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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 3,202 Documents
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Hardware-level data layout approach to mitigate the memory row conflicts on FPGA-based CNN accelerators Shalini Prasad; Suman Jayakumar; Bellary Kursheed; Aruna Mogarala Guruvaya; Rashmi Shivaswamy
Bulletin of Electrical Engineering and Informatics Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i4.11386

Abstract

Memory row conflicts (MRCs) continue to be a major bottleneck that results in higher latency, ineffective double data rate (DDR) usage, and decreased effective bandwidth in field-programmable gate array (FPGA-based) convolutional neural network (CNN) accelerators. The majority of current effort focuses on computational optimization, frequently ignoring inefficient memory access. In order to reduce memory reference codes (MRCs), this research suggests a hardware-level data layout technique using a memory-centric accelerator architecture. In order to improve hit rates and row buffer locality, the architecture incorporates a dynamic cursor-based address mapping method that adjusts to different feature map sizes across CNN layers and a dual-DDR setup for concurrent data access. The experimental results on VGG16, YOLOv2, and AlexNet show an 18% reduction in MRCs, a 40% increase in throughput, and a 23% decrease in latency compared to state-of-the-art techniques. The design uses a Xilinx Kintex-7 FPGA with low power usage of 1.52 W. The suggested method improves memory performance in FPGA-based CNN accelerators in a scalable and hardware-efficient manner without requiring a large computational burden.
Security concern based Damgard-Jurik algorithm for data transmission in decentralized cloud storage Karuppasamy Lakshmanan; Vasudevan Venkatraman
Bulletin of Electrical Engineering and Informatics Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i4.10756

Abstract

Decentralized cloud storage (DCS) provides IT resources to a growing community of users. Decentralized storage systems offer availability, redundancy, and security because the data will be spread across numerous nodes. Despite its benefits, there are still challenges associated with DCS, such as inconsistency in data versions, complicated data retrieval, and the problem of data integrity and privacy. To effectively handle these challenges, it is necessary to come up with new solutions. To overcome these issues, a novel Dual-Chunk redundancy assisted Damgard-Jurik-incorporated slice-based data security (DRAGO-SLICE) framework has been suggested in this paper to improve security and reliability in DCS. The suggested approach utilizes the Damgard-Jurik algorithm (DJA) for encrypting the cloud resource data. The slicing process divides encrypted data into multiple chunks to increase security. Enhanced system reliability has been achieved by implementing dual chunk redundancy (DCR). Python has been used to simulate the suggested model. The efficacy of the developed approach is evaluated utilizing metrics namely decryption time (DT), security strength, encryption time (ET), latency, computational overhead, reliability, storage efficiency, and throughput. The proposed DRAGO-SLICE strategy performs better in terms of security than the existing methods, including Ethereum virtual machine elliptic-curve cryptography (EVM-ECC), decentralized blockchain-based security (DeBlock-Sec), and blockchain-based decentralized storage system (BC-DSS) approaches, by 21.05%, 13.74%, and 8.52%, respectively.
Water-inspired WCA optimization of a 180 nm CMOS OTA for ultra-low-power analog interfaces Ahamri Fatima-Zohra; Khadija Slaoui; Meryem Ameur
Bulletin of Electrical Engineering and Informatics Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i4.11057

Abstract

The necessity of ultra-low-power analog front-ends, especially in modern integrated systems, is becoming more evident by the day. Here, we present a two-stage operational transconductance amplifiers (OTAs), in a 180 nm process, with excellent optimization performed using the water cycle algorithm (WCA), which improves the trade-off between gain, speed, and energy. Using continuous migration and precipitation processes from WCA, and through a multi-objective approach, we achieve 80 dB of DC gain, 71.2 degrees of phase margin, and 32.1 volts per microsecond of slew rate (SR) with a total power consumption of 21.3 microwatts. The amplifier demonstrates excellent disturbance rejection with a power supply rejection ratio (PSRR) of 75 dB and a common-mode rejection ratio (CMRR) of 110 dB at 1 MHz. The WCA design methodology is the most precise alternative compared to the other design methods, and is applicable to low-dropout regulators, biomedical sensors, and embedded analog circuits. Our results support the need for the more wide-spread use of nature inspired optimization techniques in analog integrated circuits (ICs) design.
An intelligent deep learning for Arabic stemming and morphological classification Azal Alaswaad; Behrouz Minaei-Bidgoli
Bulletin of Electrical Engineering and Informatics Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i4.12127

Abstract

Arabic language, due to its complex morphology and richness of grammar features poses significant challenges in natural language processing (NLP). In this paper, we propose a two-stage deep learning pipeline that combines Arabic text stemming and morphological classification within a single deep learning architecture. The relationship between morphological reduction and grammatical categorization is exploited by combining character-level sequence processing with transformer-based classification. A bidirectional long short-term memory (Bi-LSTM) model is employed for Arabic stem extraction to build a sequence-to-sequence (seq2seq) stemming model named Char Stemmer. To evaluate the proposed model, a gold standard dataset consisting of 260,000 traditional Arabic words extracted from Quranic words and classical Arabic books is utilized. This dataset contains a wide range of challenging word structures suitable for robust evaluation. The Char Stemmer achieved an accuracy of 93.88% on the stemming task. The proposed model obtained 93.88% accuracy, demonstrating a 38% improvement over the best traditional stemmer, P-Stemmer. Beyond stemming, the impact of stemmers on subsequent tasks is evaluated, particularly Arabic word classification. Words are categorized into three morphological classes: noun, verb, and particle. Experimental results show that the proposed system achieved macro average precision, recall, and F1-score of 0.91, 0.89, and 0.90, respectively, with an overall classification accuracy of approximately 99%.
Toward generalizable unified modeling language automation: a dual case study on class and use case diagram generation Van-Viet Nguyen; Huu-Khanh Nguyen; Kim-Son Nguyen; Thi Minh-Hue Luong; Duc-Quang Vu; The-Vinh Nguyen
Bulletin of Electrical Engineering and Informatics Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i4.11226

Abstract

Manual generation of unified modeling language (UML) diagrams creates bottlenecks in agile development due to inconsistency and labor intensity. While large language models (LLMs) offer generative capabilities, existing solutions suffer from data scarcity and inadequate evaluation tools. To address this, we present a dual-LLM pipeline integrating lightweight specification generation with reasoning-oriented code synthesis. Uniquely, this framework employs a weighted multimodal validation module utilizing diverse vision-language models (VLMs) to assess diagrammatic fidelity. We further address the data shortage by releasing benchmark datasets comprising 5,000 class and 3,000 use case diagrams. Empirical results demonstrate a 95.8% rendering success rate for class diagrams and strong semantic alignment for use case models. By mitigating structural and behavioral reasoning conflicts, this research provides a replicable architecture and rigorous assessment methodology, establishing a robust foundation for scalable, artificial intelligence-driven automation in software engineering.
An assistive communication system for mute individuals using MATLAB-based image processing and sensor integration Mohan P. Thakre; Krupali Kanekar; Badal Kumar; Alok Kumar; Supriya Nilesh Thakur; Pranali M. Thakre; Prashant K. Magadum
Bulletin of Electrical Engineering and Informatics Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i4.11395

Abstract

Interactions between non-verbal people and verbal communicators have always presented serious challenges. Although functional, current sign language systems often lack the flexibility and affordability needed for wider use. This document provides a novel speaking system created for those who are mute, supporting communication using two methodologies: i) recognition of hand motions with flex sensors and ii) detection of finger positions through image processing techniques combined with MATLAB. The setup in question uses a single camera and a Raspberry Pi to capture hand photos. Finger coordinates are then extracted from these photos and compared to an existing database for matching. An appropriate verbal output is then produced from the identified gesture. Flex sensor-based inputs are simultaneously connected to an Arduino, which uses a Bluetooth module to transmit text data to an external application for speech conversion. This dual-mode technology improves everyday communication for people who are silent by providing a customized and efficient framework for converting sign-based gestures into vocal communications. This approach makes a significant contribution to the development of inclusive technology by offering an affordable, adaptable, and practical alternative for assistive communication.
Smart sensor integration for real-time quality monitoring in processed frozen foods Aina Hayani Amran; Nur Hazahsha Shamsudin; Siti Asma Che Aziz; Siti Amaniah Mohd Chachuli; Nur Fazira Haris
Bulletin of Electrical Engineering and Informatics Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i4.10480

Abstract

The demand for processed frozen food has increased due to its rich flavors, long shelf life, and convenience. This trend was noticeable during the COVID-19 pandemic as it reduced the need for frequent grocery shopping and minimized virus exposure. However, processed frozen food is still prone to spoilage over time. This study aims to monitor the quality of processed frozen food, including beef, chicken, and fish, over 24 hours using three primary sensors known as MQ4, MQ136, and MQ137. These sensors detect the main gases produced during food spoilage, which are methane (CH4), hydrogen sulphide (H2S), and ammonia (NH3), respectively, and are integrated with the ESP32 microcontroller. Each sample was analyzed using 100 g of meat placed in a sealed container, with ambient temperature and humidity levels being monitored. The pattern of gas production can be viewed on ThingSpeak, and a notification is sent via Telegram when the threshold value is reached. This study is conveniently used to identify the typical conditions under which processed frozen food is most likely to be spoiled. The result shows that the MQ137 sensor is the most sensitive in detecting early spoilage stages, which indicates the ammonia gas in high temperature and humidity levels.
An analytical survey of algorithms for efficient metadata indexing and search in distributed file systems Sonali Vidhate; Pankaj Dashore
Bulletin of Electrical Engineering and Informatics Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i4.12090

Abstract

High-performance computing (HPC) environments generate large volumes of heterogeneous data, challenging traditional metadata management in distributed file systems (DFSs). Existing portable operating system interface (POSIX)-based metadata models offer limited support for semantic queries and content-based search, leading to reliance on external crawlers or centralized services that introduce latency and scalability issues. This paper presents TagIt++, an extension of the TagIt framework, which integrates metadata indexing directly within DFS volume servers. TagIt++ introduces automated semantic metadata enrichment, locality-aware federated indexing, and secure in-situ operator execution without modifying the underlying file system. Evaluated on a 12-node HPC cluster using genomics, climate, and synthetic datasets, TagIt++ demonstrates significant improvements, including a 55% reduction in search latency, 38% higher indexing throughput, and 96% metadata coverage. Query accuracy improves by 6.7% (F1-score), while storage overhead is reduced by 25%. Ablation results confirm the effectiveness of each component.
Internet of things-enabled smart monitoring of induction motors for industrial applications Yogesh Shivaji Pawar; Sandip Rahane; Amita Panchamrao Thakare; Dipalee M. Kate; Jyoti P. Rothe; Dinesh Suryakant Wankhede; Kirti Vaidya; Hema Kale; Rakesh G. Shriwastava; Rahul Mapari
Bulletin of Electrical Engineering and Informatics Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i4.11566

Abstract

AC motors, particularly induction motors, remain the most widely used machines in industrial applications due to their simplicity, robustness, and efficiency. Given their critical role, continuous monitoring and regulation of induction motor parameters are essential to ensure reliability and prevent unexpected failures. This research presents an internet of things (IoT-based) system for real-time monitoring and control of a three-phase induction motor. Various sensors are employed to measure key parameters such as motor temperature, current, and voltage, with the collected data transmitted to a processing unit and displayed on a server for remote access. To enhance fault resilience, the system integrates both automatic and manual control mechanisms for starting or stopping motors under abnormal conditions. The proposed approach enables continuous monitoring, early fault detection, and predictive maintenance, thereby improving overall operational efficiency and reducing downtime. Induction motors, first introduced by Nikola Tesla, account for over 50% of global electricity consumption and are deployed in nearly 90% of industrial operations. Their dominance stems from inherent advantages, including being self-starting, cost-effective, reliable, and maintenance-friendly, as well as offering a strong power factor, compact design, and high efficiency. By leveraging IoT technology, this work bridges the gap between traditional motor operation and modern Industry 4.0 practices, providing a scalable solution for smart industrial environments.
Chaos and strange attractors in linear spacecraft attitude control via gradient-velocity Lyapunov Beisenbi Mamyrbek Aukebaevich; Abdiramanov Orisbay Galymdzhanovich; Saltanat Beisenbina Erkinovna; Nurbayeva Marzhan Nurbaykyzy; Basheyeva Zhuldyz Orynbassarovna
Bulletin of Electrical Engineering and Informatics Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i4.10299

Abstract

This paper investigates the generation of deterministic chaos in nonlinear spacecraft control systems using the gradient–velocity method of Lyapunov vector functions. Unlike traditional Lyapunov-based approaches, which lack a universal method for constructing functions, the proposed approach provides explicit algebraic inequalities that determine the conditions for chaotic behaviour. A nonlinear spacecraft model with linear control laws is analysed, incorporating actuator dynamics and measurement uncertainties. Numerical simulations demonstrate the transition between robustly stable and chaotic regimes under variations of system parameters. The results are validated through phase portraits and transient responses, and further supported by quantitative chaos indicators such as Lyapunov exponents and bifurcation analysis. The study shows that when robust stability boundaries are preserved, the system remains periodically stable, whereas violation of these conditions leads to deterministic chaos with the formation of strange attractors. Compared with existing methods, the gradient–velocity approach offers a systematic framework applicable to high-dimensional nonlinear systems. The proposed methodology can be extended to the synthesis of spacecraft attitude control systems, where maintaining stability under uncertainty is critical. This work contributes to the theoretical understanding and practical mitigation of chaos in aerospace applications.

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