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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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Isolation enhancement of four port multiple-input multiple-output antenna for sub-6 GHz 5G communication Manikonda, Ramesh; Sudhakar, Annapantula; Tamminaina, Govindarao
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.9948

Abstract

For 5G communication, this research suggests a small, broad band, 4-port multiple-input multiple-output (MIMO) antenna with an impedance bandwidth of 2.0 GHz (or 3.0-5.0 GHz). The n77, n78, and n79 bands are covered. The single antenna is realized by inserting the stubs and creating the ‘HI’ slot on the rectangle patch with the defect in the ground plane, using FR-4 substrate. Next, four MIMO antennas are built utilizing the reference antenna. Due to mutual interaction, implementing MIMO systems presents a substantial challenge: achieving good isolation between antenna parts in the confined space. To increase isolation with decoupling procedures, the four antennas are placed orthogonally to one another. Because the antennas are positioned orthogonally, the MIMO antenna has an isolation of 28.0 dB. The diversity gains (DG) and envelop correlation coefficient (ECC) are used to analyze the recommended antenna's diversity performance characteristics, and the results show that the values are 9.99 dB and 0.0003, respectively. The simulated S-parameters have been compared with orthogonal and adjacent positions of quad port MIMO antenna. Anritsu MS2037C VNA is used to measure the parameters, and HFSS software is used to simulate it.
Cyber security threats and web vulnerability analysis of higher educational institutions in Bangladesh Hasan Khan Janny, Shadiqul; Asadujjaman Noor, Md.; Enan Al Harun Sahan, Mohammad; Nafez Sadnan, Sheikh; Towfiqur Rahman, Muhammad; Saleh Md Bakibillah, Abu
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.9349

Abstract

This paper presents a comprehensive analysis of cyber security threats and web vulnerabilities in the context of higher educational institutions in Bangladesh, including twenty public and private universities. Educational institutions are highly vulnerable due to their negligence in maintaining a functional network, mainly owing to budgetary constraints. As a result, they have become a hacker playground for many ambitious adversaries to boast their technical skills, regardless of the harm they may inflict. Through the use of vulnerability assessment and penetration testing (VAPT), we conducted a methodical analysis of the institutions’ web infrastructures, identify and categorize the prevalent security threats and vulnerabilities that may compromise the integrity, confidentiality, and availability of information systems. Our findings reveal significant disparities in the security strength of both public and private universities, with the latter demonstrating a higher degree of vulnerability due to varying factors, such as budget constraints, policy enforcement, and awareness levels. This study underscores the urgent need for robust cyber security frameworks tailored to the higher educational sector’s unique requirements, advocating for proactive measures to mitigate potential cyber threats. The implications of this research extend beyond the academic domain, offering insights into national cyber security strategies and the safeguarding of critical information infrastructures.
Soil erosion analysis based on machine learning method Bolsynbek, Mukhammed; Abdikerimova, Gulzira; Serikbayeva, Sandugash; Batyrkhanov, Ardak; Shrymbay, Dana; Taszhurekova, Zhazira; Zhidekulova, Gulkiz; Shraimanova, Gulmira
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10452

Abstract

Soil erosion poses a serious environmental and agricultural threat that undermines land productivity, sustainability, and ecosystem stability. This study develops a robust machine learning framework for predicting and analyzing soil erosion across diverse landscapes by integrating advanced remote sensing data, climate indicators, and soil characteristics. Spectral indices such as the normalized difference vegetation index (NDVI), moisture stress index (MSI), and surface albedo were employed to assess vegetation condition, moisture levels, and surface reflectance. The proposed model, based on the extreme gradient boosting (XGBoost) algorithm, classifies erosion stages with up to 99% accuracy, ranging from healthy land to severely degraded areas. The methodology includes comprehensive feature engineering, dataset preprocessing, and model evaluation. Furthermore, a comparative analysis with traditional models (USLE and RUSLE) highlights the superior predictive performance of the proposed approach. The findings offer valuable insights for sensor-based monitoring systems and cloud-based decision-support tools, supporting sustainable land use management, erosion risk mitigation, and effective soil conservation strategies.
Enhanced speech recognition in natural language processing Chang, Siu-Hong; Ng, Kok-Why; Haw, Su-Cheng; Yoong, Yih-Jian
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.9539

Abstract

Speech recognition is crucial for helping individuals with physical disabilities access digital content. However, current systems have significant flaws that hinder user experience and complicate daily tasks. Environmental disturbances can cause misinterpretation, and existing automatic speech recognition (ASR) systems struggle with comprehending acoustic and linguistic nuances and handling diverse speaking styles and accents. To address these issues, a new model integrates bidirectional encoder representations from transformers (BERT) and transformer features with natural language processing (NLP) capabilities. This model aims to consolidate semantic, linguistic, and acoustic information extracted from the Kaldi speech recognition toolkit and improve accuracy by rescoring the list of N-best hypotheses. The innovative approach leverages advancements in NLP to enhance speech recognition's accuracy and robustness across various scenarios. Evaluations on the LibriSpeech dataset show that integrating BERT, transformer encoder, and generative pretrained transformer 2 for rescoring N-best hypotheses significantly improves transcription accuracy. The proposed model achieves a word error rate (WER) of 17.98%, outperforming other models. This development paves the way for advancements in speech recognition technology, offering better user experiences in real-world applications.
Load frequency control of multi-source power system using PID+DD controller based on chess algorithm Areeyat, Chatmongkol; Audomsi, Sitthisak; Obma, Jagraphon; Yang, Xiaoqing; Sa-ngiamvibool, Worawat
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10425

Abstract

This article presents load frequency control for a nonlinear multi-source power system divided into three areas, consisting of thermal reheat power plants, hydropower, and wind generation, while considering generation rate constraints (GRC). A proportional–integral–derivative (PID) plus second-order derivative (PID+DD) controller optimized using the chess algorithm (CA) is proposed. The effectiveness of CA is validated against hippopotamus optimization (HO), grey wolf optimizer (GWO), and ant lion optimizer (ALO) under two scenarios: a 10% step load perturbation (SLP) and a random load pattern (RLP). Simulation results indicate that the proposed CA significantly improves dynamic performance. In scenario 1 (10% SLP), CA achieves a reduction of approximately 30.5% in integral weight time absolute error (ITSE) compared to GWO and 43.7% compared to HO, while also reducing frequency undershoot in Area 2 by 15.2% compared to HO. In scenario 2 RLP, CA maintains robustness, limiting tie-line power deviations to ±8 MW, whereas HO exhibits deviations exceeding ±12 MW. Overall, the CA-tuned PID+DD controller demonstrates superior damping, reduced overshoot and undershoot, and enhanced stability across multi-area interconnected renewable systems, making it a promising approach for future real-time load frequency control (LFC) applications with higher renewable penetration.
Optimized electric vehicle charging allocation with overload management and vehicle to grid support Hamim, S. J.; Rahman, Imran; Yeamin, Md.; Saleh, Abdullah; Aziz, Tareq
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10728

Abstract

The rapid proliferation of electric vehicles (EVs) in residential distribution networks poses significant challenges, particularly in managing peak demand and maintaining grid stability during the peak demand periods. This study employs a day-ahead EV charging framework in compliance with valley-filling technique to align charging during off-peak periods for a centralized residential charging station that balances grid stability with customer satisfaction. To mitigate network overloading, vehicle to grid support is integrated through optimization based on genetic algorithm (GA), enabling optimal scheduling of both charging and discharging activities under operational constraints. Simulation outcomes substantiate the efficacy of the proposed charging scheme in preventing overloads and demonstrate a notable enhancement in the load factor from 70.68% to 82.24%, reflecting enhanced utilization of energy resources. The approach offers technical and economic benefits for both utilities and EV users, highlighting its potential for scalable and efficient grid management.
3D mapping for unmanned aerial vehicle combining LiDAR and depth camera in indoor environments Tran, Hoang Thuan; Vo, Chi Thanh; Ha, My Duyen; Tu, Nong Trong; Ngan, Du Van; Le, Nam Hoai; Hoa, Duong Van
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10573

Abstract

Indoor reconnaissance missions for unmanned aerial vehicles (UAVs) pose significant challenges in scene reconstruction, mapping, and environmental feature extraction. Relying on a single type of sensor often results in limited accuracy, increased susceptibility to environmental noise, and a lack of comprehensive spatial information. To address these issues, this study proposes a mapping method that combines light detection and ranging (LiDAR) and depth camera data. The method collects data from both LiDAR and a depth camera integrated on the UAV, then performs preprocessing on both data sources to construct local 3D maps using the real-time appearance-based mapping (RTAB-Map) algorithm. Subsequently, the local maps are merged using a filtering method to generate a detailed and complete global map. Real-time experiments conducted on Ubuntu 20.04 using the robot operating system (ROS) Noetic libraries demonstrate that this multi-sensor fusion approach provides richer and more comprehensive environmental information, thereby enhancing the effectiveness of mapping tasks in unknown indoor environments.
Dispersion compensation in single and multi-channel DWDM using chirped apodized fiber Bragg gratings Kalkala Balakrishna, Kripa; Murthy Chinnammahalli Ramappa, Gopalakrishna; Palani, Karthik
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10599

Abstract

Chromatic dispersion (CD) is a key limiting factor in long-haul optical fiber communication, particularly in multi-channel dense wavelength division multiplexing (DWDM) systems, where it introduces signal distortion and inter-symbol interference (ISI). This paper proposes a low-dispersion-offset compensation (LDOC) scheme employing Gaussian-apodized linear chirped fiber Bragg gratings (CFBGs) to enhance dispersion management in single and multi-channel DWDM optical fiber communication systems. Simulations were performed in OptiSystem 7.0 for 10 Gbps single-channel transmission over standard single-mode fiber (SSMF) spanning 110–210 km, and were extended to 4- and 8-channel DWDM systems with a 0.8 nm channel spacing. System performance was evaluated in terms of quality factor (Q-factor), bit error rate (BER), and eye height under varying fiber lengths, input powers, and chirp coefficients. The LDOC-enhanced CFBG achieved a Q-factor of 7.04 with a BER of 9.82×10⁻¹³ for single-channel transmission at 180 km, 13.83 with a BER of 5.57×10⁻⁴¹ for a 4-channel system at 150 km, and 7.56 with a BER of 7.76×10⁻¹¹ for an 8-channel system at 150 km. These results confirm significant improvements compared to conventional CFBGs, demonstrating that the proposed LDOC-based approach is a compact and effective solution for next-generation metro-core, long-haul, DWDM, and 5G/6G optical networks.
Modeling the process of magma rising in the bowels of the Earth and its eruption to the surface Taurbekova, Ainur; Karimsakova, Balnur; Mamyrbayev, Orken; Toigozhinovа, Ainur; Tergeusizova, Aliya; Doshtaev, Kuntugan; Aidaraliyeva, Zarina; Utepova, Elvira
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10454

Abstract

This paper presents a numerical model for simulating magma ascent in the Earth’s interior and its eruption to the surface, aimed at improving earthquake prediction. Magmatic flows are modeled as highly viscous fluids with a low Reynolds number (Re) using simplified Navier–Stokes equations. The approach incorporates hydrodynamic instability arising from density differences between magmatic and asthenospheric layers. Initial and boundary conditions were formulated for magma outflow from a narrow crack, and a dimensionless Euler–Reynolds (ER) parameter was introduced to characterize flow behavior. Numerical experiments for different ER values revealed that at low ER, magma spreads slowly, forming stable layers, while higher ER values accelerate vertical rise, increase pressure gradients, and enhance instability. The model identifies zones of stress accumulation that may precede seismic events. An additional method—monitoring fluid levels in deep wells—showed correlation with seismic fluctuations, supporting its potential for early warning. The results confirm the reliability of the proposed approach, demonstrating good agreement with seismological data. The developed methodology can be applied to enhance early warning systems and reduce risks in seismically active regions.
Design of compact dual-resonance multiple-input-multiple-output antenna array for internet of things application Kadu, Mahesh; Chitte, Pankaj Pramod; Udawant, Sandip R.; Ubale, Vilas S.
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10035

Abstract

This work presents a compact dual-resonance multiple-input-multiple-output (MIMO) antenna array for internet of things (IoT)-enabled smart devices requiring both 5G and Wi-Fi connectivity. The antenna operates at 3.6 GHz (5G smartphones) and 5.4 GHz (high-speed Wi-Fi), using a dual-resonance MIMO configuration for reliable multi-device communication. An integrated electromagnetic band-gap (EBG) structure suppresses surface waves, reducing mutual coupling and achieving 35 dB isolation with an envelope correlation coefficient (ECC) of 0.05. A fabricated prototype validated the design, with measurements aligning closely with simulations. The proposed antenna offers compactness, dual-band operation, low coupling, and strong MIMO performance, making it well-suited for next-generation IoT systems.

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