IJACSA Vol. 16 Issue 8 (2025)

1

Development of Web Apps for Users with Special Needs

Author 1: Silviya Varbanova Author 2: Milena Stefanova Author 3: Tihomir Stefanov

This study presents software solutions and prototypes of converters designed to assist individuals who suffer from visual impairments or deafness. The prototypes were developed in a laboratory environment using modern programming technologies, with their applicability focused on contexts such as education, employment, and online shopping. The converter prototypes are designed… Read full abstract & cite →

Braille sign language deafness visually impaired software prototypes

Abstract doi.org/10.14569/IJACSA.2025.0160801 PDF

2

How Teachers’ Gestural Culture Influences Japanese Students’ Emotions: A Machine Learning Approach

Author 1: Yuka Nishi Author 2: Olivia Kennedy Author 3: Choi Dongeun Author 4: Noriaki Kuwahara

This study analyzes differences in teachers’ gestural styles based on their culture and investigates how these differences are perceived to influence Japanese students’ emotional responses by active observers. Classroom videos of Japanese- and English-native instructors were analyzed using MediaPipe for gesture tracking and DeepFace for facial emotion recognition. Ground-truth emotion… Read full abstract & cite →

Nonverbal behavior affective computing AI-based gesture recognition cultural differences multimodal analysis cross-cultural education emotion prediction

Abstract doi.org/10.14569/IJACSA.2025.0160802 PDF

3

Enhancing Approximate Conformance Checking Accuracy with Hierarchical Clustering Model Behaviour Sampling

Author 1: Yilin Lyu

Conformance checking techniques evaluate how well a process model aligns with an actual event log. Existing methods, which are based on optimal trace alignment, are computationally intensive. To improve efficiency, a model sampling method has been proposed to construct a subset of model behaviour that represents the entire model. However… Read full abstract & cite →

Approximate conformance checking model behaviour sampling hierarchical clustering process mining

Abstract doi.org/10.14569/IJACSA.2025.0160803 PDF

4

Enhancing Cyber Security Through Predictive Analytics: Real-Time Threat Detection and Response

Author 1: Muhammad Danish

This study evaluates the application of predictive analytics for real-time cyber-attack detection and response, focusing on how statistical and machine learning methods can improve decision-making in Security Operations Centers (SOCs). Using a curated network-traffic dataset of 2,000 records, we analyzed key features such as attack type, packet length, anomaly scores… Read full abstract & cite →

Predictive analytics real-time cyber-attack detection statistical methods machine learning threat detection

Abstract doi.org/10.14569/IJACSA.2025.0160804 PDF

5

A Hybrid Approach to Automatic Timetabling Using Self-Organizing Maps, Secure Convex Dominating Sets, and Metaheuristics

Author 1: Elmo Ranolo Author 2: Ken Gorro Author 3: Pierre Anthony Gwen Abella Author 4: Lawrence Roble Author 5: Rue Nicole Santillan Author 6: Anthony Ilano Author 7: Benjie Ociones Author 8: Roel Vasquez Author 9: Deofel Balijon Author 10: Daniel Ariaso Sr. Author 11: Rose Ann Campita Author 12: Robert Jay Angco

Creating conflict-free academic timetables that respect teacher availability, subject eligibility, and limited re-sources remains a persistent challenge in educational institutions. This study introduces a novel hybrid algorithm that combines Self-Organizing Maps (SOM), Secure Convex Dominating Sets (SCDS), and Genetic Algorithms (GA) to address this problem effectively. SOM is employed to… Read full abstract & cite →

Timetable optimization Self-Organizing Maps (SOM) Secure Convex Dominating Set (SCDS) Genetic Algorithm (GA) Academic Scheduling

Abstract doi.org/10.14569/IJACSA.2025.0160805 PDF

6

Integrating Fine-Tuned GPT with Agent-Based Economic Modeling for Transparent Wage Policy Decisions

Author 1: Daniel A. Ariaso Sr. Author 2: Ken D. Gorro Author 3: Deofel Balijon Author 4: Meshel Balijon

This study presents a decision-support system powered by GPT-enhanced insights to help policymakers explore the economic effects of minimum wage policies in the Philippines. The system integrates agent-based simulation, fuzzy logic, reinforcement learning, and Fuzzy Analytic Hierarchy Process (Fuzzy AHP) to model the complex relationships between wages, inflation, firm behavior… Read full abstract & cite →

Agent-Based simulation reinforcement learning fuzzy AHP GPT

Abstract doi.org/10.14569/IJACSA.2025.0160806 PDF

7

A Privacy-Preserving Gaussian Process Regression Framework Against Membership Inference Attacks Using Random Unitary Transformation

Author 1: Md. Rashedul Islam Author 2: Jannatul Ferdous Akhi Author 3: Takayuki Nakachi

As artificial intelligence (AI) systems become increasingly embedded in sensitive domains such as healthcare and finance, they face heightened vulnerabilities to privacy threats. A prominent type of attack against AI is the membership inference attack (MIA), which aims to determine whether specific data instances were used in a model’s training… Read full abstract & cite →

Gaussian process differential privacy random unitary transformation membership inference attack machine learning

Abstract doi.org/10.14569/IJACSA.2025.0160807 PDF

8

Autonomous Driving in Adverse Weather: A Multi-Modal Fusion Framework with Uncertainty-Aware Learning for Robust Obstacle Detection

Author 1: Zhengqing Li Author 2: Baljit Singh Bhathal Singh

Robust obstacle detection in autonomous driving under adverse weather remains a critical challenge due to sensor degradation, visibility reduction, and increased uncertainty. This study proposes an Uncertainty-Aware Multi-Modal Fusion (UAMF) framework that integrates LiDAR, RGB images, and weather priors through a dynamic cross-modal attention mechanism and Bayesian uncertainty modeling. The… Read full abstract & cite →

Autonomous driving adverse weather multimodal sensor fusion Bayesian neural networks uncertainty estimation

Abstract doi.org/10.14569/IJACSA.2025.0160808 PDF

9

EcoRouting: Carbon-Aware Path Optimization in Green Internet Architectures

Author 1: Handrizal Author 2: Herriyance Author 3: Amer Sharif

The exponential growth of Internet traffic has raised increasing concerns over the environmental sustainability of network infrastructures, particularly regarding energy consumption and carbon emissions. While traditional routing algorithms prioritize performance metrics such as speed, reliability, and QoS (Quality of Service), they often overlook the environmental cost associated with data transmission… Read full abstract & cite →

EcoRouting carbon-aware routing internet green internet QoS (Quality of Service)

Abstract doi.org/10.14569/IJACSA.2025.0160809 PDF

10

Exploring the Future Research Agenda for Health Applications Adoption: A Systematic Literature Review

Author 1: Rahmat Fauzi Author 2: Adhistya Erna Permanasari Author 3: Silmi Fauziati

The healthcare sector is experiencing rapid digital transformation, marked by the growing popularity of mobile health (mHealth) and eHealth applications for various health-related purposes. However, despite their potential, the adoption of health applications remains inconsistent due to varying influencing factors. Previous reviews often focused on specific populations or limited frameworks… Read full abstract & cite →

Systematic literature review health application adoption health technology user behavior technology acceptance TAM UTAUT

Abstract doi.org/10.14569/IJACSA.2025.0160810 PDF

11

A New Method for Real-Time Fall Detection Based on MediaPipe Pose Estimation and LSTM

Author 1: Puwadol Sirikongtham Author 2: Apichaya Nimkoompai

Falls are a significant health problem among older adults, leading to serious injuries and adversely affecting both quality of life and public health burdens. Although various fall detection systems have been developed using technologies such as wearable sensors and image processing (computer vision), limitations remain in dimensions of convenience, accuracy… Read full abstract & cite →

Fall detection older adults real-time MediaPipe LSTM computer vision pose estimation

Abstract doi.org/10.14569/IJACSA.2025.0160811 PDF

12

Design of Marketing Digital Control System Based on the Integration of Big Data Analysis and Machine Learning

Author 1: Qiming Li Author 2: Songling Du Author 3: Shiyuan Zhang

The advent of the digital age has made it difficult for traditional marketing methods to meet the rapidly changing needs of the market. To improve the efficiency and effectiveness of enterprise marketing activities, it is particularly important to develop intelligent and precise marketing management systems. Therefore, the study proposes a… Read full abstract & cite →

Big data flink reinforcement learning rete network interest level term frequency-inverse document frequency rule

Abstract doi.org/10.14569/IJACSA.2025.0160812 PDF

13

Artificial Intelligence in Optometry: Potential Benefits and Key Challenges: A Narrative Review

Author 1: Noura A. Aldossary

The integration of Artificial Intelligence (AI) into healthcare is transforming many medical fields, including optometry. This study provides a narrative review of the current applications and future potential of AI in optometric practice, emphasizing its role in automated screening and diagnosis, personalized treatment planning, and enhanced accessibility through tele-optometry. Alongside… Read full abstract & cite →

Artificial intelligence automated screening tele-optometry eye care services patient autonomy

Abstract doi.org/10.14569/IJACSA.2025.0160813 PDF

14

nodeWSNsec: A Hybrid Metaheuristic Approach for Reliable Security and Node Deployment in Wireless Sensor Networks

Author 1: Rahul Mishra Author 2: Sudhanshu Kumar Jha Author 3: Naresh Kshetri Author 4: Bishnu Bhusal Author 5: Mir Mehedi Rahman Author 6: Md Masud Rana Author 7: Aimina Ali Eli Author 8: Khaled Aminul Islam Author 9: Bishwo Prakash Pokharel

Efficient and reliable node deployment in Wireless Sensor Networks is crucial for optimizing coverage of the area, connectivity among nodes, and energy efficiency. Random deployment of nodes may lead to coverage gaps, connectivity issues and reduce network lifetime. This study proposes a hybrid metaheuristic approach combining a Genetic Algorithm (GA)… Read full abstract & cite →

Node deployment wireless sensor networks genetic algorithm particular swarm optimization competitive multi-objective marine predators algorithm

Abstract doi.org/10.14569/IJACSA.2025.0160814 PDF

15

Exploring Trust Management in Fog Computing: A Comprehensive Review and Future Challenges in Task Offloading

Author 1: Liu Feng Author 2: Suhaidi Hassan Author 3: Mohammed Alsamman

With the proliferation of data-driven services and latency-sensitive applications, fog computing has emerged as a pivotal extension of cloud infrastructure, enabling data processing and resource allocation at the network edge. However, the trustworthiness of task offloading in such decentralized and heterogeneous environments remains insufficiently explored, posing significant concerns related to… Read full abstract & cite →

Trust management fog computing cloud computing task offloading heterogeneous networks trust evaluation task completion time

Abstract doi.org/10.14569/IJACSA.2025.0160815 PDF

16

AraSpam: A Multitask Deep Neural Network for Spam Detection in Arabic Twitter

Author 1: Lulua Alhamdan Author 2: Ahmed Alsanad Author 3: Nora Al-Twairesh

Twitter has become widely used for disseminating information across the Arab world. It provides diverse communicative and informational needs while serving as a rich data source for a wide range of research. However, the integrity of such data is frequently undermined by the pervasive issue of spam. Existing research proposed… Read full abstract & cite →

Spam detection Twitter multitask deep neural network transformer-based model

Abstract doi.org/10.14569/IJACSA.2025.0160816 PDF

17

Hierarchical Transformer Residual Model for Pneumonia Detection and Lesion Mapping

Author 1: Anupama Prasanth

Pneumonia, a potentially fatal infection and a common disease-causing culprit among children and the elderly, still remains as a prevalent threat even after years of research on tackling it. Rapid and proper identification is crucial for timely treatment and improved results. While thoracic radiographs are widely employed in pneumonia diagnosis… Read full abstract & cite →

Pneumonia detection lesion segmentation chest X-ray ResNet50 swin transformer global average pooling

Abstract doi.org/10.14569/IJACSA.2025.0160817 PDF

18

Developing ReAdaBalancer for Load Balancing Optimization in Networked Cloud Computing

Author 1: M Diarmansyah Batubara Author 2: Poltak Sihombing Author 3: Syahril Efendi Author 4: Suherman

Traditional load balancing systems frequently have trouble adjusting to abrupt and unexpected changes in traffic. This can cause problems like server overload, longer response times, and more requests being denied. This problem is highly important in areas like healthcare, finance, cloud computing, and e-commerce, where performance, stability, and fast data… Read full abstract & cite →

Cloud computing heuristic optimization adaptive load balancing scalability ReAdaBalancer

Abstract doi.org/10.14569/IJACSA.2025.0160818 PDF

19

An Augmentation-Based System for Diagnosing COVID-19 Using Deep Learning

Author 1: Mohamad Shady Alrahhal Author 2: Mohammad A. Mezher Author 3: Osamah A.M. Ghaleb Author 4: Mohammad Al-Hjouj Author 5: Raghad Sehly Author 6: Samir Bataineh

Recently, due to the dangerous spread of COVID-19, there has been strong competition among computer science researchers within the scientific research community to employ deep learning for the development of intelligent medical systems that diagnose this illness. Enhancing accuracy is considered the most important objective, and augmentation techniques are used… Read full abstract & cite →

COVID-19 medical images augmentation vision transformer training data ratio

Abstract doi.org/10.14569/IJACSA.2025.0160819 PDF

20

Navigating the Landscape of Automated Information Extraction for Financial Fund Prospectuses: Survey and Challenges

Author 1: Yuyao Xu Author 2: Mohamad Farhan Mohamad Mohsin

In the financial sector, a fund prospectus is a critical document mandated by the Securities and Exchange Commission (SEC) that provides vital information about investments to the public. These documents encompass a range of financial concepts that define the fund's operations, including its name and disclaimers associated with periodic reports… Read full abstract & cite →

Machine learning information automation financial documentation

Abstract doi.org/10.14569/IJACSA.2025.0160820 PDF

21

Proactive Cancer Prediction Using IoT and Deep Learning Before Symptoms

Author 1: Mohamed Amine Meddaoui Author 2: Imane Karkaba Author 3: Moulay Amzil Author 4: Mohammed Erritali

The ability to predict cancer before the onset of clinical symptoms represents a paradigm shift in oncology and preventive medicine. Existing diagnostic approaches remain reactive, relying on imaging or symptomatic manifestations that frequently detect the disease only at advanced stages, particularly in pancreatic, lung, and ovarian cancers. To address this… Read full abstract & cite →

Deep learning internet of things artificial intelligence convolutional neural network recurrent neural network long short-term memory autoencoders cancer prediction

Abstract doi.org/10.14569/IJACSA.2025.0160821 PDF

22

Comparative Analysis of Machine Learning and Deep Learning Models for Handwritten Digit Recognition

Author 1: Soukaina Chekki Author 2: Boutaina Hdioud Author 3: Rachid Oulad Haj Thami Author 4: Sanaa El Fkihi

Handwritten digit recognition (HDR) forms a key component of computer vision systems, especially in optical character recognition (OCR). This study presents a comparative analysis of Machine Learning (ML) algorithms and Deep Learning (DL) models for HDR tasks. A contour-based segmentation technique was applied in preprocessing to enhance feature extraction by… Read full abstract & cite →

Handwritten digit recognition (HDR) Optical Character Recognition (OCR) Machine Learning (ML) Deep Learning (DL) segmentation

Abstract doi.org/10.14569/IJACSA.2025.0160822 PDF

23

Residual DDPG Control with Error-Aware Reward Rescaling for Active Suspension Under Unseen Road Conditions

Author 1: Zien Zhang Author 2: Abdul Hadi Abd Rahman Author 3: Noraishikin Zulkarnain

This study investigates a hybrid residual control framework combining Deep Deterministic Policy Gradient (DDPG) and a Proportional–Integral–Derivative (PID) based correction module for active suspension (AS) systems, aiming to improve ride performance and generalization under complex road excitations. The DDPG controller is trained on sinewave inputs, while the PID module compensates… Read full abstract & cite →

Deep deterministic policy gradient active suspension reward function generalization

Abstract doi.org/10.14569/IJACSA.2025.0160823 PDF

24

Edge-Guided Multi-Scale YOLOv11n: An Advanced Framework for Accurate Ship Detection in Remote Sensing Imagery

Author 1: Yan Shibo Author 2: Liu Pan Author 3: Abudhahir Buhari

Ship detection in optical remote sensing imagery plays a vital role in maritime surveillance and environmental monitoring. However, existing deep learning models often struggle to generalize effectively in complex marine environments due to challenges such as noise interference, small object sizes, and diverse weather conditions. To address these issues, this… Read full abstract & cite →

Optical remote sensing imagery ship detection multi-scale deep convolution edge-aware feature extraction

Abstract doi.org/10.14569/IJACSA.2025.0160824 PDF

25

The ECTLC-Horcrux Protocol for Decentralized Biometric-Based Self-Sovereign Identity with Time-Lapse Encryption

Author 1: N. M. Kaziyeva Author 2: R. M. Ospanov Author 3: N. Issayev Author 4: K. Maulenov Author 5: Shakhmaran Seilov

In the era of rapid development of digital communication, there is a growing need for technologies that guarantee secure user identification, document authentication and protection of personal data, including biometrics. Previously used centralized identity management systems are becoming increasingly vulnerable to hacking, falsification and misuse. This problem is especially relevant… Read full abstract & cite →

Self-sovereign identity horcrux protocol elliptic curves time-lapse cryptography biometrics QR codes blockchain

Abstract doi.org/10.14569/IJACSA.2025.0160825 PDF

26

Integrating Chatbots into E-Learning Platforms: A Systematic Review

Author 1: Victor Sevillano-Vega Author 2: Juan Chavez-Perez Author 3: Carmen Torres-Ceclén Author 4: Orlando Iparraguirre-Villanueva

The application of chatbots in e-learning has experienced rapid growth in recent years, but a dilemma remains about their pedagogical contribution in practice. For this reason, the aim of this systematic literature review was to analyze the implementation of chatbots in e-learning platforms, evaluating their benefits, academic impact and challenges… Read full abstract & cite →

Chatbots educational platforms e-learning education challenges

Abstract doi.org/10.14569/IJACSA.2025.0160826 PDF

27

A Hybrid Approach Combining Deep CNN Features with Classical Machine Learning for Diabetic Retinopathy Diagnosis

Author 1: Amandeep Kaur Author 2: Simranjit Singh Author 3: Hardeep Singh Author 4: Sarveshwar Bharti Author 5: Jai Sharma Author 6: Himanshi Sharma

One of the main causes of vision impairment is diabetic retinopathy (DR), a common and dangerous consequence of diabetes that damages the retinal blood vessels. Preventing irreversible vision loss requires early detection of DR. Recent developments demonstrate how artificial intelligence (AI), and in particular deep learning (DL), can automate the… Read full abstract & cite →

Deep learning convolutional neural networks hybrid model diabetic retinopathy machine learning medical image analysis feature extraction

Abstract doi.org/10.14569/IJACSA.2025.0160827 PDF

28

Forecasting Currency Exchange Direction with an Advanced Immune-Inspired Model

Author 1: EL BADAOUI Mohamed Author 2: RAOUYANE Brahim Author 3: EL MOUMEN Samira Author 4: BELLAFKIH Mostafa

Accurately forecasting currency exchange rates is a persistent and significant challenge in computational finance. This study addresses the challenge by introducing an advanced model based on the Artificial Immune Recognition System (AIRS), an algorithm inspired by the adaptive learning of biological immune systems, to predict the directional movement of the… Read full abstract & cite →

Artificial immune recognition system financial market prediction machine learning predictive analytics time series forecasting

Abstract doi.org/10.14569/IJACSA.2025.0160828 PDF

29

Adaptive Ensemble Models for Robust Intrusion Detection in Cloud Environment on Imbalanced Dataset

Author 1: Swarnalatha K Author 2: Nirmalajyothi Narisetty Author 3: Gangadhara Rao Kancherla Author 4: Neelima Guntupalli Author 5: Simhadri Mallikarjuna Rao Author 6: Archana Kalidindi

The rapid development of Information storage and sharing technologies brings new challenges in protecting against network security attacks. In this study, ensemble learning models are evaluated to enhance the performance of a network intrusion detection system (NIDS) with three phases through machine learning approaches. In the first phase, the unbalanced… Read full abstract & cite →

Resampling methods cloud computing feature selection ensemble model intrusion detection system machine learning

Abstract doi.org/10.14569/IJACSA.2025.0160829 PDF

30

Detection of Leaf Fall Disease in Sembawa Rubber Plantation Through Feature Extraction Model and Clustering Methods

Author 1: Alhadi Bustamam Author 2: Devvi Sarwinda Author 3: Retno Lestari Author 4: Ahmad Ihsan Farhani Author 5: Harum Ananda Setyawan Author 6: Masita Dwi Mandini Manessa Author 7: Tri Rappani Febbiyanti Author 8: Minami Matsui

Natural rubber is one of Indonesia's most important export commodities, making the country the second-largest exporter globally with a 28.65% share of the world market. However, recent production has declined, partly due to leaf fall disease caused by the Pestalotiopsis sp. fungus. This disease leads to premature leaf drop, which… Read full abstract & cite →

Convolutional autoencoder gray level co-occurrence matrix k-means clustering rubber plant plantation Pestalotiopsis sp

Abstract doi.org/10.14569/IJACSA.2025.0160830 PDF

31

Tamil Handwritten Character Recognition: A Comprehensive Review of Recent Innovations and Progress

Author 1: Manoj K Author 2: Iyapparaja M

Recognizing handwritten characters is a complex task, particularly when dealing with Tamil, a writing system known for its intricate and stylized nature. Several challenges arise in recognizing Tamil handwritten characters, including the complexity of the writing style, similar character shapes, irregular handwriting, slanting characters, varying curves, inconsistent font sizes, and… Read full abstract & cite →

Convolutional Neural Network (CNN) handwritten recognition Tamil characters offline recognition feature extraction techniques neural network architecture Support Vector Machine (SVM) groupwise classification

Abstract doi.org/10.14569/IJACSA.2025.0160831 PDF

32

Boosting Deepfake Detection Accuracy with Unsharp Masking and EfficientNet Models

Author 1: Radwa Khaled Author 2: Hossam M. Moftah Author 3: Fahad Kamal Alsheref Author 4: Adel Saad Assiri Author 5: Kamel Hussein Rahouma Author 6: Mohammed Kayed

The rapid progress of deepfake technology, fueled by generative adversarial networks (GANs), has increased the challenge of verifying the authenticity of digital media. This study suggests a more powerful deepfake detection framework based on the EfficientNet convolutional neural network family, coupled with an unsharp masking preprocessing method to highlight manipulation… Read full abstract & cite →

Deepfake detection efficientnet unsharp masking convolutional neural networks (CNNs) facial manipulation detection computer vision artificial intelligence

Abstract doi.org/10.14569/IJACSA.2025.0160832 PDF

33

Analysis of the Possibilities of Using LLM Chatbots for Solving Course and Exam Tasks

Author 1: Svetlana Stefanova Author 2: Yordan Kalmukov

With the widespread introduction of new technologies and, in particular, AI in various areas of life, students are increasingly using large language models (LLMs) such as ChatGPT and other similar tools to help them with their academic tasks. By using them, they can improve their productivity, improve their understanding of… Read full abstract & cite →

Large language models (LLM) artificial intelligence (AI) ChatGPT Claude AI DeepSeek AI in education AI for solving exams

Abstract doi.org/10.14569/IJACSA.2025.0160833 PDF

34

Segment-Based Vehicular Congestion Detection Methods Using Vehicle ID and Loss of Expected Time of Arrival

Author 1: Mustapha Abubakar Ahmed Author 2: Azizul Rahman Mohd Shariff

Increasing number of vehicles and rapid urbanization are the significant causes of road traffic congestion. Road traffic congestion is the main issue facing world cities today. Congestion control and mitigation are necessary to mitigate the negative impacts of road traffic congestion, such as delays and increased fuel consumption, among others… Read full abstract & cite →

Vehicle ID traffic congestion congestion detection vehicle trajectories vehicle speed vehicle density loss of expected time of arrival

Abstract doi.org/10.14569/IJACSA.2025.0160834 PDF

35

Stock Market Prediction of the Saudi Telecommunication Sector Using Univariate Deep Learning Models

Author 1: Hadi S. AlQahtani Author 2: Mohammed J. Alhaddad Author 3: Mutasem Jarrah

Stock market volatility, randomness, and complexity make accurate stock price prediction very elusive, though it is required for logical investment and risk management. This study compares four Deep Learning (DL) models, Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), Convolutional Neural Network (CNN), and a CNN-LSTM model, to predict the… Read full abstract & cite →

Deep learning stock market prediction models regression time series

Abstract doi.org/10.14569/IJACSA.2025.0160835 PDF

36

A Systematic Review of Multilingual Plagiarism Detection: Approaches and Research Challenges

Author 1: Chaimaa BOUAINE Author 2: Faouzia BENABBOU Author 3: Zineb Ellaky Author 4: Amine BOUAINE Author 5: Chaimae ZAOUI

The existence of voluminous multilingual sources on the web in different fields creates numerous issues, including violations of intellectual property rights. For that, the multilingual plagiarism or cross-language plagiarism detection (CLPD) has become a great challenge, which refers to copying content from a source text in one language into a… Read full abstract & cite →

Multilingual plagiarism systematic literature review multilingual text representation translation approaches natural language processing machine learning deep learning

Abstract doi.org/10.14569/IJACSA.2025.0160836 PDF

37

Towards Explainable and Balanced Federated Learning: A Neural Network Approach for Multi-Client Fraud Detection

Author 1: Nurafni Damanik Author 2: Chuan-Ming Liu

The growing demand for secure and privacy-preserving machine learning frameworks has resulted in the implementation of federated learning (FL), especially in critical areas like Credit card fraud detection. This study presents a comprehensive federated learning architecture that incorporates Neural Networks as local models, in conjunction with KMeans-SMOTEENN to address class… Read full abstract & cite →

Component federated learning K-Means SMOTEENN credit card fraud detection LIME

Abstract doi.org/10.14569/IJACSA.2025.0160837 PDF

38

A Novel Multilevel Framework for DoS Detection in SDN

Author 1: Rejo Rajan Mathew Author 2: Amarsinh Vidhate

DoS attacks have been the most popular type of attack on SDNs. The threat landscape has widened due to advanced persistent threats. Recent studies have focused on a single level of defence and conventional detection methods, which have become redundant. The study proposes and implements a novel multilevel DoS attack… Read full abstract & cite →

Software defined network distributed denial of service openflow

Abstract doi.org/10.14569/IJACSA.2025.0160838 PDF

39

Mid-Upper Arm Circumference Measurement Using Digital Images: A Top-Down Approach with Panoptic Segmentation Using Mask R-CNN

Author 1: Maya Silvi Lydia Author 2: Pauzi Ibrahim Nainggolan Author 3: Desilia Selvida Author 4: Doli Aulia Hamdalah Author 5: Dhani Syahputra Bukit Author 6: Amalia Author 7: Rahmita Wirza Binti O. K. Rahmat

Assessing nutritional status, particularly among children and pregnant women, necessitates accurate measurement of Mid-Upper Arm Circumference (MUAC). This research introduces a novel system for MUAC estimation from digital images using the Mask R-CNN algorithm, employing a top-down panoptic segmentation strategy. The proposed model was designed to identify the upper arm… Read full abstract & cite →

Mask R-CNN mid-upper arm circumference digital images segmentation mean absolute error

Abstract doi.org/10.14569/IJACSA.2025.0160839 PDF

40

Ensemble Learning for Multi-Class Android Malware Detection: A Robust Framework for Family Level Classification

Author 1: Mana Saleh Al Reshan

The widespread popularity of Android devices has made them a prime target for sophisticated and evolving malware threats. Traditional malware detection techniques rely on binary classification (malicious vs. benign), which fails to capture the nuanced behavioral differences between malware families, critical for threat intelligence and incident response. To address this… Read full abstract & cite →

Malware detection cyber threat ML models feature selection ensemble methods

Abstract doi.org/10.14569/IJACSA.2025.0160840 PDF

41

Analyzing Cyber Attack Detection in IoT Healthcare Environments Using Artificial Intelligence

Author 1: Rawan Marzooq Alharbi Author 2: Muhammad Asif Khan

The rapid growth of the Internet of Things (IoT) has significantly increased its integration into daily life. In recent years, the integration of IoT technologies in healthcare has significantly enhanced patient care and operational efficiency. One of the most promising areas for using IoT devices in healthcare or interconnecting medical… Read full abstract & cite →

IoT healthcare security cyber-attack detection healthcare security AI in healthcare smart medical systems

Abstract doi.org/10.14569/IJACSA.2025.0160841 PDF

42

Performance Analysis of Proposed Scalable Reversible Randomization Algorithm (SRRA) in Privacy Preserving Big Data Analytics

Author 1: Mohana Chelvan P Author 2: Rajavarman V N Author 3: Dahlia Sam

The economy of today’s world is a data-driven knowledge economy, as electronic devices are mostly used for our day-to-day activities, through which organizations collect data actively or passively. The dimensionality of the dataset is also increased, along with the volume of data, because of the advancements in digital devices and… Read full abstract & cite →

Big data data analytics high dimensionality feature selection selection stability privacy preservation information loss

Abstract doi.org/10.14569/IJACSA.2025.0160842 PDF

43

Shared API Call Insights for Optimized Malware Detection in Portable Executable Files

Author 1: Mehdi Kmiti Author 2: Jallal Eddine Moussaoui Author 3: Khalid El Gholami Author 4: Yassine Maleh

Malware analysis is essential for understanding malicious software and developing effective detection strategies. Traditional detection methods, such as signature-based and heuristic-based approaches, often fail against evolving threats. To address this challenge, this study proposes a static analysis–based malware detection system that employs thirteen classifiers, including Logistic Regression, K-Nearest Neighbors (KNN)… Read full abstract & cite →

Malware detection static analysis portable executable (PE) files API calls extra trees classifier

Abstract doi.org/10.14569/IJACSA.2025.0160843 PDF

44

Intrusion Detection Using Machine Learning and Deep Learning

Author 1: Fatima Jobran ALzaher Author 2: Asma AlJarullah

As cyberattacks grow in prevalence, Intrusion Detection Systems (IDS) have become critical for securing network infrastructures. This study proposes an efficient IDS framework utilizing both machine learning (ML) and deep learning (DL) algorithms. The framework is evaluated on the “NF-UNSW-NB15-v2” dataset, which comprises a blend of normal and malicious traffic… Read full abstract & cite →

Cybersecurity cyber-attack intrusion detection system machine learning deep learning

Abstract doi.org/10.14569/IJACSA.2025.0160844 PDF

45

Comprehensive Analysis of Machine and Deep Learning Models for Stock Market Prediction

Author 1: Hadi S. AlQahtani Author 2: Mohammed J. Alhaddad Author 3: Mutasem Jarrah

Stock market prediction is a core task in financial engineering that requires sophisticated methods to extract subtle market and volatility trends. The increasing complexity of the stock market has led to the integration of advanced machine learning (ML) and deep learning (DL) techniques to improve accuracy beyond traditional statistical methods… Read full abstract & cite →

Deep learning machine learning prediction methods stock market regression taxonomy

Abstract doi.org/10.14569/IJACSA.2025.0160845 PDF

46

Consumer Adoption of Autonomous Vehicles in China: A Bibliometric Review of Intention Drivers and Perceptions

Author 1: Yunluo Zou Author 2: Syuhaily Osman Author 3: Sharifah Azizah Haron

Autonomous vehicles (AVs) are playing an increasing role in digitally enabled transportation systems with the dramatic emergence of related technologies. Consumer adoption is arguably a key factor in the deployment of AVs in China. In this study, bibliometric analysis was used to explore intention drivers regarding consumer adoption of AVs… Read full abstract & cite →

Autonomous vehicles diffusion of AVs consumer adoption consumer perception Chinese market bibliometric analysis

Abstract doi.org/10.14569/IJACSA.2025.0160846 PDF

47

RA-ACS_net Network: A Quantum Optical Reconstruction Method for Ultra-high Resolution Bioimaging

Author 1: Lin SHANG

Ultra-high resolution bioimaging based on quantum optics offers high sensitivity at relatively low cost, yet conventional reconstruction algorithms face challenges of excessive sampling time, long computation, and artifacts that limit imaging quality. To overcome these issues, this study proposes a novel quantum optical bioimaging reconstruction method termed RA-ACS_net, which integrates… Read full abstract & cite →

Ultra-high resolution bioimaging quantum optics computer vision ripple algorithm attention mechanism

Abstract doi.org/10.14569/IJACSA.2025.0160847 PDF

48

Privacy-Preserving Content-Based Medical Image Retrieval Using Integrated CNN Fusion and Quantization Optimization

Author 1: Mohamed Jafar sadik Author 2: Muhammed E Abd Alkhalec Tharwat Author 3: Noor Azah Samsudin Author 4: Ezak Fadzrin Bin Ahmad

Content‑Based Image Retrieval (CBIR) systems have become increasingly crucial in healthcare as the volume of medical imaging data continues to grow exponentially. However, existing systems struggle to balance privacy preservation, computational efficiency and retrieval accuracy, particularly in resource‑constrained healthcare environments. This research proposes a novel multi‑level privacy‑preserving CBIR architecture that… Read full abstract & cite →

Content-Based Image Retrieval (CBIR) medical image analysis privacy preservation deep learning convolutional neural networks (CNNs) feature fusion model quantization healthcare security encrypted image processing resource-constrained computing computed tomography (CT) magnetic resonance imaging (MRI)

Abstract doi.org/10.14569/IJACSA.2025.0160848 PDF

49

Innovative Model of Tourism on Educational Engineering: Transformation Learning from Experiential to Interactive

Author 1: Yurao Yan Author 2: Tara Ahmed Mohammed Author 3: Hailan Liang Author 4: Mingxi Guan

This study explores the interactive relationship between tourism education and industry development by applying a coupled coordination model and proposing an innovative framework that shifts learning from traditional experiential approaches to interactive teaching. The research establishes comprehensive evaluation indicators for both tourism industry performance and educational engineering, and quantitatively analyzes… Read full abstract & cite →

Tourism education educational engineering coupling coordination model industry–education integration

Abstract doi.org/10.14569/IJACSA.2025.0160849 PDF

50

DeepIndel: A ResNet-Based Method for Accurate Insertion and Deletion Detection from Long-Read Sequencing

Author 1: Md. Shadmim Hasan Sifat Author 2: Khandokar Md. Rahat Hossain

Structural variations (SVs) play a pivotal role in human genetics, influencing gene expression, disease mechanisms, and phenotypic diversity. Despite the advancements in short-read sequencing technologies, long-read sequencing offers superior resolution for detecting SVs, particularly in complex genomic regions. In this study, DeepIndel, a novel computational framework, is presented that leverages… Read full abstract & cite →

Structural variations (SVs) indels long-read sequencing breakpoints genomic features diseases deep learning ResNet HG002 dataset precision medicine gene expression phenotypic diversity

Abstract doi.org/10.14569/IJACSA.2025.0160850 PDF

51

A Modeling Approach for Strategic Fleet Sizing Under Maritime Sovereignty: Application to the Moroccan National Fleet

Author 1: Mohamed Anas KHALFI Author 2: Aziz AIT BASSOU Author 3: Mustapha HLYAL Author 4: Jamila EL ALAMI

The disruptions experienced by global supply chains in recent years have reignited the importance of maritime sovereignty, particularly through the creation or reinforcement of national shipping fleets. In this context, the present study explores strategic approaches to national fleet sizing, drawing from recent policy directions and maritime planning models. The… Read full abstract & cite →

Maritime fleet sizing sovereignty and national ownership strategic transport planning resilience in maritime logistics green maritime transport

Abstract doi.org/10.14569/IJACSA.2025.0160851 PDF

52

Prediction of Mining-Induced Subsidence in Saudi Arabia Phosphate Mines Using ANN Method

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

This study develops and validates an artificial neural network (ANN) model to predict mining-induced land subsidence in Saudi Arabia’s Al-Jalamid and Umm Wu’al phosphate mines. A multilayer perceptron is used with optimized hyperparameters based on four inputs (ground point position, distance from extraction center, accumulated exploitation volume, and time). The… Read full abstract & cite →

Subsidence prediction phosphate mine artificial neural network multilayer perceptron hyperparameter optimization

Abstract doi.org/10.14569/IJACSA.2025.0160852 PDF

53

A Review on Image-Based Methods for Plant Disease Identification in Diverse Data Conditions

Author 1: Feilong Tang Author 2: Rosalyn R Porle Author 3: Hoe Tung Yew Author 4: Farrah Wong

Image-based plant disease identification methods have demonstrated potential in enhancing crop protection through early detection. However, the development of this field faces several challenges, such as the scarcity of high-quality annotated data, significant intra-class variation and high inter-class similarity among plant diseases, and the limited generalization ability of current models… Read full abstract & cite →

Few-shot learning transfer learning deep learning crop protection early detection data scarcity

Abstract doi.org/10.14569/IJACSA.2025.0160853 PDF

54

Predictive Modeling for Metro Performance Using MetroPT3 Dataset

Author 1: Akshitha Mary A C Author 2: R Rakshinee Author 3: Stefani Jeyaseelan Author 4: Sakthivel V Author 5: Prakash P

The study titled "Predictive Modeling for Metro Performance Using the MetroPT3 Dataset" aims to create a predictive maintenance system for the metro systems in order to reduce unanticipated breakdowns. The dataset known as MetroPT3 is primarily used to provide data useful in monitoring the operation of certain features of the… Read full abstract & cite →

Long short-term memory autoencoder time-series anomaly detection sequence modeling reconstruction error predictive maintenance unsupervised learning encoder-decoder architecture anomaly threshold

Abstract doi.org/10.14569/IJACSA.2025.0160854 PDF

55

Artificial Intelligence in Diagnostic and Therapeutic Interventions: A Systematic Review of Randomized Controlled Trials

Author 1: Oscar Jimenez-Flores Author 2: Sandra Pajares-Centeno Author 3: Oscar Mejia-Sanchez Author 4: Rodrigo Flores-Palacios

Artificial intelligence (AI) is increasingly being integrated into diagnostic and therapeutic interventions, offering potential advantages in accuracy, efficiency, and clinical decision-making compared to conventional methods. This systematic review aimed to identify and characterise AI applications assessed in randomised controlled trials (RCTs), and to synthesise the reported clinical outcomes in comparison… Read full abstract & cite →

AI applications diagnostic interventions therapeutic interventions randomised controlled trials health technology

Abstract doi.org/10.14569/IJACSA.2025.0160855 PDF

56

Transformer-Enabled Smartphone System for Intelligent Physical Activity Monitoring

Author 1: Leping Zhang Author 2: Fengjiao Jiang Author 3: Guopeng Jia Author 4: Yue Wang

This study addresses the prevalent decline in physical activity among university students in the contemporary information society, proposing an innovative deep learning-based framework for intelligent physical activity recognition. Central to this framework is the comprehensive utilization of high-precision Inertial Measurement Units (IMUs) integrated within smartphones, encompassing triaxial accelerometers, gyroscopes, and… Read full abstract & cite →

Activity recognition smartphone transformer architecture inertial measurement units

Abstract doi.org/10.14569/IJACSA.2025.0160856 PDF

57

Game Theory-Optimized Attention-Based Temporal Graph Convolutional Network for Spatiotemporal Forecasting of Sea Level Rise

Author 1: T M Swathy Author 2: K.Ruth Isabels Author 3: A. Sindhiya Rebecca Author 4: Venubabu Rachapudi Author 5: Yousef A.Baker El-Ebiary Author 6: Shobana Gorintla Author 7: Elangovan Muniyandy

Predicting Sea level rise accurately is crucial in the formulation of effective adaptation plans to counteract the effects of climate change in vulnerable coastal areas, infrastructure, and people. The conventional forecasting models tend to fail in capturing the intricate spatiotemporal relationships affecting sea level variations. In order to overcome the… Read full abstract & cite →

Temporal graph convolutional networks attention mechanisms game theory optimization sea level rise prediction climate change adaptation

Abstract doi.org/10.14569/IJACSA.2025.0160857 PDF

58

Securing Image Messages Using Secure Hash Algorithm 3, Chaos Scheme, and DNA Encoding

Author 1: Amer Sharif Author 2: Dian Rachmawati Author 3: Wilbert

Security is an essential aspect to consider during data transmission, especially images. Threats that may occur during image transmission include images being stolen by third parties. One way to secure images is through encryption-decryption processes using cryptographic algorithms. One of the algorithms developed for image security involves combining a chaos… Read full abstract & cite →

Image encryption image decryption chaos scheme DNA encoding secure hash algorithm 3 Keccak

Abstract doi.org/10.14569/IJACSA.2025.0160858 PDF

59

Architecting a Privacy-Focused Bitcoin Framework Through a Hybrid Wallet System Integrating Multiple Privacy Techniques

Author 1: Lamiaa Said Author 2: Hatem Mohamed Author 3: Diaa Salama Author 4: Nesma Mahmoud

Although Bitcoin enables pseudonymous peer-to-peer digital transactions, its transparent public ledger architecture allows for blockchain analysis that can compromise user anonymity. Despite the presence of wallets with privacy-enhancing features, no single solution currently offers comprehensive anonymity independently. Existing privacy-preserving techniques such as CoinJoin, PayJoin, and Stealth Addresses offer differing degrees… Read full abstract & cite →

Bitcoin privacy anonymity wallet blockchain Coinjoin Payjoin stealth address

Abstract doi.org/10.14569/IJACSA.2025.0160859 PDF

60

VGG-19 and Vision Transformer Enabled Shelf-Life Prediction Model for Intelligent Monitoring and Minimization of Food Waste in Culinary Inventories

Author 1: Bindhya Thomas Author 2: Priyanka Surendran

Food waste, particularly in the prepared food industry, presents a serious worldwide concern with serious ethical, environmental and socioeconomic implications. In restaurants and catering contexts, traditional inventory and waste management systems frequently lack the versatility and granularity to mitigate spoilage in real-time. The study proposes a sophisticated deep learning framework… Read full abstract & cite →

Food waste reduction shelf-life prediction VGG-19 vision transformer image-based freshness classification sustainable food management

Abstract doi.org/10.14569/IJACSA.2025.0160860 PDF

61

Analysis of an RGB-D Simultaneous Localization and Mapping Algorithm for Unmanned Aerial Vehicle

Author 1: Muhammad Zamir Fathi Mohammad Effendi Author 2: Norhidayah Mohamad Yatim Author 3: Zarina Mohd Noh Author 4: Nur Aqilah Othman

This study investigates the implementation of an RGB-D Simultaneous Localization and Mapping (SLAM) algorithm on an unmanned aerial vehicle (UAV) equipped with an Intel RealSense D435i camera. The study focuses on Real-Time Appearance-Based Mapping (RTAB-Map), a well-established RGB-D SLAM method capable of building 3D maps while simultaneously localizing a robot… Read full abstract & cite →

Unmanned aerial vehicle UAV simultaneous localization and mapping SLAM RGB-D real-time appearance based map RTAB-map

Abstract doi.org/10.14569/IJACSA.2025.0160861 PDF

62

In-Depth Comparison of Supervised Classification Models - Performance and Adaptability to Practical Requirements

Author 1: Mouataz IDRISSI KHALDI Author 2: Allae ERRAISSI Author 3: Mustapha HAIN Author 4: Mouad BANANE

In this paper, we carried out an in-depth comparative analysis of five major supervised classification algorithms: Naïve Bayes, Decision Tree, Random Forest, KNN and SVM. These models were evaluated through a rigorous literature review, based on 20 criteria grouped into five key dimensions: algorithm performance, computational efficiency, practicality and ease… Read full abstract & cite →

Supervised classification Naïve Bayes decision tree Random Forest k-nearest neighbor Support Vector Machine algorithm performance interpretability

Abstract doi.org/10.14569/IJACSA.2025.0160862 PDF

63

Mobile Applications that Incorporate AI for Information Search and Recommendation: A Systematic Literature Review

Author 1: Mijael R. Aliaga Author 2: Jhosep S. Llacctahuaman Author 3: Carla N. Esquivel Author 4: Nemias Saboya

The inclusion of artificial intelligence (AI) has become essential for mobile application development, allowing improved personalization and optimization of the user experience. Over the past decade, smart mobile devices have been observed to enhance user experience across a variety of needs. The main objective of this study is to evaluate… Read full abstract & cite →

AI algorithms recommendation algorithms mobile applications search algorithms AI for information

Abstract doi.org/10.14569/IJACSA.2025.0160863 PDF

64

Smart Mobile Apps for Responsible Child Management: A Systematic Literature Review

Author 1: Daniel Celestino Author 2: Harol Medina Author 3: Cristian Lara Author 4: Nemias Saboya

Children are increasingly using mobile devices, which raises challenges such as restricting access to inappropriate content, reducing excessive screen exposure, and ensuring safe digital habits. Although various parental control applications exist, most studies focus on isolated aspects such as content filtering or screen time management, with limited integration of artificial… Read full abstract & cite →

Smart mobile apps parental control artificial intelligence screen time regulation responsible child management

Abstract doi.org/10.14569/IJACSA.2025.0160864 PDF

65

DMME-Driven Product Quality Prediction for Semiconductor Manufacturing

Author 1: Alif Ulfa Afifah Author 2: Angga Prastiyan Author 3: Fahmi Arif Author 4: Fadillah Ramadhan

Defective products in manufacturing can be reduced by accurately predicting quality outcomes based on process parameters. This study proposes a quality prediction framework for semiconductor manufacturing using the Data Mining Methodology for Engineering Applications (DMME). This study extends DMME with domain-specific preprocessing and demonstrates its superiority on the SECOM dataset… Read full abstract & cite →

Data mining quality prediction DMME semiconductor manufacturing random forest

Abstract doi.org/10.14569/IJACSA.2025.0160865 PDF

66

AIoT-Based Waste Classification for Solid Waste Management to Accomplish the SDGs

Author 1: T. M. Shien Author 2: M. Batumalay Author 3: Balasubramaniam Muniandy Author 4: Pavan Kumar Pagadala Author 5: Vinoth Kumar. P

The Fourth Industrial Revolution, known as IR4.0 technologies, has enhanced global economic capabilities and productivity, but there are negative environmental and health impacts due to industrialisation and urbanisation, such as greenhouse gas emissions and global warming. One effective method that reduces environmental impact is to conduct a waste classification program… Read full abstract & cite →

Solid waste management waste classification artificial intelligence of things (AIoT) well-being process innovation sustainable development goals (SDG) recycling circular economy

Abstract doi.org/10.14569/IJACSA.2025.0160866 PDF

67

A Scalable Machine Learning Framework for Predictive Analytics and Employee Performance Enhancement in Large Enterprises

Author 1: Jyoti Singh Kanwar Author 2: Ranju S Kartha Author 3: Chamandeep Kaur Author 4: Behara Venkata Nandakishore Author 5: Elangovan Muniyandy Author 6: Vuda Sreenivasa Rao Author 7: Yousef A.Baker El-Ebiary

Employee performance prediction and workforce optimization are critical for sustainable growth in large enterprises, yet traditional performance forecasting techniques often rely on regression analysis and conventional machine learning models that fail to capture the dynamic, nonlinear nature of human resource data. The approaches are not flexible, explainable, and actionable in… Read full abstract & cite →

Employee performance prediction workforce optimization performance forecasting hybrid deep dense attention network

Abstract doi.org/10.14569/IJACSA.2025.0160867 PDF

68

Deep Learning-Driven Scalable and High-Precision Malaria Detection from Microscopic Blood Smear Images

Author 1: N. Kannaiya Raja Author 2: Divya Rohatgi Author 3: Venkata Lalitha Narla Author 4: Ganesh Kumar Anbazhagan Author 5: R. Aroul Canessane Author 6: Drakshayani Sriramsetti Author 7: Yousef A.Baker El-Ebiary

Malaria continues to be a life-threatening disease, especially in tropical and low-resource regions, where timely and accurate diagnosis remains a major challenge. Traditional diagnostic approaches like manual microscopy are not only time-consuming and expertise-dependent but also prone to subjective errors. Existing deep learning methods, such as Convolutional Neural Networks (CNNs)… Read full abstract & cite →

Automated diagnosis blood smear images contrastive learning deep learning malaria detection

Abstract doi.org/10.14569/IJACSA.2025.0160868 PDF

69

Explainable Multimodal Sentiment Analysis Using Hierarchical Attention-Based Adaptive Transformer Models

Author 1: Anna Shalini Author 2: B. Manikyala Rao Author 3: Ranjitha. P. K Author 4: Guru Basava Aradhya S Author 5: S. Farhad Author 6: Elangovan Muniyandy Author 7: Yousef A. Baker El-Ebiary

Multimodal Sentiment Analysis (MSA) has emerged as a critical task in Natural Language Processing (NLP), driven by the growth of user-generated content containing textual, visual, and auditory cues. While transformer-based approaches achieve strong predictive performance, their lack of interpretability and limited adaptability restrict their use in sensitive applications such as… Read full abstract & cite →

Multimodal sentiment analysis RoBERTa Wav2Vec 2.0 vision transformer CMU-MOSEI

Abstract doi.org/10.14569/IJACSA.2025.0160869 PDF

70

A Data-Driven Approach to Achieve Low-Carbon Building Energy Optimization by Using BIM Technology

Author 1: Xin Yu Author 2: Guoliang Ren Author 3: Jie Niu

Low-carbon building energy optimization is the environmental aspect that is impacted due to the construction sector. The integration of Building Information Modelling (BIM) with Artificial Intelligence (AI) techniques offers the design and operation of buildings with a reduced carbon footprint. Usually, such systems lack flexibility and the precision of dynamically… Read full abstract & cite →

Low-carbon buildings building information modelling carbon emissions operational energy optimization SqueezeNet energy simulation

Abstract doi.org/10.14569/IJACSA.2025.0160870 PDF

71

JellyNovaNet-JSO: A Hybrid TabNet–BiLSTM Model for IoT-Based Crop Yield Prediction

Author 1: Huang Zhicheng Author 2: Zhang Yinjun

Precise prediction of crop yield is essential for sustainable agriculture, resource maximization, and food security. As the use of IoT and Wireless Sensor Networks (WSNs) gains momentum, huge amounts of heterogeneous and time-series environmental data have become readily available from intelligent greenhouses. Despite this, it is still difficult to obtain… Read full abstract & cite →

IoT agriculture crop yield prediction BiLSTM TabNet jellyfish search optimization

Abstract doi.org/10.14569/IJACSA.2025.0160871 PDF

72

Functional vs Ethical Drivers in Generative AI Adoption: A PLS-SEM Study in Business Education

Author 1: Jorge Serrano-Malebrán Author 2: Cristian Vidal-Silva Author 3: Paola von-Bichoffshausen Author 4: Romina Gómez-López Author 5: Franco Campos-Núñez

This study examined the factors influencing the use of ChatGPT by university students enrolled in business and management programs, considering the simultaneous effect of their functional perceptions and ethical or academic concerns. Using a structural equation modeling approach (PLS-SEM) applied to a sample of 118 students in Chile, the study… Read full abstract & cite →

Generative artificial intelligence student perceptions ChatGPT PLS-SEM

Abstract doi.org/10.14569/IJACSA.2025.0160872 PDF

73

An AI-Driven Approach for Real-Time Noise Level Monitoring and Analysis

Author 1: Yellamma Pachipala Author 2: L K SureshKumar Author 3: Veeranki Venkata Rama Maheswara Rao Author 4: Vijaya Chandra Jadala Author 5: T.Srinivasarao Author 6: D. Srinivasa Rao

Now a days, noise pollution is posing a public health risk, especially in residences and indoor environments like workplaces and schools. The proposed work presents a comprehensive analysis of hourly equivalent noise levels measured at 100 locations, such as the indoor environment. The proposed work is an intelligent automated noise… Read full abstract & cite →

Noise pollution IoT ESP8266 Wi-Fi smart automation AI-enabled noise pattern

Abstract doi.org/10.14569/IJACSA.2025.0160873 PDF

74

Deep Learning Meets Bibliometrics: A Survey of Transfer Learning Techniques for Breast Cancer Detection

Author 1: Amna Wajid Author 2: Natasha Nigar Author 3: Hafiz Muhammad Faisal Author 4: Olukayode Oki Author 5: Jose Lukose

This study aims to provide a comprehensive biblio-metric analysis of research on transfer learning in breast cancer detection from 2016 to 2024. It highlights publication trends, influential contributors, collaborations, and keyword patterns. Bibliometric methods are employed to analyze data extracted from the Scopus database. It includes co-occurrence and citation analyses… Read full abstract & cite →

Transfer learning breast cancer medical imaging analysis predictive analysis

Abstract doi.org/10.14569/IJACSA.2025.0160874 PDF

75

An Adaptive Levy Flight Chicken Swarm Optimization with Differential Evolution for Function Optimization Problem

Author 1: Wen-Jun Liu Author 2: Azlan Mohd Zain Author 3: Mohamad Shukor Bin Talib Author 4: Sheng-Jun Ma

This study proposes an improved swarm algorithm, Adaptive Levy Flight Chicken Swarm Optimization with Differential Evolution (ALCSODE), to overcome the low convergence accuracy and imbalance between exploration and exploitation in the original CSO algorithm. The method incorporates adaptive perturbation based on individual differences and a differential evolution mechanism into the… Read full abstract & cite →

Chicken swarm optimization levy flight differential evolution algorithm adaptive adjustment strategy function optimization

Abstract doi.org/10.14569/IJACSA.2025.0160875 PDF

76

Public Opinion Stage Segmentation in Disaster Events: A Study Based on Multimodal Sentiment Prediction Model

Author 1: Xiaogang Yuan Author 2: Jiaxi Chen Author 3: Dezhi An Author 4: Xiang Gong

Existing approaches for predicting public sentiment and analyzing opinion evolution during disaster events using multimodal data (text, video, audio) suffer from several limitations: an inadequate dynamic fusion of heterogeneous multi-source data, and imprecise division of public opinion stages. To address these issues, this paper proposes an Enhanced Disentangled Cross Fusion… Read full abstract & cite →

Multimodal sentiment prediction e-divisive with medians transformer encoder decoder cross-attention

Abstract doi.org/10.14569/IJACSA.2025.0160876 PDF

77

Machine Learning-Based Climate Prediction in Indonesia: A Baseline Experiment

Author 1: Faisal Rahutomo Author 2: Bambang Harjito

This study presents the results of a series of machine learning experiments conducted on Indonesian climate data collected between 2010 and 2020. The findings offer a comparative foundation for future research. Weather prediction remains a significant challenge due to the complex interplay of various climatic factors. Weather stations typically record… Read full abstract & cite →

Indonesia climate data experiment baseline machine learning prediction

Abstract doi.org/10.14569/IJACSA.2025.0160877 PDF

78

Graph-Based Clustering of Short Texts Using Word Embedding Similarity

Author 1: Supakpong Jinarat Author 2: Ratchakoon Pruengkarn

The exponential growth of short textual content on the Internet, such as social media posts and search snippets, necessitates effective text mining techniques. Short text clustering, a critical tool for organizing this data, contends with two primary challenges: data sparsity, which undermines the quality of traditional clustering methods, and the… Read full abstract & cite →

Clustering graph-based clustering semantic similarity short text word embedding

Abstract doi.org/10.14569/IJACSA.2025.0160878 PDF

79

A Prompt-Driven Framework for Reflective Evaluation of Course Alignment Using Large Language Models

Author 1: Mashael M. Alsulami

Large language models (LLMs) such as ChatGPT are gaining attention in educational settings, yet their potential role in supporting course design and academic quality assurance remains underexplored. This study introduces a structured, prompt-driven framework that uses ChatGPT as a reflective tool to help faculty and curriculum designers evaluate the alignment… Read full abstract & cite →

Prompt engineering Course Learning Outcomes (CLOs) Large Language Models (LLMs) curriculum alignment educational quality assurance

Abstract doi.org/10.14569/IJACSA.2025.0160879 PDF

80

AI and 5G Integration for Smart City Energy Systems: A Systematic Literature Review

Author 1: TALBI Chaymae Author 2: Rahmouni M’hamed Author 3: OUAHBI Younesse Author 4: ZITI Soumia

Smart cities increasingly rely on Artificial Intelligence (AI), 5G, and Internet of Things (IoT) technologies to enhance energy management and support real-time decision-making in smart grids. This study presents a systematic literature review of recent research on the integration of AI and 5G in urban energy systems, with a focus… Read full abstract & cite →

Smart cities artificial intelligence 5G energy management smart grids renewable energy integration IoT machine learning sustainability

Abstract doi.org/10.14569/IJACSA.2025.0160880 PDF

81

State-of-the-Art in Software Security Visualization: A Systematic Review

Author 1: Ishara Devendra Author 2: Chaman Wijesiriwardana Author 3: Prasad Wimalaratne

Software security visualization is an interdisciplinary field that combines the technical complexity of cyberse-curity, including threat intelligence and compliance monitoring, with visual analytics, transforming complex security data into easily digestible visual formats. As software systems get more complex and the threat landscape evolves, traditional text-based and numerical methods for analyzing… Read full abstract & cite →

Security visualization vulnerability analysis threat intelligence compliance monitoring

Abstract doi.org/10.14569/IJACSA.2025.0160881 PDF

82

Human Versus AI: A Comparative Study of Zero-Shot LLMs and Transformer Models Against Human Annotations for Arabic Sentiment Analysis

Author 1: Dimah Alahmadi

Accurate sentiment analysis in Arabic natural language processing (NLP) remains a complex task due to the language’s rich morphology, syntactic variability, and diverse dialects. Traditional annotation approaches require human experts, face significant challenges related to inter-annotator agreement and dialectal understanding. Recent advances in transformer-based models and large language models (LLMs)… Read full abstract & cite →

Large Language Model (LLMs) transformers NLP annotation inter agreement sentiment analysis Saudi dialects

Abstract doi.org/10.14569/IJACSA.2025.0160882 PDF

83

Simulysis: A Method to Change Impact Analysis in Simulink Projects Based on WAVE-CIA

Author 1: Hoang-Viet Tran Author 2: Ta Van Thang Author 3: Cao Xuan Son Author 4: Do Trong Thu Author 5: Pham Ngoc Hung

MATLAB and Simulink, which have more than 5 million users and are installed at more than 100,000 businesses, universities, and government organizations1, are widely used in numerous large-scale projects across various industries. These projects continually evolve in response to changes in business logic. However, managing the impact of these changes… Read full abstract & cite →

Change impact analysis WAVE-CIA MAT-LAB/Simulink projects

Abstract doi.org/10.14569/IJACSA.2025.0160883 PDF

84

Feature Selection and Classification of Microarray Datasets Based on an Improved Binary Harris Hawks Optimization Algorithm

Author 1: Guoxia LI Author 2: Wen SHI Author 3: Jingyu ZHANG Author 4: Zhixia GU Author 5: Jixiang XU Author 6: Yueyue LI Author 7: Yaxing SUN

High-dimensional microarray datasets are prone to the “curse of dimensionality” due to feature redundancy, which impairs the performance of machine learning models, and feature selection is the key to addressing this issue. This study proposes an Improved Binary Harris Hawks Optimization algorithm (IBHHO) for feature selection in high-dimensional microarray data… Read full abstract & cite →

Microarray dataset feature selection parameter optimization ReliefF

Abstract doi.org/10.14569/IJACSA.2025.0160884 PDF

85

Robust Ulcerative Colitis Detection via Integrated Convolutional Feature Encoding, Bidirectional Temporal Context, and Data Augmentation for Class Imbalance

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

Ulcerative Colitis (UC), a chronic inflammatory bowel disease, presents significant diagnostic challenges due to its overlapping symptoms with other gastrointestinal disorders and the complex visual patterns in endoscopic imagery. Accurate and early detection is essential to guide effective treatment and improve patient outcomes. This research introduces a robust hybrid framework… Read full abstract & cite →

Ulcerative Colitis Detection (UCD) CNNs Bi-GRU Bi-LSTM medical image

Abstract doi.org/10.14569/IJACSA.2025.0160885 PDF

86

DALG: A Dual Attention-Based LSTM-GRU Model for Exchange Rate Volatility Forecasting in China’s Forex Sector

Author 1: Shamaila Butt Author 2: Mohammad Abrar Author 3: Muhammad Ali Chohan Author 4: Muhammad Farrukh Shahzad

Exchange rate volatility forecasting plays a vital role in guiding financial decisions and economic planning, particularly in China’s dynamic foreign exchange market. This study proposes a novel deep learning framework, termed DALG (Dual Attention-based LSTM-GRU), designed to capture complex temporal patterns and feature dependencies in high-frequency USD/RMB exchange rate data… Read full abstract & cite →

Exchange rate forecasting deep learning LSTM-GRU hybrid attention mechanism financial time series USD/RMB volatility

Abstract doi.org/10.14569/IJACSA.2025.0160886 PDF

87

Parameter-Free Negative Extreme Anomalous Undersampling Techniques on Class Imbalance Problems

Author 1: Benjawan Jantamat Author 2: Krung Sinapiromsaran

This research addressed the critical challenge of class imbalance in classification, which is a prevalent issue in real-world applications. Standard classifiers often struggled with imbalanced datasets and frequently misclassified the minority class (positive instances) due to the overwhelming presence of the majority class (negative instances). The proposed Negative Extreme Anomalous… Read full abstract & cite →

Classification class imbalance imbalanced datasets undersampling parameter-free method negative extreme anomalous score

Abstract doi.org/10.14569/IJACSA.2025.0160887 PDF

88

Blockchain Enabled Healthcare Supply Chain: Review, Case Study and Future Opportunities

Author 1: Muhammad Saad Author 2: Kamran Ali Author 3: Muhammad Awais Javed Author 4: Ahmad Naseem Alvi Author 5: Ahmed Alfakeeh

Blockchain is a major component of future smart healthcare that can improve the security, reliability, trust and automation of healthcare supply chain processes. Blockchain has several applications in areas such as medicine procurement, supply chain tracking, and drug traceability. In this study, we present a review of recent works in… Read full abstract & cite →

Blockchain smart contracts healthcare supply chain

Abstract doi.org/10.14569/IJACSA.2025.0160888 PDF

89

An Approach Based on Named Entity Recognition and Semantic Analysis for Recruitment Efficiency and Optimization

Author 1: Ismail Ifakir Author 2: Noureddine Mohtaram Author 3: El Habib Nfaoui Author 4: Abderrahim Zannou Author 5: Mohammed El Hassouni

Modern recruitment requires smarter, faster, and more inclusive methods to manage the growing volume and diversity of job applications and candidate resumes. Manual screening is often ineffective and unreliable especially in low-resource or multilingual contexts. To address this challenge, we propose an approach that automates and optimizes key stages of… Read full abstract & cite →

Named entity recognition large language models feature extraction generate question matching

Abstract doi.org/10.14569/IJACSA.2025.0160889 PDF

90

Towards a Robust DNA Storage System with a Multilayer Approach

Author 1: Ayoub Sghir Author 2: Manar Sais Author 3: Douha Bourached Author 4: Jaafar Abouchabaka Author 5: Najat Rafalia

The growing demand for data storage requires innovative, resilient solutions to the challenges of cost, space, and energy consumption posed by current methods. DNA stands out as a promising next-generation data storage medium, offering a remarkable storage density of 1019 bits per cubic centimeter, some eight orders of magnitude denser… Read full abstract & cite →

DNA storage data compression error correction huffman encoding run-length encoding LZW LZ77

Abstract doi.org/10.14569/IJACSA.2025.0160890 PDF

91

Hybrid Recommender System for Precision Chemical Application in Banana Cultivation Using Matrix Factorization and Content-Based Filtering

Author 1: Ravi Kumar Tirandasu Author 2: Prasanth Yalla Author 3: Pachipala Yellamma

Proper management of pesticides and fertilizers is critical towards effective control of the banana diseases, but integration of various agricultural data has been a problem. The novelty of this study is the hybrid recommendation system which encompasses Content-Based Filtering (CBF) with Matrix Factorization (MF) to be used when recommending chemical… Read full abstract & cite →

Hybrid recommendation system content-based filtering matrix factorization banana disease management agricultural data heterogeneity precision agriculture chemical application optimization black sigatoka

Abstract doi.org/10.14569/IJACSA.2025.0160891 PDF

92

Autonomous Self-Adaptation in the Cloud: ML-Heal’s Framework for Proactive Fault Detection and Recovery

Author 1: Qais Al-Na’amneh Author 2: Mahmoud Aljawarneh Author 3: Rahaf Hazaymih Author 4: Ayoub Alsarhan Author 5: Khalid Hamad Alnafisah Author 6: Nayef H. Alshammari Author 7: Sami Aziz Alshammari

Cloud computing environments increasingly host applications constructed from orchestrated service compositions, which deliver enhanced functionality through distributed work-flows. This paradigm, however, introduces vulnerabilities where component failures can cascade, disrupting entire applications. Conventional fault tolerance often falls short in these dynamic settings. This paper introduces ML-Heal, an autonomous self-healing framework architected… Read full abstract & cite →

Cloud computing service composition self-healing systems autonomic computing machine learning anomaly detec-tion automated recovery fault tolerance

Abstract doi.org/10.14569/IJACSA.2025.0160892 PDF

93

Exploring the Factors Influencing School Dropout: A Logit Model Analysis

Author 1: Noaman LAKCHOUCH Author 2: Lamarti Sefian MOHAMMED Author 3: Mustapha KHALFOUNI

School dropout negatively impacts a country’s development index, with numerous factors contributing to this complex phenomenon. To investigate the factors associated with school dropout in a specific region of Morocco, a cross-sectional study was conducted, encompassing a weighted sample of 274 junior secondary education students. Data collection was facilitated through… Read full abstract & cite →

School dropout development index Morocco cross-sectional study logistic regression academic performance exam grades age gender school transportation academic success

Abstract doi.org/10.14569/IJACSA.2025.0160893 PDF

94

Securing the Healthcare Supply Chain Using Blockchain-Enabled Smart Contracts

Author 1: Muhammad Saad Author 2: Hamail Ashraf Author 3: Muhammad Saffi Ullah Khan Author 4: Muhammad Awais Javed Author 5: Ahmad Naseem Alvi Author 6: Ahmed Alfakeeh

The blockchain technology is an innovative tool that has shown its effectiveness in many sectors such as health-care and many are likely to experience a revolutionary transformation. In healthcare, the blockchain functions like a distributed network which is constantly updated with records ensuring that you cannot eliminate or alter them… Read full abstract & cite →

Blockchain smart contracts supplychain

Abstract doi.org/10.14569/IJACSA.2025.0160894 PDF

95

A Scalable and Privacy-Preserving Hybrid Blockchain Architecture for Secure Healthcare Data Management

Author 1: Sanjida Sharmin Author 2: Mohammad Shamsul Arefin Author 3: Pranab Kumar Dhar Author 4: Zinnia Sultana Author 5: Sultana Akter

The protection of sensitive medical information has become a critical concern in modern digital healthcare. This study introduces a Hybrid Architecture that ensures secure and reliable healthcare data management through the integration of blockchain technology with off-chain and on-chain mechanisms. Patient records are encrypted using AES-256-GCM, stored in the InterPlanetary… Read full abstract & cite →

Blockchain healthcare AES-256-GCM merkle tree IPFS data security scalability gas optimization ethereum hybrid architecture

Abstract doi.org/10.14569/IJACSA.2025.0160895 PDF

96

Advanced Strategies for Big Data Resource and Storage Optimization: An AI Perspective

Author 1: Ayoub Sghir Author 2: Ayoub Allali Author 3: Najat Rafalia Author 4: Jaafar Abouchabaka

The increasing use of advanced technologies with artificial intelligence in our daily lives has become an urgent necessity to facilitate tasks in a fluid and simple way, which leads to the generation of huge amounts of data. This data comes from various sources: media, social networks, connected objects., online transactions… Read full abstract & cite →

Artificial intelligence big data optimization re-source storage

Abstract doi.org/10.14569/IJACSA.2025.0160896 PDF

97

YOLOv8s-Swin: Enhanced Tomato Ripeness Detection for Smart Agriculture

Author 1: Jalal Uddin Md Akbar Author 2: Syafiq Fauzi Kamarulzaman

Accurate object detection and classification are paramount in precision agriculture for assessing ripeness stages and optimizing yield, particularly for high-value crops like toma-toes. Traditional manual inspection methods are laborious, time-consuming, and error-prone. Furthermore, existing deep learning models often struggle with real-world agricultural challenges such as varying lighting, occlusions from foliage… Read full abstract & cite →

Agricultural automation attention mechanism computer vision smart agriculture object detection YOLO swin transformer

Abstract doi.org/10.14569/IJACSA.2025.0160897 PDF

98

Next-Generation Network Security: An Analysis of Threats, Challenges and Emerging Intelligent Defenses Within SDN and NFV Architectures

Author 1: Amina SAHBI Author 2: Faouzi JAIDI Author 3: Adel BOUHOULA

The integration of Software Defined Networking (SDN) and Network Function Virtualization (NFV) offers considerable advantages in terms of scalability, interoperability, and cost-efficiency. They redefine network architecture, replacing rigid hardware-based control with a more flexible, software-driven approach. However, this convergence also introduces significant security threats and challenges due to architectural vulnerabilities… Read full abstract & cite →

Next generation network security software defined networking network function virtualization network security artificial intelligence

Abstract doi.org/10.14569/IJACSA.2025.0160898 PDF

99

Bridging Tradition and Technology: Leveraging ERP Systems for Streamlined Supply Chains and Modernized Keropok Lekor Production Management

Author 1: Faizah Aplop Author 2: Wan Muhammad Ikhwan Wan Mohammad Author 3: Muhammad Nasyrul Adly Mohd Afendy Author 4: Mustafa Man Author 5: Fakhrul Adli Mohd Zaki Author 6: Rosaida Rosly Author 7: Ismail Abu Bakar

Online marketplace and social media offers sub-stantial opportunities for business growth for many and it has contributed greatly to the increase demand of keropok lekor (fish cracker) from Terengganu throughout Malaysia as the market reach is increasing. Positive effects of these online platforms as significant digital marketing tools encourage keropok… Read full abstract & cite →

Overall equipment effectiveness real-time information centralization data-driven workflows business digitalization

Abstract doi.org/10.14569/IJACSA.2025.0160899 PDF

100

Enhanced Phishing Website Detection Using Optimized Ensemble Stacking Models

Author 1: Zainab Alamri Author 2: Abeer Alhuzali Author 3: Bassma Alsulami Author 4: Daniyal Alghazzawi

Phishing attacks remain a persistent and evolving cybersecurity threat, necessitating the development of highly accurate and efficient detection mechanisms. This research introduces an optimized ensemble stacking framework for phishing website detection, leveraging advanced machine learning techniques, hybrid feature preprocessing, and meta-learning strategies. The proposed approach systematically evaluates nine diverse base… Read full abstract & cite →

Phishing detection machine learning ensemble stacking cybersecurity

Abstract doi.org/10.14569/IJACSA.2025.01608100 PDF

101

Grey Clustering Algorithm for Urban Air Quality Classification: A Case Study in Lima, Peru

Author 1: Alexi Delgado Author 2: Katherine Paredes Guerrero Author 3: Anderson Carrillo

This study introduces a grey clustering algorithm based on the Central Triangular Whitenization Weight Function (CTWF), designed to classify urban air quality under conditions of limited or uncertain data. Based on Grey Systems The-ory (GST), the proposed algorithm facilitates structured multi-criteria assessments using sparse or irregular datasets—a condition frequently encountered… Read full abstract & cite →

Grey clustering algorithm air quality classification grey systems theory urban air pollution

Abstract doi.org/10.14569/IJACSA.2025.01608101 PDF

102

Simulation-Driven Improvement of King Khalid University Non-Monthly Entitlement Workflows in AnyLogic

Author 1: Elaf Ali Alsisi Author 2: Osman A. Nasr Author 3: Badriah Mousa Alqahtani Author 4: Rodoon Shawan Alnajei

Aiming to offer useful recommendations for enhancing process accuracy and operational performance, this study investigates the elements affecting the efficiency and timeliness of disbursing non-monthly financial entitlements to university staff. The study developed a process workflow model using AnyLogic simulation tools and structured interviews and then conducted two main tests… Read full abstract & cite →

Non-monthly financial entitlements operational efficiency Anylogic simulation process optimization university staff

Abstract doi.org/10.14569/IJACSA.2025.01608102 PDF

103

From Review to Refinement: An Expert-Informed Environmental Diagnostic Model for Stingless Bee Colony Monitoring

Author 1: Yang Lejing Author 2: Rozi Nor Haizan Nor Author 3: Yusmadi Yah Jusoh Author 4: Nur Ilyana Ismarau Tajuddin Author 5: Khairi Azhar Aziz

The resilience of stingless bee colonies has become increasingly challenged by erratic climate conditions and intensified environmental stressors. While previous studies have introduced diagnostic models for monitoring colony health, most remain constrained by a narrow reliance on either environmental or behavioral parameters alone. This study proposes a refined diagnostic model… Read full abstract & cite →

Stingless bees environmental monitoring behavioral analysis diagnostic model expert-informed refinement

Abstract doi.org/10.14569/IJACSA.2025.01608103 PDF

104

A Secure Authentication Protocol for IoT Devices

Author 1: Mohamed Ech-Chebaby Author 2: Hicham Zougagh Author 3: Hamid Garmani Author 4: Zouhair Elhadari

The rapid evolution of the Internet of Things (IoT) offers vast opportunities in automation and connectivity, yet simultaneously introduces critical security challenges. One of the most pressing concerns lies in the heterogeneity and limited computational capabilities of IoT devices, which complicate the deployment of robust security mechanisms. In this work… Read full abstract & cite →

IoT Internet of Things security authentication

Abstract doi.org/10.14569/IJACSA.2025.01608104 PDF

105

QoS-Aware Deployment and Synchronization of Digital Twins Over Federated Cloud Platforms for Smart Infrastructure Monitoring

Author 1: M V Narayana Author 2: Naveen Reddy N Author 3: Madhu S Author 4: Madhu T Author 5: Niladri Sekhar Dey Author 6: Sanjeev Shrivastava

This electronic increasingly, Digital Twin (DT) systems are being leveraged in smart infrastructure settings (e.g., structural health monitoring, intelligent traffic controls, and distributed utility networks). Yet, the available solutions all face hurdles that can prevent real-time synchronization of DT instances across federated cloud platforms, primarily due to latency variation, quality… Read full abstract & cite →

QoS-aware digital twins federated cloud synchronization smart infrastructure monitoring latency-constrained orchestration edge-assisted deployment

Abstract doi.org/10.14569/IJACSA.2025.01608105 PDF