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Enhancing source currents and ensuring load voltage stability in railway electrification system via unified power quality conditions implementation

10.11591/ijece.v15i5.pp4430-4444
Kittaya Somsai , Jeerapong Srivichai , Veera Thanyaphirak
In recent years, interest in electric railway system as a transportation solution for large urban areas has grown significantly. This increased attention stems from several key advantages, including environmental friendliness, high performance, reduced maintenance costs, and lower energy expenses. Railway electrification system rely on supplying power to trains through single-phase transformers. However, these transformers can cause issues such as current imbalances and harmonics at the system connection point, which may impact critical loads. Additionally, fluctuations in source voltage can influence the system's performance. This study examines the causes of unbalanced loading in railway electrification system and introduces an innovative unified power quality conditioner (UPQC) specifically designed for integration into low-voltage railway electrification system. The proposed UPQC aims to restore current balance, minimize harmonics, and enhance overall power quality. Furthermore, it addresses the mitigation of voltage sags in the power distribution network. The simulation results generated through MATLAB programming demonstrate the UPQC's effectiveness in enhancing system performance. The findings reveal that the UPQC reduces source current imbalance to less than 1.6% and total harmonic distortion (THD) to below 4.89% across all test scenarios. Additionally, the UPQC successfully maintains a load bus voltage of 25 kV during single-phase-to-ground and unbalanced three-phase-to-ground fault conditions.
Volume: 15
Issue: 5
Page: 4430-4444
Publish at: 2025-10-01

Comparative analysis of convolutional neural network architecture for post forest fire area classification based on vegetation image

10.11591/ijece.v15i5.pp4723-4731
Ahmad Bintang Arif , Imas Sukaesih Sitanggang , Hari Agung Adrianto , Lailan Syaufina
This study presents a comparative analysis of 7 Convolutional Neural Network (CNN) architectures—MobileNetV2, VGG16, VGG19, LeNet5, AlexNet, ResNet50, and InceptionV3—for classifying post-forest fire areas using field-based vegetation imagery. A total of 56 models were evaluated through combinations of batch size, input size, and optimizer. The results show that MobileNetV2, VGG16, and VGG19 outperformed other models, with validation accuracies exceeding 88%. MobileNetV2 emerged as the most balanced model, achieving 96% accuracy with the lowest model size and training time, making it ideal for resource-constrained applications. This study highlights the potential of CNN-based classification using mobile field imagery, offering an efficient alternative to costly and condition-dependent satellite or drone data. The findings support real-time, localized identification of burned areas after forest fires, providing actionable insights for prioritizing recovery areas and guiding ecological restoration and land rehabilitation strategies.
Volume: 15
Issue: 5
Page: 4723-4731
Publish at: 2025-10-01

Dynamic head pose estimation in varied conditions using Dlib and MediaPipe

10.11591/ijece.v15i5.pp4581-4592
Rusnani Yahya , Rozita Jailani , Nur Khalidah Zakaria , Fazah Akhtar Hanapiah
This paper presents the formulation and validation of a dynamic head pose estimation (HPE) algorithm, addressing challenges related to diverse conditions, complex poses, and partial obstructions. The study aims to create a robust algorithm that maintains high accuracy in real-time applications across varying conditions. The algorithm was implemented and assessed using Dlib and MediaPipe models. The study involved 30 participants in face and head without obstacles, face with obstacles and head with obstacles conditions. The results demonstrated impressive performance in both controlled and spontaneous head movement categories. The algorithm achieved an average accuracy of 93% for head pose estimation and 88% in detecting visual attention under spontaneous head movement categories. A correlation coefficient of 0.866 indicates a strong positive linear association between performance and attention accuracy, indicating that performance improvements are intricately linked to proportional increases in attention accuracy. However, this does not necessarily imply causation. The findings provide valuable insights into the effectiveness of the proposed algorithms in assessing visual attention and demonstrate their potential applications in healthcare monitoring, educational intervention, and driver monitoring systems. The significance of these results lies in the ability to advance human-computer interaction, enhance healthcare diagnostics, and offer innovative solutions across various domains.
Volume: 15
Issue: 5
Page: 4581-4592
Publish at: 2025-10-01

Prospective applications of assistive robotics for the benefit of population groups

10.11591/ijece.v15i5.pp4531-4541
Anny Astrid Espitia-Cubillos , Robinson Jimenez-Moreno , Javier Eduardo Martínez-Baquero
The development of robotics has reached various fields of application such as the assistance field, where robots support people with different abilities in different activities to provide independence, comfort and interaction, even improving their self-esteem and quality of life. The objective is to identify the main benefits of the application of assistive robotics achieved to project its future fields of action. For this purpose, the Scopus database is used to find documents related to assistive robotics, which are filtered by publication date and according to the elimination criteria determined by the authors, and then bibliometric networks are constructed using VOSviewer. Finally, the main findings are analyzed and presented according to their area of application. Five areas of application of assistive robotics are identified that benefit children, the elderly, provide hospital assistance, help people with disabilities or support therapy and rehabilitation work, developments that allow the formulation of areas for future study. It is concluded that there are many advances in assistive robotics that demonstrate robotic development and provide assistance to a particular population, but more work is still needed to increase the number of beneficiaries, reduce costs and expand research in the areas mentioned and to be developed.
Volume: 15
Issue: 5
Page: 4531-4541
Publish at: 2025-10-01

Field-programmable gate array-based voltage-feedback-driven battery charging with DC-DC buck converter

10.11591/ijece.v15i5.pp4993-5002
Afarulrazi Abu Bakar , Suhaimi Saiman , Tharnisha Sithananthan , Muhammad Nafis Ismail , Saidina Hamzah Che Harun
This paper presents the design and development of a reference-driven field-programmable gate array (FPGA)-based controllable battery charging system featuring a buck converter. The controller tracks and adjusts the system's duty cycle based on output voltage feedback. The primary goal was to introduce a digital pulse-width modulation generator program using a Hardware Description Language within a feedback loop. To enhance the buck converter's accuracy, the system's switching frequency was set to 20 kHz with an 8-bit counter, achieving a resolution of 0.390625% per clock cycle. An 8-bit parallel analog-to-digital converter provided feedback by measuring the output voltage and comparing it with the reference setpoint. The simulation model was developed using MATLAB/Simulink, while the Quartus II software was employed for controller programming. The resultant data was meticulously analyzed to assess the circuit's performance across various voltage and control parameters. To validate the proposed controller's effectiveness, a 400 W system prototype comprising a step-down transformer, rectifier, and buck converter was constructed and tested for voltage ranging from 24 to 72 V. Through FPGA-based digital control, this system demonstrated a voltage regulation accuracy of ±0.39 per clock cycle and the capability to continuously track and regulate the duty cycle with each clock trigger, ensuring precise control over the charging process.
Volume: 15
Issue: 5
Page: 4993-5002
Publish at: 2025-10-01

Tomographic image reconstruction enhancement through median filtering and K-means clustering

10.11591/ijece.v15i5.pp4395-4408
Nguyen Quang Huy , Nguyen Truong Thang
Ultrasound tomography is a powerful and widely utilized imaging technique in the field of medical diagnostics. Its non-invasive nature and high sensitivity in detecting small objects make it an invaluable tool for healthcare professionals. However, a significant challenge associated with ultrasound tomography is that the reconstructed images often contain noise. This noise can severely compromise the accuracy and interpretability of the diagnostic information derived from these images. In this paper, we propose and rigorously evaluate the application of a median filter to address and mitigate noise artifacts in the reconstructed images obtained through the distorted born iterative method (DBIM). The primary aim is to enhance the quality of these images and thereby improve diagnostic reliability. The effectiveness of our proposed noise reduction approach is quantitatively assessed using the normalized error evaluation metric, which provides a precise measure of improvement in image quality. Furthermore, to enhance the interpretability and utility of the reconstructed images, we incorporate a basic machine learning technique known as K-means clustering. This method is employed to automatically segment the reconstructed images into distinct regions that represent objects, background, and noise. Hence, it facilitates a clearer delineation of different components within the images. Our results demonstrate that K-means clustering, when applied to images processed with the proposed median filter method, effectively delineates these regions with a significant reduction of noise. This combination not only enhances image clarity but also ensures that critical diagnostic details are preserved and more easily interpreted by medical professionals. The substantial reduction in noise achieved through our approach underscores its potential for improving the accuracy and reliability of ultrasound tomography in medical diagnostics.
Volume: 15
Issue: 5
Page: 4395-4408
Publish at: 2025-10-01

Remote sensing applied to cocoa crop identification, a thematic review

10.11591/ijece.v15i5.pp4848-4855
Luisa Fernanda Cuellar-Escobar , Vladimir Henao-Céspedes
This article presents a thematic review of 25 publications related to the use of remote sensing techniques for the identification of cocoa crops from 2000 to 2023. Although the use of remote sensing techniques is widely used for mapping different covers because it is very useful in discriminating them, the generation of maps of cocoa crops presents challenges due to their spectral behavior similar to that of forests. This is because cocoa cultivation, being an agroforestry system that is developed in association with timber trees, causes the classification algorithms used to fail to differentiate between forest cover and cocoa crops. For this reason, this study seeks to investigate the different remote sensing techniques used in the mapping of cocoa crops, as well as an analysis of the structure of the publications highlighting the connections between countries and the factors that motivated the authors to research this crop.
Volume: 15
Issue: 5
Page: 4848-4855
Publish at: 2025-10-01

New approximations for the numerical radius of an n×n operator matrix

10.11591/ijece.v15i5.pp4732-4739
Amer Hasan Darweesh , Adel Almalki , Kamel Al-Khaled
Many mathematicians have been interested in establishing more stringent bounds on the numerical radius of operators on a Hilbert space. Studying the numerical radii of operator matrices has provided valuable insights using operator matrices. In this paper, we present new, sharper bounds for the numerical radius 1/4 ‖|A|^2+|A^* |^2 ‖≤w^2 (A)≤1/2 ‖|A|^2+|A^* |^2 ‖, that found by Kittaneh. Specifically, we develop a new bound for the numerical radius w(T) of block operators. Moreover, we show that these bounds not only improve upon but also generalize some of the current lower and upper bounds. The concept of finding and understanding these bounds in matrices and linear operators is revisited throughout this research. Furthermore, the study emphasizes the importance of these bounds in mathematics and their potential applications in various mathematical fields.
Volume: 15
Issue: 5
Page: 4732-4739
Publish at: 2025-10-01

Development of a smart portable cupping suction device with multi-mode control using PID regulation

10.11591/ijece.v15i5.pp5003-5018
Mohd Riduwan Ghazali , Mohd Ashraf Ahmad , Luqman Hakim Akmalmas
Cupping therapy is a well-established traditional treatment with various health benefits. However, existing electric cupping devices lack precise pressure control and portability which limit their usability across different skin types. This paper presents the development of a smart and portable cupping suction device with multi-mode functionality for dry, wet, and massage cuppings. Designed using an ESP32C3 XIAO microcontroller, a differential pressure sensor (MPX5100DP), and a motor driver (L293D) to enable real-time pressure regulation, the system incorporates a proportional-integral derivative (PID) to maintain a consistent suction performance at the negative pressures of -25, -35, and -45 kPa. The device was tested on different skin conditions of clean, less hairy, and slightly hairy surfaces. A real-time monitoring interface was additionally integrated using a web server to track the variation in pressure. Experimental results demonstrate effectiveness of the PID control system in achieving stable pressure with minimal fluctuations with enhanced user safety and comfort. It advances the medical devices for therapeutic automation by offering a portable, precise, and user-friendly cupping solution.
Volume: 15
Issue: 5
Page: 5003-5018
Publish at: 2025-10-01

Influence of the graph density on approximate algorithms for the graph vertex coloring problem

10.11591/ijece.v15i5.pp4714-4722
Velin Kralev , Radoslava Kraleva
This research explores two heuristic algorithms designed to efficiently solve the graph coloring problem. The implementation codes for both algorithms are provided for better understanding and practical application. The experimental methodology is thoroughly discussed to ensure clarity and reproducibility. The execution times of the algorithms were measured by running the test applications six times for each analyzed graph. The results indicate that the first algorithm generally produced better solutions than the second. In only two instances did the first algorithm produce solutions comparable to those of the second. The results reveal another trend: as the graph density exceeds 85%, the number of required colors increases significantly for both algorithms. However, even at a density of 95%, the number of colors required to color the graph's vertices does not exceed half the total number of vertices. As the graph density increases from 95% to 100%, the number of colors required to color the graph rises significantly. However, when the graph density exceeds 97%, both algorithms produce identical solutions.
Volume: 15
Issue: 5
Page: 4714-4722
Publish at: 2025-10-01

Enhancing internet of things network efficiency with clustering and random forest fusion techniques

10.11591/ijece.v15i5.pp4954-4964
Ahmed Gamal Soliman Soliman Deabes , Hani Attar , Jafar Ababneh , Hala Abd El-kader Mansour , Michael Nasief , Esraa M. Eid
The internet of things (IoT) is a key element of the future internet, enabling the acquisition and transfer of data to improve efficiency. One challenge in IoT networks is managing the energy consumption of nodes. IoT innovation constantly evolves dynamically, contributing significantly to sustainable cities and economies. Clustering techniques can help conserve energy and extend the operational lifespan of network nodes. Cluster heads (CH) manage all cluster member (CM) nodes within their group, establishing intra-cluster and inter-cluster connections. Enhancing the CH selection process can further prolong the network lifespan. Various algorithms aim to extend the active duration of IoT nodes and the overall network lifespan. A comparison of the five algorithms shows that one algorithm is better than the others in some cases. This paper discusses how fusion techniques using the random forest (RF) algorithm can enhance energy efficiency in IoT networks. Five algorithms are compared using RF, a robust machine-learning algorithm renowned for its ensemble learning capabilities. It selects the best one based on active nodes per round, residual energy for each round, and the average end-to-end delay.
Volume: 15
Issue: 5
Page: 4954-4964
Publish at: 2025-10-01

A solar-powered autonomous power system for aquaculture: optimizing dual-battery management for remote operation

10.11591/ijece.v15i5.pp4376-4386
Thomas Yuven Handaka Laksi , Levin Halim , Ali Sadiyoko
In Indonesia, growing fish consumption demands necessitate expanded, yet sustainable, fish production without sacrificing quality. The process of feeding and the quality of the surrounding water are important factors influencing fish quality. To address this, Parahyangan Catholic University's Fishery 4.0 project pioneers a unique technology that integrates water quality monitoring with a fish feeding feature. The design and implementation of an independent, reliable power module, which is fundamental to the functionality of this system, is at the focus of this research. This study shows that a designed power module adapted to the specific needs of Fishery 4.0 is feasible. The system powers all modules with a 12 V battery and is recharged with a solar panel. The battery can be charged to 95% capacity, yielding 8550 mAh from a 9000 mAh capacity. A UC-3906 charger IC controls the charging process, deliberately managing the parameters required for optimal battery charging. Particularly, when exposed to ideal solar radiation, the charger recharges a 9 Ah battery from 30% to full capacity in about 10 hours and 10 minutes. This study proposes a novel to battery management, which is critical for the operation of aquaculture equipment at isolated locations.
Volume: 15
Issue: 5
Page: 4376-4386
Publish at: 2025-10-01

Practical specification of the speech universe of the maximum power point tracking controller based on the asymmetrical fuzzy logic: a dynamic behavior study of the photovoltaic system

10.11591/ijece.v15i5.pp4355-4365
Ahmed Amine Barakate , Sami Choubane , Abdelkader Hadjoudja
In this paper, we present a procedure for extracting data from a stand-alone photovoltaic (PV) panel to program a maximum power point tracking (MPPT) controller based on the fuzzy logic (FL) method, aiming to optimize the performance of the photovoltaic system. Photovoltaic data acquisition enables the determination of the input and output speech universe for the MPPT controller using fuzzy logic. This method adapts to nonlinear systems without requiring a complex mathematical model. Additionally, it improves the performance of the photovoltaic system in both dynamic and steady-state conditions. To further enhance the method’s efficiency, an asymmetric membership function concept is proposed based on the dynamic behavior study of the photovoltaic system. Compared to the symmetric method, the asymmetric fuzzy logic controller achieves higher maximum power output and better tracking precision. This technology is essential for maximizing photovoltaic panel efficiency, a key requirement as solar energy gains prominence as a clean and renewable energy source.
Volume: 15
Issue: 5
Page: 4355-4365
Publish at: 2025-10-01

Discount factor-based data-driven reinforcement learning cascade control structure for unmanned aerial vehicle systems

10.11591/ijece.v15i5.pp4542-4554
Ngoc Trung Dang , Quynh Nga Duong
This article investigates the discount factor-based data-driven reinforcement learning control (DDRLC) algorithm for completely uncertain unmanned aerial vehicle (UAV) quadrotors. The proposed cascade control structure of UAV is categorized with two control loops of attitude and position sub-systems, which are established the proposed discount factor-based DDRLC algorithm. Through the analysis of the Bellman function's time derivative from two perspectives, a revised Hamilton-Jacobi-Bellman (HJB) equation including a discount factor is developed. Then, in the view of off-policy consideration, an equation is formulated to simultaneously solve the approximate Bellman function and approximate optimal control law in the proposed DDRLC algorithm with guaranteed convergence. According to the modified state variables vector, the development of the discount factor-based DDRLC algorithm in each control loop is indirectly implemented by transforming the time-varying tracking error model into the time invariant system. Finally, a simulation study on the proposed discount factor-based DDRLC algorithm is provided to validate its effectiveness. To validate the tracking performance of the quadrotor, four performance indices are considered, including IAE_p=3.0527, IAE_Ω=0.1175, ITAE_p=1.8408, and ITAE_Ω=0.0144, where the subscript p denotes position tracking error and Ω denotes attitude tracking error.
Volume: 15
Issue: 5
Page: 4542-4554
Publish at: 2025-10-01

Development and testing of a dedicated cooling system for photovoltaic panels

10.11591/ijece.v15i5.pp4387-4394
Omar Elkhoundafi , Rachid Elgouri
Solar energy is a viable alternative to fossil fuels, but its efficiency is limited by photovoltaic panel overheating, which causes a decrease in efficiency. This paper suggests a passive cooling method that incorporates aluminum heat sinks beneath the solar cells. This simple, low-cost device maximizes heat dissipation using natural convection. It requires no external energy. The goal is to provide a solution to the challenge of selecting an effective, sustainable, and flexible cooling system while considering technological, economic, and environmental constraints. Experimental results demonstrate that modules fitted with heatsinks experience an average 8.13 °C drop in temperature, as well as a 0.51 V rise in open-circuit voltage when compared to the reference panel. This increase demonstrates how well-designed passive solutions can dramatically improve the energy performance of solar panels. The study emphasizes the relevance of thermal design in photovoltaic system optimization and provides specific opportunities for the development of more efficient solar technologies, particularly in high-temperature situations.
Volume: 15
Issue: 5
Page: 4387-4394
Publish at: 2025-10-01
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