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Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 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. The journal publishes original papers in the field of electrical, computer and informatics engineering.
Arjuna Subject : -
Articles 2,901 Documents
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Effect of proton radiation on gallium nitride light emitting diodes Baba, Tamana; Husni, Muhammad Hazeeq; Saidin, Norazlina; Hasbullah, Nurul Fadzlin
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.6205

Abstract

The compound semiconductor gallium nitride offers enormous potential for facilitating economic expansion in the silicon-based semiconductor industry, which is currently seeing decreasing performance returns compared to investment costs. Its high electron mobility and electric field strength at the material level have already demonstrated enormous potential for photonics and high-frequency communications applications. However, its application in devices used in the radiation-prone environment is hindered by degradation and failure caused by the radiation. In this paper, the effect of proton radiation on the electrical properties of InGaN light emitting diodes (LEDs) for the fluence range of 1×1014 cm-2 to 3×1014 cm-2 is performed. On comparing the results before and after radiation, it is found that radiation mainly affected the reverse IV characteristics of the device with little or no effect on forward IV or CV characteristics. Apart from the electric properties, the optical properties of the LEDs show improvement after radiation as the light intensity increases post-irradiation.
Mathematics for 2D face recognition from real time image data set using deep learning techniques G. N., Ambika; Suresh, Yeresime
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.5424

Abstract

The recognition of human faces poses a complex challenge within the domains of computer vision and artificial intelligence. Emotions play a pivotal role in human interaction, serving as a primary means of communication. This manuscript aims to develop a robust recommendation system capable of identifying individual faces from rasterized images, encompassing features such as eyes, nose, cheeks, lips, forehead, and chin. Human faces exhibit a wide array of emotions, with some emotions, including anger, sadness, happiness, surprise, fear, disgust, and neutrality, being universally recognizable. To achieve this objective, deep learning techniques are leveraged to detect objects containing human faces. Every human face exhibits common characteristics known as Haar features, which are employed to extract feature values from images containing multiple elements. The process is executed through three distinct stages, starting with the initial image and involving calculations. Real-time images from popular social media platforms like Facebook are employed as the dataset for this endeavor. The utilization of deep learning techniques offers superior results, owing to their computational demands and intricate design when compared to classical computer vision methods using OpenCV. The implementation of deep learning is carried out using PyTorch, further enhancing the precision and efficiency of face recognition.
Deblurring image compression algorithm using deep convolutional neural network Menassel, Rafik; Gattal, Abdeljalil; Kerdoud, Fateh
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7783

Abstract

There are instances where image compression becomes necessary; however, the use of lossy compression techniques often results in visual artifacts. These artifacts typically remove high-frequency detail and may introduce noise or small image structures. To mitigate the impact of compression on image perception, various technologies, including machine learning and optimization metaheuristics that optimize the parameters of image compression algorithms, have been developed. This paper investigates the application of convolutional neural networks (CNNs) to reduce artifacts associated with image compression, and it presents a proposed method termed deblurring compression image using a CNN (DCI-CNN). Trained on a UTKFace dataset and tested on six benchmark images, the DCI-CNN aims to address artifacts such as block artifacts, ringing artifacts, blurring artifacts, color bleeding, and mosquito noise. The DCI-CNN application is designed to enhance the visual quality and fidelity of compressed images, offering a more detailed output compared to generic and other deep learning-based deblurring methods found in related work.
PiWall as a home traffic controller: enabling parental control and monitoring Abd Razak, Nurul Imanina; Kamarudin, Shafinah; Shuhud, Mohd Ilias M.; Zakaria, Muhammad Luqman Mahamad; Mohd, Siti Munirah; Wahab, Amelia Natasya Abdul
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.6599

Abstract

The movement control order (MCO) has led to a surge in internet usage among children, becoming the new normal. Most countries heavily rely on online platforms for education, granting children more freedom to explore the internet using electronic devices. Yet, it is challenging for parents to monitor their online activities. Children may stumble upon unsuitable content such as pornography or get redirected to harmful websites through pop-up advertising. To address these concerns, this study proposes PiWall, a home traffic controller. PiWall aims to block undesirable websites and filter out advertisements to help parents manage their home network. Testing shows that PiWall significantly improves the internet browsing experience by reducing website loading times and network traffic, hence offering protection against inappropriate content and malicious attacks. Implementing PiWall as a home traffic controller is a viable alternative to traditional parental controls in creating a safer internet environment for children.
A novel miniaturized radiometer front-end for early breast cancer detection using ultra-wideband flexible antenna Elouerghi, Achraf; Khomsi, Zakaryae; Bellarbi, Larbi; Jbari, Atman
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5702

Abstract

This article introduces a new design of the front-end part of a passive and miniature radiometer, which has been developed to detect breast cancer at an early stage, by measuring temperature in deep mammary tissues. The design and simulation of each element of the microwave radiometer are carried out using computer simulation technology microwave (CST MWS) software. The proposed measurement system consists of a miniaturized ultra-wideband (UWB) flexible antenna operating in the S-band (2-4 GHz), a breast phantom, a low noise amplifier (LNA), a bandpass filter, and a radio frequency (RF) power detector. These components were combined with active circuits to build the front-end system using the co-simulation modules provided by the CST MWS. The method is based on the concept that the virtually created tumor increases the temperature inside the breast phantom, and to detect the abnormality, we applied the proposed radiometer front-end on breast phantom to measure the gain variation. The results demonstrated that the design of the proposed miniaturized radiometer has promising performance in terms of stability and gain variation, indeed, the difference in maximum gain |ΔGmax| measured between abnormal and healthy phantom is about 0.92 dB at 2.75 GHz. This indicates its potential for detecting breast tumors.
Speed synchronization of two DC motors with independent loads based on the higher load torque Saqer Akayleh, Ali; Emad Said, Addasi
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.6188

Abstract

Dual-motor and multi-motor electric drive systems have been used in many industrial applications, and speed synchronization of the motors can always get worse by system parameter uncertainties and load torque perturbations. This work focuses on the application of adjustable speed double-direct current (DC) motor drive control systems. In this paper, a system of two DC motors with armature control at different load conditions has been built. The synchronization of these motors was set basing on the higher torque of the two motor shafts. When two DC motors operate at different shafts a challenge appears in synchronization of their speeds, particularly with the existence of load difference allocated on their shafts. This work paid special attention to this problem. It presents a dynamic simulation of speed control and synchronization of dual DC motor drive. The results show the advantages of the used technique in terms of steady-state and transient performance.
Handover management in vehicle communication: applications, techniques, issues, and challenges: a review Qasim, Hamzah Hadi; Zainol Abidin, Husna; Afzal Che Abdullah, Syahrul
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7549

Abstract

Vehicle-to-everything (V2X) communication is an emerging technology that facilitates communication among vehicles and numerous environmental entities. However, it encounters certain challenges throughout the handover process. This study analyses the challenges and complexity of managing handover, specifically in maintaining uninterrupted connection and meeting the service criteria outlined in the 3GPP 5G new radio (NR) standard. Various applications of V2X technology that require handover management are explored, such as vehicle safety and traffic management, enhanced driver assistance, and autonomous driving. Furthermore, this paper illuminates the most recent developments in V2X communication, highlighting the significance of efficient handover management, resolving technical issues, based on the full potential of the use of V2X apps that contribute to the establishment of a transportation ecosystem that is characterized by enhanced safety, increased intelligence, and improved connectivity. This paper can be used as a starting point for thinking about how to improve C-V2X communication.
Evaluation of domain sulfur industry for DIA translator using bilingual evaluation understudy method Mohammed Lateef, Huda; Muter Awaad, Ahmad; Ali Hameed, Diadeen; Thiab Hasa, Ghanim; Ameen Faisal, Tahseen
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.4489

Abstract

Evaluation is important part of our system development cycle; it also contributes to improving new machine translation (MT) technology optimum via comparing them with the traditional systems available to determine the weaknesses and the effectiveness to be improved in the proposed MT system. This work aiming to make a study that evaluate the performance and effectivness of the domain sulfur industry (DSI) for English-Arabic DIA translator quality. The recent study has conducted evaluating by making a comparison between this programme with the prominent Google translator through applying a rendering of 1,200 English sentences in bilingual evaluation understudy (BLUE) method. The obtain results show that the efficiency of Google translator is about 30.325%, while DIA translator efficiency in domain sulfur industry is about 73.325% and it’s more effective and give a better translation accuracy. The BLUE method efficiency is about (90.478%) compared with the human expert evaluator.
A comprehensive survey on several fire management approaches in wireless sensor networks Rajendran, Swetha; Chenniappan, Navaneethan
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.5833

Abstract

The majority of the fires are activated through environmental reasons although a minority of them are self-activated. To detect fires several safety systems were introduced. There are wired systems, cameras, satellite systems, and bluetooth feasible to provide a complete image of the world but after a long search period. These systems are not perfect since it prevents fire from finding just at the time, the fire initiates. But, recent technological development in wireless sensor networks (WSN) has spread out its fire detection application. A comprehensive survey on several fire management approaches in WSN propose to discuss various fire detection approaches like early fire detection, energy efficient fire detection, mobile agent-based fire detection, unmanned aerial vehicle (UAV)-based fire detection, threshold-based fire detection, machine learning based fire detection and secure fire detection approaches. Moreover, the comprehensive tabular study of the fire management technique is given that will assist in the suitable selection of approaches to be applied for the detection of fire. Furthermore, WSN uses the clustering method to minimize redundant dataandsecure fire detection approaches collect authenticated data related to fire detection. Early fire detection approaches detects the fire early. Machine learning algorithm detects the fire efficiently.
A review on interferometry lightning mapping system and its deployment in Palembang Indonesia Oktaviani, Wiwin A.; Sidik, Muhammad Abu Bakar; Ahmad, Mohd. Riduan; Jambak, Muhammad Irfan
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.7267

Abstract

Climate change effects influence the sustainability of wind and photovoltaic energies as renewable sources. Similarly, infrastructure for renewable energy is structurally vulnerable to lightning strikes. Hence, a system for detecting and monitoring lightning activity is necessary to predict and adapt to climate change trends and to enhance the lightning protection system's capability. One such system for observing and locating lightning is very high frequency (VHF) interferometry. Various factors, such as the baseline distance between sensors, the frequencies used, and the quality of the analyzed signal, will influence the system's accuracy. This paper discusses these factors through an extensive literature review. This study aims to identify the factor that most significantly affects the system's accuracy and to determine the technical adjustments required to improve this accuracy. Enhanced precision in the interferometry system will provide a more detailed view of lightning activity, thereby aiding in the climate change prediction that could impact electricity generation from renewable sources. Accurate lightning location detection can also serve as a basis for designing effective lightning protection systems for renewable energy infrastructure.

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