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29,922 Article Results

Design of a real-time prayer clock using geographic coordinates

10.11591/ijres.v14.i3.pp834-842
Massoum Noreddine‬‏ , Moulai Khatir Ahmed Nassim
Prayer times and calendar clock are a valuable system that relies on programs that we developed in Mikroc that allow to mathematically calculate these prayer times, which differ from one place (city) to another and from one day to another using geographical coordinates. The more precise these coordinates (latitude and longitude), the more precise the prayer times are. The research that we conducted was carried out using a 16F876A microcontroller that uses the 74HC595 circuit, an 8-bit serial input and parallel output shift register for storage. Outputs can be added to the microcontroller thanks to this. It is possible to manage this integrated circuit from three pins of our microcontroller.
Volume: 14
Issue: 3
Page: 834-842
Publish at: 2025-11-01

Exploring stock price portfolio clusters in foreign exchange markets

10.11591/ijeecs.v40.i2.pp735-744
Challa Madhavi Latha , S. Bhuvaneswari , K. L. S. Soujanya , A. Poongodai
This study explores a novel portfolio management approach dividing the currency pairs into clusters of periodic returns. The primary purpose is to improve diversification and risk-return ratios with currencies. This research studied USD, Euro, and Chinese Yuan to collect historical data from April 2012 to March 2022. The present study makes use of K-means clustering to find clusters of assets with similar return patterns, which constitute diversified portfolios. Optimized portfolio vs. benchmark portfolio performance was also evaluated based on critical performance measures like cumulative return, Sharpe ratio, and volatility. The clustering approach was also tested through sensitivity analysis to check how market-specific it is. The results suggest that more clustered portfolios outperform traditional benchmarks and provide a better risk-adjusted return. The conclusion drawn here from the findings is that portfolio segmentation is a superior approach because of risk management in ever-changing volatile markets and identifying situations that link currency pairs. This is beneficial for those investors and portfolio managers looking to maximize their foreign exchange (FOREX) investments by allowing greater visibility into how the market is functioning, which can, in turn, improve decision-making processes. According to the study, portfolio clustering substantially enhances a portfolio's return for the foreign exchange market.
Volume: 40
Issue: 2
Page: 735-744
Publish at: 2025-11-01

Improving recommendations with implicit trust propagation from ratings and check-ins

10.11591/ijeecs.v40.i2.pp814-828
Sara Medjroud , Nassim Dennouni , Mourad Loukam
This paper investigates how the propagation of implicit trust between users affects the quality of point-of-interest (POI) recommendations in location-based social networks (LBSNs). Through the analysis of user interactions via ratings and check-ins, this work proposes a recommendation model known as propagation of rating/check-in for implicit trust (PRCT). This model relies on two primary approaches: Similarity trust rating (STR), which utilizes user ratings, and similarity trust check-in (STC), which focuses on check-ins data. Both approaches employ trust propagation to enhance their similarity matrices between users. An evaluation of the PRCT model using the Yelp dataset shows that the STR approach surpasses other variants in terms of PRECISION and RECALL, while the STC approach demonstrates superior performance in terms of RMSE. Furthermore, while trust propagation in the PRCT model increases the density of its similarity matrices, it does not consistently enhance its PRECISION parameter. Only the similarity Jaccard check-in (SJC) and similarity cosine check-in (SCC) approaches show a significant improvement of this parameter. 
Volume: 40
Issue: 2
Page: 814-828
Publish at: 2025-11-01

Design and optimization of bail-shaped microstrip patch antenna for mid-band 5G application using a lightGBM model

10.11591/ijres.v14.i3.pp626-637
G. Vijayakumari , T. Annalakshmi
This study suggests a bail-shaped microstrip patch antenna designed for 5G applications. This antenna model operates in the 3.45 GHz wireless communication frequency range, which is a component of the so-called C-band (3.3 to 4.2 GHz), which is widely utilized for mid-band 5G deployments across the globe. Antenna size optimization is achieved at 31×28 mm2. On the patch, a slot is added to enhance the return loss features. The light gradient boosting machine (LightGBM) model for prediction acts as an objective function of the considered piranha foraging optimization algorithm (PFOA) to adjust the antenna's slot dimension, which will be used to optimize the slot width. In order to get a superior return loss value of around -39.90<-10 dB, the optimization approach that is provided seeks to achieve the ideal slot length. The proposed device exhibits remarkable radiation efficiency by partially grounding, with a peak gain of around 2.535 dBi at 3.45 GHz. A novel hybrid approach combines the LightGBM prediction model with the PFOA to fine-tune slot dimensions, achieving a superior return loss of -39.90 dB. The exclusivity of this effort is the incorporation of machine learning algorithms to attain significantly improved parameters.
Volume: 14
Issue: 3
Page: 626-637
Publish at: 2025-11-01

Chirp-pulsed eddy current testing for crack detection in low-carbon steel

10.11591/ijres.v14.i3.pp676-686
Dang-Khanh Le , Sy Phuong Hoang , Duc Minh Le , Phuong Huy Pham , Trung Hieu Trieu , Minhhuy Le
This paper introduces a signal processing feature for chirp-pulsed eddy current testing (C-PECT) to improve crack detection in low-carbon steel, a common material in maritime structures. While C-PECT is an established technique, inspecting ferromagnetic materials is challenging due to significant background noise from lift-off variations and material permeability. The novelty of this work lies in the proposal of a frequency-domain integration feature designed to suppress this noise. The method utilizes a chirp-pulse-excited probe with a Hall sensor to measure the magnetic field response. By integrating the signal's magnitude spectrum, the frequency feature effectively flattens the background and enhances the signal-to-noise ratio. Experimental validation on a low-carbon steel specimen with artificial cracks demonstrates the feature's superior performance in providing clear, high-contrast crack indications compared to a conventional time-domain analysis. The results indicate that this approach offers a simple, computationally efficient, and robust solution for the qualitative detection and localization of cracks, enhancing structural integrity assessments in noisy industrial environments.
Volume: 14
Issue: 3
Page: 676-686
Publish at: 2025-11-01

Economical design of WAMS through soft computing: co-optimal PMU placement and communication infrastructure

10.11591/ijres.v14.i3.pp649-658
Banumalar Koodalsamy , Vanaja Narayanasamy , Muralidharan Srinivasan
Recently, utilities have developed and deployed wide area measurement systems (WAMS) to improve the electricity grid's ability to monitor, manage, and defend itself. In a typical WAMS setup, multiple measuring devices, communication systems, and energy management systems work together to gather, transmit, and then analyze data. Although there is substantial interdependence among these three capabilities, most research treats them independently. The work presented here minimizes the total cost of the communication infrastructure (CI) by taking into account the price of phasor measurement units (PMUs) and the placement of a phasor data concentrator (PDC) at the same time. The optimum CI and PDC placement has been built with Steiner tree optimization's help. There have also been practical operating scenarios of more realistic working conditions containing pre-installed PMU, pre-installed fiber optic and N-1 contingency. The optimization hurdle has been overcome by utilizing the binary firefly algorithm (BFFA), which has undergone testing on IEEE 14, 30, and 118 bus systems to demonstrate its effectiveness. A comparison has been offered, and it clearly demonstrates the proposed approach's superiority over previously published articles.
Volume: 14
Issue: 3
Page: 649-658
Publish at: 2025-11-01

Calibration and measurement of cotton moisture using real time system with statistical analysis

10.11591/ijres.v14.i3.pp687-695
Suyog Pundlikrao Jungare , Prasad V. Joshi , M. K. Sharma
Accurate moisture measurement in cotton is essential for maintaining fibre quality, ensuring safe storage, and supporting efficient processing. Improper moisture levels can result in microbial growth, fibre degradation, or mechanical damage during ginning and spinning operations. This study presents the development of a real-time moisture measurement system for cotton used in the ginning industry. The system operates on the principle of electrical resistance change to detect varying moisture levels. Cotton samples were categorized into four types: wet, new, old, and dry. The system is designed for use on moving or in-process cotton. To evaluate system performance, linear discriminant analysis (LDA), and hierarchical clustering analysis (HCA) were employed for classification. Partial least squares (PLS) regression was used to calibrate the system against the standard oven-drying method (ASTM D2495-07). Further, artificial neural network (ANN) modelling was applied for moisture prediction. The system successfully discriminated between the cotton types, achieving over 85% explained variance in classification. ANN-based prediction aligned closely with the standard reference method. The developed system provides a low-cost, fast, and real-time solution for moisture measurement in cotton, with strong potential for industrial application.
Volume: 14
Issue: 3
Page: 687-695
Publish at: 2025-11-01

Development of a blockchain-based electronic voting system utilizing national identification number

10.11591/ijres.v14.i3.pp810-820
Olabode Idowu- Bismark , Oluwadamilola Oshin , Emmanuel Adetiba
Traditional voting methods in Nigeria face numerous challenges, including logistic issues, security concerns, and allegations of fraud, which undermine public trust. This work develops a blockchain-based electronic voting system (EVS) that leverages the national identification number (NIN) for biometric verification to address these issues. The research identifies the limitations of current blockchain voting solutions, such as implementation complexity, scalability issues, user adoption resistance, and cybersecurity threats and provide a more secure and user-friendly alternative. The system integrates blockchain technology with biometric verification to create an immutable, transparent, and secure voting process. The methodology involves designing a system architecture that includes a blockchain network, an NIN verification module, and a user interface (UI). Users register using their NIN, authenticate themselves, and cast their votes, which are then encrypted and recorded on the blockchain. The system's functionality was tested using tools like Ganache for local blockchain development, MetaMask for Ethereum wallet integration, and Solidity for writing smart contracts. Results from the implementation indicate significant improvements in security, transparency, and user accessibility compared to traditional voting systems. The user authentication test achieved a 100% valid login success rate and 0% invalid login attempts. Meanwhile, the voting test accuracy was 100%.
Volume: 14
Issue: 3
Page: 810-820
Publish at: 2025-11-01

Critical success factor blockchain technology in renewable energy: systematic literature review

10.11591/ijres.v14.i3.pp821-833
Inayatulloh Inayatulloh , Thoyyibah T.
In recent years, blockchain technology has garnered considerable interest in the renewable energy sector. Nonetheless, scholars have yet to investigate the comprehensive assessment of critical success factors (CSFs) for the implementation of blockchain technology in renewable energy. Furthermore, the current research lacks a stage framework or a standardized set of CSFs for blockchain technology. This review study seeks to establish a stage framework and identify a set of common CSFs for the effective adoption of blockchain technology by examining published materials pertinent to the topic under investigation. This evaluation employs a systematic literature review and scientific mapping methodology to objectively ascertain a collection of CSFs. We examined 65 journal articles from the Scopus database and Google Scholar, concentrating on prominent journals, keywords, countries/regions, and documents within the CSF domain of blockchain technology in renewable energy. The findings indicate that nations including China, Australia, the United States, and Germany have made the most significant contributions to this field. Among the 20 CSFs, the foremost five are regulation, integration with current systems, scalability, and security. The proposal delineates four principal research gaps and prospective research trajectories: environmental effect assessment, standardization, user experience and interface design, and management control. The insights and CSF checklist for blockchain technology will facilitate successful exploration and implementation in renewable energy.
Volume: 14
Issue: 3
Page: 821-833
Publish at: 2025-11-01

Parallel graph algorithms on a RISCV-based many-core

10.11591/ijres.v14.i3.pp843-854
Ashuthosh Moolemajalu Ravikumar , Aakarsh Vinay , Krishna K. Nagar , Madhura Purnaprajna
Graph algorithms are essential in domains like social network analysis, web search, and bioinformatics. Their execution on modern hardware is vital due to the growing size and complexity of graphs. Traditional multi-core systems struggle with irregular memory access patterns in graph workloads. Reduced instruction set computer–five (RISC-V)-based many-core processors offer a promising alternative with their customizable open-source architecture suitable for optimization. This work focuses on parallelizing graph algorithms like breadth-first search (BFS) and PageRank (PR) on RISC-V many-core systems. We evaluated performance based on graph structure and processor architecture, and developed an analytical model to predict execution time. The model incorporates the unique characteristics of the RISC-V architecture and the types and numbers of instructions executed by multiple cores, with a maximum prediction error of 11%. Our experiments show a speedup of up to 11.55× for BFS and 7.56× for PR using 16 and 8 cores, respectively, over single-core performance. Comparisons with existing graph processing frameworks demonstrate that RISC-V systems can deliver up to 20× better energy efficiency on real-world graphs from the network repository.
Volume: 14
Issue: 3
Page: 843-854
Publish at: 2025-11-01

Performance analysis of REST API in a real-time IoT-based vehicle monitoring system

10.11591/ijres.v14.i3.pp766-784
Rizki Ananta Dwiyanto , Giva Andriana Mutiara , Marlindia Ike Sari
This study studies the design and implementation of a REST API and its performance analysis for an internet of things (IoT)-based vehicles monitoring system. This system incorporates brake pad sensors, a tire pressure monitoring system (TPMS) for assessing tire pressure and temperature, light detection and ranging (LIDAR) for measuring tire thickness, and radio frequency identification (RFID) for tire identification. Data is gathered using an ESP32 microcontroller and transmitted in real-time to the server via a REST API over a wireless network. The JSON Web Token (JWT) authentication mechanism is employed to ensure data security. Testing indicates that this system has an average response time of 4–11 ms, with optimal performance recorded at 3.93 ms for the RFID sensor and peak performance at 9.19 ms for the LIDAR sensor. Load testing with 100 concurrent users demonstrates that the system maintains stability with a 100% data delivery success rate. Authentication testing demonstrates that the API is accessible solely with a valid token, hence preventing unauthorized access. This study's results demonstrate that integrating REST API with IoT monitoring systems facilitates real-time vehicle monitoring, enhances maintenance efficiency, and offers viable solutions for future predictive maintenance systems.
Volume: 14
Issue: 3
Page: 766-784
Publish at: 2025-11-01

Wideband frequency-reconfigurable antenna for sub-6 GHz wireless communication

10.11591/ijres.v14.i3.pp614-625
Tejal Tandel , Samir Trapasiya
This paper presents a compact dual-band frequency-reconfigurable monopole antenna for sub-6 GHz wireless applications. Using a single PIN diode, the antenna switches between 2.7 GHz and 3.9 GHz bands, achieving bandwidths of 472 MHz and 1130 MHz, respectively, with peak gains up to 1.65 dB. The demand for smaller devices has driven the development of compact antennas capable of operating across multiple bands. The main benefits of this antenna include its compact size, enhanced bandwidth, and design simplicity, which is achieved by integrating slots into the patch and introducing a tiny slot etched over the ground plane. The antenna is created using an FR4 material with a thickness of 1.6 mm and dimensions of 25×15 mm². The antenna prototype was fabricated and tested to validate its performance. Simulation optimization reveals that the antenna operates with a gain of 0.9–1.65 dB and a bandwidth of (472–1130 MHz). The design also achieves a VSWR of less than 1.3 and a radiation efficiency between 74% and 78%. The performance enhancement of the reconfigurable antenna was fine-tuned utilizing microwave solvers in both computer simulation technology (CST) and advance design system (ADS).
Volume: 14
Issue: 3
Page: 614-625
Publish at: 2025-11-01

A k-nearest neighbors algorithm for enhanced clustering in wireless sensor network protocols

10.11591/ijres.v14.i3.pp605-613
Adil Hilmani , Yassine Sabri , Abderrahim Maizate , Siham Aouad , Fouad Ayoub
Wireless sensor networks (WSNs) are small, autonomous, battery-powered nodes capable of sensing, storing, and processing data, while communicating wirelessly with a central base station (BS). Optimizing energy consumption is a major challenge to extend the lifetime of these networks. In this study, we propose an innovative approach combining the k-nearest neighbors (KNN) algorithm with hierarchical and flat routing protocols to improve node selection and clustering in three key protocols: low-energy adaptive clustering hierarchy (LEACH), threshold-sensitive energy efficient sensor network protocol (TEEN), and hybrid energy-efficient distributed clustering (HEED). Concretely, KNN is used to rank nodes based on their spatial and energy proximity, thus optimizing the choice of cluster heads (CHs) and reducing long and costly connections. Simulations show a reduction in the inter-CH distance, a decrease in overall energy consumption, and an extension of the network lifetime compared to conventional versions of the protocols. These improvements not only help increase operational efficiency, but also enhance communications stability and security, providing a robust and sustainable solution for critical WSN applications.
Volume: 14
Issue: 3
Page: 605-613
Publish at: 2025-11-01

Classification metrics for pet adoption prediction with machine learning

10.11591/ijres.v14.i3.pp638-648
Islamiyah Islamiyah , Muhammad Rivani Ibrahim , Suwardi Gunawan , Dyna Marisa Khairina , Erniati Erniati
Millions of pets are temporarily placed in shelters, making it challenging for shelters to ensure pets find permanent homes. High adoption rates are crucial for animal welfare and the sustainability of shelter operations. This study aims to identify key factors influencing pet adoption and create classification metrics using five machine learning (ML) classification model approaches to predict the likelihood of pet adoption, to find the best model performance for each analysis. The dataset was obtained from several features related to animal characteristics and adoption conditions. The results of the study present classification of metric models that indicate decision tree and random forest (RF) as the most effective models with superior performance in terms of accuracy and class separation ability. Further research provides initial exploration of ML models that are not only limited to classification models but also model integration into internet of things (IoT) systems for the implementation of a pet adoption prediction system based on ML inference. The implementation of ML classification models helps improve the efficiency of animal adoption programs and optimize shelter operations, ultimately increasing the chances of successful pet adoption. The results of the study provide insights into factors influencing pet adoption, minimizing the length of stay (LOS) in shelters, and contribute to practitioners/ researchers as a reference for exploring new related factors and exploring the performance of ML models, especially classification models.
Volume: 14
Issue: 3
Page: 638-648
Publish at: 2025-11-01

Implementation of hardware security module using elliptic curve cryptography for cyber-physical system

10.11591/ijres.v14.i3.pp705-716
B. Muthu Nisha , J. Selvakumar
The vision of sustainable development goal 9 (SDG 9) is realized through the integration of innovative technologies in the cyber-physical system (CPS). This work focuses on a smart network meter (SNM) application, designed to manage the extensive big data analytics required for processing and analyzing vast amounts of aggregated data in a short period. To address these demands, an advanced explicitly parallel instruction computing (AEPIC) approach is employed, leveraging a multi-core hardware security module (HSM) built on the elliptic curve cryptography (ECC) algorithm. Implementing the algorithm on various field programmable gate arrays (FPGAs) ensures adaptability to different hardware configurations, delivering scalable and optimized performance for big data aggregation in SNM applications. The proposed module showcases exceptional performance in design analysis. The Virtex-7 FPGA demonstrates excellent suitability for big data analytics in smart network applications, with dynamic power consumption accounting for 55% of total power and an on-chip power of 0.542 watts.
Volume: 14
Issue: 3
Page: 705-716
Publish at: 2025-11-01
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