Majlesi Journal of Electrical Engineering 2019-12-09T12:30:27+00:00 Dr. Mohsen Ashourian Open Journal Systems <p>The scope of MJEE is ranging from mathematical foundation to practical engineering design in all areas of electrical engineering. The editorial board is international and original unpublished papers are welcome. The journal is devoted primarily to research papers, but very high quality survey and tutorial papers are also published. There is no publication charges for authors.</p> Voltage Control of Dual Input Step-up SCI Converter using Fuzzy Switching Control Method 2019-12-06T14:55:35+00:00 Vahid Omrani Mohammad Reza Ershadi Mohammad Hossein Ershadi <p>In this paper, dual input step-up switched capacitor inductor (SCI) converters have been investigated. At first, the structure of this converter was reviewed and analyzed carefully. It is showed that besides capacitor and inductor, a small resonant inductor is also used in order to limit the current peak caused by switched capacitor. Therefore, efficiency has been improved. Fuzzy control method used for switching control of the circuit and simulation results showed that, output waveforms are according to idealized ones, output voltage ripple decreased dramatically and high voltage gained has been achieved</p> 2019-07-18T14:43:14+00:00 ##submission.copyrightStatement## Optimal Performance of Micro-grids Networks with Uncertainty using Game Theory Coalition Formulation Strategy 2019-12-06T14:55:35+00:00 Karvan Karimizadeh Soodabeh Soleymani Faramarze Faghihi <p>The demand for energy is constantly increasing, which is pushing the limitations of the current grid, increasing reliance on fossil fuels, and increasing CO2 emissions. These concerns have renewed interest in discovering ways to reduce power demand on the grid through renewable energy. However, the distribution characteristics of renewable energy make it difficult to integrate effectively into the traditional power grid. As power networks increase in scale, the drawbacks of the conventional grid, such as high cost and difficult operation, will become more apparent, and it will no longer meet increasing safety, reliability, and diversity. Therefore, applying efficient methods to improve the performance of micro-grids is necessary. In this paper the application of CRPSO algorithm based on the game theoretic formulation strategy was proposed to reduce the exchange of power between the macro station and micro-grids. The objective function of optimization involves minimizing the cost of power, loss, communication and load shedding. The advantages have caused the load of the micro-grids to be implemented as much as possible through the exchanges between the micro-grids and the cost of utilization and power supply of the loads to be minimized. Uncertainties in wind speed and solar radiation flux are also considered for the purpose of applying the random property of the distributed generation resources. The simulation results on the 33rd IEEE standard system in different scenarios indicate the desired performance of the proposed method.</p> 2019-07-29T12:21:40+00:00 ##submission.copyrightStatement## Sliding Mode Control Improvement by using Model Predictive, Fuzzy Logic, and Integral Augmented Techniques for a Quadrotor Helicopter Model 2019-12-06T14:55:35+00:00 Amir Hossein Zaeri Aida Esmaeilian-Marnani Samsul Bahari Mohd Noor <p>In this paper, a new control method is adopted based on merging multi-input integral sliding mode control with boundary layer (ISMC-BL), model predictive control (MPC), and fuzzy logic control (FLC). The aim of this merging is to take advantage of MPC ability to deal with constraints and to gain optimal solution. Moreover, FLC is considered in designing the sliding surface based on fuzzy rules and tracking error. This method is simulated on a nonlinear quadrotor helicopter model. The results reveal that the proposed control approach, which is a multi-input model predictive fuzzy integral sliding mode control with boundary layer (MPFISMC-BL), is a robust, stable, optimal, and intelligent control scheme. This finding can contribute to improve the control of similar systems.</p> 2019-08-06T12:38:16+00:00 ##submission.copyrightStatement## MMS: Multi-rate Multicast Scheduling in Multi-┬Čradio Single-cell CR-WMNs 2019-12-09T08:08:43+00:00 Fahimeh Aghaei Avid Avokh <p>Nowadays, cognitive radio technology is mentioned as a new model for wireless communication. In this paper, by extending the previous works, both multi-radio and multi-rate technologies in single-cell multi-channel cognitive radio wireless mesh networks were adopted. In this regard, an efficient scheduling algorithm is introduced named Multi-Rate Multicast Scheduling (MMS). Multi-radio technology allows the nodes to simultaneously send/receive packets on the distinct channels. Consequently, the network throughput will be increased. Furthermore, since different transmission rates lead to different spectrum utilizations, efficient use of the multi-rate capability can improve the performance of the network. Numerical results of our comprehensive simulations confirm the efficiency of the MMS algorithm.</p> 2018-06-03T00:00:00+00:00 ##submission.copyrightStatement## Improvement of the VSC-HVDC System Performances Based on the Intelligent Controller 2019-12-06T14:55:36+00:00 Hameurlaine Abdelhadi H. Sayah M. Boudiaf <p>Voltage Source Converter based High Voltage Direct Current (VSC-HVDC) has been an area of growing interest during the recent years. Indeed, VSC-HVDC has the capability to control rapidly in the same time the active power and the reactive power independently. This paper focuses mainly on the VSC-HVDC system modeling where two different controllers such as the PI controller and the fuzzy logic controller have been implanted. Furthermore, these two controllers have been analyzed and compared to each other. Whereas, the main objective of the work presented in this paper is to find the more suitable controller which allows improving the robustness of the whole system control and its impact on the dynamic performance of the VSC-HVDC during parameter uncertainties, such as load change, parametric variation and faults occurrence. The obtained results show that the use of the fuzzy controller can lead to better performance of the studied system compared to other controller. &nbsp;</p> 2019-08-21T14:21:25+00:00 ##submission.copyrightStatement## Load Balancing Based on Statistical Model in Expert Cloud 2019-12-06T14:55:36+00:00 Shiva Razzaghzadeh Ahmad Habibizad Navin Amir Masoud Rahmani Mehdi Hosseinzadeh <p>Expert Cloud is a new class of Cloud computing which enables the users to achieve their requirements from a collection containing experts and skills created by the human resources (HRs). The acquisition of these skills and experts from this collection is possible by using the Internet and Cloud computing concepts without consideration of the HRs location. The load balancing in cloud computing means equal load distribution among resources, virtual machines (VMs) and servers. The effective load distribution in a heterogeneous environment such as cloud is an important challenge. The increase in the number of users, the differences of request types and also different resources capabilities and capacities cause that some resources become overload and some others become idle. This paper presents a dynamic load balanced task scheduling algorithm in expert cloud. In this method, we utilize the genetic algorithm (GA) as a ranking for making distinction among the HRs capabilities. In our proposed method, we use interval estimation and specification matrix to allocate the HRs and also to determine the service rate. We model the load balancing and mapping process based on Simple Exponential Smoothing and Probability Theory. This statistical load balancing model allows us to allocate the HRs based on service rate and Poisson model. So, each task is delivered to the HR which is capable to execute it. The simulation results show that the expert cloud can reduce the execution and tardiness time and improve HR utilization. The cost of using resources as an effective factor is also observed.&nbsp;</p> 2019-03-12T00:00:00+00:00 ##submission.copyrightStatement## Service Composition and Customization of Its Features Based on Combined Classification 2019-12-06T14:55:36+00:00 Mohsen Eghbali Sima Emadi <p>By promoting service-oriented architecture in e-services of organizations and inter-organizational relationships, service quality is more focused. To provide high quality combined service, it is necessary to identify quality requirements of users and offer service in line with those. Service users tend to choose a combined service among the huge collection of available services based on quality of service. In the case of competition among rivals, service providers must customize features of service as one of the key strategies. Customization involves the combination of service features based on user requests, these strategies raise new problems on the expression and dissemination of quality information, service identification and setting qualitative offers to service users. In the previous methods, pre-processing step was not performed in the services set, and false service suggestions to the user were possible. &nbsp;In this study, nearest neighbor algorithm was offered to identify consumers and customize their quality of service. Also, Isodata has been used to cluster and filter the services. At the end, a case study was presented to illustrate the proposed method. The results of the evaluation show that the proposed method has tried to solve the existing shortcomings.</p> 2018-12-10T00:00:00+00:00 ##submission.copyrightStatement## The Evolution of Over The Top (OTT): Standardization, Key Players and Challenges 2019-12-06T14:55:36+00:00 Suman Pandey Mi Jung Choi Soyoung Park <p>OTT users has gained momentum through the evolution of low cost smart TV and other consumer electronic, open nature of Internet, and ever growing contents. Among consumer electronics, Smart TV with Web 2.0 features integration has given OTT service a wider range of audience through bigger screen. This has replaced broadcast TV, cable TV and IPTV models. Motivated by this scenario of OTT services we studied standardization activities of different key players including Content Providers (CP), Cloud/Content Distribution Network (CDN), Consumer Electronics (CE) and Internet Service Provider (ISPs) in TV market space. We have summarized several key challenges for OTT services from ISPs point of view for ex, single sign on for multiple OTT, scalability, heavy tail content availability, live TV etc. We also analyzed the suitability of the next-generation Internet architectures; in particular, Content-Centric Networking (CCN), Open Cache and Multicast Adaptive Bitrate (mABR) for OTT service delivery from ISP point of view.</p> 2019-10-16T07:34:56+00:00 ##submission.copyrightStatement## Simultaneous Tuning of Static Synchronous Series Compensator and Multi-Band Power System Stabilizers to Mitigate Sub-Synchronous Resonances in Power Systems 2019-12-06T14:55:37+00:00 Majid Moazzami Hassan Fayazi Bahador Fani Shadi Jalali Ghazanfar Shahgholian <p>In this paper, the concept of simultaneous tuning of static synchronous series compensators and multi-band power system stabilizers for damping out sub-synchronous resonances in a series compensated power system is presented. To achieve an effective damping effect, a supplementary sub-synchronous damping controller is added to the static synchronous series compensator. The teaching-learning-based optimization algorithm is employed for the simultaneous adjustment of the parameters of both the supplementary sub-synchronous damping controller and the power system stabilizer. The proposed method is executed on the IEEE Benchmark system and simulation results are provided to verify its capability in removing sub-synchronous resonances and maintaining the stability of the underlying system.</p> 2018-04-08T00:00:00+00:00 ##submission.copyrightStatement## Variable Structure Rough Neural Network Control for a Class of Non-Linear Systems 2019-12-06T14:55:37+00:00 Sina Dadvand Mohammad Manthouri Mohammad Teshnehlab <p>In this paper, a novel rough neural network control system based on the variable structure control developed for a class of SISO canonical nonlinear systems with taking the presence of bounded disturbance into account is presented. We assume that the nonlinear functions of the system are completely unknown. The rough neural network presented here is used to approximate the unknown nonlinear functions to a desired appropriate approximation. A fuzzy soft switching structure is developed to decide the amount of efforts taken by neural network and variable structure control systems based upon the real-time error characteristics.&nbsp; A proper Lyapunov function is defined and used to deduce adaptive laws for tunable parameters of neural network and to achieve the closed loop stability of overall system. The rough family of neural networks have a reputation of better functionality at the presence of noise and disturbance, which comes from their interval characteristic of their parameters. In this study, we utilize this property to achieve better performance. To demonstrate the effect of proposed control structure, it is applied upon three systems (one exemplary system, a dynamical and a chaotic) and the simulated results show the efficiency of this hybrid variable structure control scheme.</p> 2019-04-09T00:00:00+00:00 ##submission.copyrightStatement## Improving the Detection Rate of Forgery JPEG Images Based on Combining Histogram Features and Discrete Wavelet Transform (DWT) with the Use of Support-Vector Machine 2019-12-06T14:55:37+00:00 Azam Mohammadi Farhad Navabifar <p>Manipulating digital images is not often a difficult task due to the rapid development of software and image manipulation techniques. Hence, there is no need for professional skills or training. When used as an artistic tool, it is completely harmless, but when these images can be presented in judicial system as the evidence or for the creation of political associations, as well as using them in legal documents, electronic money circulation or press, in these cases, the distinction between an original image and a forgery image is very important. In order to solve the problem in this research, by using a discrete wavelet transform (DWT), which is performed by decomposing a signal into smaller and smaller details, as well as the use of periodic patterns in the histogram generated by double compression with different coefficients, significant improvements were made in terms of reducing computations and increasing the detection rate of forging areas. Most of the proposed methods for detecting image forgery use a feature extraction model from a valid and manipulated dataset and then classify them using machine learning with the aim of optimizing accuracy. The method used in paper, using the SVM classification identifies image forgery and then identifies the forging area after it detects the falsification or originality of the image. The results of this study indicate 97.98% accuracy in the Columbia database and 98.1% in the IFS-TC database.</p> 2019-09-20T00:00:00+00:00 ##submission.copyrightStatement## A Patch Ordering Approach to Single Image Super-resolution Problem 2019-12-09T12:30:27+00:00 Vahid Anari Farbod Razzazi Rasoul Amirfattahi <p>In this paper, we propose a novel patch ordering approach to single image super-resolution (SR) algorithm which is called as patch ordering approach to single image super resolution (POSR). We aimed at selecting more informative high-resolution (HR) and low-resolution (LR) patches for single image SR algorithms based on sparse representation and dictionary learning. Our proposed POSR algorithm, first ordered HR and LR patches for each training images based on minimization of total variation measure (TV). Then, it assigned a sampling step for patch selection in each image. In this way, training patches were extracted based on image texture complexity. This leads to training dictionaries with the high and low resolution more efficiently. Unlike other methods which have used additional restrictions in high resolution image reconstruction phase, the proposed method, has only used the basic assumption of sparse representation super resolution. The experimental results for quantitative criteria (PSNR, RMSE, SSIM and elapsed time), human observation as a qualitative measure and computational complexity verify the improvements offered by the proposed POSR algorithm.</p> 2019-07-23T00:00:00+00:00 ##submission.copyrightStatement##