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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 96 Documents
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Search results for , issue "Vol 11, No 3: June 2021" : 96 Documents clear
Contrast-distorted image quality assessment based on curvelet domain features Ismail Taha Ahmed; Chen Soong Der; Baraa Tareq Hammad; Norziana Jamil
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2595-2603

Abstract

Contrast is one of the most popular forms of distortion. Recently, the existing image quality assessment algorithms (IQAs) works focusing on distorted images by compression, noise and blurring. Reduced-reference image quality metric for contrast-changed images (RIQMC) and no reference-image quality assessment (NR-IQA) for contrast-distorted images (NR-IQA-CDI) have been created for CDI. NR-IQA-CDI showed poor performance in two out of three image databases, where the pearson correlation coefficient (PLCC) were only 0.5739 and 0.7623 in TID2013 and CSIQ database, respectively. Spatial domain features are the basis of NR-IQA-CDI architecture. Therefore, in this paper, the spatial domain features are complementary with curvelet domain features, in order to take advantage of the potent properties of the curvelet in extracting information from images such as multiscale and multidirectional. The experimental outcome rely on K-fold cross validation (K ranged 2-10) and statistical test showed that the performance of NR-IQA-CDI rely on curvelet domain features (NR-IQA-CDI-CvT) significantly surpasses those which are rely on five spatial domain features.
Minimize electricity generation cost for large scale wind- thermal systems considering prohibited operating zone and power reserve constraints Phan Nguyen Vinh; Bach Hoang Dinh; Van-Duc Phan; Hung Duc Nguyen; Thang Trung Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp1905-1911

Abstract

Wind power plants (WPs) play a very important role in the power systems because thermal power plants (TPs) suffers from shortcomings of expensive cost and limited fossil fuels. As compared to other renewable energies, WPs are more effective because it can produce electricity all a day from the morning to the evening. Consequently, this paper integrates the optimal power generation of TPs and WPs to absolutely exploit the energy from WPs and reduce the total electricity generation cost of TPs. The target can be reached by employing a proposed method, called one evaluation-based cuckoo search algorithm (OEB-CSA), which is developed from cuckoo search algorithm (CSA). In addition, conventional particle swarm optimization (PSO) is also implemented for comparison. Two test systems with thirty TPs considering prohibited working zone and power reserve constraints are employed. The first system has one wind power plant (WP) while the second one has two WPs. The result comparisons indicate that OEB-CSA can be the best method for the combined systems with WPs and TPs.
Spider monkey optimization routing protocol for wireless sensor networks Ali H. Jabbar; Imad S. Alshawi
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2432-2442

Abstract

Uneven energy consumption (UEC) is latent trouble in wireless sensor networks (WSNs) that feature a multiple motion pattern and a multi-hop routing. UEC often splits the network, reduces network life, and leads to performance degradation. Sometimes, improving energy consumption is more complicated because it does not reduce energy consumption only, but it also extends network life. This makes energy consumption balancing critical to WSN design calling for energy-efficient routing protocols that increase network life. Some energy-saving protocols have been applied to make the energy consumption among all nodes inside the network equilibrate in the expectancy and end power in almost all nodes simultaneously. This work has suggested a protocol of energy-saving routing named spider monkey optimization routing protocol (SMORP), which aims to probe the issue of network life in WSNs. The proposed protocol reduces excessive routing messages that may lead to the wastage of significant energy by recycling frequent information from the source node into the sink. This routing protocol can choose the optimal routing path. That is the preferable node can be chosen from nodes of the candidate in the sending ways by preferring the energy of maximum residual, the minimum traffic load, and the least distance to the sink. Simulation results have proved the effectiveness of the proposed protocol in terms of decreasing end-to-end delay, reducing energy consumption compared to well-known routing protocols.
Geographical queries reformulation using a parallel association rules generator to build spatial taxonomies Omar El Midaoui; Btihal El Ghali; Abderrahim El Qadi; Moulay Driss Rahmani
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2586-2594

Abstract

Geographical queries need a special process of reformulation by information retrieval systems (IRS) due to their specificities and hierarchical structure. This fact is ignored by most of web search engines. In this paper, we propose an automatic approach for building a spatial taxonomy, that models’ the notion of adjacency that will be used in the reformulation of the spatial part of a geographical query. This approach exploits the documents that are in top of the retrieved list when submitting a spatial entity, which is composed of a spatial relation and a noun of a city. Then, a transactional database is constructed, considering each document extracted as a transaction that contains the nouns of the cities sharing the country of the submitted query’s city. The algorithm frequent pattern growth (FP-growth) is applied to this database in his parallel version (parallel FP-growth: PFP) in order to generate association rules, that will form the country’s taxonomy in a Big Data context. Experiments has been conducted on Spark and their results show that query reformulation using the taxonomy constructed based on our proposed approach improves the precision and the effectiveness of the IRS.
Soil moisture index estimation from landsat 8 images for prediction and monitoring landslide occurrences in Ulu Kelang, Selangor, Malaysia Noraisyah Tajudin; Norsuzila Ya'acob; Darmawaty Mohd Ali; Nor Aizam Adnan
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2101-2108

Abstract

Soil moisture is one of the contributing factors that accelerates soil erosion and landslide events due to the increase in pore pressure which eventually reduces the soil strength. For landslide prediction and monitoring purposes, large-scale measurement involves estimating the soil moisture. However, estimation of soil moisture usually involves point-based measurements at a particular site and time, which is difficult to capture the spatial and temporal soil moisture dynamics. This paper presents the estimation of the SMI using Landsat 8 images for prediction and monitoring of landslide events in Ulu Kelang, Selangor. The selected SMI map for dry, moist, and wet seasons are obtained from climatology rainfall analysis over 20-year periods (1998-2017). SMI is assessed based on remote sensing data which are land surface temperature (LST) and normalized difference vegetation index (NDVI) using GIS software. Overall results indicated that rainfall distribution is high during inter-monsoon (IM), followed by northeast monsoon (NEM) and southwest monsoon (SWM) season. High rainfall distribution is a direct contributor towards SMI condition. Results from simulation show that April 2017 is known to have the highest SMI estimation season and selected to be the best SMI mapping parameter to be applied for prediction and monitoring of landslide events.
Clustering using kernel entropy principal component analysis and variable kernel estimator Loubna El Fattahi; El Hassan Sbai
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2109-2119

Abstract

Clustering as unsupervised learning method is the mission of dividing data objects into clusters with common characteristics. In the present paper, we introduce an enhanced technique of the existing EPCA data transformation method. Incorporating the kernel function into the EPCA, the input space can be mapped implicitly into a high-dimensional of feature space. Then, the Shannon’s entropy estimated via the inertia provided by the contribution of every mapped object in data is the key measure to determine the optimal extracted features space. Our proposed method performs very well the clustering algorithm of the fast search of clusters’ centers based on the local densities’ computing. Experimental results disclose that the approach is feasible and efficient on the performance query.
Character attachment in team-based first person shooter game with respect to the role in the combat among Korean young gamers Doo Heon Song; Seunghun Lee
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2393-2398

Abstract

Character attachment have been studied thoroughly from the view of psychology and media researches. In game playing, the player-avatar relationship is a form of character attachment and affects a good game design as well as management systems such as character customizing and in game purchasing policy. In this paper, we investigate such player-avatar relationship on the theme of team-based FPS where in general the attachment is not expected to be high. However, from the online survey for Tom Clancy’s Rainbow 6 Siege mania groups, we find that there are different character attachment patterns with respect to the role of players in the team–attacker, defender, and supporter. It shows that attackers think avatar as an ‘object, but the defenders show more ‘avatar as others’ than the attackers. The supporters show high responsibility for the avatar and their play style is most like ‘avatar as symbiote’ manner.
Hybrid feature selection method based on particle swarm optimization and adaptive local search method Malek Alzaqebah; Sana Jawarneh; Rami Mustafa A. Mohammad; Mutasem K. Alsmadi; Ibrahim Al-marashdeh; Eman A. E. Ahmed; Nashat Alrefai; Fahad A. Alghamdi
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2414-2422

Abstract

Machine learning has been expansively examined with data classification as the most popularly researched subject. The accurateness of prediction is impacted by the data provided to the classification algorithm. Meanwhile, utilizing a large amount of data may incur costs especially in data collection and preprocessing. Studies on feature selection were mainly to establish techniques that can decrease the number of utilized features (attributes) in classification, also using data that generate accurate prediction is important. Hence, a particle swarm optimization (PSO) algorithm is suggested in the current article for selecting the ideal set of features. PSO algorithm showed to be superior in different domains in exploring the search space and local search algorithms are good in exploiting the search regions. Thus, we propose the hybridized PSO algorithm with an adaptive local search technique which works based on the current PSO search state and used for accepting the candidate solution. Having this combination balances the local intensification as well as the global diversification of the searching process. Hence, the suggested algorithm surpasses the original PSO algorithm and other comparable approaches, in terms of performance.
New proposed method for traceability dissemination of capacitance measurements Heba A. M. Hamed; A. Eliwa Gad; M. Helmy A. Raouf
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp1969-1975

Abstract

Capacitance measurements at the National Institute of Standards (NIS), Egypt, are traceable to the Bureau International des Poids et Mesures (BIPM). It calibrates the main NIS standard capacitors, AH11A. In this paper, traceability of the BIPM capacitance measurements could be used to evaluate a new accurate measurement method through an Ultra-Precision Capacitance Bridge. The new method is carefully described by introducing some necessary equations and a demonstrating chart. Verification of this new method has been realized by comparing its results for the 10 pF and 100 pF capacitance standards with the results obtained by the conventional substitution method at 1 kHz and 1.592 kHz. The relative differences between the two methods are about 0.3 µF/F, which reflect the accuracy of the new measurement method. For higher capacitance ranges, the new measurement method has been applied for the capacitance measurements up to 1 μF at 1 kHz. The relative differences between the two methods are in the range of 5.5 µF/F on the average which proves the acceptable accuracy and the reliability of the new method to be used.
New adaptation method based on cross layer and TCP over protocols to improve QoS in mobile ad hoc network Moulay Hicham Hanin; Mohamed Amnai; Youssef Fakhri
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2134-2142

Abstract

Due to rapid growth of multimedia traffic used over the mobile ad-hoc networks (MANETs), to keep up with the progress of this constraints MANETs protocols becoming increasingly concerned with the quality of service. In view of the random mobility nodes in MANET, TCP becomes more unreliability in case of higher energy consumption and packet loss. In this paper we proposed a new optimization approach to enhance decision making of TCP based on some changes of IEEE 802.11 MAC uses cross layer approach. The aim is to minimize the impact of retransmissions of packet lost and energy consumption in order to analysed and chose the appropriate routing protocol for TCP that can be enhance QoS MANET. Our simulation results based QoS study using NS3 show that, our proposed achieves better performance of TCP in MANETs significantly, and also improved the throughput, energy consumption and facilitates the traffic transmission over routing protocol.

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