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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 112 Documents
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Search results for , issue "Vol 12, No 5: October 2022" : 112 Documents clear
Effective electroencephalogram based epileptic seizure detection using support vector machine and statistical moment’s features Akeel Abdulkareem Alsakaa; Mohsin Hasan Hussein; Zaid Hasan Nasralla; Hazim Alsaqaa; Kesra Nermend; Anna Borawska
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5204-5213

Abstract

Epilepsy is one of the widespread disorders. It is a noncommunicable disease that affects the human nerve system. Seizures are abnormal patterns of behavior in the electricity of the brain which produce symptoms like losing consciousness, attention or convulsions in the whole body. This paper demonstrates an effective electroencephalogram (EEG) based seizure detection method using discrete wavelet transformation (DWT) for signal decomposition to extract features. An automatic channel selection method was proposed by the researcher to select the best channel from 23 channels based on maximum variance value. The records were segmented into a nonoverlapping segment with long 1-S. The support vector machine (SVM) model was used to automatically detect segments that contain seizures, using both frequency and time domain statistical moment features. The experimental result was obtained from 24 patients in CHB-MIT database. The average accuracy is 94.1, sensitivity is 93.5, specificity is 94.6 and the false positive rate average is 0.054.
Field programmable gate array implementation of multiwavelet transform based orthogonal frequency division multiplexing system Suha Qasim Hadi; Awatif Ali Jafaar; Ban Mohammed Alameri; Sarah Ameer Malallah
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5136-5144

Abstract

This article offers an efficient design and implementation of a discrete multiwavelet critical-sampling transform based orthogonal frequency division multiplexing (DMWCST-OFDM) transceiver using field programmable gate array (FPGA) platform. The design uses 16-point discrete multiwavelet critical-sampling transform (DMWCST) and its inverse as main processing modules. All modules were designed using a part of Vivado® Design Suite version (2015.2), which is Xilinx system generator (XSG), and is compatible with MATLAB Simulink version R2013b. The FPGA implementation is carried out on a Zynq (XC7Z020-1CLG484) evaluation board with joint test action group (JTAG) hardware co-simulation. According to the results obtained from the implementation tools, the implemented system is efficient in terms of resource utilization and could support the real-time operations.
Performance analysis in text clustering using k-means and k-medoids algorithms for Malay crime documents Rosmayati Mohemad; Nazratul Naziah Mohd Muhait; Noor Maizura Mohamad Noor; Zulaiha Ali Othman
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5014-5026

Abstract

Few studies on text clustering for the Malay language have been conducted due to some limitations that need to be addressed. The purpose of this article is to compare the two clustering algorithms of k-means and k-medoids using Euclidean distance similarity to determine which method is the best for clustering documents. Both algorithms are applied to 1000 documents pertaining to housebreaking crimes involving a variety of different modus operandi. Comparability results indicate that the k-means algorithm performed the best at clustering the relevant documents, with a 78% accuracy rate. K-means clustering also achieves the best performance for cluster evaluation when comparing the average within-cluster distance to the k-medoids algorithm. However, k-medoids perform exceptionally well on the Davis Bouldin index (DBI). Furthermore, the accuracy of k-means is dependent on the number of initial clusters, where the appropriate cluster number can be determined using the elbow method.
Electrocardiograph signal recognition using wavelet transform based on optimized neural network Ali Talib Jawad; Dalael Saad Abdul-Zahra; Hassan Muwafaq Gheni; Ali Najim Abdullah
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4944-4950

Abstract

Due to the growing number of cardiac patients, an automatic detection that detects various heart abnormalities has been developed to relieve and share physicians’ workload. Many of the depolarization of ventricles complex waves (QRS) detection algorithms with multiple properties have recently been presented; nevertheless, real-time implementations in low-cost systems remain a challenge due to limited hardware resources. The proposed algorithm finds a solution for the delay in processing by minimizing the input vector’s dimension and, as a result, the classifier’s complexity. In this paper, the wavelet transform is employed for feature extraction. The optimized neural network is used for classification with 8-classes for the electrocardiogram (ECG) signal this data is taken from two ECG signals (ST-T and MIT-BIH database). The wavelet transform coefficients are used for the artificial neural network’s training process and optimized by using the invasive weed optimization (IWO) algorithm. The suggested system has a sensitivity of over 70%, a specificity of over 94%, a positive predictive of over 65%, a negative predictive of more than 93%, and a classification accuracy of more than 80%. The performance of the classifier improves when the number of neurons in the hidden layer is increased.
Challenges and perspectives of the use of photovoltaic solar energy in Colombia Christian Manuel Moreno Rocha; Celene Milanés Batista; Willian Fernando Arguello Rodríguez; Arley Jesús Fontalvo Ballesteros; José Ricardo Núñez Álvarez
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4521-4528

Abstract

This article quantifies the development of photovoltaic solar energy in Colombia and its current development prospects. The high demand for electricity in Colombia is increasing since there is a large population, industrial, and business increase, which brings a higher energy consumption and consequently economic, social, and environmental problems. Faced with this situation, a possible solution is proposed, using solar energy, to supply the increase in demand and mitigate the problems caused by current electricity generation because Colombia has high levels of solar radiation in almost the entire territory. The objective of this research is based on the analysis of the behavior of the projects on photovoltaic solar systems presented to the mining-energy planning unit (UPME) in the last 14 years until September 30, 2020, as well such as the study of the areas with the most effective implementation of this technology and their respective radiation indices. In addition, a synthesis is made of the regulations, laws, and tax incentives that exist for the implementation of this technology and the different stages of execution of the projects approved and in performance.
Super resolution image reconstruction via dual dictionary learning in sparse environment Shashi Kiran Seetharamaswamy; Suresh Kaggere Veeranna
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4970-4977

Abstract

Patch-based super resolution is a method in which spatial features from a low-resolution (LR) patch are used as references for the reconstruction of high-resolution (HR) image patches. Sparse representation for each patch is extracted. These coefficients obtained are used to recover HR patch. One dictionary is trained for LR image patches, and another dictionary is trained for HR image patches and both dictionaries are jointly trained. In the proposed method, high frequency (HF) details required are treated as combination of main high frequency (MHF) and residual high frequency (RHF). Hence, dual-dictionary learning is proposed for main dictionary learning and residual dictionary learning. This is required to recover MHF and RHF respectively for recovering finer image details. Experiments are carried out to test the proposed technique on different test images. The results illustrate the efficacy of the proposed algorithm.
Towards enhancing the user experience of ChIP-Seq data analysis web tools Mahmoud Hammad; Qanita Bani Baker; Mohammed Al-Smadi; Wesam Alrashdan
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5236-5247

Abstract

Deoxyribonucleic acid (DNA) sequencing is the process of locating the sequence of the main chemical bases in the DNA. Next-generation sequencing (NGS) is the state-of-the-art DNA sequencing technique. The NGS technique advanced the biological science in analyzing human DNA due to its scalability, high throughput, and speed. Analyzing human DNA is crucial to determine the ability of a person to develop certain diseases and his ability to respond to certain medications. ChIP-sequencing is a method that combines chromatin immunoprecipitation (ChIP) with NGS sequencing to analyze protein interactions with DNA to identify binding sites. Many online web tools have been developed to conduct ChIP-Seq data analysis to either discover or find motifs, i.e., patterns of binding sites. Since these ChIP-Seq web tools need to be used by clinical practitioners, they must comply to the web-related usability tasks including effectiveness, efficiency and satisfaction to enhance the user experience (UX). To that end, we have conducted an empirical study to understand their UX design. Specifically, we have evaluated the usability of 8 widely used ChIP-Seq web tools against 6 known usability quality metrics. Our study shows that the design of the studied ChIP-Seq web tools does not follow the UX design principles.
Two-stage parametric identification procedure to predict satellite orbital motion Oksana Sergeevna Chernikova; Yuliya Sergeevna Chetvertakova
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5348-5354

Abstract

The paper presents a new step-by-step procedure for constructing a navigation satellite motion model. At the first stage of the procedure, the parameters of the radiation pressure model are estimated using the maximum likelihood method. The statistic estimator based on the continuous-discrete adaptive unscented Kalman filter is proposed for the solar radiation model parameters estimation. Step-by-step scheme of filtering algorithm used for the software development are given. At the second stage, the parameters of the unaccounted perturbations model are estimated based on the results of residual differences measurements. The obtained results lead to significant improvement of prediction quality of the satellite trajectory.
Extraction of photovoltaic generator parameters through combination of an analytical and iterative approach Abdelaaziz Benahmida; Noureddine Maouhoub; Kawtar Tifidat; Hassan Sahsah
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4529-4537

Abstract

In the present work, we propose an improved method based on a combination of an analytical and iterative approach to extract the photovoltaic (PV) module parameters using the measured current-voltage characteristics and the simple diode model. First, we calculate the series resistance using a set of analytical formulas for the base values of the three current-voltage curves. Then, the three other parameters are analytically expressed as functions of serial resistance and ideality factor based on the linear least-squares method. Finally, the ideality factor is calculated applying an iterative algorithm to minimize the normalized root mean square error (NRMSE) value. The proposed method was validated with a real experimental set of two PV generators, which showed the best fit to the I-V curve. Moreover, the proposed method needs only the initial value of the ideality factor.
MATLAB/Simulink modeling of electric motors operating with harmonics and unbalance Adrián Bolaño Martínez; Isaac Jimenez Navarro; Vladimir Sousa Santos; Enrique Ciro Quispe; Pablo Daniel Donolo
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4640-4648

Abstract

This paper aims to present a simulation model for the analysis of the operational characteristics of electric motors (EMs). The model was developed on the Simulink platform of the MATLAB program and allows analysis in supply conditions with harmonics and voltage unbalance. The contribution of the model is that it considers the mechanical losses and provides for the study of the effect of each component of the electrical sequence of the harmonics and the voltage unbalance on the electromechanical characteristics of the EM. The model developed was tested in a 37.3 kW EM, operating under four power supply conditions: balanced sinusoidal voltages, balanced non-sinusoidal voltages (i.e., harmonics), unbalanced sinusoidal voltages, and non-sinusoidal unbalanced voltages. The results showed that under the conditions of harmonics and unbalance, the efficiency was reduced by 2%, respectively and that with the combined effects, the efficiency decreased by 4%. The results made it possible to quantify, from the current, voltage, and electrical power values of each sequence, the adverse effects caused by voltage unbalance and harmonics.

Page 11 of 12 | Total Record : 112

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