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International Journal of Electrical and Computer Engineering
ISSN : 20888708     EISSN : 27222578     DOI : -
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.
Articles 111 Documents
Search results for , issue "Vol 14, No 5: October 2024" : 111 Documents clear
Effect of Na-EDTA on electrical characteristics NaCl electrolyte battery charging solar panels Maizana, Dina; Mungkin, Moranain; Satria, Habib; Syafii, Syafii; Siregar, Muhammad Fadlan
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.pp4846-4855

Abstract

This research investigates the problem of Cu-Zn electrode batteries with NaCl electrolyte. Previous studies have indicated problems with the electrolyte and electrodes after charging, such as turbidity and deposits in the electrolyte, as well as corrosion on the electrodes. Consequently, the battery can only be used once due to a decline in its electrical characteristics after the initial charging. Through this research, improvements were made to the electrical characteristics of the battery by adding Na-EDTA to enhance usage efficiency. The research method involved mixing NaCl solution with the highest electrical conductivity, using six pairs of Cu-Zn electrodes arranged in series. The physical conditions of the electrolyte and electrodes were observed, and electrical characteristics were measured. The research results indicate that the use of NaCl+Na-EDTA electrolyte produces a battery voltage of 4.20 volts with a current of 2 Ah and can be used twice. Charging with solar panels can be done in 1 hour, but the frequency is limited to two times.
Detection and classification of breast cancer types using VGG16 and ResNet50 deep learning techniques P., Ashwini; N., Suguna; N., Vadivelan
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.pp5481-5488

Abstract

Breast cancer has become a major worldwide health issue, accounting for a large portion of the mortality rate among women. As a result, the need for early detection techniques to enhance prognosis is increasing. Many techniques are being used to detect breast cancer early, and treatment outcomes are frequently favorable when the disease is detected early. Mammography is a commonly used and very successful method for identifying breast cancer among these modalities. Through additional image processing operations like resizing and normalizing, this technology allows the detection of malignant spots from mammography pictures of the affected area. The goal of our research is to improve breast cancer detection and diagnosis speed and accuracy. In this study, we investigate the use of deep learning methods, particularly the visual geometry group (VGG16) and ResNet50 models, for mammography-based breast cancer detection. We assess the performance of the VGG16 and ResNet50 models by training and testing on a mammogram dataset that consists of 322 images from the mammographic image analysis society (MIAS) dataset. The suggested models aim to classify these images into normal, benign, and malignant groupings. Our results show better performance when compared to existing approaches. The proposed methods VGG16 and ResNet50 show promising results, achieving a classification accuracy of 91.23% and 99.01% respectively.
Mechatronic system to classify plastic and metal bottles using capacitive and inductive sensors Melo, Napoly; Gonzales, Abigail Sanchez; Paiva-Peredo, Ernesto
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.pp4970-4976

Abstract

The problem addressed in this article focuses on the management of plastic waste, which has experienced a significant increase in recent years, posing challenges in its management and recycling. In addition, the concentration of microplastics in water and their impact on health and the food chain is highlighted. The proposed solution consists of developing a mechatronic system for sorting plastic and metal bottles using capacitive and inductive sensors, respectively. The system demonstrated efficiency in tests, achieving 100% sorting for plastic and metal bottles. The need for bottles to be properly positioned for optimal performance was identified. This work highlights the importance of automation in mechatronic systems and the effectiveness of capacitive and inductive sensors in sorting materials.
Assessing power quality in individual circuits of industrial electrical system Angarita, Eliana Noriega; Santos, Vladimir Sousa; Donolo, Pablo Daniel; Quispe, Enrique Ciro
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.pp4888-4896

Abstract

This article evaluates energy quality in individual circuits within an industrial electrical system and its impact on common connection point parameters. The research is crucial due to rising challenges in power quality arising from increased nonlinear electrical loads in industrial processes. The study involves sequential steps, covering the industrial electrical system´s description, power quality parameters analysis, and issue identification. A comprehensive assessment was conducted on a 3,000 kVA, 13.8 kV/460 V point of common coupling (PCC) transformer, and 10 transformers (10 to 250 kVA) supplying individual circuits. Findings indicated load factors below 70% in all transformers and a power factor below 0.9 in eight. Issues like voltage variation, current imbalance, and harmonic distortion were identified in nine transformers supplying individual circuits, while the PCC exhibited no power quality problems. The research emphasizes the importance of including individual circuits in power quality assessments, as compliance with regulatory limits at the PCC may not guarantee the absence of power quality issues in individual circuits, affecting equipment lifespan and increasing energy losses.
The feasibility of processing waste from religious ceremonies in Bali as clean energy Nugraha, I Made Aditya; Desnanjaya, I Gusti Made Ngurah
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.pp4921-4928

Abstract

Bali is one of the islands with the largest Hindu religion in Indonesia. This is of course an attraction for tourists to see the culture and natural beauty that the island of Bali has to offer. However, apart from that, there are many religious activities that occur on the island of Bali and the waste produced is something that needs special attention. If this waste is not handled properly, it will threaten environmental sustainability in Bali and indirectly the tourism offered. Therefore, there is a need for a solution to overcome the waste problem. By conducting observations, interviews and literature studies, a way to overcome this problem was found, namely by converting the waste into aromatherapy incense, vermicomposting, briquettes and biofuel. The results of this processing have been studied and of course have the potential to be carried out on the island of Bali. The application of this method also indirectly plays an important role in preserving the environment and economy on the island of Bali.
Optimizing electric vehicle charging station placement integrates distributed generations and network reconfiguration Bukit, Ferry Rahmat Astianta; Zulkarnain, Hendra; Kusuma, Choirul Purnama
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.pp4929-4939

Abstract

The surge in adoption of electric vehicles (EVs) within the transportation sector can be attributed to the growing interest in sustainable transportation initiatives. It is imperative to position electric vehicle charging stations (EVCS) strategically and distribute generations (DGs) to mitigate the effects of electric vehicle loads. This research employs the whale optimization algorithm (WOA) to optimize the placement of EVCS and DGs alongside network reconfiguration. The backward-forward sweep (BFS) power flow technique is utilized to compute load flow under varying load conditions. The primary objective of this investigation is to minimize power losses and enhance the voltage profile within the system. The proposed approach was tested on IEEE-33 and 69 bus systems and compared with particle swarm optimization (PSO) and genetic algorithm (GA) techniques. The simulation outcomes affirm the effectiveness of whale optimization algorithm in determining that integrating 3 EVCS with 3 DGs yields optimal outcomes following network reconfiguration, resulting in a 56.22% decrease in power losses for the IEEE-33 bus system and a 76.13% reduction for the IEEE-69 bus system. The simulation results indicate that the proposed approach enhances system performance across all metrics, showcasing the superior performance of WOA compared to PSO and GA in accomplishing set objectives.
Dual soft decoding of linear block codes using memetic algorithm Sliman, Rajaa; Azouaoui, Ahmed
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.pp5263-5273

Abstract

In this article we will approach the soft-decision decoding for the linear block codes, is a kind of decoding algorithms used to decode data to form better original estimated received message, it is considered as a NP-hard problem. In this article we present a new decoder using memetic algorithm such metaheuristic technic operates on the dual code rather than the code itself that aims to find the error caused when sending a codeword calculated from a message of k bits of information, the resulting codeword contains n bits, including the redundancy bits, the efficiency of an error-correcting code is equivalent to the ratio k/n, the rate is belong the interval [0,1]. Hence a good code is the one that ensures a certain error correcting capability at minimum ratio. The results proved that this approach using a combination of genetic algorithm and local search algorithm provides a sufficiently good solution to an optimization problem; the new decoder is applied on linear codes where the structure is given by a parity check matrix.
Performance evaluation of single-mode fiber optic-based surface plasmon resonance sensor on material and geometrical parameters Tazi, Imam; Riana, Dedi; Syahadi, Mohamad; Muthmainnah, Muthmainnah; Sasmitaninghidayah, Wiwis; Aprilia, Lia; Tresna, Wildan Panji
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.pp5072-5082

Abstract

Surface plasmon resonance (SPR) sensors are proficient at detecting minute changes in refractive index, making them ideal for biomolecule detection. Traditional prism-based SPR sensors encounter miniaturization challenges, encouraging exploration of alternatives like fiber optic-based SPR (FO-SPR) sensors. This study comprehensively investigates the effects of material and geometrical parameters on the performance of single-mode FO-SPR sensors using Maxwell's equation solver software based on the finite-difference time-domain (FDTD) method. The findings highlight the influence of plasmonic thin film materials and thickness on SPR spectrum profiles and sensitivity. Silver (Ag) demonstrates superior performance compared to copper (Cu) and gold (Au) in transmission type, achieving a sensitivity of up to 2×103 nm/RIU, while the sensitivities of Cu and Au are lower. Probe length and core diameter impact spectrum profiles, specifically resonance depth, without affecting sensitivity. Furthermore, variations in core refractive index influence both spectrum profiles and sensitivity. Probe types significantly affect both spectrum profiles and sensitivity, with the reflection type surpassing the transmission type. These results provide suggestions for optimizing FO-SPR sensors in biotechnological applications.
Rotor angle deviation regulator to enhance the rotor angle stability of synchronous generators Murad, Nor Syaza Farhana Mohamad; Kamarudin, Muhammad Nizam; Zakaria, Muhammad Iqbal
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.pp4879-4887

Abstract

Occurrences of disturbance affect the rotor angle operation of a synchronous generator in the generation system of a power system. The disturbance will disrupt the synchronous generator's rotor oscillation and result in rotor angle instability, which will degrade the power system's performance. This paper aims to develop a Lyapunov-based rotor angle deviation regulator for the nonlinear swing equation of a synchronous generator. The proposed regulator is expected to assure asymptotic stability of the rotor angle and robustness to uncertainty. Backstepping and Lyapunov redesign techniques are employed in developing the regulator. To validate the effectiveness and robustness of the regulator, a simulation in MATLAB/Simulink is carried out. The simulation result shows that the asymptotic stability and robustness of the regulator are guaranteed regardless of the disturbance.
Optimizing intrusion detection in 5G networks using dimensionality reduction techniques Salah, Zaher; Elsoud, Esraa; Al-Sit, Waleed; Alhenawi, Esraa; Alshraiedeh, Fuad; Alshdaifat, Nawaf
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.pp5652-5671

Abstract

The proliferation of internet of things (IoT) technologies has expanded the user base of the internet, but it has also exposed users to increased cyber threats. Intrusion detection systems (IDSs) play a vital role in safeguarding against cybercrimes by enabling early threat response. This research uniquely centers on the critical dimensionality aspects of wireless datasets. This study focuses on the intricate interplay between feature dimensionality and intrusion detection systems. We rely on the renowned IEEE 802.11 security-oriented AWID3 dataset to implement our experiments since AWID was the first dataset created from wireless network traffic and has been developed into AWID3 by capturing and studying traces of a wide variety of attacks sent into the IEEE 802.1X extensible authentication protocol (EAP) environment. This research unfolds in three distinct phases, each strategically designed to enhance the efficacy of our framework, using multi-nominal class, multi-numeric class, and binary class. The best accuracy achieved was 99% in the three phases, while the lowest accuracy was 89.1%, 60%, and 86.7% for the three phases consecutively. These results offer a comprehensive understanding of the intricate relationship between wireless dataset dimensionality and intrusion detection effectiveness.

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