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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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Effective capacity analysis of configurable intelligent surface-assisted NOMA communications systems Q. Tran, Huu; Van Khuong, Ho
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.7485

Abstract

This paper investigates the integration of configurable intelligent surfaces (CIS) into relay radio networks, focusing on communication system enhancement. Towards this end, we propose CIS-assisted non-orthogonal multiple access (NOMA) communication systems to improve direct connections between a base station and two destination nodes. Our primary objective is to assess the net-work’s overall capacity, considering critical factors like signal-to-noise ratio, the number and placement of CIS components, quality of service exponent, and power distribution coefficients. Analytical equations developed in this research closely align with simulation results, validating our theoretical analysis. This study underscores the growing significance of CISs in modern communication systems, introducing adaptability and optimization to wireless networks. By exploring CIS-assisted NOMA communication systems, we contribute to dis-cussions about the evolving landscape of wireless communication technologies, poised to revolutionize information transmission and reception in the digital age.
Transfer learning for improved electrocardiogram diagnosis of cardiac disease: exploring the potential of pre-trained models Sayed Ismail, Sharifah Noor Masidayu; Abdul Razak, Siti Fatimah; Ab. Aziz, Nor Azlina
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.v13i5.7053

Abstract

Predicting the onset of cardiovascular disease (CVD) has been a hot topic for researchers for years, and recently, the concept of transfer learning has been gaining traction in this field. Transfer learning (TL) is a process that involves transferring information gained from one task or domain to another related task or domain. This paper comprehensively reviews recent advancements in pre-trained TL models for CVD, focusing on electrocardiogram (ECG) signals. Forty-three articles were chosen from Scopus and Google Scholar sources and reviewed, focusing on the type of CVD detected, the database used, the ECG input format, and the pre-training model used for transfer learning. The results show that more than 80% of the studies utilize 2-dimensional (2D) ECG input from the two most utilized available ECG datasets: MIT-BIH arrhythmia (ARR) and MIT-BIH normal sinus rhythm. alexnet, visual geometry group (VGG), and residual network (ResNet) are among the pre-trained TL models with the highest number used among reviewed articles. Additionally, the development of pre-trained TL models over time has made it possible to detect CVD with ECG signals. It can also address limited data problems, promote the development of more dependable and resilient detection systems, and aid medical professionals in diagnosing CVD and other diseases.
Vision-based autonomous mapping and exploration on robot tracked vehicle Mohd Shah, Hairol Nizam; Mat Yusoff, Muhamad Afif; Kamis, Zalina; Ahmad, Azhar; Baharon, Mohd Rizuan; Arshad, Mohd Ali
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5952

Abstract

Vision based mapping is an emerging technology with decades of research advancements. The most famous mapping method available is silmuntaneous localization and mapping (SLAM) which provide an accurate map projected in a simulation. Unfortunately, SLAM requires an active sensor in order to acquire the data from its environment opposite the vision-based mapping which requires a passive sensor to collect data. This project aims to develop an autonomous mapping and exploration algorithm, design a controller for the robot-tracked vehicle and analyze the accuracy of the algorithm. The problem in autonomous mapping is precision, limitation of computational power and complex computation. So, the algorithm will be based on the visual odometer algorithm through a single-visual sensor. The robot tracker has also been designed and implemented on Raspberry Pi 3. The accuracy of two object with different height was calculated to ensure the validation of the algorithm being able to project the real object in 3D projection. The result for the task is shown in figures as to present the capability of the algorithm in projecting the map in 3D projection. The algorithm works as expected but still requires improvements to increase the precision of the map projection.
Effects of processing parameters on the leakage current of silicone rubber insulator Nazir Ali, Nornazurah; Zainuddin, Hidayat; Abd Razak, Jeefferie; Abd-Rahman, Rahisham; Ambo, Nur Farhani
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.v13i2.6070

Abstract

Silicone rubber (SiR) is known for its exceptional electrical insulation properties. The performance of SiR could be affected by many factors, including processing parameters, particularly mixing speed and time. While these parameters are crucial for ensuring the homogeneity of blended polymeric materials, their electrical impact remains relatively unexplored. This research investigates the effect of varying processing parameters on SiR samples during rapid aging under the incline plane tracking (IPT) test. The study unfolds in three phases, with the final IPT stage revealing the significant influence of different mixing speeds and times on the recorded leakage current (LC) values for each sample. Sample 2, subjected to 70 rpm mixing speed and 10 minutes of mixing time, exhibited great resistance to tracking and erosion. Fourier transform infrared spectroscopy (FTIR) was conducted on the samples before and after the IPT test to further analyze the impact of the varying processing parameters. Once again, sample 2 displayed notable resilience, demonstrating lower reductions in absorbance values for key functional groups. In conclusion, the specific processing parameters of 70 rpm and 10 minutes have been shown to positively influence the performance of SiR, enhancing their resistance to tracking and erosion during rapid aging.
Recent trend and future prospect in optimization of electric vehicle charging: a systematic review Fauzi, Muhammad Ridha; Zakri, Azriyenni Azhari; Syafii, Syafii
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.8017

Abstract

Electric vehicles charging (EVs) must be done optimally to minimize the impact it causes. EVs are being recognized as a potential way to decrease greenhouse gas emissions and combat climate change. However, there are still difficulties in optimizing these systems to minimize operating costs and EVs charging waiting times. This study investigates several industrial, commercial and residential charging stations. The primary objective of this study is to systematically review the existing literature on optimizing EV charging. The collection of data was centered on scholarly articles released between the years 2018 and 2023 from Scopus, IEEE Xplore. This study presents a systematic literature review of optimizing EVs charging. As a result, 43 EVs charging optimization studies were obtained which were investigated and studied further. Identify and analysis the selected studies, there are two research topics and trends most frequently addressed by researchers: scheduling and coordination. The four most applied methods in EVs charging are identified: particle swarm optimization (PSO), genetic algorithm (GA), linear programming (LP) method, and evolutionary algorithms (EA). Future research directions: develop advanced optimization algorithms, investigating the integration of renewable energy sources into the charging infrastructure, exploring the potential of vehicle-to-grid (V2G) services, studying the impact of EVs charging on the power grid and developing strategies, considering the optimization of charging schedules and coordination strategies for large-scale EVs fleets.
Robust hybrid control strategy for active power management in Kabertene wind farm within Algeria’s PIAT grid Abderrazak, Tadjeddine Ali; Iliace, Arbaoui; Hichem, Hamiani; Mohamed Sofiane, Bendelhoum; Ridha Ilyas, Bendjillali
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.7270

Abstract

The paper introduces a hybrid control strategy for optimised active power management in Algeria's Kabertene wind farm, crucial for the pole insalah-adrar-timimoune (PIAT) grid's stability. This strategy merges simultaneous interconnection and damping assignment (SIDA) passivity theory, passivity-based control (PBC), and multivariable proportional-integral-derivative (PID) controllers. This combined approach ensures frequency and voltage stability within the PIAT grid, which encompasses various elements like wind farms, solar plants, gas turbines, and dynamic impedance (Z), current (I), and active power (P) (D-ZIP), load model. By tailoring controllers for doubly fed induction generators (DFIGs) using SIDA-PBC principles and optimising internal parameters, the strategy achieves precise control of active power output. Additionally, particle swarm optimisation (PSO) refines power scheduling, which is especially beneficial for intermittent renewable sources like DFIGs. This comprehensive strategy offers numerous advantages: improved network stability, minimized voltage deviations, reduced frequency fluctuations, and enhanced integration of renewable energy sources. The paper emphasises practical implementation considerations, providing valuable guidance for efficient Kabertene wind farm operation and integration. This research contributes significantly to fostering cleaner and more reliable energy systems, facilitating the PIAT grid's transition towards sustainable energy generation.
An inquiry smart chatbot system for Al-Zaytoonah University of Jordan Al-Madi, Nagham Azmi; Abu Maria, Khulood; Al-Madi, Mohammad Azmi; Abu Maria, Eman
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.7645

Abstract

Chatbots are important in artificial intelligence (AI) and natural language processing (NLP). The development of the chatbot is viewed as a continuous issue in the field. This is suitable for Arabic chatbots that are not widely available. This study aims to fill the gap in Arabic chatbot development by creating an Arabic chatbot system for university admissions. The system uses a deep neural network model and a manually constructed dataset for conversation pairings, utilizing the Jordanian Arabic dialect from Al-Zaytoonah University of Jordan’s (ZUJ) website. The system efficiently answers most user queries, improving the counseling experience and reducing workload in the admissions department. The adoption of this system also minimizes website traffic congestion. The study contributes to the improvement of Arabic chatbot technology by creating a deep learning-based system optimized for university admissions, demonstrating its potential impact in the Arabic-speaking context. Future research can further enhance the system’s capabilities and its applicability in other disciplines.
Employing PIPRECIA-S weighting with MABAC: a strategy for identifying organizational leadership elections Setiawansyah, Setiawansyah; Hadad, Sitna Hajar; Aldino, Ahmad Ari; Palupiningsih, Pritasari; Fitri Laxmi, Gibtha; Megawaty, Dyah Ayu
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.v13i6.7713

Abstract

The election of organizational leaders, especially in organizations whose members have diverse backgrounds and interests, can cause various problems. Problems in the selection of school organization leaders include the absence of an objective selection of organizational leadership candidates because they are selected based on comparisons between candidates without considering the criteria in the selection of organizational leadership candidates. Research related to the multi-attributive border approximation area comparison (MABAC) and simplified pivot pairwise relative criteria importance assessment (PIPRECIA-S) methods has never been conducted so far, so it is a reference in conducting this research using the MABAC and PIPRECIA-S methods. This study aims to select the head of the school organization using the MABAC method and PIPRECIA-S weighting can increase the objectivity of the criteria assessment results by relying on calculations from the PIPRECIA-S weighting method. Based on the selection results using the MABAC method and PIPRECIA-S weighting, candidate 1 was recommended as the leader of the school organization because it achieved rank 1 with a total score of 0.293. The contribution of this research is to help in the selection of the head of the organization using the PIPRECIA-S and MABAC methods as a decision-making solution.
Bayesian probabilistic modeling in robosoccer environment for robot path planning Steffi, Diana; Mehta, Shilpa; Venkatesh, Kanyakumari Ayyadurai
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.v13i1.6080

Abstract

The main goal of a route planning approach is to find a trajectory that safely transports the robot from one site to the next. Furthermore, it should provide an energy-efficient path so the computer can calculate it rapidly. This study develops a path-planning system for robots to approach the ball without collision. The Bayesian optimization algorithm (BOA) is used to identify the shortest path between the robot and the ball. BOA employs a probabilistic model to seek the optimum of an uncertain objective function efficiently. The performance of the BOA-based path planning system is compared to other optimization algorithms such as genetic algorithm, ant colony optimization, and firefly algorithm. BOA’s acquisition functions such as expected improvement, probability of improvement (PI), and upper confidence bound, are investigated. The exact locations of the robots and the ball are fed into optimization problems to discover the optimum path. The results reveal that the BOA system outperforms other systems in terms of computational time for planning the optimum path in dynamic situations and BOA-PI is the fastest algorithm.
A novel framework of building operation algorithm for the block of technical diagnostics of aircraft’s automatic control system Vuong, Trung A.; Tran, Dong LT.; Vo, Thanh C.; Nguyen, Minh T.; Tran, Hoang T.
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.5799

Abstract

This article presents the problem of designing an automatic control system that is stable against errors and failures of sensors on aircraft. The sensor system has a technical diagnostic block that ensures diagnosis and eliminates typical errors and failures. Based on the determination of the error vector, damage can occur by adding measurement elements corresponding to the measurement parameters to the control system. When there are errors or failures of the sensor elements, the state vector of the system changes and is determined by measurements. The difference between the measured vector components when there are errors, failures and when working normally is the basis of the working algorithm of the failure diagnosis block. The results demonstrate encouraging prospects for practical implementations.

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