IJACSA Vol. 16 Issue 4 (2025)

1

Augmented Sensory Experience and Retention: ASER Framework

Author 1: Samer Alhebaishi Author 2: Richard Stone

In the process of shifting from traditional teacher-centred systems to more student-engagement ones, Augmented Reality (AR) is coming into its own as a way of improving how information is delivered and received. However, while the use of AR is commonly attributed to increasing engagement, the potential of this technology to… Read full abstract & cite →

Augmented Reality (AR) emotional memory inter-active storytelling gamification Augmented Sensory Experience and Retention (ASER) Framework

Abstract doi.org/10.14569/IJACSA.2025.0160401 PDF

2

Comparing Vision-Instruct LLMs, Vision-Based Deep Learning, and Numeric Models for Stock Movement Prediction

Author 1: Qizhao Chen

This research conducts a comparative study of several stock movement prediction approaches, evaluating large language models (LLMs) and vision-based deep learning models with stock image as input, as well as models that utilize numerical data. Specifically, the study investigates a prompt-based LLM framework that processes candlestick charts, comparing its performance… Read full abstract & cite →

Convolutional Neural Network (CNN) Large Language Model (LLM) MobileNetV2 stock price prediction time series forecasting vision transformer

Abstract doi.org/10.14569/IJACSA.2025.0160402 PDF

3

Applications of Qhali-Bot in Psychological Assistance and Promotion of Well-being: A Systematic Review

Author 1: Sebastián Ramos-Cosi Author 2: Daniel Yupanqui-Lorenzo Author 3: Enrique Huamani-Uriarte Author 4: Meyluz Paico-Campos Author 5: Victor Romero-Alva Author 6: Claudia Marrujo-Ingunza Author 7: Alicia Alva-Mantari Author 8: Linett Velasquez-Jimenez

Social robots have emerged as efficient tools in the field of psychological assistance and well-being promotion, especially known as Qhalibot in prominent areas such as mental health, education and work environments. The aim of this study is to provide a comprehensive overview of their application in these contexts, through a… Read full abstract & cite →

Qhalibot robot psychological assistance well-being review

Abstract doi.org/10.14569/IJACSA.2025.0160403 PDF

4

Level of Anxiety and Knowledge About Breastfeeding in First-Time Mothers with Children Under Six Months

Author 1: Frank Valverde-De La Cruz Author 2: Maria Valverde-Ccerhuayo Author 3: Ana Huamani-Huaracca Author 4: Gina León-Untiveros Author 5: Sebastián Ramos-Cosi Author 6: Alicia Alva-Mantari

The World Health Organization notes that one in five women of reproductive age faces episodes of anxiety. In Latin America, more than 50% of women experience postnatal anxiety, and in Peru, in Huánuco, 40% of first-time mothers have moderate anxiety. The aim of this study is to analyze the relationship… Read full abstract & cite →

Anxiety knowledge breastfeeding first-time mothers children

Abstract doi.org/10.14569/IJACSA.2025.0160404 PDF

5

Economic Growth and Fiscal Policy in Peru: Prediction Using Machine Learning Models

Author 1: Fidel Huanco Ramos Author 2: Yesenia Valentin Ccori Author 3: Henry Shuta Lloclla Author 4: Martha Yucra Sotomayor Author 5: Ilda Mamani Uchasara

The empirical literature presents several indicators related to fiscal policy and economic growth. The paper aims to predict Peru's economic growth using fiscal policy variables. For this purpose, open data from the Central Reserve Bank of Peru was used, data preprocessing and the study used Python programming through Google Colab… Read full abstract & cite →

Machine learning predictive models fiscal policy economic growth

Abstract doi.org/10.14569/IJACSA.2025.0160405 PDF

6

Evaluating User Acceptance and Usability of AR-Based Indoor Navigation in a University Setting: An Empirical Study

Author 1: Toma Marian-Vladut Author 2: Turcu Corneliu Octavian Author 3: Pascu Paul

This paper presents the development and usability evaluation of a mobile augmented reality (AR) application designed to support indoor navigation within a higher education setting. The system offers real-time visual and audio guidance without requiring additional infrastructure, leveraging spatial anchors, QR code initialization, and compatibility with both ARCore and ARKit… Read full abstract & cite →

Augmented reality indoor navigation mobile application usability evaluation ARCore higher education spatial computing

Abstract doi.org/10.14569/IJACSA.2025.0160406 PDF

7

A Hybrid Length-Based Pattern Matching Algorithm for Text Searching

Author 1: Victor Cornejo-Aparicio Author 2: Cesar Cuarite-Silva Author 3: Antoni Benavente-Mayta Author 4: Karim Guevara

This paper presents a hybrid algorithm for pattern matching in text, which combines word length preprocessing with the Knuth-Morris-Pratt (KMP) algorithm. Its performance was evaluated against KMP and Boyer-Moore (BM) in two scenarios: synthetic texts and real-world texts. In the former, classical algorithms proved more efficient due to the uniform… Read full abstract & cite →

Knuth-Morris-Pratt Boyer-Moore text search hybrid algorithm preprocessing word-length patterns test text for experiments

Abstract doi.org/10.14569/IJACSA.2025.0160407 PDF

8

Pothole Detection: A Study of Ensemble Learning and Decision Framework

Author 1: Ken D. Gorro Author 2: Elmo B. Ranolo Author 3: Anthony S. Ilano Author 4: Deofel P. Balijon

This study investigates the potential use of ensemble learning (YOLOv9 and Mask R-CNN) and Multi-Criteria Decision Making for pothole detection system. A series of experiments were conducted, including variations in confidence thresholds, IoU thresholds, dynamic weight configurations, camera angles and MCDM criteria, to assess their effects on detection performance. The… Read full abstract & cite →

YOLO Mask R-CNN ensemble learning MCDM

Abstract doi.org/10.14569/IJACSA.2025.0160408 PDF

9

Approach Detection and Warning Using BLE and Image Recognition at Construction Sites

Author 1: Yuya Ifuku Author 2: Kohei Arai Author 3: Mariko Oda

Ensuring the safety of workers in dangerous areas is an important issue at construction sites. In particular, fatal accidents at construction sites often involve falls or traffic accidents, and tend to occur around hazardous areas. In this paper, to prevent such accidents, a proximity detection and warning system based on… Read full abstract & cite →

Construction site safety management intrusion detection object recognition trajectory tracking YOLOv8 ByteTrack BLE Beacon

Abstract doi.org/10.14569/IJACSA.2025.0160409 PDF

10

Flexible Software Architecture for Genetic Data Processing in Alpaca Breeding Programs

Author 1: Alfredo Gama-Zapata Author 2: Fernando Barra-Quipse Author 3: Elizabeth Vidal

Improving alpaca fiber quality is an important objective in the textile industry. There are different kinds of techniques aimed to enhance breeding outcomes. This study proposes and validates a flexible software architecture for managing genetic information in alpaca breeding, integrating genomic selection methods. The proposed architecture consists of three components… Read full abstract & cite →

Architecture genomic selection adaptability

Abstract doi.org/10.14569/IJACSA.2025.0160410 PDF

11

Method for Providing Exercise Instruction That Allows Immediate Feedback to Trainees

Author 1: Kohei Arai Author 2: Kosuke Eto Author 3: Mariko Oda

Method for providing exercise instruction that allows immediate feedback to trainees is proposed. The purpose of this research is to combine artificial intelligence technology and motion analysis methods to build an effective vocational training support program aimed at supporting the employment of children with disabilities. Specifically, we develop a system… Read full abstract & cite →

Motion training immediate feedback DTW (Dynamic Time Warping) children with disabilities skeletal detection

Abstract doi.org/10.14569/IJACSA.2025.0160411 PDF

12

Fear of Missing Out (FoMO) and Recommendation Algorithms: Analyzing Their Impact on Repurchase Intentions in Online Marketplaces

Author 1: Ati Mustikasari Author 2: Ratih Hurriyati Author 3: Puspo Dewi Dirgantari Author 4: Mokh Adieb Sultan Author 5: Neng Susi Susilawati Sugiana

The rapid growth of e-commerce has intensified consumers' Fear of Missing Out (FoMO), influencing their repurchase intentions. This study aims to examine the impact of online FoMO on repurchase intentions in marketplaces, emphasizing the role of personalized recommendations and promotional strategies. A quantitative approach was employed, collecting data from 300… Read full abstract & cite →

Component FoMO repurchase intentions online marketplace SEM consumer behavior

Abstract doi.org/10.14569/IJACSA.2025.0160412 PDF

13

A Hybrid SEM-ANN Method for Developing an Information Technology Acceptance and Utilization Model in River Tourism Services

Author 1: Mutia Maulida Author 2: Iphan Fitrian Radam Author 3: Nurul Fathanah Mustamin Author 4: Yuslena Sari Author 5: Andreyan Rizky Baskara Author 6: Eka Setya Wijaya Author 7: Muhammad Alkaff Author 8: M. Renald Abdi

Tourism is a vital sector that contributes significantly to Indonesia's economic growth. However, despite its great potential, the sector faces challenges in the application of information technology, as seen in the Go-Klotok application in Banjarmasin City which has not been well received by tourists. Therefore, it is important to understand… Read full abstract & cite →

River tourism technology acceptance TWAM E-TAM hybrid SEM-ANN

Abstract doi.org/10.14569/IJACSA.2025.0160413 PDF

14

Mitigating Catastrophic Forgetting in Continual Learning Using the Gradient-Based Approach: A Literature Review

Author 1: Haitham Ghallab Author 2: Mona Nasr Author 3: Hanan Fahmy

Continual learning, also referred to as lifelong learning, has emerged as a significant advancement for model adaptation and generalization in deep learning with the capability to train models sequentially from a continuous stream of data across multiple tasks while retaining previously acquired knowledge. Continual learning is used to build powerful… Read full abstract & cite →

Deep learning continual learning model adaptation and generalization catastrophic forgetting gradient-based approach

Abstract doi.org/10.14569/IJACSA.2025.0160414 PDF

15

IoT-Enabled Waste Management in Smart Cities: A Systematic Literature Review

Author 1: Moulay Lakbir Tahiri Alaoui Author 2: Meryam Belhiah Author 3: Soumia Ziti

The growing population of cities has increased the pressure on the waste management systems and therefore, new and better approaches are needed. This paper aims to present the theoretical underpinning of the application of Internet of Things (IoT) technologies in the improvement of waste collection in smart cities. In this… Read full abstract & cite →

Waste management smart cities Internet of Things (IoT) smart bins urban planning

Abstract doi.org/10.14569/IJACSA.2025.0160415 PDF

16

Wireless Internet of Things System Optimization Based on Clustering Algorithm in Big Data Mining

Author 1: Jing Guo

The rapid development of the Internet of Things (IoT) has highlighted the importance of Wi-Fi sensor networks in efficiently collecting data anytime and anywhere. This paper aims to propose an optimized routing protocol that significantly reduces power consumption in IoT systems based on clustering algorithms. The paper begins by introducing… Read full abstract & cite →

Wireless sensor network routing protocol clustering algorithm two-layer clustering Internet of Things

Abstract doi.org/10.14569/IJACSA.2025.0160416 PDF

17

Hybrid-Optimized Model for Deepfake Detection

Author 1: H. Mancy Author 2: Marwa Elpeltagy Author 3: Kamal Eldahshan Author 4: Aya Ismail

The advancement of deep learning models has led to the creation of novel techniques for image and video synthesis. One such technique is the deepfake, which swaps faces among persons and then produces hyper-realistic videos of individuals saying or doing things that they never said or done. These deepfake videos… Read full abstract & cite →

Bayesian optimization deepfake detection deepfake videos Mask R-CNN Xception network XGBoost

Abstract doi.org/10.14569/IJACSA.2025.0160417 PDF

18

Enhancing Usability and Cognitive Engagement in Elderly Products Through Brain-Computer Interface Technologies

Author 1: Daijiao Shi Author 2: Chao Jiang Author 3: Chenhan Huang

This study addresses the limitations of traditional elderly care products in terms of intelligence and user experience by integrating human-computer interaction (HCI) principles into a product design framework for the elderly. This study explores the importance of feature extraction in human-computer interaction systems, emphasizes its key role in enhancing user… Read full abstract & cite →

Big data human-computer interaction the elderly product design

Abstract doi.org/10.14569/IJACSA.2025.0160418 PDF

19

Analyzing RGB and HSV Color Spaces for Non- Invasive Blood Glucose Level Estimation Using Fingertip Imaging

Author 1: Asawari Kedar Chinchanikar Author 2: Manisha P. Dale

Traditional blood glucose measurement methods, including finger-prick tests and intravenous sampling, are invasive and can cause discomfort, leading to reduced adherence and stress. Non-invasive BGL estimation addresses these issues effectively. The proposed study focuses on estimating blood glucose levels (BGL) using “Red-Green-Blue (RGB)” and “Hue-Saturation-Value (HSV) color spaces” by analyzing… Read full abstract & cite →

Blood glucose Photoplethysmography non- invasive genetic algorithm XGBoost RGB HSV

Abstract doi.org/10.14569/IJACSA.2025.0160419 PDF

20

Machine Learning Advances in Technology Applications: Cultural Heritage Tourism Trends in Experience Design

Author 1: Meihua Deng

This study investigates the evolving trends in cultural heritage tourism experience design and examines how machine learning technologies are being applied to enhance visitor engagement and heritage preservation. Using bibliometric data from the Web of Science (WoS) and visualization tools such as VOSviewer, the research identifies key themes, author collaborations… Read full abstract & cite →

Heritage tourism tourism experience machine learning VOSviewer bibliometric data

Abstract doi.org/10.14569/IJACSA.2025.0160420 PDF

21

Netizens as Readers, Producers, and Publishers: Communication Ethics and Challenges in Social Media

Author 1: Burhanuddin Arafah Author 2: Muhammad Hasyim Author 3: Herawati Abbas

Social media has fundamentally transformed how people communicate and interact, creating a dynamic landscape where today's internet users assume multifaceted roles as readers, producers of text (messages), and publishers of their own content. This evolution empowers individuals to consume information and generate it, offer commentary, and share it widely across… Read full abstract & cite →

Netizen communication ethic challenge social media

Abstract doi.org/10.14569/IJACSA.2025.0160421 PDF

22

Meter-YOLOv8n: A Lightweight and Efficient Algorithm for Word-Wheel Water Meter Reading Recognition

Author 1: Shichao Qiao Author 2: Yuying Yuan Author 3: Ruijie Qi

To address the issues of low efficiency and large parameters in the current word-wheel water meter reading recognition algorithms, this paper proposes a Meter-YOLOv8n algorithm based on YOLOv8n. Firstly, the C2f component of YOLOv8n is improved by introducing an enhanced inverted residual mobile block (iRMB). It enables the model to… Read full abstract & cite →

Word-wheel water meter YOLOv8n global features slim-neck loss function

Abstract doi.org/10.14569/IJACSA.2025.0160422 PDF

23

Optimization Design of Robot Grasping Based on Lightweight YOLOv6 and Multidimensional Attention

Author 1: Junyan Niu Author 2: Guanfang Liu

To address the computational redundancy and robustness limitations of industrial grasping models in complex environments, this study proposes a lightweight capture detection framework integrating Mobile Vision Transformer (MobileViT) and You Only Look Once version 6 (YOLOv6). Three innovations are developed: 1) A cascaded architecture fusing convolution and Transformer to compress… Read full abstract & cite →

Capture detection YOLOv6 multidimensional attention MobileViT industrial robot lightweight

Abstract doi.org/10.14569/IJACSA.2025.0160423 PDF

24

Intellectual Property Protection in the Age of AI: From Perspective of Deep Learning Models

Author 1: Jing Li Author 2: Quanwei Huang

The rapid development of Artificial Intelligence (AI), especially Deep Learning (DL) technologies, has brought unprecedented challenges and opportunities for Intellectual Property (IP) protection and management. In this paper, we employ Bibliometrix and Biblioshiny to conduct a bibliometric analysis of global research at the intersection of AI-driven innovation and IP frameworks… Read full abstract & cite →

Intellectual property Artificial Intelligence Deep Learning Natural Language Processing neural network legal applicability

Abstract doi.org/10.14569/IJACSA.2025.0160424 PDF

25

Photovoltaic Fault Detection in Remote Areas Using Fuzzy-Based Multiple Linear Regression (FMLR)

Author 1: Feby Ardianto Author 2: Ermatita Ermatita Author 3: Armin Sofijan

This research focused on developing and implementing a fault detection model for photovoltaic (PV) systems in remote areas, utilizing a Fuzzy-Based Multiple Linear Regression (FMLR) approach. The study aimed to address the challenges of monitoring PV systems in locations with limited access to conventional power grids and technical resources. The… Read full abstract & cite →

Photovoltaic multiple linear regression fuzzy fault detection remote areas

Abstract doi.org/10.14569/IJACSA.2025.0160425 PDF

26

Path Planning Technology for Unmanned Aerial Vehicle Swarm Based on Improved Jump Point Algorithm

Author 1: Haizhou Zhang Author 2: Shengnan Xu

Multi-unmanned aerial vehicle path planning encounters challenges with effective obstacle avoidance and collaborative operation. The study proposes a swarm planning technique for unmanned aerial vehicles, based on an improved jump point algorithm. It introduces a geometric collision detection strategy to optimize path search and employs the dynamic window method to… Read full abstract & cite →

Unmanned aerial vehicle swarm path planning jump point search algorithm geometric collision detection dynamic window method

Abstract doi.org/10.14569/IJACSA.2025.0160426 PDF

27

AHP and Fuzzy Evaluation Methods for Improving Cangzhou Honey Date Supplier Performance Management

Author 1: Zhixin Wei

This study focuses on improving supplier performance management within the Cangzhou honey date industry by integrating the Analytic Hierarchy Process (AHP) and fuzzy evaluation methods. Recognizing the limitations of traditional evaluation systems—such as subjectivity and insufficient quantitative analysis—the research aims to build a comprehensive, data-driven evaluation framework. The methodology involves… Read full abstract & cite →

AHP fuzzy evaluation method supplier performance Cangzhou honey date supply chain management

Abstract doi.org/10.14569/IJACSA.2025.0160427 PDF

28

Air Quality Assessment Based on CNN-Transformer Hybrid Architecture

Author 1: Yuchen Zhang Author 2: Rajermani Thinakaran

Air quality assessment plays a crucial role in environmental governance and public health decision-making. Traditional assessment methods have limitations in handling multi-source heterogeneous data and complex nonlinear relationships. This paper proposes an air quality assessment model based on a CNN-Transformer hybrid architecture, which achieves end-to-end prediction by integrating CNN's local… Read full abstract & cite →

Air quality assessment deep learning CNN-Transformer hybrid architecture feature extraction

Abstract doi.org/10.14569/IJACSA.2025.0160428 PDF

29

A Novel Multitasking Framework for Feature Selection in Road Accident Severity Analysis

Author 1: Soumaya AMRI Author 2: Mohammed AL ACHHAB Author 3: Mohamed LAZAAR

In machine learning studies, feature selection presents a crucial step especially when handling complex and imbalanced datasets, such as those used in road traffic injury analysis. This study proposes a novel multitasking feature selection methodology that integrates the Grey Wolf Optimizer, knowledge transfer, and the CatBoost ensemble algorithm to enhance… Read full abstract & cite →

Feature selection road accident injury severity Grey Wolf Optimizer multitasking knowledge transfer

Abstract doi.org/10.14569/IJACSA.2025.0160429 PDF

30

Assessment of Remote Sensing Image Quality and its Application Due to Off-Nadir Imaging Acquisition

Author 1: Agus Herawan Author 2: Patria Rachman Hakim Author 3: Ega Asti Anggari Author 4: Agung Wahyudiono Author 5: Mohammad Mukhayadi Author 6: M. Arif Saifudin Author 7: Chusnul Tri Judianto Author 8: Elvira Rachim Author 9: Ahmad Maryanto Author 10: Satriya Utama Author 11: Rommy Hartono Author 12: Atriyon Julzarika Author 13: Rizatus Shofiyati

One advantage of using microsatellites for remote sensing is their maneuverability so that the target area can be captured from any viewing angle based on specific needs. However, the image captured under off-nadir acquisition will have reduced quality in both geometry and radiometric aspects. This research aims to find the… Read full abstract & cite →

Land cover land use LAPAN-A3 microsatellite off-nadir revisit time

Abstract doi.org/10.14569/IJACSA.2025.0160430 PDF

31

High-Precision Urban Air Quality Prediction Using a LSTM-Transformer Hybrid Architecture

Author 1: Yiming Liu Author 2: Mcxin Tee Author 3: Liangyan Lu Author 4: Fei Zhou Author 5: Binggui Lu

With the acceleration of urbanization, accurate air quality prediction is crucial for environmental governance and public health risk management. Existing prediction methods still face challenges in handling complex time-series dependencies and multi-scale features. In this paper, a hybrid deep learning architecture (LT-Hybrid) based on LSTM and Transformer is proposed for… Read full abstract & cite →

Air quality deep learning LSTM transformer multi-head attention mechanism temporal prediction health risk

Abstract doi.org/10.14569/IJACSA.2025.0160431 PDF

32

The Role of Artificial Intelligence in Brand Experience: Shaping Consumer Behavior and Driving Repurchase Decisions

Author 1: Ati Mustikasari Author 2: Ratih Hurriyati Author 3: Puspo Dewi Dirgantari Author 4: Mokh Adieb Sultan Author 5: Neng Susi Susilawati Sugiana

The rapid advancement of Artificial Intelligence (AI) has transformed brand experiences, influencing consumer behavior and repurchase decisions in digital marketplaces. This study aims to examine the role of AI in enhancing brand experience and its impact on consumer purchasing behavior, particularly in driving repurchase intentions. A quantitative research approach was… Read full abstract & cite →

Digital marketing artificial intelligence brand experience consumer behavior repurchase intentions

Abstract doi.org/10.14569/IJACSA.2025.0160432 PDF

33

Predicting Human Essential Genes Using Deep Learning: MLP with Adaptive Data Balancing

Author 1: Ahmed AbdElsalam Author 2: Mohamed Abdallah Author 3: Hossam Refaat

Artificial intelligence (AI) has transformed many scientific disciplines including bioinformatics. Essential gene prediction is one important use of artificial intelligence in bioinformatics since it is necessary for knowledge of the biological pathways needed for cellular survival and disease diagnosis. Essential genes are fundamental for maintaining cellular life as well as… Read full abstract & cite →

Artificial intelligence bioinformatics deep learning Multi-Layer Perceptron (MLP) imbalanced-handling techniques essential gene prediction sequence characteristics

Abstract doi.org/10.14569/IJACSA.2025.0160433 PDF

34

Personalized Recommendation for Online News Based on UBCF and IBCF Algorithms

Author 1: Wei Shi Author 2: Yitian Zhang

With the popularization of the Internet and the widespread use of mobile devices, online news has become one of the main ways for people to obtain information and understand the world. However, the increasing number and variety of news often cause users to feel troubled when searching for content of… Read full abstract & cite →

IBCF algorithm UBCF collaborative filtering news recommendations label promotion network

Abstract doi.org/10.14569/IJACSA.2025.0160434 PDF

35

Comparative Analysis of SVM, Naïve Bayes, and Logistic Regression in Detecting IoT Botnet Attacks

Author 1: Apri Siswanto Author 2: Luhur Bayu Aji Author 3: Akmar Efendi Author 4: Dhafin Alfaruqi Author 5: M. Rafli Azriansyah Author 6: Yefrianda Raihan

The rapid proliferation of Internet of Things (IoT) devices has significantly increased the risk of cyberattacks, particularly botnet intrusions, which pose serious security threats to IoT networks. Machine learning-based Intrusion Detection Systems (IDS) have emerged as effective solutions for detecting such attacks. This study presents a comparative analysis of three… Read full abstract & cite →

IoT security botnet detection machine learning intrusion detection system comparative analysis SVM naïve bayes logistic regression

Abstract doi.org/10.14569/IJACSA.2025.0160435 PDF

36

Bibliometric and Content Analysis of Large Language Models Research in Software Engineering: The Potential and Limitation in Software Engineering

Author 1: Annisa Dwi Damayanti Author 2: Hamdan Gani Author 3: Feng Zhipeng Author 4: Helmy Gani Author 5: Sitti Zuhriyah Author 6: Nurani Author 7: Nurhayati Djabir Author 8: Nur Ilmiyanti Wardani

Large Language Models (LLM) is a type of artificial neural network that excels at language-related tasks. The advantages and disadvantages of using LLM in software engineering are still being debated, but it is a tool that can be utilized in software engineering. This study aimed to analyze LLM studies in… Read full abstract & cite →

Large Language Models LLM software engineering bibliometric content analysis

Abstract doi.org/10.14569/IJACSA.2025.0160436 PDF

37

HSI Fusion Method Based on TV-CNMF and SCT-NMF Under the Background of Artificial Intelligence

Author 1: Dapeng Zhao Author 2: Yapeng Zhao Author 3: Xuexia Dou

The fusion of hyper-spectral images has important application value in fields such as remote sensing, environmental monitoring, and agricultural analysis. To improve the quality of reconstructed images, an HSI fusion method based on fully variational coupled non-negative matrix factorization and sparse constrained tensor factorization techniques is proposed. Spectral sparsity description… Read full abstract & cite →

HSI NMF sparse regularization SCT augmented Lagrangian method

Abstract doi.org/10.14569/IJACSA.2025.0160437 PDF

38

Energy Management Controller for Bi-Directional EV Charging System Using Prioritized Energy Distribution

Author 1: Ezmin Abdullah Author 2: Muhammad Wafiy Firdaus Jalil Author 3: Nabil M. Hidayat

The growing adoption of electric vehicles (EVs) has intensified the need for efficient, intelligent, and grid-independent Bi-directional charging systems. Conventional EV charging solutions heavily rely on grid electricity, leading to high energy costs, grid instability, and low renewable energy utilization. Existing Bi-directional charging systems often lack real-time prioritization of energy… Read full abstract & cite →

Energy management controller Bi-directional EV charging system safety features control algorithms energy flow optimization EV battery protection testing and validation thingsboard platform InfluxDB database

Abstract doi.org/10.14569/IJACSA.2025.0160438 PDF

39

Machine Learning-Based Prediction of Cannabis Addiction Using Cognitive Performance and Sleep Quality Evaluations

Author 1: Abdelilah Elhachimi Author 2: Mohamed Eddabbah Author 3: Abdelhafid Benksim Author 4: Hamid Ibanni Author 5: Mohamed Cherkaoui

Cannabis addiction remains a growing public health concern, particularly due to its impact on cognition and sleep quality. Conventional screening tools, such as structured interviews and self-assessments, often lack objectivity and sensitivity. This study aims to develop and compare machine learning (ML) models for the prediction of cannabis addiction using… Read full abstract & cite →

Cannabis addiction machine learning cognitive assessment sleep quality predictive modeling

Abstract doi.org/10.14569/IJACSA.2025.0160439 PDF

40

An Obesity Risk Level (ORL) Based on Combination of K-Means and XGboost Algorithms to Predict Childhood Obesity

Author 1: Ghaidaa Hamed Alharbi Author 2: Mohammed Abdulaziz Ikram

Childhood obesity is a common and serious public health problem that requires early prevention measures. Identifying children at risk of obesity is crucial for timely interventions that aim to mitigate these adverse health outcomes. Machine learning (ML) offers powerful tools to predict obesity and related complications using large and diverse… Read full abstract & cite →

Prediction system Childhood obesity K-Means XGBoost Machine learning

Abstract doi.org/10.14569/IJACSA.2025.0160440 PDF

41

Industry 4.0 for SMEs: Exploring Operationalization Barriers and Smart Manufacturing with UKSSL and APO Optimization

Author 1: Meeravali Shaik Author 2: Piyush Kumar Pareek

The research aimed to find out why SMEs have a hard time adopting smart manufacturing, what makes smart manufacturing operational, and if only large companies can afford to take advantage of technological opportunities. It used a knowledge-based semi-supervised framework named Unsupervised Knowledge-based Multi-Layer Perceptron (UKMLP), which has two parts: a… Read full abstract & cite →

European small and medium-sized enterprises artificial protozoa optimizer knowledge-based semi-supervised framework contrastive learning algorithm smart manufacturing

Abstract doi.org/10.14569/IJACSA.2025.0160441 PDF

42

An Improved Sparrow Search Algorithm for Flexible Job-Shop Scheduling Problem with Setup and Transportation Time

Author 1: Yi Li Author 2: Song Han Author 3: Zhaohui Li Author 4: Fan Yang Author 5: Zhengyi Sun

This study addresses the low production efficiency in manufacturing enterprises caused by the diversification of order products, small batches, and frequent production changeovers. Focusing on minimizing the makespan, this study establishes a Flexible Job-Shop Scheduling Problem (FJSP) model incorporating machine setup and workpiece transportation times, and proposes an improved sparrow… Read full abstract & cite →

Flexible job shop scheduling machine setup transportation sparrow search algorithm earliest completion time priority

Abstract doi.org/10.14569/IJACSA.2025.0160442 PDF

43

A Hybrid Levy Arithmetic and Machine Learning-Based Intrusion Detection System for Software-Defined Internet of Things Environments

Author 1: Wenpan SHI Author 2: Ning ZHANG

The convergence of Software-Defined Networking (SDN) and the Internet of Things (IoT) has enabled a more adaptable framework for managing SDN-enabled IoT (SD-IoT) applications, but it also introduces significant cyber security risks. This study proposes a lightweight and explainable intrusion detection system (IDS) based on a hybrid Levy Arithmetic Algorithm… Read full abstract & cite →

Intrusion detection internet of things software-defined feature selection levy arithmetic

Abstract doi.org/10.14569/IJACSA.2025.0160443 PDF

44

Reinforcement Learning-Driven Cluster Head Selection for Reliable Data Transmission in Dense Wireless Sensor Networks

Author 1: Longyang Du Author 2: Qingxuan Wang Author 3: Zhigang ZHANG

Wireless Sensor Networks (WSNs) have made significant advances towards practical applications. Data gathering in WSNs has been carried out using various techniques, such as multi-path routing, tree topologies, and clustering. Conventional systems lack a reliable and effective mechanism for dealing with end-to-end connection, traffic, and mobility problems. These deficiencies often… Read full abstract & cite →

Energy efficiency wireless sensor networks clustering reinforcement learning fuzzy inference system

Abstract doi.org/10.14569/IJACSA.2025.0160444 PDF

45

LIFT: Lightweight Incremental and Federated Techniques for Live Memory Forensics and Proactive Malware Detection

Author 1: Sarishma Dangi Author 2: Kamal Ghanshala Author 3: Sachin Sharma

Live Memory Forensics deals with acquiring and analyzing the volatile memory artefacts to uncover the trace of in-memory malware or fileless malware. Traditional forensics methods operate in a centralized manner leading to a multitude of challenges and severely limiting the possibilities of accurate and timely analysis. In this work, we… Read full abstract & cite →

Live memory forensics malware detection federated learning fileless malware anomaly detection

Abstract doi.org/10.14569/IJACSA.2025.0160445 PDF

46

Design of Control System of Water Source Heat Pump Based on Fuzzy PID Algorithm

Author 1: Min Dong Author 2: Xue Li Author 3: Yixuan Yang Author 4: Zheng Li Author 5: Hui He

This study aims to enhance the control and energy efficiency of the central air conditioning system by integrating frequency conversion fuzzy control and advanced control strategies. The focus is on optimizing the motor operation of the central air conditioning system with the help of a frequency converter and improving the… Read full abstract & cite →

Central air conditioning system frequency converter fuzzy PID control intelligent control energy saving

Abstract doi.org/10.14569/IJACSA.2025.0160446 PDF

47

Stochastic Nonlinear Analysis of Internet of Things Network Performance and Security

Author 1: Junzhou Li Author 2: Feixian Sun

Aiming at the problem of poor effect of traditional Internet of Things network performance and security analysis methods, the research uses support vector machine for Internet of Things network security situation assessment. It also introduces the grey wolf optimization algorithm improved by genetic algorithm to optimize it, and designs a… Read full abstract & cite →

Internet of Things security stochastic nonlinearity support vector machines grey wolf optimization algorithm

Abstract doi.org/10.14569/IJACSA.2025.0160447 PDF

48

Experiential Landscape Design Using the Integration of Three-Dimensional Animation Elements and Overlay Methods

Author 1: Mingjing Sun Author 2: Ming Wei

This work aims to optimize users' immersive experiences, enhance design effectiveness, and construct a scientific evaluation system for landscape design. The work begins with the collection and analysis of spatial data from the landscape design area, using 3D animation technology to generate visual models and virtually reconstruct key landscape elements… Read full abstract & cite →

3D animation integration overlay method experiential landscape design user immersive experience evaluation system design

Abstract doi.org/10.14569/IJACSA.2025.0160448 PDF

49

Database-Based Cooperative Scheduling Optimization of Multiple Robots for Smart Warehousing

Author 1: Zhenglu Zhi

This study investigates the current state and future directions of cooperative scheduling optimization for multiple robots in smart warehousing environments. With the rapid growth of logistics automation, optimizing the collaboration between intelligent robots has become essential for improving warehouse efficiency and adaptability. The research employs a bibliometric analysis based on… Read full abstract & cite →

Database intelligent warehousing robotics cooperative scheduling

Abstract doi.org/10.14569/IJACSA.2025.0160449 PDF

50

A Cross-Chain Mechanism Based on Hierarchically Managed Notary Group

Author 1: Hongliang Tian Author 2: Zhiyang Ruan Author 3: Zhong Fan

Blockchain technology, characterized by decentralization, immutability, traceability, and transparency, provides innovative solutions for data management. However, the limited cross-chain interoperability between blockchains hampers their broader application and development. To address this challenge, this paper proposes a Cross-Chain Mechanism Based on Hierarchically Managed Notary Group, abbreviated as HMNG-CCM, which enables secure… Read full abstract & cite →

Blockchain cross-chain notary group hierarchical management reputation evaluation

Abstract doi.org/10.14569/IJACSA.2025.0160450 PDF

51

Comprehensive Vulnerability Analysis of Three-Factor Authentication Protocols in Internet of Things-Enabled Healthcare Systems

Author 1: Haewon Byeon

This study evaluates a three-factor authentication protocol designed for IoT healthcare systems, identifying several key vulnerabilities that could compromise its security. The analysis reveals weaknesses in single-factor authentication, time synchronization, side-channel attacks, and replay attacks. To address these vulnerabilities, the study proposes a series of enhancements, including the implementation of… Read full abstract & cite →

Three-factor authentication IoT healthcare security multi-factor authentication side-channel attack mitigation replay attack prevention

Abstract doi.org/10.14569/IJACSA.2025.0160451 PDF

52

Real-Time Lightweight Sign Language Recognition on Hybrid Deep CNN-BiLSTM Neural Network with Attention Mechanism

Author 1: Gulnur Kazbekova Author 2: Zhuldyz Ismagulova Author 3: Gulmira Ibrayeva Author 4: Almagul Sundetova Author 5: Yntymak Abdrazakh Author 6: Boranbek Baimurzayev

Sign language recognition (SLR) plays a crucial role in bridging communication gaps for individuals with hearing and speech impairments. This study proposes a hybrid deep CNN-BiLSTM neural network with an attention mechanism for real-time and lightweight sign language recognition. The CNN module extracts spatial features from individual gesture frames, while… Read full abstract & cite →

Sign language recognition CNN-BiLSTM attention mechanism deep learning gesture classification real-time processing assistive technology

Abstract doi.org/10.14569/IJACSA.2025.0160452 PDF

53

Investigating the Impact of Hyper Parameters on Intrusion Detection System Using Deep Learning Based Data Augmentation

Author 1: Umar Iftikhar Author 2: Syed Abbas Ali

The effects of changing learning rates, data augmentation percentage and numbers of epochs on the performance of Wasserstein Generative Adversarial Networks with Gradient Penalties (WGAN-GP) are evaluated in this study. The purpose of this research is to find out how they affect the data augmentation to enhance stability during training… Read full abstract & cite →

Artificial intelligence learning rate cyber threat network intrusion detection deep learning data augmentation generative adversarial networks epochs

Abstract doi.org/10.14569/IJACSA.2025.0160453 PDF

54

Adaptive Crow Search Algorithm for Hierarchical Clustering in Internet of Things-Enabled Wireless Sensor Networks

Author 1: Lingwei WANG Author 2: Hua WANG

The Internet of Things (IoT) relies on efficient Wireless Sensor Networks (WSNs) for data collection and transmission in various applications, including smart cities, industrial automation, and environmental monitoring. Clustering is a fundamental technique for structuring WSNs hierarchically, enabling load balancing, reducing energy consumption, and extending network lifespan. However, clustering optimization… Read full abstract & cite →

Internet of things wireless sensor networks clustering energy efficiency optimization

Abstract doi.org/10.14569/IJACSA.2025.0160454 PDF

55

Understanding Brain Network Stimulation for Emotion Analyzing Connectivity Feature Map from Electroencephalography

Author 1: Mahfuza Akter Maria Author 2: M. A. H. Akhand Author 3: Md Abdus Samad Kamal

In understanding brain functioning by Electroencephalography (EEG), it is essential to be able to not only identify more active brain areas but also understand connectivity among different areas. The functional and efficient connectivity networks of the brain have been examined in this study by constructing a connectivity feature map (CFM)… Read full abstract & cite →

Brain connectivity connectivity feature map electroencephalography emotion

Abstract doi.org/10.14569/IJACSA.2025.0160455 PDF

56

AI-Driven Predictive Analytics for CRM to Enhance Retention Personalization and Decision-Making

Author 1: Yashika Gaidhani Author 2: Janjhyam Venkata Naga Ramesh Author 3: Sanjit Singh Author 4: Reetika Dagar Author 5: T Subha Mastan Rao Author 6: Sanjiv Rao Godla Author 7: Yousef A.Baker El-Ebiary

The advent of Artificial Intelligence (AI) has dramatically altered Customer Relationship Management (CRM) by allowing organizations to anticipate customer behavior, customize interactions and automate service delivery. This research introduces an extensive AI-based predictive analytics framework aimed at improving customer engagement, retention and satisfaction using advanced Machine Learning (ML) and Natural… Read full abstract & cite →

Artificial Intelligence predictive analytics customer relationship management natural language processing churn prediction

Abstract doi.org/10.14569/IJACSA.2025.0160456 PDF

57

Cognitive Load Optimization in Digital (ESL) Learning: A Hybrid BERT and FNN Approach for Adaptive Content Personalization

Author 1: Komminni Ramesh Author 2: Christine Ann Thomas Author 3: Joel Osei-Asiamah Author 4: Bhuvaneswari Pagidipati Author 5: Elangovan Muniyandy Author 6: B. V. Suresh Reddy Author 7: Yousef A.Baker El-Ebiary

Traditional English as a Secondary Language (ESL) learning platform rely on static content delivery, often failing to adapt to individual learners’ cognitive capacities, leading to inefficient comprehension and increased cognitive load. A novel hybrid Feedforward Neural Network and Bidirectional Encoder Representation Transformer (FNN-BERT) framework stands as our solution because it… Read full abstract & cite →

Cognitive load management artificial intelligence-based English as a secondary language learning adaptive content personalization

Abstract doi.org/10.14569/IJACSA.2025.0160457 PDF

58

Enhancing Cybersecurity Through Artificial Intelligence: A Novel Approach to Intrusion Detection

Author 1: Mohammed K. Alzaylaee

Modern cyber threats have evolved to sophisticated levels, necessitating advanced intrusion detection systems (IDS) to protect critical network infrastructure. Traditional signature-based and rule-based IDS face challenges in identifying new and evolving attacks, leading organizations to adopt AI-driven detection solutions. This study introduces an AI-powered intrusion detection system that integrates machine… Read full abstract & cite →

Intrusion detection machine learning deep learning zero-day attacks anomaly detection feature selection reinforcement learning cybersecurity

Abstract doi.org/10.14569/IJACSA.2025.0160458 PDF

59

Smoke Detection Model with Adaptive Feature Alignment and Two-Channel Feature Refinement

Author 1: Yuanpan Zheng Author 2: Binbin Chen Author 3: Zeyuan Huang Author 4: Yu Zhang Author 5: Chao Wang Author 6: Xuhang Liu

To address issues of missed detections and low accuracy in existing smoke detection algorithms when dealing with variable smoke patterns in small-scale objects and complex environments, FAR-YOLO was proposed as an enhanced smoke detection model based on YOLOv8. The model adopted Fast-C2f structure to optimize and reduce the amount of… Read full abstract & cite →

Smoke detection model adaptive feature alignment two-channel feature refinement attention mechanism

Abstract doi.org/10.14569/IJACSA.2025.0160459 PDF

60

Design and Modeling of a Dynamic Adaptive Hypermedia System Based on Learners' Needs and Profile

Author 1: Mohamed Benfarha Author 2: Mohammed Sefian Lamarti Author 3: Mohamed Khaldi

This study presents the design and modeling of an adaptive hypermedia system, capable of dynamically adjusting to the needs and characteristics of each learner according to their profile. In the digital age, where digital content must respond to varied profiles and adapt to learners' preferences and skills, this system offers… Read full abstract & cite →

Design adaptive hypermedia learning styles user modeling UML models

Abstract doi.org/10.14569/IJACSA.2025.0160460 PDF

61

From Code Analysis to Fault Localization: A Survey of Graph Neural Network Applications in Software Engineering

Author 1: Maojie PAN Author 2: Shengxu LIN Author 3: Zhenghong XIAO

Graph Neural Networks (GNNs) represent a class of deep machine learning algorithms for analyzing or processing data in graph structure. Most software development activities, such as fault localization, code analysis, and measures of software quality, are inherently graph-like. This survey assesses GNN applications in different subfields of software engineering with… Read full abstract & cite →

Graph neural networks fault localization code analysis software quality

Abstract doi.org/10.14569/IJACSA.2025.0160461 PDF

62

Designing Quantum-Resilient Blockchain Frameworks: Enhancing Transactional Security with Quantum Algorithms in Decentralized Ledgers

Author 1: Meenal R Kale Author 2: Yousef A.Baker El-Ebiary Author 3: L. Sathiya Author 4: Vijay Kumar Burugari Author 5: Erkiniy Yulduz Author 6: Elangovan Muniyandy Author 7: Rakan Alanazi

Quantum computing is progressing at a fast rate and there is a real threat that classical cryptographic methods can be compromised and therefore impact the security of blockchain networks. All of the ways used to secure blockchain like Rivest–Shamir–Adleman (RSA), Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm 256-bit (SHA256)… Read full abstract & cite →

Quantum resilience blockchain security Quantum Key Distribution (QKD) Post-Quantum Cryptography (PQC) Quantum Random Number Generation (QRNG) decentralized ledger

Abstract doi.org/10.14569/IJACSA.2025.0160462 PDF

63

Pose Estimation of Spacecraft Using Dual Transformers and Efficient Bayesian Hyperparameter Optimization

Author 1: N. Kannaiya Raja Author 2: Janjhyam Venkata Naga Ramesh Author 3: Yousef A.Baker El-Ebiary Author 4: Elangovan Muniyandy Author 5: N. Konda Reddy Author 6: Vanipenta Ravi Kumar Author 7: Prasad Devarasetty

Spacecraft pose estimation is an essential contribution to facilitating central space mission activities like autonomous navigation, rendezvous, docking, and on-orbit servicing. Nonetheless, methods like Convolutional Neural Networks (CNNs), Simultaneous Localization and Mapping (SLAM), and Particle Filtering suffer significant drawbacks when implemented in space. Such techniques tend to have high computational… Read full abstract & cite →

Dual-channel transformer model Bayesian optimization EfficientNet pose estimation SLAB dataset

Abstract doi.org/10.14569/IJACSA.2025.0160463 PDF

64

Energy-Efficient Cloud Computing Through Reinforcement Learning-Based Workload Scheduling

Author 1: Ashwini R Malipatil Author 2: M E Paramasivam Author 3: Dilfuza Gulyamova Author 4: Aanandha Saravanan Author 5: Janjhyam Venkata Naga Ramesh Author 6: Elangovan Muniyandy Author 7: Refka Ghodhbani

The basis for current digital infrastructure is cloud computing, which allows for scalable, on-demand computational resource access. Data center power consumption, however, has skyrocketed because of demand increases, raising operating costs and their footprint. Traditional workload scheduling algorithms often assign performance and cost priority over energy efficiency. This paper proposes… Read full abstract & cite →

Cloud computing energy efficiency reinforcement learning virtual machine workload scheduling

Abstract doi.org/10.14569/IJACSA.2025.0160464 PDF

65

WOAAEO: A Hybrid Whale Optimization and Artificial Ecosystem Optimization Algorithm for Energy-Efficient Clustering in Internet of Things-Enabled Wireless Sensor Networks

Author 1: Shengnan BAI Author 2: Ningning LIU Author 3: Yongbing JI Author 4: Kecheng WANG

In the Internet of Things (IoT) era, energy efficiency in Wireless Sensor Networks (WSNs) is of utmost importance given the finite power resources of sensor nodes. An efficient Cluster Head (CH) selection greatly influences network performance and lifetime. This paper suggests a novel energy-efficient clustering protocol that hybridizes Whale Optimization… Read full abstract & cite →

Clustering Internet of Things energy efficiency wireless sensor network network lifespan

Abstract doi.org/10.14569/IJACSA.2025.0160465 PDF

66

Improvement of Rainfall Estimation Accuracy Using a Convolutional Neural Network with Convolutional Block Attention Model on Surveillance Camera

Author 1: Iqbal Author 2: Adhi Harmoko Saputro Author 3: Alhadi Bustamam Author 4: Ardasena Sopaheluwakan

Accurate rainfall estimation is essential for various applications, including transportation management, agriculture, and climate modeling. Traditional measurement methods, such as rain gauges and radar systems, often face challenges due to limited spatial resolution and susceptibility to environmental interferences. These constraints affect the ability of the model to deliver high-resolution, real-time… Read full abstract & cite →

Rainfall surveillance camera hybrid deep learning CBAM

Abstract doi.org/10.14569/IJACSA.2025.0160466 PDF

67

Adaptive AI-Based Personalized Learning for Accelerated Vocabulary and Syntax Mastery in Young English Learners

Author 1: Angalakuduru Aravind Author 2: M. Durairaj Author 3: Preeti Chitkara Author 4: Yousef A.Baker El-Ebiary Author 5: Elangovan Muniyandy Author 6: Linginedi Ushasree Author 7: Mohamed Ben Ammar

Language acquisition is an integral part of early schooling, but young English language learners struggle to learn vocabulary and syntax since they are not provided with specialized instruction. Conventional teaching may vary according to different learning speeds and it leads to unbalanced levels of proficiency among students and possibly leading… Read full abstract & cite →

AI-based learning gamification language acquisition personalized feedback vocabulary

Abstract doi.org/10.14569/IJACSA.2025.0160467 PDF

68

DenseRSE-ASPPNet: An Enhanced DenseNet169 with Residual Dense Blocks and CE-HSOA-Based Optimization for IoT Botnet Detection

Author 1: Mohd Abdul Rahim Khan

The growing prevalence of Internet of Things (IoT) devices has heightened vulnerabilities to botnet-based cyberattacks, necessitating robust detection mechanisms. This paper proposes DenseRSE-ASPPNet, an advanced deep learning framework for botnet detection, incorporating comprehensive preprocessing, feature extraction, and optimization. The preprocessing pipeline includes data cleaning and Min-Max normalization to ensure high-quality… Read full abstract & cite →

Internet of Things botnet detection DenseRSE-ASPPNet residual squeeze-and-excitation blocks Cyclone-Enhanced Humboldt Squid Optimization Algorithm

Abstract doi.org/10.14569/IJACSA.2025.0160468 PDF

69

Clustering Analysis of Physicians' Performance Evaluation: A Comparison of Feature Selection Strategies to Support Medical Decision-Making

Author 1: Amani Mustafa Ghazzawi Author 2: Alaa Omran Almagrabi Author 3: Hanaa Mohammed Namankani

Evaluating physicians' performance is one of the fundamental pillars of improving the quality of healthcare in medical institutions, as it contributes to measuring their ability to provide appropriate treatment, interact effectively with patients, and work within healthcare teams. This study aims to explore the impact of attribute selection on the… Read full abstract & cite →

Physicians performance evaluation clustering k- means features decision making

Abstract doi.org/10.14569/IJACSA.2025.0160469 PDF

70

Exploring Digital Insurance Solutions: A Systematic Literature Review and Future Research Agenda

Author 1: Anni Wei Author 2: Yurita Yakimin Abdul Talib Author 3: Zakiyah Sharif

The purpose of this study is to explore the antecedents for the adoption of digital insurance solutions and to present current research trends and future research agendas based on a systematic literature review. The findings revealed key motivators for the adoption of digital insurance solutions, such as trust, perceived usefulness… Read full abstract & cite →

Digital insurance Technology Acceptance Model antecedents of adoption systematic literature review future research agenda

Abstract doi.org/10.14569/IJACSA.2025.0160470 PDF

71

Towards an Optimization Model for Household Waste Bins Location Management

Author 1: Moulay Lakbir Tahiri Alaoui Author 2: Meryam Belhiah Author 3: Soumia Ziti

Smart cities require effective, adaptive household waste management systems due to rapid urbanization. Traditional bin placement strategies based on placing bins equidistant among residents fail to account for actual human behavior, leading to overflowing or underused bins. This paper addresses optimizing bin location and capacity through Internet of things (IoT)… Read full abstract & cite →

Smart City IoT household waste LoRaWan bin location outlier detection

Abstract doi.org/10.14569/IJACSA.2025.0160471 PDF

72

Enhancing Electric Vehicle Security with Face Recognition: Implementation Using Raspberry Pi

Author 1: Jamil Abedalrahim Jamil Alsayaydeh Author 2: Chin Wei Yi Author 3: Rex Bacarra Author 4: Fatimah Abdulridha Rashid Author 5: Safarudin Gazali Herawan

Facial identification has emerged as a key research area due to its potential to enhance biometric security. This research proposes an advanced security system for electric vehicles (EVs) based on facial identification, implemented using Raspberry Pi. The system comprises two main modules: Face Detection and Face Recognition. For face detection… Read full abstract & cite →

Face recognition face detection Principal Component Analysis (PCA) Support Vector Machine (SVM) Raspberry Pi

Abstract doi.org/10.14569/IJACSA.2025.0160472 PDF

73

Modelling the Moderating Role of Government Policy in Cryptocurrency Investment Acceptance

Author 1: Maslinda Mohd Nadzir Author 2: Rabea Abdulrahman Raweh Author 3: Hapini Awang Author 4: Huda Ibrahim

Without the requirement for third-party approval, cryptocurrency enables anonymous, secure, quick, and inexpensive financial transactions. Although cryptocurrency is gaining global popularity, its applications are still limited. This research aims to investigate the factors influencing the acceptance of cryptocurrency as an investment tool, focusing on the moderating role of government policy… Read full abstract & cite →

Cryptocurrency acceptance investment UTAUT government policy

Abstract doi.org/10.14569/IJACSA.2025.0160473 PDF

74

Healthy and Unhealthy Oil Palm Tree Detection Using Deep Learning Method

Author 1: Kang Hean Heng Author 2: Azman Ab Malik Author 3: Mohd Azam Bin Osman Author 4: Yusri Yusop Author 5: Irni Hamiza Hamzah

Oil palm trees are the world's most efficient and economically productive oil bearing crop. It can be processed into components needed in various products, such as beauty products and biofuel. In Malaysia, the oil palm industry contributes around 2.2% annually to the nation's GDP. The continuous surge in demand for… Read full abstract & cite →

Component oil palm detection deep learning models object detection Faster R-CNN drone imagery analysis

Abstract doi.org/10.14569/IJACSA.2025.0160474 PDF

75

Intelligent Guitar Chord Recognition Using Spectrogram-Based Feature Extraction and AlexNet Architecture for Categorization

Author 1: Nilesh B. Korade Author 2: Mahendra B. Salunke Author 3: Amol A. Bhosle Author 4: Sunil M. Sangve Author 5: Dhanashri M. Joshi Author 6: Gayatri G. Asalkar Author 7: Sujata R. Kadu Author 8: Jayesh M. Sarwade

Chord prediction plays a key role in the advancement of musical technological innovations, such as automatic music transcription, real-time music tutoring, and intelligent composition tools. Accurate chord prediction can assist musicians, educators, and developers in constructing tools that help in learning, playing, and composing music. Background noise and audio distortions… Read full abstract & cite →

Chords prediction spectrogram chromagram Mel Frequency Cepstral Coefficients AlexNet

Abstract doi.org/10.14569/IJACSA.2025.0160475 PDF

76

Portable and Lightweight Signal Processing Approach for sEMG-Based Human–Machine Interaction in Robotic Hands

Author 1: Ngoc-Khoat Nguyen

Surface electromyography (sEMG) presents a viable biosignal for the control of robotic prosthetic hands, as it directly correlates with underlying muscle activity. This study introduces an efficient, computationally lightweight signal processing methodology designed for real-time embedded systems. The proposed methodology comprises a preprocessing pipeline, incorporating bandpass and notch filtering, followed… Read full abstract & cite →

sEMG myo-prosthesis myosignals human–prosthesis interface signal processing

Abstract doi.org/10.14569/IJACSA.2025.0160476 PDF

77

Enhancing Match Detection Process Using Chi-Square Equation for Improving Type-3 and Type-4 Clones in Java Applications

Author 1: Noormaizzattul Akmaliza Abdullah Author 2: Al-Fahim Mubarak-Ali Author 3: Mohd Azwan Mohamad Hamza Author 4: Siti Salwani Yaacob

Generic Code Clone Detection (GCCD) is a code clone detection model that use distance measure equation, enabling detection of all types of code clones, naming clone Type-1, Type-2, Type-3 and Type-4 in Java programming language applications. However, the detection process of GCCD did not focus on detecting clones of Type-3… Read full abstract & cite →

Code clone detection distance measure Java language Chi-square computational intelligence

Abstract doi.org/10.14569/IJACSA.2025.0160477 PDF

78

Transforming Internal Auditing: Harnessing Retrieval-Augmented Generation Technology

Author 1: Olive Stumke Author 2: Fanie Ndlovu

The advent of cloud-based Generative AI models, such as ChatGPT, Google Gemini, and Claude, has created new opportunities for improving education through real-time, adaptive learning experiences. Despite their widespread use globally, their application in South African higher education remains limited and underexplored, resulting in an application gap. This paper, as… Read full abstract & cite →

Adaptive learning Anthropic Haiku benefits challenges Generative AI Google Gemini API Pro higher education internal auditing OpenAI GPT-Turbo personalized learning RAG (Retrieval-Augmented Generation) South Africa

Abstract doi.org/10.14569/IJACSA.2025.0160478 PDF

79

Development of an Interactive Oral English Translation System Leveraging Deep Learning Techniques

Author 1: Dan Zhao Author 2: HeXu Yang

An advanced interactive English oral automatic translation system has been developed using cutting-edge deep learning techniques to address key challenges such as low success rates, lengthy processing times, and limited accuracy in current systems. The core of this innovation lies in a sophisticated deep learning translation model that leverages neural… Read full abstract & cite →

Deep learning interactive English spoken English automatic translation translation system

Abstract doi.org/10.14569/IJACSA.2025.0160479 PDF

80

Impact of Cryptocurrencies and Their Technological Infrastructure on Global Financial Regulation: Challenges for Regulators and New Regulations

Author 1: Juan Chavez-Perez Author 2: Raquel Melgarejo-Espinoza Author 3: Victor Sevillano-Vega Author 4: Orlando Iparraguirre-Villanueva

The rise of cryptocurrencies is transforming the landscape of global finance, but their very decentralized nature is triggering unprecedented challenges for regulatory systems. This systematic literature review (SLR) aimed to gather and synthesize information to understand the functioning of cryptocurrencies in relation to their regulatory challenges. The PRISMA (Preferred Reporting… Read full abstract & cite →

Cryptocurrencies financial regulation blockchain regulatory challenges cryptocurrency laws

Abstract doi.org/10.14569/IJACSA.2025.0160480 PDF

81

Developing a Comprehensive NLP Framework for Indigenous Dialect Documentation and Revitalization

Author 1: Mohammed Fakhreldin

The disappearance of Indigenous languages results in a decrease in cultural diversity, hence making the preservation of these languages extremely important. Conventional methods of documentation are lengthy, and the present AI solutions somehow do not deliver due to data scarcity, dialectal variation, and poor adaptability to low-resource languages. A novel… Read full abstract & cite →

Indigenous language preservation natural language processing meta-learning contrastive learning low-resource languages

Abstract doi.org/10.14569/IJACSA.2025.0160481 PDF

82

Optimizing Document Classification Using Modified Relative Discrimination Criterion and RSS-ELM Techniques

Author 1: Muhammad Anwaar Author 2: Ghulam Gilanie Author 3: Abdallah Namoun Author 4: Wareesa Sharif

Internet content is increasing daily, and more data are being digitized due to technological advancements. Ever-increasing textual data in words, phrases, terms, sentences, and paragraphs pose significant challenges in classifying them effectively and require sophisticated techniques to arrange them automatically. The vast amount of textual data presents an opportunity to… Read full abstract & cite →

Feature selection relative discrimination criterion ring seal search extreme learning machine metaheuristic algorithms document classification optimization

Abstract doi.org/10.14569/IJACSA.2025.0160482 PDF

83

Extracting Facial Features to Detect Deepfake Videos Using Machine Learning

Author 1: Ayesha Aslam Author 2: Jamaluddin Mir Author 3: Gohar Zaman Author 4: Atta Rahman Author 5: Asiya Abdus Salam Author 6: Farhan Ali Author 7: Jamal Alhiyafi Author 8: Aghiad Bakry Author 9: Mustafa Jamal Gul Author 10: Mohammed Gollapalli Author 11: Maqsood Mahmud

Generative adversarial networks (GANs) have gained popularity for their ability to synthesize images from random inputs in deep learning models. One of the notable applications of this technology is the creation of realistic videos known as deepfakes, which have been misused on social media platforms. The difficulty lies in distinguishing… Read full abstract & cite →

Deepfake fake videos facial features GAN

Abstract doi.org/10.14569/IJACSA.2025.0160483 PDF

84

Hybrid Approach for Early Road Defect Detection: Integrating Edge Detection with Attention-Enhanced MobileNetV3 for Superior Classification

Author 1: Ayoub Oulahyane Author 2: Mohcine Kodad Author 3: El Houcine Addou Author 4: Sofia Ourarhi Author 5: Hajar Chafik

The early detection of road defects is critical for maintaining infrastructure quality and ensuring public safety. This research presents a hybrid approach that combines edge detection techniques with an enhanced deep learning model for efficient and accurate road defect classification. The process begins with edge detection to highlight structural irregularities… Read full abstract & cite →

Road defect detection edge detection attention mechanism MobileNetV3

Abstract doi.org/10.14569/IJACSA.2025.0160484 PDF

85

Speech Decoding from EEG Signals

Author 1: Salma Fahad Altharmani Author 2: Maha M. Althobaiti

The field of speech decoding is rapidly evolving, presenting new challenges and new opportunities for people with disabilities such as amyotrophic lateral sclerosis (ALS), stroke, or paralysis, and for those who support them. However, speech decoding is complex: it requires analysing brain waves, across spatial and temporal dimensions, before translating… Read full abstract & cite →

Speech decoding EEG deep learning CNN RNN hybrid models Brain-Computer Interfaces (BCI)

Abstract doi.org/10.14569/IJACSA.2025.0160485 PDF

86

Enhanced Emotion Recognition Using a Hybrid Autoencoder-LSTM Model Optimized with a Hybrid ACO-WOA Algorithm for Hyperparameter Tuning

Author 1: Vinod Waiker Author 2: Janjhyam Venkata Naga Ramesh Author 3: Kiran Bala Author 4: V. V. Jaya Rama Krishnaiah Author 5: T. Jackulin Author 6: Elangovan Muniyandy Author 7: Osama R. Shahin

Emotion recognition is vital in the human Computer interaction because it improves interaction. Therefore, this paper proposes an improved method for emotion recognition regarding the Hybrid Autoencoder-Long Short-Term Memory (LSTM) model and the newly developed hybrid approach of the Ant Colony Optimization (ACO) and Whale Optimization Algorithm (WOA) for hyperparameters… Read full abstract & cite →

Emotion recognition autoencoder long short-term memory Ant Colony Optimization (ACO) Whale Optimization Algorithm (WOA)

Abstract doi.org/10.14569/IJACSA.2025.0160486 PDF

87

Automated Defect Detection in Manufacturing Using Enhanced VGG16 Convolutional Neural Networks

Author 1: Altynzer Baiganova Author 2: Zhanar Ubayeva Author 3: Zhanar Taskalyeva Author 4: Lezzat Kaparova Author 5: Roza Nurzhaubaeva Author 6: Banu Umirzakova

Automated defect detection in manufacturing is a critical component of modern quality control, ensuring high production efficiency and minimizing defective outputs. This study presents an enhanced VGG16-based convolutional neural network (CNN) model for defect classification and localization, improving upon traditional vision-based inspection methods. The proposed model integrates advanced deep learning… Read full abstract & cite →

Automated defect detection deep learning convolutional neural networks VGG16 quality control manufacturing inspection machine vision Industry 4.0

Abstract doi.org/10.14569/IJACSA.2025.0160487 PDF

88

Ontology-Based Business Processes Gap Analysis

Author 1: Abdelgaffar Hamed Ahmed Ali

Business processes are subject to change for quality reasons (i.e., efficiency). However, the gap analysis process is a preliminary and essential step in discovering the gap between the to-be and as-is business processes. It usually resorts to a nonstandard and manual analysis process, making it unpredictable and complex. This paper… Read full abstract & cite →

Business process gap analysis ontology for business processes

Abstract doi.org/10.14569/IJACSA.2025.0160488 PDF

89

Investigation of Convolutional Neural Network Model for Vehicle Classification in Smart City

Author 1: Ahsiah Ismail Author 2: Amelia Ritahani Ismail Author 3: Nur Azri Shaharuddin Author 4: Asmarani Ahmad Puzi Author 5: Suryanti Awang

Smart city optimize efficiency by integrating advanced digital technologies, real-time data analytics, and intelligent automation. With the evolution of big data, smart cities enhance infrastructure and provide intelligent solutions for transportation with the integration of high-level adaptability of computer technologies including artificial intelligence (AI). The optimization can be achieved through… Read full abstract & cite →

Vehicle classification Convolutional Neural Network SSD YOLO MobileNets

Abstract doi.org/10.14569/IJACSA.2025.0160489 PDF

90

Using EPP Theory and BMO-Inspired Approach to Design a Virtual Reality Dashboard Design Ontology

Author 1: Liew Kok Leong Author 2: Fazita Irma Tajul Urus Author 3: Muhammad Arif Riza Author 4: Mohammad Nazir Ahmad Author 5: Ummul Hanan Mohamad

This paper introduces the Virtual Reality Dashboard Design Ontology (VRDDO), an ontological framework developed to address the absence of standardized methodologies in designing Virtual Reality (VR) dashboards for complex data visualization, particularly in smart farm monitoring. The VRDDO is built upon the Design Science Research (DSR) approach and anchored in… Read full abstract & cite →

Design Science Research (DSR) Ontology Development Methodology (ODM) Ecological Psychological Perspective (EPP) Unified Foundational Ontology (UFO) Virtual Reality Dashboard Design Method (VRDDM)

Abstract doi.org/10.14569/IJACSA.2025.0160490 PDF

91

Quantitative Assessment and Forecasting of Control Risks in the Ore-Stream Quality Management System

Author 1: Almas Mukhtarkhanuly Soltan Author 2: Bakytzhan Turmyshevich Kobzhassarov

The paper is aimed at organizational and technological optimization of the system of remote control of ore-stream quality according to technical and economic criteria. The ore-stream in the environment of digital transformation of the mining industry is seen as a system where one of the main functions of management is… Read full abstract & cite →

Ore-stream system model technology control risks probability unmanned vehicles

Abstract doi.org/10.14569/IJACSA.2025.0160491 PDF

92

Detection and Classification of Intestinal Parasites With Bayesian-Optimized Model

Author 1: Haifa Hamza Author 2: Kamarul Hawari Ghazali Author 3: Abubakar Ahmad

Automated detection of intestinal parasites in medical imaging enhances diagnostic efficiency and reduces human error. This study evaluates object detection techniques using Faster R-CNN with different backbone architectures such as ResNet, RetinaNet, ResNext and YOLOv8 series for detecting Ascaris lumbricoides and Trichuris trichiura in microscopic images. A dataset of 2000… Read full abstract & cite →

Intestinal parasites faster region convolutional neural network You Look Only Once (YOLOv8) Bayesian Optimization medical imaging object detection

Abstract doi.org/10.14569/IJACSA.2025.0160492 PDF

93

A Comparative Study of Deep Learning and Modern Machine Learning Methods for Predicting Australia’s Precipitation

Author 1: Hira Farman Author 2: Qurat-ul-ain Mastoi Author 3: Qaiser Abbas Author 4: Saad Ahmad Author 5: Abdulaziz Alshahrani Author 6: Salman Jan Author 7: Toqeer Ali Syed

Floods are chaotic weather patterns that cause irreversible and devastating harm to people’s lives, crops, and the socioeconomic system. It causes extensive property damage, animal mortality, and even human fatalities. To mitigate the risk of flooding, it is imperative to create an early warning system that can accurately forecast the… Read full abstract & cite →

Machine learning rainfall prediction neural network Random Forest deep learning

Abstract doi.org/10.14569/IJACSA.2025.0160493 PDF

94

Hardware-Accelerated Detection of Unauthorized Mining Activities Using YOLOv11 and FPGA

Author 1: Refka Ghodhbani Author 2: Taoufik Saidani Author 3: Amani Kachoukh Author 4: Mahmoud Salaheldin Elsayed Author 5: Yahia Said Author 6: Rabie Ahmed

Illegal mining activities present significant environ-mental, economic, and safety challenges, particularly in remote and under-monitored regions. Traditional surveillance methods are often inefficient, labor-intensive, and unable to provide real-time insights. To address this issue, this study proposes a computer vision-based solution leveraging the state-of-the-art YOLOv11 Nano and Small models, fine-tuned for… Read full abstract & cite →

YOLOv11 object detection mining industry

Abstract doi.org/10.14569/IJACSA.2025.0160494 PDF

95

Healthcare 4.0: A Large Language Model-Based Blockchain Framework for Medical Device Fault Detection and Diagnostics

Author 1: Khalid Alsaif Author 2: Aiiad Albeshri Author 3: Maher Khemakhem Author 4: Fathy Eassa

This paper introduces a novel framework integrating Large Language Models (LLMs) with blockchain technology for medical device fault detection and diagnostics in Health-care 4.0 environments. The proposed framework addresses key challenges, including real-time fault detection, data security, and automated diagnostics through a multi-layered architecture incorporating Internet of Things (IoT) integration… Read full abstract & cite →

Healthcare 4.0 Large Language Models blockchain technology medical device diagnostics fault detection smart healthcare IoT healthcare security machine learning

Abstract doi.org/10.14569/IJACSA.2025.0160495 PDF

96

Knowledge Discovery of the Internet of Things (IoT) Using Large Language Model

Author 1: Bassma Saleh Alsulami

Internet of Things (IoT) technology quickly trans-formed traditional management and engagement techniques in several sectors. This work explores the trends and applications of the Internet of Things in industries, including agriculture, education, transportation, water management, air quality monitoring, underground mining, smart retail, smart home systems, and weather forecasting. The methodology… Read full abstract & cite →

Internet of Things large language model BERT knowledge discovery data mining deep learning

Abstract doi.org/10.14569/IJACSA.2025.0160496 PDF

97

Rib Bone Extraction Towards Liver Isolating in CT Scans Using Active Contour Segmentation Methods

Author 1: Mahmoud S. Jawarneh Author 2: Shahid Munir Shah Author 3: Mahmoud M. Aljawarneh Author 4: Ra’ed M. Al-Khatib Author 5: Mahmood G. Al-Bashayreh

Image segmentation is an important aspect of image processing and analysis. Medical imaging segmentation is critical for providing noninvasive information about human body structure that helps physicians analyze body anatomies efficiently. Until recently, various medical imaging segmentation approaches have been presented; however, these approaches are deficient in segmenting abdominal organs… Read full abstract & cite →

Active contour computed tomography segmentation medical diagnostics medical imaging segmentation

Abstract doi.org/10.14569/IJACSA.2025.0160497 PDF

98

Revolutionizing Road Safety and Optimization with AI: Insights from Enterprise Implementation

Author 1: OUAHBI Younesse Author 2: ZITI Soumia

This study explores the key factors influencing the adoption of artificial intelligence (AI) in the logistics sector, with a particular emphasis on road logistics management. It examines the technological, organizational, and environmental contexts that shape AI integration, as well as the challenges faced by logistics managers, including the need for… Read full abstract & cite →

AI adoption road logistics logistics management digital transformation CO2 emissions parcel tracking management

Abstract doi.org/10.14569/IJACSA.2025.0160498 PDF

99

Big Data-Driven Charging Network Optimization: Forecasting Electric Vehicle Distribution in Malaysia to Enhance Infrastructure Planning

Author 1: Ouyang Mutian Author 2: Guo Maobo Author 3: Yu Tianzhou Author 4: Liu Haotian Author 5: Yang Hanlin

The rapid growth of electric vehicles (EVs) globally and in Malaysia has raised significant concerns regarding the adequacy and spatial imbalance of charging infrastructure. Despite government incentives and policy support, Malaysia’s charging network remains insufficient and unevenly distributed, with major urban centers having better access than rural and highway regions… Read full abstract & cite →

Electric vehicles charging infrastructure CEEM-DAN XGBoost spatial optimization data-driven planning Malaysia

Abstract doi.org/10.14569/IJACSA.2025.0160499 PDF

100

Dual Neural Paradigm: GRU-LSTM Hybrid for Precision Exchange Rate Predictions

Author 1: Shamaila Butt

The USD/RMB exchange rate is significant when examining the structure of the Chinese financial system. Predicting the accurate USD/RMB exchange rate enables individuals to analyze the condition of the economy and prevent losses. We propose a novel hybrid approach of GRU-LSTM to improve the forecast of the future USD/RMB exchange… Read full abstract & cite →

Prediction LSTM GRU USD/RMB exchange rate deep learning

Abstract doi.org/10.14569/IJACSA.2025.01604100 PDF

101

AI-Driven Resource Allocation in Edge-Fog Computing: Leveraging Digital Twins for Efficient Healthcare Systems

Author 1: Brahim Ould Cheikh Mohamed Nouh Author 2: Rafika Brahmi Author 3: Sidi Cheikh Author 4: Ridha Ejbali Author 5: Mohamedade Farouk Nanne

The evolution of healthcare, driven by remote monitoring and connected devices, is transforming medical service de-livery. Digital twins, virtual replicas of patients, enable continuous monitoring and predictive analysis. However, the rapid growth of real-time health data presents major challenges in resource allocation and processing, especially in cardiac event prediction scenarios… Read full abstract & cite →

Edge computing fog computing digital twin deep learning CNN-BiLSTM Deep Q-Network (DQN) resource allocation cardiac event prediction healthcare Artificial Intelligence (AI) Internet of Things (IoT) real-time

Abstract doi.org/10.14569/IJACSA.2025.01604101 PDF

102

Predicting Multiclass Java Code Readability: A Comparative Study of Machine Learning Algorithms

Author 1: Budi Susanto Author 2: Ridi Ferdiana Author 3: Teguh Bharata Adji

The classification of program code readability has traditionally focused on two target classes: readable and unreadable. Recently, it has evolved into a multiclass classification task in three categories: readable, neutral, and unreadable. Most of the existing approaches rely on deep learning. This study investigated the multiclass classification of Java code… Read full abstract & cite →

Code readability machine learning multiclass classification hyperparameter tuning future selection

Abstract doi.org/10.14569/IJACSA.2025.01604102 PDF

103

Deep Learning-Based UI Design Analysis: Object Detection and Image Retrieval Using YOLOv8

Author 1: Roba Alghamdi Author 2: Adel Ahmad Author 3: Fawaz alsaadi

Data-driven design models support various types of mobile application design, such as design search, promoting a better understanding of best practices and trends. Designing the well User Interface (UI) makes the application practical and easy to use and contributes significantly to the application’s success. Therefore, searching for UI design examples… Read full abstract & cite →

Data-driven design YOLOv8 design search deep learning user interface design

Abstract doi.org/10.14569/IJACSA.2025.01604103 PDF

104

Adversarial Attack on Autonomous Ships Navigation Using K-Means Clustering and CAM

Author 1: Ganesh Ingle Author 2: Kailas Patil Author 3: Sanjesh Pawale

As Maritime Autonomous Surface Ships (MASSs) increasingly become part of global maritime operations, the reliability and security of their object detection systems have become a major concern. These systems, which play a crucial role in identifying small yet critical maritime objects such as buoys, vessels, and kayaks, are particularly susceptible… Read full abstract & cite →

Maritime autonomous surface ships object detection clean-label poisoning attacks adversarial attacks

Abstract doi.org/10.14569/IJACSA.2025.01604104 PDF

105

NW Logistics: System Architecture and Design for Sustainable Road Logistics

Author 1: OUAHBI Younesse Author 2: ZITI Soumia

The logistics industry is under increasing pressure to reduce carbon emissions and enhance efficiency in response to environmental and regulatory demands. However, optimizing road logistics to achieve these goals requires innovative solutions that balance operational efficiency with sustain-ability. This study addresses this need by introducing NW Logistics, an AI-powered platform… Read full abstract & cite →

Artificial Intelligence logistics supply chain supply chain management applications Internet of Things road safety environnment

Abstract doi.org/10.14569/IJACSA.2025.01604105 PDF

106

A Robust Defense Mechanism Against Adversarial Attacks in Maritime Autonomous Ship Using GMVAE+RL

Author 1: Ganesh Ingle Author 2: Kailas Patil Author 3: Sanjesh Pawale

In this paper, we propose a robust defense frame-work combining Gaussian Mixture Variational Autoencoders (GMVAE) with Reinforcement Learning (RL) to counter adversarial attacks in Maritime Autonomous Systems, specifically targeting the Singapore Maritime Database. By modeling complex maritime data distributions through GMVAE and dynamically adapting decision boundaries via RL, our approach… Read full abstract & cite →

Maritime autonomous systems reinforcement learning defense mechanisms Gaussian Mixture Variational Auto encoder Singapore maritime database

Abstract doi.org/10.14569/IJACSA.2025.01604106 PDF

107

Evaluating the Performance of Tree-Based Model in Predicting Haze Events in Malaysia

Author 1: Mahiran Muhammad Author 2: Ahmad Zia Ul-Saufie Author 3: Fadhilah Ahmad Radi

Predicting haze is crucial in controlling air pollution to reduce its impact, especially on human health. Accurate prediction of extreme values is vital to raising public awareness of this issue and better understanding of air quality management. Extreme values in air pollution refer to unusually high measure-ments of pollutants that… Read full abstract & cite →

Extreme Gradient Boosting (XGBoost) Gradient Boosting Regression (GBR) Decision Tree (DT) extreme values Particulate Matter (PM)

Abstract doi.org/10.14569/IJACSA.2025.01604107 PDF

108

Towards Hybrid Meta-Heuristic Analysis for the Optimization of Fundamental Performance in Robotic Systems

Author 1: Boudour Dabbaghi Author 2: Faical Hamidi Author 3: Mohamed Aoun Author 4: Houssem Jerbi

This paper examines the concept of implementing a hybrid optimization approach through combining analytical and meta-heuristic approaches to improve the performance of practical engineering systems. Designed in support of artificial intelligence strategy, the proposed approach ensures high stability and efficiency under actuators saturation constraint. This is a well-known and sensitive… Read full abstract & cite →

Domain of Attraction (DA) Differential Algebraic Representation (DAR) meta-heuristic approach actuators saturation

Abstract doi.org/10.14569/IJACSA.2025.01604108 PDF

109

Optimizing Data Transmission and Energy Efficiency in Wireless Networks: A Comparative Study of GA, PSO, and Hybrid Approaches

Author 1: Suhare Solaiman

As wireless communication technology evolves, efficient resource allocation in Orthogonal Frequency Division Multiple Access (OFDMA) networks is becoming more important. This study looks at three resource allocation algorithms: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and a hybrid approach that combines both. The hybrid algorithm takes advantage of the strengths… Read full abstract & cite →

Resource allocation optimization genetic algorithms particle swarm optimization hybrid algorithm

Abstract doi.org/10.14569/IJACSA.2025.01604109 PDF

110

Enhancing Precision Agriculture with YOLOv8: A Deep Learning Approach to Potato Disease Identification

Author 1: Mohammed Aleinzi

Timely and precise identification of potato leaf diseases plays a critical role in improving crop productivity and reducing the impact of plant pathogens. Conventional detection techniques are often labor-intensive, dependent on expert anal-ysis, and may not be practical for widespread agricultural use. This paper introduces an automated detection system based… Read full abstract & cite →

Potato disease detection YOLOv8 Agriculture 4.0 deep learning

Abstract doi.org/10.14569/IJACSA.2025.01604110 PDF

111

Optimizing Medical Image Analysis: A Performance Evaluation of YOLO-Based Segmentation Models

Author 1: Haifa Alanazi

Instance segmentation is a critical component of medical image analysis, enabling tasks such as tissue and organ delineation, and disease detection. This paper provides a detailed comparative analysis of two fine-tuned one-stage object detection models, YOLOv11-seg and YOLOv9-seg, tailored for instance segmentation in medical imaging. Leveraging transfer learning, both models… Read full abstract & cite →

Medical image instance segmentation one-stage object detection models transfer learning nuclei detection

Abstract doi.org/10.14569/IJACSA.2025.01604111 PDF

112

Multitask Model with an Attention Mechanism for Sequentially Dependent Online User Behaviors to Enhance Audience Targeting

Author 1: Marwa Hamdi El-Sherief Author 2: Mohamed Helmy Khafagy Author 3: Asmaa Hashem Sweidan

This paper proposes a multitask learning approach with an attention mechanism to predict audience behavior as sequential actions. The goal is to improve click-through and conversion rates by effectively targeting audience behavior. The proposed model introduces specific task sets designed to address the challenges specific to each prediction task. In… Read full abstract & cite →

Multitask learning 1D convolution neural networks attention mechanism click through rate conversion rate audience behavioral targeting audience behavior

Abstract doi.org/10.14569/IJACSA.2025.01604112 PDF

113

Secure Optimization of RPL Routing in IoT Networks: Analysis of Metaheuristic Algorithms in the Face of Attacks

Author 1: Mansour Lmkaiti Author 2: Maryem Lachgar Author 3: Ibtissam Larhlimi Author 4: Houda Moudni Author 5: Hicham Mouncif

The security and efficiency of Internet of Things (IoT) networks depend on optimizing the routing protocol for low-power, lossy networks (LPNs) to manage various challenges, including expected number of transmissions (ETX), latency and energy consumption. This study proposes an advanced meta-heuristic optimization framework integrating several algorithms, including Particle Swarm Optimization… Read full abstract & cite →

IoT Security PSO MILP ARS2A simulated annealing RPL protocol metaheuristic techniques routing efficiency ETX latency energy consumption attack mitigation blackhole wormhole grayhole cyberattack

Abstract doi.org/10.14569/IJACSA.2025.01604113 PDF