IJACSA Vol. 16 Issue 9 (2025)

1

Cognitive Biases: Understanding and Designing Fair AI Systems for Software Development

Author 1: Sheriff Adepoju Author 2: Mildred Adepoju

Artificial Intelligence (AI) systems increasingly influence decisions that affect people's lives, making fairness a core requirement. However, cognitive biases, systematic deviations in human judgment, can enter AI through data, modeling choices, and oversight, amplifying social inequities. This paper examines how three bias channels, data, algorithmic, and human, manifest across the… Read full abstract & cite →

Cognitive biases fair AI systems algorithmic bias software development bias mitigation fairness software engineering

Abstract doi.org/10.14569/IJACSA.2025.0160901 PDF

2

Multispectral Image Analysis Using Deep Neural Networks

Author 1: Arun D. Kulkarni

Multispectral image classification plays a crucial role in remote sensing applications such as land cover mapping, agricultural monitoring, and environmental surveillance. Traditional classification techniques, including the Maximum Likelihood Classifier (MLC), Support Vector Machine (SVM), Decision Tree (DT), and Multi-Layer Perceptron (MLP), often struggle with the complexity and high dimensionality of… Read full abstract & cite →

Remote sensing classification deep neural networks Landsat scene

Abstract doi.org/10.14569/IJACSA.2025.0160902 PDF

3

LegalSummNet: A Transformer-Based Model for Effective Legal Case Summarization

Author 1: Md Farhad Kabir Author 2: Sohana Afrin Mitu Author 3: Sharmin Sultana Author 4: Belal Hossain Author 5: Rakibul Islam Author 6: Khandakar Rabbi Ahmed

Expanding legal documents has become increasingly complicated and presents a greater challenge to legal professionals in extracting relevant information efficiently. In this paper, a new two-stage hybrid summarization system, called LegalSummNet, is introduced. It excels in handling the peculiarities of legal texts, such as their extremely long length, complex syntax… Read full abstract & cite →

Legal document summarization NLP extractive and abstractive summarization transformer LegalSummNet BERT LegalT5 ROUGE-L

Abstract doi.org/10.14569/IJACSA.2025.0160903 PDF

4

Real-Time Dynamic Pricing Using Machine Learning: Integrating Customer Sentiment and Predictive Models for E-Commerce

Author 1: Areyfin Mohammed Yoshi Author 2: Arafat Rohan Author 3: Sohana Afrin Mitu Author 4: Md Masud Karim Rabbi Author 5: Shahanaj Akther Author 6: Khandakar Rabbi Ahmed

Dynamic pricing has emerged as a crucial strategy for e-commerce platforms to maximize profitability while remaining competitive in rapidly changing digital markets. Traditional pricing methods often fail to capture the complexity of customer behavior and the rapid evolution of market trends. To address these limitations, this study introduces a machine… Read full abstract & cite →

Dynamic pricing machine learning XGBoost’ e-commerce analytics revenue optimization

Abstract doi.org/10.14569/IJACSA.2025.0160904 PDF

5

A Scalable Microservices Architecture for Real-Time Data Processing in Cloud-Based Applications

Author 1: Desidi Narsimha Reddy Author 2: Rahul Suryodai Author 3: Vinay Kumar S. B Author 4: M. Ambika Author 5: Elangovan Muniyandy Author 6: V. Rama Krishna Author 7: Bobonazarov Abdurasul

In today’s data-intensive landscape, the exponential growth of digital applications and IoT devices has heightened the demand for real-time data processing within cloud-native environments. Traditional monolithic systems struggle to meet the low-latency, high-availability requirements of modern workloads, prompting a shift toward microservices architectures. However, existing microservices-based approaches face persistent challenges… Read full abstract & cite →

Microservices architecture real-time data processing cloud-native systems Kubernetes orchestration API gateway

Abstract doi.org/10.14569/IJACSA.2025.0160905 PDF

6

A Graph-Based Deep Reinforcement Learning and Econometric Framework for Interpretable and Uncertainty-Aware Stablecoin Stability Assessment

Author 1: Yaozhong Zhang Author 2: Quanrong Fang

The instability of algorithmic and hybrid stablecoins has become a systemic concern in decentralized finance. This paper proposes a unified, interpretable, and uncertainty-aware framework that integrates graph-based deep reinforcement learning, GARCH econometric modeling, and Bayesian inference. Multi-stage reinforcement learning agents simulate interactions between arbitrageurs and protocol mechanisms. GARCH models capture… Read full abstract & cite →

Stablecoin stability deep reinforcement learning graph neural networks uncertainty quantification macro prudential policy

Abstract doi.org/10.14569/IJACSA.2025.0160906 PDF

7

Embedded System for ECG Signal Monitoring and Fatigue Detection in Elderly Individuals Using Machine Learning Models

Author 1: Chokri Baccouch Author 2: Chaima Bahar

Ascertaining fatigue in elderly people is crucial both for preventing future health complications and for enhancing their quality of life. In this paper, we present an embedded system for real-time fatigue detection and monitoring based on electrocardiogram (ECG) signals, leveraging cost-effective sensors and advanced deep learning architectures. The proposed framework… Read full abstract & cite →

Fatigue ECG AI classification GRU LSTM RNN

Abstract doi.org/10.14569/IJACSA.2025.0160907 PDF

8

Deep Reinforcement Learning-Based Target Detection and Autonomous Obstacle Avoidance Control for UAV

Author 1: Like Zhao Author 2: Hao Liu Author 3: Guangmin Gu Author 4: Fei Wan Author 5: Yanyang Feng

To address the challenges faced by distribution network monitoring systems—such as significant variations in anomaly scale, frequent missed and false detections of small-scale faults, and the need for real-time operational control—this paper proposes a lightweight multi-scale feature fusion detection network combined with a deep reinforcement learning-based autonomous control strategy, forming… Read full abstract & cite →

Target detection multi-scale lightweight YOLOv8 autonomous obstacle avoidance

Abstract doi.org/10.14569/IJACSA.2025.0160908 PDF

9

Beyond Words: An Advanced Ensemble Framework for Unmasking AI-Generated Content Through Linguistic Fingerprinting

Author 1: Ghada Y. Elwan Author 2: Doaa R. Fathy Author 3: Nahed M. El Desouky Author 4: Abeer S. Desuky

AI-generated content detection is vital because it helps to uphold digital integrity in most fields of application, such as in academic publishing and content verification. The process of identifying text authenticity and traceability of the source is dependent on proper detection means. The approach introduced in this paper is a… Read full abstract & cite →

AI detection machine learning text classification ensemble methods content verification

Abstract doi.org/10.14569/IJACSA.2025.0160909 PDF

10

Reliability Risk Assessment Approaches in Software Engineering: A Review Structured by Software Development LifeCycle (SDLC) Phases and Reliable Sub-Characteristics

Author 1: Lehka Subramanium Author 2: Saadah Hassan Author 3: Mohd. Hafeez Osman Author 4: Hazura Zulzalil

Reliability risk is a critical concern in software development, as failures can result in system downtime, degraded performance, data integrity issues, financial losses and loss of user trust. The increasing complexity of modern systems, driven by dynamic workloads, distributed architecture, and unpredictable interactions, amplifies these risks. In regulated industries like… Read full abstract & cite →

Reliability risk assessment SDLC

Abstract doi.org/10.14569/IJACSA.2025.0160910 PDF

11

WiTS: A Wi-Fi-Based Human Action Recognition via Spatio-Temporal Hybrid Neural Network

Author 1: Pengcheng Gao

Human action recognition has many applications in different scenarios. With the advancement of wireless sensing and the widespread deployment of Wi-Fi devices, the perception technology of Wi-Fi channel state information (CSI) has shown great potential. Related studies identified actions by capturing specific attenuation and distortion features caused by human posture… Read full abstract & cite →

Wi-Fi CSI human action recognition deep learning

Abstract doi.org/10.14569/IJACSA.2025.0160911 PDF

12

Automated Scoliosis Diagnosis in Spinal Imaging: Laboratory Validation, Clinical Limitations, and Systematic Implementation Challenge Review

Author 1: Ervin Gubin Moung Author 2: Xie Aishu Author 3: Ali Farzamnia

Technological advances in automated medical imaging diagnosis have created translation gaps between laboratory achievements and clinical implementation, with traditional manual Cobb angle measurement requiring considerable time with inevitable measurement errors. This review analyzes translation challenges in automated diagnosis systems using scoliosis assessment as a case study, examining 55 articles from… Read full abstract & cite →

Automated diagnosis medical imaging scoliosis Cobb angle clinical implementation artificial intelligence

Abstract doi.org/10.14569/IJACSA.2025.0160912 PDF

13

Adaptive Trust-Based Fault Tolerance for Multi-Drone Systems: Theory and Application in Agriculture

Author 1: Atef GHARBI Author 2: Faheed A. F. Alrslani

This paper presents RobotTrust, an adaptive trust framework for fault-tolerant coordination in multi-drone systems for precision agriculture. The study aims to improve mission reliability under sensor/actuator faults and uncertain interactions by combining a structured fault taxonomy (behavioral, actuator, sensor) with team-based recovery and an adaptive trust model that integrates direct… Read full abstract & cite →

Adaptive trust model trust-aware robotics multi-drone coordination fault-tolerant systems precision agriculture applications

Abstract doi.org/10.14569/IJACSA.2025.0160913 PDF

14

Method for Person Re-Identification with 2D-to-3D Image (Image-to-Video) Conversion

Author 1: Kohei Arai

A method for person re-identification using image-to-video conversion tools is proposed. The proposed method involves matching two images taken from different viewpoints: a reference image captured in advance and a current image captured in real-time to identify the person in concern in the current image, whose image is matched to… Read full abstract & cite →

Person re-identification identification performance 2D-to-3D image conversion method TRIPO CSM KLING

Abstract doi.org/10.14569/IJACSA.2025.0160914 PDF

15

Design of a Modular Architecture Based on AI and Blockchain for Personalized Microcredits Using Open Finance

Author 1: Pedro Hidalgo Author 2: Ciro Rodríguez Author 3: Luis Bravo Author 4: Cesar Angulo

This paper presents the design and validation of a modular architecture for smart microcredits, aimed at expanding credit access for populations excluded from the traditional financial system. The solution integrates three key technological components: data acquisition through Open Finance, automated risk assessment using Artificial Intelligence (AI) models, and the execution… Read full abstract & cite →

Smart microcredits artificial intelligence open finance blockchain smart contracts financial inclusion

Abstract doi.org/10.14569/IJACSA.2025.0160915 PDF

16

Mathematical Representation of Netflow Analysis Decision Making Based on Production Logic

Author 1: Alimdzhan Babadzhanov Author 2: Inomjon Yarashov Author 3: Maruf Juraev Author 4: Alisher Otakhonov Author 5: Adilbay Kudaybergenov Author 6: Rustam Utemuratov

In the sphere of NetFlow traffic analysis, accurate detection of anomalous behavior in real time remains a critical challenge. This study will present a mathematical representation for decision making in NetFlow analysis, production implementation logic for automated expert knowledge. A specialized software system will be developed for collecting and processing… Read full abstract & cite →

Production rules packet features PCAP network events netflow production logic confusion matrix

Abstract doi.org/10.14569/IJACSA.2025.0160916 PDF

17

AI-Enabled Demand Forecasting, Technological Capability, and Supply Chain Performance: Empirical Evidence from the Global Logistics Sector

Author 1: Mohamed Amine Frikha Author 2: Mariem Mrad

This study advances understanding of artificial intelligence (AI) integration within supply chain management, with a particular emphasis on AI-enabled demand forecasting. The research examines 1) the extent of adoption of AI-driven forecasting practices, 2) the role of technological and organizational readiness, captured through data infrastructure, workforce skills, and management support… Read full abstract & cite →

AI-enabled demand forecasting technological capability data infrastructure workforce skills management support supply chain performance artificial intelligence

Abstract doi.org/10.14569/IJACSA.2025.0160917 PDF

18

A Starfish Optimization Algorithm-Based Federated Learning Approach for Financial Risk Prediction in Manufacturing Enterprises

Author 1: Bin Liu Author 2: Liang Chen Author 3: Haitong Jiang Author 4: Rui Ma

During digital transformation, manufacturing enterprises encounter challenges such as the high cost of smart devices, operational interruptions, and increased technology expenses, raising their financial risks. Addressing the digital transformation challenges confronting manufacturing enterprises necessitates developing an intelligent financial risk prediction system leveraging AI technologies like big data and deep learning… Read full abstract & cite →

Deep learning neural Turing machine prediction starfish optimization algorithm federated learning

Abstract doi.org/10.14569/IJACSA.2025.0160918 PDF

19

User Requirements of Adaptive Learning Through Digital Game-Based Learning: User-Centered Design Approach to Enhance the Language Literacy Development

Author 1: Nur Atiqah Zaini Author 2: Tengku Siti Meriam Tengku Wook Author 3: Mohd Nor Akmal Khalid Author 4: Shahrul Azman Mohd Noah

This study aims to elicit the user requirements of digital game-based learning among the primary students through adaptive digital game-based learning, with a focus on enhancing language literacy. Hence, acquiring the user requirements through user-centered design approach is emphasized to identify the specifications and provide practical insights for language learning… Read full abstract & cite →

Digital game-based learning adaptive learning artificial intelligence language literacy optimization primary students user experience

Abstract doi.org/10.14569/IJACSA.2025.0160919 PDF

20

Towards More Effective Automatic Question Generation: A Hybrid Approach for Extracting Informative Sentences

Author 1: Engy Yehia Author 2: Neama Hassan Author 3: Sayed AbdelGaber

Informative Sentence Extraction (ISE) is one of the crucial components in Automatic Question Generation (AQG) and directly influences the quality and relevancy of the generated questions. Instructional texts often contain not only informative but also irrelevant sentences. This results in the creation of poor-quality or distorted questions when irrelevant, non-informative… Read full abstract & cite →

Automatic Question Generation (AQG) informative sentence extraction NER SBERT question answering information gain fusion strategies

Abstract doi.org/10.14569/IJACSA.2025.0160920 PDF

21

An Integrated Evaluation Using Enhanced Panel Factor Model and Machine Learning: Assessing the Level and Structure of Regional Coordinated Development in the Guangdong-Hong Kong-Macao Greater Bay Area

Author 1: Li Shi Author 2: Ting Nie

Regional sustainable and coordinated development has become a central issue in the backdrop of a reshaped global economic landscape. Therefore, it is particularly important to evaluate the level of regional coordinated development effectively. This study aimed to validate and assess the effectiveness of machine learning algorithms and the Enhanced Panel… Read full abstract & cite →

Comprehensive evaluation machine learning regional coordinated development comparative analysis

Abstract doi.org/10.14569/IJACSA.2025.0160921 PDF

22

CrypTen-FL: A Secure Federated Learning Framework for Multi-Disease Prediction from MIMIC-IV Using Encrypted EHRs

Author 1: Himanshu Author 2: Pushpendra Singh

The increasing demand for privacy-preserving machine learning in healthcare has driven the need for federated approaches that ensure data confidentiality across institutions. In this work, we present CrypTen-FL, a secure federated learning framework for disease prediction using the MIMIC-IV electronic health record (EHR) dataset. CrypTen-FL enables collaborative model training across… Read full abstract & cite →

Federated learning secure multi-party computation electronic health records disease prediction MIMIC-IV

Abstract doi.org/10.14569/IJACSA.2025.0160922 PDF

23

Is Metaverse Technology Ready to Welcome Online Banking Users?

Author 1: Yantu Ma Author 2: Dalbir Singh Author 3: Siok Yee Tan Author 4: Meng Chun Lam Author 5: Ab Ghani Nur Laili Author 6: Haodong Guan Author 7: Fengjin Lei Author 8: Ahmad Sufril Azlan Mohamed

The advent of the Web 3.0 era has precipitated the gradual emergence of Metaverse technology as the frontier of next-generation interactive technology transformation in banking. Nevertheless, a considerable disparity exists between the user experience of Metaverse banking in virtual interactive environments and traditional online banks. Consequently, in the nascent stages… Read full abstract & cite →

Banking human-computer interaction information systems Metaverse virtual reality

Abstract doi.org/10.14569/IJACSA.2025.0160923 PDF

24

Optimizing Image Retrieval: A Two-Step Content-Based Image Retrieval System Using Bag of Visual Words and Color Coherence Vectors

Author 1: Muhammad Sauood Author 2: Muhammad Suzuri Hitam Author 3: Wan Nural Jawahir Hj Wan Yussof

Content-Based Image Retrieval (CBIR) systems play a crucial role in efficiently managing and retrieving images from large datasets based on visual content. This paper presents a novel bi-layer CBIR system that integrates Bag of Visual Words (BoVW) and Color Coherence Vector (CCV) methods to enhance image retrieval accuracy and performance… Read full abstract & cite →

CBIR system Bag of Visual Words color coherence vectors bi-layer CBIR two-step CBIR feature fusion feature extraction

Abstract doi.org/10.14569/IJACSA.2025.0160924 PDF

25

An Aggregated Dataset of Agile User Stories and Use Case Taxonomy for AI-Driven Research

Author 1: Abdulrahim Alhaizaey Author 2: Majed Al-Mashari

Agile methodologies are considered revolutionary approaches in the development of systems and software. With the rapid advancement of artificial intelligence, natural language processing, and large language models, there is an increasing demand for high-quality datasets to support the design and development of intelligent, practical, and effective automation tools. However, researchers… Read full abstract & cite →

Agile software development requirements engineering user stories natural language processing datasets large language models generative language models

Abstract doi.org/10.14569/IJACSA.2025.0160925 PDF

26

Comparative Evaluation of Centrality Measures for Detecting Significant Nodes in Social Networks

Author 1: Hardeep Singh Author 2: Supreet Kaur Author 3: Karman Singh Sethi Author 4: Jai Sharma

Social networks are certainly a crucial platform for bringing people together globally. Detecting the significant nodes inside the social network remains an open problem because of the broad variety of network sizes. To solve this problem, different centrality measures have been introduced. Detecting the significant nodes is essential for speeding… Read full abstract & cite →

Social networks centrality measures significant nodes validation metrics extended gravity

Abstract doi.org/10.14569/IJACSA.2025.0160926 PDF

27

Neural Networks for Pest Diagnosis in Agriculture: A Global Literature Review

Author 1: Heling Kristtel Masgo Ventura Author 2: Italo Maldonado Ramírez Author 3: Roberto Carlos Santa Cruz Acosta Author 4: Wilfredo Ruiz Camacho Author 5: Juan Eduardo Suarez Rivadeneira Author 6: José Celso Paredes Carranza Author 7: Mayra Pamela Musayón Díaz Author 8: Cesar R. Balcazar Zumaeta Author 9: Carlos Luis Lobatón Arenas Author 10: Juan Alberto Rojas Castillo Author 11: Eli Morales-Rojas

Agricultural pests severely reduce global crop yields. To mitigate these losses, pest identification systems based on artificial intelligence have gained importance. This review analyzes worldwide advances in the use of neural networks for agricultural pest diagnosis, covering studies from 2007 to February 2024 retrieved from the Scopus database. Data were… Read full abstract & cite →

Neural networks pests agriculture developing countries

Abstract doi.org/10.14569/IJACSA.2025.0160927 PDF

28

Evaluating User Experience in a Public Sector Digital System Through Nielsen’s Heuristic Approach

Author 1: Nagyan Yosse Wibisono Author 2: Viany Utami Tjhin

The digital transformation in public administration has encouraged the Indonesian National Police (Polri) to adopt a digital government application for managing official documents electronically. Despite its functional benefits, users have reported several usability issues such as non-intuitive navigation, inconsistent interface design, inadequate system feedback, and insufficient documentation. To systematically address… Read full abstract & cite →

Usability evaluation heuristic evaluation user experience digital government PLS-SEM public sector technology UX mining usability modeling

Abstract doi.org/10.14569/IJACSA.2025.0160928 PDF

29

NEBULA Framework: An Adaptive Framework for Unstructured Description to Solve Cold Start Problem

Author 1: I Gusti Agung Gede Arya Kadyanan Author 2: Ni Made Ary Esta Dewi Wirastuti Author 3: Gede Sukadarmika Author 4: Ngurah Agus Sanjaya ER

The cold start problem is one of the main challenges in recommendation systems, especially when the system has to provide recommendations for new items that do not yet have a history of interaction. Although various approaches have been developed, most still use conventional interaction-based methods, which are not optimal in… Read full abstract & cite →

Cold start adaptive framework recommender system NER unstructured description

Abstract doi.org/10.14569/IJACSA.2025.0160929 PDF

30

Analysis of Factors Affecting Continuance Intention in Indonesian Digital Banks

Author 1: Soros Lie Author 2: Viany Utami Tjhin

Indonesian Digital Banks are currently competing to get more customers with their own mobile application, digital finance ecosystem and their promotion method. The research aims to find out the factors that influence customer satisfaction when using the digital bank application. The variables used in this study are System Quality, Service… Read full abstract & cite →

Digital banking DeLone and McLean structural equation model continuance intention user satisfaction

Abstract doi.org/10.14569/IJACSA.2025.0160930 PDF

31

Generating a Trading Strategy Using Candlestick Patterns with Machine Learning

Author 1: Hussaina Bala Malami Author 2: Badamasi Imam Ya’u Author 3: Fatima Umar Zambuk Author 4: Mohannad Alkanan Author 5: Osman Elwasila Author 6: Mohammad Shuaib Mir Author 7: Mohammed Nasir Danmalam Bawa Author 8: Yonis Gulzar

This study examines the application of machine learning (ML) algorithms for multi-day stock price prediction on the Nigerian Stock Exchange (NSE) from 2013 to 2023, to inform trading strategies. Utilizing candlestick patterns and technical indicators, including Simple Moving Average (SMA), Exponential Moving Average (EMA), and Volume Rate of Change (VROC)… Read full abstract & cite →

Nigerian stock trading machine learning pattern recognition candlestick

Abstract doi.org/10.14569/IJACSA.2025.0160931 PDF

32

Advancing Speech Enhancement with Generative Adversarial Network-Autoencoder: A Robust Adversarial Autoencoder Approach

Author 1: Mandar Diwakar Author 2: Brijendra Gupta

In day-to-day life, the speech signals are often noisy and distorted by background noise. These signals are not suitable for use in different audio-operated applications directly, as they are distorted. The use of these noisy voice signals can degrade the performance of the speech communication system. There are a huge… Read full abstract & cite →

Speech enhancement Generative Adversarial Network (GAN) Autoencoder (AE) MFCC noise robustness adversarial training

Abstract doi.org/10.14569/IJACSA.2025.0160932 PDF

33

Enhancing Smart City Safety: Deep Learning Approaches for Automatic Vehicle Accident Recognition

Author 1: Ahad AlNemari Author 2: Shahad AlOtaibi Author 3: Majd Jada Author 4: Aeshah AlHarthi Author 5: Sara AlThuwaybi Author 6: Wojoud AlNemari Author 7: Nadan Marran Author 8: Abdulmajeed Alsufyani

Traffic accidents have significant societal impacts due to the substantial human and material losses they cause. Recently, numerous AI-based traffic surveillance technologies, such as Saher, have been implemented to improve traffic safety in Saudi Arabia. The prompt detection of vehicle accidents is crucial for enhancing the response time of accident… Read full abstract & cite →

Accident detection deep learning algorithms ResNet-101 traffic safety YOLOv5 YOLOv9

Abstract doi.org/10.14569/IJACSA.2025.0160933 PDF

34

Prioritizing Non-Functional Requirements and Influencing Factors for API Quality Framework: An Industry Approach

Author 1: Aumir Shabbir Author 2: Aziz Deraman Author 3: Mohamad Nor Bin Hassan Author 4: Kamal Uddin Sarker Author 5: Shahid Kamal

Application Programming Interface (API) management is currently a trending research area; however, APIs require careful attention to Non-Functional Requirements (NFRs) to ensure system performance, maintainability, security, and resiliency. The software industry struggles to maintain API quality, especially NFRs, due to a focus on functional aspects in standards like the OpenAPI… Read full abstract & cite →

Non-Functional Requirements (NFRs) Application Programming Interface (API) software development practices API quality Non-Functional Requirement Quality Framework for APIs (NFRQF-API) ISO/IEC 25010

Abstract doi.org/10.14569/IJACSA.2025.0160934 PDF

35

Perceived Usefulness and Perceived Ease of Use as Predictors of Attitude Toward IoT Adoption Among Rice Farmers

Author 1: Hermin Arrang Author 2: Sek Yong Wee Author 3: Nazrulazar Bin Bahaman Author 4: Jack Febrian Rusdi

This study investigates key drivers influencing rice farmers’ attitudes toward Internet of Things (IoT) adoption in Indonesia, using the Technology Acceptance Model (TAM) as an analytical lens. Specifically, it evaluates the predictive roles of Perceived Usefulness (PU) and Perceived Ease of Use (PEOU), both of which are posited to shape… Read full abstract & cite →

IoT attitude towards IoT Perceived Usefulness Perceived Ease of Use technology adoption

Abstract doi.org/10.14569/IJACSA.2025.0160935 PDF

36

An Analytical Review of Environmental and Machine Learning Approaches in Dengue Prediction

Author 1: Orlando Iparraguirre-Villanueva Author 2: Juan Chavez-Perez Author 3: Eddier Flores-Idrugo Author 4: Luis Chauca-Huete

In recent years, dengue has gained prominence as a priority public health challenge due to increasing incidences of spread. The main objective of this systematic literature review (SLR) is to explore the use of environmental factors and machine learning (ML) techniques to combat dengue, based on studies published between 2020… Read full abstract & cite →

Public health analytics machine learning models disease prediction environmental risk factors dengue surveillance health data analysis

Abstract doi.org/10.14569/IJACSA.2025.0160936 PDF

37

Assessing the Effectiveness of MCR-KSM for Waiting Waste Reduction: An Empirical Study

Author 1: Nargis Fatima Author 2: Sumaira Nazir Author 3: Suriayati Chuprat

Modern Code Review (MCR) is a well-known and widely adopted quality assurance activity to develop quality software. Although it is a core activity for improving code quality, it generates various types of waste, including waiting waste, defect waste, and composite solution waste. Besides all other wastes, the waiting waste is… Read full abstract & cite →

Modern code review wastes waiting waste software quality automated code review sustainable software engineering

Abstract doi.org/10.14569/IJACSA.2025.0160937 PDF

38

A Review of Attention-Enhanced GRU Models with STL Decomposition for Food Loss Forecasting

Author 1: Ru Poh Tan Author 2: Siew Mooi Lim Author 3: Kuan Yew Leong Author 4: Shee Chia Lee Author 5: Siaw Hong Liew Author 6: Jun Kit Chaw

Forecasting food loss with high accuracy is crucial for improving global food security, optimising supply chains, and supporting sustainability goals. However, conventional time series models and standard deep learning techniques, including recurrent neural networks (RNNs), often fall short in handling the irregularity, seasonality, and complexity inherent in food loss data… Read full abstract & cite →

GRU food loss forecasting attention mechanism seasonal decomposition STL loess time series deep learning

Abstract doi.org/10.14569/IJACSA.2025.0160938 PDF

39

An Incremental LSTM Ensemble for Online Intrusion Detection in Software-Defined Networks

Author 1: Raed Basfar Author 2: Mohamed Y. Dahab Author 3: Abdullah Marish Ali Author 4: Fathy Eassa Author 5: Kholoud Bajunaied

Software-Defined Networking (SDN) promises flexible control of network flows but also exposes controllers to rapidly shifting attack surfaces. Conventional intrusion-detection engines, trained once and deployed statically, falter when traffic patterns drift. We introduce an adaptive intrusion detection system that couples a mini-batch incremental learning scheme with a five-member ensemble of… Read full abstract & cite →

Software-defined networking intrusion detection incremental learning LSTM ensemble concept drift weighted voting

Abstract doi.org/10.14569/IJACSA.2025.0160939 PDF

40

Comprehensive Analysis of YOLOv8 + DeepSORT for Vehicle Tracking: HOTA and CLEAR-Based Evaluation

Author 1: I Nyoman Eddy Indrayana Author 2: Made Sudarma Author 3: I Ketut Gede Darma Putra Author 4: Anak Agung Kompiang Oka Sudana

This paper offers a thorough comparative investigation of the performance of a vehicle multi-object tracking system, incorporating various versions of the YOLOv8 detector (from ‘n’ to ‘x’) alongside the DeepSORT tracking algorithm. This study systematically assesses the impact of the trade-off between detector speed and accuracy on tracking metrics, utilising… Read full abstract & cite →

Multi-object tracking higher order tracking accuracy metric CLEAR Metric YOLOv8

Abstract doi.org/10.14569/IJACSA.2025.0160940 PDF

41

Sentence-Level Indonesian Sign Language (BISINDO) Recognition Using 3D CNN-LSTM and 3D CNN-BiLSTM Models

Author 1: Katriel Larissa Wiguna Author 2: Rojali

Sign Language Recognition (SLR) has been an active area of research, but sentence-level SLR remains relatively underexplored. While most studies focus on recognizing individual signs, understanding full sentences presents greater challenges. This research proposes a sentence-level SLR using a combination of 3D Convolutional Neural Networks (3D CNN) for spatio-temporal feature… Read full abstract & cite →

Sign Language Recognition BISINDO (Indonesian Sign Language) 3D Convolutional Neural Network (3D CNN) Long Short-Term Memory (LSTM) Network Bidirectional Long Short-Term Memory (BiLSTM) Connectionist Temporal Classification (CTC)

Abstract doi.org/10.14569/IJACSA.2025.0160941 PDF

42

Formal Verification of a Blockchain-Based Security Model for Personal Data Sharing Using the Dolev-Yao Model and ProVerif

Author 1: Godwin Mandinyenya Author 2: Vusumuzi Malele

Secure personal data sharing remains a critical challenge in decentralized systems due to concerns over privacy, compliance, and trust. This paper presents the formal verification of a Blockchain-Based Security Model (BSM) designed to address these challenges through a multi-layered architecture. The proposed model integrates Chaincode-as-a-Service (CCaaS) on Hyperledger Fabric to… Read full abstract & cite →

Blockchain security model Chaincode-as-a-Service InterPlanetary File System Intel Software Guard Extensions Zero-Knowledge Proofs ProVerif formal verification Dolev-Yao

Abstract doi.org/10.14569/IJACSA.2025.0160942 PDF

43

Enhancing Cybersecurity Programs in Small and Medium Enterprises (SMEs): A Systematic Literature Review

Author 1: Eliana Ludin Author 2: Masnizah Mohd Author 3: Fariza Fauzi

Small and Medium Enterprises (SMEs) in Malaysia face increasing cybersecurity risks, yet their adoption of Security Education, Training, and Awareness (SETA) programs remains limited. Unlike prior reviews that focus broadly on SMEs, this study contributes novelty by systematically synthesizing empirical evidence within the Malaysian context. Guided by the PRISMA framework… Read full abstract & cite →

Cybersecurity program Security Education Training Awareness (SETA) systematic evaluation Malaysian SMEs NVivo PRISMA

Abstract doi.org/10.14569/IJACSA.2025.0160943 PDF

44

Hybrid Fuzzy–PPO Control for Precision UAV Spraying

Author 1: Ahmad B. Alkhodre Author 2: Adnan Ahmed Abi Sen Author 3: Yazed Alsaawy Author 4: Nour Mahmoud Bahbouh Author 5: Mohamed Benaida

Precision agriculture increasingly relies on autonomous UAVs for tasks, such as crop monitoring and targeted pesticide spraying. However, maintaining stable flight and precise spray delivery under varying payloads and wind disturbances remains challenging. This paper proposes a hybrid control architecture that combines interpretable Mamdani fuzzy logic controllers with a deep… Read full abstract & cite →

UAVs precision agriculture UAV spraying fuzzy logic control reinforcement learning Proximal Policy Optimization (PPO) hybrid control

Abstract doi.org/10.14569/IJACSA.2025.0160944 PDF

45

Dynamic Assessment and Optimization Strategy for Brand Tourism Competitiveness in the Yangtze River Delta City Cluster Based on Entropy Weight-TOPSIS

Author 1: Dongmei Wang Author 2: Daoyi Wu

In the context of the integrated, high-quality development of the Yangtze River Delta City Cluster (YRDCC), brand tourism competitiveness is a key indicator of cities’ attractiveness and regional synergy. However, most existing studies focus on static comparisons and fail to dynamically assess competitiveness trends among cities. This study uses 27… Read full abstract & cite →

Yangtze River Delta City Cluster brand tourism competitiveness entropy weight-TOPSIS dynamic assessment

Abstract doi.org/10.14569/IJACSA.2025.0160945 PDF

46

Edge-Integrated IoT and Computer Vision Framework for Real-Time Urban Flood Monitoring and Prediction

Author 1: Rupesh Mandal Author 2: Bobby Sharma Author 3: Dibyajyoti Chutia

Urban flash floods pose a critical threat to rapidly growing cities in India, where unplanned development, climate variability, and inadequate drainage amplify risks. Guwahati, in Northeast India, experiences recurrent inundation during monsoons, disrupting livelihoods and damaging infrastructure. This study presents an integrated IoT and AI-enabled framework for urban flood monitoring… Read full abstract & cite →

Urban flood prediction IoT sensor networks edge computing fuzzy logic fusion hydraulic blockage detection computer vision

Abstract doi.org/10.14569/IJACSA.2025.0160946 PDF

47

Privacy-Aware ML Framework for Dynamic Query Formation in Multi-Dimensional Data

Author 1: B Bhavani Author 2: Haritha Donavalli

Interactive data exploration at scale remains constrained by 1) weak adaptability to shifting query workloads, 2) limited and post hoc error guarantees, 3) poor scalability under dynamic, high-dimensional data, 4) sparse user guidance during query formulation, and 5) non-trivial system overheads from learned or probabilistic components. We propose an end-to-end… Read full abstract & cite →

Dynamic query formation Approximate Query Processing (AQP) local differential privacy contextual bandits reinforcement learning constrained randomization multi-dimensional data exploration

Abstract doi.org/10.14569/IJACSA.2025.0160947 PDF

48

Performance Analysis of Spectrogram-Based Versus Raw Waveform-Based Deep Learning Models for Smoker Detection from Cough Audio

Author 1: Widi Nugroho Author 2: Alhadi Bustamam Author 3: Rinaldi Anwar Buyung

The classification of cough sounds for smoker detection represents a challenging task in audio processing that compares different data representation methods. This study presents a performance analysis of two prominent deep learning approaches: a spectrogram-based model, the Audio Spectrogram Transformer (AST), and a raw waveform-based model, Wav2Vec2. We used 7,561… Read full abstract & cite →

Smoker detection cough audio classification deep learning Audio Spectrogram Transformer Wav2Vec2 vocal biomarker

Abstract doi.org/10.14569/IJACSA.2025.0160948 PDF

49

ProjectNavigator: A Software Project Management Approach Selection Assistant

Author 1: Lin Dongzhi Author 2: Salfarina Abdullah

In software projects, project management approaches are crucial. Selecting a suitable management approach based on the specific project characteristics becomes the key to the success of the project. However, software projects are becoming more and more complex, and project managers tend to rely on subjective judgment to select the project… Read full abstract & cite →

Software projects project management recommendation tool expert evaluation usability testing

Abstract doi.org/10.14569/IJACSA.2025.0160949 PDF

50

A Hybrid RoBERTa-BiGRU-Attention Model for Accurate and Context-Aware Figurative Language Detection

Author 1: Sreeja Balakrishnan Author 2: Rahul Suryodai Author 3: S. Manochitra Author 4: Jasgurpreet Singh Chohan Author 5: Karaka Ramakrishna Reddy Author 6: A. Smitha Kranthi Author 7: Ritu Sharma

Figurative language, especially sarcasm, poses strong challenges for Natural Language Processing (NLP) models because of its implicit, context-sensitive nature. Both traditional and transformer models tend to find it difficult to identify these subtle forms, particularly when dealing with imbalanced datasets or without mechanisms for targeted interpretability. For overcoming these shortcomings… Read full abstract & cite →

Figurative language detection sarcasm classification RoBERTa-BiGRU-Attention model contextual embeddings Natural Language Processing

Abstract doi.org/10.14569/IJACSA.2025.0160950 PDF

51

Enhancing Code Quality Through Automated Refactoring Using Transformer-Based Language Models

Author 1: A. Sri Lakshmi Author 2: E. S. Sharmila Sigamany Author 3: Roopa Traisa Author 4: Raman Kumar Author 5: Karaka Ramakrishna Reddy Author 6: Jasgurpreet Singh Chohan Author 7: Aseel Smerat

Maintaining high-quality source code is crucial for software reliability, scalability, and maintainability. Traditional refactoring methods, which involve manual code improvement or rule-based automation, often fall short due to their inability to understand the contextual semantics of code. These approaches are rigid, language-specific, and prone to inconsistencies, especially in large and… Read full abstract & cite →

Automation code refactoring maintainability transformer models unit testing

Abstract doi.org/10.14569/IJACSA.2025.0160951 PDF

52

Real-Time Biomechanical Squat and Deadlift Posture Analysis Using Google Machine Learning Kit

Author 1: Liew Yee Jie Author 2: Ting Tin Tin Author 3: Chaw Jun Kit Author 4: Ali Aitizaz Author 5: Ayodeji Olalekan Salau Author 6: Omolayo M. Ikumapayi Author 7: Lim Siew Mooi

This project presents the development of a mobile application for real-time posture analysis during squat and deadlift exercises, using Google Machine Learning (ML) Kit pose detection. Proper exercise form is critical in preventing injuries, underscoring the need for systems that provide immediate feedback, an aspect often missing in existing fitness… Read full abstract & cite →

Pose detection squat and deadlift Google ML Kit fitness posture analysis emergency public health

Abstract doi.org/10.14569/IJACSA.2025.0160952 PDF

53

A Novel CNN-Based Feature Fusion Framework for Breast Cancer Ultrasound Image Classification

Author 1: Mobarak Zourhri Author 2: Bouchaib Cherradi Author 3: Mohamed El Khaili

Breast cancer remains a major global health concern and is among the leading causes of cancer-related deaths in women. Timely and precise diagnosis significantly improves treatment outcomes and patient survival rates. This paper presents a novel deep learning-based framework for breast cancer classification using ultrasound imagery, built upon the concatenation… Read full abstract & cite →

Breast cancer classification ultrasound imaging Convolutional Neural Networks (CNN) transfer learning model fusion Grad-CAM deep learning

Abstract doi.org/10.14569/IJACSA.2025.0160953 PDF

54

Machine Learning for Recommender Systems Under Implicit Feedback and Class Imbalance

Author 1: Younes KOULOU Author 2: Norelislam EL HAMI

Recommender systems (RS) in domains with implicit feedback and significant class imbalance, such as health insurance, face unique challenges in accurately predicting user preferences. This study proposes a machine learning framework leveraging tree-based ensemble methods to address these limitations. We conducted a comprehensive comparative analysis of algorithms, including Decision Trees… Read full abstract & cite →

Recommender systems XGBoost implicit feedback class imbalance health insurance

Abstract doi.org/10.14569/IJACSA.2025.0160954 PDF

55

Mapping Elderly Residential Research During the Onset of Baby Boomer Aging: A Bibliometric Analysis

Author 1: Keyi Xiao Author 2: Han Wang Author 3: Yan Ma

As global population aging accelerates, housing for older adults has emerged as a critical interdisciplinary research topic. Understanding how academic attention has evolved in this field is essential for informing policy and guiding future research. This study conducted a bibliometric analysis of 2,141 English-language publications related to elderly residential indexed… Read full abstract & cite →

Aging housing for the elderly long-term care environment design bibliometrics

Abstract doi.org/10.14569/IJACSA.2025.0160955 PDF

56

Strategic Decision Support in Financial Management Using Deep Learning-Based Stock Price Prediction Models

Author 1: Layth Almahadeen Author 2: Chinnapareddy Venkata Krishna Reddy Author 3: Roopa Traisa Author 4: Mukhamadiev Sanjar Isoevich Author 5: Lavanya Kongala Author 6: Janvi Anand Rathi Author 7: Revati Ramrao Rautrao

The Strategic decision support creates a strong and smart decision support system for financial management through the correct forecast of stock prices with deep learning. Statistical models and shallow machine learning techniques tend to be ineffective in modeling the nonlinear relationships, sequential interdependencies, and time-dependent volatility typical of financial data… Read full abstract & cite →

Stock price forecasting deep learning temporal fusion transformer financial decision support BiLSTM

Abstract doi.org/10.14569/IJACSA.2025.0160956 PDF

57

Advancements in Texture Analysis and Classification: A Bibliometric Review of Entropy-Based Approaches

Author 1: Muqaddas Abid Author 2: Muhammad Suzuri Hitam Author 3: Rozniza Ali Author 4: Muhammad Hammad

Entropy-based texture analysis has gained significant attention in medical imaging, computer vision, and material science. The purpose of this paper is to provide a bibliometric review that maps the evolution, key contributors, research trends, and emerging themes of entropy-based texture analysis from 1980 to 2025. Using the Scopus database, 1,482… Read full abstract & cite →

Artificial intelligence bibliometric review entropy research trends texture analysis

Abstract doi.org/10.14569/IJACSA.2025.0160957 PDF

58

A Review of Visualization Techniques for Duplicate Detection in Cancer Datasets

Author 1: Nurul A. Emran Author 2: Ruhaila Maskat

As clinical cancer research increasingly depends on large, diverse datasets, concerns about data duplication have grown. Duplicates can undermine data integrity, skew analytical results, and reduce the reproducibility of studies. This review explores how visualization can play a critical role in identifying and managing duplicates in non-image clinical cancer data… Read full abstract & cite →

Duplicate detection data duplication visualization deduplication TCGA TCIA NAACCR

Abstract doi.org/10.14569/IJACSA.2025.0160958 PDF

59

Hybrid Real Time Facial Emotions Recognition on Autistic Individuals

Author 1: Fatima Ezzahrae El Rhatassi Author 2: Btihal El Ghali Author 3: Najima Daoudi

Communication and social interaction issues are frequently linked to autism, which can have an impact on quality of life, work, and education. Opportunities to lessen these difficulties are presented by assistive technology, especially those that facilitate individualized and encouraging engagement. Facial expression recognition (FER) is essential to these systems, but… Read full abstract & cite →

Facial emotion recognition video frames spatial and temporal features pretrained models LSTM autistic individuals

Abstract doi.org/10.14569/IJACSA.2025.0160959 PDF

60

Integrating YOLOv8 and IoT in a Computer Vision System for Child Detection in Smart Cities

Author 1: Modhawi Alotaibi Author 2: Atheer Alruwaythi Author 3: Sara Alenazi Author 4: Maisaa Alsaedi

In an era marked by technological advancements aimed at establishing smart cities, technology increasingly focuses on enhancing aspects related to crowd management. The widespread deployment of CCTV systems, combined with the integration of computer vision, has enabled accurate insights into crowd density estimation. Our research highlights the potential benefits of… Read full abstract & cite →

Computer vision Internet of Things deep learning YOLOv8 DeepSORT

Abstract doi.org/10.14569/IJACSA.2025.0160960 PDF

61

D.M.A.I.H.: Deepfake-Inspired Few-Shot Learning Approach with Stable Diffusion for Digital Mourning

Author 1: Btissam Acim Author 2: Hamid Ouhnni Author 3: Nassim Kharmoum Author 4: Soumia Ziti

Digital mourning (deuil numérique) is the use of digital and AI-based technologies to preserve, recontextualize, and extend the memory of deceased loved ones through personalized and meaningful virtual representations. The digital mourning process requires innovative technologies capable of preserving the memory of deceased loved ones in meaningful and humanized ways… Read full abstract & cite →

Stable diffusion few-shot learning deepfake Artificial Intelligence (AI) generative AI digital mourning

Abstract doi.org/10.14569/IJACSA.2025.0160961 PDF

62

Re-engineering Grid-Based Quorum Replication into Binary Vote Assignment on Cloud: A Scalable Approach for Strong Consistency in Cloud Databases

Author 1: Ainul Azila Che Fauzi Author 2: Noor Ashafiqa Author 3: Asiah Mat Author 4: Syerina Azlin Md Nasir Author 5: A. Noraziah

The growth of cloud computing has heightened the demand for replication strategies that ensure strong consistency, high availability, and low communication cost across distributed infrastructures. Existing systems such as DynamoDB, FoundationDB, and GeoGauss illustrate different design trade-offs but face limitations in balancing latency, correctness, and resilience under dynamic workloads. This… Read full abstract & cite →

Binary Vote Assignment in Cloud (BVAC) cloud database replication fault tolerance high availability quorum-based replication strong consistency

Abstract doi.org/10.14569/IJACSA.2025.0160962 PDF

63

Optimized Random Forest for High-Accuracy Autism Spectrum Disorder Detection via Phenotypic Data

Author 1: Mohamed Gawish Author 2: Nada S. El-Askary Author 3: Mohamed Mabrouk Morsey Author 4: Abeer M. Mahmoud Author 5: Mostafa Aref Author 6: Taha Ibrahim El-Arif

Autism Spectrum Disorder (ASD) is a mental disorder with a neurological condition noticed in patients by their persistent deficits in social communication and interaction, along with the possibility of the presence of repetitive motor behaviors or activities. Early diagnosis of this disorder is crucial for improving patients’ cognitive, emotional, and… Read full abstract & cite →

Mental healthcare ASD phenotypic data ABIDE- II random forest hyperparameter optimizations

Abstract doi.org/10.14569/IJACSA.2025.0160963 PDF

64

Robust Control of Cyber-Physical Teleoperation Systems for Synchronized Healthcare Supply Chain Management

Author 1: Mariem Mrad Author 2: Mohamed Amine Frikha

This paper presents a delay-dependent sliding mode control (SMC) framework for synchronization in a three-degree-of-freedom cyber-physical master–slave teleoperation system, with emphasis on healthcare supply chain management. Communication delays pose a critical challenge, often leading to instability, desynchronization, and inaccurate inventory records. Such discrepancies compromise patient safety and hinder reliable forecasting… Read full abstract & cite →

Sliding mode control master-slave teleoperation system cyber-physical system healthcare supply chain management inventory forecasting synchronization

Abstract doi.org/10.14569/IJACSA.2025.0160964 PDF

65

Sentiment Analysis Revisited: A Multi-Metric Comparative Study

Author 1: Kamal Walji Author 2: Allae Erraissi Author 3: Abdelali ZAKRANI Author 4: Mouad Banane

Sentiment analysis is a fundamental task in natural language processing with wide-ranging applications, from customer feedback monitoring to healthcare and social media analytics. While recent research has mainly emphasized predictive accuracy, computational efficiency has remained largely overlooked, despite its importance for large-scale and real-time deployment. This study addresses this gap… Read full abstract & cite →

Sentiment analysis natural language processing machine learning deep learning logistic regression random forest Naive Bayes LSTM CNN Efficiency Score

Abstract doi.org/10.14569/IJACSA.2025.0160965 PDF

66

Enhanced Crow Search Algorithm with Cooperative Island Strategy for Energy-Aware Routing in Wireless Sensor Networks

Author 1: Xiangqian LI Author 2: Xuemei ZHOU

Energy efficiency is a fundamental problem experienced by Wireless Sensor Networks (WSNs), as limited battery power affects network lifespan and reliability. This paper develops a novel energy-efficient routing protocol based on an Enhanced Crow Search Algorithm (ECSA) optimization approach to optimize cluster head selection. The proposed ECSA combines a cooperative… Read full abstract & cite →

Wireless sensor networks energy efficiency cluster head selection Crow Search island model routing optimization

Abstract doi.org/10.14569/IJACSA.2025.0160966 PDF

67

From Review to Practice: A Comparative Study and Decision-Support Framework for Sentiment Classification Models

Author 1: Kamal Walji Author 2: Allae Erraissi Author 3: Abdelali ZAKRANI Author 4: Mouad Banane

Sentiment classification is a core task in natural language processing (NLP), enabling automated interpretation of opinionated text across domains, such as social media, e-commerce, and healthcare. While numerous models have been proposed—from classical machine learning algorithms to deep neural networks and transformer architectures—their adoption is often hindered by trade-offs in… Read full abstract & cite →

Sentiment analysis text classification machine learning deep learning transformer models BERT LSTM random forest hybrid approaches model evaluation interpretability natural language processing

Abstract doi.org/10.14569/IJACSA.2025.0160967 PDF

68

A Weighted Scoring Model of Heuristic-Based Workload Scheduling Approaches in Edge-Cloud Environments

Author 1: Hasnae NOUHAS Author 2: Abdessamad BELANGOUR Author 3: Mahmoud NASSAR

Hybrid edge–cloud computing has emerged as a promising paradigm to meet the demands of latency-sensitive and resource-aware applications by combining the low-latency benefits of edge nodes with the scalability of cloud infrastructure. Efficient workload scheduling in such environments remains a critical challenge due to the heterogeneity of resources, dynamic network… Read full abstract & cite →

Edge computing cloud computing workload scheduling heuristic algorithms metaheuristics scheduling optimization ACO PSO HEFT Tabu Search GA Greedy Resource-Aware Heuristics Min-Min Max-Min WSM Weighted Scoring Model

Abstract doi.org/10.14569/IJACSA.2025.0160968 PDF

69

Optimization of Convolutional Neural Network Algorithm for Indonesian Sign Language Classification

Author 1: Alvin Bintang Rebrastya Author 2: Sumarni Adi Author 3: Hanif Al Fatta Author 4: Windha Mega Pradnya Dhuhita Author 5: Ika Nur Fajri Author 6: Muhammad Hanafi

Sign language serves as a primary mode of communication for individuals who are deaf or speech impaired, using hand gestures to convey meaning visually. While it facilitates communication among the deaf community, it presents challenges for interaction with those who rely on spoken language. This study aims to recognize hand… Read full abstract & cite →

Indonesian Sign Language hand sign recognition image classification Convolutional Neural Network

Abstract doi.org/10.14569/IJACSA.2025.0160969 PDF

70

Control System of Ocean Wave Simulator Using PID-Salp Swarm Algorithm

Author 1: Affiani Machmudah Author 2: Juchen Li Author 3: Mahmud Iwan Solihin Author 4: Chiong Meng Choung Author 5: Wibowo Harso Nugroho Author 6: Ahmad Syafiul Mujahid Author 7: Sahlan Author 8: Abdul Ghofur

This paper presents a control system optimization of an ocean wave simulator using a meta-heuristic optimization. The proposed control system involves finding leg length trajectories by an Inverse Kinematics (IK) to be used as references for a Proportional-Integral-Derivative (PID). PID gains are tuned using a Salp Swarm Algorithm (SSA) with… Read full abstract & cite →

Marine simulation technologies Stewart platform ocean wave control system meta-heuristic optimization Salp Swarm Algorithm

Abstract doi.org/10.14569/IJACSA.2025.0160970 PDF

71

Enhanced IoT Security Using Machine Learning Technology

Author 1: Rawan Yousef Bukhowah Author 2: Alanoud Khaled Bu Dookhi Author 3: Mounir Frikha

This paper examines the enhancement of security measures for the Internet of Things (IoT) systems through the application of Machine Learning (ML) techniques. As the number of IoT devices continues to rise, ensuring their security has become increasingly critical, given that conventional methods frequently struggle to identify advanced threats. This… Read full abstract & cite →

Internet of Things Artificial Intelligence machine learning deep learning security

Abstract doi.org/10.14569/IJACSA.2025.0160971 PDF

72

DAE-IDS: A Domain-Aware Ensemble Intrusion Detection System with Explainable AI for Industrial IoT Networks

Author 1: Saifur Rahman

The widespread deployment of Industrial Internet of Things (IIoT) devices creates an urgent need for effective intrusion detection systems (IDS). However, two critical challenges limit current approaches: severe class imbalance in network traffic data that hampers detection of rare attacks, and the “black-box” nature of machine learning models that undermines… Read full abstract & cite →

Intrusion detection systems IoT security Explainable AI (XAI) class imbalance frequency-aware ensemble SHAP interpretability domain-aware routing confidence-based ensemble Edge-IIoTset dataset optimized random forest

Abstract doi.org/10.14569/IJACSA.2025.0160972 PDF

73

Enhanced Fuzzy Clustering Approach for Overlapping Community Detection via Structural Neighborhood Similarity

Author 1: Faiza Riaz Khawaja Author 2: Zuping Zhang Author 3: Abdul Hadi Riaz Author 4: Abdolraheem Khader Author 5: Ahmed Hamza Osman Author 6: Hani Moetque Aljahdali Author 7: Ali Ahmed

The existence of complex networks can be observed in various real-world contexts, such as social, biological, and/or neurological networks. A critical analytical challenge in such networks is community detection, which entails detecting groupings of nodes with dense internal connectivity. Numerous studies have been conducted on the subject of overlapping communities… Read full abstract & cite →

Fuzzy clustering neighborhood similarity extended modularity overlapping community complex networks

Abstract doi.org/10.14569/IJACSA.2025.0160973 PDF

74

Vision-Based Autonomous Localization of Fall Protection Anchor Points on Transmission Towers Using Multi-View Geometric Perception

Author 1: Chunqing Yang Author 2: Yu Peng Author 3: Jian Yu Author 4: Dongfeng Yu Author 5: Rui Liu Author 6: Jiahui Chen

This paper presents the first systematic investigation into autonomous UAV-mounted fall protection lanyard (FPL) deployment for high-voltage transmission tower inspections, addressing a critical safety gap in the power industry where falls account for 34% of occupational fatalities. We propose a novel geometry-based solution to overcome three fundamental limitations of existing… Read full abstract & cite →

Fall protection lanyard transmission tower inspection anchor point localization multiview geometry spacial edge distance perception homography transformation

Abstract doi.org/10.14569/IJACSA.2025.0160974 PDF

75

A New Hybrid Approach Based on Discrete Wavelet Transform and Deep Learning for Traffic Sign Recognition in Autonomous Vehicles

Author 1: Rim Trabelsi Author 2: Khaled Nouri

The rapid advancement of autonomous vehicles has led to the widespread integration of advanced driver assistance systems, significantly improving vehicle control, safety, and compliance with traffic regulations. A crucial aspect of these systems is the reliable detection and recognition of traffic signs, which play a key role in managing urban… Read full abstract & cite →

Safety discrete wavelet transform traffic sign recognition autonomous vehicles deep learning

Abstract doi.org/10.14569/IJACSA.2025.0160975 PDF

76

A Computer-Aided Diagnosis System for Ulcerative Colitis Classification Using Vision Transformer

Author 1: Dharmendra Gupta Author 2: Jayesh Gangrade Author 3: Yadvendra Pratap Singh Author 4: Shweta Gangrade

An unhealthy digestive condition that inflames the colon is called ulcerative colitis (UC). Utilising colonoscopy information to assess disease severity is a laborious process that concentrates on the most severe anomalies. The severity of this condition can significantly impact a patient’s quality of life. Current diagnostic methods, primarily colonoscopy, for… Read full abstract & cite →

Ulcerative Colitis (UC) colonoscopy videos deep learning vision transformer

Abstract doi.org/10.14569/IJACSA.2025.0160976 PDF

77

Graph Neural Networks with Shapley-Value Explanations for Hierarchical Recommendation Systems

Author 1: Redwane Nesmaoui Author 2: Mouad Louhichi Author 3: Mohamed Lazaar

Hierarchical structures are prevalent in real-world recommendation systems; however, existing graph neural networks (GNNs) struggle to capture them effectively because of their reliance on Euclidean geometry and a lack of Interpretability. This paper presents a novel architecture, Hyperbolic Graph Neural Networks with Shapley-Value Explanations (HGNN-SV), which simultaneously addresses both challenges… Read full abstract & cite →

Hyperbolic graph neural networks Shapley value explainable recommendation hierarchical recommendation systems interpretability Explainable AI (XAI) Poincar´e ball embeddings graph neural networks feature attribution hyperbolic geometry user-item graph embeddings

Abstract doi.org/10.14569/IJACSA.2025.0160977 PDF

78

Benchmarking Large Language Models for Hate Speech Detection in Arabic Dialects: Focus on the Saudi Dialects

Author 1: Omaima Fallatah

This study investigates the effectiveness of large language models (LLMs) in detecting Arabic hate speech, with a particular focus on prompt-based learning and the sociolinguistic challenges of Saudi dialects. We evaluate four LLMs, GPT-4o, LLaMA3, Gemma2, and ALLaM, using zero-shot, one-shot, and three-shot prompting strategies. The results show that all… Read full abstract & cite →

Arabic hate speech detection large language models (LLMs) in-context learning Arabic NLP

Abstract doi.org/10.14569/IJACSA.2025.0160978 PDF

79

Task-Oriented Evaluation of Assamese Tokenizers Using Sentiment Classification

Author 1: Basab Nath Author 2: Sagar Tamang Author 3: Osman Elwasila Author 4: Yonis Gulzar

Tokenization is a foundational step in the NLP pipeline, and its design strongly influences the performance of transformer-based models, particularly for morphologically rich and low-resource languages such as Assamese. While most tokenizers are traditionally assessed using intrinsic metrics, their practical impact on downstream tasks has remained underexplored. This study systematically… Read full abstract & cite →

Assamese NLP tokenization subword tokenization sentiment analysis low-resource languages BERT class imbalance

Abstract doi.org/10.14569/IJACSA.2025.0160979 PDF

80

Leveraging Distance-Optimized Transformers for High-Performance Arabic Short Answers Grading

Author 1: Hatem M. Noaman Author 2: Mohsen Rashwan Author 3: Hazem Raafat

This study presents comprehensive distance-optimized transformer architecture for Automated Arabic Short Answers Grading (AASAG) that systematically evaluates multiple semantic similarity measures. Short answer grading—assessment of responses typically 1-3 sentences long requiring conceptual understanding rather than factual recall—poses significant challenges in Arabic due to morphological complexity and limited computational resources. Our… Read full abstract & cite →

Automatic Arabic Short Answers Grading; Arabic language processing; educational technology; pre-trained language models; semantic similarity

Abstract doi.org/10.14569/IJACSA.2025.0160980 PDF

81

A FOREX Trading System Based on Semi-Supervised News Classification, Market Sentiment Analysis, and GRU-CNN Deep Learning Models

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

Investors access the foreign exchange market (FOREX) not only to preserve their wealth but also to generate profits and achieve specific financial goals. It is one of the largest financial markets that investors rely on, and it is based on fluctuations in currency exchange rates to make a profit in… Read full abstract & cite →

FOREX trading semi-supervised classification sentiment analysis machine learning deep learning RNN CNN GRU

Abstract doi.org/10.14569/IJACSA.2025.0160981 PDF

82

Scalable Formal Verification of Modular Concurrent Systems: A Survey of Techniques, Tools and Challenges

Author 1: Sawsen Khlifa Author 2: Chiheb Ameur Abid Author 3: Asma ben Letaifa Author 4: Belhassen Zouari

The increasing complexity of distributed and con-current systems raises pressing challenges for ensuring correctness and reliability. Formal verification, and in particular model checking, offers a rigorous foundation to validate system properties, yet suffers from the well-known state space explosion problem. This difficulty is especially acute in modular architectures, where local… Read full abstract & cite →

Distributed systems state space Modular Petri Net formal verification state explosion problem model checking temporal logic reduction techniques RDSS ROS2 scalability modularity model checking

Abstract doi.org/10.14569/IJACSA.2025.0160982 PDF

83

New Explainable Overlapping Co-Clustering for Recommender Systems: Capturing Multifaceted Preferences with Enhanced Interpretability

Author 1: Chiheb Eddine Ben Ncir Author 2: Mohammed Ibrahim Alattas

Recommender systems have become critical tools in reducing information overload by providing personalized recommendations across several application domains including commerce, industry, education, academic research, etc. Clustering-based recommender systems, which use the clustering technique to group similar users or items to generate suggestions, have shown high accuracy and efficiency. However, conventional… Read full abstract & cite →

Clustering-based recommender systems modularity maximization overlapping co-clustering multiple-user-preferences recommendation interpretability

Abstract doi.org/10.14569/IJACSA.2025.0160983 PDF

84

Applying a Lightweight Graphics Library to Visually Corroborate Learning in Programming Introduction Courses

Author 1: Claudia De La Fuente Author 2: Cristian Vidal-Silva Author 3: Liza Jeg´o-Mendoza Author 4: Patricia Pedrero-Valenzuela

Learning to program in first-year courses is challenging because the link between source code and program behaviour is not immediately visible to novices. This paper reports on the deployment of UFramework, a lightweight graphics library developed in C++/Visual Studio, designed to help students visually corroborate their learning by observing the… Read full abstract & cite →

Structured programming visual corroboration self-regulated learning metacognition program visualization project-based learning

Abstract doi.org/10.14569/IJACSA.2025.0160984 PDF

85

Mental Health Monitoring in Neurodivergent Children Using NeuroSky TGAM1: Real-Time EEG Signal Processing for Cognitive and Emotional Assessment

Author 1: Erika Yolanda Aguilar Del Villar Author 2: Jes´us Jaime Moreno Escobar Author 3: Claudia Hern´andez Aguilar

This study presents a real-time electroencephalography (EEG) monitoring system tailored for neurodivergent children, leveraging the affordable, single-channel NeuroSky TGAM1 sensor. We introduce a robust signal processing pipeline based on spectral power density analysis (from Delta to Gamma bands) to identify discrete cognitive-emotional states during therapy sessions. The system demonstrates 82.3%… Read full abstract & cite →

EEG neurodivergent children wearable spectral power density analysis therapy sessions

Abstract doi.org/10.14569/IJACSA.2025.0160985 PDF

86

A Weakly Supervised MIL Approach to Fake News Detection via Propagation Tree Analysis

Author 1: Shariq Bashir

This paper presents a weakly supervised Multiple Instance Learning (MIL) framework for fake news detection in social media, leveraging propagation tree analysis to model the spread of misinformation across online networks. Unlike traditional text-based or graph-based methods, our approach captures fine-grained post-level stances (support, denial, question, comment) and aggregates them… Read full abstract & cite →

Identifying fake news social network analysis post stance detection deep learning information retrieval multiple instance learning

Abstract doi.org/10.14569/IJACSA.2025.0160986 PDF

87

Hierarchical Adaptive Gap-Run TID Compression for Large-Scale Frequent Itemset Mining

Author 1: Xin Dai Author 2: Chenjiao Liu Author 3: Xue Hao Author 4: Qichen Su

Frequent itemset mining faces the prominent problems of high storage space requirements and low efficiency in a large-scale transaction data environment.The traditional Eclat algorithm usually uses bitmap or sparse array to represent a single transaction identifier (TID), which is difficult to adapt to the changes of dense and sparse transaction… Read full abstract & cite →

Frequent itemset mining pure Eclat Hierarchical Adaptive Gap-Run List (HAGL-TID) large-scale transaction data

Abstract doi.org/10.14569/IJACSA.2025.0160987 PDF

88

Optimizing Energy Efficiency and Increasing Scalability in 6G-IoT Networks Through SDN, Duty Cycling, and AI-Driven Slicing

Author 1: Marwah Albeladi Author 2: Kamal Jambi Author 3: Fathy E. Eassa Author 4: Maher Khemakhem

As sixth-generation (6G) and Internet of Things (IoT) networks expand rapidly, concerns are growing about their energy consumption and scalability. This is primarily because more devices are being connected, resulting in increased energy consumption energy consumption.This study examines three primary strategies for optimizing energy efficiency and improving scalability in 6G-IoT… Read full abstract & cite →

6G-IoT energy efficiency scalability SDN duty cycling network slicing CNN BiLSTM AI-driven optimization

Abstract doi.org/10.14569/IJACSA.2025.0160988 PDF

89

Chaotic Compressed Sensing for Secure Image Transmission in LoRa IoT Systems

Author 1: Chatchai Wannaboon Author 2: Shamsul Ammry Bin Shamsul Ridzwan Author 3: Sorawit Fong-In

Transmitting image data reliably over long distances with low cost and minimal storage consumption is critical for LoRa-enabled IoT devices. Conventional methods often rely on high-power consumption or computationally intensive hardware, rendering them unsuitable for cost-sensitive and resource-limited IoT deployments. This paper presents a hybrid compressed sensing approach designed for… Read full abstract & cite →

Secure image transmission compressed sensing chaotic maps long-range radio signals LoRa

Abstract doi.org/10.14569/IJACSA.2025.0160989 PDF

90

Predictive Models in Mental Health Based on Unsupervised Data Clustering

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

In the university context, students’ mental health has been progressively affected over time. The objective of this research was to develop a predictive model of machine learning based on the K-Means algorithm, with the purpose of identifying and classifying mental health profiles among university students. For the construction of this… Read full abstract & cite →

Behavioral patterns clustering machine learning mental health university students

Abstract doi.org/10.14569/IJACSA.2025.0160990 PDF

91

TomDetLeaf: A Realistic Multi-Source Dataset for Real-Time Tomato Leaf Detection

Author 1: Yassmine Ben Dhiab Author 2: Mohamed Ould-Elhassen Aoueileyine Author 3: Abdallah Namoun Author 4: Ridha Bouallegue

Plant diseases remain a major threat to crop productivity, especially where timely diagnosis is difficult. This paper introduces TomDetLeaf, a new annotated dataset designed for tomato leaf detection in diverse agricultural environments, supporting the development of generalizable deep learning models for edge AI deployment. Unlike existing datasets such as PlantVillage… Read full abstract & cite →

Tomato leaf detection smart agriculture dataset tomato leaf dataset real-time inference Edge AI object detection

Abstract doi.org/10.14569/IJACSA.2025.0160991 PDF

92

Comparative Analysis of Statistical, Machine Learning, and Deep Learning Approaches for Frost Prediction in the Peruvian Altiplano

Author 1: Fred Torres-Cruz Author 2: Dina Maribel Yana-Yucra Author 3: Richar Andre Vilca-Solorzano

Frost events represent a critical climatic hazard for agricultural systems in the Peruvian highlands, impacting approximately 74% of rural communities in the Puno region. This research addresses the question of whether machine learning (ML) and deep learning (DL) approaches can significantly outperform traditional statistical methods for frost prediction in extreme… Read full abstract & cite →

Frost prediction machine learning deep learning ensemble methods Altiplano agricultural early warning systems

Abstract doi.org/10.14569/IJACSA.2025.0160992 PDF

93

Towards the Hybrid Approach for Predicting Stroke Risk: A Feature Augmented Model

Author 1: Ting Tin Tin Author 2: Wong Jia Qian Author 3: Ali Aitizaz Author 4: Ayodeji Olalekan Salau Author 5: Omolayo M. Ikumapayi Author 6: Sunday A. Afolalu

This project addresses the critical challenge of stroke prediction by developing a hybrid model that integrates the strengths of the Random Forest (RF) and Support Vector Machine (SVM) algorithms. Stroke risk is highly influenced by lifestyle-related factors such as smoking, hypertension, heart disease, and elevated body mass index (BMI). Although… Read full abstract & cite →

Public health Random Forest Support Vector Machine hybrid model stroke prediction

Abstract doi.org/10.14569/IJACSA.2025.0160993 PDF

94

Socio-Technical Factors Influencing Business Intelligence Adoption in SMEs

Author 1: Ibrahim Abdusalam Abubaker Alsibhawi Author 2: Hazura Binti Mohamed Author 3: Jamaiah Binti Yahaya

This study explores the major challenges that Small and Medium-sized Enterprises (SMEs) encounter when adopting Business Intelligence Systems (BIS), particularly in complex socio-political environments, such as Libya. It aims to understand how internal constraints, like limited financial capacity, resistance to change among management, and weak knowledge-sharing practices, combined with external… Read full abstract & cite →

Information quality social influences perceived usefulness of Business Intelligence Adoption perceived ease of adoption of Business Intelligence System Business Intelligence System adoption

Abstract doi.org/10.14569/IJACSA.2025.0160994 PDF

95

An Improved BFT Algorithm in Traceability Data for Supply Chain

Author 1: Zhiyong Liang Author 2: Rongwang Jiang Author 3: Ming Yang Author 4: Boxiong Yang

Byzantine Fault Tolerance (BFT) is a class of faulttolerance techniques in the field of distributed computing. Aiming at the risks of error-prone and tampering data brought by the centralized database in the traditional supply chain traceability process, the use of the BFT consensus algorithm in combination with the alliance blockchain… Read full abstract & cite →

Tendermint BFT consensus consortium blockchain traceability data for supply chain

Abstract doi.org/10.14569/IJACSA.2025.0160995 PDF