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International Journal of Electrical and Computer Engineering

IJECE
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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 6,301 Documents

147 148 149 150 151

A Detail Study of Wavelet Families for EMG Pattern Recognition Jingwei Too; A. R. Abdullah; Norhashimah Mohd Saad; N. Mohd Ali; H. Musa
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Wavelet transform (WT) has recently drawn the attention of the researchers due to its potential in electromyography (EMG) recognition system. However, the optimal mother wavelet selection remains a challenge to the application of WT in EMG signal processing. This paper presents a detail study for different mother wavelet function in discrete wavelet transform (DWT) and continuous wavelet transform (CWT). Additionally, the performance of different mother wavelet in DWT and CWT at different decomposition level and scale are also investigated. The mean absolute value (MAV) and wavelength (WL) features are extracted from each CWT and reconstructed DWT wavelet coefficient. A popular machine learning method, support vector machine (SVM) is employed to classify the different types of hand movements. The results showed that the most suitable mother wavelet in CWT are Mexican hat and Symlet 6 at scale 16 and 32, respectively. On the other hand, Symlet 4 and Daubechies 4 at the second decomposition level are found to be the optimal wavelet in DWT. From the analysis, we deduced that Symlet 4 at the second decomposition level in DWT is the most suitable mother wavelet for accurate classification of EMG signals of different hand movements.

Serious Games Adaptation According to the Learner’s Performances Amine Belahbib; Lotfi Elaachak; Mohamed Bouhorma; Othman Bakkali Yedri; Slimani Abdelali; Elouaai Fatiha
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 1: February 2017
Publisher : Institute of Advanced Engineering and Science

Basically, serious games provides enjoyment and knowledge, several researches in this field have focused into joining these two proprieties and make the best balance between them, in order, to provide the best game and enjoyable game experience and ensure the learning of the needed knowledge. Players differ and their knowledge background can be a lot different from one to the other. This study focused on how the SG adapts and provide the needed knowledge and enjoyment. The game should analyze players behavior from different angles, thus it can add difficulty, information, immersion or enjoyment modules to fit the player skills/knowledge.

A hybrid algorithm to size the hospital resources in the case of a massive influx of victims Abderrahmane Ben Kacem; Oualid Kamach; Samir Chafik; Mohamed Ait Hammou
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

Disaster situations either natural or made-man caused a large number of deaths and injured people. Morocco has experienced several disasters recently, the last one was the railway accident on 16 October 2018, which caused 127 serious injuries and 7 deaths. This large number was a big problem for the hospital to manage the received victims in right direction, which caused lives lost and disability. In this article, in collaboration with Mohammed (V) hospital in Casablanca city in Morocco, we suggested a solution that saves lives and eliminates number of disability by using a hybrid algorithm to size the hospital resources in the case of a massive influx of victims. We also suggested a support decision tool that is called Emergency Support Decision Tool. This helpful tool gives an idea about the needed resources that support these emergencies according to the victim’s number. The proposed solution consisted in making a hybrid algorithm that mixed the theoretical simulation process and the experience feedback by developing hybrid genetic and hybrid heuristic algorithms. These algorithms using as an input the matrix solutions that generated under ARENA software and the solution generated by neural networks that based on experiences feedback. The objective was to provide a solution based on available resources. In fact, the results showed that the hybrid heuristic algorithm is more performant than the hybrid genetic algorithm.

Wavelet based Fault Detection Method for Ungrounded Power System with Balanced and Unbalanced load Vishwakumar Revanasiddappa Sheelavant; Vijaya C; S C Shiralashetti
International Journal of Electrical and Computer Engineering (IJECE) Vol 1, No 1: September 2011
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (133.961 KB)

Modern spectral and harmonic analysis is based on Fourier transforms. However, these techniques are less efficient in tracking the signal dynamics for transient disturbances. Consequently, the wavelet transform has been introduced as an adaptable technique for non-stationary signal analysis. Although the application of wavelets in the area of power system engineering is still relatively new, it is evolving very rapidly. In this paper wavelet based method for detection of faults in an ungrounded integrated power system (IPS) of Navy ships is proposed. However the “Virtual ground” exists between the modules of IPS and ship hull, because of insulation capacitance of the cable and the EMI filters between the modules of the IPS. The fault current is very low for a single line to ground fault in this ungrounded system allowing continuous operation but also making fault detection difficult. The proposed method uses wavelets for detection of ground fault in ungrounded power system. The ground fault conditions are simulated using MATLAB-SIMULINK and fault detection implemented with Daubechies wavelets. It is shown that transient ground faults can be detected by wavelet analysis of the line to line voltages when ship load is balanced and unbalanced. Verification of the proposed method has been done by simulating fault between a line and ship hull and analyzing the results.DOI:http://dx.doi.org/10.11591/ijece.v1i1.57

Optimizing Apple Lossless Audio Codec Algorithm using NVIDIA CUDA Architecture Rafid Ahmed; Md. Sazzadul Islam; Jia Uddin
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science

As majority of the compression algorithms are implementations for CPU architecture, the primary focus of our work was to exploit the opportunities of GPU parallelism in audio compression. This paper presents an implementation of Apple Lossless Audio Codec (ALAC) algorithm by using NVIDIA GPUs Compute Unified Device Architecture (CUDA) Framework. The core idea was to identify the areas where data parallelism could be applied and parallel programming model CUDA could be used to execute the identified parallel components on Single Instruction Multiple Thread (SIMT) model of CUDA. The dataset was retrieved from European Broadcasting Union, Sound Quality Assessment Material (SQAM). Faster execution of the algorithm led to execution time reduction when applied to audio coding for large audios. This paper also presents the reduction of power usage due to running the parallel components on GPU. Experimental results reveal that we achieve about 80-90% speedup through CUDA on the identified components over its CPU implementation while saving CPU power consumption.

Diagnosis of Stator Turn-to-Turn Fault and Stator Voltage Unbalance Fault Using ANFIS Sk Moin Ahmed; Haitham Abu-Rub; Shady S. Refaat; Atif Iqbal
International Journal of Electrical and Computer Engineering (IJECE) Vol 3, No 1: February 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (370.329 KB)

An induction machine is a highly non-linear system that poses a great challenge because of its fault diagnosis due to the processing of large and complex data. The fault in an induction machine can lead to excessive downtimes that can lead to huge losses in terms of maintenance and production. This paper discusses the diagnosis of stator winding faults, which is one of the common faults in an induction machine. Several diagnostics techniques have been presented in the literature. Fault detection using traditional analytical methods are not always possible as this requires prior knowledge of the exact motor model. The motor models are also susceptible to inaccuracy due to parameter variations. This paper presents Adaptive Neuro-fuzzy Inference system (ANFIS) based fault diagnosis of induction motors. The distinction between the stator winding fault and supply unbalance is addressed in this paper. Experimental data is collected by shorting the turns of a health motor as well as creating unbalance in the stator voltage. The data is processed and fed to an ANFIS classifier that accurately identifies the faulted condition and unbalanced supply voltage conditions. The ANFIS provides almost 99% accurate and computationally efficient output in diagnosing the faults and unbalance conditions.DOI:http://dx.doi.org/10.11591/ijece.v3i1.1854

Automated segmentation and classification technique for brain stroke N. S. M. Noor; N. M. Saad; A. R. Abdullah; N. M. Ali
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Difussion-Weighted Imaging (DWI) plays an important role in the diagnosis of brain stroke by providing detailed information regarding the soft tissue contrast in the brain organ. Conventionally, the differential diagnosis of brain stroke lesions is performed manually by professional neuroradiologists during a highly subjective and time- consuming process. This study proposes a segmentation and classification technique to detect brain stroke lesions based on diffusion-weighted imaging (DWI). The type of stroke lesions consists of acute ischemic, sub-acute ischemic, chronic ischemic and acute hemorrhage. For segmentation, fuzzy c-Means (FCM) and active contour is proposed to segment the lesion’s region. FCM is implemented with active contour to separate the cerebral spinal fluid (CSF) with the hypointense lesion. Pre-processing is applied to the DWI for image normalization, background removal and image enhancement. The algorithm performance has been evaluated using Jaccard Index, Dice Coefficient (DC) and both false positive rate (FPR) and false negative rate (FNR). The average results for the Jaccard index, DC, FPR and FNR are 0.55, 0.68, 0.23 and 0.23, respectively. First statistical order method is applied to the segmentation result to obtain the features for the classifier input. For classification technique, bagged tree classifier is proposed to classify the type of stroke. The accuracy results for the classification is 90.8%. Based on the results, the proposed technique has potential to segment and classify brain stroke lesion from DWI images.

Using the Fuzzy Logic to Find Optimal Centers of Clusters of K-means Wed Kadhim Oleiwi
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 6: December 2016
Publisher : Institute of Advanced Engineering and Science

Techniques of data mining that used in the medical diagnosis a number of diseases like cancer, diabetes, stroke, and heart disease. The great importance emerging fields for providing diagnosis and a profounder understanding of medical data, its coms from Data mining in medical field .researcher attempts to solve real world health problems in the prognosis and treatment of diseases, by using Healthcare data mining. In this research, the algorithm of k-means is used for grouping medical data, the problem of k-means is to find optimal centers of clusters so, and fuzzy logic is used to get optimal centers of clusters.

Fuzzy n-s-homogeneity and fuzzy weak n-s-homogeneity Samer Al Ghour; Almothana Azaizeh
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

Fuzzy n-s-homogeneity and fuzzy weak n-s-homogeneity are introduced in fuzzy bitopological spaces. Several relationships, characterizations and examples related to them are given.

Improved p-q Harmonic Detection Method for Hybrid Active Power Filter Chau Minh Thuyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

The accuratedetermination of the load harmonic current is one of the important factors, it decides to effect of harmonic filtering and reactive power compensation for Hybrid Active Power Filter. The p-q harmonic detection method has been widely used in determining the harmonic currents of Hybrid Active Power Filter. However, when using this method, the dynamic response of Hybrid Active Power Filter in the transient period will have a large transient time and overshoot whenever the load changes abruptly. Therefore, in this paper an improved p-q harmonic current detection method based on fuzzy logic is proposed, which aims to reduce the overshoot and transient time in transient duration of Hybrid Active Power Filter. In order to compare the dynamic response of conventional and improved p-q harmonic detection methods, simulation results have demonstrated that: the proposed method has a shorter response time, the magnitude of the supply current in the transient time is smaller and the overshoot of the fundamental active and reactive power components is very small. This has a practical significance that contributes to the stability of the Hybrid Active Power Filter system

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Home Page

OAI Link

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Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

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Abstract

Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

Phone
-

Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA