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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 6,301 Documents
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Optimal task partitioning to minimize failure in heterogeneous computational platform Narayana, Divyaprabha Kabbal; Babu, Sudarshan Tekal Subramanyam
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp1079-1088

Abstract

The increased energy consumption by heterogeneous cloud platforms surges the carbon emissions and reduces system reliability, thus, making workload scheduling an extremely challenging process. The dynamic voltage- frequency scaling (DVFS) technique provides an efficient mechanism in improving the energy efficiency of cloud platform; however, employing DVFS reduces reliability and increases the failure rate of resource scheduling. Most of the current workload scheduling methods have failed to optimize the energy and reliability together under a central processing unit - graphical processing unit (CPU-GPU) heterogeneous computing platform; As a result, reducing energy consumption and task failure are prime issues this work aims to address. This work introduces task failure minimization (TFM) through optimal task partitioning (OTP) for workload scheduling in the CPU-GPU cloud computational platform. The TFM-OTP introduces a task partitioning model for the CPU-GPU pair; then, it provides a DVFS- based energy consumption model. Finally, the energy-load optimization problem is defined, and the optimal resource allocation design is presented. The experiment is conducted on two standard workloads namely SIPHT and CyberShake workload. The result shows that the proposed TFA-OTP model reduces energy consumption by 30.35%, reduces makespan by 70.78% and reduces task failure energy overhead by 83.7% in comparison with energy minimized scheduling (EMS) approach.
Evaluating geometrically-approximated principal component analysis vs. classical eigenfaces: a quantitative study using image quality metrics Ennaama, Faouzia; Ennaama, Sara; Chakri, Sana
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp311-318

Abstract

Principal component analysis (PCA) is essential for diminishing the number of dimensions across various fields, preserving data integrity while simplifying complexity. Eigenfaces, a notable application of PCA, illustrates the method's effectiveness in facial recognition. This paper introduces a novel PCA approximation technique based on maximizing distance and compares it with the traditional eigenfaces approach. We employ several image quality metrics including Euclidean distance, mean absolute error (MAE), peak signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR), and structural similarity index measure (SSIM) for a quantitative assessment. Experiments conducted on the Brazilian FEI database reveal significant differences between the approximated and classical eigenfaces. Despite these differences, our approximation method demonstrates superior performance in retrieval and search tasks, offering faster and parallelizable implementation. The results underscore the practical advantages of our approach, particularly in scenarios requiring rapid processing and expansion capabilities.
Enhancing online exam security: encryption and authentication in Jordanian and international universities Al-Ghonmein, Ali M.; Alemami, Yahia; Al-Moghrabi, Khaldun G.; Atiewi, Saleh
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp719-727

Abstract

In today's educational landscape, the online examination system has become crucial, particularly due to the challenges posed by the coronavirus disease 2019 (COVID-19) pandemic. Despite its advantages in expediting result dissemination and reducing resource consumption, online examinations face significant security threats like leakage, cheating, fraud, and hacking, which hinder their widespread adoption. This paper addresses these security concerns by proposing integrating advanced security algorithms and biometric devices. It presents a comprehensive literature review on existing online examination systems, focusing on their security mechanisms, and compares these findings with a proposed framework. Additionally, a questionnaire was administered across Jordanian governmental and private universities to explore strategies for safeguarding computerized tests through encryption and authentication methods. The results reveal that Jordanian institutions lack adequate security safeguards and procedural standards. Key recommendations include encrypting the question bank stored in databases and employing biometric identification techniques to enhance the security and effectiveness of student verification. The proposed framework aims to improve the overall security, speed, and secrecy of the online examination process, addressing the critical gaps identified in current systems. This research contributes to developing more secure and reliable online examination systems in higher education.
Video conferencing algorithms for enhanced access to mental healthcare services in cloud-powered telepsychiatry Senkamalavalli, Rajagopalan; Prasad, Subramaniyan Nesamony Sheela Evangelin; Shobana, Mahalingam; Sri, Chellaiyan Bharathi; Sandiri, Rajendar; Karthik, Jayavarapu; Murugan, Subbiah
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp1142-1151

Abstract

Exploring the video conferencing algorithms for cloud-powered telepsychiatry to improve mental healthcare access. The goal is to evaluate and optimise these algorithms' latency, bandwidth utilisation, packet loss, and jitter across worldwide locations. To provide a smooth and high-quality virtual consultation between patients and mental health providers. Using performance data to identify areas for development, the effort aims to lower technological hurdles and increase telepsychiatry session dependability. Findings will help create strong, efficient algorithms that can handle different network situations, increasing patient outcomes and extending mental healthcare services. In the 1st instance latent analysis in a sample of 5 cities, the average latency (ms) is 45, the peak latency is 120, the off-peak latency is 30, and the packet loss is 0.5. In another instance, bandwidth utilisation in a sample of 5 sessions ranged from 30 to 120 minutes, with data supplied in MB - 150-600 and received in MB - 160-620, with average bandwidth (Mbps) - 5-15 and maximum bandwidth: 10-20.
Robust adaptive integral sliding mode control of a half-bridge bidirectional DC-DC converter Cham, Julius Derghe; Koffi, Francis Lénine Djanna; Boum, Alexandre Teplaira; Harrison, Ambe
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp114-128

Abstract

A novel approach to improving the dynamic response of a half-bridge bidirectional DC-DC converter is presented in this paper, particularly in the face of disturbances from internal or external sources. These converters, which are integral to the operation of DC microgrids, are responsible for stepping up or stepping down voltage as required. To optimize the converter's performance under varying conditions, we propose an adaptive integral sliding mode controller (AISMC) enhanced by particle swarm optimization (PSO). The proposed controller leverages the strengths of both super-twisting sliding mode control (STSMC) and adaptive control, providing a robust and responsive solution to the challenges posed by the converter's nonlinear dynamics. The system's stability is rigorously ensured through the application of Lyapunov stability criteria, which underpin the enhanced performance of the controller. Simulations conducted in the MATLAB/Simulink environment demonstrate that the AISMC-PSO outperforms conventional control strategies, offering superior stability, robustness, and precision. The results clearly indicate that the proposed approach minimizes errors and enhances the overall efficiency and reliability of the bidirectional half-bridge DC-DC converter, making it a highly effective solution for DC microgrid applications.
Denigration analysis of Twitter data using cyclic learning rate based long short-term memory Rajendra, Suhas Bharadwaj; Kuzhalvaimozhi, Sampath; Prasad, Vedavathi Nagendra
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp700-710

Abstract

Technological innovation has given rise to a new form of bullying, often leading to significant harm to one's reputation within social circles. When a single person becomes target to animosity and harassment in a cyberbullying incident, it is termed as denigration. Many different cyberbullying detection techniques are carried out to counter this, concentrating on word-based data and user account features only. The main objective of this research is to enhance the learning rate of long short-term memory (LSTM) using cyclic learning rate (CLR). Therefore, in this research, cyberbullying in social media is detected by developing a framework based on LSTM-CLR which is more stable for enhancing classification accuracy without the need for multiple trials and modifications. The effectiveness of the suggested LSTM-CLR is assessed for identifying cyberbullying using Twitter data. The attained results show that the proposed LSTM-CLR obtains 82% accuracy, 80% precision, 83% recall and 81% F-measure in the classification of cyberbullying tweets, which is superior when compared with the existing multilayer perceptron (MLP) and bidirectional encoder representations from transformers (BERT) models.
Towards optimal fillet portioning: a computer vision system for determining the fish fillet volume Nguyen, Chanh-Nghiem; Vo, Ngọc-Tan; Nguyen, Ngoc-Thanh; Tran, Nhut-Thanh; Nguyen, Chi-Ngon
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp550-558

Abstract

Portioning large fish fillets for packaging is usually performed manually by skilled workers. Automating this process and obtaining packaged products with attractive shapes and affordable weights will be beneficial for promoting purchase decisions. Towards developing an automated fish fillet portioning system, this study investigated a computer vision approach for determining the fillet volume. A belt conveyor would transport a fish fillet to the image capture booth, where its cross-section areas would be calculated for volume determination. The developed system could be operated with a conveyor speed ranging from 7.5 to 30.6 mm/s. The system performance was evaluated at a conveyor speed of 7.5 mm/s using small catfish fillets from 142.2 to 225.4 cm3. A mean percent error of 9.2% was observed, and the smallest percent error of 3.8% was obtained with a 225.4 cm3 fillet. With minor measurement errors obtained for larger fillets, the proposed computer vision system showed great potential for developing a cost-effective automated system for customized fish fillet partitioning to accelerate purchase decisions and also for quality control and classification of the fish fillets.
Modeling of Glugur Substation grounding systems using MATLAB graphical user interface Roza, Indra; Nugraha, Yoga Tri; Rida, Rizkha; Irwanto, Muhammad; Othman, Mohd. Azlishah
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp15-23

Abstract

The grounding system in substations generally uses electrode rods, because electrodes can affect the effectiveness of fault current conduction, so the equipment will be safer. Considering the importance of the grounding system, the installed grounding system must be considered and maintained properly. One of them is the grounding found in Glugur. The main objective of this research is to comprehensively evaluate the substation grounding system by modeling the grounding system at the Glugur Substation using MATLAB graphical user interface (GUI). The grounding resistance follows a grid system with an area of 20×15=300 m² with specific resistance being clay using 100 rod electrodes. From the results of ground resistance simulation modeling using MATLAB GUI, it can be concluded as follows: for a certain resistance value, the number of electrodes for 100 Ωm is 3.55 Ω, for ground resistance with a constant depth and a varying number of 100 electrodes, it is 3.45 Ω, and for. The grounding resistance with a constant and varying number of 1,000 rods is obtained at 2.65 Ω. From these results, the modeling carried out is in accordance with the standards of electricity regulations in Indonesia.
Wireless sensor networks based efficient drip irrigation monitoring systems Ashok, Karthik Sagar; Nagendrappa, Basavaraj Gangasamudra; Anjaneyalu, Mohan Bangalore; Nandihal, Priya; Reddy, Veena Narayana; Syed, Liyakathunisa; Noor, Ayman
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp677-688

Abstract

Cotton has profound significance in the textile industry due to its versatility, comfort and ease of care. But the main problem with conventional cotton farming is that it uses more water. These issues are made more difficult by conventional irrigation methods, such as drip irrigation. To address this problem researchers are using traditional farming techniques with advanced wireless sensor network (WSN) protocols to resolve catastrophic issues, such as pipe bursts or blocked emitters which are detected early to save the water. This paper introduces efficient WSN architecture using priority-based directed information sharing (DIS) protocol for efficient utilization of water. The proposed architecture was implemented using TinyOS sensor network (TOSSIM) simulators. Exceptional quality of service (QoS) is achieved using new routing protocol exclusively for catastrophic failures. The proposed architecture is compared with standard protocols such as topology geographic greedy forwarding (TPGF), link carrier sense avoidance (LinkCSA) and tiny carrier sense avoidance (TinyCSA). Due to implementation optimized priority, DIS latency has been reduced from 11.3% to 11.02% and packet delivery ratio (PDR) is enhanced by 35% to 78% concerning benchmark protocols. The experimental results proves drastic improvement in PDR and delay performance as compared to the existing WSN protocol.
Enhancing routing efficiency in highway environments of vehicular ad hoc networks through fuzzy logic-based protocols Al Shugran, Mahmoud A.; Abu-Al-Aish, Ahmad; Jaradat, Ghaith M.; Alghamdi, Fahad Ali; Alqurni, Jehad Saad; Alsmadi, Mutasem Khalil; AL Hawamdeh, Majd; Alfagham, Hayat; Badawi, Usama A.; Gharaibeh, Mutaz Falah
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp493-504

Abstract

The predictive directional greedy routing (PDGR) protocol is widely utilized in highway settings within vehicular ad hoc networks (VANETs). However, PDGR encounters a notable challenge when packets lack a suitable vehicle directionally, leading to network disconnections. This triggers a shift to carry and forward recovery mode due to outdated neighbor information in the vehicle's neighbor table (VNT). To address this, our study proposes an improved fuzzy logic-based improved PDGR (IPDGR). This novel algorithm dynamically adjusts beaconing intervals based on real-time network dynamics. Through comprehensive evaluation using VANET simulators, IPDGR demonstrates superior performance compared to PDGR and directional greedy routing (DGR) protocols across various metrics including Inconsistency of vehicle's neighbor's table (IVNT), packet delivery ratio (PDR), routing path length (RPL), and number of hole problem occurrence (NHPO).

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