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IJACSA Vol. 15 Issue 11 (2024)

Open Access | | 136 papers

Copyright Statement: This is an open access publication licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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1

Predicting Cervical Cancer Based on Behavioral Risk Factors

Author 1: Rakeshkumar Mahto Author 2: Kanika Sood

Machine learning (ML) based predictive models are increasingly used in various fields due to their ability to find patterns and interpret complex relationships between variables in an extensive dataset. However, getting a comprehensive dataset is challenging in the field of medicine for rare or emerging infections. Therefore, developing a robust… Read full abstract & cite →

Cervical cancer random forest voting classifier Adaptive Synthetic Sampling (ADASYN) predictive model
Abstract doi.org/10.14569/IJACSA.2024.0151101 PDF
2

Comparative Analysis of Machine Learning Models for Forecasting Infectious Disease Spread

Author 1: Praveen Damacharla Author 2: Venkata Akhil Kumar Gummadi

Accurate forecasting of infectious disease spread is essential for effective resource planning and strategic decision-making in public health. This study provides a comprehensive evaluation of various machine learning models, from traditional statistical approaches to advanced deep learning techniques, for forecasting disease outbreak dynamics. Focusing on daily positive cases and daily… Read full abstract & cite →

Machine learning linear regression random forest time series XGBoost
Abstract doi.org/10.14569/IJACSA.2024.0151102 PDF
3

Augmented Reality in Education: Revolutionizing Teaching and Learning Practices – State-of-the-Art

Author 1: Samer Alhebaishi Author 2: Richard Stone

The evolution and contemporary applications of instructional technology, particularly the transformative impact of Augmented Reality (AR) in education, are comprehensively explored in this study. Tracing the journey from early visual aids to sophisticated AR, the aim is to highlight continuous efforts to enhance educational experiences. The effectiveness of AR in… Read full abstract & cite →

Augmented reality education instructional technology technology integration student engagement teacher training
Abstract doi.org/10.14569/IJACSA.2024.0151103 PDF
4

The Future of Mainframe IDMS: Leveraging Artificial Intelligence for Modernization and Efficiency

Author 1: Vasanthi Govindaraj

IDMS (Integrated Database Management System) has long been a backbone for mission-critical systems in finance, healthcare, and government sectors. However, the rigid architecture of legacy systems poses challenges in scalability, flexibility, and integration with modern technologies. This paper explores IDMS modernization using Artificial Intelligence (AI), with a focus on predictive… Read full abstract & cite →

IDMS modernization artificial intelligence in legacy systems mainframe database optimization predictive maintenance cloud integration AI-driven query optimization
Abstract doi.org/10.14569/IJACSA.2024.0151104 PDF
5

The Future of IoT Security in Saudi Arabian Start-Ups: A Position Paper

Author 1: Safar Albaqami Author 2: Maziar Nekovee Author 3: Imran Khan

This research explores the intricacies of implementing and securing Internet of Things (IoT) technology in Saudi Arabian startups. In the middle of Saudi Arabia's ambitious pursuit of social and economic progress via IoT breakthroughs, entrepreneurs have emerged as critical participants grappling with serious computing security challenges. This study conducts a… Read full abstract & cite →

IoT Saudi Arabia start-ups computing security challenges technology innovation cyber threats
Abstract doi.org/10.14569/IJACSA.2024.0151105 PDF
6

A Low-Cost IoT Sensor for Indoor Monitoring with Prediction-Based Data Collection

Author 1: Paolo Capellacci Author 2: Lorenzo Calisti Author 3: Emanuele Lattanzi

The proliferation of Internet of Things technologies has revolutionized the landscape of indoor environmental monitoring, offering opportunities to enhance comfort, health, and energy efficiency. This paper presents the development and implementation of a low-cost IoT sensor system designed for indoor monitoring with a Machine Learning-driven prediction-based data collection approach. Leveraging… Read full abstract & cite →

IoT indoor monitoring prediction-based data collection deep-learning
Abstract doi.org/10.14569/IJACSA.2024.0151106 PDF
7

Reliable Logistic Regression for Credit Card Fraud Detection

Author 1: Yassine Hmidy Author 2: Mouna Ben Mabrouk

Credit card fraud poses a significant threat to financial institutions and consumers worldwide, necessitating robust and reliable detection methods. Traditional classification models often struggle with the challenges of imbalanced datasets, noise, and outliers inherent in transaction data. This paper introduces a novel fraud detection approach based on a discrete non-additive… Read full abstract & cite →

Credit card fraud fraud detection computational complexity
Abstract doi.org/10.14569/IJACSA.2024.0151107 PDF
8

AI Ethical Framework: A Government-Centric Tool Using Generative AI

Author 1: Lalla Aicha Kone Author 2: Anna Ouskova Leonteva Author 3: Mamadou Tourad Diallo Author 4: Ahmedou Haouba Author 5: Pierre COLLET

Artificial Intelligence (AI) is transforming industries and societies globally. To fully harness this advancement, it is crucial for countries to integrate AI across different domains. Moral relativism in AI ethics suggests that as ethical norms vary significantly across societies, frameworks guiding AI development should be context-specific, reflecting the values, norms… Read full abstract & cite →

AI ethics Gen AI LLMs moral relativism ethical norms adaptive ethical framework
Abstract doi.org/10.14569/IJACSA.2024.0151108 PDF
9

Simulation-Based Analysis of Evacuation Information Sharing Systems Using Geographical Data

Author 1: Tatsuki Fukuda

In this study, we developed an agent-based model (ABM) to simulate and improve evacuation rates during flood disasters. Utilizing the “Evacuate Now Button”, a previously proposed system for sharing real-time evacuation rates among residents, our experimental findings demonstrate a significant enhancement in evacuation behavior through this system. Simulations were conducted… Read full abstract & cite →

Evacuation flood disaster evacuation rate agent-based model evacuate now button
Abstract doi.org/10.14569/IJACSA.2024.0151109 PDF
10

Application of Unbalanced Optimal Transport in Healthcare

Author 1: Qui Phu Pham Author 2: Nghia Thu Truong Author 3: Hoang-Hiep Nguyen-Mau Author 4: Cuong Nguyen Author 5: Mai Ngoc Tran Author 6: Dung Luong

Optimal Transport (OT) is a powerful tool widely used in healthcare applications, but its high computational cost and sensitivity to data changes make it less practical for resource-constrained settings. These limitations also contribute to increased environmental impact due to higher CO2 emissions from computing. To address these challenges, we explore… Read full abstract & cite →

Optimal transport unbalanced optimal transport healthcare
Abstract doi.org/10.14569/IJACSA.2024.0151110 PDF
11

Fuzzy Logic-Driven Machine Learning Algorithms for Improved Early Disease Diagnosis

Author 1: Leena Arya Author 2: Narasimha Swamy Lavudiya Author 3: G Sateesh Author 4: Harish Padmanaban Author 5: B. V. Srinivasulu Author 6: Ravi Rastogi

Early disease diagnosis is critical in improving patient outcomes, reducing healthcare costs, and preferably timely intervention. Unfortunately, the algorithms used in conventional diagnostic technology have difficulties dealing with uncertain and imprecise medical data, which may result in either delay or misdiagnosis. This paper describes the combined framework of fuzzy logic… Read full abstract & cite →

Decision trees Fuzzy Inference System (FIS) heart disease diagnosis neural networks Support Vector Machine (SVM)
Abstract doi.org/10.14569/IJACSA.2024.0151111 PDF
12

Automatic Detection of Lumbar Spine Disc Herniation

Author 1: Mohammed Al Masarweh Author 2: Olukola Oluseyi Author 3: Ala Alkafri Author 4: Hiba Alsmadi Author 5: Tariq Alwadan

Advanced deep-learning approaches have set new standards for computer vision and pattern recognition. However, the complexity of medical images frequently impedes the creation of high-quality ground truth data. In this article, we offer a method for autonomously generating ground truth data from MRI images using instance segmentation, with a novel… Read full abstract & cite →

Lumbar Disc Herniation MASK-RCNN computer vision artificial intelligence MR Images
Abstract doi.org/10.14569/IJACSA.2024.0151112 PDF
13

AI-Powered AOP: Enhancing Runtime Monitoring with Large Language Models and Statistical Learning

Author 1: Anas AlSobeh Author 2: Amani Shatnawi Author 3: Bilal Al-Ahmad Author 4: Alhan Aljmal Author 5: Samer Khamaiseh

Modern software systems must adapt to dynamic artificial intelligence (AI) environments and evolving requirements. Aspect-oriented programming (AOP) effectively isolates crosscutting concerns (CCs) into single modules called aspects, enhancing quality metrics, and simplifying testing. However, AOP implementation can lead to unexpected program outputs and behavior changes. This paper proposes an AI-enhanced… Read full abstract & cite →

Artificial Intelligence (AI) Aspect-Oriented Programming (AOP) runtime monitoring Large Language Models (LLMs) Codex AI software validation statistical model checking dynamic program analysis cross-cutting concerns joinpoints pointcut
Abstract doi.org/10.14569/IJACSA.2024.0151113 PDF
14

Optimizing Stroke Risk Prediction Using XGBoost and Deep Neural Networks

Author 1: Renuka Agrawal Author 2: Aaditya Ahire Author 3: Dimple Mehta Author 4: Preeti Hemnani Author 5: Safa Hamdare

Predicting brain strokes is inherently complex due to the multifaceted nature of brain health. Recent advancements in machine learning (ML) and deep learning (DL) algorithms have shown promise in forecasting stroke occurrences to a certain extent. This research paper explores the predictive potential of ML and DL models by utilizing… Read full abstract & cite →

DNN XGBoost stress level stroke prediction
Abstract doi.org/10.14569/IJACSA.2024.0151114 PDF
15

Financial Shifts, Ethical Dilemmas, and Investment Insights in Nursing Homes: A Pre- and Post-Pandemic Analysis

Author 1: Amir El-Ghamry Author 2: Ameera Ibrahim Author 3: Noha Elfiky Author 4: Safwat Hamad

The COVID-19 pandemic has significantly transformed the operational, financial, and ethical frameworks of nursing homes in the United States. This study offers a detailed analysis of the nursing home sector from 2015 to 2021, focusing on the financial viability and ethical standards before, during, and after the pandemic. The methodology… Read full abstract & cite →

Component COVID-19 impact nursing home financial performance post-pandemic investment ethical standards in nursing homes
Abstract doi.org/10.14569/IJACSA.2024.0151115 PDF
16

FusionSec-IoT: A Federated Learning-Based Intrusion Detection System for Enhancing Security in IoT Networks

Author 1: Jatinder Pal Singh Author 2: Rafaqat Kazmi

Internet of Things (IoT) has become one of the most significant technological advancements of the modern era, which has impacted multiple sectors in the way it provides communication between connected devices. However, this growth has led to security risks in the IoT devices especially when constructing resource-limited IoT networks that… Read full abstract & cite →

IoT security Intrusion Detection System (IDS) federated learning multi-view learning cyberattack detection
Abstract doi.org/10.14569/IJACSA.2024.0151116 PDF
17

Incorporating Local Texture Adversarial Branch and Hybrid Attention for Image Super-Resolution

Author 1: Na Zhang Author 2: Hanhao Yao Author 3: Qingqi Zhang Author 4: Xiaoan Bao Author 5: Biao Wu Author 6: Xiaomei Tu

In the field of image Super-Resolution reconstruction (SR), traditional SR techniques such as regression-based methods and CNN-based models fail to retain texture details in the reconstructed images. Conversely, Generative Adversarial Networks (GANs) have significantly enhanced the visual quality of image reconstruction through their adversarial training architecture. However, existing GANs still… Read full abstract & cite →

Super-resolution reconstruction generative adversarial network hybrid attention local texture sampling
Abstract doi.org/10.14569/IJACSA.2024.0151117 PDF
18

Image Restoration of Landscape Design Based on DCGAN Optimization Algorithm

Author 1: Wenjun Zhang

To enhance the quality and effectiveness of image restoration in landscape design, this study optimizes the existing methods for low efficiency and incomplete feature extraction in processing high-resolution and detail rich landscape design images. Firstly, based on the traditional generative adversarial network (GAN), a novel deep convolutional generative adversarial network… Read full abstract & cite →

Deep convolutional generative adversarial network image restoration landscape architecture squeeze-and-excitation network dense convolutional network
Abstract doi.org/10.14569/IJACSA.2024.0151118 PDF
19

Tennis Action Evaluation Model Based on Weighted Counter Clockwise Rotation Angle Similarity Measurement Method

Author 1: Danni Jiang Author 2: Ge Liu

In order to intelligently analyze tennis movements and improve evaluation efficiency, a counter clockwise rotation angle of limbs is proposed to solve the direction problem of tennis movements. A dynamic time regularization algorithm is optimized by combining global time weighting and adjacent frame weighting. The results indicated that the proposed… Read full abstract & cite →

Action evaluation counter clockwise rotation angle weighting dynamic time warping tennis
Abstract doi.org/10.14569/IJACSA.2024.0151119 PDF
20

Internet of Things User Behavior Analysis Model Based on Improved RNN

Author 1: Keling Bi

Currently, there are issues with low efficiency and outdated Internet of Things resource allocation. To study real Internet of Things user behavior data, a Bayesian optimization algorithm is used to automatically select hyperparameter combinations and construct an Internet of Things user behavior analysis model based on long short-term memory. The… Read full abstract & cite →

Internet of Things user behaviors recurrent neural network Bayesian optimization long short-term memory hyperparameter
Abstract doi.org/10.14569/IJACSA.2024.0151120 PDF
21

Network Security Based on Improved Genetic Algorithm and Weighted Error Back-Propagation Algorithm

Author 1: Junjuan Liang

In order to solve the problem of feature selection and local optimal solution in the field of network security, a network security protection model based on improved genetic algorithm and weighted error back-propagation algorithm is proposed. The model combines the dynamic error weight and adaptive learning rate of the weighted… Read full abstract & cite →

Genetic algorithm weighted error back-propagation multiple strategies network security
Abstract doi.org/10.14569/IJACSA.2024.0151121 PDF
22

Q-FuzzyNet: A Quantum Inspired QIF-RNN and SA-FPA Optimizer for Intrusion Detection and Mitigation in Intelligent Connected Vehicles

Author 1: Abdullah Alenizi

In the evolving landscape of Intelligent Connected Vehicles (ICVs), ensuring cybersecurity is crucial due to the increasing number of cyber threats. Besides, challenges like data breaches, unauthorized access, and hacking attempts are prevalent due to the interconnected nature of ICVs. Several methods have been proposed to secure ICVs; however, accurate… Read full abstract & cite →

Cybersecurity intelligent connected vehicles artificial intelligence quantum neural network recurrent neural network flower pollination algorithm
Abstract doi.org/10.14569/IJACSA.2024.0151122 PDF
23

Predicting Learners’ Academic Progression Using Subspace Clique Model in Multidimensional Data

Author 1: Oyugi Odhiambo James Author 2: Waweru Mwangi Author 3: Kennedy Ogada

Subspace clustering examines the traditional clustering techniques that have previously been considered the best approaches to clustering data. This study uses a subspace clustering approach to predict learners' academic progress over time. Using the subspace clustering method, a model was developed that improves the classic Clique by optimizing clustering performance… Read full abstract & cite →

Subspace clustering clique model academic progression multidimensional data feature engineering cross validation and principal component analysis
Abstract doi.org/10.14569/IJACSA.2024.0151123 PDF
24

Enhanced TODIM-TOPSIS Framework for Interior Design Quality Evaluation in Public Spaces Under Hesitant Fuzzy Sets

Author 1: Lu Peng

The evaluation of interior landscape design in public spaces involves several aspects, including aesthetics, functionality, sustainability, and user experience. Aesthetic evaluation focuses on the visual appeal and stylistic consistency of the design. Functionality considers the practicality and convenience of the space layout. Sustainability evaluates the environmental friendliness of materials and… Read full abstract & cite →

Multiple-attribute decision-making (MADM) hesitant fuzzy sets (HFSs) TODIM TOPSIS design quality evaluation
Abstract doi.org/10.14569/IJACSA.2024.0151124 PDF
25

ARO-CapsNet: A Novel Method for Evaluating User Experience in Immersive VR Furniture Design

Author 1: Yin Luo Author 2: Jun Liu Author 3: Li Zhang

Immersive virtual reality (VR) technology has become an essential tool in enhancing user experience across industries, particularly in furniture design. With the ability to provide realistic, interactive, and immersive environments, it significantly improves user engagement and decision-making in product design. However, existing analysis methods lack precision in evaluating user experience… Read full abstract & cite →

Immersive virtual reality furniture design application analysis artificial rabbit optimisation algorithm
Abstract doi.org/10.14569/IJACSA.2024.0151125 PDF
26

Application Pigeon Swarm Intelligent Optimisation BP Neural Network Algorithm in Railway Tunnel Construction

Author 1: Feng Zhou Author 2: Hong Ye Author 3: Jie Song Author 4: Hui Guo Author 5: Peng Liu

Due to the uncertainty and complexity of the risk factors of the urban railway tunnel project to increase the difficulty of risk analysis, so that the traditional risk assessment methods can not accurately assess the construction risk of the urban railway tunnel project. Aiming at the problems of the existing… Read full abstract & cite →

Municipal railway tunnel construction optimization scenario risk assessment machine learning pigeon flock optimisation algorithm
Abstract doi.org/10.14569/IJACSA.2024.0151126 PDF
27

A Data-Driven Deep Machine Learning Approach for Tunnel Deformation Risk Assessment

Author 1: Fusheng Liu

The shallow overburden pipe jacking over operation tunnel construction project in chalk stratum has the risk of deformation of the soil layer and the existing tunnel, which increases the difficulty of pipe jacking over construction, and the risk assessment and control become the key technology for the safe and successful… Read full abstract & cite →

Pipe jacking up and over operational tunnel construction tunnel deformation risk assessment deep limit learning machine hybrid leader optimisation algorithm control strategy
Abstract doi.org/10.14569/IJACSA.2024.0151127 PDF
28

Scalp Disorder Imaging: How Deep Learning and Explainable Artificial Intelligence are Revolutionizing Diagnosis and Treatment

Author 1: Vinh Quang Tran Author 2: Haewon Byeon

Scalp disorders, affecting millions worldwide, significantly impact both physical and mental health. Deep learning has emerged as a promising tool for automated diagnosis, but ensuring model transparency and reliability is crucial. This review explores the integration of explainable AI (XAI) techniques to enhance the interpretability of deep learning models in… Read full abstract & cite →

Scalp disorders artificial intelligence explainable artificial intelligence deep learning interpretability
Abstract doi.org/10.14569/IJACSA.2024.0151128 PDF
29

A Theoretical Framework of Extrinsic Feedback Evaluation in Football Training Based on Motion Templates Using Motion Capture

Author 1: Amir Irfan Mazian Author 2: Wan Rizhan Author 3: Normala Rahim Author 4: Muhammad D. Zakaria Author 5: Mohd Sufian Mat Deris Author 6: Fadzli Syed Abdullah Author 7: Ahmad Rafi

Motion capture technology (MoCap) has emerged as a pivotal innovation, significantly impacting various sectors, including sports. In football training, MoCap is especially crucial for analyzing player movements with precision. Despite its potential, there remains a notable gap in the utilization of MoCap to create motion templates (MTs) that generate extrinsic… Read full abstract & cite →

Motion capture motion templates football extrinsic feedback reverse-gesture description language
Abstract doi.org/10.14569/IJACSA.2024.0151129 PDF
30

An Application of Graph Neural Network Model Design for Residential Building Layout Design

Author 1: Shiyu Wang Author 2: Ningbo Wang

In the current process of residential building layout design, there are problems such as low design efficiency, excessive manual intervention, and difficulty in meeting personalized needs. To address these issues, a residential building layout design method based on graph neural network model is proposed to improve the intelligence level of… Read full abstract & cite →

Residential building layout plan deep learning GNN model space utilization rate resident comfort level quantum particle swarm algorithm Node2vec algorithm
Abstract doi.org/10.14569/IJACSA.2024.0151130 PDF
31

An Intelligent Transport System for Prediction of Urban Traffic Congestion Level

Author 1: Mohammad Khalid Imam Rahmani Author 2: Shahnawaz Khan Author 3: Md Ezaz Ahmed Author 4: Khurram Jawad

Developing a resilient infrastructure is crucial for nation-building by supporting innovations and promoting sustainable growth. The Kingdom of Saudi Arabia is striving to achieve the Sustainable Development Goals (SDGs) set by the United Nations. Industry, Innovation, and Infrastructure (I3) are some of the strategic objectives of the Kingdom’s Vision 2030… Read full abstract & cite →

Sustainable development goals traffic congestion traffic prediction Gated Recurrent Unit long short-term memory intelligent transport system
Abstract doi.org/10.14569/IJACSA.2024.0151131 PDF
32

SAM-PIE: SAM-Enabled Photovoltaic-Module Image Enhancement for Fault Inspection and Analysis Using ResNet50 and CNNs

Author 1: Rotimi-Williams Bello Author 2: Pius A. Owolawi Author 3: Etienne A. van Wyk Author 4: Chunling Du

Different models have been developed for segmentation tasks, each with its uniqueness. Recently, the Segment Anything Model (SAM) was added to the pool of these models with expectations of addressing their weaknesses. SAM, although trained on a huge dataset for segmentation of anything, particularly images of natural source, produces suboptimal… Read full abstract & cite →

Anomaly convolution neural networks crack hotspot photovoltaic Residual Network-50 shading
Abstract doi.org/10.14569/IJACSA.2024.0151132 PDF
33

Understanding Mental Health Content on Social Media and It’s Effect Towards Suicidal Ideation

Author 1: Mohaiminul Islam Bhuiyan Author 2: Nur Shazwani Kamarudin Author 3: Nur Hafieza Ismail

The study “Understanding Mental Health Content on Social Media and Its Effect Towards Suicidal Ideation” aims to detail the recognition of suicidal intent through social media, with a focus on the improvement and part of the machine learning (ML), deep learning (DL), and natural language processing (NLP). This review underscores… Read full abstract & cite →

Suicidal ideation detection social media analysis mental health text analysis machine learning
Abstract doi.org/10.14569/IJACSA.2024.0151133 PDF
34

Classification of Liver Disease Using Conventional Tree-Based Machine Learning Approaches with Feature Prioritization Using a Heuristic Algorithm

Author 1: Proloy Kumar Mondal Author 2: Haewon Byeon

Liver disease ranks as one of the leading causes of mortality globally, often going undetected until advanced stages. This study aims to enhance early detection of liver disease by employing machine learning models that utilize key health indicators. Utilizing the Indian Liver Patient Dataset (ILPD) from the UCI repository, we… Read full abstract & cite →

Liver disease classification prediction CatBoost algorithm machine learning optimization algorithm
Abstract doi.org/10.14569/IJACSA.2024.0151134 PDF
35

Optimizing Deep Learning for Diabetic Retinopathy Diagnosis

Author 1: Krit Sriporn Author 2: Cheng-Fa Tsai Author 3: Li-Jia Rong Author 4: Paohsi Wang Author 5: Tso-Yen Tsai Author 6: Chih-Wen Chen

The detection of diabetic retinopathy traditionally requires the expertise of medical professionals, making manual detection both time- and labor-intensive. To address these challenges, numerous studies in recent years have proposed automatic detection methods for diabetic retinopathy. This research focuses on applying deep learning and image processing techniques to overcome the… Read full abstract & cite →

Diabetic retinopathy deep learning image processing technologies imbalanced image dataset computer aided diagnosis
Abstract doi.org/10.14569/IJACSA.2024.0151135 PDF
36

Assessing the Usability of M-Health Applications: A Comparison of Usability Testing, Heuristics Evaluation and Cognitive Walkthrough Methods

Author 1: Obead Alhadreti

Mobile health applications have increasingly become an important channel for providing services in the health sector. However, poor usability can be a major barrier for the rapid adoption of mobile services. The purpose of this study is to compare the relative performance of three usability evaluation methods, namely, usability testing… Read full abstract & cite →

Mobile health applications usability usability testing heuristics evaluation cognitive walkthrough
Abstract doi.org/10.14569/IJACSA.2024.0151136 PDF
37

Automated Hydroponic Growth Simulation for Lettuce Using ARIMA and Prophet Models During Rainy Season in Indonesia

Author 1: Lendy Rahmadi Author 2: Hadiyanto Author 3: Ridwan Sanjaya

Hydroponic farming particularly lettuce cultivation, is gaining popularity in Indonesia due to its economical use of water and space, as well as its short growing season. This study focuses on developing of an Automated Hydroponic Growth Simulation for Lettuce Using ARIMA and Prophet Models during the Rainy Season in Indonesia… Read full abstract & cite →

ARIMA automated growth hydroponic prophet simulation
Abstract doi.org/10.14569/IJACSA.2024.0151137 PDF
38

Improved Real-Time Smoke Detection Model Based on RT-DETR

Author 1: Yuanpan ZHENG Author 2: Zeyuan HUANG Author 3: Binbin CHEN Author 4: Chao WANG Author 5: Yu ZHANG

Fire remains a major threat to society and economic activities. Given the real-time demands of smoke detection, most research in deep learning has focused on Convolutional Neural Networks. The Real-Time Detection Transformer (RT-DETR) introduces a promising alternative for this task. This paper extends RT-DETR to address challenges such as morphological… Read full abstract & cite →

RT-DETR smoke detection deformable convolution multi-scale feature fusion EIoU image enhancement dark channel
Abstract doi.org/10.14569/IJACSA.2024.0151138 PDF
39

Predicting Stock Price Bubbles in China Using Machine Learning

Author 1: Yunxi Wang Author 2: Tongjai Yampaka

Financial bubbles have long been a focus of researchers, particularly due to the severe negative impacts following the bursting of financial bubbles. Therefore, the ability to effectively predict financial bubbles is of paramount importance. The aim of this study is to measure and predict the stock market price bubble in… Read full abstract & cite →

Stock price bubbles machine learning Chinese stock market
Abstract doi.org/10.14569/IJACSA.2024.0151139 PDF
40

Multi-Factor Risk Assessment and Route Optimization for Safe Human Travel

Author 1: Thilagavathi T Author 2: Subashini A

In the modern world, frequent travel has become a necessity, with vehicles being the primary mode of transportation. Ensuring human safety while traveling is paramount. To address this, it is essential to adopt a combination of numerous static and dynamic parameters to achieve optimal route design in today’s complex transportation… Read full abstract & cite →

Multi-factor risk assessment route optimization human travel safety static and dynamic parameters risk factor analysis
Abstract doi.org/10.14569/IJACSA.2024.0151140 PDF
41

An Ensemble Machine Learning Model for Predictive Maintenance on Water Injection Pumps in the Oil and Gas Industry

Author 1: Salama Mohamed Almazrouei Author 2: Fikri Dweiri Author 3: Ridvan Aydin Author 4: Abdalla Alnaqbi

The effective operation of water injection pumps is vital for enhancing oil recovery in the oil and gas industry. To ensure optimal pump performance and prevent unplanned downtime, this study focused on implementing predictive maintenance strategies. We began by identifying five critical operational parameters—Seal Pressure 1, Seal Pressure 2, Vibration… Read full abstract & cite →

Ensemble machine learning models oil and gas industry predictive maintenance water injection pumps
Abstract doi.org/10.14569/IJACSA.2024.0151141 PDF
42

Performance Evaluation of the AuRa Consensus Algorithm for Digital Certificate Processes on the Ethereum Blockchain

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

The blockchain serves as a distributed database where data is stored across different servers and networks. It encompasses various types, with Bitcoin, Ethereum, and Hyperledger being notable examples. To safeguard the security of data transactions on the blockchain, it relies on a consensus algorithm. This algorithm facilitates agreement among nodes… Read full abstract & cite →

Blockchain Ethereum consensus algorithm smart contract AuRa_ori AuRa_v1
Abstract doi.org/10.14569/IJACSA.2024.0151142 PDF
43

Enhancing Multiple-Attribute Decision-Making with Interval-Valued Neutrosophic Sets: Diverse Applications in Evaluating English Teaching Quality

Author 1: Lijuan Zhao Author 2: Shuo Du

The evaluation of college English teaching quality is a key method for systematically analyzing and providing feedback on the teaching process and outcomes. It aims to comprehensively assess the effectiveness of teaching, student learning outcomes, and the appropriateness of the course design. The evaluation typically covers aspects such as teaching… Read full abstract & cite →

Multiple-attribute decision-making interval-valued neutrosophic sets (IVNSs) Aczel-Alsina operations teaching quality evaluation
Abstract doi.org/10.14569/IJACSA.2024.0151143 PDF
44

A Smoke Source Location Method Based on Deep Learning Smoke Segmentation

Author 1: Yuanpan ZHENG Author 2: Zeyuan HUANG Author 3: Hui WANG Author 4: Binbin CHEN Author 5: Chao WANG Author 6: Yu ZHANG

The generation of smoke is an early warning sign of a fire, and fast, accurate detection of smoke sources is crucial for fire prevention. However, due to the strong diffusivity of smoke, its morphology is easily influenced by environmental factors, and in complex real-world scenarios, smoke sources are often obscured… Read full abstract & cite →

Smoke segmentation smoke source detection deep learning instance segmentation mathematical modeling
Abstract doi.org/10.14569/IJACSA.2024.0151144 PDF
45

Detecting GPS Spoofing Attacks Using Corrected Low-Cost INS Data with an LSTM Network

Author 1: Mohammed AFTATAH Author 2: Khalid ZEBBARA

With the emergence of new technologies ranging from smart cities to the Internet of Things (IoT), many objects rely on satellite-based navigation systems, such as GPS, to accomplish their tasks securely. However, GPS receivers are exposed to various unintentional and intentional attacks, threatening the availability and reliability of the delivered… Read full abstract & cite →

Secure navigation GPS spoofing inertial systems LSTM M-of-N method anti-spoofing techniques
Abstract doi.org/10.14569/IJACSA.2024.0151145 PDF
46

Time Distributed MobileNetV2 with Auto-CLAHE for Eye Region Drowsiness Detection in Low Light Conditions

Author 1: Farrikh Alzami Author 2: Muhammad Naufal Author 3: Harun Al Azies Author 4: Sri Winarno Author 5: Moch Arief Soeleman

Driver drowsiness is a critical factor in road safety, contributing significantly to traffic accidents. This study proposes an innovative approach integrating Auto-CLAHE with Time Distributed MobileNetV2 to enhance drowsiness detection accuracy. This study leveraged the ULg Multimodality Drowsiness Database (DROZY) for facial expression analysis, focusing on the eye region. This… Read full abstract & cite →

Driver drowsiness detection Auto-CLAHE time distributed MobileNetV2 eye region analysis
Abstract doi.org/10.14569/IJACSA.2024.0151146 PDF
47

Random Forest Algorithm for HR Data Classification and Performance Analysis in Cloud Environments

Author 1: Fangfang Dong

This study applies the Random forest algorithm to classify and evaluate the effectiveness of business human resources (HR) data, focusing on its potential in supporting strategic decision-making and enhancing organizational efficiency. The research introduces a model that automates the categorization of HR data, including employee records, performance evaluations, and training… Read full abstract & cite →

Random forest algorithm business human resources data classification
Abstract doi.org/10.14569/IJACSA.2024.0151147 PDF
48

Feature Selection Methods Using RBFNN-Based to Enhance Air Quality Prediction: Insights from Shah Alam

Author 1: Siti Khadijah Arafin Author 2: Ahmad Zia Ul-Saufie Author 3: Nor Azura Md Ghani Author 4: Nurain Ibrahim

This study examines the predictive efficiency of several feature selection approaches in air quality models aimed to predict next-day PM2.5 concentrations in Shah Alam, Malaysia. Air pollution in urban areas is a significant public health concern, and accurate prediction models are essential for timely interventions. However, determining the most important… Read full abstract & cite →

Lasso mRMR PM2.5 concentration RBFNN ReliefF
Abstract doi.org/10.14569/IJACSA.2024.0151148 PDF
49

Optimizing CatBoost Model: AI-based Analysis on Rail Transit Figma Platform Practice

Author 1: Ruobing Li Author 2: Hong Qian

The research introduces a novel approach that utilizes the Frilled Lizard Optimization (FLO) algorithm to enhance the hyperparameters of the CatBoost model. First, the Figma platform is analyzed in terms of its innovative design applications in rail transit. Then, the FLO algorithm is applied to optimize the CatBoost model, improving… Read full abstract & cite →

Rail transport figma platform innovation design intelligent analysis and evaluation algorithm umbrella lizard optimisation algorithm CatBoost
Abstract doi.org/10.14569/IJACSA.2024.0151149 PDF
50

Color Matching and Light and Shadow Processing in Intelligent Interior Environment Art Design Analysis and Application Based on Neural Network

Author 1: Ji Yang Author 2: Meifen Song

In recent years, the application of Virtual Reality (VR) technology in the field of interior environmental design has expanded significantly, offering designers innovative methods to present complex design concepts within virtual spaces. However, the current color matching and light and shadow processing in reality are not mature enough, and the… Read full abstract & cite →

Interior environment design color matching virtual reality neural network light and shadow processing
Abstract doi.org/10.14569/IJACSA.2024.0151150 PDF
51

Selecting the Best Machine Learning Models for Industrial Robotics with Hesitant Bipolar Fuzzy MCDM

Author 1: Chan Gu Author 2: Bo Tang

Machine learning models (MLMs) are used in industry to automate complicated activities, minimize human error, and improve decision-making by evaluating large volumes of data in real time. To managing inventory and quality control in the apparel and auto industries, they provide predictive capabilities such as predicting equipment breakdowns, maintenance and… Read full abstract & cite →

Machine Learning Model (MLM) Hesitant Bipolar Fuzzy Set (HBFS) Dual Hesitant Bipolar Fuzzy Set (DHBFS) Hesitant Bipolar Fuzzy Aggregation Operators (HBFAO) Dual Hesitant Bipolar Fuzzy Aggregation Operators (DHBFAO) Multi-Criteria Decision-Making (MCDM)
Abstract doi.org/10.14569/IJACSA.2024.0151151 PDF
52

Real-Time Data Acquisition in SCADA Systems: A JavaWeb and Swarm Intelligence-Based Optimization Framework

Author 1: Lingyi Sun Author 2: Tieliang Sun Author 3: Ruojia Xin Author 4: Feng Yan Author 5: Yue Li Author 6: Hengyu Wang Author 7: Yecen Tian Author 8: Dongqing You Author 9: Yun Liu Author 10: Muhao Lv

This paper aims to improve the accuracy and efficiency of SCADA software design and testing for oil and gas pipelines. It proposes a JavaWeb-based SCADA software solution optimized by the Bird Foraging Search (BFS) algorithm combined with an Echo State Network (ESN) for enhanced testing and analysis. A multi-tiered distributed… Read full abstract & cite →

JAVAWeb oil and gas pipelines SCADA software design analysis bird foraging search algorithm
Abstract doi.org/10.14569/IJACSA.2024.0151152 PDF
53

Cyber Resilience Model Based on a Self Supervised Anomaly Detection Approach

Author 1: Eko Budi Cahyono Author 2: Suriani Binti Mohd Sam Author 3: Noor Hafizah Binti Hassan Author 4: Amrul Faruq

Cyber resilience plays an important role in dealing with cybersecurity and business continuity uncertainty in the post-COVID-19 era. The fundamental problem of cyber resilience is the complexity of real-world problems. Therefore, it is necessary to reduce the complexity of real-world problems to be simple and easy to analyze through cyber… Read full abstract & cite →

Cybersecurity anomaly detection cyber resilience model statistical machine learning data generating process bias variance alignment likelihood ratios self-supervised learning
Abstract doi.org/10.14569/IJACSA.2024.0151153 PDF
54

Evaluation of the Optimal Features and Machine Learning Algorithms for Energy Yield Forecasting of a Rural Rooftop PV Installation

Author 1: Boris Evstatiev Author 2: Katerina Gabrovska-Evstatieva Author 3: Tsvetelina Kaneva Author 4: Nikolay Valov Author 5: Nicolay Mihailov

The stability and reliability of the electric grid strongly depend on the ability to schedule and forecast the energy output of all sources. Even though the share of photovoltaic installation in the energy mix is continuously increasing, they have one major drawback: their dependence on different environmental parameters, such as… Read full abstract & cite →

PV yield forecasting machine learning deep learning features solar radiation ambient temperature wind speed hour of the day
Abstract doi.org/10.14569/IJACSA.2024.0151154 PDF
55

Edge Computing in Water Management: A KPCA-DeepESN and HOA-Optimized Framework for Urban Resource Allocation

Author 1: Hanchao Liao Author 2: Miyuan Shan

This paper presents a novel approach to optimizing urban water resource allocation by integrating Kernel Principal Component Analysis (KPCA) with a Deep Echo State Network (DeepESN), further optimized using the Hiking Optimization Algorithm (HOA). The proposed model addresses the issue of achieving an optimal balance between water supply and demand… Read full abstract & cite →

KPCA Method water supply and demand equilibrium allocation of resources in urban water environment optimization strategy for hiking DeepESN
Abstract doi.org/10.14569/IJACSA.2024.0151155 PDF
56

Road Surface Crack Detection Based on Improved YOLOv9 Image Processing

Author 1: Quanwu Li Author 2: Shaopeng Duan

Road surface crack detection is a critical task in road maintenance and safety management. Cracks in road surfaces are often the early indicators of larger structural issues, and if not detected and repaired in time, they can lead to more severe deterioration and increased maintenance costs. Effective and timely crack… Read full abstract & cite →

Road crack YOLOv9 deep learning surveillance
Abstract doi.org/10.14569/IJACSA.2024.0151156 PDF
57

DBN-GRU Fusion and Decomposition-Optimisation-Reconstruction Algorithm in Advertising Traffic Prediction

Author 1: Ronghua Zhang

As the premise and foundation of advertisement traffic selling and distribution, effective IPTV advertisement traffic prediction not only reduces the operation cost, but also improves the intelligent level of new media advertisement traffic management. In order to further improve the accuracy of new media advertisement traffic prediction, this paper proposes… Read full abstract & cite →

New media advertising traffic prediction kernel principal component analysis variational modal decomposition quilt group algorithm deep learning decomposition-optimisation-reconstruction algorithm
Abstract doi.org/10.14569/IJACSA.2024.0151157 PDF
58

Applying Data-Driven APO Algorithms for Formative Assessment in English Language Teaching

Author 1: Guojun Zhou

This study proposes an innovative approach for improving the accuracy and efficiency of formative assessment in English language teaching. The method integrates the Artificial Protozoa Optimization (APO) algorithm with the Kernel Extreme Learning Machine (KELM) to overcome limitations such as local optima in traditional models. The study utilizes data from… Read full abstract & cite →

Big data technology APO algorithm formative assessment in English language teaching nuclear limit learning machine
Abstract doi.org/10.14569/IJACSA.2024.0151158 PDF
59

Enhancing Diabetic Retinopathy Classification Using Geometric Augmentation and MobileNetV2 on Retinal Fundus Images

Author 1: Helmi Imaduddin Author 2: Adnan Faris Naufal Author 3: Fiddin Yusfida A'la Author 4: Firmansyah

Diabetic retinopathy (DR) ranks among the foremost contributors to blindness worldwide, particularly affecting the adult demographic. Detecting DR at an early stage is crucial for preventing vision loss; however, conventional approaches like fundus examinations are often lengthy and reliant on specialized expertise. Recent developments in machine learning, especially the application… Read full abstract & cite →

Diabetic retinopathy data augmentation InceptionV3 MobileNetV2 transfer learning
Abstract doi.org/10.14569/IJACSA.2024.0151159 PDF
60

New Method in SEM Analysis Using the Apriori Algorithm to Accelerate the Goodness of Fit Model

Author 1: Dien Novita Author 2: Ermatita Author 3: Samsuryadi Author 4: Dian Palupi Rini

This research aims to develop a new method in Structural Equation Modelling (SEM) analysis using the Apriori algorithm to accelerate the achievement of Goodness of Fit models, focusing on traditional retail purchasing decision models in Indonesia, especially in Palembang. SEM will be used to model causal relationships between variables that… Read full abstract & cite →

APR-SEM method goodness of fit traditional retail
Abstract doi.org/10.14569/IJACSA.2024.0151160 PDF
61

Optimizing Energy Efficient Cloud Architectures for Edge Computing: A Comprehensive Review

Author 1: TA Gamage Author 2: Indika Perera

Now-a-days, edge computing and cloud computing are considered for collaborating together to produce computing solutions that are more effective, scalable and adaptable. The proliferation of cloud infrastructures has drastically increased energy consumption leading to the need for more research in optimizing energy efficiency for sustainable and efficient systems with reduced… Read full abstract & cite →

Cloud computing edge computing energy efficiency sustainability
Abstract doi.org/10.14569/IJACSA.2024.0151161 PDF
62

Malicious Traffic Detection Algorithm for the Internet of Things Based on Temporal Spatial Feature Fusion

Author 1: Linzhong Zhang

With the rapid development of the Internet of Things, the security issues of its network environment have gradually attracted attention. To enable faster and more accurate identification and detection of malicious traffic attacks in the Internet of Things, an optimized malicious traffic detection algorithm based on fusion of temporal and… Read full abstract & cite →

Internet of Things network security temporal-spatial characteristics traffic detection fusion algorithm
Abstract doi.org/10.14569/IJACSA.2024.0151162 PDF
63

Replace Your Mouse with Your Hand! HandMouse: A Gesture-Based Virtual Mouse System

Author 1: Qiujiao Wang Author 2: Zhijie Xie

The existing gesture-based operating systems can only simply operate a single piece of software or a specific system, and are not compatible with other applications of mainstream operating systems. In this paper, based on the MediaPipe gesture recognition framework, we design HandMouse, a virtual mouse system that operates using hand… Read full abstract & cite →

Virtual mouse ergonomics gesture MediaPipe
Abstract doi.org/10.14569/IJACSA.2024.0151163 PDF
64

Deep Learning-Based Network Security Threat Detection and Defense

Author 1: Jinjin Chao Author 2: Tian Xie

This paper introduces deepnetguard, an innovative deep learning algorithm designed to efficiently identify potential security threats in large-scale network traffic.deepnetguard achieves automated feature learning by fusing basic, statistical, and behavioral features through a multi-level feature extraction strategy, and is capable of identifying both short-time patterns and long-time dependencies. To adapt… Read full abstract & cite →

Network security threat detection defense multilevel feature extraction dynamic weight adjustment mechanism interpretability
Abstract doi.org/10.14569/IJACSA.2024.0151164 PDF
65

Development of Fuzzy Logic CRITIC Coupling Coordination Degree Evaluation Algorithm

Author 1: Fangfang Hu

The integrated development of culture and tourism in the Yangtze River Economic Belt refers to a strategic initiative to push economic development and regional coordinated development with culture and tourism as the core. The purpose of this paper is to evaluate the coupling coordination degree of the integrated development of… Read full abstract & cite →

Cultural and tourism integration Yangtze River Economic Belt coupling coordination degree CRITIC algorithm
Abstract doi.org/10.14569/IJACSA.2024.0151165 PDF
66

Performance Comparison of Pretrained Deep Learning Models for Landfill Waste Classification

Author 1: Hussein Younis Author 2: Mahmoud Obaid

The escalating challenge of waste management, particularly in developed nations, necessitates innovative approaches to enhance recycling and sorting efficiency. This study investigates the application of Convolutional Neural Networks (CNNs) for landfill waste classification, addressing the limitations of traditional sorting methods. We conducted a performance comparison of five prevalent CNN models—VGG-16… Read full abstract & cite →

Waste management deep learning waste classification real-waste dataset performance comparison
Abstract doi.org/10.14569/IJACSA.2024.0151166 PDF
67

Yolov5-Based Attention Mechanism for Gesture Recognition in Complex Environment

Author 1: Deepak Kumar Khare Author 2: Amit Bhagat Author 3: R. Vishnu Priya

Object detection is a fundamental task in gesture recognition, involving identifying and localising human hand or body gestures within images or videos amidst varying environmental conditions. To address the inadequate recognition rate of gesture detection algorithms in intricate surroundings caused by issues such as inconsistent illumination, background colors resembling skin… Read full abstract & cite →

Gesture recognition Yolov5 object detection attention mechanism bidirectional feature pyramid
Abstract doi.org/10.14569/IJACSA.2024.0151167 PDF
68

Multi-Label Aspect-Sentiment Classification on Indonesian Cosmetic Product Reviews with IndoBERT Model

Author 1: Ng Chin Mei Author 2: Sabrina Tiun Author 3: Gita Sastria

For an existing cosmetic company to expand, it is crucial to understand customers’ opinions regarding cosmetic products through product reviews. Aspect-based sentiment classification (ABSC), which consists of text representation and classification stages, is typically employed to automatically extract the interested insights from review. Existing studies of ABSC primarily used single-label… Read full abstract & cite →

Aspect-based sentiment analysis IndoBERT multi-label classification IndoBERTweet problem transformation
Abstract doi.org/10.14569/IJACSA.2024.0151168 PDF
69

CCNet: CNN CapsNet-Based Hybrid Deep Learning Model for Diagnosing Plant Diseases Using Thermal Images

Author 1: Hassan Al_Sukhni Author 2: Qusay Bsoul Author 3: Rami Hasan AL-Taani Author 4: Fadi yassin Salem Al jawazneh Author 5: Basma S. Alqadi Author 6: Misbah Mehmood Author 7: Asif Nawaz Author 8: Tariq Ali Author 9: Diaa Salama AbdElminaam

Plant disease diagnosis at an early stage enables farmers, gardeners and agricultural experts to manage and control the spread of illnesses in a timely and suitable manner. The traditional methods of plant disease diagnosis are expensive and might need significant manpower and advanced level machinery. In addition to that, conventional… Read full abstract & cite →

CapsNet classification CNN feature extraction plant disease thermal images
Abstract doi.org/10.14569/IJACSA.2024.0151169 PDF
70

A Gradient Technique-Based Adaptive Multi-Agent Cloud-Based Hybrid Optimization Algorithm

Author 1: Mohammad Nadeem Ahmed Author 2: Mohammad Rashid Hussain Author 3: Mohammad Husain Author 4: Abdulaziz M Alshahrani Author 5: Imran Mohd Khan Author 6: Arshad Ali

Efficient virtual machine (VM) movement and task scheduling are crucial for optimal resource utilization and system performance in cloud computing. This paper introduces AMS-DDPG, a novel approach combining Deep Deterministic Policy Gradient (DDPG) with Adaptive Multi-Agent strategies to enhance resource allocation. To further refine AMS-DDPG's performance, we propose ICWRS, which… Read full abstract & cite →

Adaptive multi-agent cloud-based hybrid optimization task scheduling virtual machine migration gradient technique
Abstract doi.org/10.14569/IJACSA.2024.0151170 PDF
71

Internet of Things and Cloud Computing-Based Adaptive Content Delivery in E-Learning Platforms

Author 1: Lili QIU

In recent years, cloud computing and Internet of Things (IoT) technologies have reshaped e-learning, leading to adaptive content delivery tailored to learners' needs. These paradigms have changed e-learning platforms by providing a scalable and flexible infrastructure for storing and processing large amounts of data. This enables seamless access to teaching… Read full abstract & cite →

Cloud computing Internet of Things adaptive content delivery personalized learning e-learning
Abstract doi.org/10.14569/IJACSA.2024.0151171 PDF
72

Design of a Mobile Language Learning App for Students with ADHD Using Augmented Reality

Author 1: Leonardo Paolo Cesias-Diaz Author 2: Jorge Armando Laban-Hijar Author 3: Juan Carlos Morales-Arevalo

Attention Deficit Hyperactivity Disorder, ADHD for short, impedes submission to traditional teaching as it affects cognitive abilities such as executive function skills, memorization, and focus. In this case, how will kids with ADHD learn languages? This paper provides a solution by presenting the capabilities of a mobile language learning tool… Read full abstract & cite →

ADHD augmented reality language learning technology in education mobile application design prototype
Abstract doi.org/10.14569/IJACSA.2024.0151172 PDF
73

Classification of Painting Style Based on Image Feature Extraction

Author 1: Yuting Sun

The classification of painting style can help viewers find the works they want to appreciate more conveniently, which has a very important role. This paper realized image feature extraction and classification of paintings based on ResNet50. On the basis of ResNet50, squeeze-and-excitation, and convolutional block attention module (CBAM) attention mechanisms… Read full abstract & cite →

Feature extraction painting style classification ResNet50 attention
Abstract doi.org/10.14569/IJACSA.2024.0151173 PDF
74

Application of Contrast Enhancement Method on Hip X-ray Images as a Media for Detecting Hip Osteoarthritis

Author 1: Faisal Muttaqin Author 2: Jamari Author 3: R Rizal Isnanto Author 4: Tri Indah Winarni Author 5: Athanasius Priharyoto Bayuseno

Image enhancement is one of the most important areas that is being developed in the field of image processing technology. Image contrast enhancement can significantly improve the perception of the digital image itself. X-ray images are crucial in assisting physicians in the formulation of treatment decisions based on diagnostic information… Read full abstract & cite →

X-ray image enhancement digital image image processing grayscale image
Abstract doi.org/10.14569/IJACSA.2024.0151174 PDF
75

Computer-Vision-Based Detection and Monitoring System for Mature Coconut Fruits with a Web Dashboard Visualization Platform

Author 1: Samfford S. Cabaluna Author 2: Maria Fe P. Bahinting Author 3: Leah A. Alindayo

The Philippines is the second largest producer of coconut products in the world with 347 million trees planted in 3.6 million hectares of land across the country. Traditionally, harvesting coconuts is a labor-intensive process in the Philippines that involves manual climbing and chopping fruits, which carries a high risk of… Read full abstract & cite →

Coconut fruit maturity coconut maturity detection computer vision crop monitoring
Abstract doi.org/10.14569/IJACSA.2024.0151175 PDF
76

Simulation Analysis of Intelligent Control System for Excavators in Large Mining Plants Based on Electronic Control Technology

Author 1: Lei Sun

With the increasing demand for large-scale mine equipment and the complexity of the operating environment, the intelligent trajectory planning and control of mine systems becomes very important. This paper proposes a proportional-integral-differential (PID) feedback controller combined with adaptive improvement. This controller combines Genetic Algorithm and Particle Swarm Optimization technology to… Read full abstract & cite →

Genetic Algorithm Particle Swarm Optimization proportional-integral-differential mining system intelligent control
Abstract doi.org/10.14569/IJACSA.2024.0151176 PDF
77

Predicting Graft Failure Within Year After Transplantation Using Data Mining Techniques

Author 1: Meshari Alwazae Author 2: Saad Alghamdi Author 3: Lulu Alobaid Author 4: Bader Aljaber Author 5: Reem Altwaim

The complex factors of liver transplant survival and the potential for post-transplant complications are significant challenges for healthcare professionals. This paper aims to identify the ability to use data mining techniques to develop a predictive model for liver transplant failure by identifying the relationship between abnormalities in periodic patients' laboratory… Read full abstract & cite →

Graft failure liver transplant data mining predictive model classification association rules
Abstract doi.org/10.14569/IJACSA.2024.0151177 PDF
78

Synthesizing Realistic Knee MRI Images: A VAE-GAN Approach for Enhanced Medical Data Augmentation

Author 1: Revathi S A Author 2: B Sathish Babu

This study presents a novel approach for synthesizing knee MRI images by combining Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs). By leveraging the strengths of VAEs for efficient latent space representation and GANs for their advanced image generation capabilities, we introduce a VAE-GAN hybrid model tailored specifically for medical… Read full abstract & cite →

Custom loss function decoder discriminator GAN latent space VAE
Abstract doi.org/10.14569/IJACSA.2024.0151178 PDF
79

Enhancing Mobility – An Intelligent Robot for the Visually Impaired

Author 1: Ahmad M. Bisher Author 2: Rufaida M. Shamroukh Author 3: Abed M. Shamroukh

Efficient robot navigation in operational environments requires precise tracking of the path from the starting point to the destination, typically generated using pre-stored map data. However, obstacles in the environment can complicate this process, making reliable obstacle avoidance critical for successful navigation. This paper introduces innovative techniques for robotic navigation… Read full abstract & cite →

Robot obstacle avoidance visually impaired sensors
Abstract doi.org/10.14569/IJACSA.2024.0151179 PDF
80

Face Anti-Spoofing Using Chainlets and Deep Learning

Author 1: Sarah Abdulaziz Alrethea Author 2: Adil Ahmad

Now-a-days, biometric technology is widely employed for many security purposes. Facial recognition is one of the biometric technologies that is increasingly utilized because it is convenient and contactless. However, the facial recognition system has become the most targeted by unauthorized users to get access to the system. Most facial recognition… Read full abstract & cite →

Presentation attacks Chainlets contour handcrafted features chain code CNN face anti-spoofing
Abstract doi.org/10.14569/IJACSA.2024.0151180 PDF
81

DSTC-Sum: A Supervised Video Summarization Model Using Depthwise Separable Temporal Convolutional

Author 1: M. Hamza Eissa Author 2: Hesham Farouk Author 3: Kamal Eldahshan Author 4: Amr Abozeid

The exponential growth in video content has created a critical need for efficient video summarization techniques to enable faster and more accurate information retrieval. Video summarization has excellent potential to simplify the analysis of large video databases in various application areas ranging from surveillance, education, entertainment, and research. DSTC-Sum, a… Read full abstract & cite →

Video summarization depthwise separable temporal convolutional video processing deep learning
Abstract doi.org/10.14569/IJACSA.2024.0151181 PDF
82

A Taxonomic Study: Data Placement Strategies in Cloud Replication Environments

Author 1: Fazlina Mohd Ali Author 2: Marizuana Mat Daud Author 3: Fadilla Atyka Nor Rashid Author 4: Nazhatul Hafizah Kamarudin Author 5: Syahanim Mohd Salleh Author 6: Nur Arzilawati Md Yunus

Since the past decades, the data replication trend has not subsided; it is progressing rapidly from multiple perspectives to enhance cloud replication performance. Researchers are eagerly focusing on improving the strategies in various perceptions; unfortunately, the vulnerability in every strategy is inevitable. A non-comprehensive replica strategy would have vulnerability and… Read full abstract & cite →

Cloud environment data replication placement strategies replication taxonomy performance metrics
Abstract doi.org/10.14569/IJACSA.2024.0151182 PDF
83

Optimizing House Renovation Projects Using Industrial Engineering-Based Approaches

Author 1: Lim Rou Yan Author 2: Siti Noor Asyikin Mohd Razali Author 3: Muhammad Ammar Shafi Author 4: Norazman Arbin

The persistent challenge of project delays poses significant issues with the escalating demand for house renovations. The company in Kedah, Malaysia, faces frequent project delays due to ineffective project management, leading to substantial liquidated damages. This study aims to minimise project delays and ensure timely completion within budget constraints, focusing… Read full abstract & cite →

House renovation Program Evaluation and Review Technique (PERT) Critical Path Method (CPM) project crashing techniques construction project management linear programming optimisation
Abstract doi.org/10.14569/IJACSA.2024.0151183 PDF
84

FSFYOLO: A Lightweight Model for Forest Smoke and Fire Detection

Author 1: Yinglai HUANG Author 2: Jing LIU Author 3: Liusong YANG

The detection and identification of forest smoke and fire are critical for forest fire prevention efforts. However, current forest smoke and fire target detection algorithms confront obstacles such as high memory usage, computational costs, and deployment difficulty. Regarding these key issues, this paper presents FSFYOLO, a lightweight forest smoke and… Read full abstract & cite →

Forest smoke and fire target detection lightweight YOLOv8 EfficientViT
Abstract doi.org/10.14569/IJACSA.2024.0151184 PDF
85

Identification of Chili Plant Diseases Based on Leaves Using Hyperparameter Optimization Architecture Convolutional Neural Network

Author 1: Murinto Author 2: Sri Winiarti Author 3: Ardi Pujiyanta

This paper proposes a method to detect chili plant diseases based on leaves. Studies in recent years have shown that chili production in Indonesia has decreased. This is because there are several influencing factors. One common factor is the presence of diseases in chili plants that cause less than optimal… Read full abstract & cite →

Chili leaf deep learning MobileNetV2 transfer learning VGG16
Abstract doi.org/10.14569/IJACSA.2024.0151185 PDF
86

The Application of K-MEANS Algorithm-Based Data Mining in Optimizing Marketing Strategies of Tobacco Companies

Author 1: Mingqian Ma

With the continuous development of data mining technology, more and more industries are applying data mining techniques to optimize their marketing strategies. In response to the persistent decline in tobacco sales and the gradual erosion of customer base in a particular enterprise in recent years, this study employs data mining… Read full abstract & cite →

Data mining homomorphic encryption k-means tobacco marketing strategy indicator system
Abstract doi.org/10.14569/IJACSA.2024.0151186 PDF
87

Application of Machine Learning Algorithms for Predicting Energy Consumption of Servers

Author 1: Meryeme EL YADARI Author 2: Saloua EL MOTAKI Author 3: Ali YAHYAOUY Author 4: Khalid EL FAZAZY Author 5: Hamid GUALOUS Author 6: Stéphane LE MASSON

Energy management in data centers is currently a major challenge and arouses considerable interest. Many data center operators are seeking solutions to reduce energy consumption. In this work, the problem of resource overutilization-defined as the excessive usage of critical server resources such as CPU, RAM and storage surpassing their optimal… Read full abstract & cite →

Data center server machine learning energy consumption parametric methods ensemble methods
Abstract doi.org/10.14569/IJACSA.2024.0151187 PDF
88

CQRS and Blockchain with Zero-Knowledge Proofs for Secure Multi-Agent Decision-Making

Author 1: Ayman NAIT CHERIF Author 2: Mohamed YOUSSFI Author 3: Zakariae EN-NAIMANI Author 4: Ahmed TADLAOUI Author 5: Maha SOULAMI Author 6: Omar BOUATTANE

Autonomous decision-making in decentralized multi-agent systems (MAS) poses significant challenges related to security, scalability, and privacy. This paper introduces an innovative architecture that integrates Decentralized Identifiers (DIDs), Zero-Knowledge Proofs (ZKPs), Hyperledger Fabric blockchain, OAuth 2.0 authorization, and the Command Query Responsibility Segregation (CQRS) pattern to establish a secure, scalable, and… Read full abstract & cite →

Decentralized multi-agent systems decentralized identifiers zero-knowledge proofs hyperledger fabric OAuth 2.0 CQRS smart grids healthcare data management IoT supply chain management
Abstract doi.org/10.14569/IJACSA.2024.0151188 PDF
89

An Efficient Privacy-Preserving Randomization-Based Approach for Classification Upon Encrypted Data in Outsourced Semi-Honest Environment

Author 1: Vijayendra Sanjay Gaikwad Author 2: Kishor H. Walse Author 3: Mohammad Atique Mohammad Junaid

In cloud environment context, organizations often rely on the platform for data storage and on demand access. Data is typically encrypted either by the cloud service itself or by the data owners before outsourcing it to maintain confidentiality. However, when it comes to processing encrypted data for tasks like kNN… Read full abstract & cite →

Partial homomorphic encryption classification using encrypted data randomization k- nearest neighbours
Abstract doi.org/10.14569/IJACSA.2024.0151189 PDF
90

Modeling the Impact of Robotics Learning Experience on Programming Interest Using the Structured Equation Modeling Approach

Author 1: Nazatul Aini Abd Majid Author 2: Noor Faridatul Ainun Zainal Author 3: Zarina Shukur Author 4: Mohammad Faidzul Nasrudin Author 5: Nasharuddin Zainal

Proficiency in programming is crucial for driving the Fourth Industrial Revolution. Therefore, interest in programming needs to be instilled in students starting from the school level. While the use of robotics can attract students' interest in programming, there is still a lack of research modeling, the impact of robotic learning… Read full abstract & cite →

Programming robotics Structural Equation Modeling (SEM) experiential learning student engagement
Abstract doi.org/10.14569/IJACSA.2024.0151190 PDF
91

Lampung Batik Classification Using AlexNet, EfficientNet, LeNet and MobileNet Architecture

Author 1: Rico Andrian Author 2: Rahman Taufik Author 3: Didik Kurniawan Author 4: Abbie Syeh Nahri Author 5: Hans Christian Herwanto

This study explores the application of image recognition technology based on Convolutional Neural Network (CNN) to classify Lampung batik motifs. Four CNN architectures are employed, namely AlexNet, EfficientNet, LeNet, and MobileNet. The dataset consist of ten motif classes, including Siger Ratu Agung, Sembagi, Jung Agung, Kembang Cengkih, Granitan, Abstract, Sinaran… Read full abstract & cite →

Lampung Batik image classification convolutionl neural network AlexNet EfficientNet LeNet MobileNet
Abstract doi.org/10.14569/IJACSA.2024.0151191 PDF
92

Optimization of DL Technology for Auxiliary Painting System Construction Based on FST Algorithm

Author 1: Pengpeng Xu Author 2: Guo Chen

The continuous development of computers has brought about the emergence of many image processing software, but these software have relatively limited functions and cannot learn and create works according to the prescribed style. To make it easier for ordinary people to create artistic style paintings, this study proposes the construction… Read full abstract & cite →

Finite state transducer deep learning CNN auxiliary painting style transfer
Abstract doi.org/10.14569/IJACSA.2024.0151192 PDF
93

BackC&P: Augmenting Copy and Paste Operations on Mobile Touch Devices Through Back-of-device Interaction

Author 1: Liang Chen

As more and more complex applications, e.g. photo editing software and slideshow editing software, can be used on mobile touch devices, some simple operations, such as copying and pasting, are used more frequently by ordinary mobile users. However, the existing touch techniques are far from perfectly supporting these simple operations… Read full abstract & cite →

Back-of-device interaction copy and paste operations mobile touch devices touch interaction
Abstract doi.org/10.14569/IJACSA.2024.0151193 PDF
94

A Review: PTSD in Pre-Existing Medical Condition on Social Media

Author 1: Zaber Al Hassan Ayon Author 2: Nur Hafieza Ismail Author 3: Nur Shazwani Kamarudin

Post-Traumatic Stress Disorder (PTSD) is a multifaceted mental health condition, particularly challenging for individuals with pre-existing medical conditions. This review critically examines the intersection of PTSD and chronic illnesses as expressed on social media platforms. By systematically analyzing literature from 2008 to 2024, the study explores how PTSD manifests and… Read full abstract & cite →

PTSD mental health social media natural language processing health informatics
Abstract doi.org/10.14569/IJACSA.2024.0151194 PDF
95

CIPHomeCare: A Machine Learning-Based System for Monitoring and Alerting Caregivers of Cognitive Insensitivity to Pain (CIP) Patients

Author 1: Rahaf Alsulami Author 2: Hind Bitar Author 3: Abeer Hakeem Author 4: Reem Alyoubi

Congenital Insensitivity to Pain (CIP) patients, particularly infants, are vulnerable to self-injury due to their inability to perceive pain, which can lead to severe harm, such as biting their hands. This research introduces "CIPHomeCare," a wearable monitoring solution designed to prevent self-injurious behaviors in CIP patients aged 6 to 24… Read full abstract & cite →

Cognitive insensitivity to pain patients CIP machine learning motion sensors quality of life wearable activity recognition
Abstract doi.org/10.14569/IJACSA.2024.0151195 PDF
96

A Multi-Person Collaborative Design Method Driven by Augmented Reality

Author 1: Liqun Gao

The current interior design of commercial buildings is facing innovative challenges, requiring a balance between aesthetics, functionality, and economic benefits. The design industry faces challenges in interdisciplinary integration, lack of standardized processes, and limitations of traditional design methods in complex situations. Although virtual reality technology provides new solutions, its integration… Read full abstract & cite →

Digital twin optimized design interior space multi-person collaborative design
Abstract doi.org/10.14569/IJACSA.2024.0151196 PDF
97

A Safety Detection Model for Substation Operations with Fused Contextual Information

Author 1: Bo Chen Author 2: Hongyu Zhang Author 3: Runxi Yang Author 4: Lei Zhao Author 5: Yi Ding

Detecting and regulating compliance at substation construction sites is critical to ensure the safety of workers. The complex backgrounds and diverse scenes of construction sites, as well as the variations in camera angles and distances, make the object detection models face low accuracy and missed detection problems. In addition, the… Read full abstract & cite →

Object detection context information electricity construction operation model complexity lightweight
Abstract doi.org/10.14569/IJACSA.2024.0151197 PDF
98

Preprocessing and Analysis Method of Unplanned Event Data for Flight Attendants Based on CNN-GRU

Author 1: Dongyang Li

The data of unplanned flight attendant events has characteristics such as diversity and complexity, which pose great challenges to data preprocessing and analysis. This study proposes a preprocessing and analysis method for unplanned flight attendant event data based on Convolutional Neural Networks (CNN) and Gated Recurrent Units (GRU). Firstly, an… Read full abstract & cite →

Convolutional neural network gate recurrent units air crew unplanned events data preprocessing data analysis
Abstract doi.org/10.14569/IJACSA.2024.0151198 PDF
99

CNN-BiGRU-Focus: A Hybrid Deep Learning Classifier for Sentiment and Hate Speech Analysis of Ashura-Arabic Content for Policy Makers

Author 1: Sarah Omar Alhumoud

The rise of hate speech on social media during significant cultural and religious events, such as Ashura, poses serious challenges for content moderation, particularly in languages like Arabic, which present unique linguistic complexities. Most existing hate speech detection models, primarily developed for English text, fail to effectively handle the intricacies… Read full abstract & cite →

Arabic hate speech sentiment analysis deep learning convolutional neural networks bidirectional gated recurrent unit attention mechanism social media analysis Ashura content natural language processing
Abstract doi.org/10.14569/IJACSA.2024.0151199 PDF
100

Percussion Big Data Mining and Modeling Method Based on Deep Neural Network Model

Author 1: Xi Song

In order to improve the analysis effector percussion waveform, this paper studies the percussion big data mining and modeling method based on the deep neural network model. Aiming at the problem of the high sampling rate of Analog to Digital Converter (ADC) when the wideband frequency-hopping Linear Frequency Modulation (LFM)… Read full abstract & cite →

Deep neural network percussion big data mining modeling
Abstract doi.org/10.14569/IJACSA.2024.01511100 PDF
101

Deep Image Keypoint Detection Using Cascaded Depth Separable Convolution Modules

Author 1: Rui Deng

Depth images have become an important data source for human bone keypoint detection due to their three-dimensional information. To optimize the efficiency of keypoint detection in depth images, a depth image keypoint detection model that combines cascaded depth separable convolution modules is constructed. The model first performs data cleaning and… Read full abstract & cite →

Depth image DWCA key point detection OpenPose cascade depth
Abstract doi.org/10.14569/IJACSA.2024.01511101 PDF
102

Development of a Service Robot for Hospital Environments in Rehabilitation Medicine with LiDAR-Based Simultaneous Localization and Mapping

Author 1: Sayat Ibrayev Author 2: Arman Ibrayeva Author 3: Bekzat Amanov Author 4: Serik Tolenov

This paper presents the development and evaluation of a medical service robot equipped with 3D LiDAR and advanced localization capabilities tailored for use in hospital environments. The robot employs LiDAR-based Simultaneous Localization and Mapping (SLAM) to navigate autonomously and interact effectively within complex and dynamic healthcare settings. A comparative analysis… Read full abstract & cite →

Medical service robots 3D LiDAR technology autonomous navigation hospital environments robot-assisted healthcare healthcare robotics operational reliability patient care automation
Abstract doi.org/10.14569/IJACSA.2024.01511102 PDF
103

Multi-Sensor Data Fusion Analysis for Tai Chi Action Recognition

Author 1: Jingying Ouyang Author 2: Jisheng Zhang Author 3: Yuxin Zhao Author 4: Changhuo Yang

The continuous development of action recognition technology can capture the decomposition data of Tai Chi movements, provide precise assistance for learners to correct erroneous movements and enhance their interest in practicing Tai Chi. Inertial sensors and human skeletal models are used to collect motion data. Combined with visual sensors, the… Read full abstract & cite →

Inertial sensor visual sensors segmentation clustering support vector machine dynamic time warping algorithm
Abstract doi.org/10.14569/IJACSA.2024.01511103 PDF
104

Skywatch: Advanced Machine Learning Techniques for Distinguishing UAVs from Birds in Airspace Security

Author 1: Muhyeeddin Alqaraleh Author 2: Mowafaq Salem Alzboon Author 3: Mohammad Subhi Al-Batah

This study addresses the critical challenge of distinguishing Unmanned Aerial Vehicles (UAVs) from birds in real-time for airspace security in both military and civilian contexts. As UAVs become increasingly common, advanced systems must accurately identify them in dynamic environments to ensure operational safety. We evaluated several machine learning algorithms, including… Read full abstract & cite →

Unmanned Aerial Vehicles (UAVs) machine learning image recognition real-time processing security computer vision image processing
Abstract doi.org/10.14569/IJACSA.2024.01511104 PDF
105

Design and Research of Artwork Interactive Exhibition System Based on Multi-Source Data Analysis and Augmented Reality Technology

Author 1: Xiao Chen Author 2: Qibin Wang

The current system has problems such as low efficiency of data processing, lack of smooth user experience and poor combination of display content and interactive technology, etc. There is a pressing need to optimize the integration of data analysis and augmented reality technology to improve the interactivity and visual appeal… Read full abstract & cite →

Multi-source data feature analysis augmented reality technology artwork interactive exhibition system prediction model
Abstract doi.org/10.14569/IJACSA.2024.01511105 PDF
106

Optimization of Carbon Dioxide Dense Phase Injection Model Based on DBN Deep Learning Algorithm

Author 1: Juan Zhou Author 2: Dalong Wang Author 3: Tieya Jing Author 4: Zhiwen Liu Author 5: Yihe Liang Author 6: Yaowu Nie

Carbon dioxide dense phase injection images have providing new research ideas for differential detection. Aiming at the drawbacks of large data volume, low matching efficiency, and longtime consumption of high-resolution carbon dioxide dense phase injection models, a registration algorithm for carbon dioxide dense phase injection models based on quadratic matching… Read full abstract & cite →

Supercritical CO2 DBN deep learning algorithm throttling characteristics security control dense phase injection model
Abstract doi.org/10.14569/IJACSA.2024.01511106 PDF
107

Intelligent Medical Multi-Department Information Attribute Encryption Access Control Method Under Cloud Computing

Author 1: Shubin Liao

This paper studies the encrypted access control method of smart medical multi-department information attributes in the cloud computing environment. Under the current wave of informatization, smart medical care has become an important development direction of medical services. However, the ensuing information security issues have become increasingly prominent. Especially in the… Read full abstract & cite →

Cloud computing smart medical care multi-sectoral information attribute encryption
Abstract doi.org/10.14569/IJACSA.2024.01511107 PDF
108

Application of Data Exchange Model and New Media Technology in Computer Intelligent Auxiliary Platform

Author 1: Na Li

To improve the use of computer-assisted learning, the author presents a method based on the use of new technologies. The system hardware model has a three-layer model system, including the user interface layer, the business option layer, and the data management layer. After teachers, students, and other users log in… Read full abstract & cite →

Computer intelligent assisted teaching system information exchange stress testing new media technology
Abstract doi.org/10.14569/IJACSA.2024.01511108 PDF
109

Blockchain-Enhanced Security and Efficiency for Thailand’s Health Information System

Author 1: Thattapon Surasak

This study seeks to enhance the security, efficiency, and usability of Thailand’s health information system through the integration of blockchain technology and a user-friendly web application. Blockchain’s inherent strengths in secure data stor-age and sharing make it particularly well-suited for addressing the critical challenges of healthcare data management. Currently, Thai… Read full abstract & cite →

Blockchain technology healthcare information system Electronic Medical Records (EMRs) user experience (UX) testing web application data security
Abstract doi.org/10.14569/IJACSA.2024.01511109 PDF
110

Automatic Generation of Comparison Charts of Similar GitHub Repositories from Readme Files

Author 1: Emad Albassam

GitHub is a widely used platform for hosting open-source projects, with over 420 million repositories, promoting code sharing and reusability. However, with this tremendous number of repositories, finding a desirable repository based on user needs takes time and effort, especially as the number of candidate repositories increases. A user search… Read full abstract & cite →

Multi-class classification keyword-driven classification rule-based classification unsupervised classification GitHub repositories comparison charts
Abstract doi.org/10.14569/IJACSA.2024.01511110 PDF
111

An Ontology-Based Intelligent Interactive Knowledge Interface for Groundnut Crop Information

Author 1: Purvi H. Bhensdadia Author 2: C. K. Bhensdadia

This paper presents an ontology-based interactive interface designed to provide farmers in Gujarat with information related to groundnut crops. An ontology specific to the groundnut crop was developed and used to create a semantic question-answering (QA) interface. The proposed QA interface converts natural language question into SPARQL Query and provides… Read full abstract & cite →

Agriculture ontology; ontology construction; question answer system; groundnut ontology
Abstract doi.org/10.14569/IJACSA.2024.01511111 PDF
112

Leveraging Semi-Supervised Generative Adversarial Networks to Address Data Scarcity Using Decision Boundary Analysis

Author 1: Mohamed Ouriha Author 2: Omar El Mansouri Author 3: Younes Wadiai Author 4: Boujamaa Nassiri Author 5: Youssef El Mourabit Author 6: Youssef El Habouz

Convolutional Neural Networks (CNNs) are widely regarded as one of the most effective solutions for image classification. However, developing high-performing systems with these models typically requires a substantial number of labeled images, which can be difficult to acquire. In image classification tasks, insufficient data often leads to overfitting, a critical… Read full abstract & cite →

Decision boundary convolutional neural network Generative Adversarial Networks MNIST classification semi-supervised classification
Abstract doi.org/10.14569/IJACSA.2024.01511112 PDF
113

Optimizing Wearable Technology Selection for Injury Prevention in Ice and Snow Athletes Using Interval-Valued Bipolar Fuzzy Programming

Author 1: Aichen Li

The growing importance of wearable technology in ice and snow sports highlights its role in injury prevention, where environmental hazards elevate injury risks. To address this, we propose a decision-making model using interval-valued bipolar fuzzy programming (IVBFP) for the optimal selection of wearable devices focused on athlete safety. The model… Read full abstract & cite →

Wearable technology injury prevention Interval-Valued Bipolar Fuzzy Programming (IVBFP) Multi-Criteria Decision-Making (MCDM) fuzzy logic real-time monitoring
Abstract doi.org/10.14569/IJACSA.2024.01511113 PDF
114

LRSA-Hybrid Encryption Method Using Linear Cipher and RSA Algorithm to Conceal the Text Messages

Author 1: Rundan Zheng Author 2: Chai Wen Chuah Author 3: Janaka Alawatugoda

Computer science and telecommunications technologies have been experiencing rapid advancements in recent years to protect sensitive data or information from potential harm, misuse, or destruction. By enhancing data security through various methodologies and algorithms, data can be better protected against attacks that may compromise its confidentiality, particularly in the case… Read full abstract & cite →

Confidentiality data encryption hybrid encryption linear cipher RSA algorithm Gradatim LRSA Optimized LRSA
Abstract doi.org/10.14569/IJACSA.2024.01511114 PDF
115

Enterprise Architecture Framework Selection for Collaborative Freight Transportation Digitalization: A Hybrid FAHP-FTOPSIS Approach

Author 1: Abdelghani Saoud Author 2: Adil Bellabdaoui Author 3: Mohamed Lachgar Author 4: Mohamed Hanine Author 5: Imran Ashraf

Collaborative freight transportation plays a crucial role for Logistic Service Providers (LSPs) seeking to enhance profitability and service quality, yet it faces challenges at strategic, operational, and technical levels. Digital transformation creates opportunities to overcome these hurdles by extending collaboration beyond physical logistics to encompass information management and digital transformation… Read full abstract & cite →

Digital transformation freight transportation enterprise architecture multi-criteria decision-making analytic hierarchy process fuzzy technique for order of preference by similarity to ideal solution
Abstract doi.org/10.14569/IJACSA.2024.01511115 PDF
116

ATG-Net: Improved Feature Pyramid Network for Aerial Object Detection

Author 1: Junbao Zheng Author 2: ChangHui Yang Author 3: Jiangsheng Gui

Object detection in aerial images is gradually gaining wide attention and application. However, given the prevalence of numerous small objects in the Unmanned Aerial Vehicle (UAV) aerial images, the extraction of superior fusion features is critical for the detection of small objects. However, feature fusion in many detectors does not… Read full abstract & cite →

Object detection feature pyramid network adaptive tri-layer weighting triple feature encoding global attention mechanism
Abstract doi.org/10.14569/IJACSA.2024.01511116 PDF
117

Deep Learning Classification of Gait Disorders in Neurodegenerative Diseases Among Older Adults Using ResNet-50

Author 1: K. A. Rahman Author 2: E. F. Shair Author 3: A. R. Abdullah Author 4: T. H. Lee Author 5: N. H. Nazmi

Gait disorders in older adults, particularly those associated with neurodegenerative diseases such as Parkinson’s Disease, Huntington’s Disease, and Amyotrophic Lateral Sclerosis , present significant diagnostic challenges. Since these NDDs primarily affect older adults, it is crucial to focus on this population to improve early detection and intervention. This study aimed… Read full abstract & cite →

Gait disorders neurodegenerative diseases deep learning vertical Ground Reaction Force (vGRF) ResNet-50
Abstract doi.org/10.14569/IJACSA.2024.01511117 PDF
118

How Predictable are Fitness Landscapes with Machine Learning? A Traveling Salesman Ruggedness Study

Author 1: Mohammed El Amrani Author 2: Khaoula Bouanane Author 3: Youssef Benadada

The notion of fitness landscape (FL) has shown promise in terms of optimization. In this paper we propose a machine learning (ML) prediction approach to quantify FL ruggedness by computing the entropy. The approach aims to build a model that could reveal information about the ruggedness of unseen instances. Its… Read full abstract & cite →

Fitness landscape analysis optimization algorithms machine learning landscape ruggedness traveling salesman problem
Abstract doi.org/10.14569/IJACSA.2024.01511118 PDF
119

Analyzing EEG Patterns in Functional Food Consumption: The Role of PCA in Decision-Making Processes

Author 1: Mauro Daniel Castillo P´erez Author 2: Jes´us Jaime Moreno Escobar Author 3: Ver´onica de Jes´us P´erez Franco Author 4: Ana Lilia Coria Pa´ez Author 5: Oswaldo Morales Matamoros

The impact of obesity and diabetes are two central reasons for the high rate of developing cardiovascular diseases in this country, which is largely due to their ultra-processed, diet-rich foods. Supervised Learning for Decision Making: A Case Study of Functional Food Taste Perceptions In this experiment, we trained ordinary consumers… Read full abstract & cite →

EEG analysis functional foods decision-making deep learning and Principal Component Analysis (PCA)
Abstract doi.org/10.14569/IJACSA.2024.01511119 PDF
120

Learning Local Reconstruction Errors for Face Forgery Detection

Author 1: Haoyu Wu Author 2: Lingyun Leng Author 3: Peipeng Yu

Although several deepfake detection technologies have achieved great detection accuracy inside the data domain in recent years, there are still limitations in cross-domain generalization. This is due to the model’s ease of fitting the data sample distribution in the training data domain and its tendency to detect a specific forgery… Read full abstract & cite →

Face forgery deepfake detection local anomalies generalized detection
Abstract doi.org/10.14569/IJACSA.2024.01511120 PDF
121

Integrated Detection and Tracking Framework for 3D Multi-Object Tracking in Vehicle-Infrastructure Cooperation

Author 1: Tao Hu Author 2: Ping Wang Author 3: Xinhong Wang

Vehicle-infrastructure cooperative perception has emerged as a promising approach to enhance 3D multi-object tracking by leveraging complementary data from vehicle and infrastructure sensors. However, existing methods face significant challenges, including difficulty in handling occlusions, suboptimal identity association, and inefficiencies in trajectory management, limiting their performance in real-world scenarios. In this… Read full abstract & cite →

Vehicle-infrastructure cooperative perception 3D multi-object tracking XIOU metric four-stage cascade matching integrated detection-tracking framework
Abstract doi.org/10.14569/IJACSA.2024.01511121 PDF
122

A Robust Model for a Healthcare System with Chunk Based RAID Encryption in a Multitenant Blockchain Network

Author 1: Bharath Babu S Author 2: Jothi K R

Healthcare informatics has revolutionized data extraction from large datasets. However, using analytics while protecting sensitive healthcare data is a major challenge. A novel methodology for Privacy-Preserving Analytics in Healthcare Records addresses this essential issue in this study. The multi-tenant Blockchain framework uses chunk-based RAID encryption. For the healthcare business, chunk-based… Read full abstract & cite →

Multi-tenant chunk-based RAID blockchain healthcare records
Abstract doi.org/10.14569/IJACSA.2024.01511122 PDF
123

Enhanced Adaptive Hybrid Convolutional Transformer Network for Malware Detection in IoT

Author 1: Abdulaleem Ali Almazroi

Many university networks use IoT devices, which increases vulnerability and malware threats. The complex, multi-dimensional structure of IoT network traffic and the imbalance between benign and dangerous data make traditional malware detection techniques ineffective. The Adaptive Hybrid Convolutional Transformer Network (AHCTN) is a novel model that uses CNNs for spatial… Read full abstract & cite →

IoT security malware detection convolutional transformer network cybersecurity machine learning network anomaly detection
Abstract doi.org/10.14569/IJACSA.2024.01511123 PDF
124

Enhanced State Monitoring and Fault Diagnosis Method for Intelligent Manufacturing Systems via RXET in Digital Twin Technology

Author 1: Min Li

To maintain efficiency and continuity in Industry 4.0, intelligent manufacturing systems use enhanced problem detection and condition monitoring. Existing models typically miss uncommon and essential errors, causing expensive downtimes and lost production. ResXEffNet-Transformer (RXET), a hybrid deep learning model, improves defect identification and pre-dictive maintenance by integrating ResNet, Xception, Efficient-Net… Read full abstract & cite →

RXET fault diagnosis intelligent manufacturing transformer-based attention predictive maintenance deep learning
Abstract doi.org/10.14569/IJACSA.2024.01511124 PDF
125

Recognizing Multi-Intent Commands of the Virtual Assistant with Low-Resource Languages

Author 1: Van-Vinh Nguyen Author 2: Ha Nguyen-Tien Author 3: Anh-Quan Nguyen-Duc Author 4: Trung-Kien Vu Author 5: Cong Pham-Chi Author 6: Minh-Hieu Pham

Virtual Assistants (VAs) are widely used in many fields. Recently, VAs have been effectively applied in technical drawing tasks, such as in Photoshop and Microsoft Word. Understanding multi-intent commands in VAs poses a significant challenge, especially when the language in query is low-resource, like Vietnamese (no training dataset available for… Read full abstract & cite →

Vietnamese command corpus chatbot virtual assistants multi-intent command artificial intelligence technical drawing SCADA framework build semi-automatic data low-resource languages
Abstract doi.org/10.14569/IJACSA.2024.01511125 PDF
126

AudioMag: A Hybrid Audio Protection Scheme in Multilevel DWT-DCT-SVD Transformations for Data Hiding

Author 1: Jingjin Yu Author 2: Chai Wen Chuah Author 3: Rundan Zheng Author 4: Janaka Alawatugoda

Steganography is a technique used to hide data within an image or audio in order to maintain the secrecy of the message being communicated. There are several methods used in steganography to achieve this, but commonly, the data hiding is between the same stegoentity, such as an image with an… Read full abstract & cite →

Steganography image steganography audio steganography data hiding stegoentity
Abstract doi.org/10.14569/IJACSA.2024.01511126 PDF
127

Using Hybrid Compact Transformer for COVID-19 Detection from Chest X-Ray

Author 1: Ghadeer Almoeili Author 2: Abdenour Bounsiar

By the end of December 2019, the novel coronavirus 2019 (COVID-2019), became a world pandemic affecting the respiratory system. Scientists started investigating using Deep Learning and Convolutional Neural Networks (CNNs) to detect COVID-19 using Chest X-rays (CXRs). One of the main difficulties researchers reported in the detection of lung diseases… Read full abstract & cite →

Deep convolutional neural network CXR chest X-Ray COVID-19 pneumonia vision transformers compact convolutional transformer hybrid compact transformer
Abstract doi.org/10.14569/IJACSA.2024.01511127 PDF
128

AI-Blockchain Approach for MQTT Security: A Supply Chain Case Study

Author 1: Raouya AKNIN Author 2: Hind El Makhtoum Author 3: Youssef Bentaleb

The use of the MQTT protocol in critical sectors such as healthcare and industry has prompted research to propose solutions for strengthening its security and preventing it from attacks that are growing exponentially and becoming increasingly sophisticated and difficult to detect. This paper aims to improve the security of the… Read full abstract & cite →

IoT MQTT blockchain smart contracts AI hybrid model device reputation
Abstract doi.org/10.14569/IJACSA.2024.01511128 PDF
129

Optimized SMS Spam Detection Using SVM-DistilBERT and Voting Classifier: A Comparative Study on the Impact of Lemmatization

Author 1: Sinar Nadhif Ilyasa Author 2: Alaa Omar Khadidos

The rapid growth of digital communication has led to a surge in spam messages, particularly through Short Message Service (SMS). These unsolicited messages pose risks such as phishing and malware, necessitating robust detection mechanisms. This study focuses on a comparative analysis of machine learning models for SMS spam detection, with… Read full abstract & cite →

SMS spam detection Support Vector Machine (SVM) DistilBERT hyperparameter optimization LIME
Abstract doi.org/10.14569/IJACSA.2024.01511129 PDF
130

A Machine Learning Approach to pH Monitoring: Mango Leaf Colorimetry in Aquaculture

Author 1: Hajar Rastegari Author 2: Romi Fadilah Rahmat Author 3: Farhad Nadi

Maintaining optimal water quality is crucial for successful aquaculture. This necessitates careful management of various water quality parameters, including pH levels within their ideal range. There is growing interest in creating affordable optical pH sensors that provide accurate readings across a wide range of pH values. Development of sensors that… Read full abstract & cite →

Aquaculture machine learning XGboost water quality sustainable aquaculture practices water quality monitoring mango leaf extract
Abstract doi.org/10.14569/IJACSA.2024.01511130 PDF
131

Unveiling Hidden Variables in Adversarial Attack Transferability on Pre-Trained Models for COVID-19 Diagnosis

Author 1: Dua’a Akhtom Author 2: Manmeet Mahinderjit Singh Author 3: Chew XinYing

Adversarial attacks represent a significant threat to the robustness and reliability of deep learning models, particularly in high-stakes domains such as medical diagnostics. Advanced Persistent Threat (APT) attacks, characterized by their stealth, complexity, and persistence, exploit adversarial examples to undermine the integrity of AI-driven healthcare systems, posing severe risks to… Read full abstract & cite →

Adversarial attack advanced persistent threat pre-trained model robust DL transferable attack
Abstract doi.org/10.14569/IJACSA.2024.01511131 PDF
132

Image Information Hiding Processing Based on Deep Neural Network Algorithm

Author 1: Zhe Zhang

In order to more effectively hide and extract image information, a deep neural network-based algorithm and computer-aided image information hiding method is proposed. The hardware design of the system includes the selection of the main control chip, the design of the parallel processing structure, and the design of the Ethernet… Read full abstract & cite →

Image information hiding neural networks system design image acquisition information processing
Abstract doi.org/10.14569/IJACSA.2024.01511132 PDF
133

Intelligent Digital Virtual Clothing Display System Based on LDA Mathematical Model

Author 1: Zhao Wu Author 2: Qingyuan He

In order to understand the intelligent digital virtual clothing display system based on mathematical models, the author proposes a research on an intelligent digital virtual clothing display system based on LDA mathematical models. The author first analyzes the realization of clothing matching function, and selects the cooperation between human skin… Read full abstract & cite →

Mathematical model virtual technology clothing display
Abstract doi.org/10.14569/IJACSA.2024.01511133 PDF
134

Enhancing Alzheimer's Detection: Leveraging ADNI Data and Large Language Models for High-Accuracy Diagnosis

Author 1: Hassan Almalki Author 2: Alaa O. Khadidos Author 3: Nawaf Alhebaishi

Alzheimer's disease (AD), the most common type of dementia, is expected to affect 152 million people by 2050, emphasizing the importance of early diagnosis. This study uses the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, combining cognitive tests, biomarkers, demographic details, and genetic data to build predictive models. Using large language… Read full abstract & cite →

Alzheimer dementia LLMs ChatGPT LSTM
Abstract doi.org/10.14569/IJACSA.2024.01511134 PDF
135

Visual Recognition and Localization of Industrial Robots Based on SLAM Algorithm

Author 1: Wei Cui Author 2: Yuefan Zhao Author 3: Litao Sun

The front-end feature matching module of traditional SLAM systems is characterized by sparse or dense feature points, it is difficult to generate accurate camera trajectory and scene reconstruction results, in response to this problem, the author studied a fast reconstruction algorithm for any path based on V-SLAM, by using improved… Read full abstract & cite →

SLAM algorithm industrial robot visual recognition location
Abstract doi.org/10.14569/IJACSA.2024.01511135 PDF
136

Optimizing Threat Intelligence Strategies for Cybersecurity Awareness Using MADM and Hybrid GraphNet-Bipolar Fuzzy Rough Sets

Author 1: Qian Zhang

Advanced threat detection systems are needed more than ever as cyber-attacks become more advanced. A novel cybersecurity model uses Bipolar Fuzzy Rough Sets, Graph Neural Networks, and dense network (BFRGD-Net) architectures to identify threats with unmatched accuracy and speed. The approach optimizes threat detection using Dynamic Range Realignment, anomaly-driven feature… Read full abstract & cite →

Cybersecurity awareness threat intelligence MADM framework BFRGD-Net hybrid model deep learning
Abstract doi.org/10.14569/IJACSA.2024.01511136 PDF
IJACSA Journal Cover

Important Dates

Volume 17 No. 11, November 2026
Paper Submission Due October 25, 2026
Review Notification November 15, 2026
Publication Date November 30, 2026
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IJACSA