IJACSA Vol. 16 Issue 10 (2025)

1

AI-Assisted Workflow Optimization and Automation in the Compliance Technology Field

Author 1: Zhen Zhong

Against the backdrop of digital transformation and stricter regulation, enterprise compliance work demands higher efficiency and accuracy. The auxiliary compliance process has become an important entry point for optimizing the compliance system due to its strong transactional nature and high degree of repetition. This study focuses on the process characteristics… Read full abstract & cite →

Compliance technology auxiliary process process optimization automation

Abstract doi.org/10.14569/IJACSA.2025.0161001 PDF

2

From Legacy to Cloud: Migration Strategies for Traditional Financial Institutions Using AWS

Author 1: Uday Kiran Chilakalapalli Author 2: Brij Mohan Author 3: Vinodkumar Reddy Surasani

Traditional financial institutions face unprecedented pressure to modernize their technological infrastructure while maintaining regulatory compliance and operational stability. This research examines the strategic approaches, implementation challenges, and outcomes of migrating legacy banking systems to Amazon Web Services (AWS) cloud infrastructure through a mixed-methods analysis of twelve financial institutions that completed… Read full abstract & cite →

Cloud migration financial services AWS compliance risk management governance

Abstract doi.org/10.14569/IJACSA.2025.0161002 PDF

3

From Logs to Knowledge: LLM-Powered Dynamic Knowledge Graphs for Real-Time Cloud Observability

Author 1: Nurmyrat Amanmadov Author 2: Tarlan Abdullayev

Cloud platforms continuously generate vast amounts of logs, metrics, and traces that are vital for monitoring and debugging distributed systems. However, current observability solutions are often siloed, dashboard-centric, and limited to surface-level correlations, making it difficult to derive actionable insights in real time. In this work, we present Log2Graph, a… Read full abstract & cite →

Large Language Models (LLMs) AI for cloud computing knowledge graphs logs

Abstract doi.org/10.14569/IJACSA.2025.0161003 PDF

4

IoT-Enabled Data-Driven Optimization of Dynamic Thermal Loads for Low-Energy Buildings

Author 1: Zhaojiang Lyu

Energy-efficient building operation requires accurate prediction and optimization of dynamic thermal loads under noisy IoT data streams. We propose an integrated framework that combines 1) mutual-information–based online feature selection to filter redundant signals, 2) an attention-enhanced LSTM forecaster to capture nonlinear spatiotemporal dependencies, and 3) multi-agent cooperative reinforcement learning for… Read full abstract & cite →

IoT-enabled optimization dynamic thermal load attention-enhanced forecasting multi-agent reinforcement learning energy-efficient buildings

Abstract doi.org/10.14569/IJACSA.2025.0161004 PDF

5

Quantifying Career Preferences and Perceptions of Software Testing Among Filipino IT Students: A Mixed-Method Analysis

Author 1: Chrisza Joy M. Carrido Author 2: Abeer Alsadoon Author 3: Thair Al-Dala’in Author 4: Ahmed Hamza Osman Author 5: Abubakar Elsafi Author 6: Azhari Qismallah Author 7: Albaraa Abuobieda

Software testing (ST) careers have consistently demonstrated low appeal among IT students globally, creating significant workforce gaps in this essential field of information technology. This study investigates the extent to which Filipino IT students share this disinterest in software testing careers as observed in previous international studies, while examining the… Read full abstract & cite →

Software testing career preferences Filipino IT students mixed methods education reform

Abstract doi.org/10.14569/IJACSA.2025.0161005 PDF

6

Pedestrian Navigation System with 3D Map and Charging Server Based on Steganography

Author 1: Kohei Arai

A pedestrian navigation system with a steganography-based 3D map and billing server is proposed. The proposed system includes a server system that provides topographical maps and navigation information to both pedestrians and vehicles. When using the proposed system, necessary images of cross sections, intersections, or points of interest can be… Read full abstract & cite →

Pedestrian navigation steganography client-server system geographic information system GIS

Abstract doi.org/10.14569/IJACSA.2025.0161006 PDF

7

Comparative Evaluation of CNN Architectures for Skin Cancer Classification

Author 1: Taopik Hidayat Author 2: Nurul Khasanah Author 3: Elly Firasari Author 4: Laela Kurniawati Author 5: Eni Heni Hermaliani

Skin cancer is one of the fastest-growing health problems worldwide. Early and accurate diagnosis is essential for improving treatment success and patient survival. However, many previous studies have focused on single CNN architectures or limited datasets, resulting in models with restricted generalizability. To address this gap, this study presents a… Read full abstract & cite →

Artificial intelligence convolutional neural network deep learning dermoscopic images skin cancer classification

Abstract doi.org/10.14569/IJACSA.2025.0161007 PDF

8

TabNet–XGBoost Hybrid Model for Student Performance Prediction and Customized Feedback

Author 1: Anupama Prasanth

Virtual Learning Environments (VLEs) have emerged as a cornerstone of modern education, enabling large-scale delivery of learning materials, assessments, and interactions in fully or partially online formats. The dynamic and self-paced nature of VLEs makes the early prediction of learner scores crucial for timely intervention and support. The existing frameworks… Read full abstract & cite →

Virtual learning environments student performance prediction TabNet XGBoost SHAP feedback generation quality education

Abstract doi.org/10.14569/IJACSA.2025.0161008 PDF

9

Enhanced Fault Detection in Software Using an Adaptive Neural Algorithm

Author 1: Jasem Alostad

Software fault detection is crucial for ensuring reliable and high-quality software systems. However, traditional fault detection methods often rely on manual inspection or rule-based techniques, which are time-consuming and prone to human errors. In this research, the researchers propose an enhanced fault detection approach using an adaptive neural transfer learning… Read full abstract & cite →

Software fault detection adaptive neural algorithm software reliability neural networks fault classification

Abstract doi.org/10.14569/IJACSA.2025.0161009 PDF

10

Construction and Characteristics of an Engineering Economic Risk Management Platform Based on the BO-GBM Model

Author 1: Chaojian Wang Author 2: Die Liu

Economic risk control is pivotal to the success of engineering projects. Traditional risk assessment methods often fall short in handling the high-dimensional, nonlinear, and strongly correlated risk factors prevalent in modern large-scale projects. To address these limitations, this study constructs an engineering economic risk management platform based on the BO-GBM… Read full abstract & cite →

Engineering economic risk management platform BO-GBM model Bayesian Optimization gradient boosters

Abstract doi.org/10.14569/IJACSA.2025.0161010 PDF

11

Adaptive Virtual Machine Consolidation Based on Autoformer and Enhanced Double Q-Network for Energy-Efficient Cloud Data Center

Author 1: Kaiqi Zhang Author 2: Youbo Lyu Author 3: Dequan Zheng Author 4: Yanping Chen Author 5: Jianshan Xu

As the scale of cloud data centers continues to expand, energy consumption has become a critical issue. Virtual machine (VM) consolidation is a key technology for improving resource utilization and reducing energy consumption, yet it remains challenging to effectively balance energy efficiency with service level agreement violations (SLAV) in dynamic… Read full abstract & cite →

Cloud computing virtual machine consolidation load prediction energy efficiency deep reinforcement learning Autoformer

Abstract doi.org/10.14569/IJACSA.2025.0161011 PDF

12

Handwriting Detectives Using Wavelet Siamese Technology to Verify Signature Fraud

Author 1: Mohamed Nazir Author 2: Ali Maher Author 3: Mostafa Eltokhy Author 4: Ali M. El-Rifaie Author 5: Tarek Hosny Author 6: Hani M. K. Mahdi

This paper addresses the escalating challenge of signature forgery detection through an innovative hybrid verification system. We integrate Siamese Neural Networks with wavelet scattering transformations to precisely capture signature characteristics while accommodating inherent variations. Our principal contribution, the "common anchor methodology," identifies a singular representative signature per individual, substantially reducing… Read full abstract & cite →

Biometric authentication Siamese neural networks scattering wavelets common anchor selection neutrosophic logic signature verification

Abstract doi.org/10.14569/IJACSA.2025.0161012 PDF

13

A New Hybrid Algorithm for Vision-Based Sleep Posture Analysis Integrating CNN, LSTM and MediaPipe

Author 1: Apichaya Nimkoompai Author 2: Puwadol Sirikongtham

Sleep posture is a critical factor affecting sleep quality and long-term health, particularly for the elderly and patients with chronic conditions. This research proposes a novel hybrid algorithm for real-time, vision-based sleep posture analysis by integrating Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, and MediaPipe pose estimation. The… Read full abstract & cite →

Sleep posture detection MediaPipe CNN LSTM real-time monitoring pose estimation

Abstract doi.org/10.14569/IJACSA.2025.0161013 PDF

14

NetDAIL: An Optimized Deep Learning-Based Hybrid Model for Anomaly Detection in Network Traffic

Author 1: Saad Khalifa Author 2: Mohamed Marie Author 3: Wael Mohamed

Detecting rare and subtle anomalies is critical for ensuring cybersecurity, financial integrity, and operational safety. High-dimensional features, severe class imbalance, and large data volumes often challenge conventional intrusion detection methods. This study presents NetDAIL, a hybrid framework that integrates deep feature learning using a denoising autoencoder, anomaly scoring through Isolation… Read full abstract & cite →

Anomaly detection deep learning autoencoders NetDAIL unsupervised learning intrusion detection NSL-KDD KDD Cup 1999

Abstract doi.org/10.14569/IJACSA.2025.0161014 PDF

15

An Integrated CNN, YOLOv5 and Faster R-CNN Framework for Real-Time Water Pipe Defect Detection

Author 1: Chu Fu Author 2: Mideth Abisado

In the context of rapidly expanding urban water supply networks and the prevalence of pipe defects – for example, corrosion, cracks, leaks, blockages – that undermine efficiency and pose safety risks, this study presents an intelligent detection system aimed at improving maintenance accuracy and operational stability. We propose a fusion-based… Read full abstract & cite →

Deep learning Convolutional Neural Network YOLOv5 Faster R-CNN machine vision

Abstract doi.org/10.14569/IJACSA.2025.0161015 PDF

16

SD-CNN: A Novel Lightweight Convolutional Neural Network Model for Fall Detection

Author 1: Han-lin Shen Author 2: Tian-hu Wang Author 3: Hong Mu

Aiming at the traditional deep learning fall detection model due to high computational complexity and a large number of parameters, this study proposes a lightweight convolutional neural network model, SD-CNN (SMA-Enhanced Depthwise Convolutional Neural Network), for fall detection. The model is first designed with an SMA attention module to enhance… Read full abstract & cite →

Fall detection lightweight SMA attention depth-separable convolution

Abstract doi.org/10.14569/IJACSA.2025.0161016 PDF

17

Efficient Lightweight Detection and Classification Method for Field-Grown Horticultural Crops

Author 1: Yaru Huang Author 2: Hua Zhou Author 3: Zhongyi Shu

As the core carrier of human food supply and agricultural economy, manual management in large-scale crop cultivation faces bottlenecks such as low efficiency, high cost, and difficulty in standardization. There is an urgent need for computer vision technology to realize automated detection and growth stage classification. However, most existing algorithms… Read full abstract & cite →

Computer vision neural network object detection and classification lightweight horticultural crops

Abstract doi.org/10.14569/IJACSA.2025.0161017 PDF

18

Using Combined Weighting and BP Neural Networks for Relative Poverty Measurement and its Evaluation

Author 1: Xiaohua Cai Author 2: Ya Zhao Author 3: Lijia Chen Author 4: Juan Huang Author 5: Yang Xu

This study addresses the challenges of measuring and evaluating relative poverty by introducing a comprehensive evaluation model based on the Analytic Hierarchy Process (AHP)-entropy method and BP neural networks. A multidimensional evaluation index system was constructed through expert consultation and literature review. The AHP-entropy method was then employed to determine… Read full abstract & cite →

Analytic hierarchy process (AHP) entropy method BP neural network model relative poverty measurement

Abstract doi.org/10.14569/IJACSA.2025.0161018 PDF

19

Evaluating Transformer-Based Pretrained Models for Classical Arabic Named Entity Recognition

Author 1: Mariam Muhammed Author 2: Shahira Azab

This study presents a comprehensive comparative evaluation of transformer-based pretrained language models for Named Entity Recognition (NER) in Classical Arabic, an underexplored linguistic variety characterized by rich morphology, orthographic ambiguity, and the absence of diacritics. The main objective of this work is to identify the most effective transformer model for… Read full abstract & cite →

Classical Arabic Named Entity Recognition transformer models pretrained models CANERCorpus

Abstract doi.org/10.14569/IJACSA.2025.0161019 PDF

20

A Hippopotamus Optimization Algorithm-Based Convolutional Neural Network Model for Mental Health Assessment Among College Students

Author 1: Gai Hang Author 2: Lin Yang

The mental health of adult students is crucial not only for enhancing their learning experience and overall quality of life, but also for alleviating academic and employment-related anxiety. A significant challenge in developing effective online mental health support systems is the accurate assessment of students' mental health status. Current evaluation… Read full abstract & cite →

Convolutional Neural Network Long Short-Term Memory hippopotamus optimization algorithm mental health assessment deep learning

Abstract doi.org/10.14569/IJACSA.2025.0161020 PDF

21

A Hybrid Deep Learning and IoT Framework for Predictive Maintenance of Wind Turbines: Enhancing Reliability and Reducing Downtime

Author 1: Amina Eljyidi Author 2: Hakim Jebari Author 3: Siham Rekiek Author 4: Kamal Reklaoui

The global shift towards renewable energy has positioned wind power as a cornerstone of sustainable development. However, the operational efficiency of wind farms is significantly hampered by unexpected component failures, leading to substantial downtime and maintenance costs. Traditional scheduled maintenance protocols are inefficient, often leading to unnecessary interventions or catastrophic… Read full abstract & cite →

Predictive maintenance wind turbine artificial intelligence deep learning Convolutional Neural Network Long Short-Term Memory Internet of Things Remaining Useful Life condition monitoring

Abstract doi.org/10.14569/IJACSA.2025.0161021 PDF

22

Federated Machine Learning for Monitoring Student Mental Health in Kazakhstan

Author 1: Bakirova Gulnaz Author 2: Bektemyssova Gulnara Author 3: Nor'ashikin Binti Ali

Federated Learning (FL) offers a privacy-preserving and decentralized paradigm for machine learning, making it particularly suitable for analyzing sensitive psychological and physiological data. This study aims to develop and evaluate a federated learning framework for assessing the psycho-emotional well-being of students in Kazakhstani educational institutions, where data privacy and infrastructural… Read full abstract & cite →

Federated Learning data privacy FedOpt FedAvg FedProx mental health non-IID data educational data mining psychological analytics

Abstract doi.org/10.14569/IJACSA.2025.0161022 PDF

23

Exploring Hallucination in Large Language Models

Author 1: Nesreen M. Alharbi Author 2: Thoria Alghamdi Author 3: Raghda M. Alqurashi Author 4: Reem Alwashmi Author 5: Amal Babour Author 6: Entisar Alkayal

Large Language Models such as GPT-4o and GPT-4o-mini have shown significant promise in various fields. However, hallucination, when models generate inaccurate information, remains a critical challenge, especially in domains that require high accuracy, such as the healthcare field. This study investigates hallucinations in two different LLMs, focusing on the healthcare… Read full abstract & cite →

ChatGPT GPT-4o GPT-4o-mini hallucination healthcare large language models

Abstract doi.org/10.14569/IJACSA.2025.0161023 PDF

24

Game-Theoretic Approaches for Robust Stability of DC Motor Systems

Author 1: Mohamed Ayari Author 2: Atef Gharbi Author 3: Yamen El Touati Author 4: Zeineb Klai Author 5: Mahmoud Salaheldin Elsayed Author 6: Elsaid Md. Abdelrahim

This study proposes a game-theoretic framework for achieving robust stability in DC motor systems operating under parametric uncertainty and external disturbances. We model the controller, disturbance, and uncertainty as strategic players in a non-cooperative differential game and synthesize equilibrium policies using a Lyapunov–game approach. Practically, the method integrates: 1) LMI-based… Read full abstract & cite →

Game theory DC motor control robust stability differential games Lyapunov stability reinforcement learning evolutionary algorithms

Abstract doi.org/10.14569/IJACSA.2025.0161024 PDF

25

Comparative Performance Analysis of Original AuRa and Improved AuRa Consensus Algorithms in Chain Hammer Digital Certificate Simulation

Author 1: Robiah Arifin Author 2: Wan Aezwani Wan Abu Bakar Author 3: Mustafa Man Author 4: Evizal Abdul Kadir

The blockchain functions as a distributed database, where data is securely stored across multiple servers and network nodes. It exists in various forms, with Bitcoin, Ethereum, and Hyperledger being among the most prominent examples. To ensure the integrity and security of transactions within a blockchain network, a consensus algorithm is… Read full abstract & cite →

Blockchain Ethereum AuRa_ori AuRa_v1 TPS TGS

Abstract doi.org/10.14569/IJACSA.2025.0161025 PDF

26

An Improved Marine Predators Algorithm-Based UAV Path Planning for 10-kV Distribution Networks Inspection in Live Working Scenarios

Author 1: Dapeng Ma Author 2: Hongtao Jiang Author 3: Lichao Jiang Author 4: Chi Zhang Author 5: Changwu Li Author 6: Xin Zheng Author 7: Mingxian Liu Author 8: Kai Li

Before conducting maintenance on 10-kV distribution networks, the use of unmanned aerial vehicles (UAVs) for inspecting distribution lines can effectively enhance the operational efficiency of personnel in live working scenarios. For UAV-based inspection of power distribution networks, an optimal flight path ensures both operational safety and comprehensive image acquisition in… Read full abstract & cite →

Marine predictors algorithm YOLOv11 defect classification UAV path planning live power lines

Abstract doi.org/10.14569/IJACSA.2025.0161026 PDF

27

Enhancing Predictive Maintenance Method Using Machine Learning to Improve IoT-Embedded Machinery Efficiency and Performance

Author 1: Abiinesh Nadarajan Author 2: Iskandar Ishak Author 3: Noridayu Manshor Author 4: Raihani Mohamed Author 5: Mohamad Yusnisyahmi Yusof

Predictive maintenance plays a crucial role in minimizing unplanned downtimes, reducing maintenance costs, and optimizing the operational efficiency of IoT-embedded industrial machinery. Despite its transformative potential, traditional predictive maintenance methods often face challenges such as limited accuracy, high latency, and inefficiencies in processing large and imbalanced datasets. This study proposes… Read full abstract & cite →

Internet of Things machine learning predictive maintenance

Abstract doi.org/10.14569/IJACSA.2025.0161027 PDF

28

A Hybrid Deep Learning and Forensic Approach for Robust Deepfake Detection

Author 1: Sales Aribe Jr

The rapid evolution of generative adversarial networks (GANs) and diffusion models has made synthetic media increasingly realistic, raising societal concerns around misinformation, identity fraud, and digital trust. Existing deepfake detection methods either rely on deep learning, which suffers from poor generalization and vulnerability to distortions, or forensic analysis, which is… Read full abstract & cite →

Adversarial robustness deepfake detection diffusion models explainable AI forensic fusion multimedia forensics trustworthy AI

Abstract doi.org/10.14569/IJACSA.2025.0161028 PDF

29

Facial Expression Recognition Under Partial Occlusion Using Part-Based Ensemble Learning

Author 1: Evangelions Felix Yehdeya Author 2: Wahyono

Facial expression recognition (FER) under partial occlusion remains a challenging task, especially when key regions of the face, such as the mouth and nose, are covered by medical masks. Such conditions significantly reduce the discriminative features available for accurate emotion recognition, limiting the effectiveness of conventional full-face approaches. To address… Read full abstract & cite →

Facial expression recognition partial occlusion partial part model support vector machine ensemble learning

Abstract doi.org/10.14569/IJACSA.2025.0161029 PDF

30

Ambulance Detection and Priority Passage at Urban Intersections Using Transfer Learning and Explainable AI

Author 1: Murtaza Hanif Author 2: Taj Muhammad Author 3: Atif Ikram Author 4: Shahid Yousaf Author 5: Marwan Abu-Zanona Author 6: Asef Mohammad Ali Al Khateeb Author 7: Bassam Elzaghmouri Author 8: Saad Mamoun Abdel Rahman Ahmed Author 9: Lamia Hassan Rahamatalla

Static traffic signal timings often cause severe delays for emergency vehicles, including ambulances at junctions in urban areas, putting lives at risk. To highlight this, the present study proposes an intelligent traffic control system that dynamically adjusts traffic signals based on real-time monitoring. The system employs a yolov8-based deep learning… Read full abstract & cite →

Ambulance detection YOLOV8 LIME transfer learning NorFair urban area traffic control smart traffic management

Abstract doi.org/10.14569/IJACSA.2025.0161030 PDF

31

Digital Trust and Legacy: Mapping the Intersection of Inheritance Systems and Emerging Technologies (2010–2025)

Author 1: Nor Aimuni Md Rashid Author 2: Faiqah Hafidzah Halim Author 3: Hazrati Zaini Author 4: Norshahidatul Hasana Ishak Author 5: Nur Farahin Mohd Johari Author 6: Alya Geogiana Buja

Inheritance systems worldwide are undergoing a paradigm shift evolving from manually administered processes to technologically enabled platforms for managing both tangible and digital assets. Yet, the scholarly understanding of how technologies ranging from information systems to blockchain have transformed inheritance management remains underexplored and fragmented. This study aims to trace… Read full abstract & cite →

Inheritance systems digitalization secure data trust technologies digital legacy blockchain digital assets

Abstract doi.org/10.14569/IJACSA.2025.0161031 PDF

32

A Quality Assessment Study of Deep Learning Techniques for Medical Image Diagnosis and Their Applications: A Systematic Literature Review

Author 1: Amine Berquedich Author 2: Ahmed Zellou

Medical imaging is one of the cornerstones of modern medicine, planning treatments, monitoring patient progress and aiding clinicians in diagnosing diseases such as tumors, cancer, and many others. With the rise of neural networks, especially deep learning (DL) approaches, significant advancements have been made in this domain. This systematic literature… Read full abstract & cite →

Deep learning medical image segmentation systematic review convolutional neural networks

Abstract doi.org/10.14569/IJACSA.2025.0161032 PDF

33

Modeling and Analyzing Malware Behavior in Virtual Networks Using EVE-NG

Author 1: Maria-Madalina Andronache Author 2: Alexandru Vulpe Author 3: Corneliu Burileanu

Malicious attacks have become increasingly common in all organizations and systems. The continued evolution of such software aims to extract information from diverse systems. Therefore, the objective of this study is to introduce another approach to analyze some network attacks, within a virtual infrastructure, through multi-vendor network emulation software (Emulated… Read full abstract & cite →

EVE-NG network attacks network defense SIEM network architecture

Abstract doi.org/10.14569/IJACSA.2025.0161033 PDF

34

Predicting Stock Market Performance Based on Sentiment Analysis of Online Comments

Author 1: Wenhao Suo Author 2: Tongjai Yampaka

In China's retail-focused stock market, the influence of social media sentiment during off-hours on the next day's opening price has received limited attention. This paper takes Kweichow Moutai—a leading Chinese company with substantial market capitalization—as the research sample. It gathers investor commentary data from financial platforms, and uses natural language… Read full abstract & cite →

Investor sentiment non-trading hour sentiment social media comments dual-channel LSTM

Abstract doi.org/10.14569/IJACSA.2025.0161034 PDF

35

User Satisfaction in AI-Driven Islamic Fintech: An Extended Technology Acceptance Model with Task–Technology Fit and Sharia Compliance

Author 1: Mardiana Andarwati Author 2: Sari Yuniarti Author 3: Andriyan Rizki Jatmiko Author 4: Firnanda Al-Islama Achyunda Putra Author 5: Galandaru Swalaganata Author 6: Ahmad Taufiq Andriono

The rapid development of digital financial services has transformed financial intermediation through improved access, transparency, and efficiency. In the Indonesian context, Islamic financial technology (fintech) offers an alternative aligned with Sharia principles, particularly through e-ijarah contracts that provide MSMEs with productive asset access without interest-bearing debt. This study aims to… Read full abstract & cite →

Task–Technology fit sharia compliance technology acceptance model user satisfaction AI Islamic fintech MSMEs

Abstract doi.org/10.14569/IJACSA.2025.0161035 PDF

36

Multimodal Deep Learning for Tuberculosis Detection Using Cough Audio and Clinical Data with Health Acoustic Representations (HeAR)

Author 1: Rinaldi Anwar Buyung Author 2: Widi Nugroho

Tuberculosis (TB) remains a significant global health challenge, necessitating rapid and accessible screening methods. This study proposes a multimodal deep learning model for non-invasive TB detection by fusing acoustic features from cough sounds with clinical metadata. We utilize the pre-trained Health Acoustic Representations (HeAR) model as a powerful backbone to… Read full abstract & cite →

Tuberculosis cough detection Health Acoustic Representation multimodal vocal biomarker

Abstract doi.org/10.14569/IJACSA.2025.0161036 PDF

37

EYE-GDM: Clinically Validated, Explainable Ensemble Learning for Gestational Diabetes

Author 1: Shatha Alghamdi Author 2: Rashid Mehmood Author 3: Fahad Alqurashi Author 4: Turki Alghamdi Author 5: Sarah Ghazali Author 6: Asmaa AlAhmadi

As artificial intelligence (AI) advances in healthcare, its use in maternal health shows promise but faces challenges of trust due to the black-box nature of many models. Gestational diabetes mellitus (GDM), a transient yet high-risk condition, demands accurate and interpretable prediction tools. However, existing GDM prediction studies often rely on… Read full abstract & cite →

Explainable Artificial Intelligence (XAI) interpretable machine learning (IML) Gestational diabetes mellitus (GDM) maternal health healthcare AI GDM risk prediction transparency trust

Abstract doi.org/10.14569/IJACSA.2025.0161037 PDF

38

An Intelligent Platform for Behavior Modification and Office Syndrome Risk Reduction Using MediaPipe and Computer Vision

Author 1: Sumran Chaikhamwang Author 2: Wijitra Montri Author 3: Chalida Janthajirakowit Author 4: Srinuan fongmanee

Office Syndrome, a musculoskeletal disorder prevalent among office workers, poses significant risks to health, productivity, and quality of life. Traditional preventive approaches, such as ergonomic guidelines and reminder-based systems, often fail due to limited user adherence and practicality. To address this gap, this study developed an intelligent platform that integrates… Read full abstract & cite →

Office syndrome computer vision MediaPipe behavior modification ergonomics

Abstract doi.org/10.14569/IJACSA.2025.0161038 PDF

39

A Review of Ransomware Detection Models for Cybersecurity Driven IIoT in Cloud Environments

Author 1: Abrar Ali Author 2: Norah Hamed Author 3: Monir Abdullah

Ransomware is currently one of the most severe cybersecurity threats and not only attacks legacy systems but cloud systems and Industrial Internet of Things (IIoT) systems as well. Security and privacy threats are heightened as these systems integrate more closely and thus are exposed to sophisticated and long-lasting attacks. This… Read full abstract & cite →

Ransomware Industrial Internet of Things cloud computing machine learning deep learning blockchain

Abstract doi.org/10.14569/IJACSA.2025.0161039 PDF

40

A Comprehensive Survey of Visual SLAM Technology: Methods, Challenges, and Perspectives

Author 1: Aidos Ibrayev Author 2: Amanzhol Bektemessov

Visual Simultaneous Localization and Mapping (Visual SLAM) has become a cornerstone of autonomous navigation and spatial understanding in robotics, augmented reality, and computer vision. This review presents a comprehensive examination of algorithmic progress in Visual SLAM, focusing on the three principal paradigms: monocular, stereo, and RGB-D SLAM. Monocular SLAM, known… Read full abstract & cite →

Visual SLAM monocular SLAM Stereo SLAM RGB-D SLAM 3D mapping pose estimation loop closure semantic SLAM deep learning sensor fusion

Abstract doi.org/10.14569/IJACSA.2025.0161040 PDF

41

Uneven But Accelerating: AI Adoption in Higher Education

Author 1: Mahendra Adhi Nugroho Author 2: Umar Yeni Suyanto Author 3: Didik Hariyanto Author 4: Septiningdyah Arianisari

Artificial Intelligence (AI) is increasingly recognized as a transformative force in higher education, yet adoption remains patchy and often confined to partial implementations. Using the PRISMA protocol, this study systematically reviews 74 Scopus-indexed articles published between 2015 and 2025. Publication activity rose sharply after 2020, led by contributions from China… Read full abstract & cite →

Artificial intelligence adoption higher education sustainable education developing country

Abstract doi.org/10.14569/IJACSA.2025.0161041 PDF

42

Comparative Review of Confidence and Other Evaluation Metrics in Predictive Modeling for Procurement Fraud Coalition

Author 1: Saifuddin Mohd Author 2: Mohamad Taha Ijab

Procurement fraud, particularly when bidders act together through collusion or coalition schemes, remains a major threat to fair competition in public procurement. Predictive modeling has emerged as a key analytical tool for detecting such behaviors yet choosing appropriate evaluation metrics continues to be a challenge, especially with imbalanced or correlated… Read full abstract & cite →

Procurement fraud predictive modeling confidence evaluation metrics association rule mining coalition detection public sector analytics

Abstract doi.org/10.14569/IJACSA.2025.0161042 PDF

43

Correcting Blue-Shift in Single-Image Dehazing via Haze-Compensated Von Kries Adaptation

Author 1: Asniyani Nur Haidar Abdullah Author 2: Mohd Shafry Mohd Rahim Author 3: Sim Hiew Moi Author 4: Azah Kamilah Draman Author 5: Ahmad Hoirul Basori Author 6: Novanto Yudistira

Haze severely degrades image quality by reducing contrast, obscuring details, and introducing a blue-shift color cast caused by atmospheric scattering. Traditional dehazing methods, including prior-based approaches (e.g., DCP, CAP, LPMinVP) and preprocessing techniques (e.g., ICAP WB, Dynamic Gamma), improve visibility but fail to correct haze-induced color imbalance, resulting in unstable… Read full abstract & cite →

Image dehazing blue-shift correction color compensation Von Kries adaptation preprocessing

Abstract doi.org/10.14569/IJACSA.2025.0161043 PDF

44

Enhancing Dermatological Diagnostics: An Enhanced Approach for Skin Cancer Classification Using pix2pix GAN

Author 1: Adnan Afroz Author 2: Shaheena Noor Author 3: Shakil Ahmed Bashir Author 4: Umair Jilani

Skin cancer is among the predominant forms of the disease that includes malignant squamous cell carcinoma, basal cell carcinoma, and melanoma that is characterized by aberrant melanocyte cell development. Frequent screenings and examinations enhance the prognosis for people with skin cancer. Sadly, a lot of patients with skin cancer are… Read full abstract & cite →

Deep learning skin cancer generative adversarial network pix2pixHD classification

Abstract doi.org/10.14569/IJACSA.2025.0161044 PDF

45

A Hybrid AI Framework for DDoS Detection and Mitigation in SDN Environments Using CNN, GAN, and Semi-Supervised Learning

Author 1: Abdelhakim HADJI Author 2: Brahim RAOUYANE

The fast technological evolution seen in recent years enhanced the performance and scalability of cloud computing infrastructure and Software-Defined Networking architectures. SDN provides programmability, centralized orchestration, and dynamic resource provisioning, while separating the control and data planes to offer promising architectural paradigm for cloud computing environments. Openness and flexibility expose… Read full abstract & cite →

SDN CNN GAN DDOS OpenDaylight Mininet semi-supervised learning hybrid AI framework

Abstract doi.org/10.14569/IJACSA.2025.0161045 PDF

46

Benchmarking Deep Learning Models for Visual Classification and Segmentation of Horticultural Commodities

Author 1: Fuzy Yustika Manik Author 2: Syahril Efendi Author 3: Jos Timanta Tarigan Author 4: Maya Silvi Lydia

Recent advances in computer vision have enabled new approaches for automated quality assessment of tropical fruits, where accurate classification and segmentation are essential for postharvest inspection. A major challenge lies in identifying deep learning architectures that achieve high accuracy while remaining computationally efficient for potential edge-based deployment. This study benchmarks… Read full abstract & cite →

Fruit quality assessment classification segmentation EfficientNet-B0 DeepLabV3+ AISAM-CSNet

Abstract doi.org/10.14569/IJACSA.2025.0161046 PDF

47

Towards Designing a Blockchain-Based Model for E-Book Publishing

Author 1: Maznun Arifa Mohammadan Makhtar Author 2: Novia Admodisastro Author 3: Suleymenova Laura Askarbekkyzy

This paper examines the application of blockchain technology in e-book publishing by analyzing previous research and identifying current limitations. The study investigates how smart contracts and cryptographic algorithms can facilitate agreements between publishers and authors. While blockchain has been widely adopted in digital publishing domains, such as image, video, music… Read full abstract & cite →

e-book publishing Ethereum blockchain technology smart contract

Abstract doi.org/10.14569/IJACSA.2025.0161047 PDF

48

Adaptive Hybrid Deep Learning with Recursive Feature Elimination for Physical Violence Detection

Author 1: Sukmawati Anggraeni Putri Author 2: Duwi Cahya Putri Buani Author 3: Achmad Rifa’i Author 4: Imam Nawawi

Physical violence among students remains a persistent issue that often goes undetected, especially in school environments without intelligent real-time monitoring systems. Such incidents pose serious risks to student safety and hinder the creation of a secure learning atmosphere. This study aims to develop an adaptive visual-based system for detecting physical… Read full abstract & cite →

Violence detection deep learning VGG19 BiLSTM RFE Educational AI

Abstract doi.org/10.14569/IJACSA.2025.0161048 PDF

49

Transformative Integration of Machine Learning in Software Applications in Light of Current Software Engineering Practices

Author 1: Fawzi Abdulaziz Albalooshi

This study critically reviews the transformative integration of machine learning (ML) into software engineering, detailing its evolution from traditional DevOps to MLOps, which has significantly enhanced software development by enabling adaptive and intelligent systems, improving processes, and boosting software quality. Despite these benefits, the integration introduces unique challenges across technical… Read full abstract & cite →

Machine learning (ML) software engineering DevOps MLOps ML integration challenges integrated software development

Abstract doi.org/10.14569/IJACSA.2025.0161049 PDF

50

Bridging Machine-Readable Code of Regulations and its Application on Generative AI: A Survey

Author 1: Samira Yeasmin Author 2: Bader Alshemaimri

Machine-Readable Code (MRC) and Machine-Readable Regulations (MRR) enable the conversion of complex regulations into structured formats such as JSON, XML, and X2RL, allowing machines to parse and interpret regulatory texts efficiently. Currently, organizations face challenges in regulatory compliance due to the complexity of regulations, frequent updates, and difficulty in identifying… Read full abstract & cite →

Regulatory compliance natural language processing machine learning machine-readable code Machine-Readable Regulations generative AI large language models RegTech conflicting regulations regulation issuance

Abstract doi.org/10.14569/IJACSA.2025.0161050 PDF

51

Energy Efficient Workflow Allocation in Cloud Computing Using Improved Grey Wolf Optimization

Author 1: Md. Mazhar Nezami Author 2: Anoop Kumar

Cloud computing has emerged as a dominant platform for hosting complex applications, offering scalable and flexible resources on demand. However, the dynamic and heterogeneous nature of cloud environments poses significant challenges for efficient workflow scheduling, particularly when aiming to minimize total execution time, energy consumption, and operational cost. In this… Read full abstract & cite →

Cloud computing energy efficient workflow Heterogeneous Earliest Finish Time (HEFT) Grey Wolf Optimization (GWO) makespan cost

Abstract doi.org/10.14569/IJACSA.2025.0161051 PDF

52

Feature Pyramid Network with Dual-Decoder Supervision for Accurate Stroke Lesion Localization in Multi-Modal Brain MRI

Author 1: Satmyrza Mamikov Author 2: Zhansaya Yakhiya Author 3: Bauyrzhan Omarov Author 4: Yernar Mamashov Author 5: Akbayan Aliyeva Author 6: Balzhan Tursynbek

This study presents a novel Feature Pyramid Network with Dual-Decoder Supervision for accurate stroke lesion localization in multi-modal brain MRI. The proposed architecture integrates a Swin Transformer backbone with multi-scale feature aggregation, enabling effective fusion of hierarchical representations from DWI, ADC, and FLAIR sequences. A dual-decoder structure is employed, where… Read full abstract & cite →

Stroke lesion localization multi-modal MRI feature pyramid network segmentation deep learning

Abstract doi.org/10.14569/IJACSA.2025.0161052 PDF

53

Leveraging AI and Hybrid Intelligence for Robust Geospatial Data Fusion in Autonomous Terrestrial Navigation

Author 1: Manel Salhi Author 2: Mounir Bouzguenda Author 3: Faouzi Benzarti Author 4: Fawaz Alanazi Author 5: Ezzeddine Touti

Rapid advancement of artificial intelligence (AI) and geospatial data fusion has enabled the development of highly autonomous terrestrial navigation systems with improved accuracy, adaptability, and robustness. This paper proposes a novel framework integrating multi-source geospatial data fusion with deep learning-based decision-making for autonomous terrestrial navigation. Unlike conventional approaches that rely… Read full abstract & cite →

Autonomous navigation geospatial data fusion graph neural networks transformer-based models sensor fusion AI-driven mobility

Abstract doi.org/10.14569/IJACSA.2025.0161053 PDF

54

SEARCHX: An Integrated Framework of Distributed Intelligent Search Services Based on Web Browser

Author 1: Zehui Zhang Author 2: Lin Zhou Author 3: Jie Peng Author 4: Liwei Wang Author 5: Bo Cheng

To address the growing demand for web search and improve the performance and accuracy of search systems, this study proposes a distributed intelligent search service integration framework based on SEARCHX. This framework leverages the local computational power of the browser, integrating inverted indexing, data sharding, and replication mechanisms, as well… Read full abstract & cite →

Web TF-IDF distributed network intelligent search SEARCHX

Abstract doi.org/10.14569/IJACSA.2025.0161054 PDF

55

Multi-Criteria Using Dijkstra’s Algorithm to Determine Optimal Time Paths in Vehicle Route Optimization

Author 1: Basorudin Author 2: Handaru Jati Author 3: Nurkhamid Author 4: Puput Dani Prasetyo Adi

This research is the development of a Road Traffic Network using one of the methods in Mathematics, namely Dijkstra's Algorithm, Weighted Sum Method (WSM), and Weighted Product Method (WPM). Meanwhile, the parameters used are route, volume, capacity, DOS, distance, and travel time. The objective of this research is to find… Read full abstract & cite →

Dijkstra’s algorithm multi-criteria road traffic network Weighted Sum Method (WSM) Weighted Product Method (WPM) mathematics

Abstract doi.org/10.14569/IJACSA.2025.0161055 PDF

56

Embedding Models: A Comprehensive Review with Task-Oriented Assessment

Author 1: Lahbib Ajallouda Author 2: Meriem Hassani Saissi Author 3: Ahmed Zellou

Sentence embedding is a very important technique in most natural language processing (NLP) tasks, such as answer generation, semantic similarity detection, text classification and information retrieval. This technique aims to transform the semantic meaning of a sentence into a fixed-dimensional vector, allowing machines to understand human language. Sentence embedding has… Read full abstract & cite →

Natural language processing sentence embedding models transformer models embedding models challenges

Abstract doi.org/10.14569/IJACSA.2025.0161056 PDF

57

Machine Learning-Driven Emotional Feedback Analysis and Adaptive Content Generation for VR Movie and TV Users

Author 1: Yun TANG

With the growing demand for immersive audiovisual experiences, user sentiment feedback analysis has become a pivotal factor in improving personalization and interactivity in virtual reality (VR) movie and television. This study proposes a machine learning–driven framework that integrates sentiment feedback recognition and adaptive content generation to optimize user experience. First… Read full abstract & cite →

Machine learning VR movie and television user sentiment feedback analysis adaptive content generation reinforcement learning

Abstract doi.org/10.14569/IJACSA.2025.0161057 PDF

58

Meta-Learning Prediction Framework for Asphalt Mixtures Fatigue Life Modeling

Author 1: Longmeng Tan Author 2: Krzysztof Kowalski

In order to improve the accuracy and generalization ability of asphalt mixture fatigue life prediction, this study introduces the meta-learning method, which aims to solve the problems of poor adaptability and strong data dependence of the traditional prediction model under complex working conditions. In this study, a prediction framework based… Read full abstract & cite →

Asphalt mixtures fatigue life meta-learning prediction mechanism analysis

Abstract doi.org/10.14569/IJACSA.2025.0161058 PDF

59

Quality Classification of Harumanis Mango Based on External Multi-Parameter and Machine Learning Techniques

Author 1: Mohd Nazri Abu Bakar Author 2: Abu Hassan Abdullah Author 3: Muhamad Imran Ahmad Author 4: Norasmadi Abdul Rahim Author 5: Haniza Yazid Author 6: Wan Mohd Faizal Wan Nik Author 7: Shafie Omar Author 8: Shahrul Fazly Man@Sulaiman Author 9: Tan Shie Chow Author 10: Fahmy Rinanda Saputri

Grading Harumanis mangoes is traditionally done through manual visual inspection, which is subjective, inconsistent, and labor-intensive. Industry practices report only 70–80% consistency among human graders, with accuracy further declining under fatigue or high volumes. These limitations hinder uniform quality assurance, especially for export markets. To address this, an image-based, non-destructive… Read full abstract & cite →

Machine learning image processing quality assessment Harumanis mango appearance attributes

Abstract doi.org/10.14569/IJACSA.2025.0161059 PDF

60

Fourier Transform and Attention Guided Deep Neural Network for Face Anti-Spoofing in Medical Applications

Author 1: Zhanseri Ikram

Face recognition systems have become prevalent in mobile devices and security applications, increasing the demand for robust face presentation attack detection. Early efforts based on handcrafted features struggled to cope with variations in illumination, pose, and attack modalities, prompting a transition toward deep learning solutions capable of extracting subtle discriminative… Read full abstract & cite →

Liveness detection face anti-spoofing deep learning CNN frequency domain

Abstract doi.org/10.14569/IJACSA.2025.0161060 PDF

61

A Technique for Automated Parallel Optimization of Function Calls in C++ Code

Author 1: Shuruq Abed Alsaedi Author 2: Fathy Elbouraey Eassa Author 3: Amal Abdullah AlMansour Author 4: Lama Abdulaziz Al Khuzayem Author 5: Rsha Talal Mirza

In modern software development, achieving high performance increasingly relies on effective parallelization. While much of the existing research has focused on loop-level parallelism, function-level parallelization remains relatively underutilized. Yet, in many real-world applications, function calls serve as natural units of computation that could greatly benefit from concurrent execution. To address… Read full abstract & cite →

Automatic parallelization function-level parallelization C++ code optimization parallel computing control flow graph dependency analysis performance optimization

Abstract doi.org/10.14569/IJACSA.2025.0161061 PDF

62

Unveiling the Drivers of Consumer Purchase Intention in Short-Form Video Marketing

Author 1: Merisa Syafrina Author 2: Viany Utami Tjhin

Short-video features on e-commerce platforms have become a key driver of social commerce, enhancing user engagement and purchase intention. However, user reviews of Shopee Video reveal issues such as disruptive autoplay, limited content control, and unintuitive navigation. While prior studies have examined engagement and satisfaction in general e-commerce, limited research… Read full abstract & cite →

E-commerce purchase intention Shopee Video social commerce SEM-PLS

Abstract doi.org/10.14569/IJACSA.2025.0161062 PDF

63

Integrative Hybrid Metaheuristic Algorithm for Hyperparameter Optimisation in Pre-Trained Convolutional Neural Network Models (I-HAHO)

Author 1: Nazleeni Samiha Haron Author 2: Jafreezal Jaafar Author 3: Izzatdin Abdul Aziz Author 4: Mohd Hilmi Hasan Author 5: Muhammad Hamza Azam

Hyperparameter optimisation (HPO) remains a fundamental challenge in deep learning, especially for pre-trained convolutional neural networks (CNNs). While pre-trained models reduce the computational burden of training from scratch, their effectiveness depends heavily on tuning parameters such as learning rate, batch size, dropout, weight decay, and optimizer type. The search space… Read full abstract & cite →

Hyperparameter Optimisation (HPO) Convolutional Neural Networks (CNNs) Artificial Bee Colony (ABC) Harris Hawks Optimisation (HHO) Hybrid Metaheuristic Algorithm

Abstract doi.org/10.14569/IJACSA.2025.0161063 PDF

64

A Novel Performance-Based Time Series Forecast Combination Method and Applications with Neural Networks

Author 1: M. Burak Erturan

Performance-based forecast combination approaches determine the weights of the individual forecasts based on the inverse average error for a past time interval. However, although the performances are calculated for a time span, the aim is mostly a one-step-ahead time-point forecast. In these classical methods, a relatively higher prediction error of… Read full abstract & cite →

Combination forecast performance-based combination neural networks multi-layer perceptron extreme learning machine

Abstract doi.org/10.14569/IJACSA.2025.0161064 PDF

65

Integration of Color QR-Code Technology in Biometric Data Encoding and Facial Identity Systems

Author 1: Nazym Kaziyeva Author 2: Kalybek Maulenov Author 3: Ruslan Ospanov Author 4: Abzhan Khamza Mukhtaruly

This paper presents an enhanced algorithm for the generation of color biometric QR codes capable of encoding facial image data, anthropometric parameters, and personal identity information simultaneously within a single RGB-based QR structure. The proposed approach extends existing monochrome QR models by integrating optimized image decomposition, modular QR block generation… Read full abstract & cite →

Color biometric QR code facial image encoding RGB channel decomposition biometric data integration secure identification facial recognition QR animation identity encoding privacy protection data capacity OpenCV computer vision

Abstract doi.org/10.14569/IJACSA.2025.0161065 PDF

66

Enhancing the Scanability of Damaged QR Codes Through Image Restoration Using GANs Combined with the Spectral Normalization Technique

Author 1: Puwadol Sirikongtham Author 2: Apichaya Nimkoompai

QR Codes are widely used in the digital era for storing and sharing information in various applications. However, they are often susceptible to physical damage such as scratches, tears, or fading, which can result in scanning failures and limit their usability. To overcome this issue, this research introduces a Generative… Read full abstract & cite →

QR Code restoration Generative Adversarial Networks spectral normalization image inpainting deep learning damage reconstruction

Abstract doi.org/10.14569/IJACSA.2025.0161066 PDF

67

Recent Integrating Machine Learning and Malay-Arabic Lexical Mapping for Halal Food Classification

Author 1: Noorrezam Yusop Author 2: Massila Kamalrudin Author 3: Nuridawati Mustafa Author 4: Tao Hai Author 5: Mohd Nazrien Zaraini Author 6: Halimaton Hakimi Author 7: Siti Fairuz Nurr Sardikan

The rapid growth of e-commerce has changed the way people engage with businesses, notably in the food industry. For the Muslim community, guaranteeing Halal conformity in digital transactions is critical. This study provides a comprehensive framework for improving Halal E-Commerce systems that include machine learning, pattern libraries, and multilingual support… Read full abstract & cite →

Malay-Arabic lexical mapping natural language processing machine learning halal food classification halal food e-commerce

Abstract doi.org/10.14569/IJACSA.2025.0161067 PDF

68

Evaluating Head Pose Estimation for Assessing Visual Attention in Children with Special Needs During Robot-Assisted Therapy

Author 1: Rusnani Yahya Author 2: Rozita Jailani Author 3: Nur Khalidah Zakaria Author 4: Fazah Akhtar Hanapiah

This study investigates the application of head pose estimation (HPE) to assess visual attention in children with special needs (CwSN) during robot-assisted therapy sessions, focusing on its effectiveness and the attention patterns exhibited by these children. CwSN often faces unique challenges, such as sensory processing difficulties or delayed cognitive processing… Read full abstract & cite →

Head pose estimation visual attention robot-assisted therapy children with special needs

Abstract doi.org/10.14569/IJACSA.2025.0161068 PDF

69

A Novel Taxonomy for Human Activity Recognition Based on a Systematic Analysis of Public UAV Datasets

Author 1: Sumaya Abdulrahman Altuwairqi Author 2: Salma Kammoun Jarraya

In recent decades, unmanned aerial vehicles (UAVs) have become widely utilized for many real-world applications, including surveillance, crowd management, and threat detection, providing a new perspective to recognize human behaviors. However, current UAV-based video datasets adopt categorization schemes that rely on broad and inconsistent categories relative to real-world aerial contexts… Read full abstract & cite →

Human action recognition UAV videos surveillance systems categorization framework

Abstract doi.org/10.14569/IJACSA.2025.0161069 PDF

70

Evaluation of the Impact of Cybersecurity Knowledge on the Prevention of Social Cybercrime Among University Students in Mexico, Colombia, and Peru

Author 1: Yasmina Riega-Viru Author 2: Lainiver Mendoza Munar Author 3: Mario Ninaquispe-Soto Author 4: Kiara Nilupu-Moreno Author 5: Juan Luis Salas-Riega Author 6: Alfonso Renato Vargas-Murillo Author 7: Yolanda Pinto Bouroncle

Objectives: This study aims to evaluate the degree of cybersecurity knowledge and awareness among university students in Peru, Mexico, and Colombia, and to determine how these factors contribute to protection against social cybercrime. This cross-regional analysis represents a novel contribution by comparing cybersecurity preparedness across three Latin American countries, an… Read full abstract & cite →

Cybersecurity social cybercrime university students

Abstract doi.org/10.14569/IJACSA.2025.0161070 PDF

71

Understanding Echo Chambers in Recommender Systems: A Systematic Review

Author 1: Meriem HASSANI SAISSI Author 2: Nouhaila IDRISSI Author 3: Ahmed ZELLOU

Echo chambers refer to the phenomenon in which individuals are consistently exposed to content that aligns with their existing viewpoints. Over time, this can narrow a user’s perspective and make it harder to encounter different opinions. In this systematic literature review, we looked at studies published between 2019 and early… Read full abstract & cite →

Echo chamber recommender systems filter bubbles collaborative filtering systematic literature review

Abstract doi.org/10.14569/IJACSA.2025.0161071 PDF

72

Critical Review of Object Detection Techniques for Traffic Light Detection in Intelligent Transportation Systems

Author 1: Adhwa Salemi Author 2: Muhammad Arif Mohamad

Object detection and tracking play a critical role in intelligent transportation systems (ITS), particularly in recognizing and monitoring traffic lights to ensure safety and improve traffic efficiency. Despite progress in deep learning and optimization algorithms, traffic light detection still faces persistent challenges under varying conditions such as illumination changes, occlusions… Read full abstract & cite →

Object detection traffic light detection optimization intelligent transportation systems review

Abstract doi.org/10.14569/IJACSA.2025.0161072 PDF

73

Conversational AI-Powered VR Development Model for Tourism Promotion in Thailand: Expert Assessment and Stakeholder Acceptance

Author 1: Jenasama Srihirun Author 2: Kridsanapong Lertbumroongchai Author 3: Vitsanu Nittayathammakul Author 4: Pimon Kaewdang

Thailand’s tourism sector increasingly requires immersive digital innovations that preserve local identity while enhancing visitor engagement. However, there remains a lack of a comprehensive model to guide such developments. This study aims to propose the Conversational AI-powered Virtual Reality Development Model for Tourism Promotion in Thailand, providing an integrated and… Read full abstract & cite →

Virtual reality conversational AI Model Development digital tourism technology adoption

Abstract doi.org/10.14569/IJACSA.2025.0161073 PDF

74

Roadmap for Emerging Cyberbullying Mitigation: Integrating AI-Based Solutions, Ethics, and Policy

Author 1: Atif Mahmood Author 2: Shaik Shabana Anjum Author 3: Umm E Mariya Shah Author 4: Pavani Cherukuru Author 5: Javid Iqbal Author 6: Sarah Bukhari

Cyberbullying is one of these challenges that are most found among the younger users of social media which affects the mental health. Artificial Intelligence (AI) is rapidly developing and has enormous potential to mitigate cyberbullying. Therefore, this chapter will talk about the role AI has started playing in strengthening the… Read full abstract & cite →

Cyberbullying human computer interaction artificial intelligence natural language processing machine learning content moderation predictive analytics online safety youth protection mental health mental illness cybercrime

Abstract doi.org/10.14569/IJACSA.2025.0161074 PDF

75

Intelligent Visualization and Knowledge Graph Analysis for Trend Detection

Author 1: Sunan Lv

This research employs scientometric examination and visual analytics techniques anchored in the Web of Science (WoS) repository to methodically delineate predominant research themes, foundational academic works, and emerging scholarly directions within industry-education integration studies. The investigation seeks to elucidate the discipline's epistemological framework and longitudinal transformation patterns while offering innovative… Read full abstract & cite →

Reviewer industry-education integration hotspot visualization and analysis

Abstract doi.org/10.14569/IJACSA.2025.0161075 PDF

76

An Efficient and Scalable Reinforcement Learning-Driven Intelligent Resource Management and Secure Framework for LoRaWAN

Author 1: Shaista Tarannum Author 2: Usha S. M

This study proposes a Q-learning-based adaptive duty cycle scheduling algorithm for LoRaWAN in a smart city eco-system to enhance the energy efficiency, reduce transmission delay, and handle dynamic traffic conditions. Additionally, it also incorporates an intelligent and efficient channel utilization scheme for LoRaWAN-enabled IoT networks and also integrates a lightweight… Read full abstract & cite →

LoRa LoRaWAN Q-learning adaptive duty cycle channel scheduling energy efficiency intrusion detection trust score resource management IoT security

Abstract doi.org/10.14569/IJACSA.2025.0161076 PDF

77

Real-Time Multi-Scale Object Detection in Surveillance Using Hybrid Transformer Architecture

Author 1: Roshan D Suvaris Author 2: Rahul Suryodai Author 3: S. Narayanasamy Author 4: Aanandha Saravanan Author 5: Raman Kumar Author 6: P N V Syamala Rao M Author 7: Elangovan Muniyandy

Real-time surveillance systems require accurate and efficient object detection to ensure safety and situational awareness. Existing methods, such as YOLOv5 and Vision Transformer-based detectors, often struggle to reliably identify small, distant, or occluded objects while maintaining real-time inference, limiting their applicability in complex surveillance environments. To address these challenges, this… Read full abstract & cite →

Real-time object detection hybrid transformer–YOLOv8 Context-Aware Feed Forward Network (CA-FFN) Cross-Scale Attention Skip Connections (CSASC) surveillance video analytics multi-scale feature fusion

Abstract doi.org/10.14569/IJACSA.2025.0161077 PDF

78

Aerial Draft Surveyor (ADS)

Author 1: John Matthew H. Escarro Author 2: Fharjan M. Taguinopon Author 3: Gyrielle Kysha M. Demegillo Author 4: Dan Kevin T. Amper Author 5: Rosanna C. Ucat Author 6: Mark John S. Pag-Alaman

Draft surveying is an essential procedure in determining the displacement and loaded cargo weight of bulk carriers. Currently, the most acceptable method is through manual visual observation by trained draft surveyors. However, this process is subjective, error-prone, and unsafe under poor visibility or during rough sea conditions. This study presents… Read full abstract & cite →

Draft survey UAV machine learning computer vision

Abstract doi.org/10.14569/IJACSA.2025.0161078 PDF

79

Privacy-Aware Federated Graph Neural Networks for Adaptive and Explainable Cancer Drug Personalization

Author 1: Tripti Sharma Author 2: Lakshmi K Author 3: M. Misba Author 4: Jasgurpreet Singh Chohan Author 5: R. Aroul Canessane Author 6: Komatigunta Nagaraju Author 7: Adlin Sheeba

Personalized cancer treatment remains challenging due to the complexity of genomic data and variability in drug responses. Previous federated learning (FL) approaches handled distributed patient data to preserve privacy but treated genomic and pharmacological features as flat, tabular inputs, limiting the ability to capture gene–drug interactions. In this study, we… Read full abstract & cite →

Graph Neural Networks cancer drug dosage privacy preservation genomic profiling precision oncology

Abstract doi.org/10.14569/IJACSA.2025.0161079 PDF

80

Hybrid Vision Transformer and MLP-Mixer for Epileptic Seizure Detection in Intracranial EEG

Author 1: Thouraya Guesmi Author 2: Abir Hadriche Author 3: Nawel Jmail

Accurate and timely seizure detection is essential for effective epilepsy management, and automated systems can play a valuable role in supporting clinical practice. In this study, we introduce a hybrid approach that uses time-frequency representations of Intracranial electroencephalography (iEEG) signals filtered at High-Frequency Oscillations (HFOs) bands as input to different… Read full abstract & cite →

Vision transformer MLP-Mixer iEEG HFOs ResNet GoogleNet EfficientNetB0

Abstract doi.org/10.14569/IJACSA.2025.0161080 PDF

81

Truth Under Pressure: A Deep Learning-Based Lie Detection System for Online Lending Using Voice Stress and Response Latency

Author 1: Ahmad Ihsan Farhani Author 2: Alhadi Bustamam Author 3: Rinaldi Anwar Author 4: Titin Siswantining

The rapid increase in defaults in the online lending industry highlights significant flaws in current debtor verification, which largely relies on static, preparable interviews, leading to high non-performing loans. Existing research is fragmented: while Large Language Models (LLMs) show promise in question generation, their application is confined to non-financial domains… Read full abstract & cite →

Online lending lie detection large language model deep learning voice acoustics response latency

Abstract doi.org/10.14569/IJACSA.2025.0161081 PDF

82

Classification of Mangrove Ecosystem Health Using Sentinel-2 Images with Genetic Algorithm Optimization in Machine Learning Algorithms

Author 1: Putri Yuli Utami Author 2: Murni Ramadhani Author 3: Rudi Alfian Author 4: Barry Ceasar Octariadi Author 5: Dimas Kurniawan

Mangrove ecosystems play an important role in maintaining coastal ecological balance, including as carbon sinks and natural protection from abrasion, but mangrove areas in Mempawah Regency have experienced significant degradation due to anthropogenic pressures. Therefore, this study aims to classify the health condition of mangroves using multi-temporal Sentinel-2 imagery with… Read full abstract & cite →

Classification genetic algorithm machine learning mangrove ecosystem Sentinel-2

Abstract doi.org/10.14569/IJACSA.2025.0161082 PDF

83

User Identity Confirmation Property Management System Based on State Secret Algorithm and Blockchain Technology

Author 1: Xiao Tian Author 2: Xing Chen

The existing user identity confirmation methods in property management systems are vulnerable to attacks and forgery, posing serious threats to system security and reliability. To address these issues, this study proposes a novel user identity confirmation method that combines the state secret SM9 algorithm with blockchain technology. The system utilizes… Read full abstract & cite →

User identification state secret algorithm blockchain technology property management system security

Abstract doi.org/10.14569/IJACSA.2025.0161083 PDF

84

Coordination, Communication and Robustness in Multi-Agents: An Industrial Network Scenario Using Trust Region Policy Optimization

Author 1: Munam Ali Shah

Numerous practical uses necessitate multi-agent systems, including managing traffic, assigning tasks, regulating ant colonies, and operating self-driving cars, and drones. These systems involve multiple agents working together, communicating and engaging with their surroundings to achieve the highest possible total numerical reward. Deep Reinforcement Learning (DRL) approaches are used to address… Read full abstract & cite →

Safety robustness reinforcement learning multi-agents safe state collaboration

Abstract doi.org/10.14569/IJACSA.2025.0161084 PDF

85

Spatiotemporal Graph Networks for Relational Reasoning in Campus Infrastructure Management

Author 1: Sanjay Agal Author 2: Krishna Raulji Author 3: Nikunj Bhavsar Author 4: Pooja Bhatt

The efficient management of campus infrastructure presents a complex spatiotemporal forecasting challenge characterized by dynamic interdependencies between physical assets. Traditional models fail to capture these intricate relationships as they treat buildings as independent entities or rely on static correlation structures. This paper introduces a novel Spatiotemporal Graph Neural Network (ST-GNN)… Read full abstract & cite →

Spatiotemporal Graph Neural Networks relational reasoning smart campus management infrastructure utilization forecasting graph attention networks temporal convolutional networks dynamic graph construction energy optimization predictive analytics

Abstract doi.org/10.14569/IJACSA.2025.0161085 PDF

86

A Voting-Based Ensemble Method for Deep Learning Performance Enhancement

Author 1: Mohammed Abdel Razek Author 2: Rania Salah El-Sayed Author 3: Arwa Mashat Author 4: Shereen A. El-aal

Overfitting and limited generalization remain significant challenges for deep learning models, often leading to suboptimal performance on unseen data. To address this, The Divided Ensemble Voting (DEV) method was introduced, a novel approach that strategically partitions a dataset into distinct sub-sets to train an independent model on each partition. This… Read full abstract & cite →

Divided Ensemble Voting (DEV) deep learning (DL) CNN binary classification performance metrics

Abstract doi.org/10.14569/IJACSA.2025.0161086 PDF

87

A Spatiotemporal Forex Trading System Based on a Hybrid Model GAT-LSTM: Forecasting Forex Price Directions

Author 1: Nabil MABROUK Author 2: Marouane CHIHAB Author 3: Younes CHIHAB

Due to the high volatility and complex interdependencies within financial markets, predicting Forex prices becomes a difficult challenge for investors. Furthermore, the traditional trading models struggle to capture those relationships. To address this issue, we introduced a spatiotemporal Forex trading system, GAT-LSTM-based; it is a hybrid approach that combines Graph… Read full abstract & cite →

Forex trading hybrid deep learning model Graph Attention Network (GAT) Long Short-Term Memory (LSTM) spatiotemporal forecasting

Abstract doi.org/10.14569/IJACSA.2025.0161087 PDF

88

Experimental Validation of an Adaptive Controller for a Mecanum-Wheel Robot with Unknown Center-of-Gravity Offset and Slope Inclination

Author 1: Chawannat Chaichumporn Author 2: Supaluk Prapan Author 3: Nghia Thi Mai Author 4: Md Abdus Samad Kamal Author 5: Iwanori Murakami Author 6: Kou Yamada

High-precision path tracking for a Four-Mecanum-Wheel Mobile Robot (FMWMR) is challenged by real-world factors such as payload-induced shifts in the center-of-gravity (CoG) and operation on inclined surfaces. These uncertainties introduce complex, coupled dynamic forces that degrade the performance of conventional controllers. This study addresses this problem with a Model Reference… Read full abstract & cite →

Model reference adaptive control Mecanum Wheel Robot center of gravity offset

Abstract doi.org/10.14569/IJACSA.2025.0161088 PDF

89

Enhancing Out-of-Distribution Detection for Retail Time-Series Data Using Entropic Methods

Author 1: Nga Nguyen Thi Author 2: Tuan Vu Minh Author 3: Khanh Nguyen-Trong

Machine learning models are typically developed under the “closed-world” assumption, where training and testing data originate from a consistent distribution. However, in real-world scenarios, especially in the retail domain, this assumption can become problematic due to the frequent introduction of new products, seasonal promotions, and irregular sales events. When models… Read full abstract & cite →

Out-of-Distribution Detection entropic learning IsoMax+ loss time-series classification retail forecasting deep learning spectrogram transformation

Abstract doi.org/10.14569/IJACSA.2025.0161089 PDF

90

A Review of Artificial Intelligence in Inventory Management: Methods, Applications and Directions

Author 1: Jinjin Li Author 2: Huijun Huang Author 3: Yuping Gong Author 4: Lei Wang Author 5: Xiangui Yin Author 6: Yichang Liu

Effective inventory management is fundamental to supply chain resilience and efficiency. Artificial intelligence (AI) has emerged as a transformative solution that enables more dynamic and data-driven inventory strategies. To map the latest advancements in this rapidly evolving field, this study presents a systematic literature review (SLR) of AI techniques in… Read full abstract & cite →

Inventory management artificial intelligence demand forecasting inventory control inventory classification machine learning

Abstract doi.org/10.14569/IJACSA.2025.0161090 PDF

91

Glioma Classification Using Harris Hawks-Driven Optimized Gradient Boosting Classifier Along with SHAP-Based Interpretability

Author 1: SM Naim Author 2: Jun-Jiat Tiang Author 3: Abdullah-Al Nahid

Gliomas are considered one of the most lethal and aggressive types of brain cancer, responsible for countless deaths worldwide. This study seeks to improve glioma classification using cutting-edge machine learning (ML) techniques to differentiate between glioma subtypes based on clinical and genomic data. The goal is to identify important biomarkers… Read full abstract & cite →

Glioma gradient boosting Harris Hawks Optimization (HHO) SHAP feature selection interpretability TCGA IDH1 EGFR

Abstract doi.org/10.14569/IJACSA.2025.0161091 PDF

92

Federated Performance-based Averaging (FedPA): A Robust and Selective Learning Framework for Chest X-Ray Classification in Heterogeneous Data Environments

Author 1: Atif Mahmood Author 2: Tashin Khan Sadique Author 3: Saaidal Razalli Azzuhri Author 4: Roziana Ramli Author 5: Leila Ismail

Chest X-ray imaging remains a cornerstone in the diagnosis of thoracic conditions such as COVID-19, pneumonia, and lung opacity. Despite advancements in deep learning, the development of robust and generalizable models is limited by data privacy constraints, as patient data cannot be centralized across institutions. Federated Learning (FL) has emerged… Read full abstract & cite →

Public health industrial growth federated learning FedAvg FedPA FedSGD

Abstract doi.org/10.14569/IJACSA.2025.0161092 PDF

93

Privacy-Preserving Education Data Sharing Scheme Based on Consortium Blockchain

Author 1: Jiaqi Guo Author 2: Zhuoran Wang Author 3: Ningning Liu

With the growing emphasis on lifelong education and the rapid expansion of open education platforms, the secure and efficient management and sharing of lifelong learning data have become critical challenges. To address these issues, this paper proposes a Privacy-Preserving Educational Data Sharing (PPEDS) scheme based on blockchain technology. The PPEDS… Read full abstract & cite →

Consortium blockchain access control secure search life-long education data sharing

Abstract doi.org/10.14569/IJACSA.2025.0161093 PDF

94

RT-DETR Edge Deployment: Real-Time Detection Transformer for Distracted Driving Detection

Author 1: Fares Hamad Aljahani

Distracted driving is one of the primary contributors to road accidents worldwide, highlighting the urgent need for reliable in-cabin driver monitoring systems. Existing approaches often face trade-offs: CNN-based classifiers achieve high recognition accuracy but lack spatial localization, while lightweight real-time detectors sacrifice contextual reasoning for efficiency. To bridge this gap… Read full abstract & cite →

RT-DETR real-time inference autonomous vehicles

Abstract doi.org/10.14569/IJACSA.2025.0161094 PDF

95

Breast Cancer Classification Using Ensemble Voting: A Feature Selection Approach

Author 1: Antu Kumar Guha Author 2: Jun-Jiat Tiang Author 3: Abdullah-Al Nahid

Breast cancer is one of the most common and deadly diseases affecting women around the worldwide. It is specially affecting in regions where has limited access to advanced diagnostic tools. Recent studies have shown that blood-based biomarkers can give a cost-effective alternative for early detection. This paper represents a machine… Read full abstract & cite →

Breast cancer machine learning feature selection ensemble learning AdaBoost biomedical data classification

Abstract doi.org/10.14569/IJACSA.2025.0161095 PDF

96

A Two-Stage Framework for Abnormalities Detection in WCE Images by Combining Semantic Segmentation and Deformable Agent-Based Classification

Author 1: Brahim Alibouch Author 2: Yasmina El Khalfaoui

Wireless capsule endoscopy (WCE) has revolutionized gastrointestinal (GI) diagnostics by offering a patient-friendly imaging and diagnostic tool compared to traditional endoscopic techniques. However, the manual assessment of these images is a time-consuming task and is prone to inaccuracies, which necessitates the implementation of automated approaches. In this paper, we introduce… Read full abstract & cite →

Wireless capsule endoscopy deep learning classification gastrointestinal abnormalities

Abstract doi.org/10.14569/IJACSA.2025.0161096 PDF

97

Predicting Employee Attrition in the Saudi Private Sector Using Machine Learning

Author 1: Haya Alqahtani Author 2: Hana Almagrabi Author 3: Amal Alharbi

Employee attrition represents a prominent issue facing organizations, as human capital represents one of the most valuable resources. Attrition refers to the voluntary or involuntary reduction in the number of employees, which can negatively affect profitability, reputation, and overall organizational performance. Therefore, a comprehensive understanding of this phenomenon, its causal… Read full abstract & cite →

Employee attrition attrition prediction predictive models machine learning voting classifier ensemble methods Saudi private sector employee turnover employee retention feature importance

Abstract doi.org/10.14569/IJACSA.2025.0161097 PDF

98

Optimizing Asset Transfer Process in ERP Using Business Process Management Technique

Author 1: Ravindu Yasarathne Author 2: Naduni Ranatunga Author 3: Vikasitha Herath Author 4: Lakshan Chalinda Author 5: Chathurangika Kahandawaarachchi Author 6: Sanjeeva Perera Author 7: Chamath Randula

Enterprise Resource Planning (ERP) systems are critical for managing enterprise-wide business processes, including asset management. Yet, many ERP platforms lack efficient mechanisms for bulk asset transfers, leading to high manual effort, increased costs, and data inconsistencies. This study applies Business Process Reengineering (BPR) techniques as the methodology to optimize ERP… Read full abstract & cite →

Asset management bulk asset transfer Business Process Reengineering (BPR) Enterprise Resource Planning (ERP) workflow optimization

Abstract doi.org/10.14569/IJACSA.2025.0161098 PDF

99

Stochastic Policies, Deterministic Minds: A Calibrated Evaluation Protocol and Diagnostics for Deep Reinforcement Learning

Author 1: Sooyoung Jang Author 2: Seungho Yang Author 3: Changbeom Choi

Deep reinforcement learning (DRL) typically in-volves training agents with stochastic exploration policies while evaluating them deterministically. This discrepancy between stochastic training and deterministic evaluation introduces a potential objective mismatch, raising questions about the validity of current evaluation practices. Our study involved training 40 Proximal Policy Optimization agents across eight Atari… Read full abstract & cite →

Deep reinforcement learning policy evaluation stochastic policy temporal difference error Atari PPO

Abstract doi.org/10.14569/IJACSA.2025.0161099 PDF

100

Expert Systems in Tuberculosis Prevention Established in Certainty Factor

Author 1: Inooc Rubio Paucar Author 2: Cesar Yactayo-Arias Author 3: Laberiano Andrade-Arenas

Tuberculosis remains a highly relevant public health concern, especially in contexts with limited access to medical services, highlighting the need for tools that support early diagnosis. In this study, a web-based expert system was developed to assist in tuberculosis detection, using Buchanan’s methodology, which consists of five phases: identification, conceptualization… Read full abstract & cite →

Buchanan’s methodology certainty factor expert system public health tuberculosis web application

Abstract doi.org/10.14569/IJACSA.2025.01610100 PDF

101

Feature-Optimized Machine Learning for High-Accuracy Ammunition Detection in X-Ray Security Screening

Author 1: Osama Dorgham Author 2: Nijad Al-Najdawi Author 3: Mohammad H. Ryalat Author 4: Sara Tedmori Author 5: Sanad Aburass

This paper introduces a machine learning system that is feature-optimized to enhance the detection of concealed ammunition in X-Ray security imaging. The system integrates advanced image analysis techniques with a cascade-AdaBoost classifier and Multi-scale Block Local Binary Pattern (MB-LBP) features, which are particularly effective for object recognition and classification in… Read full abstract & cite →

Feature optimization ammunition detection X-Ray images machine learning security imaging

Abstract doi.org/10.14569/IJACSA.2025.01610101 PDF

102

Evaluating Transparency in the Development of Artificial Intelligence Systems: A Systematic Literature Review

Author 1: Giulia Karanxha Author 2: Paulinus Ofem

Transparency is increasingly recognised as a cornerstone of trustworthy artificial intelligence (AI), yet its operationalisation remains fragmented and underdeveloped. Existing methods often rely on qualitative checklists or domain-specific case studies, limiting comparability, reproducibility, and regulatory alignment. This paper presents a Systematic Literature Review (SLR) of 28 peer-reviewed studies that explicitly… Read full abstract & cite →

Artificial intelligence transparency evaluation trustworthy AI transparency metrics EU AI Act systematic literature review

Abstract doi.org/10.14569/IJACSA.2025.01610102 PDF

103

Auditable Real-Time Cold-Chain Monitoring with IoT and Blockchain Anchoring

Author 1: Mohamed DOUBIZ Author 2: Mouad BANANE Author 3: Abdelali ZAKRANI Author 4: Allae ERRAISSI

Safe vaccine storage hinges on continuous, trust-worthy temperature supervision and evidence that records have not been altered. Yet many cold rooms still rely on fragmented logging tools that lack real-time alerts, end-to-end traceability, and audit-ready data. This paper presents a practical, low-cost architecture that integrates Internet of Things (IoT) sensing… Read full abstract & cite →

Internet of Things blockchain cold chain vaccine storage real-time monitoring tamper-evident data provenance traceability

Abstract doi.org/10.14569/IJACSA.2025.01610103 PDF

104

Systematic Literature Review of Reactive Jamming Attacks Mitigation Techniques in Internet of Things Networks

Author 1: Enos Letsoalo Author 2: Topside Mathonsi Author 3: Tshimangadzo Tshilongamulenzhe Author 4: Daniel du Duplesis

Internet of Things (IoT) networks have become a prevalently exploited research area in academia and industry. IoT networks benefit from a variety of applications, including smart cities, smart homes, intelligent transportation, smart agriculture, monitoring, surveillance, etc. The security challenges associated with IoT networks have been broadly studied in the literature… Read full abstract & cite →

IoT networks reactive jamming attacks mitigation methods systematic literature review electronic digital libraries

Abstract doi.org/10.14569/IJACSA.2025.01610104 PDF

105

Virtual Assistant Based on Recurrent Neural Networks: Scope and Coverage of Health Insurance

Author 1: Diego Alberto Paz-Medina Author 2: David Eduardo Rojas-Cavassa Author 3: Ernesto Adolfo Carrera-Salas

In Peru, the use of health services provided by state institutions has decreased, largely due to perceived deficiencies in care quality, such as delays in medical attention and administrative barriers that hinder timely access to information on insurance scope and coverage. This study develops a web-based application with an integrated… Read full abstract & cite →

Insurance insurance coverage web application chatbot Recurrent Neural Networks

Abstract doi.org/10.14569/IJACSA.2025.01610105 PDF

106

Text Information Data Mining Method in Natural Language Processing Tasks

Author 1: Shengguo Guo Author 2: Dandan Xing

Text mining methods often rely on a single data source or simple word frequency statistics, making it difficult to capture multi-source text semantic associations and local contextual dependencies, resulting in poor mining accuracy. Therefore, a method for text information data mining in natural language processing tasks is proposed. Using Python… Read full abstract & cite →

Natural language processing text information data mining VSM TF-IDF BERT

Abstract doi.org/10.14569/IJACSA.2025.01610106 PDF

107

Document Similarity Detection for Project Development Using Fused Interactive Attention Mechanisms

Author 1: Chao Zhang Author 2: Ying Zhang Author 3: Gang Yang Author 4: Fan Hu

This study introduces a novel multi-feature fusion model aimed at improving text similarity calculation in scientific and technological projects. The primary objective is to enhance the accuracy and efficiency of assessing text similarities, particularly in evaluating originality and identifying duplications in project submissions. To overcome the limitations of traditional text… Read full abstract & cite →

Text similarity multi-feature fusion model word2vec cw2vec MP-CNN fusion attention mechanism semantic extraction project evaluation

Abstract doi.org/10.14569/IJACSA.2025.01610107 PDF

108

A Comparison Between FAHP-TOPSIS and FAHP-FTOPSIS Methods for Selecting the Best Products for Home-Based Sellers: A Performance Analysis

Author 1: Selvia Lorena Br Ginting Author 2: Zulaiha Ali Othman

This study discusses common problems faced by home-based sellers in determining the right product ideas to sell. To overcome this problem, a method is needed that can help home-based sellers to choose the right product. Therefore, a decision support system using a multi-criteria decision-making technique with a hybrid approach was… Read full abstract & cite →

Home-based sellers product selection FAHP-TOPSIS FAHP-FTOPSIS sensitivity analysis

Abstract doi.org/10.14569/IJACSA.2025.01610108 PDF