IJACSA Vol. 15 Issue 3 (2024)

1

Network Intrusion Detection in Cloud Environments: A Comparative Analysis of Approaches

Author 1: Sina Ahmadi

This research study comprehensively analyzes network intrusion detection in cloud environments by examining several approaches. These approaches have been explored and compared to determine the optimal and appropriate choice based on specific conditions. This research study employs a qualitative approach, specifically conducting a thematic literature analysis from 2020 to 2024… Read full abstract & cite →

Cloud networking cloud security firewall intrusion detection NIDS

Abstract doi.org/10.14569/IJACSA.2024.0150301 PDF

2

Analysis of Gait Motion Sensor Mobile Authentication with Machine Learning

Author 1: Sara Kokal Author 2: Mounika Vanamala Author 3: Rushit Dave

In recent decades, mobile devices have evolved in potential and prevalence significantly while advancements in security have stagnated. As smartphones now hold unprecedented amounts of sensitive data, there is an increasing need to resolve this gap in security. To address this issue, researchers have experimented with biometric-based authentication methods to… Read full abstract & cite →

Machine learning machine learning algorithms behavioral biometrics gait dynamics motion sensors

Abstract doi.org/10.14569/IJACSA.2024.0150302 PDF

3

Privacy-Aware Decision Making: The Effect of Privacy Nudges on Privacy Awareness and the Monetary Assessment of Personal Information

Author 1: Vera Schmitt Author 2: James Nicholson Author 3: Sebastian Moller

Nowadays, smartphones are equipped with various sensors collecting a huge amount of sensitive personal information about their users. However, for smartphone users, it remains hidden, and sensitive information is accessed by used applications and data requesters. Moreover, governmental institutions have no means to verify if applications requesting sensitive informa-tion are… Read full abstract & cite →

Privacy protection privacy policy analysis GDPR willingness to pay privacy awareness

Abstract doi.org/10.14569/IJACSA.2024.0150303 PDF

4

User Experience and Behavioural Adaptation Based on Repeated Usage of Vehicle Automation: Online Survey

Author 1: Naomi Y. Mbelekani Author 2: Klaus Bengler

For years, Level 2 vehicle automation systems (VAS) have been commercially available, yet the extent to which users comprehend their capabilities and limitations remains largely unclear. This study aimed to evaluate user knowledge regarding Level 2 VAS and explore the correlation between user experiences (UX), behavioural adaptations, trust, and acceptance… Read full abstract & cite →

Automated vehicles automation effects user experience (UX) trust acceptance behavioural adaptations

Abstract doi.org/10.14569/IJACSA.2024.0150304 PDF

5

Generative Adversarial Neural Networks for Realistic Stock Market Simulations

Author 1: Badre Labiad Author 2: Abdelaziz Berrado Author 3: Loubna Benabbou

Stock market simulations are widely used to create synthetic environments for testing trading strategies before deploying them to real-time markets. However, the weak realism often found in these simulations presents a significant challenge. Improving the quality of stock market simulations could be facilitated by the availability of rich and granular… Read full abstract & cite →

Limit order book simulations transformers wasserstein GAN with gradient penalty FI-2010 benchmark dataset

Abstract doi.org/10.14569/IJACSA.2024.0150305 PDF

6

Integrating Generative AI for Advancing Agile Software Development and Mitigating Project Management Challenges

Author 1: Anas BAHI Author 2: Jihane GHARIB Author 3: Youssef GAHI

Agile software development emphasizes iterative progress, adaptability, and stakeholder collaboration. It champions flexible planning, continuous improvement, and rapid delivery, aiming to respond swiftly to change and deliver value efficiently. Integrating Generative Artificial Intelligence (AI) into Agile software development processes presents a promising avenue for overcoming project management challenges and enhancing… Read full abstract & cite →

Artificial intelligence software engineering Agile software development

Abstract doi.org/10.14569/IJACSA.2024.0150306 PDF

7

Comparing Regression Models to Predict Property Crime in High-Risk Lima Districts

Author 1: Maria Escobedo Author 2: Cynthia Tapia Author 3: Juan Gutierrez Author 4: Victor Ayma

Crime continues to be an issue, in Metropolitan Lima, Peru affecting society. Our focus is on property crimes. We recognized the lack of studies on predicting these crimes. To tackle this problem, we used regression techniques such as XGBoost, Extra Tree, Support Vector, Bagging, Random Forest and AdaBoost. Through GridsearchCV… Read full abstract & cite →

Supervised techniques machine learning regression crime prediction

Abstract doi.org/10.14569/IJACSA.2024.0150307 PDF

8

Educational Performance Prediction with Random Forest and Innovative Optimizers: A Data Mining Approach

Author 1: Yanli Chen Author 2: Ke Jin

In the ever-evolving landscape of education, institutions grapple with the intricate task of evaluating individual capabilities and forecasting student performance. Providing timely guidance becomes pivotal, steering students toward specific areas for focused academic enhancement. Within the educational domain, the utilization of data mining emerges as a powerful tool, revealing latent… Read full abstract & cite →

Student performance Random Forest Classification victoria amazonia phasor particle swarm

Abstract doi.org/10.14569/IJACSA.2024.0150308 PDF

9

Fuzzy Deep Learning Approach for the Early Detection of Degenerative Disease

Author 1: Chairani Author 2: Suhendro Y. Irianto Author 3: Sri Karnila Author 4: Adimas

Degenerative diseases can impact individuals of any age, encompassing children and teenagers; however, they typically tend to affect productive or adult individuals. Globally, conventional and advanced diagnostic methods, including those developed in Indonesia, have emerged to identify and manage these health conditions. Problems in brain tumor detection are the intricate… Read full abstract & cite →

Degenerative diseases brain tumor fuzzy deep learning

Abstract doi.org/10.14569/IJACSA.2024.0150309 PDF

10

Offline Author Identification using Non-Congruent Handwriting Data Based on Deep Convolutional Neural Network

Author 1: Ying LIU Author 2: Gege Meng Author 3: Naiyue ZHANG

This investigation presents a novel technique for offline author identification using handwriting samples across diverse experimental conditions, addressing the intricacies of various writing styles and the imperative for organizations to authenticate authorship. Notably, the study leverages inconsistent data and develops a method independent of language constraints. Utilizing a comprehensive dataset… Read full abstract & cite →

Handwriting recognition offline author identification deep convolutional neural network image processing language versatility feature extraction hierarchical model

Abstract doi.org/10.14569/IJACSA.2024.0150310 PDF

11

An Efficient and Intelligent System for Controlling the Speed of Vehicle using Fuzzy Logic and Deep Learning

Author 1: Anup Lal Yadav Author 2: Sandip Kumar Goyal

Vehicle collisions are a significant problem worldwide, causing injuries, fatalities, and property damage. There are several reasons for the collapse of vehicles such as rash driving, over speeding, less driving skills, increasing number of vehicles, drunk and drive, etc. However, over speeding is one of the critical factors out of… Read full abstract & cite →

Speed control fuzzy logics deep learning decision making collision avoidance

Abstract doi.org/10.14569/IJACSA.2024.0150311 PDF

12

A Single Stage Detector for Breast Cancer Detection on Digital Mammogram

Author 1: Li Xu Author 2: Nan Jia Author 3: Mingmin Zhang

Medical image processing plays a pivotal role in modern healthcare, and the early detection of breast cancer in digital mammograms. Several methods have been explored in the literature to improve breast cancer detection, with deep-learning approaches emerging as particularly promising due to their ability to provide accurate results. However, a… Read full abstract & cite →

Breast cancer detection digital mammogram deep learning YOLOv5 algorithm medical image processing

Abstract doi.org/10.14569/IJACSA.2024.0150312 PDF

13

Introducing an Innovative Approach to Mitigate Investment Risk in Financial Markets: A Case Study of Nikkei 225

Author 1: Xiao Duan

When the value of an investor's stock portfolio rises during a period of great market performance, investors often experience a gain in wealth. Spending may increase when people feel more at ease and confident about their financial circumstances. On the other hand, during a market crisis, a fall in wealth… Read full abstract & cite →

NIKKEI 225 index artificial bee colony stock price financial markets support vector regression

Abstract doi.org/10.14569/IJACSA.2024.0150313 PDF

14

Clustering Algorithms in Sentiment Analysis Techniques in Social Media – A Rapid Literature Review

Author 1: Vasile Daniel Pavaloaia

Based on the high dynamic of Sentiment Analysis (SA) topic among the latest publication landscape, the current review attempts to fill a research gap. Consequently, the paper elaborates on the most recent body of literature to extract and analyze the papers that elaborate on the clustering algorithms applied on social… Read full abstract & cite →

Clustering algorithms K-means HAC DBSCAN sentiment analysis natural language processing techniques social media datasets Twitter/X

Abstract doi.org/10.14569/IJACSA.2024.0150314 PDF

15

A Systematic Review of the Literature on the Use of Artificial Intelligence in Forecasting the Demand for Products and Services in Various Sectors

Author 1: José Rolando Neira Villar Author 2: Miguel Angel Cano Lengua

This systematic review, carried out under the PRISMA methodology, aims to identify the recently proposed artificial intelligence models for demand forecasting, distinguishing the problems they try to overcome, recognizing the artificial intelligence methods used, detailing the performance metrics used, recognizing the performance achieved by these models and identifying what is… Read full abstract & cite →

Demand agglomeration algorithm services PRISMA methodology artificial intelligence

Abstract doi.org/10.14569/IJACSA.2024.0150315 PDF

16

Integration of Effective Models to Provide a Novel Method to Identify the Future Trend of Nikkei 225 Stocks Index

Author 1: Jiang Zhu Author 2: Haiyan Wu

The stock market refers to a financial market in which individuals and institutions engage in the buying and selling of shares of publicly listed firms. The valuation of stocks is influenced by the interplay between the forces of supply and demand. The act of allocating funds to the stock market… Read full abstract & cite →

Financial market stock future trend Nikkei 225 index random forest artificial bee colony

Abstract doi.org/10.14569/IJACSA.2024.0150316 PDF

17

A CNN-based Deep Learning Framework for Driver’s Drowsiness Detection

Author 1: Ali Sohail Author 2: Asghar Ali Shah Author 3: Sheeba Ilyas Author 4: Nizal Alshammry

Accidents are one of the major causes of injuries and deaths worldwide. According to the WHO report, in 2022 an estimated 1.3 million people die from road accidents. Driver fatigue is the primary factor in these traffic accidents. There are a number of studies presented by previous researchers in the… Read full abstract & cite →

Drowsiness detection face detection eye detection yawn detection deep learning convolutional neural network electroencephalograph eye aspect ratio

Abstract doi.org/10.14569/IJACSA.2024.0150317 PDF

18

A Fire and Smoke Detection Model Based on YOLOv8 Improvement

Author 1: Pengcheng Gao

The warning of fire and smoke provides security for people's lives and properties. The utilization of deep learning for fire and smoke warning has been an active area of research, especially the use of target detection algorithms has achieved significant results. For improving the fire and smoke detection performance of… Read full abstract & cite →

Fire and smoke detection deep learning computer vision YOLO

Abstract doi.org/10.14569/IJACSA.2024.0150318 PDF

19

Prediction of Cardiovascular Disease using Machine Learning Algorithms

Author 1: Mahesh Kumar Joshi Author 2: Deepak Dembla Author 3: Suman Bhatia

Heart is the most critical organ of our body for being responsible for regulating and maintaining the blood circulation levels. Globally, heart disease cases are prevalent and constitute a significant cause of mortality. Manifestations such as chest discomfort and irregular heartbeat are notable symptoms. The healthcare sector has amassed substantial… Read full abstract & cite →

Cardiovascular disease heart logistic regression K-NN machine learning naïve bayes SVM

Abstract doi.org/10.14569/IJACSA.2024.0150319 PDF

20

Underwater Image Enhancement via Higher-Order Moment CLAHE Model and V Channel Substitute

Author 1: Chen Yahui Author 2: Liang Yitao Author 3: Li Yongfeng Author 4: Liu Hongyue Author 5: Li Lan

Images captured underwater often exhibit low contrast and color distortion attributed to special properties of light in water. Underwater image enhancement methods have become an effective solution to address these issues due to its simplicity and effectiveness. However, underwater image enhancement methods (such as CLAHE) face challenge of increasing image… Read full abstract & cite →

Underwater images contrast enhancement adaptive CLAHE high-order moments dynamic features

Abstract doi.org/10.14569/IJACSA.2024.0150320 PDF

21

Towards Digital Preservation of Cultural Heritage: Exploring Serious Games for Songket Tradition

Author 1: Nor Hafidzah Abdullah Author 2: Wan Malini Wan Isa Author 3: Syadiah Nor Wan Shamsuddin Author 4: Norkhairani Abdul Rawi Author 5: Maizan Mat Amin Author 6: Wan Mohd Adzim Wan Mohd Zain

Over the past few decades, Malaysia has undergone remarkable technological advancement, establishing itself as a vibrant hub for innovation in Southeast Asia. However, technological progress must be harmonized with preserving and promoting the country's cultural heritage. Digital preservation of cultural heritage emerges as a critical endeavor, particularly for future generations… Read full abstract & cite →

Cultural Heritage digital preservation serious game Songket

Abstract doi.org/10.14569/IJACSA.2024.0150321 PDF

22

RUICP: Commodity Recommendation Model Based on User Real Time Interest and Commodity Popularity

Author 1: Wenchao Xu Author 2: Ling Xia

At present, the recommendation of massive commodities mainly depends on the short-term click through rate of commodities and the data directly browsed and clicked by users. This recommendation method can better meet the shopping needs of users, but there are two shortcomings. One is to recommend homogeneous commodities to long-term… Read full abstract & cite →

User real time interest commodity popularity recommend

Abstract doi.org/10.14569/IJACSA.2024.0150322 PDF

23

Beyond BERT: Exploring the Efficacy of RoBERTa and ALBERT in Supervised Multiclass Text Classification

Author 1: Christian Y. Sy Author 2: Lany L. Maceda Author 3: Mary Joy P. Canon Author 4: Nancy M. Flores

This study investigates the performance of transformer-based machine learning models, specifically BERT, RoBERTa, and ALBERT, in multiclass text classification within the context of the Universal Access to Quality Tertiary Education (UAQTE) program. The aim is to systematically categorize and analyze qualitative responses to uncover domain-specific patterns in students' experiences. Through… Read full abstract & cite →

Multi-class text classification Bidirectional Encoder Representations from Transformers (BERT) RoBERTa ALBERT Universal Access to Quality Tertiary Education (UAQTE) program educational policy reforms

Abstract doi.org/10.14569/IJACSA.2024.0150323 PDF

24

Assessment of Attention-based Deep Learning Architectures for Classifying EEG in ADHD and Typical Children

Author 1: Mingzhu Han Author 2: Guoqin Jin Author 3: Wei Li

Although limited research has explored the integration of electroencephalography (EEG) and deep learning approaches for attention deficit hyperactivity disorder (ADHD) detection, using deep learning models for actual data, including EEGs, remains a difficult endeavour. The purpose of this work was to evaluate how different attention processes affected the performance of… Read full abstract & cite →

ADHD EEG deep learning attention mechanisms CNN LSTM

Abstract doi.org/10.14569/IJACSA.2024.0150324 PDF

25

Precision Face Mask Detection in Crowded Environment using Machine Vision

Author 1: Jamil Abedalrahim Jamil Alsayaydeh Author 2: Mohd Faizal bin Yusof Author 3: Chan Yoke Lin Author 4: Mohammed Nasser Mohammed Al-Andoli Author 5: Safarudin Gazali Herawan Author 6: Ida Syafiza Md Isa

In the face of rampant global disease transmission, effective preventive strategies are imperative. This study tackles the challenge of ensuring compliance in crowded settings by developing a sophisticated face mask detection system. Utilizing MATLAB and the Cascade Object detector, the system focuses on detecting white surgical masks in frontal images… Read full abstract & cite →

Face mask detection machine vision cascade object detector cross-validation

Abstract doi.org/10.14569/IJACSA.2024.0150325 PDF

26

Predicting Obesity in Nutritional Patients using Decision Tree Modeling

Author 1: Orlando Iparraguirre-Villanueva Author 2: Luis Mirano-Portilla Author 3: Manuel Gamarra-Mendoza Author 4: Wilmer Robles-Espiritu

Obesity has become a widespread problem that affects not only physical well-being but also mental health. To address this problem and provide solutions, Machine Learning (ML) technology tools are being applied. Studies are currently being developed to improve the prediction of obesity. This study aimed to predict obesity levels in… Read full abstract & cite →

Obesity Machine Learning (ML) Decision Tree (DT) Prediction CRISP-DM

Abstract doi.org/10.14569/IJACSA.2024.0150326 PDF

27

Presenting a Hybrid Method to Overcome the Challenges of Determining the Uncertainty of Future Stock Price Identification

Author 1: Zhiqiong Zou Author 2: Guangyu Xiao

A particular location, framework, or forum where buyers and sellers congregate to trade products, services, or assets is referred to as an economic market. While the future is unpredictable and unknowable, it is still possible to make informed predictions about the course of events. Predicting stock market movements using artificial… Read full abstract & cite →

Stock market prediction movement prediction models Radical basis function optimization approaches

Abstract doi.org/10.14569/IJACSA.2024.0150327 PDF

28

Design and Implementation of a Real-Time Image Processing System Based on Sobel Edge Detection using Model-based Design Methods

Author 1: Taoufik Saidani Author 2: Refka Ghodhbani Author 3: Mohamed Ben Ammar Author 4: Marouan Kouki Author 5: Mohammad H Algarni Author 6: Yahia Said Author 7: Amani Kachoukh Author 8: Amjad A. Alsuwaylimi Author 9: Albia Maqbool Author 10: Eman H. Abd-Elkawy

Image processing and computer vision applications often use the Sobel edge detection technique in order to discover corners in input photographs. This is done in order to improve accuracy and efficiency. For the great majority of today's image processing applications, real-time implementation of image processing techniques like Sobel edge detection… Read full abstract & cite →

Image processing sobel edge detection high level synthesis model based design Zynq7000 MATLAB HDL coder

Abstract doi.org/10.14569/IJACSA.2024.0150328 PDF

29

Framework for Organization of Medical Processes in Medical Institutions Based on Big Data Technologies

Author 1: Botagoz Zhussipbek Author 2: Tursinbay Turymbetov Author 3: Nuraim Ibragimova Author 4: Zinegul Yergalauova Author 5: Gulmira Nigmetova Author 6: Saule Tanybergenova Author 7: Zhanar Musagulova

This research paper delves into the burgeoning field of Big Data analytics in healthcare, proposing an innovative framework aimed at refining the organization and management of medical processes within healthcare institutions. Through the lens of detailed case studies, including stroke diagnosis leveraging the UNet model, and the identification of heart… Read full abstract & cite →

Big data data-driven technology artificial intelligence medical processes medical institutions

Abstract doi.org/10.14569/IJACSA.2024.0150329 PDF

30

Research on Personalized Recommendation Algorithms Based on User Profile

Author 1: Guo Hui Author 2: Zhou LiQing Author 3: Chen Mang Author 4: Xv ShiKun

In recent decades, recommendation systems (RS) have played a pivotal role in societal life, closely intertwined with people's everyday activities. However, traditional recommendation systems still require thorough consideration of comprehensive user profiles as they have struggled to provide more personalized and accurate recommendation services. This paper delves into the analysis… Read full abstract & cite →

Recommender system large language model user profile multi-disciplinary

Abstract doi.org/10.14569/IJACSA.2024.0150330 PDF

31

Intelligent Fuzzy-PID Temperature Control System for Ensuring Comfortable Microclimate in an Intelligent Building

Author 1: Rustam Abdrakhmanov Author 2: Kamalbek Berkimbayev Author 3: Angisin Seitmuratov Author 4: Almira Ibashova Author 5: Akbayan Aliyeva Author 6: Gulira Nurmukhanbetova

In an era characterized by the growing significance of energy-efficient and human-centric environmental control systems, this research endeavors to investigate the efficacy of a Fuzzy Proportional-Integral-Derivative (PID) control approach for temperature regulation within Heating, Ventilation, and Air Conditioning (HVAC) systems. The study leverages the adaptability and robustness of fuzzy logic… Read full abstract & cite →

Fuzzy logic PID Temperature Microclimate Smart Building

Abstract doi.org/10.14569/IJACSA.2024.0150331 PDF

32

Machine Learning Enhanced Framework for Big Data Modeling with Application in Industry 4.0

Author 1: Gulnur Kazbekova Author 2: Zhuldyz Ismagulova Author 3: Botagoz Zhussipbek Author 4: Yntymak Abdrazakh Author 5: Gulzipa Iskendirova Author 6: Nurgul Toilybayeva

In the dynamic milieu of Industry 4.0, characterized by the deluge of big data, this research promulgates a groundbreaking framework that harnesses machine learning (ML) to optimize big data modeling processes, addressing the intricate requirements and challenges of contemporary industrial domains. Traditional data processing mechanisms falter in the face of… Read full abstract & cite →

Industry 4.0 machine learning big data application management

Abstract doi.org/10.14569/IJACSA.2024.0150332 PDF

33

Deep CNN Approach with Visual Features for Real-Time Pavement Crack Detection

Author 1: Bakhytzhan Kulambayev Author 2: Gulnar Astaubayeva Author 3: Gulnara Tleuberdiyeva Author 4: Janna Alimkulova Author 5: Gulzhan Nussupbekova Author 6: Olga Kisseleva

This research delves into an innovative approach to an age-old urban maintenance challenge: the timely and accurate detection of pavement cracks, a key issue linked to public safety and fiscal efficiency. Harnessing the power of Deep Convolutional Neural Networks (DCNNs), the study introduces a cutting-edge model, meticulously optimized for the… Read full abstract & cite →

Road damage crack image processing classification segmentation

Abstract doi.org/10.14569/IJACSA.2024.0150333 PDF

34

Development of Deep Learning Enabled Augmented Reality Framework for Monitoring the Physical Quality Training of Future Trainers-Teachers

Author 1: Sarsenkul Tileubay Author 2: Meruert Yerekeshova Author 3: Altynzer Baiganova Author 4: Dariqa Janyssova Author 5: Nurlan Omarov Author 6: Bakhytzhan Omarov Author 7: Zakhira Baiekeyeva

The fusion of augmented reality (AR) and deep learning technologies has ushered in a transformative era in the realm of real-time physical activity monitoring. This research paper introduces a system that harnesses the capabilities of PoseNet-based skeletal keypoint extraction and deep neural networks to achieve unparalleled accuracy and real-time functionality… Read full abstract & cite →

PoseNET MoveNET deep learning exercise computer vision

Abstract doi.org/10.14569/IJACSA.2024.0150334 PDF

35

A Cyclic Framework for Ethical Implications of Artificial Intelligence in Autonomous Vehicles

Author 1: Ahmed M. Shamsan Saleh

The emergence of artificial intelligence (AI)-powered autonomous vehicles (AVs) represents a significant turning point in field of transportation, offering the potential for improved safety, efficiency, and convenience. However, the use of AI in this particular context exhibits significant ethical implications that require careful examination. This paper presents an extensive analysis… Read full abstract & cite →

Artificial intelligence autonomous vehicles ethical implications AI decision-making

Abstract doi.org/10.14569/IJACSA.2024.0150335 PDF

36

Deep Learning to Predict Start-Up Business Success

Author 1: Lobna Hsairi

Over the past few decades, there has been rapid growth in the formation of new start-ups around the world. Thus, it is an important and challenging task to understand what makes start-ups successful and to predict their success. Several reasons are responsible for the success and failure of a start-up… Read full abstract & cite →

Deep learning Convolutional Neural Network (CNN) prediction start-up business

Abstract doi.org/10.14569/IJACSA.2024.0150336 PDF

37

Data-Driven Rice Yield Predictions and Prescriptive Analytics for Sustainable Agriculture in Malaysia

Author 1: Muhammad Marong Author 2: Nor Azura Husin Author 3: Maslina Zolkepli Author 4: Lilly Suriani Affendey

Maximizing rice yield is critical for ensuring food security and sustainable agriculture in Malaysia. This research investigates the impact of environmental conditions and management methods on crop yields, focusing on accurate predictions to inform decision-making by farmers. Utilizing machine learning algorithms as decision-support tools, the study analyses commonly used models—Linear… Read full abstract & cite →

Rice yield prediction sustainable agriculture linear regression support vector machine artificial neural network predictive analytics

Abstract doi.org/10.14569/IJACSA.2024.0150337 PDF

38

AI-based KNN Approaches for Predicting Cooling Loads in Residential Buildings

Author 1: Zhaofang Du

Cooling Load (CL) estimation in residential buildings is crucial for optimizing energy consumption and ensuring indoor comfort. This article presents an innovative approach that leverages Artificial Intelligence (AI) techniques, particularly K-Nearest Neighbors (KNN), in combination with advanced optimizers, including Dynamic Arithmetic Optimization (DAO) and Wild Geese Algorithm (WGA), to enhance… Read full abstract & cite →

Cooling load K-nearest neighbor dynamic arithmetic optimization wild geese algorithm

Abstract doi.org/10.14569/IJACSA.2024.0150338 PDF

39

Enhanced Detection of COVID-19 using Deep Learning and Multi-Agent Framework: The DLRPET Approach

Author 1: Rupinder Kaur Walia Author 2: Harjot Kaur

The ongoing global pandemic caused by novel coronavirus (COVID-19) has emphasized the urgent need for accurate and efficient methods of detection. Over the past few years, several methods were proposed by various researchers for detecting COVID-19, but there is still a scope of improvement. Considering this, an effective and highly… Read full abstract & cite →

COVID-19 deep learning SVM ResNet disease classification biomedical applications multi-agent

Abstract doi.org/10.14569/IJACSA.2024.0150339 PDF

40

Experimental IoT System to Maintain Water Quality in Catfish Pond

Author 1: Adani Bimasakti Wibisono Author 2: Riyanto Jayadi

This study investigates the challenges in catfish aquaculture, mainly focusing on water quality, which is crucial for successful fish farming. This research aims to implement Internet of Things (IoT) technology with sensors connected to a microcontroller to monitor and control critical parameters such as temperature, pH, and oxygen levels in… Read full abstract & cite →

IoT aquaculture catfish cultivation monitoring controlling

Abstract doi.org/10.14569/IJACSA.2024.0150340 PDF

41

Revolutionizing Education: Cutting-Edge Predictive Models for Student Success

Author 1: Moyan Li Author 2: Suyawen

Student performance prediction systems are crucial for improving educational outcomes in various institutions, including universities, schools, and training centers. These systems gather data from diverse sources such as examination centers, registration departments, virtual courses, and e-learning platforms. Analyzing educational data is challenging due to its vast and varied nature, and… Read full abstract & cite →

Student performance Support Vector Classification sea horse optimization adaptive opposition slime mould algorithm

Abstract doi.org/10.14569/IJACSA.2024.0150341 PDF

42

Disease-Aware Chest X-Ray Style GAN Image Generation and CatBoost Gradient Boosted Trees

Author 1: Andi Besse Firdausiah Mansur

Artificial Intelligence has significantly advanced and is proficient in image classification. Even though the COVID-19 pandemic has ended, the virus is now considered to have entered an endemic phase. Historically, COVID-19 detection has predominantly depended on a single technology known as the polymerase chain reaction (PCR). The academic community is… Read full abstract & cite →

Artificial intelligence StyleGAN chest X-ray prediction COVID19 CatBoost gradient boosted trees

Abstract doi.org/10.14569/IJACSA.2024.0150342 PDF

43

Cyber Security Intrusion Detection and Bot Data Collection using Deep Learning in the IoT

Author 1: Fahad Ali Alotaibi Author 2: Shailendra Mishra

In the digital age, cybersecurity is a growing concern, especially as IoT continues to grow rapidly. Cybersecurity intrusion detection systems are critical in protecting IoT environments from malicious activity. Deep learning approaches have emerged as promising intrusion detection techniques due to their ability to automatically learn complex patterns and features… Read full abstract & cite →

Internet of things intrusion detection system random neural networks feed forward neural networks convolutional neural networks

Abstract doi.org/10.14569/IJACSA.2024.0150343 PDF

44

Method for Disaster Area Detection with Just One SAR Data Acquired on the Day After Earthquake Based on YOLOv8

Author 1: Kohei Arai Author 2: Yushin Nakaoka Author 3: Hiroshi Okumura

Method for earthquake disaster area detection with just a single satellite-based SAR data which is acquired on the day after earthquake based on object detection method of YOLOv8 and Detectron2 is proposed. Through experiments with several SAR data derived from the different SAR satellites which observed Noto Peninsula earthquake occurred… Read full abstract & cite →

SAR YOLOv8 Detectron2 earthquake disaster disaster area detection noto peninsula earthquake

Abstract doi.org/10.14569/IJACSA.2024.0150344 PDF

45

Forecasting the Yoga Influence on Chronic Venous Insufficiency: Employing Machine Learning Methods

Author 1: Xiao Du

This investigation introduces a groundbreaking approach to unravel the complexities of Chronic Venous Insufficiency (CVI) by leveraging machine learning, notably the Support Vector Classification (SVC), alongside optimization systems like Dwarf Mon-goose Optimization (DMO) and Smell Agent Optimization (SAO). This pioneering strategy not only aims to bolster predictive Precision but also… Read full abstract & cite →

Chronic Venous Insufficiency yoga classification machine learning Support Vector Classification smell agent optimization Dwarf Mongoose Optimization

Abstract doi.org/10.14569/IJACSA.2024.0150345 PDF

46

Multi-Track Music Generation Based on the AC Algorithm and Global Value Return Network

Author 1: Wei Guo

In the current field of deep learning and music information retrieval, automated music generation has become a hot research topic. This study addresses the issues of low clarity and musicality in current multi-track music generation by combining the Actor-Critic algorithm and the Global Value Return Network to create a novel… Read full abstract & cite →

AC global value return network track music model rhythm melody

Abstract doi.org/10.14569/IJACSA.2024.0150346 PDF

47

Defining Integrated Agriculture Information System Non-Functional Requirement and Re-engineering the Metadata

Author 1: Argo Wibowo Author 2: Antonius Rachmat Chrismanto Author 3: Gabriel Indra Widi Tamtama Author 4: Rosa Delima

Developing a well-functioning information system like integrated agriculture information system (IAIS) requires a list of task requirements that will be transformed into system features. Feature Driven Development (FDD) model is suitable for this situation. The requirements for building an information system are not solely based on functional needs but also… Read full abstract & cite →

Information system non-functional requirements BPMN metadata feature-driven development

Abstract doi.org/10.14569/IJACSA.2024.0150347 PDF

48

Novel Design of a Robotic Arm Prototype with Complex Movements Based on Surface EMG Signals to Assist Disabilities in Vietnam

Author 1: Ngoc–Khoat Nguyen Author 2: Thi–Mai–Phuong Dao Author 3: Van–Kien Nguyen Author 4: Van–Hung Pham Author 5: Van–Minh Pham Author 6: Van–Nam Pham

In recent years, surface electromyography (sEMG) signals have been recognized as a type of signal with significant practical implications not only in medicine but also in the field of science and engineering for functional rehabilitation. This study focuses on understanding the application of surface electromyography signals in controlling a robotic… Read full abstract & cite →

Disabilities sEMG signal processing human arm robotic arm

Abstract doi.org/10.14569/IJACSA.2024.0150348 PDF

49

A Bloom Cognitive Hierarchical Classification Model for Chinese Exercises Based on Improved Chinese-RoBERTa-wwm and BiLSTM

Author 1: Zhaoyu Shou Author 2: Yipeng Liu Author 3: Dongxu Li Author 4: Jianwen Mo Author 5: Huibing Zhang

Assessing students' cognitive ability is one of the most important prerequisites for improving learning effectiveness, and the process involves aspects such as exercises, students' answers and teaching cases. In order to effectively assess students' cognitive ability, this paper proposes a Chinese text classification model that can automatically and accurately classify… Read full abstract & cite →

Chinese Text Classification Chinese-RoBERTa-wwm BiLSTM Bloom Cognitive Hierarchy

Abstract doi.org/10.14569/IJACSA.2024.0150349 PDF

50

The Application of Improved Scale Invariant Feature Transformation Algorithm in Facial Recognition

Author 1: Yingzi Cong

Currently, face recognition models suffer from insufficient accuracy, stability, and computational efficiency. To address this issue, an improved feature extraction algorithm on the ground of Haar wavelet features and scale invariant feature transformation algorithm is proposed. In addition, the study also combines this algorithm with deep belief networks to construct… Read full abstract & cite →

Haar wavelet features scale invariant feature transformation algorithm deep belief network facial recognition performance improvement

Abstract doi.org/10.14569/IJACSA.2024.0150350 PDF

51

Designing a Mobile Application for Identifying Strawberry Diseases with YOLOv8 Model Integration

Author 1: Thuy Van Tran Author 2: Quang - Huy Do Ba Author 3: Kim Thanh Tran Author 4: Dang Hai Nguyen Author 5: Dinh Chung Dang Author 6: Van - Luc Dinh

The progress in computer vision has led to the development of potential solutions, becoming a versatile technological key to addressing challenging issues in agriculture. These solutions aim to enhance the quality of agricultural products, boost the economy's competitiveness, and reduce labor and costs. Specifically, the detection of diseases in various… Read full abstract & cite →

Computer vision YOLOv8 strawberry diseases

Abstract doi.org/10.14569/IJACSA.2024.0150351 PDF

52

Exploring the Landscape: Analysis of Model Results on Various Convolutional Neural Network Architectures for iRESPOND System

Author 1: Freddie Prianes Author 2: Kaela Marie Fortuno Author 3: Rosel Onesa Author 4: Brenda Benosa Author 5: Thelma Palaoag Author 6: Nancy Flores

In the era of rapid technological advancement, the integration of cutting-edge technologies plays a pivotal role in enhancing the efficiency and responsiveness of critical systems. iRESPOND, a real-time Geospatial Information and Alert System, stands at the forefront of such innovations, facilitating timely and informed decision-making in dynamic environments. As the… Read full abstract & cite →

Artificial intelligence image classification emergency response model training optimizers learning rate

Abstract doi.org/10.14569/IJACSA.2024.0150352 PDF

53

Performance Analysis for Secret Message Sharing using Different Levels of Encoding Over QSDC

Author 1: Nur Shahirah Binti Azahari Author 2: Nur Ziadah Binti Harun Author 3: Chai Wen Chuah Author 4: Rosmamalmi Mat Nawi Author 5: Zuriati Binti Ahmad Zukarnain Author 6: Nor Iryani Binti Yahya

It was recently proposed to use quantum secure direct communication (QSDC), a branch of quantum cryptography, to secure data transfers from sender to receiver without relying on computational complexity. Despite the benefits of multiphoton, sending secret messages between several parties in a quantum channel still presents a challenge because the… Read full abstract & cite →

Multiphoton approach multi-party level of encoding scalability error probability

Abstract doi.org/10.14569/IJACSA.2024.0150353 PDF

54

Handling Transactional Data Features via Associative Rule Mining for Mobile Online Shopping Platforms

Author 1: Maureen Ifeanyi Akazue Author 2: Sebastina Nkechi Okofu Author 3: Arnold Adimabua Ojugo Author 4: Patrick Ogholuwarami Ejeh Author 5: Christopher Chukwufunaya Odiakaose Author 6: Frances Uche Emordi Author 7: Rita Erhovwo Ako Author 8: Victor Ochuko Geteloma

Transactional data processing is often a reflection of a consumer's buying behavior. The relational records if properly mined, helps business managers and owners to improve their sales volume. Transaction datasets are often rippled with the inherent challenges in their manipulation, storage and handling due to their infinite length, evolution of… Read full abstract & cite →

Association rule mining online shopping platforms feature evolution concept drift concept evolution shelf placement

Abstract doi.org/10.14569/IJACSA.2024.0150354 PDF

55

An Approach for Developing an Ontology: Learned from Business Model Ontology Design and Development

Author 1: Ahadi Haji Mohd Nasir Author 2: Mohd Firdaus Sulaiman Author 3: Liew Kok Leong Author 4: Ely Salwana Author 5: Mohammad Nazir Ahmad

Ontology, serving as an explicit specification of conceptualization, has found widespread applications across various fields. Business Model Ontology (BMO) stands out as a prominent ontology, especially in the domains of business and entrepreneurship. This study employs the narrative literature review method to delve into the Ontology Development Method (ODM). By… Read full abstract & cite →

Ontology Ontology Development Method (ODM) Business Model Ontology (BMO) Unified Ontology Approach (UOA)

Abstract doi.org/10.14569/IJACSA.2024.0150355 PDF

56

Deep Convolutional Neural Networks Fusion with Support Vector Machines and K-Nearest Neighbors for Precise Crop Leaf Disease Classification

Author 1: Sunil Kumar H R Author 2: Poornima K M

Maize and Paddy are pivotal crops in India, playing a vital role in ensuring food security. Timely detection of diseases and the implementation of remedial measures are crucial for securing optimal crop yield and profitability for farmers. This study utilizes a dataset encompassing images of diseased maize and paddy leaves… Read full abstract & cite →

Deep Convolutional Neural Network (DCNN) multiclass Support Vector Machine (SVM) K-Nearest Neighbor (KNN) ensemble features accuracy

Abstract doi.org/10.14569/IJACSA.2024.0150356 PDF

57

Towards a Machine Learning-based Model for Corporate Loan Default Prediction

Author 1: Imane RHZIOUAL BERRADA Author 2: Fatimazahra BARRAMOU Author 3: Omar BACHIR ALAMI

As the core business of the banking system is to lend money and then get it back, loan default is one of the most crucial issues for commercial banks. With data analysis and artificial intelligence, extracting valuable information from historical data, to lower their losses, banks would be able to… Read full abstract & cite →

Loan default prediction artificial intelligence data analysis machine learning companies corporate real estate bank

Abstract doi.org/10.14569/IJACSA.2024.0150357 PDF

58

Enhancing Data Warehouses Security

Author 1: Muhanad A. Alkhubouli Author 2: Hany M. Lala Author 3: AbdAllah A. AlHabshy Author 4: Kamal A. ElDahshan

Data Warehouses (DWs) are essential for enterprises, containing valuable business information and thus becoming prime targets for internal and external attacks. Data warehouses are crucial assets for organizations, serving critical purposes in business and decision-making. They consolidate data from diverse sources, making it easier for organizations to analyze and derive… Read full abstract & cite →

Data warehouse data security encryption security issues data integrity privacy confidentiality

Abstract doi.org/10.14569/IJACSA.2024.0150358 PDF

59

Speech Emotion Recognition in Multimodal Environments with Transformer: Arabic and English Audio Datasets

Author 1: Esraa A. Mohamed Author 2: Abdelrahim Koura Author 3: Mohammed Kayed

Speech Emotion Recognition (SER) is a fast-developing area of study with a primary goal of automatically identifying and analyzing the emotional states expressed in speech. Emotions are crucial in human communication as they impact the effectiveness and meaning of linguistic expressions. SER aims to create computational approaches and models to… Read full abstract & cite →

Speech emotion recognition transformer encoder fine-tuning wav2vec multimodal emotion recognition

Abstract doi.org/10.14569/IJACSA.2024.0150359 PDF

60

A Method for Constructing and Managing Level of Detail for Non-Closed Boundary Models of Buildings

Author 1: Ahyun Lee

An urban digital twin (UDT) involves creating a virtual three-dimensional (3D) digital replica of a real-world city. To build a UDT model, it needs a comprehensive 3D representation of the city's terrain, buildings, and infrastructure. In order to effectively visualize and manage large-scale spatial data in 3D, it is essential… Read full abstract & cite →

GIS digital twin 3D map level of detail

Abstract doi.org/10.14569/IJACSA.2024.0150360 PDF

61

The Optimal Allocation Method for Energy Storage in Low Voltage Distribution Power Network

Author 1: Lin Zhu Author 2: Xiaofang Meng Author 3: Nannan Zhang

In order to promote the absorption of photovoltaic in low-voltage distribution network, and reduce the voltage over-limit problem caused by high proportion of distributed photovoltaics, this paper proposes a method for optimizing the allocation of distributed energy storage system in low voltage distribution network. Firstly, based on the node voltage… Read full abstract & cite →

Optimal allocation voltage over-limit distributed energy storage low voltage distribution networks

Abstract doi.org/10.14569/IJACSA.2024.0150361 PDF

62

Enhancing Harris Hawks Optimization Algorithm for Resource Allocation in Cloud Computing Environments

Author 1: Ganghua Bai

Cloud computing is revolutionizing the delivery of on-demand scalable and customizable resources. With its flexible resource access and diverse service models, cloud computing is essential to modern computing infrastructure. In cloud environments, assigning Virtual Machines (VMs) to Physical Machines (PMs) remains a complex and challenging task critical to optimizing resource… Read full abstract & cite →

Cloud computing virtual machine allocation energy efficiency resource utilization

Abstract doi.org/10.14569/IJACSA.2024.0150362 PDF

63

Hybrid Machine Learning Approaches for Predicting and Diagnosing Major Depressive Disorder

Author 1: N. Balakrishna Author 2: M. B. Mukesh Krishnan Author 3: D. Ganesh

Major Depressive Disorder (MDD) is common and debilitating, requiring accurate prediction and diagnosis. This study uses clinical, demographic, and EEG data to test hybrid machine learning methods for MDD prediction and diagnosis. EEG data reveals brain electrical activity and can identify MDD patterns and traits. The study aimed to enhance… Read full abstract & cite →

Major Depressive Disorder (MDD) hybrid machine learning cat boost random forest XG boost XGB random forest SVM logistic regression EEG data

Abstract doi.org/10.14569/IJACSA.2024.0150363 PDF

64

Enhance Telecommunication Security Through the Integration of Support Vector Machines

Author 1: Agus Tedyyana Author 2: Adi Affandi Ahmad Author 3: Mohd Rushdi Idrus Author 4: Ahmad Hanis Mohd Shabli Author 5: Mohamad Amir Abu Seman Author 6: Osman Ghazali Author 7: Jaroji Author 8: Abd Hadi Abd Razak

This research investigates the escalating issue of telephone-based fraud in Indonesia, a consequence of enhanced connectivity and technological advancements. As the telecommunications sector expands, it faces increased threats from sophisticated criminal activities, notably voice call fraud, which leads to significant financial losses and diminishes trust in digital systems. This study… Read full abstract & cite →

Call security system artificial intelligence support vector machine data analysis fraud detection system

Abstract doi.org/10.14569/IJACSA.2024.0150364 PDF

65

Virtual Reality and Augmented Reality in Artistic Expression: A Comprehensive Study of Innovative Technologies

Author 1: Fan Wang Author 2: Zonghai Zhang Author 3: Liangyi Li Author 4: Siyu Long

Over the last decade, Virtual Reality (VR) and Augmented Reality (AR) have gained popularity across various industries, particularly the arts, thanks to technological advances and inexpensive hardware and software availability. These technologies have redefined the boundaries of creativity and immersive experiences in artistic expression. This paper explores the dynamic interface… Read full abstract & cite →

Virtual reality augmented reality artistic expression emerging technologies immersive experiences

Abstract doi.org/10.14569/IJACSA.2024.0150365 PDF

66

NovSRC: A Novelty-Oriented Scientific Collaborators Recommendation Model

Author 1: Xiuxiu Li Author 2: Mingyang Wang Author 3: Chaoran Wang Author 4: Yujia Fu Author 5: Xianjie Wang

Collaborator recommendation is a crucial topic in research management. This paper proposes a Novelty-Oriented Scientific Research Collaborator recommendation model (NovSRC). By recommending collaborators under the guidance of novel indicators, NovSRC aims to broaden scholars' research perspectives and facilitate the progress of research innovation. NovSRC utilizes heterogeneous academic networks composed of… Read full abstract & cite →

Scientific collaborator recommendation novelty heterogeneous academic collaboration network network representation learning

Abstract doi.org/10.14569/IJACSA.2024.0150366 PDF

67

A Deep Learning Model for Prediction of Cardiovascular Disease Using Heart Sound

Author 1: Rohit Ravi Author 2: P. Madhavan

Cardiovascular disease is the most emerging disease in this generation of youth. You need to know about your heart condition to overcome this disease appropriately. An electronic stethoscope is used in the cardiac auscultation technique to listen to and analyze heart sounds. Several pathologic cardiac diseases can be detected by… Read full abstract & cite →

Cardiovascular disease prediction LSTM MFCC deep learning

Abstract doi.org/10.14569/IJACSA.2024.0150367 PDF

68

Optimized Deep Belief Networks Based Categorization of Type 2 Diabetes using Tabu Search Optimization

Author 1: Smita Panigrahy Author 2: Sachikanta Dash Author 3: Sasmita Padhy

Diabetics mellitus has the potential to result in numerous challenges. Based on the increasing morbidity rates in recent years, it is projected that the global diabetic population will surpass 642 million by 2040, indicating that approximately one in every ten individuals will have diabetes. Undoubtedly, this alarming statistic necessitates urgent… Read full abstract & cite →

Deep belief network Tabu search diabetics mellitus hyper-parameters optimization

Abstract doi.org/10.14569/IJACSA.2024.0150368 PDF

69

A Model for Automatic Code Generation from High Fidelity Graphical User Interface Mockups using Deep Learning Techniques

Author 1: Michel Samir Author 2: Ahmed Elsayed Author 3: Mohamed I. Marie

Graphical user interface (GUI) is the most prevalent type of user interfaces (UI) due to its visual nature, which allows direct manipulation and interaction with the software. Mockup-based design is a frequently used workflow for constructing GUI. In this workflow, the anticipated UI design process typically progresses through multiple steps… Read full abstract & cite →

Code generation graphical user interfaces deep learning computer vision mockups

Abstract doi.org/10.14569/IJACSA.2024.0150369 PDF

70

NTDA: The Mitigation of Denial of Service (DoS) Cyberattack Based on Network Traffic Detection Approach

Author 1: Muhannad Tahboush Author 2: Adel Hamdan Author 3: Firas Alzobi Author 4: Moath Husni Author 5: Mohammad Adawy

Security is one of the important aspects which is used to protect data availability from being compromised. Denial of service (DoS) attack is a common type of cyberattack and becomes serious security threats to information systems and current computer networks. DoS aims to explicit attempts that will consume and disrupt… Read full abstract & cite →

Network security DoS attack cyberattack network traffic

Abstract doi.org/10.14569/IJACSA.2024.0150370 PDF

71

Word2vec-based Latent Semantic Indexing (Word2Vec-LSI) for Contextual Analysis in Job-Matching Application

Author 1: Sukri Sukri Author 2: Noor Azah Samsudin Author 3: Ezak Fadzrin Author 4: Shamsul Kamal Ahmad Khalid Author 5: Liza Trisnawati

Job-matching applications have become a technology that provides solutions for making decisions about accepting and looking for work. The contextual analysis of documents or data from job matching is needed to make decisions. Some existing studies on the analysis of job-matching applications can use the Latent Semantic Indexing (LSI) method… Read full abstract & cite →

Contextual LSI job-matching text-base word2vec

Abstract doi.org/10.14569/IJACSA.2024.0150371 PDF

72

An Effective Forecasting Approach of Temperature Enabling Climate Change Analysis in Saudi Arabia

Author 1: Sultan Noman Qasem Author 2: Samah M. Alzanin

Climate change is a global issue with far-reaching consequences, and understanding regional temperature patterns is critical for effective climate change analysis. In this context, accurate forecasting of temperature is critical for mitigating and understanding its impact. This study proposes an effective temperature forecasting approach in Saudi Arabia, a region highly… Read full abstract & cite →

Climate change Saudi Arabia temperature forecasting recurrent neural network models

Abstract doi.org/10.14569/IJACSA.2024.0150372 PDF

73

Utilizing the Metaverse in Astrosociology: Examine Students' Perspectives of Space Science Education

Author 1: Yahya Almurtadha

Big economic countries must invest in space skills to create a favorable business environment, particularly in KSA considering the present mindset in outer space. KSA's vast landmass is a tremendous asset that makes it the perfect position to provide space services throughout the Middle East and the world. Space science… Read full abstract & cite →

Metaverse space science education astrosociology virtual reality space simulation

Abstract doi.org/10.14569/IJACSA.2024.0150373 PDF

74

Student Outcome Assessment on Structured Query Language using Rubrics and Automated Feedback Generation

Author 1: Sidhidatri Nayak Author 2: Reshu Agarwal Author 3: Sunil Kumar Khatri Author 4: Masoud Mohammadian

Automated assessment of student assignment based on SQL(Structured Query Language) queries is an efficient method for evaluating and providing feedback on their DBMS-related skills. This paper provides a three step approach of how student submissions are assessed automatically using various machine learning approaches and introduced an automated grading system for… Read full abstract & cite →

Automated SQL Query grading system Cosine similarity LSA Multinomialnb KNN Logistic regression student outcome assessment rubric feedback

Abstract doi.org/10.14569/IJACSA.2024.0150374 PDF

75

Genetic Algorithms and Feature Selection for Improving the Classification Performance in Healthcare

Author 1: Alaa Alassaf Author 2: Eman Alarbeed Author 3: Ghady Alrasheed Author 4: Abdulsalam Almirdasie Author 5: Shahd Almutairi Author 6: Mohammed Abullah Al-Hagery Author 7: Faisal Saeed

Microarray technology appeared recently and is used in genetic research to study gene expressions. Microarray has been widely applied to many fields, especially the health sector, such as diagnosing and predicting diseases, specifically cancer diseases. These experiments usually generate a huge amount of gene expression data with analytical and computational… Read full abstract & cite →

Cancer classification gene expression feature selection microarray data algorithm machine learning genetic algorithm

Abstract doi.org/10.14569/IJACSA.2024.0150375 PDF

76

Optimization Strategy for Industrial Machinery Product Selection Scheme Based on DMOEA

Author 1: Shichang Liu Author 2: Xinbin Yang Author 3: Haihua Huang

With the continuous innovation and replacement of industrial machinery products, the traditional optional configuration plans are no longer able to complete product selection work with high quality. To further optimize the product selection process and solve the multi-objective selection problem of industrial machinery products, a multi-objective problem model for product… Read full abstract & cite →

Industrial machinery products optional configuration plan multi objective evolutionary algorithm density calculation selection success rate

Abstract doi.org/10.14569/IJACSA.2024.0150376 PDF

77

A Deep Learning Framework for Detection and Classification of Implant Manufacturer using X-Ray Radiographs

Author 1: Attar Mahay Sheetal Author 2: K. Sreekumar

Now-a-days, artificial prosthesis is widely used to mitigate pain in damaged shoulders and restore their movement ability. The process involves a complex surgery that attempts to fix an artificial prosthesis into a dead shoulder as a replacement for the ball and socket joints of the shoulder. Long after the surgical… Read full abstract & cite →

Machine learning deep learning convolution neural network Adversarial Network (GAN) Principal Component Analysis (PCA) shoulder implants

Abstract doi.org/10.14569/IJACSA.2024.0150377 PDF

78

Rolling Bearing Life Prediction Technology Based on Feature Screening and LSTM Model

Author 1: Yujun Zhao

As one of the important components of industrial equipment, the health condition of rolling bearings will directly affect the operational effectiveness of the equipment. Therefore, to ensure equipment safety and reduce maintenance costs, an intelligent rolling bearing life prediction technology is proposed. Firstly, it extracts the fault information of rolling… Read full abstract & cite →

Features rolling bearings prediction fisher score bidirectional long short term model

Abstract doi.org/10.14569/IJACSA.2024.0150378 PDF

79

Retrieval-Augmented Generation Approach: Document Question Answering using Large Language Model

Author 1: Kurnia Muludi Author 2: Kaira Milani Fitria Author 3: Joko Triloka Author 4: Sutedi

This study introduces the Retrieval Augmented Generation (RAG) method to improve Question-Answering (QA) systems by addressing document processing in Natural Language Processing problems. It represents the latest breakthrough in applying RAG to document question and answer applications, overcoming previous QA system obstacles. RAG combines search techniques in vector store and… Read full abstract & cite →

Natural Language Processing Large Language Model Retrieval Augmented Generation Question Answering GPT

Abstract doi.org/10.14569/IJACSA.2024.0150379 PDF

80

A User Control Framework for Cloud Data Migration in Software as a Service

Author 1: Danga Imbaji Injuwe Author 2: Hamidah Ibrahim Author 3: Fatimah Sidi Author 4: Iskandar Ishak

Cloud computing represents the overarching paradigm that enables organizations to leverage cloud services for data storage and application deployment. Nowadays, organizations that use the cloud services can migrate their data using software as a service (SaaS). The organizations’ data and application are deployed over the cloud through the cloud data… Read full abstract & cite →

Comparative analysis cloud computing cloud data migration on-premises to cloud migration user control Software as a Service

Abstract doi.org/10.14569/IJACSA.2024.0150380 PDF

81

Blockchain-Enabled Cybersecurity Framework for Safeguarding Patient Data in Medical Informatics

Author 1: Prajakta U. Waghe Author 2: A Suresh Kumar Author 3: Arun B Prasad Author 4: Vuda Sreenivasa Rao Author 5: E. Thenmozhi Author 6: Sanjiv Rao Godla Author 7: Yousef A.Baker El-Ebiary

Securing patient information is crucial in the quickly changing field of healthcare informatics to guarantee privacy, reliability, and adherence to legal requirements. This article presents a complete cybersecurity architecture enabled by blockchain and customized for the medical informatics area. The framework initiatives to provide adequate safeguards for sensitive patient data… Read full abstract & cite →

Block Chain Cybersecurity Diffie Hellmen Patient Data Proof of Work

Abstract doi.org/10.14569/IJACSA.2024.0150381 PDF

82

Reliable Hybridization Approach for Estimation of The Heating Load of Residential Buildings

Author 1: Huanhuan Li

In recent times, the world's growing population, coupled with its ever-increasing energy demands, has led to a significant rise in the consumption of fossil fuels. Consequently, this surge in fossil fuel usage has exacerbated the threat of global warming. Building energy consumption represents a significant portion of global energy usage… Read full abstract & cite →

Heating load residential buildings k-nearest neighbor snake optimizer black widow optimizers

Abstract doi.org/10.14569/IJACSA.2024.0150382 PDF

83

Enhancing Security in IoT Networks: Advancements in Key Exchange, User Authentication, and Data Integrity Mechanisms

Author 1: Alumuru Mahesh Reddy Author 2: M. Kameswara Rao

Future Internet (FI) will be shaped by the Internet of Things (IoT), however because of their limited resources and varied communication capabilities, IoT devices present substantial challenges when it comes to securing connectivity. The adoption of robust security measures is hindered by limited compute power, memory, and energy resources, hence… Read full abstract & cite →

IoT Public key key authentication gate way node data integrity mechanisms

Abstract doi.org/10.14569/IJACSA.2024.0150383 PDF

84

Student Performance Estimation Through Innovative Classification Techniques in Education

Author 1: Hui Fan Author 2: Guoping Zhu Author 3: Jianhua Zhan

In the current era of intense educational competition, institutions must effectively classify individuals based on their abilities, proactively forecast student performance, and work towards enhancing their forthcoming examination outcomes. Providing early guidance to students is crucial in helping them focus their efforts on specific areas to boost their academic achievements… Read full abstract & cite →

Student performance Gaussian Process Classification Golden Eagle Optimizer Pelican Optimization Algorithm

Abstract doi.org/10.14569/IJACSA.2024.0150384 PDF

85

Penetration Testing Framework using the Q Learning Ensemble Deep CNN Discriminator Framework

Author 1: Dipali Nilesh Railkar Author 2: Shubhalaxmi Joshi

Penetration testing (PT) serves as an effective tool for examining networks and identifying vulnerabilities by simulating a hacker's attack to uncover valuable information, such as details about the host's operating and database systems. Strong penetration testing is crucial for assessing system vulnerabilities in the constantly changing world of cyber security… Read full abstract & cite →

Penetration testing Q-learning ensemble deep CNN prairie natural swarm optimization Nmap script engine

Abstract doi.org/10.14569/IJACSA.2024.0150385 PDF

86

Educational Data Mining in European Union – Achievements and Challenges: A Systematic Literature Review

Author 1: Corina Simionescu Author 2: Mirela Danubianu Author 3: Bogdanel Constantin Gradinaru Author 4: Marius Silviu Maciuca

The quality of education is one of the pillars of sustainable development, as set out in “The 2030 Agenda for Sustainable Development”, adopted by all United Nations Member States in 2015. Recent social and technological developments, as well as events such as the COVID-19 pandemic or conflicts in many parts… Read full abstract & cite →

Educational data mining systematic literature review European Union Kitchenham methodology data mining techniques

Abstract doi.org/10.14569/IJACSA.2024.0150386 PDF

87

Enhancing Cryptojacking Detection Through Hybrid Black Widow Optimization and Generative Adversarial Networks

Author 1: Meenal R. Kale Author 2: Deepa Author 3: Anil Kumar N Author 4: N. Lakshmipathi Anantha Author 5: Vuda Sreenivasa Rao Author 6: Sanjiv Rao Godla Author 7: E. Thenmozhi

Cybercriminals now find cryptocurrency mining to be a lucrative endeavour. This is frequently seen in the form of cryptojacking, which is the illegal use of computer resources for cryptocurrency mining. Protecting user resources and preserving the integrity of digital ecosystems depend heavily on the detection and mitigation of such threats… Read full abstract & cite →

Cryptojacking attack detection Generative Adversarial Networks Black Widow Optimization cybercriminals

Abstract doi.org/10.14569/IJACSA.2024.0150387 PDF

88

DeepEmoVision: Unveiling Emotion Dynamics in Video Through Deep Learning Algorithms

Author 1: Prathwini Author 2: Prathyakshini

Emotion detection from videos plays a pivotal role in understanding human behavior and interaction. This study delves into a cutting-edge method that leverages Recurrent Neural Networks (RNN), Support Vector Machines (SVM), K-Nearest Neighbours (KNN), Convolutional Neural Networks (CNN) and to precisely detect emotions exhibited in video content, holding significant importance… Read full abstract & cite →

Emotion detection video analysis Recurrent Neural Networks (RNN) Support Vector Machines (SVM) K-Nearest Neighbours (KNN) Convolutional Neural Networks (CNN) facial expression recognition machine learning

Abstract doi.org/10.14569/IJACSA.2024.0150388 PDF

89

Botnet Detection and Incident Response in Security Operation Center (SOC): A Proposed Framework

Author 1: Roslaily Muhammad Author 2: Saiful Adli Ismail Author 3: Noor Hafizah Hassan

In the dynamic landscape of evolving cyber threats, Security Operations Centers (SOCs) play an important role in protecting digital assets. Among these threats, botnets are particularly challenging due to their ability to take over many devices and launch coordinated attacks. Through comparative analysis, the research gaps in existing frameworks have… Read full abstract & cite →

Botnet detection threat incident response security operation center

Abstract doi.org/10.14569/IJACSA.2024.0150389 PDF

90

Enhancing Customer Segmentation Insights by using RFM + Discount Proportion Model with Clustering Algorithms

Author 1: Victor Hugo Antonius Author 2: Devi Fitrianah

In this digital era, the use of e-commerce has expanded and is widely adopted by society. One of the reasons why people use e-commerce platforms is because of their convenience and ease of use. However, the rapid growth of e-commerce has led to a substantial rise in transactions within the… Read full abstract & cite →

Clustering RFM discount proportion customer segmentation data mining

Abstract doi.org/10.14569/IJACSA.2024.0150390 PDF

91

Adapting Outperformer from Topic Modeling Methods for Topic Extraction and Analysis: The Case of Afaan Oromo, Amharic, and Tigrigna Facebook Text Comments

Author 1: Naol Bakala Defersha Author 2: Kula Kekeba Tune Author 3: Solomon Teferra Abate

Facebook users generate a vast amount of data, including posts, comments, and replies, in various formats such as short text, long text, structured, unstructured, and semi structured. Consequently, obtaining import information from social media data becomes a significant challenge for low-resource languages such as Afaan Oromo, Amharic, and Tigrigna. Topic… Read full abstract & cite →

Afaan oromo amharic tigrigna BERTopic topic extraction social media data

Abstract doi.org/10.14569/IJACSA.2024.0150391 PDF

92

Artificial Intelligence System for Malaria Diagnosis

Author 1: Phoebe A Barracloug Author 2: Charles M Were Author 3: Hilda Mwangakala Author 4: Gerhard Fehringer Author 5: Dornald O Ohanya Author 6: Harison Agola Author 7: Philip Nandi

Malaria threats have remained one of the major global health issues over the past decades specifically in low-middle income countries. 70% of the Kenya population lives in malaria endemic zones and the majority have barriers to access health services due to factors including lack of income, distance, and social culture… Read full abstract & cite →

Malaria diagnosis malaria symptoms artificial intelligence and machine learning classifier malaria classifier

Abstract doi.org/10.14569/IJACSA.2024.0150392 PDF

93

A New Time-Series Classification Approach for Human Activity Recognition with Data Augmentation

Author 1: Youssef Errafik Author 2: Younes Dhassi Author 3: Adil Kenzi

Accurate classification of multivariate time series data represents a major challenge for scientists and practitioners exploring time series data in different domains. LSTM-Auto-encoders are Deep Learning models that aim to represent input data efficiently while minimizing information loss during the reconstruction phase. Although they are commonly used for Dimensionality Reduction… Read full abstract & cite →

Deep Learning (DL) multivariate time series Time Series Classification (TSC) Human Activity Recognition (HAR)

Abstract doi.org/10.14569/IJACSA.2024.0150393 PDF

94

Adaptive Threshold Tuning-based Load Balancing (ATTLB) for Cost Minimization in Cloud Computing

Author 1: Lama S. Khoshaim

Cloud computing has revolutionized the on-demand resource provisioning through virtualization. However, dynamic pricing of cloud resources presents cost management challenges. Load balancing is critical for cloud efficiency; however, current algorithms use static thresholds and are unable to adapt to fluctuating prices. This study proposes a novel Dynamic Threshold Tuning (ATTLB)… Read full abstract & cite →

Cloud computing load balancing threshold optimization cost minimization pricing models CloudSim resource allocation cost-aware load balancing

Abstract doi.org/10.14569/IJACSA.2024.0150394 PDF

95

Facial Emotion Recognition-based Engagement De-tection in Autism Spectrum Disorder

Author 1: Noura Alhakbani

Engagement is the state of alertness that a person experiences and the deliberate focus of their attention on a task-relevant stimulus. It positively correlates with many aspects such as learning, social support, and acceptance. Facial emotion recog-nition using artificial intelligence can be beneficial to automati-cally measure individual engagement especially when… Read full abstract & cite →

Engagement detection facial emotion recognition autistic chil-dren convolutional neural networks

Abstract doi.org/10.14569/IJACSA.2024.0150395 PDF

96

State-Feedback Control of Ball-Plate System: Geometric Approach

Author 1: Khalid Lefrouni Author 2: Saoudi Taibi

This research focuses on investigating the issue of accurately controlling the location of the ball in the ball and plate system. The findings of this research have practical applications across several domains, including optimizing the alignment of solar panels to enhance their energy generation capacity. In this work, we propose… Read full abstract & cite →

Ball-plate system Delay systems Geometric approach State-feedback control

Abstract doi.org/10.14569/IJACSA.2024.0150396 PDF

97

Maximizing Solar Panel Efficiency in Partial Shade: The Improved POA Solution for MPPT

Author 1: Youssef Mhanni Author 2: Youssef Lagmich

This paper presents an innovative approach to improving Maximum Power Point Tracking (MPPT) in solar photovoltaic (PV) systems affected by partial shading, a common challenge that significantly reduces efficiency. Our research focuses on enhancing the Pelican Optimization Algorithm (POA), a promising tool in solar energy optimization, to better tackle the… Read full abstract & cite →

Pelican Optimization Algorithm (POA) Maximum Power Point Tracking (MPPT) Solar Photovoltaic Systems Partial Shading

Abstract doi.org/10.14569/IJACSA.2024.0150397 PDF

98

An Integrated CNN-BiLSTM Approach for Facial Expressions

Author 1: B. H. Pansambal Author 2: A. B. Nandgaokar Author 3: J. L. Rajput Author 4: Abhay Wagh

Deep learning algorithms have demonstrated good performance in many sectors and applications. Facial expression recognition (FER) is recognizing the emotions through images. FER is an integral part of many applications. With the help of the CNN-BiLSTM integrated approach, higher accuracy can be achieved in identification of the facial expressions. Convolutional… Read full abstract & cite →

CNN (Convolutional Neural Network) BiLSTM (Bi Directional Long Short Term Memory) facial expression recognition deep learning flattening

Abstract doi.org/10.14569/IJACSA.2024.0150398 PDF

99

Research on Innovative Design of Towable Caravans Integrating Kano-AHP and TRIZ Theories

Author 1: Jinyang Xu Author 2: Xuedong Zhang Author 3: Aihu Liao Author 4: Shun Yu Author 5: Yanming Chen Author 6: Longping Chen

The caravan industry in China is facing significant challenges, primarily because the mode of caravan travel is relatively niche within the country and the industry as a whole has had a slow start. This has ultimately resulted in a mismatch between the design aesthetics of caravans and the preferences of… Read full abstract & cite →

Kano model towed caravans exterior design Analytic Hierarchy Process (AHP) TRIZ theory

Abstract doi.org/10.14569/IJACSA.2024.0150399 PDF

100

Enhancing Employee Performance Management

Author 1: Zbakh Mourad Author 2: Aknin Noura Author 3: Chrayah Mohamed Author 4: Bouzidi Abdelhamid

Human resource management (HRM) plays a crucial role in the effective functioning of modern businesses. However, As the volume of data continues to increase, HR professionals are facing growing challenges in objectively gathering, measuring, and interpreting human resources data. The research problem addressed in this study is the need to… Read full abstract & cite →

HRM HR analytics Employee Performance Prediction Support Vector Machine (SVM) Algorithm K-Nearest Neighbor (KNN) Algorithm Multiple Linear Regression (MLR) algorithm Principal Component Analysis (PCA)

Abstract doi.org/10.14569/IJACSA.2024.01503100 PDF

101

Advancing Strawberry Disease Detection in Agriculture: A Transfer Learning Approach with YOLOv5 Algorithm

Author 1: Chunmao LIU

Strawberry Disease Detection in the Agricultural Sector is of paramount importance, as it directly impacts crop yield and quality. A multitude of methods have been explored in the literature to address this challenge, but deep learning techniques have consistently demonstrated superior accuracy in disease detection. Nevertheless, the current research challenge… Read full abstract & cite →

Strawberry disease detection deep learning agricultural YOLOv5 model training

Abstract doi.org/10.14569/IJACSA.2024.01503101 PDF

102

Profiling and Classification of Users Through a Customer Feedback-based Machine Learning Model

Author 1: Jihane LARIOUI Author 2: Abdeltif EL BYED

The systems aimed at predicting user preferences and providing recommendations are now commonly used in many systems such as online shops, social websites, and tourist guide websites. These systems typically rely on collecting user data and learning from it in order to improve their performance. In the context of urban… Read full abstract & cite →

Machine learning urban mobility multimodal transportation multi-agent systems

Abstract doi.org/10.14569/IJACSA.2024.01503102 PDF

103

Detection of Harassment Toward Women in Twitter During Pandemic Based on Machine Learning

Author 1: Wan Nor Asyikin Wan Mustapha Author 2: Norlina Mohd Sabri Author 3: Nor Azila Awang Abu Bakar Author 4: Nik Marsyahariani Nik Daud Author 5: Azilawati Azizan

Harassment is an offensive behavior, intimidating and could cause discomfort to the victims. In some cases, the harassments could lead to a traumatic experience to the vulnerable victims. Currently, the harassments towards women in social media have become more daring and are rising. The increasing number of the social media… Read full abstract & cite →

Harassment women detection twitter SVM

Abstract doi.org/10.14569/IJACSA.2024.01503103 PDF

104

Deep Learning-based Food Calorie Estimation Method in Dietary Assessment: An Advanced Approach using Convolutional Neural Networks

Author 1: Kalivaraprasad B Author 2: Prasad M.V.D Author 3: Naveen kishore Gattim

Dietary pattern assessments, essential for chronic illness management and well-being, involve time-consuming manual data input and food intake remembering. A more dependable and automated approach is needed since such procedures may create mistakes and inconsistencies. This study solves a long-standing problem by automating nutritional assessment using deep learning and image… Read full abstract & cite →

Deep learning convolutional neural networks food calorie estimation dietary assessment computer vision health informatics

Abstract doi.org/10.14569/IJACSA.2024.01503104 PDF

105

Multi-Objective Reinforcement Learning for Virtual Machines Placement in Cloud Computing

Author 1: Chayan Bhatt Author 2: Sunita Singhal

The rapid demand for cloud services has provoked cloud providers to efficiently resolve the problem of Virtual Machines Placement in the cloud. This paper presents a VM Placement using Reinforcement Learning that aims to provide optimal resource and energy management for cloud data centers. Reinforcement Learning provides better decision-making as… Read full abstract & cite →

Virtual machines placement cloud computing reinforcement learning energy consumption resource utilization

Abstract doi.org/10.14569/IJACSA.2024.01503105 PDF

106

A New Aerial Image Segmentation Approach with Statistical Multimodal Markov Fields

Author 1: Jamal Bouchti Author 2: Ahmed Bendahmane Author 3: Adel Asselman

Aerial images, captured by drones, satellites, or aircraft, are omnipresent in diverse fields, from mapping and surveillance to precision agriculture. The efficacy of image analysis in these domains hinges on the quality of segmentation, and the precise delineation of objects and regions of interest. In this context, leveraging Markov fields… Read full abstract & cite →

Image segmentation multimodal markov fields statistical integration CIEDE2000 color difference texture features edge information

Abstract doi.org/10.14569/IJACSA.2024.01503106 PDF

107

Path Planning and Control of Intelligent Delivery UAV Based on Internet of Things and Edge Computing

Author 1: Xiuzhu Zhang

This paper investigates the intelligent delivery UAV path planning and control problem based on the Internet of Things and edge computing, and proposes a novel model and algorithm to realize the collaborative optimization of the path planning and control of the UAV, which improves the intelligence level and flight efficiency… Read full abstract & cite →

Internet of things edge computing smart distribution drone path planning and control

Abstract doi.org/10.14569/IJACSA.2024.01503107 PDF

108

Secure IoT Seed-based Matrix Key Generator

Author 1: Youssef NOUR-EL AINE Author 2: Cherkaoui LEGHRIS

The rapid evolution of the Internet of Things (IoT) has significantly transformed various aspects of both personal and professional spheres, offering innovative solutions in fields from home automation to industrial manufacturing. This progression is driven by the integration of physical devices with digital networks, facilitating efficient communication and data processing… Read full abstract & cite →

Security IoT steganography key exchange cryptography

Abstract doi.org/10.14569/IJACSA.2024.01503108 PDF

109

Hierarchical Spatiotemporal Aspect-Based Sentiment Analysis for Chain Restaurants using Machine Learning

Author 1: Mouyassir Kawtar Author 2: Abderrahmane Fathi Author 3: Noureddine Assad Author 4: Ali Kartit

In recent years, aspect-based sentiment analysis of restaurant business reviews has emerged as a pivotal area of research in natural language processing (NLP), aiming to provide detailed analytical methods benefiting both consumers and industry professionals. This study introduces a novel approach, Hierarchical Spatiotemporal Aspect-Based Sentiment Analysis (HISABSA), which combines lexicon-based… Read full abstract & cite →

HISABSA hybrid model NLP ML VADER Lexicon AFFIN model TextBlob ABSA Restaurant reviews Transformer-based models Lexicon-based methods RoBERTa model BERT model

Abstract doi.org/10.14569/IJACSA.2024.01503109 PDF

110

Enhancing Water Quality Forecasting Reliability Through Optimal Parameterization of Neuro-Fuzzy Models via Tunicate Swarm Optimization

Author 1: Kambala Vijaya Kumar Author 2: Y Dileep Kumar Author 3: Sanjiv Rao Godla Author 4: Mohammed Saleh Al Ansari Author 5: Yousef A.Baker El-Ebiary Author 6: Elangovan Muniyandy

Forecasting water quality is critical to environmental management because it facilitates quick decision-making and resource allocation. On the opposite hand, current methods are not always able to produce reliable forecasts, which is often due to challenges in parameter optimization for complex models. This research presents a novel approach to enhance… Read full abstract & cite →

Water quality forecasting neuro-fuzzy models tunicate swarm optimization parameter optimization environmental decision support

Abstract doi.org/10.14569/IJACSA.2024.01503110 PDF

111

Revolutionizing Healthcare by Unleashing the Power of Machine Learning in Diagnosis and Treatment

Author 1: Medini Gupta Author 2: Sarvesh Tanwar Author 3: Salil Bharany Author 4: Faisal Binzagr Author 5: Hadia Abdelgader Osman Author 6: Ashraf Osman Ibrahim Author 7: Samsul Ariffin Abdul Karim

Machine learning (ML) is a versatile technology that has the potential to revolutionize various industries. ML can predict future trends in customer expectations that allow organizations to develop new products accordingly. ML is a crucial field of data science that uses different algorithms to predict insights and improve decision-making. The… Read full abstract & cite →

Machine Learning Health Diagnosis Supervised Learning Prediction Classification

Abstract doi.org/10.14569/IJACSA.2024.01503111 PDF

112

Ceramic Microscope Image Classification Based on Multi-Scale Fusion Bottleneck Structure and Chunking Attention Mechanism

Author 1: Zhihuang Zhuang Author 2: Xing Xu Author 3: Xuewen Xia Author 4: Yuanxiang Li Author 5: Yinglong Zhang

In recent years, the status of ceramics in fields such as art, culture, and historical research has been continuously improving. However, the increase in malicious counterfeiting and forgery of ceramics has disrupted the normal order of the ceramic market and brought challenges to the identification of authenticity. Due to the… Read full abstract & cite →

Deep learning ceramic anti-counterfeiting image classification attention mechanism

Abstract doi.org/10.14569/IJACSA.2024.01503112 PDF

113

Weighted PSO Ensemble using Diversity of CNN Classifiers and Color Space for Endoscopy Image Classification

Author 1: Diah Arianti Author 2: Azizi Abdullah Author 3: Shahnorbanun Sahran Author 4: Wong Zhyqin

Endoscopic image is a manifestation of visualization technology to the human gastrointestinal tract, allowing detection of abnormalities, characterization of lesions, and guidance for therapeutic interventions. Accurate and reliable classification of endoscopy images remains challenging due to variations in image quality, diverse anatomical structures, and subtle abnormalities such as polyps and… Read full abstract & cite →

Convolution neural network particle swarm optimization diversity weighted ensemble

Abstract doi.org/10.14569/IJACSA.2024.01503113 PDF

114

Research Octane Number Prediction Based on Feature Selection and Multi-Model Fusion

Author 1: Junlin Gu

The catalytic cracking-based process for lightening heavy oil yields gasoline products with sulfur and olefin contents surpassing 95%, consequently diminishing the Research Octane Number (RON) of gasoline during desulfurization and olefin reduction stages. Hence, investigating methodologies to mitigate RON loss in gasoline while maintaining effective desulfurization is imperative. This study… Read full abstract & cite →

Feature selection random forest model support vector machine model RON loss

Abstract doi.org/10.14569/IJACSA.2024.01503114 PDF

115

Spherical Fuzzy Z-Numbers-based CRITIC CRADIAS and MARCOS Approaches for Evaluating English Teacher Performance

Author 1: Jie Niu

Consider combining quantitative and qualitative data for these case studies, such as interviews with English teachers, student evaluations, classroom observations, and surveys. Contextual elements, including community support, resources, and school demographics, should also be taken into consideration. The assessment process in English teaching performance evaluation is very complicated and diverse… Read full abstract & cite →

SFZNS CRITRIC technique CRADIAS method MARCOS method

Abstract doi.org/10.14569/IJACSA.2024.01503115 PDF

116

Issuance Policies of Route Origin Authorization with a Single Prefix and Multiple Prefixes: A Comparative Analysis

Author 1: Zetong Lai Author 2: Zhiwei Yan Author 3: Guanggang Geng Author 4: Hidenori Nakazato

Resource Public Key Infrastructure (RPKI) is a solution to mitigate the security issues faced by inter-domain routing. Within the RPKI framework, Route Origin Authorization (ROA) plays a crucial role as an RPKI object. ROA allows address space holders to place a single IP address prefix or multiple IP address prefixes… Read full abstract & cite →

BGP RPKI route origin authorization inter-domain routing security computer network protocols routing

Abstract doi.org/10.14569/IJACSA.2024.01503116 PDF

117

Scientometric Analysis and Knowledge Mapping of Cybersecurity

Author 1: Fahad Alqurashi Author 2: Istiak Ahmad

Cybersecurity research includes several areas, such as authentication, software and hardware vulnerabilities, and defences against cyberattacks. However, only a limited number of cybersecurity experts have a comprehensive understanding of all aspects of this sector. Hence, it is vital to possess an impartial comprehension of the prevailing patterns in cyberse-curity research… Read full abstract & cite →

Cybersecurity cyber threats scientometric analysis bibliomatic analysis

Abstract doi.org/10.14569/IJACSA.2024.01503117 PDF

118

SCEditor: A Graphical Editor Prototype for Smart Contract Design and Development

Author 1: Yassine Ait Hsain Author 2: Naziha Laaz Author 3: Samir Mbarki

In recent years, particularly with the Ethereum blockchain’s advent, smart contracts have gained significant interest as a means of regulating exchanges among multiple parties via code. This surge has prompted the emergence of various smart contract (SC) programming languages, each possessing distinct philosophies, grammatical structures, and components. Conse-quently, developers are… Read full abstract & cite →

Blockchain Metamodel Model-driven Engineering (MDE) Smart Contract (SC) SC Programming

Abstract doi.org/10.14569/IJACSA.2024.01503118 PDF

119

Software Defect Prediction via Generative Adversarial Networks and Pre-Trained Model

Author 1: Wei Song Author 2: Lu Gan Author 3: Tie Bao

Software defect prediction, which aims to predict defective modules during software development, has been implemented to assist developers in identifying defects and ensure software quality. Traditional defect prediction methods utilize manually designed features such as “Lines Of Code” that fail to capture the syntactic and semantic structures of code. Moreover… Read full abstract & cite →

Software defect prediction semi-supervised learning generative adversarial networks deep learning

Abstract doi.org/10.14569/IJACSA.2024.01503119 PDF

120

Enhancing Model Robustness and Accuracy Against Adversarial Attacks via Adversarial Input Training

Author 1: Ganesh Ingle Author 2: Sanjesh Pawale

Adversarial attacks present a formidable challenge to the integrity of Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) models, particularly in the domain of power quality disturbance (PQD) classification, necessitating the development of effective defense mechanisms. These attacks, characterized by their subtlety, can significantly degrade the performance of models critical for maintaining… Read full abstract & cite →

Adversarial attacks Input Adversarial Training (IAT) deep learning security model robustness

Abstract doi.org/10.14569/IJACSA.2024.01503120 PDF

121

Image Binary Matrix Processing to Encrypt-Decrypt Digital Images

Author 1: Mohamad Al-Laham Author 2: Firas Omar Author 3: Ziad A. Alqadi

This research study presents a simple cryptographic solution for protecting grayscale and colored digital images, which are commonly used in computer applications. Due to their widespread use, protecting these photos is crucial to preventing unauthorized access. This article’s methodology manipulates an image’s binary matrix using basic operations. These specified actions… Read full abstract & cite →

Image processing binary matrix encrypt-decrypt digital image

Abstract doi.org/10.14569/IJACSA.2024.01503121 PDF

122

An End-to-End Model of ArVi-MoCoGAN and C3D with Attention Unit for Arbitrary-view Dynamic Gesture Recognition

Author 1: Huong-Giang Doan Author 2: Hong-Quan Luong Author 3: Thi Thanh Thuy Pham

Human gesture recognition is an attractive research area in computer vision with many applications such as human-machine interaction, virtual reality, etc. Recent deep learning techniques have been efficiently applied for gesture recognition, but they require a large and diverse amount of training data. In fact, the available gesture datasets contain… Read full abstract & cite →

Dynamic gesture recognition attention unit generative adversarial network

Abstract doi.org/10.14569/IJACSA.2024.01503122 PDF

123

Predicting ICU Admission for COVID-19 Patients in Saudi Arabia: A Comparative Study of AdaBoost and Bagging Methods

Author 1: Hamza Ghandorh Author 2: Mohammad Zubair Khan Author 3: Mehshan Ahmed Khan Author 4: Yousef M. Alsofayan Author 5: Ahmed A. Alahmari Author 6: Anas A. Khan

COVID-19’s high fatality rate and accurately deter-mining the mortality rate within a particular geographic region continue to be significant concerns. In this study, the authors investigated and assessed the performance of two advanced machine learning approaches, Adaptive Boosting (AdaBoost) and Bootstrap Aggregation (Bagging), as strong predictors of COVID- 19-related intensive… Read full abstract & cite →

COVID-19 adaptive boosting bootstrap aggregation prediction ICU admission Saudi Arabia machine learning

Abstract doi.org/10.14569/IJACSA.2024.01503123 PDF

124

Secure Sharing of Patient Controlled e-Health Record using an Enhanced Access Control Model with Encryption Based on User Identity

Author 1: Mohinder Singh B Author 2: Jaisankar N

Healthcare industry is converting to digital due to the constantly evolving medical needs in the modern digital age. Many researchers have put up models like Ciphertext Policy Attribute Based Encryption (CPABE) to provide security to health records. But, the CPABE-variants failed to give total control of a medical record to… Read full abstract & cite →

Access permissions fine-grained access control identity based encryption key generation center electronic health record

Abstract doi.org/10.14569/IJACSA.2024.01503124 PDF

125

Unmasking Fake Social Network Accounts with Explainable Intelligence

Author 1: Eman Alnagi Author 2: Ashraf Ahmad Author 3: Qasem Abu Al-Haija Author 4: Abdullah Aref

The recent global social network platforms have intertwined a web connecting people universally, encouraging unprecedented social interactions and information exchange. However, this digital connectivity has also spawned the growth of fake social media accounts used for mass spamming and targeted attacks on certain accounts or sites. In response, carefully con-structed… Read full abstract & cite →

Explainable Artificial Intelligence (XAI) Shapley Additive exPlanations (SHAP) feature selection fake accounts detection social media

Abstract doi.org/10.14569/IJACSA.2024.01503125 PDF

126

The Effect of Pre-processing on a Convolutional Neural Network Model for Dorsal Hand Vein Recognition

Author 1: Omar Tarawneh Author 2: Qotadeh Saber Author 3: Ahmed Almaghthawi Author 4: Hamza Abu Owida Author 5: Abedalhakeem Issa Author 6: Nawaf Alshdaifat Author 7: Ghaith Jaradat Author 8: Suhaila Abuowaida Author 9: Mohammad Arabiat

There are numerous techniques for identifying users, including cards, passwords, and biometrics. Emerging technologies such as cloud computing, smart gadgets, and home automation have raised users’ awareness of the privacy and security of their data. The current study aimed to utilise the CNN model augmented with various pre-processing filters to… Read full abstract & cite →

CNNs preprocessing dorsal hand vein recognition CNN authentication

Abstract doi.org/10.14569/IJACSA.2024.01503126 PDF

127

A Machine Learning-based Solution for Monitoring of Converters in Smart Grid Application

Author 1: Umaiz Sadiq Author 2: Fatma Mallek Author 3: Saif Ur Rehman Author 4: Rao Muhammad Asif Author 5: Ateeq Ur Rehman Author 6: Habib Hamam

The integration of renewable energy sources and the advancement of smart grid technologies have revolutionized the power distribution landscape. As the smart grid evolves, the monitoring and control of power converters play a crucial role in ensuring the stability and efficiency of the overall system. This research paper introduced a… Read full abstract & cite →

Artificial intelligence photovoltaic support vector machine machine learning K-Nearest neighbor maximum power point tracking pulse width modulation prognostic analysis one-against-rest one-against-one direct acyclic graph multi class support vector machine DC-DC converter zeta c

Abstract doi.org/10.14569/IJACSA.2024.01503127 PDF

128

Robust Stability Analysis of Switched Neutral Delayed Systems with Parameter Uncertainties

Author 1: Nidhal Khorchani Author 2: Rafika El Harabi Author 3: Wiem Jebri Jemai Author 4: Hassen Dahman

A time-delay neural system is an accurate class of neural system that exposes delays in both the state values and their derivatives. In this case, it is critical to maintain the system stability. Here, the stability investigation on uncertain switched-neutral systems with state-time delays is the focus of this paper… Read full abstract & cite →

Switched neutral systems parameter uncertainties delay-dependent robust stability multiple quadratic Lyapunov-Krasovskii LMI technique

Abstract doi.org/10.14569/IJACSA.2024.01503128 PDF

129

Video-based Domain Generalization for Abnormal Event and Behavior Detection

Author 1: Salma Kammoun Jarraya Author 2: Alaa Atallah Almazroey

Surveillance cameras have been widely deployed in public and private areas in recent years to enhance security and ensure public safety, necessitating the monitoring of unforeseen incidents and behaviors. An intelligent automated system is essential for detecting anomalies in video scenes to save the time and cost associated with manual… Read full abstract & cite →

Domain generalization abnormal event abnormal behavior

Abstract doi.org/10.14569/IJACSA.2024.01503129 PDF

130

An Efficient Blockchain Neighbor Selection Framework Based on Agglomerative Clustering

Author 1: Marwa F. Mohamed Author 2: Mostafa Elkhouly Author 3: Safa Abd El-Aziz Author 4: Mohamed Tahoun

Blockchain-based decentralized applications have garnered significant attention and have been widely deployed in recent years. However, blockchain technology faces several challenges, such as limited transaction throughput, large blockchain sizes, scalability, and consensus protocol limitations. This paper introduces an efficient framework to accelerate broadcast efficiency and enhance the blockchain system’s throughput… Read full abstract & cite →

Blockchain scalability agglomerative clustering broadcasting optimized neighbor selection minimum spanning tree parallel processing

Abstract doi.org/10.14569/IJACSA.2024.01503130 PDF

131

Unified Access Management for Digital Evidence Storage: Integrating Attribute-based and Role-based Access Control with XACML

Author 1: Ayu Maulina Author 2: Zulfany Erlisa Rasjid

Digital evidence is stored in digital evidence storage. An access control system is crucial in situations where not all users can access digital evidence, ensuring that each user’s access is limited to what is essential for them to do their jobs. As a result, access control must be included. Role-based… Read full abstract & cite →

ABAC RBAC digital evidence storage XACML network security

Abstract doi.org/10.14569/IJACSA.2024.01503131 PDF

132

Detecting and Visualizing Implementation Feature Interactions in Extracted Core Assets of Software Product Line

Author 1: Hamzeh Eyal Salman Author 2: Yaqin Al-Ma’aitah Author 3: Abdelhak-Djamel Seriai

Recently, software products have played a vital role in our daily lives, having a significant impact on industries and the economy. Software product line engineering is an engineering strategy that allows for the systematic reuse and development of a set of software products simultaneously, rather than just one software product… Read full abstract & cite →

Unwanted feature interaction core assets extractive approach visualization shared artifacts implementation dependency

Abstract doi.org/10.14569/IJACSA.2024.01503132 PDF

133

An Optimized Air Traffic Departure Sequence According to the Standard Instrument Departures

Author 1: Abdelmounaime Bikir Author 2: Otmane Idrissi Author 3: Khalifa Mansouri Author 4: Mohamed Qbadou

Sequencing efficiently the departure traffic remains among the critical parts of air traffic management these days. It not only reduces delays and congestion at hold points, but it also enhances airport operations, improves traffic planning, and increases capacity. This research paper proposes an approach, that employs a genetic algorithm (GA)… Read full abstract & cite →

Air traffic management standard instrument departure departure traffic sequencing genetic algorithm heuristic algorithm

Abstract doi.org/10.14569/IJACSA.2024.01503133 PDF

134

Utilizing Various Machine Learning Techniques for Diabetes Mellitus Feature Selection and Classification

Author 1: Alaa Sheta Author 2: Walaa H. Elashmawi Author 3: Ahmad Al-Qerem Author 4: Emad S. Othman

Diabetes mellitus is a chronic disease affecting over 38.4 million adults worldwide. Unfortunately, 8.7 million were undiagnosed. Early detection and diagnosis of diabetes can save millions of people’s lives. Significant benefits can be achieved if we have the means and tools for the early diagnosis and treatment of diabetes since… Read full abstract & cite →

Diabetes machine learning random forest SMOTE technique

Abstract doi.org/10.14569/IJACSA.2024.01503134 PDF

135

Screening Cyberattacks and Fraud via Heterogeneous Layering

Author 1: Abdulrahman Alahmadi

On the Internet of Things (IoT) age, intelligent equipment is employed to give effective and dependable utilization of applications. IoT devices may recognize and provide extensive information while also intelligently processing that data. Data systems, systems for control, plus sensing are growing increasingly vital in contemporary manufacturing processes. The amount… Read full abstract & cite →

Fraud Internet of Things (IoT) Deep Learning (DL) ensemble stacking cyberattack Machine Learning (ML)

Abstract doi.org/10.14569/IJACSA.2024.01503135 PDF

136

DeepSL: Deep Neural Network-based Similarity Learning

Author 1: Mohamedou Cheikh Tourad Author 2: Abdali Abdelmounaim Author 3: Mohamed Dhleima Author 4: Cheikh Abdelkader Ahmed Telmoud Author 5: Mohamed Lachgar

The quest for a top-rated similarity metric is inherently mission-specific, with no universally ”great” metric relevant across all domain names. Notably, the efficacy of a similarity metric is regularly contingent on the character of the challenge and the characteristics of the records at hand. This paper introduces an innovative mathematical… Read full abstract & cite →

Similarity learning Siamese networks MCESTA triplet loss similarity metrics

Abstract doi.org/10.14569/IJACSA.2024.01503136 PDF

137

Unveiling the Dynamic Landscape of Malware Sandboxing: A Comprehensive Review

Author 1: Elhaam Debas Author 2: Norah Alhumam Author 3: Khaled Riad

In contemporary times, the landscape of malware analysis has advanced into an era of sophisticated threat detection. Today’s malware sandboxes conduct rudimentary analyses and have evolved to incorporate cutting-edge artificial intelligence and machine learning capabilities. These advancements empower them to discern subtle anomalies and recognize emerging threats with a heightened… Read full abstract & cite →

Malware analysis threat hunting security operations machine learning cutting-edge AI sandboxing

Abstract doi.org/10.14569/IJACSA.2024.01503137 PDF

138

Enhancing Low-Resource Question-Answering Performance Through Word Seeding and Customized Refinement

Author 1: Hariom Pandya Author 2: Brijesh Bhatt

The state-of-the-art approaches in Question-Answering (QA) systems necessitate extensive supervised training datasets. In low-resource languages (LRL), the scarcity of data poses a bottleneck, and the manual annotation of labeled data is a rigorous process. Addressing this challenge, some recent efforts have explored cross-lingual or multilingual QA learning by leveraging training… Read full abstract & cite →

Embedding learning words seeding bilingual dataset generation low-resource question-answering

Abstract doi.org/10.14569/IJACSA.2024.01503138 PDF