International Journal of Electrical and Computer Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Articles
6,393 Documents
Wireless sensor network’s localization based on multiple signal classification algorithm
Lafta, Nabeel Aad;
Hreshee, Saad S.
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i1.pp498-507
Wireless sensor networks (WSNs) are a number of sensitive nodes senses a physical phenomenon at the position of their deployment then sends information to the base station to take appropriate operation. (WSNs) are used in many applications such track military targets, discover fires, study natural phenomena such as earthquakes, humidity, heat, etc. The nodes are spread in large areas and it is difficult to locate them manually because they are published randomly by planes or any other method and since the information received from sensitive nodes is useless without knowing their location in this case a problem resulted in the positioning of the nodes. So it unacceptable to equip each sensor node with global position system (GPS) due to various problems such as raises cost and energy consumption. In this paper explained a non-GPS technique to self-positioning of nodes in (WSNs) by using the multiple signal classification (MUSIC) algorithm to determine the position of the active sensor through estimated the direction of arrival (DOA) of the node signal. Then modified MUSIC algorithm (M-MUSIC) to solve the problem of coherent signal. MATLAB program successfully used to simulate the proposed algorithm.
Different valuable tools for Arabic sentiment analysis: a comparative evaluation
Zahidi, Youssra;
El Younoussi, Yacine;
Al-Amrani, Yassine
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i1.pp753-762
Arabic Natural language processing (ANLP) is a subfield of artificial intelligence (AI) that tries to build various applications in the Arabic language like Arabic sentiment analysis (ASA) that is the operation of classifying the feelings and emotions expressed for defining the attitude of the writer (neutral, negative or positive). In order to work on ASA, researchers can use various tools in their research projects without explaining the cause behind this use, or they choose a set of libraries according to their knowledge about a specific programming language. Because of their libraries' abundance in the ANLP field, especially in ASA, we are relying on JAVA and Python programming languages in our research work. This paper relies on making an in-depth comparative evaluation of different valuable Python and Java libraries to deduce the most useful ones in Arabic sentiment analysis (ASA). According to a large variety of great and influential works in the domain of ASA, we deduce that the NLTK, Gensim and TextBlob libraries are the most useful for Python ASA task. In connection with Java ASA libraries, we conclude that Weka and CoreNLP tools are the most used, and they have great results in this research domain.
Stochastic local search: a state-of-the-art review
Kastrati, Muhamet;
Biba, Marenglen
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i1.pp716-727
The main objective of this paper is to provide a state-of-the-art review, analyze and discuss stochastic local search techniques used for solving hard combinatorial problems. It begins with a short introduction, motivation and some basic notation on combinatorial problems, search paradigms and other relevant features of searching techniques as needed for background. In the following a brief overview of the stochastic local search methods along with an analysis of the state-of-the-art stochastic local search algorithms is given. Finally, the last part of the paper present and discuss some of the most latest trends in application of stochastic local search algorithms in machine learning, data mining and some other areas of science and engineering. We conclude with a discussion on capabilities and limitations of stochastic local search algorithms.
Global convergence of new conjugate gradient method with inexact line search
Chergui Ahmed;
Bouali Tahar
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i2.pp1469-1475
In this paper, We propose a new nonlinear conjugate gradient method (FRA) that satisfies a sufficient descent condition and global convergence under the inexact line search of strong wolf powell. Our numerical experiment shaw the efficiency of the new method in solving a set of problems from the CUTEst package, the proposed new formula gives excellent numerical results at CPU time, number of iterations, number of gradient ratings when compared to WYL, DY, PRP, and FR methods.
A framework for IoT-enabled environment aware traffic management
Mohamed Firdhous, Mohamed Fazil;
Sudantha, B. H.;
Hussien, Naseer Ali
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i1.pp518-527
Vehicular traffic has increased across all over the world especially in urban areas due to many reasons including the reduction in the cost of vehicles, degradation of the quality of public transport services and increased wealth of people. The traffic congestion created by these vehicles causes many problems. Increased environment pollution is one of the most serious negative effects of traffic congestion. Noxious gases and fine particles emitted by vehicles affect people in different ways depending on their age and present health conditions. Professionals and policy makers have devised schemes for better managing traffic in congested areas. These schemes suffer from many shortcomings including the inability to adapt to dynamic changes of traffic patterns. With the development of technology, new applications like Google maps help drivers to select less congested routes. But, the identification of the best route takes only the present traffic condition on different road segments presently. In this paper the authors propose a system that helps drivers select routes based on the present and expected environment pollution levels at critical points in a given area.
Computational and experimental study of air-core HTS transformer electrothermal behaviour at current limiting mode
Manusov, V. Z.;
Kriukov, D. O.;
Semenov, A. V.
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i1.pp155-162
The paper provides the results of the experimental and computational study of the processes occurring in high temperature superconducting transformer windings while secondary winding is short-circuited. The obtained mathematical simulation matches closely with the experimental results. The temperature variation curves for superconducting windings were analysed, and conclusions were made on the necessity of changes in HTS transformer design, namely the necessity of windings heat-insulation from each other and adding a high-resistance coating material for HTS wire in HTS transformer primary winding.
FPGA configuration of an alloyed correlated branch predictor used with RISC processor for educational purposes
Mahmood, Hadeel SH.
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i1.pp265-271
Instructions pipelining is one of the most outstanding techniques used in improving processor speed; nonetheless, these pipelined stages are constantly facing stalls that caused by nested conditional branches. During the execution of nested conditional branches, the behavior of the running branch depends on the history information of the previous ones; therefore, these branches have the greatest effect in reducing the prediction accuracy of a branch predictor among conditional branches. The purpose of this research is to reduce the stall cycles caused by correlated branches misprediction by introducing a hardware model of a branch predictor that combines both local and global prediction techniques. This predictor integrates the prediction characteristics of the alloyed predictor with those of the correlated predictor. the predictor design which implemented in VHDL (Very high-speed IC hardware description language) was inserted in previously designed MIPS (microprocessor without interlocked pipelined stages) processor and its prediction accuracy was confirmed by executing a program using the selection sort algorithm to sort 100 input numbers of different combinations ascendingly.
FACTS allocation considering loads uncertainty, steady state operation constraints, and dynamic operation constraints
M. M. H. Elroby;
S. F. Mekhamer;
H. E. A. Talaat;
M. A. Moustafa Hassan
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i2.pp945-955
This study proposes an algorithm to allocate different types of flexible AC transmission system (FACTS) in power systems. The main objective of this study is to maximize profit by minimizing the system’s operating cost including FACTS devices (FDs) installation cost. Dynamic and steady state operating restrictions with loads uncertainty are included in the problem formulation. The overall problem is solved using both teaching learning based optimization (TLBO) technique for attaining the optimal allocation of the FDs as main-optimization problem and matpower interior point solver (MIPS) for optimal power flow (OPF) as the sub-optimization problem. The validation of the proposed approach is verified by applying it to test system of 59-bus; Simplified 14-Generator model of the South East Australian power system.
Simulation of a microgrid for a non-interconnected zone that integrates renewable energies
Reina, German;
Mauledoux, Mauricio;
Aviles, Oscar A.
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i1.pp201-216
This paper develops a simulation of a small electrical network (Microgid) that integrates renewable energies, the model of the micro network is made up of a solar energy source, a wind energy source, an energy storage element, a non-renewable source such as a diesel generator. The model of the microgrid represent a non-interconnected area from the electrical network in Colombia. The non-interconnected areas sometimes depend on unreliable connections to the grid integration of renewable energies could be the best option to guarantee energy in these sectors and allow generating projects with social impact. A possible solution to this deficit of energy is to supplement the production of energy with renewable energy plants from resources as sun or wind. The simulated model allowed to study the effects of the network in island mode and in interconnected mode, showing the imbalances that can be obtained by integrating renewable energies and storage systems. It is verified that with an inclusion of more than 30% of power in renewable energies there is the possibility of having load imbalances, which affect the frequency and cause instability in the network. It also verifies how a control system can regulate the load balance but must interact with the other energy sources.
DTC based on SVM for induction motor sensorless drive with fuzzy sliding mode speed controller
Massoum, Sarra;
Meroufel, Abdelkader;
Massoum, Ahmed;
Patrice, Wira
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i1.pp171-181
By using the direct torque control (DTC), robust response in ac drives can be produced. Ripples of currents, torque and flux are oberved in steady state. space vector modulation (SVM) applied in DTC and used for a sensorless induction motor (IM) with fuzzy sliding mode speed controller (FSMSC) is studied in this paper. This control can minimize the torque, flux, current and speed pulsations in steady state. To estimate the rotor speed and stator flux the model reference adaptive system (MRAS) is used that is designed from identified voltages and currents. The FSMSC is used to enhance the efficiency and the robustness of the presented system. The DTC transient advantage are maintained, while better quality steady-state performance is produced in sensorless implementation for a wide speed range. The drive system performances have been checked by using Matlab Simultaion, and successful results have been obtained. It is deduced that the proposed control system produces better results than the classical DTC.