid in the near future is very poor, because of political and financial issues. This paper will illustrate the techno- economic impact of electrification small communities using micro-grid photovoltaic systems, and also the CO2 emission that will be reduced in comparative of using diesel generator which pollutes the environment. The implementation of two micro-grid PV-systems for electrification of two communities in Palestine will cover the electricity needs of households and street lighting, and can replace candles, kerosene and traditional unsustainable biomass and diesel generators. Beside economic and social benefits, micro-grid PV systems also have positive impacts on people’s health and on the environment due to the reduction of smoke and toxic waste. [ABSTRACT FROM AUTHOR]

Nowadays, energy supplied by the reliable manner is one of the important challenges of the distribution company in the radial distribution system. Therefore, this paper considers these challenges by the optimal DG placement to minimize power losses with considering the analysis related to the reliability and voltage profile. In this paper, exchange market algorithm (EMA) is used as a powerful tool to solve the optimization problem. In order to extract the global optimum point, EMA uses two searching operators and two absorbent operators based on the generation of random numbers. To evaluate the goals of this paper, EMA is successfully implemented on 10, 33, and 69 bus IEEE test systems. Simulation results have illustrated that power losses are reduced by the optimal DG placement and size. Finally, the analysis of obtained results has shown the system's reliability; voltage profile can be improved if the DGs are allocated optimally in the radial network. [ABSTRACT FROM AUTHOR]

This paper proposes a new Space Vector Modulation (SVM) technique to control the grid-side inverter for improving the output power quality of a Doubly-Fed Induction Generator (DFIG) based Wind Energy Conversion System (WECS). A five-level Cascaded H-Bridge Inverter (CHBI) was used to connect the DFIG to the grid. The SVM algorithm enables controlling of the DFIG inverter which improves the quality of the output power by reducing the Total Harmonic Distortion (THD) of the generated currents and power ripples. However, the multi-level inverter has a major drawback, the even-order harmonics production, which can be overcame by controlling the five-level CHBI using this novel SVM technique generalized to N-level. The paper further presents the mechanism of this algorithm and a method to deduce the trajectories from the sequences, enabling reduction of the time and number of commutations, a better performance among several possible trajectories, and reduction of the THD rate of the DFIG output currents. [ABSTRACT FROM AUTHOR]

Ensemble Clustering (EC) methods became more popular in recent years. In this methods, some primary clustering algorithms are considered to be as inputs and a single cluster is generated to achieve the best results combined with each other. In this paper, we considered three hierarchical methods, which are single-link, average-link, and complete-link as the primary clustering and the results were combined with each other. This combination was done based on correlation matrix. The basic algorithms were combined as binary and triplicate and the results were evaluated as well. the IMDB film dataset were clustered based on existing features. CH, Silhouette and Dunn Index criteria were used to evaluate the results. These criteria evaluate the clustering quality by calculating intra-cluster and inter-cluster distances. CH index had the highest value when all three basic clusters are combined. Our method shows that EC can achieve better results and present clusters with higher robustness and accuracy. [ABSTRACT FROM AUTHOR]

Nowadays Vehicular Ad-Hoc Networks (VANETs) are very popular and significantly used, due to their unique abilities to improve road safety. As a consequence, the security of these networks is of great importance and it has become one of the central topics in scientific and research fields such as information exchange. Sybil attack is one of the challenges for Ad-Hoc networks security. In this paper, a cross-layer approach and fuzzy logic method are used to detect the Sybil attacks. The proposed fuzzy logic method has four inputs form different OSI layers: entry time to the network, a number of neighbors, buffer size and signal to noise ratio. These inputs are imported to several membership functions of the fuzzy logic methods and the simulation results indicate that the proposed solution provides a robust technique in Sybil attack detection. [ABSTRACT FROM AUTHOR]

As a real time process, in tuning the coefficients of PID controllers in AVRs, accuracy vs. speed is an important issue. Considering complexity of the problem and real systems requirements, various methods, including exact methods and approximation algorithms, have been implemented for this purpose. Since the conventional methods based on metaheuristic algorithms solving this problem, generally use population-based algorithms such as GA and PSO, this paper aims to investigate the efficiency and performance of single- solution based metaheuristics to solve this problem. So Simulated Annealing (SA) algorithm is proposed, and implemented for optimizing PID coefficients. In addition, an extension of SA is presented improving the search strategy based on neighborhood adjustment. The results indicate that the proposed algorithms as single based metaheuristics, have a good or even better performance vs. population based metaheuristics, in spite of simplicity in implementation and less computation requirements. This fact implies that the landscape complexity of these problems does not necessarily require population-based algorithms. The presented method is also applied to multiple objective functions regarding different time response criteria in output voltage and leads to better results in less time. [ABSTRACT FROM AUTHOR]

Quantum Cellular Automata (QCA) is an alternative promising nanotechnology for semiconductor transistor based technology. QCA benefits from several features such as high speed, low power consumption and can be used for extremely dense structures. One of the important issues in arithmetic circuits is design of full adder/full subtractor (FA/FS respectively). Our main contribution in this paper is proposing a one-bit FA/FS which benefits from less cell counts compared to the state-of-the-art technologies. The proposed QCA FA/FS ameliorate the number of cells in comparison with the best FA/FS studied in the literature. As well as the mentioned feature, temperature analysis of suggested circuit shows that our design is more tough compared to the previous works. [ABSTRACT FROM AUTHOR]

DDoS (Distributed Denial-of-Service) attacks are among the cyberattacks that are increasing day by day and have caused problems for computer network servers. With the advent of SDN networks, they are not immune to these attacks, and due to the software-centric nature of these networks, this type of attack can be much more difficult for them, ignoring effective parameters such as port and Source IP in detecting attacks, providing costly solutions which are effective in increasing CPU load, and low accuracy in detecting attacks are of the problems of previously presented methods in detecting DDoS attacks. Given the importance of this issue, the purpose of this paper is to increase the accuracy of DDoS attack detection using the second order correlation coefficient technique based on ∅-entropy according to source IP and selection of optimal features. To select the best features, by examining the types of feature selection algorithms and search methods, the WrapperSubsetEval feature selection algorithm, the Best-First search method, and the best effective features were selected. This study was performed on CTU-13 and ISOT datasets and the results were compared with other methods. The accuracy of the detection in this work indicates the high efficiency of the proposed approach compared to other similar methods. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSNs) are a special class of wireless ad-hoc networks where their performance is affected by different factors. Congestion is of paramount importance in WSNs. It badly affects channel quality, loss rate, link utilization, throughput, network life time, traffic flow, the number of retransmissions, energy, and delay. In this paper, congestion control schemes are classified as classic or soft computing-based schemes. The soft computing-based congestion control schemes are classified as fuzzy logic-based, game theory-based, swarm intelligence-based, learning automata-based, and neural network-based congestion control schemes. Thereafter, a comprehensive review of different soft computing-based congestion control schemes in wireless sensor networks is presented. Furthermore, these schemes are compared using different performance metrics. Finally, specific directives are used to design and develop novel soft computing-based congestion control schemes in wireless sensor networks. [ABSTRACT FROM AUTHOR]

Optical Coherence Tomography (OCT) imaging technique has emerged as a non- or minimally invasive modality in the clinical pathogenesis such as deep tissue examining and optical biopsy etc. The OCT imaging increases the Depth of Focus (DoF) by devising mechanisms to increase an Optical Transfer Function (OTF) of the imaging system. This is achieved through an apodization technique on the surface of lens in conjugation with the femtosecond Bessel-type laser beam. An investigation on postulation of OTF through a masked aperture, or specifically a micro-dot is investigated to measure variations of intensity profile at the optical coordinates in the radial as well as axial directions. The intensity variations in the radial and axial coordinates are calibrated to obtain the information, which significantly helps in devising of OCT imaging system. A theoretical investigation of OTF matching the experimental relationship between spot size and DoF in response to obscuration ratio is presented in this paper. This mathematical approach could be applied to different types of masking functions by meticulously exploring the parameters of optical coordinates. [ABSTRACT FROM AUTHOR]

Emotion Speech Recognition (ESR) is recognizing the formation and change of speaker’s emotional state from his/her speech signal. The main purpose of this field is to produce a convenient system that is able to effortlessly communicate and interact with humans. The reliability of the current speech emotion recognition systems is far from being achieved. However, this is a challenging task due to the gap between acoustic features and human emotions, which relies strongly on the discriminative acoustic features extracted for a given recognition task. Deep learning techniques have been recently proposed as an alternative to traditional techniques in ESR. In this paper, an overview of Deep Learning techniques that could be used in Emotional Speech recognition is presented. Different extracted features like MFCC as well as feature classifications methods including HMM, GMM, LTSTM and ANN have been discussed. In addition, the review covers databases used, emotions extracted, and contributions made toward ESR. [ABSTRACT FROM AUTHOR]

Sleep is a normal state in humans and the subconscious level of brain activity increases during sleep. The brain plays a prominent role during sleep, so a variety of mental and brain-related diseases can be identified through sleep analysis. A complete sleep period according to the two world standards R&K and AASM consists of seven and five steps, respectively. To diagnose diseases through sleep, it is necessary to identify different stages of sleep because the disorder at each stage indicates a certain disease. On the other hand, efficient and useful features should be selected to increase the accuracy of sleep stage classification. In this paper, at first, different statistical, entropy, and chaotic features are extracted from sleep data. Afterwards, by introducing and using the Laplacian score selector, the best feature set is selected. At the end, some conventional classification algorithms such as SVM, ANN and KNN are used to classify different sleep stages. Simulation results confirms the superiority of the proposed method based on the classification results. With the proposed algorithm, 2, 3, 4, 5 and 6 stages of sleep were classified by SVM and decision tree with 98.0%, 98.0%, 97.3%, 96.6%, and 95.0% accuracy, which are more superior to previous method’s results. [ABSTRACT FROM AUTHOR]

Modern distribution system including Distributed Generation (DG) requires reliable and fast islanding detection algorithms in order to determine the grid status. In this paper, a new multi-model classification-based method is proposed, in order to detect islanding condition for photovoltaic units. Decision tree is chosen as the classification algorithm to classify input feature vectors. The final result is based on voting among three decision tree algorithms. First order derivatives of electrical parameters are employed to construct feature vectors. To cover intermittent nature of renewable sources, different generating states for PV unit are assumed. Probable events are simulated under different system operating states to generate classification data set. The proposed method is tested on typical distribution system including the PV unit, different loads, and synchronous generator. This study showed that this method succeeds in highly fast islanding detection. This quick response can be used in micro-grid application as well as anti-islanding strategy. The results revealed that the proposed voting-base algorithm could classify instances with very high accuracy which leads to reliable operation of distributed generation units. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) is a major clinical tool to diagnose, monitor and manage neurological disorders which is mostly affected by artifacts. Given the importance and the need for an automated method to remove artifacts, in this paper some intelligent automated methods are proposed which are composed of three main parts as extraction of effective input, filtering and filter optimization. Wavelet transform is utilized to extract the effective input, and the wavelet approximation coefficients are used as an effective input signal. In addition, Radial Basis Function Neural Network (RBFNN) has been used for filtering. The appropriate number of RBFs has been selected using extensive simulations, and the optimal value of spread parameter has been achieved by Bees algorithm (BA). Finally, the proposed artifact removal schemes have been evaluated on some real contaminated EEG signals in Mashad Ghaem hospital database. The results show that the proposed artifact removal schemes are able to effectively remove artifacts from EEG signals with little underlying brain signal distortion. [ABSTRACT FROM AUTHOR]

The multi-phase permanent-magnet motors are suitable choices for certain purposes like aircrafts, marine, and electric vehicles due to the fault tolerance and high-power density capabilities. The paper aims to design and prototype an optimized five-phase fractional slot concentrated windings surface mounted permanent magnet motor. To optimize the designed multi-phase motor, a multi-objective optimization technique based on the genetic algorithm method has been applied. The machine design objectives are to minimize mass and loss, subsequently, to determine the best choice of the designed machine parameters. Afterwards, 2-Dimensional Finite Element Method (2D-FEM) has been used to verify the performance of the optimized machine. Finally, the optimized machine has been prototyped. The results of the prototyped machine have validated the results of the theatrical analyses of the machine, and accurate consideration of the parameters improved the performance of the machine. [ABSTRACT FROM AUTHOR]

This paper objective presents static synchronous series compensation FACTS device with biogeography based optimization (BBO) to deal for obtaining worthwhile power flow control. The biogeography based optimization method is utilized to find the optimal fitted child sets by surviving parents with the help of migration and mutation Jaipur process. The present BBO technique from the evolutionary strategy with static synchronous series compensator provides improved outcomes in comparison to other optimization methods. The simulation outcomes illustrate that the proposed BBO algorithm is efficacious, secure and correct to search the optimized values with SSSC based FACTS devices. The proposed method is considering the solution quality an optimistic substitute method for extricating the OPF problems. The simplification and effectiveness of this method are validated on the IEEE 57 bus and 75 bus Systems. In this paper, from the outcome results, it is clearly shown that the proposed technique execution can be properly and effectively applied to the optimal position of multiple OPF problems. i.e. BBO based algorithm with SSSC FACTS device is found better results when compared to without SSSC device in all aspects. [ABSTRACT FROM AUTHOR]

This paper presents a simulation of the dynamic voltage stability in power system. In application of modern power system, dynamic assessment of voltage stability is known as basic concept. In order to study dynamic voltage stability in a power system, different dynamic boundaries are defined such as, Hopf bifurcation (HB) boundary. HB point is an oscillatory boundary in power system. For recognition of the bifurcations, it is unavoidable to study the eigenvalues of power system. In spite of this, determination of these eigenvalues needs to dynamic Jacobian matrix of power system and modal analysis that is very time consuming and complex in large systems. Also, different industrial loads (static and dynamic) e.g. induction motors can effect on dynamic voltage stability boundaries. In this paper, we proposed a solution method based on analyzing the eigenvalues of reduced Jacobian matrix and time domain simulation for assessment of dynamic voltage stability. In addition, effects of industrial electrical loads on the small disturbance voltage stability are evaluated by the proposed method. To show the effectiveness of the proposed solution method, it is tested on IEEE 14 bus and New England test systems. [ABSTRACT FROM AUTHOR]

In this paper Fuzzy-FOPID controller is used in order to control automatic voltage regulator (AVR) system. This controller has six parameters. In this paper optimization method is employed to determine the controller parameters. For this purpose, imperialist competitive algorithm (ICA) is used for its high accuracy and good performance. To illustrate performance of proposed controller, some simulations are carried out in MATALB and the results are compared with FOPID controller results. Good performance of proposed controller is validated by results of simulations. [ABSTRACT FROM AUTHOR]

In this paper, an optical communication receiver system for 5Gbps applications is proposed concerning power consumption. An inductor-less circuit in three-stages is proposed as the trans-impedance amplifier (TIA), which benefits from the inherent low input resistance of a common gate topology as the first stage. By forming two zeros in this TIA, proper frequency response is obtained while the DC current is reduced. In order to obtain extra gain for the receiver system, three stages of conventional limiting amplifier (LA) are used. In order to verify the circuit performance, the proposed receiver is simulated in HSPICE using 90nm CMOS technology parameters. The receiver is mathematically studied and is matched with the simulations. This paper conducts the simulations, such as eyediagram, noise analysis and fabrication process analysis (Monte-Carlo). The proposed Trans-Impedance Amplifier shows 53.9dbΩ gain, 3.5GHz bandwidth, 15.2pA/√Hz and only 1.52mw power consumption for 1.2v supply voltage, and the receiver system shows 90.9dbΩ, 3.5GHz bandwidth and 6.34mw power consumption (for 2 stages of TIA and 3 stages of LA) for 1.2v supply voltage. Results indicate that the proposed receiver is suitable to work as a low-power 5Gbps optical communication receiver system. [ABSTRACT FROM AUTHOR]

Taking the advantages of alternative energy sources is currently a trending concept in the field of energy management. Meanwhile, microgrids and hybrid energy systems are of great importance due to their numerous benefits for both consumers and utility. This paper presents technical feasibility study of a hybrid energy system, including renewable and non-renewable resources and energy storage system, for electrification of a Disaster Management Basement located in Tehran, Iran. To simulate the potential power blackout caused by a disaster, the proposed system is simulated and optimized in off-grid mode, using HOMER simulation software. Since the disaster occurrence is unpredictable, while the system is simulated in a whole year, the results are analyzed in two winter and summer cases. Regarding reliability of the system, a sensitivity analysis is carried out. It was found that with diesel prices up to 0.5- 0.6 $/L, the only optimal power system is diesel generator. With prices more than this, wind and solar power sources should be added to the power system. As the main result of the paper, it was found that renewables can act as good backup power systems in cases of shortages in conventional energy resources to ensure high reliability of the system. [ABSTRACT FROM AUTHOR]

In this paper, new reactive power market structure is studied and presented. In this paper, after separating active and reactive losses from each other, the reactive losses which are generated from active power flow is considered in the reactive power market. As this reactive power loss are generated by the implementation of the energy market and not related to reactive power market, they must be generated mandatory by each unit. So, the main purpose of this paper is to consider reactive losses of the active power flow without any payment to it. Hence, this study tries to improve reactive power market and create fair competition in reactive power generation through modifying the market structure. The advantage of this method is determining the mandatory region of units based on both active power output and its distance from the load. In order to stimulate the proposed method, IEEE 24 is used, and this method is compared with each the conventional reactive power market. As it will be shown, the total payment by ISO will be reduced by using this method. [ABSTRACT FROM AUTHOR]