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IJACSA Vol. 15 Issue 8 (2024)

Open Access | | 131 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

Ensemble Learning with Sleep Mode Management to Enhance Anomaly Detection in IoT Environment

Author 1: Khawlah Harahsheh Author 2: Rami Al-Naimat Author 3: Malek Alzaqebah Author 4: Salam Shreem Author 5: Esraa Aldreabi Author 6: Chung-Hao Chen

The rapid proliferation of Internet of Things (IoT) devices has underscored the critical need for energy-efficient cybersecurity measures. This presents the dual challenge of maintaining robust security while minimizing power consumption. Thus, this paper proposes enhancing the machine learning performance through Ensemble Techniques with Sleep Mode Management (ELSM) approach for… Read full abstract & cite →

IoT IDS machine learning ensemble technique sleep-awake cycle cybersecurity anomaly detection
Abstract doi.org/10.14569/IJACSA.2024.0150801 PDF
2

Optimizing Low-Resource Zero-Shot Event Argument Classification with Flash-Attention and Global Constraints Enhanced ALBERT Model

Author 1: Tongyue Sun Author 2: Jiayi Xiao

Event Argument Classification (EAC) is an essential subtask of event extraction. Most previous supervised models rely on costly annotations, and reducing the demand for computa-tional and data resources in resource-constrained environments is a significant challenge within the field. We propose a Zero-Shot EAC model, ALBERT-F, which leverages the efficiency of… Read full abstract & cite →

Artificial intelligence natural language processing event argument classification zero-shot learning flash-Attention global constraints low-resource
Abstract doi.org/10.14569/IJACSA.2024.0150802 PDF
3

A Personalized Hybrid Tourist Destination Recommendation System: An Integration of Emotion and Sentiment Approach

Author 1: Suphitcha Chanrueang Author 2: Sotarat Thammaboosadee Author 3: Hongnian Yu

This research introduces a personalized hybrid tourist destination recommendation system tailored for the growing trend of independent travel, which leverages social media data for trip planning. The system sets itself apart from traditional models by incorporating both emotional and sentiment data from social platforms to create customized travel experiences. The… Read full abstract & cite →

Recommendations hybrid recommendation system Collaborative Filtering Content-based Filtering social media data travel planning
Abstract doi.org/10.14569/IJACSA.2024.0150803 PDF
4

Automatic Identification and Evaluation of Rural Landscape Features Based on U-net

Author 1: Ling Sun Author 2: Jun Liu Author 3: Yi Qu Author 4: Jiashun Jiang Author 5: Bin Huang

The study delves into the landscape feature identification method and its application in Xijingyu Village, investigating landscape composition elements. Analyzing rural landscape structure holistically aids in dividing landscape characteristic zoning maps, essential for guiding rural landscape and territorial spatial planning. By utilizing GIS software for superposition analysis based on topography… Read full abstract & cite →

Rural landscape foreground area extraction deep learning phase unwrapping ResU-net
Abstract doi.org/10.14569/IJACSA.2024.0150804 PDF
5

Analysis of Customer Behavior Characteristics and Optimization of Online Advertising Based on Deep Reinforcement Learning

Author 1: Zhenyan Shang Author 2: Bi Ge

With the shift from traditional media to online advertising, real-time strategies have become crucial, evolving to meet contemporary demands. Advertisers strive to succeed in online advertising evaluations by demand-side platforms to secure display opportunities. Discrepancies in information evaluation can impact click-through rates, emphasizing the need for precise prediction models in… Read full abstract & cite →

Real-time online advertising ARMA-XGBoost model information asymmetry deep reinforcement learning decision-making behavior Transfer Learning
Abstract doi.org/10.14569/IJACSA.2024.0150805 PDF
6

Logistics Transportation Vehicle Monitoring and Scheduling Based on the Internet of Things and Cloud Computing

Author 1: Kang Wang Author 2: Xin Wang

This paper addresses challenges in the logistics industry, particularly information lag, inefficient resource allocation, and poor management, exacerbated by global economic integration and e-commerce growth. An advanced logistics and transportation vehicle monitoring and scheduling system is designed using IoT and cloud computing technologies. This system integrates Yolov5 for real-time vehicle… Read full abstract & cite →

Internet of Things cloud computing logistics and transportation vehicle monitoring vehicle scheduling
Abstract doi.org/10.14569/IJACSA.2024.0150806 PDF
7

Performance and Accuracy Research of the Large Language Models

Author 1: Nicoleta Cristina GAITAN

Starting with the end of 2022, there has been a massive global interest in Artificial Intelligence and, in particular, in the technology of large language models. These reduced the resolution of many problems dailies of varying degrees of complexity at a level accessible to every individual, whether it was an… Read full abstract & cite →

Large language models artificial intelligence ChatGPT natural language processing
Abstract doi.org/10.14569/IJACSA.2024.0150807 PDF
8

Image Generation Using StyleVGG19-NST Generative Adversarial Networks

Author 1: Dorcas Oladayo Esan Author 2: Pius Adewale Owolawi Author 3: Chunling Tu

Creating new image styles from the content of existing images is challenging to conventional Generative Adversarial Networks (GANs), due to their inability to generate high-quality image resolutions. The study aims to create top-notch images that seamlessly blend the style of one image with another without losing its style to artefacts… Read full abstract & cite →

Artworks VGG19 Neural Style Transfer Generative Adversarial Network inception score StyleGAN
Abstract doi.org/10.14569/IJACSA.2024.0150808 PDF
9

Applied to Art and Design Scene Visual Comprehension and Recognition Algorithm Research

Author 1: Yuxin Shi

Combining advanced intelligent algorithms to improve the scene visual understanding and recognition method for art design can not only provide more inspirations and creative materials for artists, but also improve the efficiency and quality of art creation, and provide scientific and accurate references of artworks. Focusing on the art design… Read full abstract & cite →

Art design scene visual understanding and recognition multilayer perceptron pond goose algorithm image dataset
Abstract doi.org/10.14569/IJACSA.2024.0150809 PDF
10

Quantitative Measurement and Preference Research of Urban Landscape Environmental Image Based on Computer Vision

Author 1: Yan Wang

At present, research on landscape preferences mostly uses traditional questionnaire surveys to obtain public aesthetic attitudes, and the analysis method still relies on manual coding with small sample sizes. However, the research on landscape preference of applying network big data and computer vision technology is rare, and the research content… Read full abstract & cite →

Computer vision urban landscape environmental image quantification measure
Abstract doi.org/10.14569/IJACSA.2024.0150810 PDF
11

Clustering Algorithms to Analyse Smart City Traffic Data

Author 1: Praveena Kumari M K Author 2: Manjaiah D H Author 3: Ashwini K M

Urban transportation systems encounter significant challenges in extracting meaningful traffic patterns from extensive historical datasets, a critical aspect of smart city initiatives. This paper addresses the challenge of analyzing and understanding these patterns by employing various clustering techniques on hourly urban traffic flow data. The principal aim is to develop… Read full abstract & cite →

Clustering smart city traffic analyze
Abstract doi.org/10.14569/IJACSA.2024.0150811 PDF
12

Prediction of Outpatient No-Show Appointments Using Machine Learning Algorithms for Pediatric Patients in Saudi Arabia

Author 1: Abdulwahhab Alshammari Author 2: Fahad Alotaibi Author 3: Sana Alnafrani

Patient no-shows are prevalent in pediatric outpatient visits, leading to underutilized medical resources, increased healthcare costs, reduced clinic efficiency, and decreased access to care. The use of machine learning techniques provides insights to mitigate this problem. This study aimed to develop a predictive model for patient no-shows at the Ministry… Read full abstract & cite →

No-show pediatric machine learning algorithms prediction outpatients
Abstract doi.org/10.14569/IJACSA.2024.0150812 PDF
13

Performance Optimization of Support Vector Machine with Adversarial Grasshopper Optimization for Heart Disease Diagnosis and Feature Selection

Author 1: Nan Tang Author 2: Lele Wang Author 3: Kangming Li Author 4: Zhen Liu Author 5: Yanan Dai Author 6: Ji Hao Author 7: Qingdui Zhang Author 8: Huamei Sun Author 9: Chunmei Qi

The World Health Organization reports that cardiac disorders result in approximately 1.02 million deaths. Over the last years, heart disorders, also known as cardiovascular diseases, have significantly influenced the medical sector due to their immense global impact and high level of danger. Unfortunately, accurate prognosis of heart problems or CD… Read full abstract & cite →

Heart disease predictions Support Vector Machine Grasshopper Optimization Algorithm feature selection
Abstract doi.org/10.14569/IJACSA.2024.0150813 PDF
14

Sleep Disorder Diagnosis Through Complex-Morlet-Wavelet Representation Using Bi-GRU and Self-Attention

Author 1: Mubarak Albathan

Sleep disorders pose notable health risks, impacting memory, cognitive performance, and overall well-being. Traditional polysomnography (PSG) used for sleep disorder diagnosis are complex and inconvenient due to complex multi-class representation of signals. This study introduces an automated sleep-disorder-detection method using electrooculography (EOG) and electroencephalography (EEG) signals to address the gaps… Read full abstract & cite →

Deep learning complex morlet wavelet bidirectional gated recurrent unit sleep stage detection multistage sleep disorder ensemble-bagged tree classifier
Abstract doi.org/10.14569/IJACSA.2024.0150814 PDF
15

Digital Landscape Architecture Design Combining 3D Image Reconstruction Technology

Author 1: Chen Chen

To achieve better digital landscape design and visual presentation effects, this study proposes a digital landscape design method based on improved 3D image reconstruction technology. Firstly, a precise point cloud registration algorithm combining normal distribution transformation and Trimmed iterative nearest point algorithm is proposed. A color texture method for 3D… Read full abstract & cite →

3D image reconstruction PSO gardens RGBD digital landscape
Abstract doi.org/10.14569/IJACSA.2024.0150815 PDF
16

Software Systems Documentation: A Systematic Review

Author 1: Abdullah A H Alzahrani

In the domain of software engineering, software documentation encompasses the methodical creation and management of artifacts describing software systems. Traditionally linked to software maintenance, its significance extends throughout the entire software development lifecycle. While often regarded as a quintessential indicator of software quality, the perception of documentation as a time-consuming… Read full abstract & cite →

Software engineering software systems documentation software maintenance software quality software development
Abstract doi.org/10.14569/IJACSA.2024.0150816 PDF
17

Optimizing Data Security in Computer-Assisted Test Applications Through the Advanced Encryption Standard 256-Bit Cipher Block Chaining

Author 1: M. Afridon Author 2: Agus Tedyyana Author 3: Fajar Ratnawati Author 4: Afis Julianto Author 5: M. Nur Faizi

In the digital education era, the importance of Computer-Assisted Test programs is underscored by their efficiency in conducting assessments. However, the increasing incidence of data breaches and cyberthreats has made the implementation of robust data protection measures imperative. This study explores the adoption of the Advanced Encryption Standard 256-bit Cipher… Read full abstract & cite →

AES256-CBC data security computer-assisted test academic integrity encryption standards digital assessment security
Abstract doi.org/10.14569/IJACSA.2024.0150817 PDF
18

Diabetes Prediction Using Machine Learning with Feature Engineering and Hyperparameter Tuning

Author 1: Hakim El Massari Author 2: Noreddine Gherabi Author 3: Fatima Qanouni Author 4: Sajida Mhammedi

Diabetes, a chronic illness, has seen an increase in prevalence over the years, posing several health challenges. This study aims to predict diabetes onset using the Pima Indians Diabetes dataset. We implemented several machine learning algorithms, namely Random Forest, Gradient Boosting, XGBoost, LightGBM, and CatBoost. To enhance model performance, we… Read full abstract & cite →

Machine learning feature engineering hyperparameter tuning diabetes prediction healthcare
Abstract doi.org/10.14569/IJACSA.2024.0150818 PDF
19

Computational Modeling of the Thermally Stressed State of a Partially Insulated Variable Cross-Section Rod

Author 1: Zhuldyz Tashenova Author 2: Elmira Nurlybaeva Author 3: Zhanat Abdugulova Author 4: Shirin Amanzholova Author 5: Nazira Zharaskhan Author 6: Aigerim Sambetova Author 7: Anarbay Kudaykulov

The formulation of the proposed methods and algorithms facilitates a comprehensive examination of intricate non-stationary thermo-mechanical processes in rods with varying cross-sectional geometries. Furthermore, it advances the theoretical framework for analyzing the thermo-mechanical properties of rod structures utilized in the machinery industry of the Republic of Kazakhstan. The creation of… Read full abstract & cite →

Heat flow heat transfer thermal expansion coefficient thermal conductivity modulus of elasticity
Abstract doi.org/10.14569/IJACSA.2024.0150819 PDF
20

Performance Analysis of a Hyperledger-Based Medical Record Data Management Using Amazon Web Services

Author 1: Mohammed K Elghoul Author 2: Sayed F. Bahgat Author 3: Ashraf S. Hussein Author 4: Safwat H. Hamad

Recently, there's been growing excitement around the innovative capabilities of blockchain technology, especially for enhancing security, privacy, and transparency. Its application in various sectors, like finance and logistics, is intriguing, but its potential in healthcare stands out. Specifically, in the realm of medical data management, blockchain can transform how we… Read full abstract & cite →

Hyperledger blockchain healthcare data management
Abstract doi.org/10.14569/IJACSA.2024.0150820 PDF
21

Enhancing Business Intelligence with Hybrid Transformers and Automated Annotation for Arabic Sentiment Analysis

Author 1: Wael M.S. Yafooz

Business is a key focus for many individuals, companies, countries and organisations. One effective way to enhance business performance is by analysing customer opinions through sentiment analysis. This technique offers valuable insights, known as business intelligence, which directly benefits business owners by informing their decisions and strategies. Substantial attention has… Read full abstract & cite →

Business intelligence machine learning sentiment analysis transformers BERT Arabic annotation
Abstract doi.org/10.14569/IJACSA.2024.0150821 PDF
22

A Method by Utilizing Deep Learning to Identify Malware Within Numerous Industrial Sensors on IoTs

Author 1: Ronghua MA

The industrial sensors of IoT is an emerging model, which combines Internet and the industrial physical smart objects. These objects belong to the broad domains like the smart homes, the smart cities, the processes of the industrial and the military, the agriculture and the business. Due to the substantial advancement… Read full abstract & cite →

Malware malware detection industrial sensors Internet of Things (IoTs) Deep Learning (DL)
Abstract doi.org/10.14569/IJACSA.2024.0150822 PDF
23

Quantifying the Effects of Homogeneous Interference on Coverage Quality in Wireless Sensor Networks

Author 1: Qingmiao Liu Author 2: Qiang Liu Author 3: Minhuan Wang

This study develops a coverage perception interference model for Wireless Sensor Networks, focusing on the challenges of homogeneous interference within Regions of Interest. Traditional perception models often overlook areas that, while covered, do not meet the required coverage standards for accurate classification. This model addresses both uncovered areas and those… Read full abstract & cite →

Wireless sensor networks homogeneous interference basic probability assignment coverage quality Dempster-Shafer theory
Abstract doi.org/10.14569/IJACSA.2024.0150823 PDF
24

Lightweight and Efficient High-Resolution Network for Human Pose Estimation

Author 1: Jiarui Liu Author 2: Xiugang Gong Author 3: Qun Guo

To address the challenges of high parameter quantities and elevated computational demands in high-resolution network, which limit their application on devices with constrained computational resources, we propose a lightweight and efficient high-resolution network, LE-HRNet. Firstly, we designs a lightweight module, LEblock, to extract feature information. LEblock leverages the Ghost module… Read full abstract & cite →

Human pose estimation model lightweighting Ghost module attention mechanism multi-scale feature fusion
Abstract doi.org/10.14569/IJACSA.2024.0150824 PDF
25

Enhanced Resume Screening for Smart Hiring Using Sentence-Bidirectional Encoder Representations from Transformers (S-BERT)

Author 1: Asmita Deshmukh Author 2: Anjali Raut

In a world inundated with resumes, the hiring process is often challenging, particularly for large organizations. HR professionals face the daunting task of manually sifting through numerous applications. This paper presents ‘Enhanced Resume Screening for Smart Hiring using Sentence-Bidirectional Encoder Representations from Transformers (S-BERT)’ to revolutionize this process. For HR… Read full abstract & cite →

S-BERT resume automated screening job CV
Abstract doi.org/10.14569/IJACSA.2024.0150825 PDF
26

Machine Learning Techniques for Protecting Intelligent Vehicles in Intelligent Transport Systems

Author 1: Yuan Chen

Intelligent transport system (ITS) is the development direction of future transport systems, in which intelligent vehicles are the key components. In order to protect the safety of intelligent vehicles, machine learning techniques are widely used in ITS. For intelligent protection in ITS, the study introduces an improved driving behaviour modelling… Read full abstract & cite →

Intelligent vehicle protection machine learning techniques Gaussian Process Regression convolutional neural networks long and short-term memory networks
Abstract doi.org/10.14569/IJACSA.2024.0150826 PDF
27

Automation of Book Categorisation Based on Network Centric Quality Management System

Author 1: Tingting Liu Author 2: Qiyuan Liu Author 3: Linya Fu

In order to improve the efficiency of automatic book classification, the study uses a crawler to crawl book data from regular websites and perform data cleaning and fusion to build a structured knowledge graph. Meanwhile, the processed data is applied to a pre-trained model to improve it, and migration learning… Read full abstract & cite →

Crawler books automated classification Recurrent Neural Network Multiple Attention Mechanism knowledge graphs
Abstract doi.org/10.14569/IJACSA.2024.0150827 PDF
28

Optimization of Distribution Routes in Agricultural Product Supply Chain Decision Management Based on Improved ALNS Algorithm

Author 1: Liling Liu Author 2: Yang Chen Author 3: Ao Li

The transportation of fresh agricultural products is not conducted along a sufficiently precise route, resulting in an extended transportation time for vehicles and a consequent deterioration in product freshness. Therefore, the study proposes an agricultural product transportation path optimization model based on an optimized adaptive large neighborhood search algorithm. The… Read full abstract & cite →

ALNS agricultural products path optimization cold chain transportation supply chain
Abstract doi.org/10.14569/IJACSA.2024.0150828 PDF
29

Harnessing Technology to Achieve the Highest Quality in the Academic Program of University Studies

Author 1: Rania Aboalela

This research aims to utilize information technology to improve education quality, particularly in higher education. A key contribution of this research is the application of generative artificial intelligence, specifically ChatGPT, to validate test questions that meet both international (ABET) and local (NCAAA) academic accreditation standards. The study was conducted within… Read full abstract & cite →

ChatGPT academic accreditations technology programs computer science Kingdom of Saudi Arabia website development NCAAA ABET
Abstract doi.org/10.14569/IJACSA.2024.0150829 PDF
30

Enhancing Digital Financial Security with LSTM and Blockchain Technology

Author 1: Thanyah Aldaham Author 2: Hedi HAMDI

The growing dependence on digital financial and banking transactions has brought about a significant focus on implementing strong security protocols. Blockchain technology has proved itself throughout the years to be a reliable solution upon which transactions can safely take place. This study explores the use of blockchain technology, specifically Ethereum… Read full abstract & cite →

Digital financing block chain ETC security anomaly detection machine learning LSTM
Abstract doi.org/10.14569/IJACSA.2024.0150830 PDF
31

Sketch and Size Orient Malicious Activity Monitoring for Efficient Video Surveillance Using CNN

Author 1: K. Lokesh Author 2: M. Baskar

Towards malicious activity monitoring in organizations, there exist several techniques and suffer with poor accuracy. To handle this issue, an efficient Sketch and Size orient malicious activity monitoring (SSMAM) is presented in this article. The model captures the video frames and performs segmentation to extract the features of frames as… Read full abstract & cite →

Video surveillance deep learning activity monitoring malicious activity SSMAM SSM
Abstract doi.org/10.14569/IJACSA.2024.0150831 PDF
32

Enhancing Arabic Phishing Email Detection: A Hybrid Machine Learning Based on Genetic Algorithm Feature Selection

Author 1: Amjad A. Alsuwaylimi

Recently, owing to widespread Internet use and technological breakthroughs, cyber-attacks have increased. One of the most common types of attacks is phishing, which is executed through email and is a leading cause of the recent surge in cyber-attacks. These attacks maliciously demand sensitive or private information from individuals and companies… Read full abstract & cite →

Machine learning phishing email BiLSTM Arabic content-based
Abstract doi.org/10.14569/IJACSA.2024.0150832 PDF
33

A Feature Interaction Based Neural Network Approach: Predicting Job Turnover in Early Career Graduates in South Korea

Author 1: Haewon Byeon

Predicting job turnover among early career university graduates is crucial for both employees and employers. This study introduced a Feature Interaction based Neural Network model designed to predict job turnover among university graduates in their 20s and 30s in South Korea within the first five years of employment. The FINN… Read full abstract & cite →

Job turnover prediction feature interaction based neural network employment data analysis predictive modeling university graduates
Abstract doi.org/10.14569/IJACSA.2024.0150833 PDF
34

A Systematic Review of Virtual Commerce Solutions for the Metaverse

Author 1: Ghazala Bilquise Author 2: Khaled Shaalan Author 3: Manar Alkhatib

The metaverse, a rapidly evolving field, promises to transform online shopping through immersive technologies. This systematic review aims to explore and analyze the key design features of Virtual Commerce (v-commerce) solutions within this digital environment. By examining 24 studies that have developed immersive v-commerce applications, this review seeks to compile… Read full abstract & cite →

Metaverse v-commerce immersive technologies design attributes
Abstract doi.org/10.14569/IJACSA.2024.0150834 PDF
35

DIAUTIS III: A Fuzzy and Affective Platform for Obtaining Autism Mental Models and Learning Aids

Author 1: Mohamed El Alami Author 2: Sara El khabbazi Author 3: Fernando de Arriaga

Autism spectrum disorders (ASD) are conditions characterized by social interaction and communication difficulties, atypical patterns of activities, and unusual reactions to sensations. Char-acteristics of autism may be detected in early childhood, but diagnosis is often delayed. The diagnosis of autistic children typically aligns with medical and psychological recommenda-tions, but it… Read full abstract & cite →

Fuzzy computing affective computing mental models learning aids autism category theory
Abstract doi.org/10.14569/IJACSA.2024.0150835 PDF
36

Stock Price Forecasting with Optimized Long Short-Term Memory Network with Manta Ray Foraging Optimization

Author 1: Zhongpo Gao Author 2: Junwen Jing

The stock market is a financial marketplace where investors may participate through the acquisition and sale of stocks in publicly traded companies. Predicting stock prices in the securities sector may be challenging due to the intricate nature of the subject, which necessitates a comprehensive grasp of several interconnected factors. Numerous… Read full abstract & cite →

Stock price hybrid forecasting method Manta Ray Foraging Optimization empirical mode decomposition Nasdaq index
Abstract doi.org/10.14569/IJACSA.2024.0150836 PDF
37

Modified TOPSIS Method for Neutrosophic Cubic Number Multi-Attribute Decision-Making and Applications to Music Composition Effectiveness Evaluation of Film and Television

Author 1: Liang Yang Author 2: Jun Zhao

Contemporary music composition for film and television has exhibited a trend towards diversification, which is reflected in various aspects such as the diversity of musical styles, the integration of music and visuals, as well as the technical means of music creation. With the continuous advancement of music production technology and… Read full abstract & cite →

Multi-Attribute Decision-Making (MADM) NCSs TOPSIS approach music composition effectiveness evaluation
Abstract doi.org/10.14569/IJACSA.2024.0150837 PDF
38

Heuristic Intelligent Algorithm-Based Approach for In-Depth Development and Application Analysis of Micro- and Nanoembedded Systems

Author 1: Buzhong Liu

Developing application analysis and testing methods is an important part of the in-depth development of micro-nano embedded systems under complex integrated architectures. Therefore, the research on application analysis and testing models is of great significance for the in-depth development and efficient design of embedded systems. In order to fully explore… Read full abstract & cite →

Photon search algorithm deep development of micro- and nanoembedded systems application test and analysis methodology LightGBM
Abstract doi.org/10.14569/IJACSA.2024.0150838 PDF
39

Optimization of Knitting Path of Flat Knitting Machine Based on Reinforcement Learning

Author 1: Tianqi Yang

In the textile industry, the flat knitting machine plays a crucial role as a production tool, and the quality of its weaving path is closely related to the overall product quality and production efficiency. Seeking to improve and optimize the knitting path to improve product effectiveness and productivity has become… Read full abstract & cite →

Flat knitting machine reinforcement learning weaving path optimization textile industry
Abstract doi.org/10.14569/IJACSA.2024.0150839 PDF
40

Design and Research of Cross-Border E-Commerce Short Video Recommendation System Based on Multi-Modal Fusion Transformer Model

Author 1: Yiran Hu

This study designed a cross-border e-commerce short video recommendation system based on Transformer's multimodal analysis model. When mining associations, the model not only focuses on the relationships between modalities, but also improves semantic context by addressing contextual correlations within and between modalities. At the same time, the model uses a… Read full abstract & cite →

Multimodal fusion transformer model cross-border e-commerce short video recommendation system
Abstract doi.org/10.14569/IJACSA.2024.0150840 PDF
41

A Hidden Markov Model-Based Performance Recognition System for Marching Wind Bands

Author 1: Wei Jiang

This paper explores the automatic recognition of marching band performances using advanced music information retrieval techniques. Music, a crucial medium for emotional expression and cultural exchange, greatly benefits from the harmonic backing provided by marching wind orchestras. Identifying these performances manually is both time-consuming and labor-intensive, particularly for non-professionals. This… Read full abstract & cite →

Music information retrieval Hidden Markov Model feature extraction automatic music recognition marching band performance PCP features
Abstract doi.org/10.14569/IJACSA.2024.0150841 PDF
42

Fitness Equipment Design Based on Web User Text Mining

Author 1: Jinyang Xu Author 2: Xuedong Zhang Author 3: Xinlian Li Author 4: Shun Yu Author 5: Yanming Chen

To propose home fitness equipment that meets modern users' needs, this study employs web user text mining, combined with the Fuzzy Analytic Hierarchy Process (FAHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), to design and evaluate home fitness equipment that aligns with contemporary demands. First… Read full abstract & cite →

Home fitness equipment crawler data FAHP TOPSIS product design
Abstract doi.org/10.14569/IJACSA.2024.0150842 PDF
43

Evaluating the Impact of Fuzzy Logic Controllers on the Efficiency of FCCUs: Simulation-Based Analysis

Author 1: Harsh Pagare Author 2: Kushagra Mishra Author 3: Kanhaiya Sharma Author 4: Sandeep Singh Rawat Author 5: Shailaja Salagrama

This study investigates the methods for creating nonlinear models and developing Fuzzy logic controllers for the Fluidized Catalytic Cracking Unit (FCCU) at different global refineries. The FCCU plays a crucial role in the petrochemical sector, processing a significant portion of the world's crude oil - in 2006, FCCUs were responsible… Read full abstract & cite →

Non-Linear modeling fuzzy logic controller machine learning optimization
Abstract doi.org/10.14569/IJACSA.2024.0150843 PDF
44

Hybrid Machine Learning Approach for Real-Time Malicious URL Detection Using SOM-RMO and RBFN with Tabu Search

Author 1: Swetha T Author 2: Seshaiah M Author 3: Hemalatha K L Author 4: Murthy S V N Author 5: Manjunatha Kumar BH

The proliferation of malicious URLs has become a significant threat to internet security, encompassing SPAM, phishing, malware, and defacement attacks. Traditional detection methods struggle to keep pace with the evolving nature of these threats. Detecting malicious URLs in real-time requires advanced techniques capable of handling large datasets and identifying novel… Read full abstract & cite →

Malicious URL detection self-organizing map Radial Movement Optimization ensemble radial basis function network Tabu Search
Abstract doi.org/10.14569/IJACSA.2024.0150844 PDF
45

Missing Value Imputation in Data MCAR for Classification of Type 2 Diabetes Mellitus and its Complications

Author 1: Anik Andriani Author 2: Sri Hartati Author 3: Afiahayati Author 4: Cornelia Wahyu Danawati

Type 2 diabetes mellitus (T2DM) is a disease that is at risk for many complications. Previous research on the prognosis of T2DM and its complications is limited to the impact of T2DM on one particular disease. Guidebook for T2DM Management in Indonesia has eight categories of T2DM complications. The purpose… Read full abstract & cite →

Missing value prognosis of diabetes mellitus missing completely at random decision tree
Abstract doi.org/10.14569/IJACSA.2024.0150845 PDF
46

Optimizing Dance Training Programs Using Deep Learning: Exploring Motion Feedback Mechanisms Based on Pose Recognition and Prediction

Author 1: Yuting Jiao

Dance pose recognition and prediction is an important part of dance training and a challenging task in the field of artificial intelligence. Due to the diverse styles and significant variations in dance movements, conventional methods struggle to capture effective dance pose features for recognition. In this context, we have developed… Read full abstract & cite →

Deep learning pose recognition pose prediction dance training graph convolutional network attention mechanism
Abstract doi.org/10.14569/IJACSA.2024.0150846 PDF
47

Improved Decision Support System for Alzheimer's Diagnosis Using a Hybrid Machine Learning Approach with Structural MRI Brain Scans

Author 1: Niranjan Kumar Parvatham Author 2: Lakshmana Phaneendra Maguluri

Alzheimer's disease (AD) causes damage to brain cells and their activities. This disease is typically caused by ageing, making people over the age of 65 more susceptible. As the disease progresses, it slowly destroys brain cells, making it harder to think clearly, recall things, and do everyday tasks. The end… Read full abstract & cite →

Alzheimer’s disease binary classification Convolutional Neural Network (CNN) horizontal flipping healthcare decision support system MRI images Support Vector Machine(SVM)
Abstract doi.org/10.14569/IJACSA.2024.0150847 PDF
48

Innovative Melanoma Diagnosis: Harnessing VI Transformer Architecture

Author 1: Sreelakshmi Jayasankar Author 2: T. Brindha

Melanoma, the most severe type of skin cancer, ranks ninth among the most prevalent cancer types. Prolonged exposure to ultraviolet radiation triggers mutations in melanocytes, the pigment -producing cells responsible for melanin production. This excessive melanin secretion leads to the formation of dark-colored moles, which can evolve into cancerous tumors… Read full abstract & cite →

Vision transformer melanoma convolutional neural networks deep learning model transformer encoder dermoscopy image
Abstract doi.org/10.14569/IJACSA.2024.0150848 PDF
49

Enhancing Safety for High Ceiling Emergency Light Monitoring

Author 1: G. X. Jun Author 2: M. Batumalay Author 3: C. Batumalai Author 4: Prabadevi B

The performance of information technology has gradually improved and advanced during this period for safety management. Nonetheless, there is no disputing that during power outages, emergency lights continue to be crucial to people's safety and comfort. Regrettably, businesses don't give emergency lighting in buildings enough thought. The primary causes of… Read full abstract & cite →

Safety management Internet of Things high ceiling safety high building safety safety process innovation
Abstract doi.org/10.14569/IJACSA.2024.0150849 PDF
50

Data-Driven Approaches to Energy Utilization Efficiency Enhancement in Intelligent Logistics

Author 1: Xuan Long

With the rapid development of intelligent logistics, new challenges and opportunities are presented for energy utilization efficiency improvement. This study explores the feasibility and effectiveness of using data-driven methods to improve energy utilization efficiency in an intelligent logistics environment and provides theoretical support and practical guidance for achieving the sustainable… Read full abstract & cite →

Intelligent logistics energy utilization efficiency data-driven
Abstract doi.org/10.14569/IJACSA.2024.0150850 PDF
51

Design and Application of the DPC-K-Means Clustering Algorithm for Evaluation of English Teaching Proficiency

Author 1: Mei Niu

Effective and precise methodologies for evaluating the proficiency in English language instruction are instrumental in enhancing educators' competencies and the effectiveness of educational administrative processes. The objective of this paper is to refine the neutrality and precision of such assessments by introducing a novel approach that leverages an advanced K-means… Read full abstract & cite →

K-Means density-peak clustering algorithm ELT competency assessment convolutional neural network
Abstract doi.org/10.14569/IJACSA.2024.0150851 PDF
52

Enhancing Indonesian Text Summarization with Latent Dirichlet Allocation and Maximum Marginal Relevance

Author 1: Muhammad Faisal Author 2: Bima Hamdani Mawaridi Author 3: Ashri Shabrina Afrah Author 4: Supriyono Author 5: Yunifa Miftachul Arif Author 6: Abdul Aziz Author 7: Linda Wijayanti Author 8: Melisa Mulyadi

Maximum Marginal Relevance (MMR) Summarization of text is very important in grasping quickly long articles particularly for people who are very busy. In this paper, we use LDA to give topic queries for news articles, which then become inputs to the MMR method. According to this paper's summarization system, the… Read full abstract & cite →

Indonesian summarization LDA MMR ROUGE evaluation
Abstract doi.org/10.14569/IJACSA.2024.0150852 PDF
53

Research on Traffic Flow Prediction Using the MSTA-GNet Model Based on the PeMS Dataset

Author 1: Deng Cong

This study introduces the MSTA-GNet (Multi-Scale Spatiotemporal Attention Graph Network), a novel deep learning model which integrates spatiotemporal self-attention mechanisms to model heterogeneous dependencies in traffic networks. The primary objective of the study is to improve existing traffic flow prediction models to address the inadequacies of traditional models in complex… Read full abstract & cite →

MSTA-GNet deep learning PeMS dataset traffic flow prediction
Abstract doi.org/10.14569/IJACSA.2024.0150853 PDF
54

Laboratory Abnormal Behavior Recognition Method Based on Skeletal Features

Author 1: Dawei Zhang

The identification of abnormal laboratory behavior is of great significance for the safety monitoring and management of laboratories. Traditional identification methods usually rely on cameras and other equipment, which are costly and prone to privacy leakage. In the process of human body recognition, they are easily affected by various factors… Read full abstract & cite →

Skeletal features abnormal behavior recognition OpenPose algorithm Kinect sensor Discrete Fourier Transform
Abstract doi.org/10.14569/IJACSA.2024.0150854 PDF
55

Twitter Truth: Advanced Multi-Model Embedding for Fake News Detection

Author 1: Yasmine LAHLOU Author 2: Sanaa El FKIHI Author 3: Rdouan FAIZI

The identification of fake news represents a substantial challenge within the context of the accelerated dissemination of digital information, most notably on social media and online platforms. This study introduces a novel approach, entitled " MT-FND: Multi-Model Embedding Approach to Fake News Detection," which is designed to enhance the detection… Read full abstract & cite →

Fake news detection transformer-based models text classification sentiment analysis
Abstract doi.org/10.14569/IJACSA.2024.0150855 PDF
56

Protein-Coding sORFs Prediction Based on U-Net and Coordinate Attention with Hybrid Encoding

Author 1: Ziling Wang Author 2: Wenxi Yang Author 3: Zhijian Qu

Small proteins encoded by small open reading frames (sORFs) exhibit significant biological activity in crucial biological processes such as embryonic development and metabolism. Accurately predicting whether sORFs encode small proteins is a key challenge in current research. To address this challenge, many methods have been proposed, however, existing methods rely… Read full abstract & cite →

Small open reading frames deep learning hybrid coding U-Net coordinate attention
Abstract doi.org/10.14569/IJACSA.2024.0150856 PDF
57

An Improved YOLOv8 Method for Measuring the Body Size of Xinjiang Bactrian Camels

Author 1: Yue Peng Author 2: Alifu Kurban Author 3: Mengmei Sang

Camel body size measurement has initially been applied in livestock production. However, current methods suffer from low measurement accuracy due to detection box localization loss and occlusions. This study proposes an effective algorithm, Camel-YOLOv8, specifically designed for detecting Xinjiang Bactrian camels and calculating their body sizes. By integrating the Selective… Read full abstract & cite →

YOLOv8 Asymptotic Feature Pyramid Network SKAttention Bactrian camel body size measurement
Abstract doi.org/10.14569/IJACSA.2024.0150857 PDF
58

Towards Secure Internet of Things-Enabled Healthcare: Integrating Elliptic Curve Digital Signatures and Rivest Cipher Encryption

Author 1: Longyang Du Author 2: Tian Xie

The expansion of Internet of Things (IoT) applications, such as wireless sensor networks, intelligent devices, Internet technologies, and machine-to-machine interaction, has changed current information technology in recent decades. The IoT enables the exchange of information and communication between items via an internal network. Nevertheless, the advancement of technology raises the… Read full abstract & cite →

IoT-enabled healthcare data privacy security hybrid security framework SHA-256 RC4 encryption data integrity
Abstract doi.org/10.14569/IJACSA.2024.0150858 PDF
59

Dose Archiving and Communication System in Moroccan Healthcare: A Unified Approach to X-Ray Dose Management and Analysis

Author 1: Lhoucine Ben Youssef Author 2: Abdelmajid Bybi Author 3: Hilal Drissi Author 4: El Ayachi Chater

This study explores the implementation of a Dose Archiving and Communication System (DACS) in Moroccan healthcare, highlighting the importance of X-ray dose management in modern radiology. It emphasizes patient safety and the ALARA principle to minimize radiation exposure while maintaining diagnostic accuracy. The research discusses advancements in imaging technologies, such… Read full abstract & cite →

DACS Real-time monitoring radiation protection radiology practice healthcare professionals x-ray doses regulatory compliance patient safety Moroccan healthcare
Abstract doi.org/10.14569/IJACSA.2024.0150859 PDF
60

UTAUT Model for Digital Mental Health Interventions: Factors Influencing User Adoption

Author 1: Mohammed Alojail

The impact of digital revolution on mental health therapies is examined in this research. As explained in the paper, the delivery of mental healthcare is being revolutionized by digital transformation, which is providing creative answers to the problems associated with mental health illnesses. But knowing and managing user approval is… Read full abstract & cite →

Digital transformation mental health interventions UTAUT model TAM SmartPLS user acceptance hypothesis testing
Abstract doi.org/10.14569/IJACSA.2024.0150860 PDF
61

ResNet50 and GRU: A Synergistic Model for Accurate Facial Emotion Recognition

Author 1: Shanimol. A Author 2: J Charles

Humans use voice, gestures, and emotions to communicate with one another. It improves oral communication effectiveness and facilitates concept of understanding. Majority of people are able to identify facial emotions with ease, regardless of gender, nationality, culture, or ethnicity. The recognition of facial expressions is becoming more and more significant… Read full abstract & cite →

Deep convolutional neural network ResNet-50 Facial Emotion Recognition Gated Recurrent Unit
Abstract doi.org/10.14569/IJACSA.2024.0150861 PDF
62

Efficient Parallel Algorithm for Extracting Fuzzy-Crisp Formal Concepts

Author 1: Ebtesam Shemis Author 2: Arabi Keshk Author 3: Ammar Mohammed Author 4: Gamal Elhady

Fuzzy Formal Concept Analysis (FFCA) is a robust mathematical tool for analyzing data, particularly where uncertainty or fuzziness is inherent. FFCA is utilized across various domains, including data mining, information retrieval, and knowledge representation. However, fuzzy concepts extraction is a crucial yet computationally intensive task. This paper addresses the challenge… Read full abstract & cite →

Fuzzy Formal Concept Analysis single-sided fuzzy concept fuzzy-crisp concepts parallel algorithm fuzzy concepts extraction knowledge representation
Abstract doi.org/10.14569/IJACSA.2024.0150862 PDF
63

Automatic Plant Disease Detection System Using Advanced Convolutional Neural Network-Based Algorithm

Author 1: Sai Krishna Gudepu Author 2: Vijay Kumar Burugari

With technology innovations such as Artificial Intelligence (AI) and Internet of Things (IoT), unprecedented applications and solutions to real world problems are made possible. Precision agriculture is one such problem which is aimed at technology driven agriculture. So far, the research on agriculture and usage of technologies are at government… Read full abstract & cite →

Plant disease detection advanced CNN Artificial Intelligence (AI) deep learning precision agriculture
Abstract doi.org/10.14569/IJACSA.2024.0150863 PDF
64

Towards Secure Cloud-Enabled Wireless Ad-Hoc Networks: A Novel Cross-Layer Validation Mechanism

Author 1: Zhenguo LIU

Network security tackles a broad spectrum of damaging activities that threaten network infrastructure. Addressing these risks is essential to keep data accurate and networks running. This research aims to detect and prevent blackholes and wormholes in cloud-based wireless ad-hoc networks. A new Cross-Layer Validation Mechanism (CLVM) is introduced to detect… Read full abstract & cite →

Network security wireless ad-hoc networks cloud environments cross-layer validation blackhole and wormhole attacks
Abstract doi.org/10.14569/IJACSA.2024.0150864 PDF
65

UWB Printed MIMO Antennas for Satellite Sensing System (SRSS) Applications

Author 1: Wyssem Fathallah Author 2: Chafai Abdelhamid Author 3: Chokri Baccouch Author 4: Alsharef Mohammad Author 5: Khalil Jouili Author 6: Hedi Sakli

The deployment of ultra-wideband (UWB) technology offers enhanced capabilities for various Internet of Things (IoT) applications, including smart cities, smart buildings, smart aggregation, and smart healthcare. UWB technology supports high data rate communication over short distances with very low power densities. This paper presents a UWB printed antenna design with… Read full abstract & cite →

5G antenna 5G satellite networks millimeter band wireless communications SRR IoT
Abstract doi.org/10.14569/IJACSA.2024.0150865 PDF
66

Novel Data-Driven Machine Learning Models for Heating Load Prediction: Single and Optimized Naive Bayes

Author 1: Fangyuan Li

Numerous approaches can be employed to create models for assessing the heat gains of a building arising from both external and internal sources. This modeling process evaluates effective operational strategies, conducts retrofit audits, and projects energy consumption. These techniques range from simple regression analyses to more intricate models grounded in… Read full abstract & cite →

Prediction models heating load demand building energy consumption Naive Bayes metaheuristic optimization algorithms
Abstract doi.org/10.14569/IJACSA.2024.0150866 PDF
67

Facial Expression Real-Time Animation Simulation Technology for General Mobile Platforms Based on OpenGL

Author 1: Mingzhe Cao

With the popularization and development of mobile devices, the demand for image processing continues to increase. However, the limited hardware resources of mobile devices make traditional CPU computing unable to meet the requirements of real-time image processing. In response to the limited rendering resources of mobile platforms, this study adopts… Read full abstract & cite →

OpenGL mobile platform facial expressions animation simulation rendering
Abstract doi.org/10.14569/IJACSA.2024.0150867 PDF
68

Noise Reduction Techniques in Adas Sensor Data Management: Methods and Comparative Analysis

Author 1: Ahmed Alami Author 2: Fouad Belmajdoub

This review examines noise reduction techniques in Advanced Driver Assistance Systems (ADAS) sensor data management, crucial for enhancing vehicle safety and performance. ADAS relies on real-time data from conventional sensors (e.g., wheel speed sensors, LiDAR, radar, cameras) and MEMS sensors (e.g., accelerometers, gyroscopes) to execute critical functions like lane keeping… Read full abstract & cite →

ADAS sensor data management noise reduction KalmanNet Wavelet Denoising RADAR SMA EMA LPF HIL bench testing
Abstract doi.org/10.14569/IJACSA.2024.0150868 PDF
69

DMMFnet: A Dual-Branch Multimodal Medical Image Fusion Network Using Super Token and Channel-Spatial Attention

Author 1: Yukun Zhang Author 2: Lei Wang Author 3: Muhammad Tahir Author 4: Zizhen Huang Author 5: Yaolong Han Author 6: Shanliang Yang Author 7: Shilong Liu Author 8: Muhammad Imran Saeed

Multimodal medical image fusion leverages the correlation between different modal images to enhance the information contained within a single medical image. Existing fusion methods often fail to effectively extract multiscale features from medical images and establish long-distance relationships between deep feature blocks. To address these issues, we propose DMMFnet, an… Read full abstract & cite →

Medical image fusion channel-spatial attention super token sampling encoder–decoder
Abstract doi.org/10.14569/IJACSA.2024.0150869 PDF
70

Deep Learning and Computer Vision-Based System for Detecting and Separating Abnormal Bags in Automatic Bagging Machines

Author 1: Trung Dung Nguyen Author 2: Thanh Quyen Ngo Author 3: Chi Kien Ha

This paper presents a novel deep learning and computer vision-based system for detecting and separating abnormal bags within automatic bagging machines, addressing a key challenge in industrial quality control. The core of our approach is the development of a data collection system seamlessly integrated into the production line. This system… Read full abstract & cite →

Automatic bagging machines deep learning computer vision bags classification data augmentation
Abstract doi.org/10.14569/IJACSA.2024.0150870 PDF
71

Implementing Optimization Methods into Practice to Enhance the Performance of Solar Power Systems

Author 1: Luçiana Toti Author 2: Alma Stana Author 3: Alma Golgota Author 4: Eno Toti

The use of contemporary technological tools, as well as the modernization of curricula in the field of electronic and electrical engineering, is one of the main objectives of the academic staff at the Universities. Efforts to improve curricula and scientific research infrastructure find strong support from the CBHE programs funded… Read full abstract & cite →

Optimization photovoltaic systems education performance controller SIMULINK
Abstract doi.org/10.14569/IJACSA.2024.0150871 PDF
72

Combined Framework for Type-2 Neutrosophic Number Multiple-Attribute Decision-Making and Applications to Quality Evaluation of Digital Agriculture Park Information System

Author 1: Wei Ji Author 2: Ning Sun Author 3: Botao Cao Author 4: Xichan Mu

A digital agriculture park refers to an agricultural production and organizational unit of a certain scale where digital technology is used to optimize the agricultural supply chain. It enhances park management and service levels, achieving a new development model characterized by safe, low-carbon, high-quality, high-yield, precise, and efficient production, management… Read full abstract & cite →

Multiple-Attribute Decision-Making (MADM) Type-2 Neutrosophic Numbers (T2NNs) ExpTODIM approach TOPSIS approach quality evaluation
Abstract doi.org/10.14569/IJACSA.2024.0150872 PDF
73

Using Pretrained VGG19 Model and Image Segmentation for Rice Leaf Disease Classification

Author 1: Gulbakhram Beissenova Author 2: Almira Madiyarova Author 3: Akbayan Aliyeva Author 4: Gulsara Mambetaliyeva Author 5: Yerzhan Koshkarov Author 6: Nagima Sarsenbiyeva Author 7: Marzhan Chazhabayeva Author 8: Gulnara Seidaliyeva

This study explores the application of the VGG19 convolutional neural network (CNN) model, pre-trained on ImageNet, for the classification of rice crop diseases using image segmentation techniques. The research aims to enhance disease detection accuracy by integrating a robust deep learning framework tailored to the specific challenges of agricultural pathology… Read full abstract & cite →

Rice crop diseases convolutional neural networks VGG19 model image segmentation disease classification data augmentation model generalization sustainable farming
Abstract doi.org/10.14569/IJACSA.2024.0150873 PDF
74

Blockchain-Based Vaccination Record Tracking System

Author 1: Shwetha G K Author 2: Jayantkumar A Rathod Author 3: Naveen G Author 4: Mounesh Arkachari Author 5: Pushparani M K

Blockchain technology is basically a decentralized database maintained by applicable parties and has been extensively used in colorful scripts similar as logistics and finance. In terms of operations in the medical field, it's getting increasingly important because the case's symptoms may be related to a certain vaccine. Whether the case… Read full abstract & cite →

Blockchain technology decentralized vaccine record tracking integrity smart contracts vaccination record storage traceability
Abstract doi.org/10.14569/IJACSA.2024.0150874 PDF
75

Enhance the Security of the Cloud Using a Hybrid Optimization-Based Proxy Re-Encryption Technique Considered Blockchain

Author 1: Ahmed I. Alutaibi

Every day, a vast amount of data with incalculable value will be generated by the IoT devices that are deployed in various types of applications. It is crucial to ensure the reliability and safety of IoT data exchange in a cloud context because this data frequently contains the user's private… Read full abstract & cite →

Cloud security Internet of Things proxy re-encryption blockchain data sharing hybrid optimization
Abstract doi.org/10.14569/IJACSA.2024.0150875 PDF
76

Malicious Website Detection Using Random Forest and Pearson Correlation for Effective Feature Selection

Author 1: Esha Sangra Author 2: Renuka Agrawal Author 3: Pravin Ramesh Gundalwar Author 4: Kanhaiya Sharma Author 5: Divyansh Bangri Author 6: Debadrita Nandi

In recent years, the internet has expanded rapidly, driving significant advancements in digitalization that have transformed day to day lives. Its growing influence on consumers and the economy has increased the risk of cyberattacks. Cybercriminals exploited network misconfigurations and security vulnerabilities during these transitions. Among countless cyberattacks, phishing remains the… Read full abstract & cite →

Malicious URL machine learning feature selection Random Forest cybercrime
Abstract doi.org/10.14569/IJACSA.2024.0150876 PDF
77

Enhancing Orchard Cultivation Through Drone Technology and Deep Stream Algorithms in Precision Agriculture

Author 1: P. Srinivasa Rao Author 2: Anantha Raman G R Author 3: Madira Siva Sankara Rao Author 4: K. Radha Author 5: Rabie Ahmed

The integration of cutting-edge technology in agriculture has revolutionized traditional farming practices, paving the way for Smart Agriculture. This research presents a novel approach to enhancing the cultivation of orchard crops by combining deep-stream algorithms with drone technology. Focusing on pomegranate farming, the study employs a drone system with four… Read full abstract & cite →

Smart agriculture crops cultivation deep stream algorithms drone and technology
Abstract doi.org/10.14569/IJACSA.2024.0150877 PDF
78

Comparative Analysis of Small and Medium-Sized Enterprises Cybersecurity Program Assessment Model

Author 1: Wan Nur Eliana Wan Mohd Ludin Author 2: Masnizah Mohd Author 3: Wan Fariza Paizi@Fauzi

In the digital age, Small and Medium-sized Enterprises must review and improve their cybersecurity posture to combat rising risks. This paper thoroughly compares Small and Medium-sized Enterprises cybersecurity program assessment approaches. The National Institute of Standards and Technology's Cybersecurity Framework, CyberSecurity Readiness Model for SMEs, Cybersecurity Evaluation Model, and Adaptable… Read full abstract & cite →

Cybersecurity SMEs cybersecurity program assessment models cybersecurity assessment frameworks
Abstract doi.org/10.14569/IJACSA.2024.0150878 PDF
79

Real-Time Robotic Force Control for Automation of Ultrasound Scanning

Author 1: Ungku Muhammad Zuhairi Ungku Zakaria Author 2: Seri Mastura Mustaza Author 3: Mohd Hairi Mohd Zaman Author 4: Ashrani Aizzuddin Abd Rahni

Ablation represents a minimally invasive option for liver cancer treatment, commonly guided by imaging techniques such as ultrasound. Recently, there has been a surge in interest in semi-automated or fully automated robotic image acquisition. Specifically, there is a continuing interest in automating medical ultrasound image acquisition due to ultrasound being… Read full abstract & cite →

Real-time position control force control ROS collaborative robot admittance control kinematics dynamic tool center point damping
Abstract doi.org/10.14569/IJACSA.2024.0150879 PDF
80

Deep Learning Model for Enhancing Automated Recycling Machine with Incentive Mechanisms

Author 1: Razali Tomari Author 2: Aeslina Abdul Kadir Author 3: Wan Nurshazwani Wan Zakaria Author 4: Dipankar Das Author 5: Muhamad Bakhtiar Azni

Automated Recycling Machine (ARM) can be defined as an interactive tool to flourish recycling culture among community by providing incentive to the user that deposit the recyclable items. To enable this, the machine crucially needs a material validation module to identify the deposited recyclable items. Utilizing combination of sensors for… Read full abstract & cite →

Recycling machine You Only Look Once (YOLO) vision system interactive recycling deep learning
Abstract doi.org/10.14569/IJACSA.2024.0150880 PDF
81

A Hybrid of Extreme Learning Machine and Cellular Neural Network Segmentation in Mangrove Fruit Classification

Author 1: Romi Fadillah Rahmat Author 2: Opim Salim Sitompul Author 3: Maya Silvi Lydia Author 4: Fahmi Author 5: Shifani Adriani Ch Author 6: Pauzi Ibrahim Nainggolan Author 7: Riza Sulaiman

Mangroves are a collection of plants that inhabit the intertidal zone, namely the area between the lowest and highest points reached by the tide. Overall, mangroves provide a range of advantages, including the prevention of coastal erosion, the inhibition of seawater intrusion onto land leading to brackish groundwater, and serving… Read full abstract & cite →

Mangroves mangrove conservation image processing ecological informatics cellular neural network extreme learning machine
Abstract doi.org/10.14569/IJACSA.2024.0150881 PDF
82

Evaluating the Impact of Yoga Practices to Improve Chronic Venous Insufficiency Symptoms: A Classification by Gaussian Process

Author 1: Feng Yun Gou

Chronic Venous Insufficiency (CVI) is a widespread condition marked by diverse venous system irregularities stemming from occlusion and varicosities. Factors like family history and lifestyle choices amplify CVI's economic consequences, emphasizing the need for proactive measures. The sedentary lifestyle of many individuals can contribute to various diseases, including CVI. Yoga… Read full abstract & cite →

Chronic venous insufficiency yoga Gaussian Process Classifier Crystal Structure Algorithm Fire Hawk Optimizer
Abstract doi.org/10.14569/IJACSA.2024.0150882 PDF
83

A Semantic Segmentation Method for Road Scene Images Based on Improved DeeplabV3+ Network

Author 1: Lihua Bi Author 2: Xiangfei Zhang Author 3: Shihao Li Author 4: Canlin Li

Semantic segmentation of road scenes plays a crucial role in many fields such as autonomous driving, intelligent transportation systems and urban planning. Through the precise identification and segmentation of elements such as roads, pedestrians, vehicles, and traffic signs, the system can better understand the surrounding environment and make safe and… Read full abstract & cite →

Image enhancement attention mechanism semantic segmentation road scene images
Abstract doi.org/10.14569/IJACSA.2024.0150883 PDF
84

Enhancing Tuberculosis Diagnosis and Treatment Outcomes: A Stacked Loopy Decision Tree Approach Empowered by Moth Search Algorithm Optimization

Author 1: Huma Khan Author 2: Mithun DSouza Author 3: K. Suresh Babu Author 4: Janjhyam Venkata Naga Ramesh Author 5: K. R. Praneeth Author 6: Pinapati Lakshmana Rao

Chest X-ray imaging is the main tool for detecting tuberculosis (TB), providing essential information about pulmonary abnormalities that may indicate the presence of the disease. Still, manual interpretation is a common component of older diagnostic methods, and it may be laborious and subjective. The development of sophisticated machine learning methods… Read full abstract & cite →

Tuberculosis (TB) chest x-ray stacked loopy decision trees (SLDT) moth search algorithm (MSA) medical imaging
Abstract doi.org/10.14569/IJACSA.2024.0150884 PDF
85

Complex Environmental Localization of Scenic Spots by Integrating LANDMARC Localization System and Traditional Location Fingerprint Localization

Author 1: Shasha Song Author 2: Cong Li

The scenic spot contains complex and changeable indoor and outdoor environments, some of which may be difficult to work effectively due to signal occlusion, multipath effect and other factors. In response to this problem, this paper proposes a method of Location Identification Based on the Dynamic Active Radio Frequency IDentification… Read full abstract & cite →

LANDMARC localization system fingerprint localization environmental localization scenic spot
Abstract doi.org/10.14569/IJACSA.2024.0150885 PDF
86

Development of a 5G-Optimized MIMO Antenna with Enhanced Isolation Using Neutralization Line and SRRs Metamaterials

Author 1: Chaker Essid Author 2: Linda Chouikhi Author 3: Alsharef Mohammad Author 4: Bassem Ben Salah Author 5: Hedi Sakli

This paper presents the design of a Multiple Input Multiple Output (MIMO) antenna intended for 5G wireless applications operating in the 3.5 GHz frequency range. The MIMO system consists of two adjacent antennas, measuring 100 mm × 80 mm × 1.6 mm, with spacing between radiating elements equal to one-eighth… Read full abstract & cite →

5G antenna MIMO SRRs metamaterials isolation IOT neutralization line (NL)
Abstract doi.org/10.14569/IJACSA.2024.0150886 PDF
87

Deep Learning Fusion for Intracranial Hemorrhage Classification in Brain CT Imaging

Author 1: Padma Priya S. Babu Author 2: T. Brindha

Brain hemorrhages are characterized by the rupture in the arteries of brain due blood clotting or high blood pressure (BP), presents a significant risk of traumatic injury or even death. This bleeding results in the damage in brain cells, with common causes including brain tumors, aneurysm, blood vessel abnormalities, amyloid… Read full abstract & cite →

Intracranial hemorrhage deep learning DenseNet 121 LSTM brain CT images
Abstract doi.org/10.14569/IJACSA.2024.0150887 PDF
88

Romanian Sign Language and Mime-Gesture Recognition

Author 1: Enachi Andrei Author 2: Turcu Cornel Author 3: George Culea Author 4: Sghera Bogdan Constantin Author 5: Ungureanu Andrei Gabriel

This paper presents a comprehensive approach to Romanian Sign Language (RSL) recognition using machine learning techniques. The primary focus is on developing and evaluating a robust model capable of accurately classifying hand and mime gestures representative of RSL and converting it into speech through an application. Utilizing a dataset of… Read full abstract & cite →

RSL sign language machine learning model mime gestures
Abstract doi.org/10.14569/IJACSA.2024.0150888 PDF
89

Multiclass Osteoporosis Detection: Enhancing Accuracy with Woodpecker-Optimized CNN-XGBoost

Author 1: Mithun DSouza Author 2: Divya Nimma Author 3: Kiran Sree Pokkuluri Author 4: Janjhyam Venkata Naga Ramesh Author 5: Suresh Babu Kondaveeti Author 6: Lavanya Kongala

In the realm of medical diagnostics, accurately identifying osteoporosis through multiclass classification poses a significant challenge due to the subtle variations in bone density and structure. This study proposes a novel approach to enhance detection accuracy by integrating the Woodpecker Optimization Algorithm with a hybrid Convolutional Neural Network (CNN) and… Read full abstract & cite →

Osteoporosis detection multiclass classification Woodpecker Optimization Algorithm Convolutional Neural Network (CNN) XGBoost
Abstract doi.org/10.14569/IJACSA.2024.0150889 PDF
90

Attention-Based Joint Learning for Intent Detection and Slot Filling Using Bidirectional Long Short-Term Memory and Convolutional Neural Networks

Author 1: Yusuf Idris Muhammad Author 2: Naomie Salim Author 3: Sharin Hazlin Huspi Author 4: Anazida Zainal

Effective natural language understanding is crucial for dialogue systems, requiring precise intent detection and slot filling to facilitate interactions. Traditionally, these subtasks have been addressed separately, but their interconnection suggests that joint solutions yield better results. Recent neural network-based approaches have shown significant performance in joint intent detection and slot… Read full abstract & cite →

Joint learning intent detection slot filling multichannel
Abstract doi.org/10.14569/IJACSA.2024.0150890 PDF
91

Attention-Based Deep Learning Approach for Pedestrian Detection in Self-Driving Cars

Author 1: Wael Ahmad AlZoubi Author 2: Girish Bhagwant Desale Author 3: Sweety Bakyarani E Author 4: Uma Kumari C R Author 5: Divya Nimma Author 6: K Swetha Author 7: B Kiran Bala

Autonomous vehicle safety relies heavily on the ability to accurately detect pedestrians, as this capability is crucial for preventing accidents and saving lives. Pedestrian recognition is particularly challenging in the dynamic and complex environments of urban areas. Effective pedestrian detection is crucial for ensuring road safety in autonomous vehicles. Current… Read full abstract & cite →

Pedestrian recognition autonomous vehicle safety deep learning attention mechanism Bidirectional Gated Recurrent Units
Abstract doi.org/10.14569/IJACSA.2024.0150891 PDF
92

Cryptographic Techniques in Digital Media Security: Current Practices and Future Directions

Author 1: Gongling ZHANG

Content privacy and unauthorized access to copyrighted digital media content are common in the dynamic, fast-paced digitalized media marketplace. Cryptographic methods are the foundation of modern digital media security, and they must ensure the security, integrity, and authenticity of digital media data. This article analyses cryptographic methods that are used… Read full abstract & cite →

Digital media cryptographic content security digital rights management watermarking blockchain
Abstract doi.org/10.14569/IJACSA.2024.0150892 PDF
93

Detecting Online Gambling Promotions on Indonesian Twitter Using Text Mining Algorithm

Author 1: Reza Bayu Perdana Author 2: Ardin Author 3: Indra Budi Author 4: Aris Budi Santoso Author 5: Amanah Ramadiah Author 6: Prabu Kresna Putra

This study addresses the pressing challenge of detecting online gambling promotions on Indonesian Twitter using text mining algorithms for text classification and analytics. Amid limited research on this subject, especially in the Indonesian context, we aim to identify common textual features used in gambling promotions and determine the most effective… Read full abstract & cite →

Social media analytics online gambling intention classification
Abstract doi.org/10.14569/IJACSA.2024.0150893 PDF
94

Securing RPL Networks with Enhanced Routing Efficiency with Congestion Prediction and Load Balancing Strategy

Author 1: Saumya Raj Author 2: Rajesh R

Low power and Lossy Networks (LLNs) are essential components of the Internet of Things (IoT) environment. In LNNs, the Routing Protocol for LLN (RPL)-based Internet Protocol Version 6 (IPv6) routing protocol is regarded as a standardized solution. However, the existing models did not account for the issues with congestion and… Read full abstract & cite →

Low power and Lossy Network (LLN) Routing Protocol for LLN (RPL) load balancing Internet of Things (IoT) Internet Protocol Version 6 (IPv6)
Abstract doi.org/10.14569/IJACSA.2024.0150894 PDF
95

Optimizing Hyperparameters in Machine Learning Models for Accurate Fitness Activity Classification in School-Aged Children

Author 1: Britsel Calluchi Arocutipa Author 2: Magaly Villegas Cahuana Author 3: Vanessa Huanca Hilachoque Author 4: Marco Cossio Bolaños

Classification using machine learning algorithms in physical fitness tests carried out by students in educational centers can help prevent obesity and other related diseases. This research aims to evaluate physical fitness using percentiles of the tests and machine learning algorithms with hyperparameter optimization. The process followed was knowledge discovery in… Read full abstract & cite →

Machine learning classification physical fitness schoolchildren hyperparameters
Abstract doi.org/10.14569/IJACSA.2024.0150895 PDF
96

Modeling Micro Traffic Flow Phenomena Based on Vehicle Types and Driver Characteristics Using Cellular Automata and Monte Carlo

Author 1: Tri Harsono Author 2: Kohei Arai

The modeling of micro traffic flow on a highway has been extensively observed and studied in various aspects, such as driver characteristics in car-following and lane-changing behaviors. Regarding car-following and lane-changing, an interesting aspect is how to model the movement conditions of vehicles on a highway that exhibit unique characteristics… Read full abstract & cite →

Micro traffic flow driver characteristics cellular automata Monte Carlo
Abstract doi.org/10.14569/IJACSA.2024.0150896 PDF
97

Convolutional Neural Network Model for Cacao Phytophthora Palmivora Disease Recognition

Author 1: Jude B. Rola Author 2: Jomari Joseph A. Barrera Author 3: Maricel V. Calhoun Author 4: Jonah Flor Oraño – Maaghop Author 5: Magdalene C. Unajan Author 6: Joshua Mhel Boncalon Author 7: Elizabeth T. Sebios Author 8: Joy S. Espinosa

Cacao, scientifically known as Theobroma cacao, is a highly nutritious food and is extensively utilized in multiple sectors, including agriculture and health. Nevertheless, the agricultural sector encounters notable obstacles as a result of Cacao disease such as pod rot, predominantly attributed to the Phytophthora genus. The objective of this work… Read full abstract & cite →

Machine-learning Convolutional Neural Network detection of P. palmivora
Abstract doi.org/10.14569/IJACSA.2024.0150897 PDF
98

Leveraging Mechanomyography Signal for Quantitative Muscle Spasticity Assessment of Upper Limb in Neurological Disorders Using Machine Learning

Author 1: Muhamad Aliff Imran Daud Author 2: Asmarani Ahmad Puzi Author 3: Shahrul Na’im Sidek Author 4: Ahmad Anwar Zainuddin Author 5: Ismail Mohd Khairuddin Author 6: Mohd Azri Abdul Mutalib

Upper motor neuron syndrome is characterised by spasticity, which represents a neurological disability that can be found in several disorders such as cerebral palsy, amyotrophic lateral sclerosis, stroke, brain injury, and spinal cord injury. Muscle spasticity is always assessed by therapists using conventional methods involving passive movement and assigning spasticity… Read full abstract & cite →

Spasticity mechanomyography Modified Ashworth Scale machine learning
Abstract doi.org/10.14569/IJACSA.2024.0150898 PDF
99

Interactive Color Design Based on AR Virtual Implantation Technology Between Users and Artificial Intelligence

Author 1: Jun Ma Author 2: Ying Chen

To achieve user interactive color design, this study takes furniture color interactive design as an example, introduces artificial intelligence and augmented reality virtual implantation technology, allowing users to design furniture colors and styles according to their own ideas. By improving cyclic consistency to generate adversarial networks, furniture image style transfer… Read full abstract & cite →

Artificial intelligence AR virtual implantation technology color style transfer furniture
Abstract doi.org/10.14569/IJACSA.2024.0150899 PDF
100

A Comprehensive Authentication Taxonomy and Lightweight Considerations in the Internet-of-Medical-Things (IoMT)

Author 1: Azlina Ahmadi Julaihi Author 2: Md Asri Ngadi Author 3: Raja Zahilah binti Raja Mohd Radzi

The potential of Internet-of-Things (IoT) in healthcare is evident in its ability to connect medical equipment, sensors, and healthcare personnel to provide high-quality medical expertise in remote locations. The constraints faced by these devices such as limited storage, power, and energy resources necessitate the need for a lightweight authentication mechanism… Read full abstract & cite →

Lightweight authentication Aggregated Authentication’ Multi-Factor Authentication (MFA) Internet-of-Medical Things (IoMT)
Abstract doi.org/10.14569/IJACSA.2024.01508100 PDF
101

Dynamic Simulation and Forecasting of Spatial Expansion in Small and Medium-Sized Cities Using ANN-CA-Markov Models

Author 1: Chengquan Gao

This study utilizes the ANN-CA-Markov (Artificial Neural Network-Cellular Automata-Markov) model to address spatial planning and expansion challenges in China’s small and medium-sized cities. With China’s urbanization rate reaching 59.58% in 2018 and expected to hit 70% by 2030, the country is entering a mid-stage of urbanization, leading to rapid expansion… Read full abstract & cite →

ANN-CA Markov small and medium-sized cities spatial planning
Abstract doi.org/10.14569/IJACSA.2024.01508101 PDF
102

Advanced IoT-Enabled Indoor Thermal Comfort Prediction Using SVM and Random Forest Models

Author 1: Nurtileu Assymkhan Author 2: Amandyk Kartbayev

Predicting thermal comfort within indoor environments is essential for enhancing human health, productivity, and well-being. This study uses interdisciplinary approaches, integrating insights from engineering, psychology, and data science to develop sophisticated machine learning models that predict thermal comfort. Traditional methods often depend on subjective human input and can be inefficient… Read full abstract & cite →

Heating building energy management thermal comfort IoT Support Vector Machine Random Forest
Abstract doi.org/10.14569/IJACSA.2024.01508102 PDF
103

Exploration of Deep Semantic Analysis and Application of Video Images in Visual Communication Design Based on Multimodal Feature Fusion Algorithm

Author 1: Yanlin Chen Author 2: Xiwen Chen

Fully utilizing image and video semantic processing techniques can play a more effective role in visual communication design. In order to further explore the application of multimodal feature fusion algorithm (MFF) in video image feature analysis in visual communication design, with the aim of enhancing the depth and breadth of… Read full abstract & cite →

Video semantics understanding visual communication design
Abstract doi.org/10.14569/IJACSA.2024.01508103 PDF
104

A Deep Reinforcement Learning (DRL) Based Approach to SFC Request Scheduling in Computer Networks

Author 1: Eesha Nagireddy

This study investigates the use of Deep Reinforcement Learning (DRL) to minimize the latency between the source and destination of Service Function Chaining (SFC) requests in Neural Networks. The approach utilizes Deep-Q-Network (DQN) reinforcement learning to determine the shortest path between two nodes using the Greedy-Simulated Annealing (GSA) Dijkstra's Algorithm… Read full abstract & cite →

RL models SFC chain Deep-Q-Network Dijkstra’s algorithm
Abstract doi.org/10.14569/IJACSA.2024.01508104 PDF
105

Improving Automatic Short Answer Scoring Task Through a Hybrid Deep Learning Framework

Author 1: Soumia Ikiss Author 2: Najima Daoudi Author 3: Manar Abourezq Author 4: Mostafa Bellafkih

An automatic short-answer scoring system involves using computational techniques to automatically evaluate and score student answers based on a given question and desired answer. The increasing reliance on automated systems for assessing student responses has highlighted the need for accurate and reliable short-answer scoring mechanisms. This research aims to improve… Read full abstract & cite →

Student answer automatic scoring BERT language model LSTM neural network Natural Language Processing
Abstract doi.org/10.14569/IJACSA.2024.01508105 PDF
106

BlockChain and Deep Learning with Dynamic Pattern Features for Lung Cancer Diagnosis

Author 1: A. Angel Mary Author 2: K. K. Thanammal

Cancers in the respiratory tract grow out of control in lung carcinoma, a deadly disease. Because cancers have irregular shapes, it can be challenging to diagnose them and determine their sizes and forms from imaging studies. Furthermore, a serious issue with health image inquiry is large disparity. Artificial intelligence and… Read full abstract & cite →

Lung cancer spiking convolutional neural network LIDC-IDRI CLAHE Honey Badger optimization Algorithm segmentation classification
Abstract doi.org/10.14569/IJACSA.2024.01508106 PDF
107

Application of Improved CSA Algorithm-Based Fuzzy Logic in Computer Network Control Systems

Author 1: Jianxi Yu

In the past few years, with the high-speed popularization of computers and the widespread use of smart phones and mobile devices, the Internet has gradually become an indispensable part of people's daily lives. The Internet is constantly driving the process of digital society and providing people with more convenient and… Read full abstract & cite →

CSA computer network fuzzy logic principal component analysis method network operation situation awareness
Abstract doi.org/10.14569/IJACSA.2024.01508107 PDF
108

Application of Sanda-Assisted Teaching System Integrating VR Technology from a 5G Perspective

Author 1: Zhaoquan Zhang Author 2: Yong Ding

Since the focus of Sanda teaching is to allow students to master martial arts techniques through confrontational exercises, Sanda teaching in colleges and universities commonly adopts contextualized teaching methods. However, this Sanda teaching method suffers from deficiencies such as poor teaching effectiveness and difficulty in reflecting the effectiveness of Sanda… Read full abstract & cite →

VR technology Sanda teaching system motion recognition feature extraction
Abstract doi.org/10.14569/IJACSA.2024.01508108 PDF
109

Data Collection Method Based on Data Perception and Positioning Technology in the Context of Artificial Intelligence and the Internet of Things

Author 1: Xinbo Zhao Author 2: Fei Fei

Wireless sensor networks are an important technical form of the underlying network of the Internet of Things. The energy of each node in the network is finite. When a node runs out of energy, it can cause network interruptions, which can affect the reliability of data collection. To reduce the… Read full abstract & cite →

Wireless sensor network data collection compression perception technology Sparse Bayesian Learning signal reconstruction
Abstract doi.org/10.14569/IJACSA.2024.01508109 PDF
110

Hyperparameter Optimization in Transfer Learning for Improved Pathogen and Abiotic Plant Disease Classification

Author 1: Asha Rani K P Author 2: Gowrishankar S

The application of machine learning, particularly through image-based analysis using computer vision techniques, has greatly improved the management of crop diseases in agriculture. This study explores the use of transfer learning to classify both spreadable and non-spreadable diseases affecting soybean, lettuce, and banana plants, with a special focus on various… Read full abstract & cite →

Spreadable diseases non-spreadable diseases transfer learning Keras optimizers CNN underfitting and overfitting retraining the models base models finetuning abiotic biotic infectious and non-infectious diseases custom optimization techniques hyperparameter tuning in neural networks hybrid activation functions
Abstract doi.org/10.14569/IJACSA.2024.01508110 PDF
111

Design and Application of Intelligent Visual Communication System for User Experience

Author 1: Chao Peng

The design and application of visual communication system should be human-oriented, but currently this is often ignored by designers, resulting in poor user experience of visual communication. In order to improve the experience effect of visual communication system, combined with the existing computer technology, this paper proposes an intelligent visual… Read full abstract & cite →

Visual communication system user experience-oriented multimodal features recommendation algorithm
Abstract doi.org/10.14569/IJACSA.2024.01508111 PDF
112

Synchronous Update and Optimization Method for Large-Scale Image 3D Reconstruction Technology Under Cloud-Edge Fusion Architecture

Author 1: Jian Zhang Author 2: Jingbin Luo Author 3: Yilong Chen

Aiming at the problems of limited bandwidth and network delay in the traditional centralized cloud computing mode during large-scale image processing of transmission and distribution digital corridors, a synchronous updating and optimization method for large-scale image 3D reconstruction technology under cloud-edge fusion architecture is proposed. Based on the cloud-side fusion… Read full abstract & cite →

Cloud-edge fusion cloud-edge collaboration 3D reconstruction synchronized update
Abstract doi.org/10.14569/IJACSA.2024.01508112 PDF
113

The Application of Anti-Collision Algorithms in University Records Management

Author 1: Ying Wang Author 2: Ying Mi

University records management has grown in importance as a result of the quick growth of big data, artificial intelligence, and other technologies. However, university archives management is prone to data loss, redundancy, and errors. Moreover, the use of scientific management systems and algorithms can effectively improve such problems. To create… Read full abstract & cite →

Anti-collision algorithms archive management systems information networks RFID technology
Abstract doi.org/10.14569/IJACSA.2024.01508113 PDF
114

Advancements in Deep Learning Architectures for Image Recognition and Semantic Segmentation

Author 1: Divya Nimma Author 2: Arjun Uddagiri

This paper focuses on using Convolutional Neural Networks (CNNs) for tasks such as image classification. It covers both pre-trained models and those that are built from scratch. The paper begins by demonstrating how to utilize the well-known AlexNet model, which is highly effective for image recognition due to transfer learning… Read full abstract & cite →

Convolutional Neural Networks (CNNs) AlexNet image classification transfer learning MNIST Dataset Custom CNN Architecture deep learning model training and evaluation neural network optimization activation functions feature extraction machine learning pattern recognition data preprocessing loss functions model accuracy
Abstract doi.org/10.14569/IJACSA.2024.01508114 PDF
115

Optimized Retrieval and Secured Cloud Storage for Medical Surgery Videos Using Deep Learning

Author 1: Megala G Author 2: Swarnalatha P

Efficient secured storage and retrieval of medical surgical videos are essential for modern healthcare systems. Traditional methods often struggle with scalability, accessibility, and data security, necessitating innovative solutions. This study introduces a novel deep learning-based framework that leverages a hybrid algorithm combining a Variational Autoencoder (VAE) and Group Lasso for… Read full abstract & cite →

Medical video storage feature selection Variational Auto Encoder (VAE) weighted-graph-based prefetching algorithm group lasso
Abstract doi.org/10.14569/IJACSA.2024.01508115 PDF
116

Rolling Bearing Reliability Prediction Based on Signal Noise Reduction and RHA-MKRVM

Author 1: Yifan Yu

In order to solve the problem of reliability assessment and prediction of rolling bearings, a noise reduction method (CEEMDAN-GRCMSE) based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN) combined with generalized refined composite multi-scale sample entropy (GRCMSE) is proposed from the vibration signals to remove the noise from the… Read full abstract & cite →

Rolling bearing reliability evaluation and pre-diction complete ensemble empirical mode decomposition with adaptive noise generalized refined composite multi-scale sample entropy uniform manifold approximation and projection red-tailed hawk algorithm mixed kernel relevance vector machine
Abstract doi.org/10.14569/IJACSA.2024.01508116 PDF
117

EiAiMSPS: Edge Inspired Artificial Intelligence-based Multi Stakeholders Personalized Security Mechanism in iCPS for PCS

Author 1: Swati Devliyal Author 2: Sachin Sharma Author 3: Himanshu Rai Goyal

Artificial Intelligence (AI) is becoming more prevalent in the healthcare sector like in pharmaceutical care to achieve rapid and precise outcomes. Machine learning techniques are critical in preserving this balance since they ensure both the confidentiality and authenticity of healthcare data. Early sickness projections benefit clinicians when establishing early monetary… Read full abstract & cite →

Internet of things pharmaceutical care machine learning authentication artificial intelligence
Abstract doi.org/10.14569/IJACSA.2024.01508117 PDF
118

Integrated IoT-Driven System with Fuzzy Logic and V2X Communication for Real-Time Speed Monitoring and Accident Prevention in Urban Traffic

Author 1: Khadiza Tul Kubra Author 2: Tajim Md. Niamat Ullah Akhund Author 3: Waleed M. Al-Nuwaiser Author 4: Md Assaduzzaman Author 5: Md. Suhag Ali Author 6: M. Mesbahuddin Sarker

Road safety is a critical concern globally, with speeding being a leading cause of traffic accidents. Leveraging advanced technologies can significantly enhance the ability to monitor and control vehicle speeds in real time. Traditional methods of speed monitoring are often limited in their ability to provide real-time, adaptive interventions. Existing… Read full abstract & cite →

Internet of Things high-speed monitoring alcohol detection matlab simulation write FIS
Abstract doi.org/10.14569/IJACSA.2024.01508118 PDF
119

TGMoE: A Text Guided Mixture-of-Experts Model for Multimodal Sentiment Analysis

Author 1: Xueliang Zhao Author 2: Mingyang Wang Author 3: Yingchun Tan Author 4: Xianjie Wang

Multimodal sentiment analysis seeks to determine the sentiment polarity of targets by integrating diverse data types, including text, visual, and audio modalities. However, during the process of multimodal data fusion, existing methods often fail to adequately analyze the sentimental relationships between different modalities and overlook the varying contributions of different… Read full abstract & cite →

Multimodal fusion sentiment analysis cross modal mixture of experts
Abstract doi.org/10.14569/IJACSA.2024.01508119 PDF
120

A Simple and Efficient Approach for Extracting Object Hierarchy in Image Data

Author 1: Saravit Soeng Author 2: Vungsovanreach Kong Author 3: Munirot Thon Author 4: Wan-Sup Cho Author 5: Tae-Kyung Kim

An object hierarchy in images refers to the structured relationship between objects, where parent objects have one or more child objects. This hierarchical structure is useful in various computer vision applications, such as detecting motorcycle riders without helmets or identifying individuals carrying illegal items in restricted areas. However, extracting object… Read full abstract & cite →

Object hierarchy object relationship object detection computer vision
Abstract doi.org/10.14569/IJACSA.2024.01508120 PDF
121

Priority-Based Service Provision Using Blockchain, Caching, Reputation and Duplication in Edge-Cloud Environments

Author 1: Tarik CHANYOUR Author 2: Seddiq EL KASMI ALAOUI Author 3: Mohamed EL GHMARY

The integration of Multi-access Edge Computing (MEC) and Dense Small Cell (DSC) infrastructures within 5G and beyond networks marks a substantial leap forward in communication technologies. This convergence is critical for meeting the stringent low latency demands of services delivered to Smart Devices (SDs) through lightweight containers. This paper introduces… Read full abstract & cite →

Multi-access Edge-cloud Computing container base image chunks replication fragmentation service provision blockchain Markov approximation
Abstract doi.org/10.14569/IJACSA.2024.01508121 PDF
122

A Data Augmentation Approach to Sentiment Analysis of MOOC Reviews

Author 1: Guangmin Li Author 2: Long Zhou Author 3: Qiang Tong Author 4: Yi Ding Author 5: Xiaolin Qi Author 6: Hang Liu

To address the lack of Chinese online course review corpora for aspect-based sentiment analysis, we pro-pose Semantic Token Augmentation and Replacement (STAR), a semantic-relative distance-based data augmentation method. STAR leverages natural language processing techniques such as word embedding and semantic similarity to extract high-frequency words near aspect terms, learns their… Read full abstract & cite →

Data augmentation sentiment analysis MOOC natural language processing deep learning
Abstract doi.org/10.14569/IJACSA.2024.01508122 PDF
123

Design and Implementation of Style-Transfer Operations in a Game Engine

Author 1: Haechan Park Author 2: Nakhoon Baek

The image style transfer operations are a kind of high-level image processing techniques, in which a target image is transformed to show a given style. These kind of operations are typically acquired with modern neural network models. In this paper, we aim to achieve the image style-transfer operations in real… Read full abstract & cite →

Style transfer neural network models game engine rendering textures real-time operations
Abstract doi.org/10.14569/IJACSA.2024.01508123 PDF
124

Under Sampling Techniques for Handling Unbalanced Data with Various Imbalance Rates: A Comparative Study

Author 1: Esraa Abu Elsoud Author 2: Mohamad Hassan Author 3: Omar Alidmat Author 4: Esraa Al Henawi Author 5: Nawaf Alshdaifat Author 6: Mosab Igtait Author 7: Ayman Ghaben Author 8: Anwar Katrawi Author 9: Mohmmad Dmour

Unbalanced data sets represent data sets that contain an unequal number of examples for different classes. This dataset represents a problem faced by machine learning tools; as in datasets with high imbalance ratios, false negative rate per-centages will be increased because most classifiers will be affected by the major class… Read full abstract & cite →

Clusters centroid decision tree neighborhood cleaning rule random under sampling Tomek Link under sampling unbalanced datasets
Abstract doi.org/10.14569/IJACSA.2024.01508124 PDF
125

Multiclass Chest Disease Classification Using Deep CNNs with Bayesian Optimization

Author 1: Maneet Kaur Bohmrah Author 2: Harjot Kaur

Ever since its outbreak, numerous research studies have been initiated worldwide as an attempt for an accurate and efficient diagnosis of COVID-19. In the recent past, patients suffering from various chronic lung diseases, either passed away due to COVID-19 or Pneumonia. Both of these pulmonary diseases are strongly correlated as… Read full abstract & cite →

Deep neural networks machine learning Bayesian optimization image preprocessing COVID-19 pneumonia
Abstract doi.org/10.14569/IJACSA.2024.01508125 PDF
126

Preprocessing Techniques for Clustering Arabic Text: Challenges and Future Directions

Author 1: Tahani Almutairi Author 2: Shireen Saifuddin Author 3: Reem Alotaibi Author 4: Shahendah Sarhan Author 5: Sarah Nassif

Arabic is a complex language for text analysis because of its orthographic features, rich synonyms, and semantic style. Thus, Arabic text must be prepared more carefully in the preprocessing stage for the analyzer to improve the quality of the results. Moreover, many preprocessing steps have been proposed to improve the… Read full abstract & cite →

Arabic preprocessing Arabic language survey clustering Arabic analysis
Abstract doi.org/10.14569/IJACSA.2024.01508126 PDF
127

Impact of Emojis Exclusion on the Performance of Arabic Sarcasm Detection Models

Author 1: Ghalyah Aleryani Author 2: Wael Deabes Author 3: Khaled Albishre Author 4: Alaa E. Abdel-Hakim

The complex challenge of detecting sarcasm in Arabic speech on social media is exacerbated by the language’s diversity and the nature of sarcastic expressions. There is a significant gap in the capability of existing models to effectively interpret sarcasm in Arabic, necessitating more sophisticated and precise detection methods. In this… Read full abstract & cite →

Arabic language AraBERT sarcasm detecting data preprocessing emojis impact social media content
Abstract doi.org/10.14569/IJACSA.2024.01508127 PDF
128

A Configurable Framework for High-Performance Graph Storage and Mutation

Author 1: Soukaina Firmli Author 2: Dalila Chiadmi Author 3: Kawtar Younsi Dahbi

In the realm of graph processing, efficient storage and update mechanisms are crucial due to the large volume of graphs and their dynamic nature. Traditional data structures such as adjacency lists and matrices, while effective in certain scenarios, often suffer from performance trade-offs such as high memory consumption or slow… Read full abstract & cite →

Data structures concurrency graph processing graph mutations high-performance computing traffic management
Abstract doi.org/10.14569/IJACSA.2024.01508128 PDF
129

Detecting Malware on Windows OS Using AI Classification of Extracted Behavioral Features from Images

Author 1: Nooraldeen Alhamedi Author 2: Kang Dongshik

In this research, using dynamic analysis ten critical features were extracted from malware samples operating in isolated virtual machines. These features included process ID, name, user, CPU usage, network connections, memory usage, and other pertinent parameters. The dataset comprised 50 malware samples and 11 benign programs, providing a data for… Read full abstract & cite →

Malware analysis dynamic analysis image classification malware behavior extraction text
Abstract doi.org/10.14569/IJACSA.2024.01508129 PDF
130

The Impact of Virtual Collaboration Tools on 21st-Century Skills, Scientific Process Skills and Scientific Creativity in STEM

Author 1: Nur Atiqah Jalaludin Author 2: Mohamad Hidir Mhd Salim Author 3: Mohamad Sattar Rasul Author 4: Athirah Farhana Muhammad Amin Author 5: Mohd Aizuddin Saari

Virtual collaboration tools have become increasingly important in STEM education, especially after the COVID-19 pandemic. These tools offer many benefits, including developing 21st-century skills and fostering scientific process skills and scientific creativity. However, there are concerns regarding their effectiveness across different genders and regions. This study evaluates the impact of… Read full abstract & cite →

Virtual collaboration tools 21st-century skills scientific process skills scientific creativity STEM education
Abstract doi.org/10.14569/IJACSA.2024.01508130 PDF
131

The Impact of E-Commerce Drivers on the Innovativeness in Organizational Practices

Author 1: Abdulghader Abu Reemah A Abdullah Author 2: Ibrahim Mohamed Author 3: Nurhizam Safie Mohd Satar

Innovation in e-commerce practices has revolution-ized the way goods and services are purchased or sold online. This relatively new tool for online transaction provides range of access to wealth of information and knowledge needed to facilitate electronic commerce globally using internet network. The case is not the same in the… Read full abstract & cite →

E-commerce innovation e-commerce drivers performance management decision making management style
Abstract doi.org/10.14569/IJACSA.2024.01508131 PDF
IJACSA Journal Cover

Call for Papers - Important Dates

Volume 17 No. 11, November 2026
Paper Submission Due October 25, 2026
Review Notification November 15, 2026
Publication Date November 30, 2026
Call for Papers Submit Paper

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