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31,128 Article Results

Dual view explainability-aware log preprocessing for robust anomaly detection toward ER-CyRIS

10.11591/ijeecs.v43.i3.pp871-879
Fathoni Mahardika , Ema Utami , Kusrini Kusrini , Ferry Wahyu Wibowo
Machine learning based intrusion detection can achieve strong benchmark performance yet remain fragile under operational telemetry changes. This paper proposes a dual-view, explainability-aware log preprocessing layer for robust anomaly detection toward ER-CyRIS. The novelty is the use of dynamic-token preservation together with feature stability score (FSS), which turns SHapley additive exPlanations (SHAP)-ranking stability into a preprocessing-level evaluation criterion rather than a post-hoc explanation only. The layer preserves structural log patterns and contextual dynamic tokens, and is evaluated through detection performance, noise degradation, and SHAP-ranking stability. A leakage-controlled ablation on HDFS, BGL, CICIDS2018, and UNSW-NB15 shows that the CICIDS2018 baseline reached F1 = 0.9999 but degraded by 68.1% for XGBoost and 93.9% for random forest under small Gaussian noise. Contextual preprocessing reduced degradation to 58.7%, 54.9%, and 53.6% in selected settings. FSS reached 100% for XGBoost on HDFS and CICIDS2018. The results show that preprocessing mitigates, but does not eliminate, operational brittleness.
Volume: 43
Issue: 3
Page: 871-879
Publish at: 2026-09-01

Automated recognition of Thai fabric patterns using transfer learning with ResNet-50

10.11591/ijeecs.v43.i3.pp847-856
Kittiya Poonsilp , Pijitra Jomsri , Dulyawit Prangchumpol , Thammarat Panityakul
Traditional Thai fabric patterns are valuable cultural heritage, but expert knowledge of these patterns is declining. This study uses a convolutional neural network (CNN) with transfer learning (ResNet-50) to classify traditional Thai fabric patterns automatically. We collected 961 images across 19 pattern categories, split into training (57%), validation (11%), and test (32%) sets. Using ImageNet pre-trained weights and progressive fine-tuning, the model achieved 99.68% test accuracy with macro-averaged F1-score of 99.35%. Ablation studies validated our approach: augmentation improved accuracy by 2.26%, fine-tuning outperformed frozen backbone by 4.84%, and backbone comparison showed ResNet-50 achieves higher F1-score than MobileNetV2 while MobileNetV2 offers 90% parameter reduction for mobile deployment. Controlled stress tests demonstrated robustness under image degradations typical of smartphone photography. Unlike previous studies using controlled conditions, our dataset includes real-world variations. These results show that transfer learning with small datasets can match expert-level pattern recognition for cultural heritage preservation.
Volume: 43
Issue: 3
Page: 847-856
Publish at: 2026-09-01

Low-cost BLDC drive with PBBO-tuned FOPID controller for enhanced speed regulation and torque ripple reduction

10.11591/ijeecs.v43.i3.pp956-964
Pandi Maharajan M. , Rohini G. , Ravindran Ramkumar , Dharani Kumar Narne
Torque ripple (TR) minimization in brushless DC (BLDC) motors has become a critical research focus due to its direct impact on drive performance, efficiency, and reliability. Conventional BLDC drives typically employ large DC-link capacitors, which increase system cost and weight and are highly sensitive to operating temperature, thereby reducing lifetime. To address these limitations, this work proposes a low-cost capacitor-based BLDC drive integrated with a torque ripple compensation (TRC) technique and optimized control using the probabilistic biogeography-based optimization (PBBO) algorithm. The PBBO method is employed to tune the parameters of a fractional-order proportional-integral-derivative (FOPID) controller, ensuring effective speed regulation and TR reduction. By probabilistically refining migration and emigration rates, PBBO enhances convergence and eliminates redundant species movements, leading to superior controller parameter optimization. Simulation studies validate the proposed PBBO-FOPID approach, demonstrating significant improvements in TR reduction and speed control compared to conventional controllers such as DGOA-FOPID and spider web-based controller (SWC). Results confirm that the PBBO-FOPID controller achieves smoother torque response, reduced ripple, and enhanced speed regulation, establishing it as a cost effective and high-performance solution for BLDC motor drives.
Volume: 43
Issue: 3
Page: 956-964
Publish at: 2026-09-01

Automated smart handbag with enhanced women's safety using cutting edge technology

10.11591/ijra.v15i3.pp669-677
Vijayaraja Loganathan , Dhanasekar Ravikumar , Ashish Ragavendra Nattamai Uthayakumar , Arulmurugan Nagarajan Renukadevi , Rishikeshwaran Balamurugan Rani , Rupa Kesavan
Women’s safety has been an area of concern, especially in public places where timely assistance cannot be provided. To mitigate this problem, this paper proposes an intelligent handbag-based women’s safety system that utilizes the concept of biometric identification, location tracking, and edge computing-based AI threat verification. The proposed system, unlike other traditional women’s safety devices that rely on GPS-GSM for emergency alerts and are more likely to send false alarms, utilizes fingerprint identification for secure and authorized use, along with YOLO v3 vision model on an ESP32-CAM for threat verification. Upon failure in the authentication process or threat detection, the system sends an SOS message with the current location via GSM with the help of GPS coordinates. The system achieves an emergency response time of 33 seconds, primarily limited by GPS acquisition delay. The results confirm the effectiveness and applicability of the proposed system in providing an intelligent emergency response system for women’s safety.
Volume: 15
Issue: 3
Page: 669-677
Publish at: 2026-09-01

A self-lift quadratic boost converter topology for efficient marine propulsion drive systems

10.11591/ijpeds.v17.i3.pp1852-1858
Subbulakshmy Ramamurthi , Dhandapani Meena , Velmurugan Palani , Shobana Devendiran , S. Ganesh Kumaran
This paper proposes a high-gain self-lift quadratic boost converter (SL-QBC) topology tailored for efficient marine propulsion drive systems. The presented converter architecture incorporates a self-lift circuit embedded within a quadratic boost stage to achieve significant voltage gain while maintaining low component stress and high conversion efficiency. Specifically, the converter is capable of boosting a low input voltage of 45 V to a high output voltage of 473 V. The high-voltage output is then fed to the marine propulsion system through a three-phase, three-level neutral point clamped (NPC) inverter, which drives a three-phase induction motor. Designed to interface low-voltage DC sources such as batteries, photovoltaic panels, or fuel cells with high-power marine propulsion motors, the proposed topology offers a compact and cost-effective solution for electric and hybrid marine applications. The self-lift mechanism enhances voltage boosting capability by leveraging additional inductive and capacitive energy transfer paths. The topology ensures continuous current operation, reduced voltage ripple, and improved dynamic response, all of which are critical for smooth and reliable marine drive performance. Simulation results validate the converter’s effectiveness, confirming its potential as a robust and efficient power conditioning stage in next-generation marine energy systems.
Volume: 17
Issue: 3
Page: 1852-1858
Publish at: 2026-09-01

Multi-objective planning of distributed resources (PV and SVC) with NSGA-II for radial networks: application to the IEEE 33-bus test system

10.11591/ijape.v15.i3.pp1243-1252
Hassane Ousseyni Ibrahim , Abdoul Malik Maman Issaka , Moussa Gonda , Arouna Oloulade , François-Xavier Fifatin
The quality of electricity supply in distribution networks is critically dependent on minimizing active power losses and ensuring voltage stability. This study proposes a unified multi-objective optimization approach for the simultaneous placement and sizing of a photovoltaic (PV) source and a static var compensator (SVC) in radial networks. The non-dominated sorting genetic algorithm II (NSGA-II) is employed as the robust methodology to generate the Pareto optimal front, effectively exploring the trade-offs between two conflicting objectives: active loss minimization and voltage profile improvement. Unlike sequential or single-unit optimization strategies, this joint optimization framework is the key novelty, leveraging the specific physical interaction between PV active power injection and SVC-based dynamic reactive support to maximize overall network efficiency. Simulations are performed on the standard IEEE 33-bus test system. The results demonstrate that the optimal and coordinated integration of a 0.97 MW PV system at bus 14 and a 1.32 MVAr SVC at bus 30 yields superior electrical performance. Specifically, the system achieves a substantial active power loss reduction of 62.53% and decreases the voltage deviation index from 0.117 p.u. to a minimum of 0.0169 p.u., confirming the effectiveness of the proposed NSGA-II approach for comprehensive distributed resource planning.
Volume: 15
Issue: 3
Page: 1243-1252
Publish at: 2026-09-01

Association between occupational NO₂ exposure and hypertension risk: a PRISMA-based systematic review with risk-of-bias assessment

10.11591/ijphs.v15i3.27111
Ayudhia Rachmawati , Morrin Choirunnisa Thohira , Muhammad Aidil Fitrah , Vivi Filia Elvira
Nitrogen dioxide (NO₂) is a major air pollutant generated from fossil fuel combustion in transportation and industrial activities and is associated with adverse health effects. Prolonged exposure to NO₂ may induce chronic inflammation and endothelial dysfunction, which contribute to the development of hypertension. This study aimed to systematically review the association between NO₂ exposure and the incidence of hypertension among workers. The review was conducted in accordance with PRISMA guidelines, with literature searches performed in Google Scholar, PubMed, and ScienceDirect for publications from 2020 to 2025. Inclusion criteria comprised full-text articles in English or Indonesian employing observational study designs (cross-sectional, cohort, case-control, or ecological) and involving workers in both formal and informal sectors. Eligible studies examined NO₂ exposure as the independent variable and hypertension as the outcome. Of 2,051 records identified, five studies met the inclusion criteria, originating from China and Nigeria. Risk of bias was assessed using the office of health assessment and translation (OHAT) risk of bias tool. The findings demonstrated a consistent association between NO₂ exposure and an increased risk of hypertension, particularly in poorly ventilated work environments. These results underscore the importance of improving workplace air quality management, strengthening exposure monitoring, and implementing preventive occupational health strategies.
Volume: 15
Issue: 3
Page: 868-878
Publish at: 2026-09-01

Integrative functional annotation of rheumatoid arthritis risk genes using a multi-database bioinformatics approach

10.11591/ijphs.v15i3.27002
Muhammad Nuh , Lolita Lolita
Rheumatoid arthritis (RA) is an autoimmune disease involving the interaction of genetic and immunological factors. Genome-wide association studies (GWAS) have identified many RA risk loci, but the biological mechanisms linking genetic variation to disease pathogenesis are not yet fully understood. This study aims to prioritize RA candidate genes through a multi-database bioinformatics approach. SNPs significantly associated with RA were obtained from the GWAS catalog, followed by linkage disequilibrium (LD) screening and functional annotation to identify missense variants. The data were integrated with cis-expression quantitative trait loci (cis-eQTL) information, gene ontology (GO) annotation, and Kyoto Encyclopedia of Genes and Genomes (KEGG) molecular pathway mapping. Genes with a total score ≥2 were classified as RA risk genes. A total of 3.145 RA-significant SNPs were identified, of which 58 were missense variants that could potentially affect protein function. The integration of cis-eQTL and functional annotation resulted in a number of candidate genes with the highest scores (score = 4), where TYK2, IL23R, and IRAK1 were identified as priority RA genes in the main immune pathways, namely JAK-STAT signaling, IL-23/Th17 axis, and Toll-like receptor-NF-κB signaling. These findings demonstrate that this multi-database-based bioinformatics approach successfully identifies RA candidate genes with strong biological relevance.
Volume: 15
Issue: 3
Page: 848-859
Publish at: 2026-09-01

Empowering disaster volunteers through a web-based information system for health workforce and logistics coordination

10.11591/ijphs.v15i3.26973
Emmelia Kristina Hutagaol , Afif Wahyudi Hidayat , Nico Suwarno , Nurali Nurali , Joao Manuel Correia Ximenes
Digital transformation plays a critical role in strengthening disaster management systems, particularly in disaster-prone countries such as Indonesia. Despite the availability of several government-led digital platforms, limited systems integrate volunteer coordination, health workforce mapping, and logistics tracking within a unified framework. This study aimed to develop and evaluate a web-based information system designed to empower disaster volunteers by integrating volunteer profiling, healthcare human resource availability, logistics documentation, and public education features. A mixed-methods descriptive analytical design was employed. Qualitative data were collected through in-depth interviews to identify system requirements and operational challenges, while quantitative data were obtained from structured questionnaires completed by 71 of 75 health-background from TAGANA Rajawali Indonesia Foundation members and at least one disaster respon experience. Descriptive non-parametric analysis informed system design and feature prioritization. Results showed that 100% of respondents supported the development of a digital coordination platform, 94.7% preferred WhatsApp integration for communication, and 86.7% were willing to contribute as digital resource persons for public education. The developed system integrates real-time manpower mapping, logistics tracking, donation management, multimedia documentation, and reporting dashboards. This model addresses a critical gap in volunteer-centered digital disaster management and strengthens community-based preparedness by improving coordination efficiency, transparency, and public health resilience.
Volume: 15
Issue: 3
Page: 879-886
Publish at: 2026-09-01

Campus life adaptation and dietary patterns among first-year health science students in Indonesia: a cross-sectional study

10.11591/ijphs.v15i3.27000
Rukmoyo Endrawan , Daning Widi Istianti
Adaptation to campus life can be a challenging process for new students and may influence health-related behaviors, including dietary patterns. A preliminary study involving five first-year students showed that they experienced difficulties managing their dietary patterns during their first semester. However, evidence regarding the relationship between adaptation to campus life and dietary patterns among first-year health students in Indonesia remains limited. This study employed a correlational design with a cross-sectional approach and involved 36 respondents. Data were collected using the Student Adaptation to College Questionnaire (SACQ) and the Adolescent Food Habits Checklist (AFHC) and were analyzed using Spearman’s rho correlation test. Most respondents were female (81%), and 69% were in the adolescent age group. The majority of respondents demonstrated a moderate level of adaptation to campus life (92%) and reported healthy dietary patterns (92%). A significant positive correlation was found between adaptation to campus life and dietary patterns (p < 0.001, r = 0.734), indicating that students with higher levels of adaptation tended to have healthier dietary patterns. These findings suggest that institutions should provide campus-based health promotion programs, including student services, counseling, stress management programs, and dietary education.
Volume: 15
Issue: 3
Page: 831-838
Publish at: 2026-09-01

Effectiveness and acceptability of a digital early warning system for gestational diabetes management: a quasi-experimental study in Lampung Province

10.11591/ijphs.v15i3.27139
Aprina Aprina , Anita Anita , Titi Astuti
Despite growing evidence supporting digital health interventions for gestational diabetes mellitus (GDM), no study has evaluated the acceptability and effectiveness of such interventions across geographically heterogeneous healthcare settings in low-resource contexts, where disparities in infrastructure and connectivity may critically influence outcomes. This study addresses this gap by introducing and evaluating the Early Warning System for Gestational Diabetes Mellitus (EWSDMG), a novel digital application uniquely designed to function across diverse geographical conditions. A quasi-experimental one-group pre-test post-test design was employed with 200 GDM-diagnosed pregnant women across four sites in Lampung, Indonesia, representing urban, remote, coastal, and rural settings. Technology acceptability was measured using the System Usability Scale (SUS), while knowledge, adherence, and glycemic profiles were assessed before and after 8 weeks of intervention. The overall SUS score was 77.9 ± 6.4 (Good/Acceptable), with urban settings scoring highest (82.4 ± 5.2). Knowledge and adherence scores increased significantly by 26.27 and 24.35 points, respectively (p < 0.001). Fasting and 2-hour post-prandial glucose decreased by 13.3 mg/dL (p = 0.002) and 22.2 mg/dL (p = 0.001), respectively. SUS scores strongly correlated with glycemic improvement (r = 0.642, p < 0.001). This study provides the first evidence that a single digital GDM intervention can achieve consistent acceptability and clinical effectiveness across heterogeneous geographical settings, offering a scalable model for equitable GDM management in resource-limited regions.
Volume: 15
Issue: 3
Page: 794-801
Publish at: 2026-09-01

Immersive technology in English language learning: a bibliometric analysis

10.11591/ijere.v15i4.37947
Zhou Bo , Lim Seong Pek , Nahdia Kabir , Mohamed Bouteraa , Asna Asna
This bibliometric analysis, drawing on data from the Web of Science (WoS) core collection, explores the expanding role of immersive technologies in English language education. Virtual reality (VR) and augmented reality (AR) have shown strong potential to improve learner motivation, engagement, and communicative competence, yet their integration into formal English language settings remains uneven. By analyzing 248 peer-reviewed articles published between 2021 and 2025, this study finds significant trends, influential contributors, and emerging areas of interest within the field. The findings show a steady increase in publications and citations, reflecting growing recognition of the educational value of immersive environments. Prominent themes include emotional engagement, lowered language anxiety, and improved performance in vocabulary, speaking, listening, and cultural understanding. Much of the literature underlines authentic and situated learning, VR-based interactive environments, VR-supported problem-based learning, and AR-assisted vocabulary development. The analysis also identifies leading countries, with China and the United States producing the largest share of research, a pattern supported by strong institutional participation worldwide. These insights help guide educators and policymakers as they consider how to bring immersive technologies into English instruction. The study also establishes a foundation for future research on effective, engaging, and sustainable immersive language learning practices. Overall, these findings clarify how research on immersive technologies in English language education has evolved between 2021 and 2025 and identify influential studies and key contributors. They also point to persisting gaps, such as equity, teacher readiness, and cognitive-load–informed design, that warrant further investigation.
Volume: 15
Issue: 4
Page: 3623-3635
Publish at: 2026-08-01

Rethinking computer-based examinations in higher education: psychological, technical, and pedagogical challenges from students’ learning experience and future directions

10.11591/ijere.v15i4.39228
Ahmad Adnan AlZyoud , Eman Mohammad Qudah
The swift adoption of computer-based examinations (CBEs) in higher education has revolutionized assessment methods; nonetheless, there is a lack of thorough research investigating the psychological, technical, and pedagogical experiences of students using these systems. This research explores the various challenges associated with CBEs at Yarmouk University and assesses their influence on students’ learning experiences. A cross-sectional quantitative survey was conducted among 545 undergraduate students from various academic fields during the first semester of the 2025–2026 academic year. Both descriptive and inferential analyses were performed to evaluate students’ perceptions. Research shows a moderate level of acceptance for CBEs, but notable worries remain. The main source of stress was found to be technical reliability, often overshadowing worries about educational content. The one-way navigation aspect was recognized as a significant obstacle, which restricted students’ ability to review answers and added to cognitive strain and hasty decision-making. Furthermore, a significant gap in feedback was noted, as students mostly viewed the system as a tool for grading rather than a resource for ongoing learning. The research finds that successful digital assessment necessitates not just operational effectiveness but also adaptable design, alignment with pedagogical goals, and valuable feedback systems. Practical implications involve rethinking navigation elements, improving technical support, and offering focused training for faculty.
Volume: 15
Issue: 4
Page: 2861-2873
Publish at: 2026-08-01

English medium instruction in Jordanian medical education: a systematic review

10.11591/ijere.v15i4.39643
Hassan Mohammad Bani-Issa , Norsofiah Abu Bakar , Muhammad Zaid Daud , Jong Hui Ying , Hytham M. Bany Issa
English-medium instruction (EMI) dominates Jordanian medical education, yet its equity implications and consequences for assessment validity remain poorly evidenced, particularly after the disruptions of the COVID-19 pandemic. Following preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 guidelines, this review searched Scopus, Web of Science, ERIC, and PubMed for peer-reviewed work published between 2000 and 2024. A total of 34 studies met inclusion criteria after mixed methods appraisal tool (MMAT) quality appraisal and were analyzed through thematic synthesis. The evidence reveals a structural paradox: EMI supports international academic integration while disadvantaging students from Arabic-medium secondary schools by conflating English proficiency with medical competence. The lexical and morphological complexity of medical English increases cognitive demands and became more pronounced during pandemic-related online teaching. Students rely on code-switching and morphological analysis as coping strategies, but neither is recognized in policy or assessment. The review delivers the first PRISMA-aligned synthesis of EMI in Jordanian medical education, proposes the Jordanian Medical English Corpus (JoMEC) as a corpus-based diagnostic for measuring lexical burden, and reframes EMI equity as a measurable issue of assessment validity rather than a normative concern alone. Findings support bilingual scaffolding and validity-oriented assessment reform to advance equity in medical education across Jordan and comparable Middle East and North Africa (MENA) contexts.
Volume: 15
Issue: 4
Page: 3204-3214
Publish at: 2026-08-01

Determinants of entrepreneurial intentions of private university students in Thailand

10.11591/ijere.v15i4.39455
Nithima Yuenyong , Tanpat Kraiwanit , Ekaphot Congkrarian
The growing interest in student entrepreneurship, research has yet to comprehensively examine both internal and external determinants of startup intentions among private university undergraduates in Thailand, a context shaped by rapid digital transformation and national innovation priorities. This study investigates the factors predicting entrepreneurial intentions among 400 undergraduate students at private universities in Pathum Thani, Thailand. Using a quantitative research design, data were collected via a validated structured questionnaire and analyzed through descriptive statistics and stepwise multiple regression. Five factors significantly predicted startup entrepreneurial intention: financial resources, entrepreneurial skills, prior experience, economic conditions, and technological factors, collectively explaining 60.3% of the variance. Financial resources and entrepreneurial skills emerged as the strongest predictors, while political-legal, socio-cultural, and environmental factors were not significant predictors. The study concludes that entrepreneurial intention is shaped by the interplay between individual competencies and contextual enablers. These findings call for universities to strengthen entrepreneurship education across all faculties and for policymakers to improve students' access to financial resources and startup support mechanisms.
Volume: 15
Issue: 4
Page: 3111-3123
Publish at: 2026-08-01
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