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International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics 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.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 6,393 Documents
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Adaptive key generation algorithm based on software engineering methodology Croock, Muayad Sadik; Hassan, Zahraa Abbas; Khudhur, Saja Dhyaa
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i1.pp589-595

Abstract

Recently, the generation of security keys has been considered for guaranteeing the strongest of them in terms of randomness. In addition, the software engineering methodologies are adopted to ensure the mentioned goal is reached. In this paper, an adaptive key generation algorithm is proposed based on software engineering techniques. The adopted software engineering technique is self-checking process, used for detecting the fault in the underlying systems. This technique checks the generated security keys in terms of validity based on randomness factors. These factors include the results of National Institute of standard Test (NIST) tests. In case the randomness factors are less than the accepted values, the key is regenerated until obtaining the valid one. It is important to note that the security keys are generated using shift register and SIGABA technique. The proposed algorithm is tested over different case studies and the results show the effective performance of it to produce well random generated keys.
Investigation of deformation of the cornea during tonometry using FEM Bharathi R. B.; Gopalakrishna Prabhu; Ramesh S. Ve; Rakshath Poojary; S. Meenatchi Sundaram
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (714.08 KB) | DOI: 10.11591/ijece.v10i6.pp5631-5641

Abstract

A three dimensional finite element model of the human eye is developed to evaluate the force which will be applied over the surface of cornea during tonometry and gonioscopy tests. The standard tonometers and gonioscopy experiences deformation from 0.5mm to 3mm of the cornea is adopted during both point contact and boundary contact on the surface of the cornea. The results demonstrate the maximum force experienced by the tonometer with point contact at the center of the cornea for the maximum possible deformation of the cornea during tonometry. The study also analyzes for the force experienced by the tonometer or goniolens with boundary layer contact for the defined deformation of the cornea along the direction from cornea towards the retina.
Coyote multi-objective optimization algorithm for optimal location and sizing of renewable distributed generators E. M. Abdallah; M. I. El Sayed; M. M. Elgazzar; Amal A. Hassan
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp975-983

Abstract

Research on the integration of renewable distributed generators (RDGs) in radial distribution systems (RDS) is increased to satisfy the growing load demand, reducing power losses, enhancing voltage profile, and voltage stability index (VSI) of distribution network. This paper presents the application of a new algorithm called ‘coyote optimization algorithm (COA)’ to obtain the optimal location and size of RDGs in RDS at different power factors. The objectives are minimization of power losses, enhancement of voltage stability index, and reduction total operation cost. A detailed performance analysis is implemented on IEEE 33 bus and IEEE 69 bus to demonstrate the effectiveness of the proposed algorithm. The results are found to be in a very good agreement.
Real-time simulation of static synchronous condenser (STATCOM) for compensation of reactive power Abdellatif Hinda; Mounir Khiat
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (744.921 KB) | DOI: 10.11591/ijece.v10i6.pp5599-5608

Abstract

This paper presents a real time simulation stability of power system by static synchronous condenser (STATCOM) in modern platform real-time simulator named (RT-LAB) using the latest INTEL quad-core processors to simulate a relatively large power system In our work, We have to study the problem of controlling voltage and reactive power in electric system by static synchronous condenser (STATCOM). All the simulations for the above work have been carried out using MATLAB /Simulink and RT-LAB Various simulations have given very satisfactory results and we have successfully improved the voltage by injecting a FACTS device, which is the STATCOM, the Studies and Comparisons of real-time simulation results of the power system with and without STATCOM connected illustrate the effectiveness and capability of STATCOM in improving voltage stability in power system.
Software development effort estimation modeling using a combination of fuzzy-neural network and differential evolution algorithm Karimi, Amir; Gandomani, Taghi Javdani
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i1.pp707-715

Abstract

Software cost estimation has always been a serious challenge lying ahead of software teams that should be seriously considered in the early stages of a project. Lack of sufficient information on final requirements, as well as the existence of inaccurate and vague requirements, are among the main reasons for unreliable estimations in this area. Though several effort estimation models have been proposed over the recent decade, an increase in their accuracy has always been a controversial issue, and researchers' efforts in this area are still ongoing. This study presents a new model based on a hybrid of adaptive network-based fuzzy inference system (ANFIS) and differential evolution (DE) algorithm. This model tries to obtain a more accurate estimation of software development effort that is capable of presenting a better estimate within a wide range of software projects compared to previous works. The proposed method outperformed other optimization algorithms adopted from the genetic algorithm, evolutionary algorithms, meta-heuristic algorithms, and neuro-fuzzy based optimization algorithms, and could improve the accuracy using MMRE and PRED (0.25) criteria up to 7%.
Design and implementation a network mobile application for plants shopping center using QR code Saja Nasir; Salih Al-Qaraawi; Muayad Croock
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1370.458 KB) | DOI: 10.11591/ijece.v10i6.pp5940-5950

Abstract

During the revolution of developing mobile phone applications, they can be used in different fields like business, health, transportation, communications and tourism, and other uses. This paper presents QR based information management system for plants shopping centers. This system includes two main sides: mobile and server. The proposed application is used as a substitute for the human guide that each visitor needs in the plants shopping center. The complete information can be provided on any seedling displayed in the shop depending on the QR code technology. Each branch of the same enterprise includes sub-server that is linked to the main server using a private computer network. The server side contains information of all plants and all branches for such enterprise in the form of text and image in different languages. The proposed application facilitates the movement of the customer inside the place, the ease in preparing bills electronically that helps the visitor to save the time of queue to preparing the bill and paying. The proposed system is tested over different case studies to prove the efficiency in terms of information and selling management.
Recognition of corona virus disease (COVID-19) using deep learning network Abdulmunem, Ashwan A.; Abutiheen, Zinah Abdulridha; Aleqabie, Hiba J.
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i1.pp365-374

Abstract

Corona virus disease (COVID-19) has an incredible influence in the last few months. It causes thousands of deaths in round the world. This make a rapid research movement to deal with this new virus. As a computer science, many technical researches have been done to tackle with it by using image processing algorithms. In this work, we introduce a method based on deep learning networks to classify COVID-19 based on x-ray images. Our results are encouraging to rely on to classify the infected people from the normal. We conduct our experiments on recent dataset, Kaggle dataset of COVID-19 X-ray images and using ResNet50 deep learning network with 5 and 10 folds cross validation. The experiments results show that 5 folds gives effective results than 10 folds with accuracy rate 97.28%.
On solving fuzzy delay differential equation using bezier curves Ali F. Jameel; Sardar G. Amen; Azizan Saaban; Noraziah H. Man
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v10i6.pp6521-6530

Abstract

In this article, we plan to use Bezier curves method to solve linear fuzzy delay differential equations. A Bezier curves method is presented and modified to solve fuzzy delay problems taking the advantages of the fuzzy set theory properties. The approximate solution with different degrees is compared to the exact solution to confirm that the linear fuzzy delay differential equations process is accurate and efficient. Numerical example is explained and analyzed involved first order linear fuzzy delay differential equations to demonstrate these proper features of this proposed problem.
Identification of interstitial lung diseases using deep learning Nidhin Raju; Anita H. B.; Peter Augustine
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v10i6.pp6283-6291

Abstract

The advanced medical imaging provides various advantages to both the patients and the healthcare providers. Medical Imaging truly helps the doctor to determine the inconveniences in a human body and empowers them to make better choices. Deep learning has an important role in the medical field especially for medical image analysis today. It is an advanced technique in the machine learning concept which can be used to get efficient output than using any other previous techniques. In the anticipated work deep learning is used to find the presence of interstitial lung diseases (ILD) by analyzing high-resolution computed tomography (HRCT) images and identifying the ILD category. The efficiency of the diagnosis of ILD through clinical history is less than 20%. Currently, an open chest biopsy is the best way of confirming the presence of ILD. HRCT images can be used effectively to avoid open chest biopsy and improve accuracy. In this proposed work multi-label classification is done for 17 different categories of ILD. The average accuracy of 95% is obtained by extracting features with the help of a convolutional neural network (CNN) architecture called SmallerVGGNet.
A generalized switching function-based SVM algorithm of single-phase three-leg converter with active power decoupling Watcharin Srirattanawichaikul
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v10i6.pp6189-6201

Abstract

In this paper, a generalized switching function-based space vector modulation (SVM) algorithm is presented and evaluated to minimize the dc voltage utilization and the ac utility grid current total harmonic distortion. This paper explores the control and modulation techniques of a single-phase three-leg converter with an active power decoupling method, where a generalized SVM algorithm is proposed and evaluated for easy implementation in a digital control platform. The active power decoupling method with the proposed converter can be achieved via dependent control and modulation techniques. The control method is separated into the ac active power control part and the dc power ripple control part, which can maintain a unity power factor at the ac utility grid and reduced the double-frequency ripple power effect on the dc-side. Simulation results validate the performance of the modulation algorithm and its control and demonstrate the feasibility of the proposed power converter, as well as the two mentioned operation modes of the power converter.

Page 312 of 640 | Total Record : 6393

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