IJACSA Vol. 15 Issue 12 (2024)

1

algoTRIC: Symmetric and Asymmetric Encryption Algorithms for Cryptography – A Comparative Analysis in AI Era

Author 1: Naresh Kshetri Author 2: Mir Mehedi Rahman Author 3: Md Masud Rana Author 4: Omar Faruq Osama Author 5: James Hutson

The increasing integration of artificial intelligence (AI) within cybersecurity has necessitated stronger encryption methods to ensure data security. This paper presents a comparative analysis of symmetric (SE) and asymmetric encryption (AE) algorithms, focusing on their role in securing sensitive information in AI-driven environments. Through an in-depth study of various encryption… Read full abstract & cite →

Algorithms analysis artificial intelligence asymmetric encryption cryptography cybersecurity symmetric encryption

Abstract doi.org/10.14569/IJACSA.2024.0151201 PDF

2

A Framework for Privacy-Preserving Detection of Sickle Blood Cells Using Deep Learning and Cryptographic Techniques

Author 1: Kholoud Alotaibi Author 2: Naser El-Bathy

Sickle cell anemia is a hereditary disorder where abnormal hemoglobin causes red blood cells to become rigid and crescent-shaped, obstructing blood flow and leading to severe health complications. Early detection of these abnormal cells is essential for timely treatment and reducing disease progression. Traditional screening methods, though effective, are time-intensive… Read full abstract & cite →

Sickle cells deep learning transfer learning encryption AES SOA

Abstract doi.org/10.14569/IJACSA.2024.0151202 PDF

3

Trustworthiness in Conversational Agents: Patterns in User personality-Based Behavior Towards Chatbots

Author 1: Jieyu Wang Author 2: Merary Rangel Author 3: Mark Schmidt Author 4: Pavel Safonov

As artificial intelligence conversational agent (CA) usage is increasing, research has been done to explore how to improve chatbot user experience by focusing on user personality. This work aims to help designers and industrial professionals understand user trust related to personality in CAs for better human-centered AI design. To achieve… Read full abstract & cite →

Trust personality human-centered AI design user experience

Abstract doi.org/10.14569/IJACSA.2024.0151203 PDF

4

An Enhanced Real-Time Intrusion Detection Framework Using Federated Transfer Learning in Large-Scale IoT Networks

Author 1: Khawlah Harahsheh Author 2: Malek Alzaqebah Author 3: Chung-Hao Chen

The exponential growth of Internet of Things (IoT) devices has introduced critical security challenges, particularly in scalability, privacy, and resource constraints. Traditional centralized intrusion detection systems (IDS) struggle to address these issues effectively. To overcome these limitations, this study proposes a novel Federated Transfer Learning (FTL)-based intrusion detection framework tailored… Read full abstract & cite →

Intrusion detection systems federated learning transfer learning cybersecurity scalability resource constraints machine learning Internet of Things

Abstract doi.org/10.14569/IJACSA.2024.0151204 PDF

5

Forecasting Unemployment Rate for Multiple Countries Using a New Method for Data Structuring

Author 1: Amjad M. Monir Aljinbaz Author 2: Mohamad Mahmoud Al Rahhal

Forecasting the Unemployment Rate (UR) plays a key role in shaping economic policies and development strategies. While most research focuses on predicting UR for individual countries, there has been limited progress in creating a unified forecasting model that works across multiple countries. Traditional time series methods are usually designed for… Read full abstract & cite →

Unemployment rate artificial neural network time series hybrid model genetic algorithm

Abstract doi.org/10.14569/IJACSA.2024.0151205 PDF

6

Exploring Wealth Dynamics: A Comprehensive Big Data Analysis of Wealth Accumulation Patterns

Author 1: Karim Mohammed Rezaul Author 2: Mifta Uddin Khan Author 3: Nnamdi Williams David Author 4: Kazy Noor e Alam Siddiquee Author 5: Tajnuva Jannat Author 6: Md Shabiul Islam

The study offers a thorough examination of the accumulation and distribution of wealth among billionaires through the application of big data analytics methodologies. This research centres on an extensive dataset known as "Billionaires.csv," [19] which encompasses a range of information about billionaires from diverse nations, including their demographic characteristics, company… Read full abstract & cite →

Big data python billionaires net worth wealth accumulation wealth inheritance geographic location statistical analysis

Abstract doi.org/10.14569/IJACSA.2024.0151206 PDF

7

AI-Enabled Vision Transformer for Automated Weed Detection: Advancing Innovation in Agriculture

Author 1: Shafqaat Ahmad Author 2: Zhaojie Chen Author 3: Aqsa Author 4: Sunaia Ikram Author 5: Amna Ikram

Precision agriculture is focusing on automated weed detection in order to improve the use of inputs and minimize the application of herbicides. The presented paper outlines a Vision Transformer (ViT) model for weed detection in crop fields, that tackle difficulties stemming from the resemblance of crops and weeds, especially in… Read full abstract & cite →

Precision agriculture weed detection vision transformer UAV imagery crop-weed classification AI-Tractors

Abstract doi.org/10.14569/IJACSA.2024.0151207 PDF

8

The Heart of Artificial Intelligence: A Review of Machine Learning for Heart Disease Prediction

Author 1: Brayan R. Neciosup-Bolaños Author 2: Segundo E. Cieza-Mostacero

Heart disease is one of the main heart diseases that cause the death of people worldwide, affecting the engine of the human body: the heart. It has a greater incidence in underdeveloped countries such as Angola, Bangladesh, Ethiopia and Haiti, for this reason, obtaining accurate results based on risk factors… Read full abstract & cite →

Machine learning heart disease prediction systematic review artificial intelligence algorithms literature heart

Abstract doi.org/10.14569/IJACSA.2024.0151208 PDF

9

Software Design Aimed at Proper Order Management in SMEs

Author 1: Linett Velasquez Jimenez Author 2: Herbert Grados Espinoza Author 3: Santiago Rubiños Jimenez Author 4: Juan Grados Gamarra Author 5: Claudia Marrujo-Ingunza

The design and evaluation of an order management software oriented to SMEs in Lima is presented. Using Design Thinking, a prototype was developed focusing on Usability, Design and User Satisfaction. Through a Likert scale survey of 308 SME employees, perceptions on operational efficiency and user experience were measured. The results… Read full abstract & cite →

Design thinking SMEs order management software design usability user perception

Abstract doi.org/10.14569/IJACSA.2024.0151209 PDF

10

Design of a Mobile Learning App for Financial Literacy in Young People Using Gamification

Author 1: Angie Nayeli Ruiz-Carhuamaca Author 2: Juliana Alexandra Yauricasa-Seguil Author 3: Juan Carlos Morales-Arevalo

This research paper addresses the issue of insufficient financial literacy among young people, a challenge that affects their ability to make informed financial decisions. A survey was conducted to assess the current state of financial literacy among young people, whose results show a significant gap in the understanding of key… Read full abstract & cite →

Financial literacy gamification financial education challenge education

Abstract doi.org/10.14569/IJACSA.2024.0151210 PDF

11

Comprehensive Evaluation of Machine Learning Techniques for Obstructive Sleep Apnea Detection

Author 1: Alaa Sheta Author 2: Walaa H. Elashmawi Author 3: Adel Djellal Author 4: Malik Braik Author 5: Salim Surani Author 6: Sultan Aljahdali Author 7: Shyam Subramanian Author 8: Parth S. Patel

Obstructive Sleep Apnea (OSA) is a prevalent health issue affecting 10-25% of adults in the United States (US) and is associated with significant economic consequences. Machine learning methods have shown promise in improving the efficiency and accessibility of OSA diagnoses, thus reducing the need for expensive and challenging tests. A… Read full abstract & cite →

Machine learning obstructive sleep apnea random forest classifier oversampling classification

Abstract doi.org/10.14569/IJACSA.2024.0151211 PDF

12

Design of On-Premises Version of RAG with AI Agent for Framework Selection Together with Dify and DSL as Well as Ollama for LLM

Author 1: Kohei Arai

Currently, most RAGs are cloud-based and include Bedrock. However, there is a trend to return from the cloud to on-premises due to security concerns. In addition, it is common for APIs to call Lambda or EC2 for data access, but it is not easy to select the optimal framework depending… Read full abstract & cite →

RAG (Retrieval-Augmented Generation) API (Application Programming Interface) Lambda EC2 (Amazon Elastic Compute Cloud) AI agent Dify DSL (domain specific language) ollama YAML (YAML Ain't Markup Language)

Abstract doi.org/10.14569/IJACSA.2024.0151212 PDF

13

Deep Ensemble Method for Healthcare Asset Mapping Using Geographical Information System and Hyperspectral Images of Tirupati Region

Author 1: P. Bhargavi Author 2: T. Sarath Author 3: Gopichand G Author 4: G V Ramesh Babu Author 5: T Haritha Author 6: A. Vijaya Krishna

The ever-increasing capabilities of deep learning for image analysis and recognition have encouraged some researchers investigates potential benefits of merging Hyperspectral Images (HSI) and Geographic Information Systems (GIS) with deep learning in the healthcare industry. Healthcare is an ever-changing sector that constantly adopts new technologies to improve decision-making and patient… Read full abstract & cite →

Geographical information system hyperspectral image remote sensing images big data analytics deep ensemble methods healthcare asset

Abstract doi.org/10.14569/IJACSA.2024.0151213 PDF

14

Path Planning for Laser Cutting Based on Thermal Field Ant Colony Algorithm

Author 1: Junjie GE Author 2: Guangfa ZHANG Author 3: Tian CHEN

In laser cutting technology, path planning is the key to optimizing cutting quality. Traditional ant colony optimization path planning does not prevent excessive heat effects after processing. This paper addresses the problem of heat accumulation during drilling by introducing a heat factor and a heat threshold into the traditional ant… Read full abstract & cite →

Laser cutting path planning ant colony algorithm thermal field control method

Abstract doi.org/10.14569/IJACSA.2024.0151214 PDF

15

Laser Distance Measuring and Image Calibration for Robot Walking Using Mean Shift Algorithm

Author 1: Rujipan Kosarat Author 2: Anan Wongjan

In this research, we have measured the physical distance between the robot and its surroundings using a laser distance measuring device that we have developed, designed controllers for, and tested operationally. We will record the distance using the USB camera and integrate the LDMSB board into the laser distance measuring… Read full abstract & cite →

Laser distance image calibration mean shift algorithm LabVIEW

Abstract doi.org/10.14569/IJACSA.2024.0151215 PDF

16

Predicting Chronic Obstructive Pulmonary Disease Using ML and DL Approaches and Feature Fusion of X-Ray Image and Patient History

Author 1: Fatema Kabir Author 2: Nahida Akter Author 3: Md. Kamrul Hasan Author 4: Md. Tofael Ahmed Author 5: Mariam Akter

By 2030, chronic obstructive pulmonary disease (COPD) is expected to become one of the top three causes of death and a leading contributor to illness globally. Chronic Obstructive Pulmonary Disease (COPD) is a debilitating respiratory disease and lung ailment caused by smoking-related airway inflammation, leading to breathing difficulties. Our COPD… Read full abstract & cite →

Chronic obstructive pulmonary disease COPD COPD healthcare advanced monitoring system COPD early detection respiratory disease machine learning deep learning

Abstract doi.org/10.14569/IJACSA.2024.0151216 PDF

17

Cloud Computing: Enhancing or Compromising Accounting Data Reliability and Credibility

Author 1: Mohammed Shaban Thaher

Business development is intrinsically tied to the evolution of accounting systems, and in today’s digital economy, automation has become indispensable despite increasing setup and maintenance costs. Cloud computing emerges as a promising solution, offering cost reduction and greater flexibility in accounting processes. This paper investigates the influence of cloud technology… Read full abstract & cite →

Cloud computing information security infrastructure as a service platform as a service software as a service

Abstract doi.org/10.14569/IJACSA.2024.0151217 PDF

18

Security Gap in Microservices: A Systematic Literature Review

Author 1: Nurman Rasyid Panusunan Hutasuhut Author 2: Mochamad Gani Amri Author 3: Rizal Fathoni Aji

The growing importance of microservices architecture has raised concerns about its security despite a rise in publications addressing various aspects of microservices. Security issues are particularly critical in microservices due to their complex and distributed nature, which makes them vulnerable to various types of cyber-attacks. This study aims to fill… Read full abstract & cite →

Microservice security cyber-attacks container security standards access control

Abstract doi.org/10.14569/IJACSA.2024.0151218 PDF

19

New Knowledge Management Model: Enhancing Knowledge Creation with Zack Gap, Brand Equity, and Data Mining in the Sports Business

Author 1: Fransiska Prihatini Sihotang Author 2: Ermatita Author 3: Dian Palupi Rini Author 4: Samsuryadi

This research improves Socialization, Externalization, Combination, and Internalization (SECI) knowledge management model by combining it with Zack's knowledge gap model, brand equity concept, and data mining. Zack's model is incorporated into the SECI model to identify the gap between the knowledge in the organization and the knowledge that the organization… Read full abstract & cite →

SECI model zack model data mining brand equity sport business

Abstract doi.org/10.14569/IJACSA.2024.0151219 PDF

20

Systematic Review of Prediction of Cancer Driver Genes with the Application of Graph Neural Networks

Author 1: Noor Uddin Qureshi Author 2: Usman Amjad Author 3: Saima Hassan Author 4: Kashif Saleem

Graph Neural Networks (GNNs) have emerged as a potential tool in cancer genomics research due to their ability to capture the structural information and interactions between genes in a network, enabling the prediction of cancer driver genes. This systematic literature review assesses the capabilities and challenges of GNNs in predicting… Read full abstract & cite →

Graph neural network cancer driver genes prediction personalized medicine

Abstract doi.org/10.14569/IJACSA.2024.0151220 PDF

21

Albument-NAS: An Enhanced Bone Fracture Detection Model

Author 1: Evandiaz Fedora Author 2: Alexander Agung Santoso Gunawan

Diagnosing fracture locations accurately is challenging, as it heavily depends on the radiologist's expertise; however, image quality, especially with minor fractures, can limit precision, highlighting the need for automated methods. The accuracy of diagnosing fracture locations often relies on radiologists' expertise; however, image quality, particularly with smaller fractures, can limit… Read full abstract & cite →

Albumentation augmentation bone fracture deep learning object detection YOLO-NAS

Abstract doi.org/10.14569/IJACSA.2024.0151221 PDF

22

FKMU: K-Means Under-Sampling for Data Imbalance in Predicting TF-Target Genes Interactions

Author 1: Thanh Tuoi Le Author 2: Xuan Tho Dang

Identifying interactions between transcription factors (TFs) and target genes is critical for understanding molecular mechanisms in biology and disease. Traditional experimental approaches are often costly and not scalable. We introduce FKMU, a K-means-based under-sampling method designed to address data imbalance in predicting TF-target interactions. By selecting low-frequency TF samples within… Read full abstract & cite →

K-means clustering imbalanced data TF-target gene interactions heterogeneous network meta-path

Abstract doi.org/10.14569/IJACSA.2024.0151222 PDF

23

A Deep Learning-Based LSTM for Stock Price Prediction Using Twitter Sentiment Analysis

Author 1: Shimaa Ouf Author 2: Mona El Hawary Author 3: Amal Aboutabl Author 4: Sherif Adel

Numerous economic, political, and social factors make stock price predictions challenging and unpredictable. This paper focuses on developing an artificial intelligence (AI) model for stock price prediction. The model utilizes LSTM and XGBoost techniques in three sectors: Apple, Google, and Tesla. It aims to detect the impact of combining sentiment… Read full abstract & cite →

Sentiment analysis stocks price prediction correlation natural language processing (NLP) machine learning model LSTM XGBoost

Abstract doi.org/10.14569/IJACSA.2024.0151223 PDF

24

A Multimodal Data Scraping Tool for Collecting Authentic Islamic Text Datasets

Author 1: Abdallah Namoun Author 2: Mohammad Ali Humayun Author 3: Waqas Nawaz

Making decisions based on accurate knowledge is agreed upon to provide ample opportunities in different walks of life. Machine learning and natural language processing (NLP) systems, such as Large Language Models, may use unrecognized sources of Islamic content to fuel their predictive models, which could often lead to incorrect judgments… Read full abstract & cite →

Web scraping Islamic knowledge machine learning natural language processing question and answering AI chatbots

Abstract doi.org/10.14569/IJACSA.2024.0151224 PDF

25

Hybrid Transfer Learning for Diagnosing Teeth Using Panoramic X-rays

Author 1: M. M. EL-GAYAR

The increasing focus on oral diseases has highlighted the need for automated diagnostic processes. Dental panoramic X-rays, commonly used in diagnosis, benefit from advancements in deep learning for efficient disease detection. The DENTEX Challenge 2023 aimed to enhance the automatic detection of abnormal teeth and their enumeration from these X-rays… Read full abstract & cite →

Machine learning deep learning dental diagnosis transfer learning

Abstract doi.org/10.14569/IJACSA.2024.0151225 PDF

26

Development of Smart Financial Management Research in Shared Perspective: A CiteSpace-Based Analysis Review

Author 1: Rongxiu Zhao Author 2: Duochang Tang

At a time when information technology is advancing by leaps and bounds, smart financial management is becoming a hotspot of common concern in both academic and practical circles. The purpose of this paper is to systematically sort out the research development trend of smart financial management under the shared vision… Read full abstract & cite →

Smart finance financial management financial sharing bibliometrics CiteSpace

Abstract doi.org/10.14569/IJACSA.2024.0151226 PDF

27

Explainable AI-Driven Chatbot System for Heart Disease Prediction Using Machine Learning

Author 1: Salman Muneer Author 2: Taher M. Ghazal Author 3: Tahir Alyas Author 4: Muhammad Ahsan Raza Author 5: Sagheer Abbas Author 6: Omar AlZoubi Author 7: Oualid Ali

Heart disease (HD) continues to rank as the top cause of morbidity and mortality worldwide, prompting the enormous importance of correct prediction for effective intervention and prevention strategies. The proposed research involves developing a novel explainable AI (XAI)-driven chatbot system for HD prediction, combined with cutting-edge machine learning (ML) algorithms… Read full abstract & cite →

Heart disease prediction machine learning chatbot system XAI

Abstract doi.org/10.14569/IJACSA.2024.0151227 PDF

28

Integrating Local Channel Attention and Focused Feature Modulation for Wind Turbine Blade Defect Detection

Author 1: Zheng Cao Author 2: Rundong He Author 3: Shaofei Zhang Author 4: Zhaoyang Qi Author 5: Sa Li Author 6: Tong Liu Author 7: Yue Li

In the wind power industry, the health state of wind turbine paddles is directly related to the power generation efficiency and the safe operation of the equipment. In order to solve the problems of low efficiency and insufficient accuracy of traditional detection methods, this paper proposes a wind turbine blade… Read full abstract & cite →

Fan blades YOLO attention mechanism defect detection inner-IoU

Abstract doi.org/10.14569/IJACSA.2024.0151228 PDF

29

Construction and Optimization of Multi-Scenario Autonomous Call Rule Models in Emergency Command Scenarios

Author 1: Weiyan Zheng Author 2: Chaoyue Zhu Author 3: Di Huang Author 4: Bin Zhou Author 5: Xingping Yan Author 6: Panxia Chen

In response to the slow processing speed, weak anti-interference, and low accuracy of autonomous call models in current emergency command scenarios, the research focuses on the fire scenario, aiming to improve the emergency response efficiency through technological innovation. The research innovatively integrates digital signal processing algorithm and two-tone multi-frequency signal… Read full abstract & cite →

Digital signal processing algorithm dual tone multi-frequency signal detection algorithm fire autonomous call model

Abstract doi.org/10.14569/IJACSA.2024.0151229 PDF

30

Enhancing User Comfort in Virtual Environments for Effective Stress Therapy: Design Considerations

Author 1: Farhah Amaliya Zaharuddin Author 2: Nazrita Ibrahim Author 3: Azmi Mohd Yusof

Mental stress has emerged as a widespread concern in modern society, impacting individuals from diverse demographic backgrounds. Therefore, exploring effective methods for therapy, such as virtual environments tailored for stress management, is vital for advancing mental health and improving coping strategies. Prioritising user comfort in the design of virtual environments… Read full abstract & cite →

Virtual environment design virtual reality stress therapy user comfort

Abstract doi.org/10.14569/IJACSA.2024.0151230 PDF

31

A Machine Learning Model for Crowd Density Classification in Hajj Video Frames

Author 1: Afnan A. Shah

Managing the massive annual gatherings of Hajj and Umrah presents significant challenges, particularly as the Saudi government aims to increase the number of pilgrims. Currently, around two million pilgrims attend Hajj and 26 million attend Umrah making crowd control especially in critical areas like the Grand Mosque during Tawaf, a… Read full abstract & cite →

Hajj moderate crowd overcrowded very dense crowd machine learning

Abstract doi.org/10.14569/IJACSA.2024.0151231 PDF

32

Towards an Ontology to Represent Domain Knowledge of Attention Deficit Hyperactivity Disorder (ADHD): A Conceptual Model

Author 1: Shahad Mansour Alsaedi Author 2: Aishah Alsobhi Author 3: Hind Bitar

Attention deficit/hyperactivity disorder (ADHD) represents a highly heterogeneous and complex medical domain with numerous multidisciplinary research areas. Despite the rising number of research on the pathophysiology of ADHD, the available information in the ADHD domain is still scattered and disconnected. This research study mainly aims to develop a conceptual model… Read full abstract & cite →

Conceptual model ontology ADHD knowledge engineering

Abstract doi.org/10.14569/IJACSA.2024.0151232 PDF

33

Leiden Coloring Algorithm for Influencer Detection

Author 1: Handrizal Author 2: Poltak Sihombing Author 3: Erna Budhiarti Nababan Author 4: Mohammad Andri Budiman

In today's digital age, the role of influencers, especially on social media platforms, has grown significantly. A commonly used feature by business professionals today is follower grouping. However, this feature is limited to identifying influencers based solely on mutual followership, highlighting the need for a more sophisticated approach to influencer… Read full abstract & cite →

Influencer Louvain coloring Leiden Leiden coloring

Abstract doi.org/10.14569/IJACSA.2024.0151233 PDF

34

Construction and Optimal Control Method of Enterprise Information Flaw Risk Contagion Model Based on the Improved LDA Model

Author 1: Jun Wang Author 2: Zhanhong Zhou

In this study, we construct a risk contagion model for corporate information disclosure using complex network methods and incorporate the manipulative perspective of management tone into it. We employ an enhanced LDA model to analyze and refine the relevant data and models presented in this paper. The results of quantitative… Read full abstract & cite →

Management tone manipulation enterprise information disclosure risk contagion optimal control

Abstract doi.org/10.14569/IJACSA.2024.0151234 PDF

35

A Machine Learning-Based Intelligent Employment Management System by Extracting Relevant Features

Author 1: Yiming Wang Author 2: Chi Che

In recent years, there has been a significant increase in the number of students trying to broaden the work opportunities available to college graduates. This study presents an intelligent employment management system that may be used in educational institutions for students to gain a better understanding of their occupations and… Read full abstract & cite →

Employment management system recommendation system feature index accuracy and employment intention index

Abstract doi.org/10.14569/IJACSA.2024.0151235 PDF

36

Optimizing the Fault Localization Path of Distribution Network UAVs Based on a Cloud-Pipe-Side-End Architecture

Author 1: Lan Liu Author 2: Ping Qin Author 3: Xinqiao Wu Author 4: Chenrui Zhang

The currently proposed optimization algorithm for cooperative fault inspection of distribution network UAVs struggles to accurately detect fault points quickly, leading to low inspection efficiency. To address these issues, we investigate a new fault localization path optimization algorithm for distribution network UAVs based on a cloud-pipe-edge-end architecture. This architecture employs… Read full abstract & cite →

Cloud-pipe-edge-end architecture distribution network UAV cloud-edge collaboration edge computing

Abstract doi.org/10.14569/IJACSA.2024.0151236 PDF

37

Predicting the Number of Video Game Players on the Steam Platform Using Machine Learning and Time Lagged Features

Author 1: Gregorius Henry Wirawan Author 2: Gede Putra Kusuma

Predicting player count can provide game developers with valuable insights into players’ behavior and trends on the game population, helping with strategic decision-making. Therefore, it is important for the prediction to be as accurate as possible. Using the game’s metadata can help with predicting accuracy, but they stay the same… Read full abstract & cite →

Video games regression method feature selection time series forecasting machine learning

Abstract doi.org/10.14569/IJACSA.2024.0151237 PDF

38

Cross-Entropy-Driven Optimization of Triangular Fuzzy Neutrosophic MADM for Urban Park Environmental Design Quality Evaluation

Author 1: Xing She Author 2: Xi Xie Author 3: Peng Xie

The evaluation of urban park environmental design quality focuses on functionality, aesthetics, ecology, and user experience. Functionality ensures practical facilities, clear zoning, and accessibility. Aesthetics emphasizes visual harmony, cultural integration, and artistic appeal. Ecological quality assesses vegetation, biodiversity, and sustainability, promoting environmental protection. User experience evaluates comfort, safety, inclusivity, and… Read full abstract & cite →

Multiple-Attribute Decision-Making (MADM) problems Triangular Fuzzy Neutrosophic Sets (TFNSs) cross-entropy approach TFNN-CE approach urban park environmental design

Abstract doi.org/10.14569/IJACSA.2024.0151238 PDF

39

Improved YOLOv11pose for Posture Estimation of Xinjiang Bactrian Camels

Author 1: Lei Liu Author 2: Alifu Kurban Author 3: Yi Liu

Automatic pose estimation of camels is crucial for long-term health monitoring in animal husbandry. There is currently less research on camels, and our study has certain practical application value in actual camel farms. Due to the high similarity of camels, this has brought us a huge challenge in pose estimation… Read full abstract & cite →

YOLOv11pose efficient channel attention multi-scale pooling structure DECA-block Bactrian camel posture estimation；SimSPPF ECA

Abstract doi.org/10.14569/IJACSA.2024.0151239 PDF

40

A Hybrid Machine Learning Approach for Continuous Risk Management in Business Process Reengineering Projects

Author 1: RAFFAK Hicham Author 2: LAKHOUILI Abdallah Author 3: MANSOURI Moahmed

This study proposes a hybrid machine learning approach for continuous risk management in Business Process Reengineering (BPR) projects. This approach combines supervised and unsupervised learning techniques, integrating feature selection and preprocessing through Principal Component Analysis (PCA), clustering with K-means, and visualization with t-SNE. The labeled data are then used as… Read full abstract & cite →

BPR Risk management PCA K-means XGBoost PSO GWO

Abstract doi.org/10.14569/IJACSA.2024.0151240 PDF

41

Enhancing CURE Algorithm with Stochastic Neighbor Embedding (CURE-SNE) for Improved Clustering and Outlier Detection

Author 1: Dewi Sartika Br Ginting Author 2: Syahril Efendi Author 3: Amalia Author 4: Poltak Sihombing

This study focuses on analyzing stunting data using the CURE and CURE-SNE algorithms for clustering and outlier detection. The primary challenge is identifying patterns in stunting data, which includes variables such as age, gender, height, weight, and nutritional status. Both algorithms were employed to group the data and detect outliers… Read full abstract & cite →

Stunting clustering algorithm CURE CURE-SNE outliers

Abstract doi.org/10.14569/IJACSA.2024.0151241 PDF

42

Distributed Networks for Brain Tumor Classification Through Temporal Learning and Hybrid Attention Segmentation

Author 1: Sayeedakhanum Pathan Author 2: Savadam Balaji

Brain Tumor (BT), which is the progress of abnormal cells in brain surface is categorized into different types based on the symptoms and the affected parts in brain. Classification of BT using Magnetic Resonance Imaging (MRI) is an important and challenging task for BT diagnosis. Various approaches are designed to… Read full abstract & cite →

Brain tumor magnetic resonance imaging Gaussian filter hybrid attention-VNet distributed convolution neural network

Abstract doi.org/10.14569/IJACSA.2024.0151242 PDF

43

A Distributed Framework for Indoor Product Design Using VR and Intelligent Algorithms

Author 1: Yaoben Gong Author 2: Zhenyu Gao

This paper presents an innovative approach to the digital design of indoor home products by integrating virtual reality (VR) technology with intelligent algorithms to enhance design accuracy and efficiency. A model combining the Red deer Optimization Algorithm with a Simple Recurrent Unit (SRU) network is proposed to evaluate and optimize… Read full abstract & cite →

Interior home products virtual reality technology digital design algorithms improved simple cyclic units intelligent algorithms for design application evaluation

Abstract doi.org/10.14569/IJACSA.2024.0151243 PDF

44

Convolutional Layer-Based Feature Extraction in an Ensemble Machine Learning Model for Breast Cancer Classification

Author 1: Shofwatul ‘Uyun Author 2: Lina Choridah Author 3: Slamet Riyadi Author 4: Ade Umar Ramadhan

Mammography and ultrasound are the main medical imaging modalities for identifying breast lesions. Computer-assisted diagnosis (CAD) is an important tool for radiologists, helping them differentiate benign and malignant lesions more quickly and objectively. The use of appropriate features in mammography and ultrasound is one of the key factors determining the… Read full abstract & cite →

Ensemble learning feature extraction convolutional layer breast cancer

Abstract doi.org/10.14569/IJACSA.2024.0151244 PDF

45

Design and Application of a TOPSIS-Based Fuzzy Algorithm

Author 1: Fei Liu

The study aims to evaluate the tourism attractiveness of different tourist attractions in the same region through the TOPSIS model in the perspective of culture and tourism integration, so as to provide theoretical and practical support for the tourism development of the region. On the basis of the concept of… Read full abstract & cite →

Cultural and tourism integration attractiveness TOPSIS entropy weight method

Abstract doi.org/10.14569/IJACSA.2024.0151245 PDF

46

Enhanced Butterfly Optimization Algorithm for Task Scheduling in Cloud Computing Environments

Author 1: Yue ZHAO

Cloud computing is transforming the provision of elastic and adaptable capabilities on demand. A scalable infrastructure and a wide range of offerings make cloud computing essential to today's computing ecosystem. Cloud resources enable users and various companies to utilize data maintained in a distant location. Generally, cloud vendors provide services… Read full abstract & cite →

Cloud computing resource utilization task scheduling Butterfly Optimization Algorithm fuzzy decision strategy

Abstract doi.org/10.14569/IJACSA.2024.0151246 PDF

47

Leveraging Large Language Models for Automated Bug Fixing

Author 1: Shatha Abed Alsaedi Author 2: Amin Yousef Noaman Author 3: Ahmed A. A. Gad-Elrab Author 4: Fathy Elbouraey Eassa Author 5: Seif Haridi

Bug fixing, which is known as Automatic Program Repair (APR), is a significant area of research in the software engineering field. It aims to develop techniques and algorithms to automatically fix bugs and generate fixing patches in the source code. Researchers focus on developing many APR algorithms to enhance software… Read full abstract & cite →

Bug fixing automated program repair large language models software debugging software maintenance machine learning

Abstract doi.org/10.14569/IJACSA.2024.0151247 PDF

48

Towards Secure Internet of Things Communication Through Trustworthy RPL Routing Protocols

Author 1: Rui LI

The Internet of Things (IoT) refers to a network of connected objects for autonomous data exchange and processing. With the increasing growth in IoT, ensuring data transmission integrity and security is essential, as data is subject to many attacks. Currently, the routing protocol for low-power lossy networks is RPL and… Read full abstract & cite →

Internet of Things routing trust data transmission

Abstract doi.org/10.14569/IJACSA.2024.0151248 PDF

49

Cybersecurity Awareness in Schools: A Systematic Review of Practices, Challenges, and Target Audiences

Author 1: Abdulrahman Abdullah Arishi Author 2: Nazhatul Hafizah Kamarudin Author 3: Khairul Azmi Abu Bakar Author 4: Zarina Binti Shukur Author 5: Mohammad Kamrul Hasan

This systematic literature review examines cybersecurity awareness in schools, focusing on effective practices, challenges, and future directions. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, peer-reviewed publications in English were sourced from ACM Digital Library, IEEE Xplore, ScienceDirect, SpringerLink, and Emerald, covering the period from 2019… Read full abstract & cite →

Cybersecurity awareness threats awareness programs education school security

Abstract doi.org/10.14569/IJACSA.2024.0151249 PDF

50

Integrating Multi-Agent System and Case-Based Reasoning for Flood Early Warning and Response System

Author 1: Nor Aimuni Md Rashid Author 2: Zaheera Zainal Abidin Author 3: Zuraida Abal Abas

This research addresses the limitations of current Multi-Agent Systems (MAS) in Flood Early Warning and Response Systems (FEWRS), focusing on gaps in risk knowledge, monitoring, forecasting, warning dissemination, and response capabilities. These shortcomings reduce the system’s reliability and public trust, highlighting the need for better flood preparedness and learning mechanisms… Read full abstract & cite →

Flood multi-agent system flood early warning system case-based reasoning quadruple helix flood risk

Abstract doi.org/10.14569/IJACSA.2024.0151250 PDF

51

Multi-Source Consistency Deep Learning for Semi-Supervised Operating Condition Recognition in Sucker-Rod Pumping Wells

Author 1: Jianguo Yang Author 2: Bin Zhou Author 3: Muhammad Tahir Author 4: Min Zhang Author 5: Xiao Zheng Author 6: Xinqian Liu

How making full use of the multiple measured information sources obtained from the sucker-rod pumping wells based on deep learning is crucial for precisely recognizing the operating conditions. However, the existing deep learning-based operating condition recognition technology has the disadvantages of low accuracy and weak practicality owing to the limitations… Read full abstract & cite →

Operating condition recognition of sucker-rod pumping wells multi-source consistency learning semi-supervised learning CNN attention mechanism

Abstract doi.org/10.14569/IJACSA.2024.0151251 PDF

52

Development of a Smart Water Dispenser Based on Object Recognition with Raspberry Pi 4

Author 1: Dani Ramdani Author 2: Puput Dani Prasetyo Adi Author 3: Andriana Author 4: Tjahjo Adiprabowo Author 5: Yuyu Wahyu Author 6: Arief Suryadi Satyawan Author 7: Sally Octaviana Sari Author 8: Zulkarnain Author 9: Noor Rohman

In this project, we develop and apply a Smart Water Dispenser system, which is combined with object recognition and fluid level control supported by Ultrasonic Sensors, Raspberry Pi, and also DC Motors. The essence of this system is to develop a system using the Raspberry Pi 4 Model B with… Read full abstract & cite →

Smart water dispenser object recognition Raspberry Pi 4 YOLO VB ultrasonic sensor

Abstract doi.org/10.14569/IJACSA.2024.0151252 PDF

53

Machine Learning as a Tool to Combat Ransomware in Resource-Constrained Business Environment

Author 1: Luis Jesús Romero Castro Author 2: Piero Alexander Cruz Aquino Author 3: Fidel Eugenio Garcia Rojas

Ransomware has emerged as one of the leading cybersecurity threats to microenterprises, which often lack the technological and financial resources to implement advanced protection systems. This study proposes a cybersecurity model based on machine learning, designed not only for the detection and mitigation of ransomware attacks but also as a… Read full abstract & cite →

Ransomware cybersecurity machine learning microenterprise threat detection

Abstract doi.org/10.14569/IJACSA.2024.0151253 PDF

54

Traffic Speed Prediction Based on Spatial-Temporal Dynamic and Static Graph Convolutional Recurrent Network

Author 1: YANG Wenxi Author 2: WANG Ziling Author 3: CUI Tao Author 4: LU Yudong Author 5: QU Zhijian

Traffic speed prediction based on spatial-temporal data plays an important role in intelligent transportation. The time-varying dynamic spatial relationship and complex spatial-temporal dependence are still important problems to be considered in traffic prediction. In response to existing problems, a Dynamic and Static Graph Convolutional Recurrent Network (DASGCRN) model for traffic… Read full abstract & cite →

Intelligent transportation traffic speed prediction spatial-temporal correlation dynamic graph graph convolution recurrent network

Abstract doi.org/10.14569/IJACSA.2024.0151254 PDF

55

Enhanced Aquila Optimizer Algorithm for Efficient Stance Classification in Online Social Networks

Author 1: Na LI

Stance classification in Online Social Networks (OSNs) is essential to comprehend users' standpoints on various issues relating to social, political, and commercial aspects. However, traditional methods applied to large datasets and complex text structures usually face several challenges. This study introduces the Enhanced Aquila Optimizer (EAO), a metaheuristic algorithm designed… Read full abstract & cite →

Stance classification online social networks opposition-based learning chaotic local search Aquila Optimizer

Abstract doi.org/10.14569/IJACSA.2024.0151255 PDF

56

Math Role-Play Game Using Lehmer’s RNG Algorithm

Author 1: Chong Bin Yong Author 2: Rajermani Thinakaran Author 3: Nurul Halimatul Asmak Ismail Author 4: Samer A. B. Awwad

Due to the COVID-19 pandemic, schools in Malaysia have been physically closed for more than 40 weeks and the students have to learn online. As Malaysia transitions to endemicity, many younger students struggle to keep up with their education due to significant learning loss caused by school closures and the… Read full abstract & cite →

Lehmer’s RNG algorithm online educational gamification

Abstract doi.org/10.14569/IJACSA.2024.0151256 PDF

57

The Impact of Malware Attacks on the Performance of Various Operating Systems

Author 1: Maria-Madalina Andronache Author 2: Alexandru Vulpe Author 3: Corneliu Burileanu

Latest research in the field of cyber security concludes that a permanent monitoring of the network and its protection, based on various tools or solutions, are key aspects for protecting it against vulnerabilities. So, it is imperative that solutions such as firewall, antivirus, Intrusion Detection System, Intrusion Prevention System, Security… Read full abstract & cite →

Cybersecurity network security network monitoring incident analysis incident response

Abstract doi.org/10.14569/IJACSA.2024.0151257 PDF

58

A Malware Analysis Approach for Identifying Threat Actor Correlation Using Similarity Comparison Techniques

Author 1: Ahmad Naim Irfan Author 2: Suriayati Chuprat Author 3: Mohd Naz'ri Mahrin Author 4: Aswami Ariffin

Cybersecurity is essential for organisations to protect critical assets from cyber threats in the increasingly digital and interconnected world. However, cybersecurity incidents are rising each year, leading to increased workloads. Current malware analysis approaches are often case-by-case, based on specific scenarios, and are typically limited to identifying malware. When cybersecurity… Read full abstract & cite →

Malware analysis APT group threat actor correlation CTI

Abstract doi.org/10.14569/IJACSA.2024.0151258 PDF

59

Usability Heuristic Evaluation of Mobile Learning Applications Based on the Usability Design Model for Adult Learners

Author 1: Amy Ling Mei Yin Author 2: Ahmad Sobri B Hashim Author 3: Mazeyanti Bt M Ariffin

Adult ownership of mobile devices has exploded over the past few years, and smartphones and tablets have become vital for communication, productivity, entertainment, and learning. Some common problems adults face are that they find it difficult to use new technology-based apps because many devices are small. Tasks on new technology-based… Read full abstract & cite →

Usability design model mobile learning adult learners heuristic evaluation

Abstract doi.org/10.14569/IJACSA.2024.0151259 PDF

60

Radar Spectrum Analysis and Machine Learning-Based Classification for Identity-Based Unmanned Aerial Vehicles Detection and Authentication

Author 1: Aminu Abdulkadir Mahmoud Author 2: Sofia Najwa Ramli Author 3: Mohd Aifaa Mohd Ariff Author 4: Muktar Danlami

The significant use of Unmanned Aerial Vehicles (UAVs) in commercial and civilian applications presents various cybersecurity challenges, particularly in detection and authentication. Unauthorized UAVs can be very harmful to the people on the ground, the infrastructure, the right to privacy, and other UAVs. Moreover, using the internet for UAV communication… Read full abstract & cite →

Authentication detection cybersecurity Micro-Doppler radar Unmanned Aerial Vehicle (UAV)

Abstract doi.org/10.14569/IJACSA.2024.0151260 PDF

61

Application of Residual Graph Attention Networks Algorithm in Credit Evaluation for Financial Enterprises

Author 1: Wenxing Zeng

In the context of digital transformation of enterprises, credit evaluation of financial enterprises faces new challenges and opportunities. Digital transformation introduces a large amount of data and advanced analytical tools, providing richer information and methods for credit evaluation. In this paper, we propose a credit evaluation model based on improved… Read full abstract & cite →

Quantum genetic algorithm residual networks attention mechanisms graph neural networks credit evaluation

Abstract doi.org/10.14569/IJACSA.2024.0151261 PDF

62

A Conceptual Framework for Agricultural Water Management Through Smart Irrigation

Author 1: Abdelouahed Tricha Author 2: Laila Moussaid Author 3: Najat Abdeljebbar

The demand for freshwater resources has risen significantly due to population growth and increasing drought conditions in agricultural regions worldwide. Irrigated agriculture consumes a substantial amount of water, often leading to wastage due to inefficient irrigation practices. Recent breakthroughs in emerging technologies, including machine learning, the Internet of Things, wireless… Read full abstract & cite →

Agriculture irrigation system water management Internet of Things sustainability

Abstract doi.org/10.14569/IJACSA.2024.0151262 PDF

63

An Efficient Diabetic Retinopathy Detection and Classification System Using LRKSA-CNN and KM-ANFIS

Author 1: Rachna Kumari Author 2: Sanjeev Kumar Author 3: Sunila Godara

If Diabetic Retinopathy (DR) is not diagnosed in the early stages, it leads to impaired vision and often causes blindness. So, diagnosis of DR is essential. For detecting DR and its diverse stages, various approaches were developed. However, they are limited in considering microstructural changes of visual pathways associated with… Read full abstract & cite →

Intervening contour similarity weights based watershed segmentation (ICSW-WS) min-max normalization based green anaconda optimization (MM-GAO) krusinka membership based adaptive neuro fuzzy interference system (KM-ANFIS) linearly regressed kernel and scaled activation based convolution neural network (LRKSA-CNN) deep learning

Abstract doi.org/10.14569/IJACSA.2024.0151263 PDF

64

Mining High Utility Itemset with Hybrid Ant Colony Optimization Algorithm

Author 1: Keerthi Mohan Author 2: Anitha J

A significant area of study within data mining is high-utility itemset mining (HUIM). The exponential problem of broad search space usually comes up while using traditional HUIM algorithms when the database size or the number of unique objects is huge. Evolutionary computation (EC) -based algorithms have been presented as an… Read full abstract & cite →

Utility mining high utility itemset ant colony optimization genetic algorithm evolutionary computation

Abstract doi.org/10.14569/IJACSA.2024.0151264 PDF

65

Enhancing IoT Security Through User Categorization and Aberrant Behavior Detection Using RBAC and Machine Learning

Author 1: Alshawwa Izzeddin A O Author 2: Nor Adnan Bin Yahaya Author 3: Ahmed Y. mahmoud

The proliferation of Internet of Things (IoT) technology in recent years has revolutionized several industries, providing customers with reliable and efficient IoT services. However, as the IoT ecosystem grows, attention has switched away from straightforward user access to the crucial topic of security. Among others, there is a need to… Read full abstract & cite →

Machine learning classification SVM LOF IF classification methods aberrant user behavior Role-Based Access Control (RBAC) IoT user dataset and user categorization

Abstract doi.org/10.14569/IJACSA.2024.0151265 PDF

66

A Real-Time Nature-Inspired Intrusion Detection in Virtual Environments: An Artificial Bees Colony Approach Based on Cloud Model

Author 1: Ayanseun S. Ayanboye Author 2: John E. Efiong Author 3: Temitope O. Ajayi Author 4: Rotimi A. Gbadebo Author 5: Bodunde O. Akinyemi Author 6: Emmanuel A. Olajubu Author 7: Ganiyu A. Aderounmu

Real-time intrusion detection in virtual environments is crucial for maintaining the security and integrity of modern computing infrastructures. This paper proposes a nature-inspired mathematical model designed to detect both known and unknown attacks on virtual machines, focusing on enhancing detection accuracy and minimizing false alarm rates. The proposed model, named… Read full abstract & cite →

Real-time intrusion detection virtual environments artificial bee colony algorithm cloud model algorithms intrusion detection system feature selection classification swarm intelligence fuzzy logic DNN ABC_DNN DABCO_CM

Abstract doi.org/10.14569/IJACSA.2024.0151266 PDF

67

YOLO-Driven Lightweight Mobile Real-Time Pest Detection and Web-Based Monitoring for Sustainable Agriculture

Author 1: Wong Min On Author 2: Nirase Fathima Abubacker

Nowadays, pest infestations cause significant reductions in agricultural productivity all over the world. To control pests, farmers often apply excessive volumes of pesticides due to the difficulty of manually detecting the pest at an early stage. Their overuse of pesticides has led to environmental pollution and health risks. To address… Read full abstract & cite →

Pest detection YOLO deep learning real-time monitoring smartphone application web-based platform object detection pest management pesticide reduction sustainable agriculture

Abstract doi.org/10.14569/IJACSA.2024.0151267 PDF

68

Improved Decision Tree, Random Forest, and XGBoost Algorithms for Predicting Client Churn in the Telecommunications Industry

Author 1: Mohamed Ezzeldin Saleh Author 2: Nadia Abd-Alsabour

Traditional machine learning models, especially decision trees, face great challenges when applied to high-dimensional and imbalanced telecommunication datasets. The research presented in this paper aims to enhance the performance of traditional Decision Tree (DT), Decision Tree with grid search (DT+), random forest (RF), and XGBoost (XGB) models. This is accomplished… Read full abstract & cite →

Churn prediction decision trees grid search random forest XGBoost

Abstract doi.org/10.14569/IJACSA.2024.0151268 PDF

69

Cyber Security Risk Assessment Framework for Cloud Customer and Service Provider

Author 1: N. Sujata Kumari Author 2: Naresh Vurukonda

The rapid development of cloud computing demands an effective cybersecurity framework for protecting the sensitive information of the infrastructure. Currently, many organizations depend on cloud services for their operation, increasing the risk of cybersecurity. Hence, an intelligent risk assessment mechanism is significant for detecting and mitigating the cybersecurity threats associated… Read full abstract & cite →

Deep recurrent neural network krill herd optimization artificial bee colony optimization elliptic curve cryptography

Abstract doi.org/10.14569/IJACSA.2024.0151269 PDF

70

Optimizing Cervical Cancer Diagnosis with Correlation-Based Feature Selection: A Comparative Study of Machine Learning Models

Author 1: Wiwit Supriyanti Author 2: Sujalwo Author 3: Dimas Aryo Anggoro Author 4: Maryam Author 5: Nova Tri Romadloni

Cervical cancer remains a significant global health issue, particularly in developing countries where it is a leading cause of mortality among women. The development of machine learning-based approaches has become essential for early detection and diagnosis of cervical cancer. This research explores the optimization of classification algorithms through Correlation-Based Feature… Read full abstract & cite →

Cervical cancer feature selection machine learning

Abstract doi.org/10.14569/IJACSA.2024.0151270 PDF

71

Intelligent System for Stability Assessment of Chest X-Ray Segmentation Using Generative Adversarial Network Model with Wavelet Transforms

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

Accurate segmentation of chest X-rays is essential for effective medical image analysis, but challenges arise due to inherent stability issues caused by factors such as poor image quality, anatomical variations, and disease-related abnormalities. While Generative Adversarial Networks (GANs) offer automated segmentation, their stability remains a significant limitation. In this paper… Read full abstract & cite →

Deep learning X-rays segmentation medical imaging Generative Adversarial Networks wavelet transforms

Abstract doi.org/10.14569/IJACSA.2024.0151271 PDF

72

Real-Time Monitoring and Analysis Through Video Surveillance and Alert Generation for Prompt and Immediate Response

Author 1: Akshat Kumar Author 2: Renuka Agrawal Author 3: Akshra Singh Author 4: Aaftab Noorani Author 5: Yashika Jaiswal Author 6: Preeti Hemnani Author 7: Safa Hamdare

The efficacy of Closed-Circuit Television systems (CCTV) in residential areas is often linked to the lack of real-time alerts and rapid response mechanisms. Enabling immediate notifications upon the identification of irregularities or aggressive conduct can greatly enhance the possibility of averting serious incidents, or at the very least, significantly mitigate… Read full abstract & cite →

Rapid response anomaly detection MobileNetV2 VGG16 BiLSTM

Abstract doi.org/10.14569/IJACSA.2024.0151272 PDF

73

Sentiment Analysis of Web Images by Integrating Machine Learning and Associative Reasoning Ideas

Author 1: Yuan Fang Author 2: Yi Wang

To achieve automatic recognition and understanding of image sentiment analysis, the study proposes an image sentiment prediction network based on multi-excitation fusion. This network simultaneously handles multiple excitations, such as color, object, and face, and is designed to predict the sentiment associated with an image. A visual emotion inference network… Read full abstract & cite →

Sentiment analysis multi-excitation fusion image emotion prediction associative reasoning attention mechanism

Abstract doi.org/10.14569/IJACSA.2024.0151273 PDF

74

Deep Learning for Coronary Artery Stenosis Localization: Comparative Insights from Electrocardiograms (ECG), Photoplethysmograph (PPG) and Their Fusion

Author 1: Mohd Syazwan Md Yid Author 2: Rosmina Jaafar Author 3: Noor Hasmiza Harun Author 4: Mohd Zubir Suboh Author 5: Mohd Shawal Faizal Mohamad

Coronary artery stenosis (CAS) is a critical cardiovascular condition that demands accurate localization for effective treatment and improved patient outcomes. This study addresses the challenge of enhancing CAS localization through a comparative analysis of deep learning techniques applied to electrocardiogram (ECG), photoplethysmograph (PPG), and their combined signals. The primary research… Read full abstract & cite →

Coronary artery stenosis deep learning ECG PPG ECG-PPG fusion CNN LSTM attention mechanism

Abstract doi.org/10.14569/IJACSA.2024.0151274 PDF

75

Unlocking the Potential of Cloud Computing in Healthcare: A Comprehensive SWOT Analysis of Stakeholder Readiness and Implementation Challenges

Author 1: Alaa Abas Mohamed

The adoption of cloud computing in healthcare holds the potential to revolutionize healthcare delivery, particularly in developing regions. Despite its promise of scalability, cost-effectiveness, and improved data management, challenges such as digital literacy gaps, infrastructure deficiencies, and security concerns hinder its implementation. This study evaluates the readiness for adopting cloud… Read full abstract & cite →

Cloud computing SWOT strength weakness opportunities threat

Abstract doi.org/10.14569/IJACSA.2024.0151275 PDF

76

A Novel Approach Based on Information Relevance Perspective and ANN for Predicting the Helpfulness of Online Reviews

Author 1: Nur Syadhila Bt Che Lah Author 2: Khursiah Zainal-Mokhtar

This study presents a novel approach to predicting the helpfulness of online reviews using Artificial Neural Networks (ANNs) focused on information relevance. As online reviews significantly influence consumer decision-making, it is critical to understand and identify reviews that provide the most value. This research identifies four key textual features namely… Read full abstract & cite →

Review helpfulness online reviews information relevance review novelty review readability review specificity Artificial Neural Networks

Abstract doi.org/10.14569/IJACSA.2024.0151276 PDF

77

An Advanced Semantic Feature-Based Cross-Domain PII Detection, De-Identification, and Re-Identification Model Using Ensemble Learning

Author 1: Poornima Kulkarni Author 2: Cauvery N K Author 3: Hemavathy R

The digital data being core to any system requires communication across peers and human machine interfaces; however, ensuring (data) security and privacy remains a challenge for the industries, especially under the threat of man-in-the-middle attacks, intruders and even ill-intended unauthorized access at warehouses. Almost all digital communication practices embody personally… Read full abstract & cite →

PII Detection machine learning natural language processing artificial intelligence de-identification

Abstract doi.org/10.14569/IJACSA.2024.0151277 PDF

78

Risk Assessment for Geological Exploration Projects Based on the Fuzzy-DEMATEL Method

Author 1: Zhenhua Yang Author 2: Hua Shi Author 3: Ning Tian Author 4: Juan Bai Author 5: Xiaoyu Han

This paper briefly introduces the analytic hierarchy process (AHP) method and uses the fuzzy decision-making and trial evaluation laboratory (DEMATEL) method to adjust the index weight in it. The geological exploration project of Qingdao undersea tunnel project in Shandong Province was selected as the subject of case study. Firstly, the… Read full abstract & cite →

Geological exploration project analytic hierarchy process DEMATEL fuzzy theory risk assessment

Abstract doi.org/10.14569/IJACSA.2024.0151278 PDF

79

Blockchain-Based Financial Control System

Author 1: Tedan Lu

In order to solve the problems of data security and low efficiency of information transmission in traditional financial control systems, this paper discusses in depth the application of blockchain technology in financial control systems. In order to optimize the performance of the traditional financial control system, this paper introduces blockchain… Read full abstract & cite →

Blockchain technology financial control system resource allocation information exchange consensus mechanism

Abstract doi.org/10.14569/IJACSA.2024.0151279 PDF

80

User Interface Design of SEVIMA EdLink Platform for Facilitating Tri Kaya Parisudha-Based Asynchronous Learning

Author 1: Agus Adiarta Author 2: I Made Sugiarta Author 3: Komang Krisna Heryanda Author 4: I Komang Gede Sukawijana Author 5: Dewa Gede Hendra Divayana

This research aims to show the user interface design of the SEVIMA EdLink platform to facilitate Tri Kaya Parisudha-based asynchronous learning in the nuances of independent learning. This research used the Research and Development method with the Borg & Gall development model, which focused on several stages, including research and… Read full abstract & cite →

Design user interface SEVIMA EdLink asynchronous Tri Kaya Parisudha independent learning

Abstract doi.org/10.14569/IJACSA.2024.0151280 PDF

81

Deep Learning-Optimized CLAHE for Contrast and Color Enhancement in Suzhou Garden Images

Author 1: Chuanyuan Li Author 2: Ziyun Jiao

Suzhou gardens are renowned for their unique color palettes and rich cultural significance. This study introduces a deep learning-optimized Contrast Limited Adaptive Histogram Equalization (CLAHE) method to enhance image contrast and improve color extraction accuracy in Suzhou garden images. An initial collection of 18,502 images was refined to 11,526 high-quality… Read full abstract & cite →

Deep Learning-Optimized CLAHE image contrast enhancement color extraction Suzhou gardens VGG16 semantic segmentation

Abstract doi.org/10.14569/IJACSA.2024.0151281 PDF

82

Surface Roughness Prediction Based on CNN-BiTCN-Attention in End Milling

Author 1: Guanhua Xiao Author 2: Hanqian Tu Author 3: Yunzhe Xu Author 4: Jiahao Shao Author 5: Dongming Xiang

Surface roughness is a pivotal indicator of surface quality for machined components. It directly influences the performance and lifespan of manufactured products. Precise prediction of surface roughness is instrumental in refining production processes and curtailing costs. However, despite the use of identical processing parameters, the final surface roughness would be… Read full abstract & cite →

Surface roughness prediction end milling CNN-BiTCN-Attention deep learning

Abstract doi.org/10.14569/IJACSA.2024.0151282 PDF

83

Enriching Sequential Recommendations with Contextual Auxiliary Information

Author 1: Adel Alkhalil

Recommender Systems (RS) play a key role in offering suggestions and predicting items for users on e-commerce and social media platforms. Sequential recommendation systems (SRS) leverage the user’s previous interaction history to forecast the next user-item interaction. Although deep learning methods like CNNs and RNNs have enhanced recommendation quality, current… Read full abstract & cite →

Recommender system sequential recommendation auxiliary information sentence transformer sentence embedding

Abstract doi.org/10.14569/IJACSA.2024.0151283 PDF

84

On the Context-Aware Anomaly Detection in Vehicular Networks

Author 1: Mohammed Abdullatif H. Aljaafari

Transportation systems are moving towards autonomous and intelligent vehicles due to advancements in embedded systems, control algorithms, and wireless communications. By enabling connectivity among vehicles, a vehicular network can be developed which offers safe and efficient driving applications. Security is a major challenge for vehicular networks as application reliability depends… Read full abstract & cite →

Fog computing load balancing task offloading

Abstract doi.org/10.14569/IJACSA.2024.0151284 PDF

85

TLDViT: A Vision Transformer Model for Tomato Leaf Disease Classification

Author 1: Sami Aziz Alshammari

Accurate and efficient diagnostic methods are essential for crop health monitoring due to the substantial impact of tomato leaf diseases on crop yield and quality. Traditional machine learning models, such as convolutional neural networks (CNNs), have shown promise in plant disease classification; however, they often require extensive data preprocessing and… Read full abstract & cite →

Tomato Leaf Disease Vision Transformer (ViT) crop health monitoring plant disease classification

Abstract doi.org/10.14569/IJACSA.2024.0151285 PDF

86

Hybrid Approach of Classification of Monkeypox Disease: Integrating Transfer Learning with ViT and Explainable AI

Author 1: MD Abu Bakar Siddick Author 2: Zhang Yan Author 3: Mohammad Tarek Aziz Author 4: Md Mokshedur Rahman Author 5: Tanjim Mahmud Author 6: Sha Md Farid Author 7: Valisher Sapayev Odilbek Uglu Author 8: Matchanova Barno Irkinovna Author 9: Atayev Shokir Kuranbaevich Author 10: Ulugbek Hajiev

Human monkeypox is a persistent global health challenge, ranking among the most common illnesses worldwide. Early and accurate diagnosis is critical to developing effective treatments. This study proposes a comprehensive approach to monkeypox diagnosis using deep learning algorithms, including Vision Transformer, MobileNetV2, EfficientNetV2, ResNet-50, and a hybrid model. The hybrid… Read full abstract & cite →

Monkeypox vision transformer hybrid model transfer learning explainable artificial intelligence

Abstract doi.org/10.14569/IJACSA.2024.0151286 PDF

87

Explainable Deep Transfer Learning Framework for Rice Leaf Disease Diagnosis and Classification

Author 1: Md Mokshedur Rahman Author 2: Zhang Yan Author 3: Mohammad Tarek Aziz Author 4: MD Abu Bakar Siddick Author 5: Tien Truong Author 6: Md. Maskat Sharif Author 7: Nippon Datta Author 8: Tanjim Mahmud Author 9: Renzon Daniel Cosme Pecho Author 10: Sha Md Farid

Rice plays a vital role in the food stock. But sometimes this crop leaf falls into disease. And, the amount of food consumed will decrease due to leaf disease. So, discovering the rice leaf disease is necessary to improve rice productivity. Currently, many researchers use deep learning methods to solve… Read full abstract & cite →

Rice leaf ensemble-learning explainable AI disease diagnosis transfer learning

Abstract doi.org/10.14569/IJACSA.2024.0151287 PDF

88

Multi-Label Decision-Making for Aerobics Platform Selection with Enhanced BERT-Residual Network

Author 1: Yan Hu

In response to the increased demand for individualized workout routines, online aerobics programs are struggling to fulfil the needs of their various user bases with specialized suggestions. Current systems seldom combine multiple data sources to analyze user preferences, reducing customization accuracy and engagement. Enhanced BERT-Residual Network (EBRN) evaluates multimodal input… Read full abstract & cite →

Personalized fitness aerobics recommendations artificial intelligence Enhanced BERT-Residual Network (EBRN) hybrid models user engagement

Abstract doi.org/10.14569/IJACSA.2024.0151288 PDF

89

Recursive Center Embedding: An Extension of MLCE for Semantic Evaluation of Complex Sentences

Author 1: ShivKishan Dubey Author 2: Narendra Kohli

A novel method for representing hierarchical sentences, named Multi-Leveled Center Embedding (MLCE), has recently been introduced. The approach utilizes the concept of center-embedded structures to demonstrate the structural complexity of complex sentences through iterative calculations of differences between the original and modified embeddings of its hierarchy. Through an implementation of… Read full abstract & cite →

Recursive Center Embedding (RCE) Multi-Level Center Embedding (MLCE) complex sentences structural similarity

Abstract doi.org/10.14569/IJACSA.2024.0151289 PDF

90

Fault-Tolerant Control of Nonlinear Delayed Systems Using Lyapunov Approach: Application to a Hydraulic Process

Author 1: Tayssir Abdelkrim Author 2: Adel Tellili Author 3: Nouceyba Abdelkrim

Designing stabilizing controllers for delayed non-linear systems with control constraints presents a significant challenge. This paper addresses this issue by proposing a fault-tolerant control approach for a specific class of delayed nonlin-ear systems with actuator faults based on Lyapunov redesign principle. Initially, an assumption is introduced to facilitate the control… Read full abstract & cite →

Delayed nonlinear system actuator faults delayed hydraulic process additive fault tolerant control redesign Lya-punov approach

Abstract doi.org/10.14569/IJACSA.2024.0151290 PDF

91

Advanced Deep Learning Approaches for Fault Detection and Diagnosis in Inverter-Driven PMSM Systems

Author 1: Abdelkabir BACHA Author 2: Ramzi El IDRISSI Author 3: Fatima LMAI Author 4: Hicham EL HASSANI Author 5: Khalid Janati Idrissi Author 6: Jamal BENHRA

This paper presents a comprehensive approach to fault detection and diagnosis (FDD) in inverter-driven Permanent Magnet Synchronous Motor (PMSM) systems through the innovative integration of transformer-based architectures with physics-informed neural networks (PINNs). The methodology addresses critical challenges in power electronics reliability by incorporating domain-specific physical constraints into the learning process… Read full abstract & cite →

Fault detection and diagnosis PMSM deep learning transformers physics-informed neural networks power electronics

Abstract doi.org/10.14569/IJACSA.2024.0151291 PDF

92

A Framework for Age Estimation of Fish from Otoliths: Synergy Between RANSAC and Deep Neural Networks

Author 1: Souleymane KONE Author 2: Abdoulaye SERE Author 3: Dekpeltaki´e Augustin METOUALE SOMDA Author 4: Jos´e Arthur OUEDRAOGO

This study represents a significant advancement in fish ecology by applying deep learning techniques to automate and improve the counting of growth rings in otoliths, which are essential for determining the age and growth patterns of fish. Traditionally, manual methods have been used to analyze these rings, but these approaches… Read full abstract & cite →

Otoliths deep learning pattern recognition RANSAC automated counting

Abstract doi.org/10.14569/IJACSA.2024.0151292 PDF

93

Enhancing Steganography Security with Generative AI: A Robust Approach Using Content-Adaptive Techniques and FC DenseNet

Author 1: Ayyah Abdulhafidh Mahmoud Fadhl Author 2: Bander Ali Saleh Al-rimy Author 3: Sultan Ahmed Almalki Author 4: Tami Alghamdi Author 5: Azan Hamad Alkhorem Author 6: Frederick T. Sheldon

Content-adaptive image steganography based on minimizing the additive distortion function and Generative Ad-versarial Networks (GAN) is a promising trend. This approach can quickly generate an embedding probability map and has a higher security performance than hand-crafted methods. however, existing works have ignored the semantic information between neighbouring pixels and the… Read full abstract & cite →

Content adaptive distortion function GAN FC DenseNet steganography steganalysis

Abstract doi.org/10.14569/IJACSA.2024.0151293 PDF

94

Novel Collaborative Intrusion Detection for Enhancing Cloud Security

Author 1: Widad Elbakri Author 2: Maheyzah Md. Siraj Author 3: Bander Ali Saleh Al-rimy Author 4: Sultan Ahmed Almalki Author 5: Tami Alghamdi Author 6: Azan Hamad Alkhorem Author 7: Frederick T. Sheldon

Intrusion Detection Models (IDM) often suffer from poor accuracy, especially when facing coordinated attacks such as Distributed Denial of Service (DDoS). One significant limitation of existing IDM solutions is the lack of an effective technique to determine the optimal period for sharing attack information among nodes in a distributed IDM… Read full abstract & cite →

Cloud security intrusion detection collaborative model feature selection anomaly detection Pruned Exact Linear Time (PELT) gradient boosting machine support vector machine NSL-KDD DDoS

Abstract doi.org/10.14569/IJACSA.2024.0151294 PDF

95

Near-Optimal Traveling Salesman Solution with Deep Attention

Author 1: Natdanai Kafakthong Author 2: Krung Sinapiromsaran

The Traveling Salesman Problem (TSP) is a well-known problem in computer science that requires finding the shortest possible route that visits every city exactly once. TSP has broad applications in logistics, routing, and supply chain management, where finding optimal or near-optimal solutions efficiently can lead to substantial cost and time… Read full abstract & cite →

Traveling salesman problem deep learning genetic algorithm

Abstract doi.org/10.14569/IJACSA.2024.0151295 PDF

96

Leveraging Deep Learning for Enhanced Information Security: A Comprehensive Approach to Threat Detection and Mitigation

Author 1: KaiJing Wang

Forcing developments in cyberspace means protecting information resources requires enhanced and more dynamic protection models. Traditional approaches don’t adequately address the numerous, sophisticated, varied, and frequently intersecting emergent security challenges, such as malware, phishing, and DDoS attacks. This paper introduces a novel hybrid deep learning framework leveraging convolutional neural networks… Read full abstract & cite →

Artificial intelligence deep learning information security threat detection cybersecurity convolutional neural net-work recurrent neural network mitigation

Abstract doi.org/10.14569/IJACSA.2024.0151296 PDF

97

SGCN: Structure and Similarity-Driven Graph Convolutional Network for Semi-Supervised Classification

Author 1: WenQiang Guo Author 2: YongLong Hu Author 3: YongYan Hou Author 4: BoFeng Xue

Traditional Graph Convolutional Networks (GCNs) primarily utilize graph structural information for information aggregation, often neglecting node attribute information. This approach can distort node similarity, resulting in ineffective node feature representations and reduced performance in semi-supervised node classification tasks. To address these issues, this study introduces a similarity measure based on… Read full abstract & cite →

Graph convolutional networks semi-supervised node classification Minkowski distance similarity information

Abstract doi.org/10.14569/IJACSA.2024.0151297 PDF

98

Empowering Home Care: Utilizing IoT and Deep Learning for Intelligent Monitoring and Management of Chronic Diseases

Author 1: Nouf Alabdulqader Author 2: Khaled Riad Author 3: Badar Almarri

Integrating Internet of Things (IoT) with Artificial Intelligence (AI) is one of the catalysts for improving traditional healthcare services. This integration has created many opportunities that have led to healthcare shifting towards enabling home care, the concept that harnesses the technologies advanced potential such as the IoT and deep learning… Read full abstract & cite →

IoT IoMT intelligent monitoring chronic diseases deep learning home care physiological data mHealth

Abstract doi.org/10.14569/IJACSA.2024.0151298 PDF

99

Performance Comparison of Object Detection Models for Road Sign Detection Under Different Conditions

Author 1: Zainab Fatima Author 2: M. Hassan Tanveer Author 3: Hira Mariam Author 4: Razvan Cristian Voicu Author 5: Tanazzah Rehman Author 6: Rizwan Riaz

During driving, drivers often overlook the traffic signs along the roads compromising road safety and increasing the risk of accidents. To address this, artificial intelligence (AI) and deep learning techniques are employed, taking into consideration the improvement of advances in Artificial Neural Networks (ANNs) and image processing for robust road… Read full abstract & cite →

Artificial intelligence artificial neural networks image processing deep learning road signs detection

Abstract doi.org/10.14569/IJACSA.2024.0151299 PDF

100

Accuracy Optimization and Wide Limit Constraints of DC Energy Measurement Based on Improved EEMD

Author 1: Xiaoyu Wang Author 2: Xin Yin Author 3: Xinggang Li Author 4: Jiangxue Man Author 5: Yanhe Liang Author 6: Fan Xu

In modern power systems, with the increasing application of renewable energy, direct current transmission technology has put forward new requirements for energy metering. In order to solve the accuracy problem of traditional electric energy metering under DC energy, the research is based on the classical empirical modal decomposition (EEMD), and… Read full abstract & cite →

EEMD direct current energy measurement width limit ACROA

Abstract doi.org/10.14569/IJACSA.2024.01512100 PDF