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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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A significant features vector for internet traffic classification based on multi-features selection techniques and ranker, voting filters Munther, Alhamza; Abualhaj, Mosleh M.; Alalousi, Alabass; Fadhil, Hilal A.
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6958-6968

Abstract

The pursuit of effective models with high detection accuracy has sparked great interest in anomaly detection of internet traffic. The issue still lies in creating a trustworthy and effective anomaly detection system that can handle massive data volumes and patterns that change in real-time. The detection techniques used, especially the feature selection methods and machine learning algorithms, are crucial to the design of such a system. The fundamental difficulty in feature selection is selecting a smaller subset of features that are more related to the class but are less numerous. To reduce the dimensionality of the dataset, this research offered a multi-feature selection technique (MFST) using four filter techniques: fast correlation-based filter, significance feature evaluator, chi-square, and gain ratio. Each technique's output vector is put via ranker and Borda voting filters. The feature with the highest number of votes and rank values will be selected from the dataset. The performance of the given MFST framework was the best when compared to the four strategies listed above functioning alone; three different classifiers were employed to test the accuracy. C4.5, nave Bayes, and support vector machine. The experiment outcomes employed ten datasets of different sizes with 10,000-300,000 instances. Only 8 out of 248 characteristics were chosen, with classifiers percentages averaging 65%, 93.8%, and 95.5%.
Experimental and simulation analysis for insulation deterioration and partial discharge currents in nanocomposites of power cables Thabet, Ahmed; Fouad, Mohamed
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp1194-1202

Abstract

Partial discharge (PD) has a well-established relationship with the lifespan of power cables. This paper has been treated the polyvinyl chloride (PVC) with specified nanoparticles for enhancing dielectric degradation and reducing partial discharge current to extending lifespan of power cables. It has been succeeded to creation new polyvinyl chloride nanocomposites that have been synthesized experimentally via using solution-gel (SOL-GEL) technique and have high featured electric and dielectric properties. The validation of nanoparticles penetration inside polyvinyl chloride during synthesis process have been constructed and tested via scanning electron microscope (SEM) images. The partial discharge current mechanisms in polyvinyl chloride nanocomposites have also been simulated in this work by using MATLAB® software. This paper has explored the characterization of partial discharge current for variant void patterns (air, water, rubber impurity) in polyvinyl chloride nanocomposites insulations of power cables to clarify the benefit of filling different nanoparticles (Clay, MgO, ZnO, and BaTiO3) with varied patterns inside power cables dielectrics. A comparative study has been done for different partial discharges patterns to propose characterization of partial discharges using nanoparticles of appropriate types and concentrations.
Development and assessment of solar radiation forecasting models based on operational data Suwarno, Suwarno; Cahyadi, Catra Indra; Sukarwoto, Sukarwoto; Napitupulu, Janter
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp4838-4845

Abstract

Operational forecasting of solar radiation is critical for better decision-making by solar energy system operators, due to the variability of energy resources and demand. Although the numerical weather forecasting (NWP) model can predict solar radiation variables, there are often significant errors, especially in direct normal irradiation (DNI), which are influenced by the type and concentration of aerosols and clouds. This paper presents an artificial neural network (ANN) based method to generate operational DNI forecasts using weather and aerosol forecast data from the European Center for medium-range weather forecasts (ECMWF) and Copernicus atmospheric monitoring service (CAMS) respectively. The ANN model is designed to predict weather and aerosol variables at a certain time as input, while other models use the DNI forecast improvement period before the instant forecast. The model was developed using North Sumatra location observations and obtained DNI forecasting results every 10 minutes on the first day with DNI forecasting compared to the initial forecasting which was scaled down with the R2, mean absolute error (MAE), and relative mean square error (RMSE) models were 0.6753, 151.2, and 210.2 W/m2, so that and provides good agreement with experimental data.
Evaluation of machine learning and deep learning methods for early detection of internet of things botnets Mashaleh, Ashraf S.; Ibrahim, Noor Farizah; Alauthman, Mohammad; Al-karaki, Jamal; Almomani, Ammar; Atalla, Shadi; Gawanmeh, Amjad
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp4732-4744

Abstract

The internet of things (IoT) represents a rapidly expanding sector within computing, facilitating the interconnection of myriad smart devices autonomously. However, the complex interplay of IoT systems and their interdisciplinary nature has presented novel security concerns (e.g. privacy risks, device vulnerabilities, Botnets). In response, there has been a growing reliance on machine learning and deep learning methodologies to transition from conventional connectivity-centric IoT security paradigms to intelligence-driven security frameworks. This paper undertakes a comprehensive comparative analysis of recent advancements in the creation of IoT botnets. It introduces a novel taxonomy of attacks structured around the attack life-cycle, aiming to enhance the understanding and mitigation of IoT botnet threats. Furthermore, the paper surveys contemporary techniques employed for early-stage detection of IoT botnets, with a primary emphasis on machine learning and deep learning approaches. This elucidates the current landscape of the issue, existing mitigation strategies, and potential avenues for future research.
Internet of things-based digital scale to detect stunting symptoms in babies under two years of age Hutabarat, Daniel Patricko; Wijaya, Willis; Wijaya, Wilbert Devin
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3467-3474

Abstract

Given the ongoing global challenge of stunting, characterized primarily by chronic underweight in infants under two years of age, a new approach leveraging digital scale and the internet of things (IoT) has been developed. This innovative system was designed to facilitate the early detection and continual monitoring of stunting symptoms caused by malnourishment. Key features include an IoT-enabled digital scale for precise weight measurement, a robust cloud platform for reliable data storage and comprehensive analysis, and an easy-to-use mobile app for user engagement. This system demonstrates its potential to simplify tracking fluctuations in baby weight and development progress related to stunting over time. Early trials demonstrated an impressive accuracy rate of 99.4% in body weight measurements and provided excellent conclusions in determining the body weight status of the infants. Overall, this IoT-based solution catalyzes the improvement of stunting detection methodologies and early intervention strategies, thus promising a better solution and a significant positive impact on global child health.
Mobile application for the prevention and self-care of varicose veins Andrade-Arenas, Laberiano; Retuerto, Margarita Giraldo; Yactayo-Arias, Cesar
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6560-6571

Abstract

Details the process of creating a prototype of a mobile application designed to promote prevention and self-care of varicose veins in patients at high vascular risk. The objective is to investigate the experience of patients at high vascular risk when using a mobile application created for the prevention and self-care of varicose veins. The methodology used is design thinking, a user-centered approach that seeks to solve complex challenges through creativity, design and problem solving. The results obtained from the expert judgment, based on ATLAS.ti 23, provide valuable insight into the feasibility and potential of the technological tools as the interface has the highest variability among the criteria evaluated, followed by interaction and quality, while usability presents the lowest variability. This suggests that usability evaluations tend to be more consistent compared to the other criteria. In conclusion, the present work analyzes how mobile applications can play a crucial role in promoting prevention and self-care of varicose veins in patients at high vascular risk. The good reception of the prototype confirms the importance of technology in the field of vascular health and highlights the value of this approach to improve quality of life and health management in this demographic group.
Hardware-in-the-loop setup for enhanced modular multi-level converter with reduced circulating currents Soomro, Jahangeer Badar; Ali, Khawaja Haider; Memon, Abdul Aziz
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp1448-1458

Abstract

Owing to its essential features, such as modularity and exceptional power quality, the modular multilevel converter (MMC) emerges as the optimal converter topology for high-voltage direct current (HVDC) applications. Traditionally, MMCs are controlled through a method called nearest level modulation (NLM), which generates N+1 AC output voltages, where N represents the number of sub modules (SMs) per arm. In this paper, we introduce a modified NLM technique designed to yield 2N+1 and 4N+1 levels, with a focus on efficiently controlling internal dynamics. The proposed MMC is evaluated using a hardware-in-the-loop (HIL) environment to obtain real-time simulation outcomes. This MMC topology demonstrates a reduction in circulating currents and capacitor voltage ripple.
Comparative design of harmonic current reduction in variable speed drive using space vector pulse width modulation and hybrid pulse width modulation Siregar, Yulianta; Situmeang, Farel; Mohamed, Nur Nabila
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp4907-4920

Abstract

In industry and commerce, three-phase induction motors are frequently utilized as the primary power source for machinery. However, to increase motor performance efficiency, induction motors also need a tool for speed control. The variable speed drive (VSD) is one tool used to control the rotation speed of three-phase induction motors. Since VSD is a non-linear load, harmonic distortion will result from it. The space vector pulse width modulation (SVPWM) injection method and the hybrid pulse width modulation method were the two techniques employed by the author in this study to lower the current in the VSD. With the SVPWM injection approach, the variable speed drive's current total harmonic distortion (THD) values in the R, S, and T phases dropped to 3.77%, 3.53%, and 2.19% from 7.14%, 7.17%, and 7.58%.
Encountering distributed denial of service attack utilizing federated software defined network Abdelhadi, Rima; Alsafasfeh, Moath H.; Alqudah, Bilal I.
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp574-588

Abstract

This research defines the distributed denial of service (DDoS) problem in software-defined-networks (SDN) environments. The proposes solution uses Software defined networks capabilities to reduce risk, introduces a collaborative, distributed defense mechanism rather than server-side filtration. Our proposed network detection and prevention agent (NDPA) algorithm negotiates the maximum amount of traffic allowed to be passed to server by reconfiguring network switches and routers to reduce the ports' throughput of the network devices by the specified limit ratio. When the passed traffic is back to normal, NDPA starts network recovery to normal throughput levels, increasing ports' throughput by adding back the limit ratio gradually each time cycle. The simulation results showed that the proposed algorithms successfully detected and prevented a DDoS attack from overwhelming the targeted server. The server was able to coordinate its operations with the SDN controllers through a communication mechanism created specifically for this purpose. The system was also able to determine when the attack was over and utilize traffic engineering to improve the quality of service (QoS). The solution was designed with a sophisticated way and high level of separation of duties between components so it would not be affected by the design aspect of the network architecture.
A new airfield lighting system network architecture Derraa, Amine; Ouaaline, Najat; Nassiri, Boujemaa
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp3607-3615

Abstract

Airport navigation lights are essential for safe night and adverse weatherflying. Airfield ground lighting (AGL) systems providevisual guidanceduring airport operations. These systems use multiple lamps connected inseries with constant current regulators (CCRs) to provide power. Promptdetection and location of failed lamps are critical to airport efficiency andcost savings. Local area network (LAN) communication facilitates lampmonitoring and control, improving system performance and reducingmaintenance costs. Effective transmission media are critical for systemreliability and efficiency. This article presents a new network architecturefor AGL systems that connects lamps and the control system using a newintelligent module; this architecture combines star and bus topologies in ahybrid intranet network. The obtained results show excellent networkingperformances by means oflatency and throughput. This architectureimproves operational efficiency and reduces maintenance for AGL systems.

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