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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 75 Documents
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Search results for , issue "Vol 13, No 6: December 2024" : 75 Documents clear
Implementation of deep learning models in FPGA development board for recognition accuracy enhancement Jassim, Salah Ayad; Khider, Ibrahim
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.v13i6.7683

Abstract

Deep learning (DL) model performance is intricately tied to the quality of training, influenced by several parameters. Of these, the computing unit employed significantly impacts training efficiency. Traditional setups use central processing units (CPUs) or graphics processing units (GPUs) for DL training. This paper proposes an alternative using field programmable gate arrays (FPGAs) for DL training, leveraging their customizable and parallelizable architecture. FPGA programming allows for tailored circuit designs, optimizing DL training requirements and enabling efficient parallel processing. The use of FPGAs in DL training has garnered attention for their potential in achieving high computational throughput and energy efficiency, attributed to advantages like low latency, high bandwidth, and reconfigurability. By exploiting FPGA parallel processing capabilities, faster training times and the potential for larger, more complex DL models are feasible. This paper provides an overview of state-of-the-art techniques for FPGA-based DL model training, discussing challenges such as hardware architecture design, memory management, and algorithm optimization. Additionally, various FPGA-based DL frameworks and libraries facilitating DL model development and deployment on FPGAs are explored.
An ANN enabled joint power allocation and base station switching system for EE heterogeneous networks Euttamarajah, Shornalatha; Ng, Yin Hoe; Tan, Chee Keong
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.v13i6.7262

Abstract

In recent years, dynamic and complex development in wireless communication in network models or environments led to more tedious and complicated resource management issues (i.e., power allocation and base station switching (BSS)). Conventional solutions often suffer from delays and degraded network service quality. Due to the ability of machine learning in analyzing huge volumes of data and automatically adapt to environmental changes, it emerges as a highly sought-after technique. In this work, we propose a machine learning approach based on feed-forward neural network (FFNN) to predict the active BS sets and estimate the power allocation to each user equipment (UE) within the active BSs for energy-efficiency (EE) maximization of a coordinated multi-point (CoMP-enabled) cellular system with hybrid-powered transmitting nodes in a HetNet-based architecture. By training the neural network model efficiently using a regression-based supervised learning technique that employs various backpropagation algorithms, almost similar EE performance (less than 5% difference) can be achieved with significantly reduced computational complexity and delay compared to the traditional methods, such as the well-known dual decomposition and brute force techniques. The effects of various hyper parameters and back-propagation algorithms are also investigated. Our results demonstrate that the proposed framework is a promising solution for establishing a fully green and intelligent network.
The analysis of soft error in static random access memory and mitigation by using transmission gate Kadir, Farhana Mohamad Abdul; Julai, Norhuzaimin
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.v13i6.7664

Abstract

As the progress of technology continues in accordance to Moore’s law, the density and downsizing of circuitry presents a significant vulnerability to the effects of soft errors. This study proposed a novel method to mitigate soft errors by increasing the robustness of complementary metal oxide semiconductor (CMOS) technology against soft errors via the use of transmission gates within the memory nodes of static random access memory (SRAM) which functioned as a low pass filter that disallowed the occurrence of data corruption. The proposed SRAM was tested against parameter variation of supply voltage and temperature. The critical charge was observed to increase with supply voltage increase, with the opposite being true of the increase in temperature. The increase in critical charge of up to 88.63% was achieved with regards to parameter variation for the transmission gate SRAM in comparison to the 6T SRAM.
Real-time object detection and distance measurement for humanoid robot using you only look once Dwijayanti, Suci; Suprapto, Bhakti Yudho; Mutiyara, Mutiyara; Rendyansyah, Rendyansyah
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.v13i6.7476

Abstract

Humanoid robots are designed to mimic human structures and utilize cameras to process visual input to identify surrounding objects. However, previous studies have focused solely on object detection, overlooking both the complexities of real-world implementation and the significance of calculating the distance between objects and the robot. This study proposes a system that employs the you only look once (YOLO) algorithm to detect various objects in the proximity of a robot. Using a dataset of primary data collected in a laboratory, the detected objects are from 12 classes, including humans, chairs, tables, cabinets, computers, books, doors, bottles, eggs, learning modules, cups, and hands, with each class comprising 1500 data points. Two YOLO architectures, namely tiny YOLOv3 and tiny YOLOv4, are assessed for their performance in object detection, with the tiny YOLOv4 demonstrating a superior accuracy of 82.99% compared to tiny YOLOv3. Evaluation under simulated conditions yields an accuracy of 74.16%, while in real-time scenarios, accuracies are 61.66% under bright conditions and 38.33% under dim conditions, affirming tiny YOLOv4’s efficacy. Moreover, this study reveals an average error distance of 31% between an object and the robot in real-time conditions. The developed system enhances human–robot interaction capabilities via data transmission.
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 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.
Active filter harmonic compensator with proportional resonant current controller for photovoltaic inverter Nam, Le Khoa; Lam, Le Hong; Hieu, Trinh Trung; Hieu, Nguyen Huu
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.v13i6.8167

Abstract

The strong development of renewable energy sources (RES), especially distributed energy sources, brings many benefits to the power system. Single-phase photovoltaic (PV) systems are the fastest growing type of distributed energy source worldwide today. Besides the beneficial factors for the distribution power system, the high penetration rate of solar power systems also causes negative impacts, especially power quality issues. PV inverters generate harmonics during the high-frequency switching of semiconductor elements. Traditionally available passive filters are not effective enough to ensure output power quality when the PV system generates power to the distribution grid. Therefore, this study presents the design of a proportional resonant current controller combined with active filter harmonic compensated (PR+HC) for a single-phase PV inverter. This controller, when integrated into traditional PV inverter, will provide better output power quality, contributing to reducing total harmonic distortion (THD) on the distribution grid. This study analyzes the parameters affecting the harmonic attenuation effect of the PR+HC controller, then simulates it on MATLAB Simulink to evaluate the results. The results of the study show that the PR+HC controller is not only effective in reducing the amplitude of odd harmonics, but also operates reliably even when the grid frequency fluctuates widely.
6G networks: insights and reliability analysis Basahel, Ahmed Abdullah; Islam, Md. Rafiqul; Habaebi, Mohamed Hadi
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.v13i6.7896

Abstract

As we are living in a fast-moving dynamic world. Emerging technologies such as artificial intelligence (AI), internet of things (IoT), virtual reality (VR), augmented reality (AR), fourth industrial revolution (Industry 4.0), metaverse, and edge computing are expected to play an essential role in our daily life. These technologies require high-speed, sustainable, and reliable communications networks which are expected by sixth generation (6G) wireless communications networks. 6G will be the backbone for these emerging technologies as well as for the technology-driven digital infrastructure. Governments as well as research and development (RD) of the technology companies are gearing up to conduct a regulatory framework to standardize 6G networks; studying and conducting experimental setups to examine and evaluate the deployment of 6G networks; both in which they will have opportunities and challenges. This paper provides insights and guidelines for 6G networks in terms of standards, implementations, applications, and research trends. In addition, it provides reliability analysis for terrestrial 6G networks. A carrier class availability could be achieved over a maximum of 4 km link distance. These insights and availability figures may be used as a useful tool for researchers and industry stakeholders for the deployment and rollout of the next generation 6G wireless communications networks.
Quasi resonant topology based highly efficient solar-powered induction cooker Ahmad, Shameem; Awalin, Lilik Jamilatul; Nahid Hasan, Sheikh Md.; Saha, Arghya; Ali, Mohd Syukri; Syafiq, Amirul; Wang, Li
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.v13i6.7925

Abstract

The energy crisis is a major issue in developing countries, with fossil fuels being the main source of cooking. Induction cookers have received attention due to their safe operation and eco-friendliness, but traditional AC induction cookers are costly and inefficient due to an inverter and rectifier. In this regard, this paper aims to model and develop a solar-powered, low-cost, and highly efficient induction cooker that can be operated directly by solar panels through a battery. By utilizing the solar panels’ maximum output, a maximum power point tracking (MPPT)-based solar power controller has been utilized to charge the battery. A modified coil structure for the cooker is proposed to decrease the coil’s excitation time and increase the resonant frequency. A quasi-resonant converter topology has been used in the proposed induction cooker, as it operates at high frequencies above 20 kHz to avert audible noise and below 100 kHz to minimize losses in switching. The performance of the suggested induction cooktop has been validated by modifying the circuit and the coil of a traditional 220 V, 2 kW induction cooker. Based on the outcomes, it is observed that the efficiency of the proposed induction cooker reached 93%, which is better than that of existing induction cookers.
A frequency adaptive multiple complex coefficient filter for grid connected applications Boumediene, Bachir; Araria, Rabah; Chedjara, Zakaria; Mekhloufi, Belkacem; Bey, Mohamed; Wira, Patrice
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.v13i6.7245

Abstract

In the realm of synchronization techniques, the dichotomy between open loops (OLSs) and closed loops (CLSs) presents a perennial challenge: how to enhance dynamic performance without sacrificing stability and disturbance rejection. While OLS techniques offer rapid dynamic response and unwavering stability, they often falter in non-nominal frequency scenarios. Conversely, CLS techniques grapple with the delicate balance of bolstering dynamic performance while maintaining robust stability. To surmount these obstacles, this study proposes an innovative approach: the integration of a frequency locked loop (FLL) as a secondary frequency detector within synchronization structures, coupled with the multiple-complex coefficient-filter (MCCF). This amalgamation bestows notable advantages. Firstly, from a control perspective, the resultant synchronization technique resembles a quasi-OLS, obviating the need for intricate stability analyses. Moreover, it exhibits commendable disturbances rejection alongside swift dynamic response. Through comprehensive simulation, our proposed technique showcases superiority over existing counterparts, evidencing enhanced settling time, disturbances rejection, and efficiency in the face of frequency drifts.

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