IJACSA Vol. 15 Issue 5 (2024)

1

Multiview Outlier Filtered Pediatric Heart Sound Classification

Author 1: Sagnik Dakshit

The advancements in deep learning has generated a large-scale interest in development of black-box models for various use cases in different domains such as healthcare, in both at-home and critical setting for diagnosis and monitoring of various health conditions. The use of audio signals as a view for diagnosis is… Read full abstract & cite →

Deep learning outlier filtering machine learning ECG

Abstract doi.org/10.14569/IJACSA.2024.0150501 PDF

2

Trigger Screen Restriction Framework, iOS use Case Towards Building a Gamified Physical Intervention

Author 1: Majed Hariri Author 2: Richard Stone

The growing trend of inactive lifestyles caused by excessive use of mobile devices raises severe concerns about people’s health and well-being. This paper illustrates the technical implementation of the Trigger Screen Restriction (TSR) framework, which integrates advanced technologies, including machine learning and gamification techniques, to address the limitations of traditional… Read full abstract & cite →

Gamification physical activity screen-time restriction triggered screen restriction framework TSR Framework personalized interventions gamified physical intervention

Abstract doi.org/10.14569/IJACSA.2024.0150502 PDF

3

An Intelligent Method for Collecting and Analyzing Voice Reviews to Gauge Customer Satisfaction

Author 1: Nail Khabibullin

Customer loyalty and customer satisfaction are premier goals of modern business since these factors indicate customers’ future behaviour and ultimate impact on the revenue and value of a business. The customers’ reviews, ratings, and rankings are a primary source for gauging customer satisfaction levels. Similar efforts have been reported in… Read full abstract & cite →

Voice reviews customer satisfaction text mining sentiment analysis

Abstract doi.org/10.14569/IJACSA.2024.0150503 PDF

4

Intelligent Framework in a Serverless Computing for Serving using Artificial Intelligence and Machine Learning

Author 1: Deepak Khatri Author 2: Sunil Kumar Khatri Author 3: Deepti Mishra

Serverless computing has grown in popularity as a paradigm for deploying applications in the cloud due to its ability to scale, cost-effectiveness, and simplified infrastructure management. Serverless architectures can benefit AI and Machine Learning (ML) models, which are becoming increasingly complex and resource-intensive. This study investigates the integration of AI/ML… Read full abstract & cite →

Machine learning data analytics serverless computing performance testing

Abstract doi.org/10.14569/IJACSA.2024.0150504 PDF

5

Find a Research Collaborator: An Ontology-Based Solution to Find the Right Resources for Research Collaboration

Author 1: Nada Abdullah Alrehaili Author 2: Muhammad Ahtisham Aslam Author 3: Amani Falah Alharbi Author 4: Rehab Bahaaddin Ashari

Researchers in Higher Education (HE) institution-s/academia and in industry are continuously engaged in gen-erating new solutions and products for existing and emergent problems. Doing quality research and producing better scientific results depend greatly on solid research teams and scientific collaborators. Research output in HE institutions and industry can be optimized… Read full abstract & cite →

Higher Education Ontology (HEO) Linked Open Data (LOD) Machine Reasoning Semantic Web (SW) SPARQL Queries

Abstract doi.org/10.14569/IJACSA.2024.0150505 PDF

6

Advancing Hospital Cybersecurity Through IoT-Enabled Neural Network for Human Behavior Analysis and Anomaly Detection

Author 1: Faisal ALmojel Author 2: Shailendra Mishra

The integration of Internet of Things (IoT) technologies in hospital environments has introduced transformative changes in patient care and operational efficiency. However, this increased connectivity also presents significant cybersecurity challenges, particularly concerning the protection of patient data and healthcare operations. This research explores the application of advanced machine learning models… Read full abstract & cite →

IoT security cyber security network security machine learning LSTM

Abstract doi.org/10.14569/IJACSA.2024.0150506 PDF

7

Tile Defect Recognition Network Based on Amplified Attention Mechanism and Feature Fusion

Author 1: JiaMing Zhang Author 2: ZanXia Qiang Author 3: YuGang Li

For the current situation of low AP of tile defect detection with incomplete detection of defect types, this paper proposes YOLO-SA, a detection neural network based on the enhanced attention mechanism and feature fusion. We propose an enhanced attention mechanism named amplified attention mechanism to reduce the information attenuation of… Read full abstract & cite →

Amplified attention mechanism defect recognition small target recognition Yolo feature fusion

Abstract doi.org/10.14569/IJACSA.2024.0150507 PDF

8

Tendon-Driven Robotic Arm Control Method Based on Radial Basis Function Adaptive Tracking Algorithm

Author 1: Xiaoke Fang

With the rapid development of intelligent technology, robotic arms are widely used in different fields. The study combines the tendon drive theory and radial basis function neural network to construct the robotic arm model, and then combines the back-stepping method and non-singular fast terminal sliding mode to improve the controller… Read full abstract & cite →

Tendon drive adaptive neural network dynamic relationship sliding membrane control trajectory tracking

Abstract doi.org/10.14569/IJACSA.2024.0150508 PDF

9

Construction of Cloud Computing Task Scheduling Model Based on Simulated Annealing Hybrid Algorithm

Author 1: Kejin Lv Author 2: Tianxu Huang

With the development of cloud computing technology, effective task scheduling can help people improve work efficiency. Therefore, this study presented a hybrid algorithm on the grounds of simulated annealing and taboo search to optimize task scheduling in cloud computing. This study presented a hybrid algorithm for optimizing the cloud computing… Read full abstract & cite →

Simulated annealing algorithm taboo search optimization algorithm cloud computing task scheduling completion time load balancing degree

Abstract doi.org/10.14569/IJACSA.2024.0150509 PDF

10

Ensemble Empirical Mode Decomposition Based on Sparse Bayesian Learning with Mixed Kernel for Landslide Displacement Prediction

Author 1: Ping Jiang Author 2: Jiejie Chen

Inspired by the principles of decomposition and ensemble, we introduce an Ensemble Empirical Mode Decomposition (EEMD) method that incorporates Sparse Bayesian Learning (SBL) with Mixed Kernel, referred to as EEMD-SBLMK, specifically tailored for landslide displacement prediction. EEMD and Mutual Information (MI) techniques were jointly employed to identify potential input variables… Read full abstract & cite →

Bubble cublic ensemble empirical mode decomposition landslide Sparse Bayesian Learning

Abstract doi.org/10.14569/IJACSA.2024.0150510 PDF

11

Adaptive Scheduling of Robots in the Mixed Flow Workshop of Industrial Internet of Things

Author 1: Dejun Miao Author 2: Rongyan Xu Author 3: Yizong Dai Author 4: Jiusong Chen

With the deep integration of industrial Internet of Things technology and artificial intelligence technology, the material robot has been widely used in the Internet of Things workshop. In view of many complex factors such as real-time dynamic change and uncertain condition in workshop, this paper proposes to realize workshop adaptive… Read full abstract & cite →

Industrial Internet of Things mixed flow workshop robot Markov decision-making process SPMCTS

Abstract doi.org/10.14569/IJACSA.2024.0150511 PDF

12

Optimization of Student Behavior Detection Algorithm Based on Improved SSD Algorithm

Author 1: Yongqing CAO Author 2: Dan LIU

Despite advancements in educational technology, traditional action recognition algorithms have struggled to effectively monitor student behavior in dynamic classroom settings. To address this gap, the Single Shot Detector (SSD) algorithm was optimized for educational environments. This study aimed to assess whether integrating the Mobilenet architecture with the SSD algorithm could… Read full abstract & cite →

Improved single shot detector (SSD) model mobilenet network class behavior recognition artificial intelligence

Abstract doi.org/10.14569/IJACSA.2024.0150512 PDF

13

Detecting User Credibility on Twitter using a Hybrid Machine Learning Model of Features’ Selection and Weighting

Author 1: Nahid R. Abid-Althaqafi Author 2: Hessah A. Alsalamah

With the pervasive and rapidly growing presence of the internet and social media, creating untrustworthy accounts has become effortless, allowing fake news to be spread for personal or private interests. As a result, it is crucial in this era to investigate the credibility of users on social networking platforms such… Read full abstract & cite →

User credibility supervised machine learning feature selection feature weighting social network twitter

Abstract doi.org/10.14569/IJACSA.2024.0150513 PDF

14

Automated Motor Imagery Detection Through EEG Analysis and Deep Learning Models for Brain-Computer Interface Applications

Author 1: Yang Li Author 2: Bocheng Liu Author 3: Yujia Tian

The classification of motor imagery holds significant importance within brain-computer interface (BCI) research as it allows for the identification of a person's intention, such as controlling a prosthesis. Motor imagery involves the brain's dynamic activities, commonly captured using electroencephalography (EEG) to record nonstationary time series with low signal-to-noise ratios. While… Read full abstract & cite →

Brain-computer interface (BCI) Electroencephalogram (EEG) motor imagery deep learning classification

Abstract doi.org/10.14569/IJACSA.2024.0150514 PDF

15

Exploring Differential Entropy and Multifractal Cumulants for EEG-based Mental Workload Recognition

Author 1: Yan Lu

In the current research, two nonlinear features were utilized for the design of EEG-based mental workload recognition: one feature based on differential entropy and the other feature based on multifractal cumulants. Clean EEGs recorded from 36 healthy volunteers in both resting and task states were subjected to feature extraction via… Read full abstract & cite →

Mental workload EEG nonlinear analysis multifractal differential entropy fuzzy KNN classification

Abstract doi.org/10.14569/IJACSA.2024.0150515 PDF

16

Predicting Math Performance in High School Students using Machine Learning Techniques

Author 1: Yuan hui

In the field of education, understanding and predicting student performance plays a crucial role in improving the quality of system management decisions. In this study, the power of various machine learning techniques to learn the complicated task of predicting students’ performance in math courses using demographic data of 395 students… Read full abstract & cite →

Student performance math grade prediction feature selection regression analysis machine learning data mining

Abstract doi.org/10.14569/IJACSA.2024.0150516 PDF

17

IoT Device Identity Authentication Method Based on rPPG and CNN Facial Recognition

Author 1: Liwan Wu Author 2: Chong Yang

This study aims to address the insufficient model recognition accuracy and limitations of authentication techniques in current IoT authentication methods. The research presents a more accurate face video image authentication technique by using a new authentication method that combines convolutional neural networks (CNN) and remote Photoplethysmography (rPPG) volumetric tracing. This… Read full abstract & cite →

Internet of Things identity authentication facial recognition remote photoplethysmography error rate

Abstract doi.org/10.14569/IJACSA.2024.0150517 PDF

18

Logistics Path Planning Method using NSGA-II Algorithm and BP Neural Network in the Era of Logistics 4.0

Author 1: Liuqing Li

The distribution of fresh food is affected by its perishable characteristics, and compared with ordinary logistics distribution, the distribution path needs to be very reasonably planned. However, the complexity of the actual road network and the time variation of traffic conditions are not considered in the existing food logistics planning… Read full abstract & cite →

Whale optimization algorithm non-dominant ordering genetic algorithm backpropagation network logistics and distribution path planning

Abstract doi.org/10.14569/IJACSA.2024.0150518 PDF

19

Cloud-Enabled Real-Time Monitoring and Alert System for Primary Network Resource Scheduling and Large-Scale Users

Author 1: Bin Zhang Author 2: Hongchun Shu Author 3: Dajun Si Author 4: Jinding He Author 5: Wenlin Yan

This paper innovatively combines cloud computing with Bayesian networks, aiming to provide an efficient and real-time prediction and scheduling platform for power main network scheduling and large-scale user monitoring. The core of the research lies in the development of a set of novel intelligent scheduling algorithms, which integrates multi-objective optimization… Read full abstract & cite →

Cloud computing main network scheduling large users real-time monitoring monitoring and prediction systems research

Abstract doi.org/10.14569/IJACSA.2024.0150519 PDF

20

A Comparative Work to Highlight the Superiority of Mouth Brooding Fish (MBF) over the Various ML Techniques in Password Security Classification

Author 1: Yan Shi Author 2: Yue Wang

Within the domain of password security classification, the pursuit of practical and dependable methodologies has prompted the examination of both biological and technological paradigms. The present study investigates the efficacy of Mouth Brooding Fish (MBF) as an innovative method in contrast to conventional Machine Learning (ML) approaches for classifying password… Read full abstract & cite →

Mouth Brooding Fish (MBF) password security Sber dataset SVM Random Forest AdaBoost

Abstract doi.org/10.14569/IJACSA.2024.0150520 PDF

21

Comparative Study: Mouth Brooding Fish (MBF) as a Novel Approach for Android Malware Detection

Author 1: Kangle Zhou Author 2: Panpan Wang Author 3: Baiqing He

Android Malware Detection has become increasingly prevalent, with the highest market share among all other mobile operating systems due to its open-source nature and user-friendliness. This has resulted in an uncontrolled proliferation of malicious applications targeting the Android platform. Emerging trends of Android malware are employing highly sophisticated detection and… Read full abstract & cite →

Android malware detection ensemble learning SVM MLP RF

Abstract doi.org/10.14569/IJACSA.2024.0150521 PDF

22

Examining the Various Neural Network Algorithms Considering the Superiority of Mouth Brooding Fish in Data Classification

Author 1: Lang Liu Author 2: Yong Zhu

Data classification, a crucial practice in information management, involves categorizing data based on its sensitivity to determine appropriate access levels and protection measures. This paper explores the utilization of novel algorithms, including mouth-brooding fish (MBF), alongside machine learning techniques, for the analysis of medical health data. The SVM exhibits suboptimal… Read full abstract & cite →

Medical data analysis clinical decision support dataset classification Mouth Brooding Fish Support Vector Machine (SVM)

Abstract doi.org/10.14569/IJACSA.2024.0150522 PDF

23

A Method for Assessing Financial Market Price Behavior: An Analysis of the Shanghai Stock Exchange Index

Author 1: Zhi Huang Author 2: Jiansheng Li

A stock market is a venue where the shares of publicly traded companies are available for purchase and sale by individuals. The financial markets exert a substantial influence on various domains, including technology, employment, and business. Given the substantial rewards and risks associated with stock trading, investors are exceedingly concerned… Read full abstract & cite →

Financial market shanghai stock exchange price gated recurrent unit grasshopper optimization algorithm

Abstract doi.org/10.14569/IJACSA.2024.0150523 PDF

24

Stock Market Volatility Estimation: A Case Study of the Hang Seng Index

Author 1: Shengwen Wu Author 2: Qiqi Lin Author 3: Xuefeng liu

Among the influential elements in the national economy is the stock market. The stock market is a multifaceted system that combines economics, investor psychology, and other market mechanics. The objective of the financial market investment is to maximize profits; but, due to the market's complexity and the multitude of factors… Read full abstract & cite →

Hang Seng index financial market stock price prediction Random Forest biological bases optimization

Abstract doi.org/10.14569/IJACSA.2024.0150524 PDF

25

Presenting a New Approach for Clustering Optimization in Wireless Sensor Networks using Fuzzy Cuckoo Search Algorithm

Author 1: Bing ZHOU Author 2: Youyou LI

Because of the developments in this technology, wireless sensor networks are now among the most commonly used in the domains of agriculture, harsh environments, medical, and the military. Among the many problems with these networks is their limited lifespan. Much work has been done in the fields of sensor communication… Read full abstract & cite →

Wireless sensor network fuzzy cuckoo search algorithm clustering fuzzy model

Abstract doi.org/10.14569/IJACSA.2024.0150525 PDF

26

Enhancing Fraud Detection in Credit Card Transactions using Optimized Federated Learning Model

Author 1: Mustafa Abdul Salam Author 2: Doaa L. El-Bably Author 3: Khaled M. Fouad Author 4: M. Salah Eldin Elsayed

In recent years, credit card transaction fraud has inflicted significant losses on both consumers and financial institutions. To address this critical issue, we propose an optimized framework for fraud detection. This study deals with non-identically independent distributions (IIDs) involving different numbers of clients. The proposed framework empowers banks to construct… Read full abstract & cite →

Credit card fraud detection (CCFD) federated learning optimization algorithms identically independent distributions (IIDs) metaheuristic optimization techniques

Abstract doi.org/10.14569/IJACSA.2024.0150526 PDF

27

Embedding Emotions in the Metaverse: The Emotive Keywords for Augmented Reality Mobile Library Application

Author 1: Nik Azlina Nik Ahmad Author 2: Munaisyah Abdullah Author 3: Ahmad Iqbal Hakim Suhaimi Author 4: Anitawati Mohd Lokman

The emergence of the metaverse, marked by the seamless integration of augmented reality (AR) applications across various sectors is driving a profound transformation in the digital landscape. As we delve into the digital realm of the metaverse, just like other applications, it unfolds as an equally captivating canvas for emotional… Read full abstract & cite →

Affective engineering emotional design human factor Kansei engineering metaverse library mobile augmented reality user experience

Abstract doi.org/10.14569/IJACSA.2024.0150527 PDF

28

The Impact of Dual Objective Optimization Model Combining Non-Dominated Genetic Algorithm on Rural Industrial Ecological Economy

Author 1: Ying Wang

Due to the development of industrial economy, it has caused serious damage to the ecological environment. Based on the industrial structure and production scale, rural industrial economic parks are planned to analyze the quantity and weight of pollutants emitted from the original industries. The results showed that the quantity and… Read full abstract & cite →

Industrial chain production mode ecological economy environmental benefits non-dominated sorting genetic algorithm dual objective programming model

Abstract doi.org/10.14569/IJACSA.2024.0150528 PDF

29

Performance Enhancement of Wi-Fi Fingerprinting-based Indoor Positioning using Truncated Singular Value Decomposition and LSTM Model

Author 1: Duc Khoi Nguyen Author 2: Thi Hang Duong Author 3: Le Cuong Nguyen Author 4: Manh Kha Hoang

Wi-Fi based indoor positioning has been considered as the most promising approach for civil location-based service due to the widespread availability Wi-Fi systems in many buildings. One of the most favorable approaches is to employ received signal strength indicator (RSSI) of Wi-Fi access points as the signals for estimating the… Read full abstract & cite →

Indoor positioning Wi-Fi fingerprinting Truncated Singular Value Decomposition LSTM

Abstract doi.org/10.14569/IJACSA.2024.0150529 PDF

30

Design and Implementation of an Information Management System for College Students in Higher Education Institutions Based on Cloud Computing

Author 1: Mo Bin

A cloud computing-based system has been developed to enhance the efficiency and practicality of the information management system for college students in higher vocational colleges. This system incorporates a well-defined architecture that leverages cloud computing technology. The management layer's logic module ensures the security of vocational college students' information by… Read full abstract & cite →

Cloud computing student information management system load balancing virtual gateway personalized recommendation

Abstract doi.org/10.14569/IJACSA.2024.0150530 PDF

31

A Deep Learning-based Method for Determining Semantic Similarity of English Translation Keywords

Author 1: Wu Zhili Author 2: Zhang Qian

In the English translation task, the semantics of context play an important role in correctly understanding the subtle differences between keywords. The bidirectional LSTM includes a positive LSTM and a reverse LSTM. When processing sequence data, you can consider the information of the preceding and following text at the same… Read full abstract & cite →

Deep learning English translation keyword semantic similarity co-occurrence of words bidirectional LSTM neural network

Abstract doi.org/10.14569/IJACSA.2024.0150531 PDF

32

An Improved VMD and Wavelet Hybrid Denoising Model for Wearable SSVEP-BCI

Author 1: Yongquan Xia Author 2: Keyun Li Author 3: Duan Li Author 4: Jiaofen Nan Author 5: Ronglei Lu

The brain-computer interface (BCI) based on steady-state visual evoked potentials (SSVEP) has attracted considerable attention due to its non-invasiveness, low user training requirements, and efficient information transfer rate. To optimize the accuracy of SSVEP detection, we propose an innovative hybrid EEG denoising model combining variational mode decomposition (VMD) with wavelet… Read full abstract & cite →

Brain-computer interface steady-state visual evoked potential style variational mode decomposition wavelet packet transform

Abstract doi.org/10.14569/IJACSA.2024.0150532 PDF

33

Analyzing Quantity-based Strategies for Supply Chain Sustainability and Resilience in Uncertain Environment

Author 1: Dounia SAIDI Author 2: Aziz AIT BASSOU Author 3: Mustapha HLYAL Author 4: Jamila EL ALAMI

In today's interconnected world, where supply chains are the backbone of commerce, ensuring their resilience and sustainability is paramount. This study investigates how quantity-based strategies in supply chain networks are influenced by sustainability and resilience considerations. A conceptual framework is devised, focusing on a two-echelon supply chain network comprising a… Read full abstract & cite →

Supply chain management competition sustainability resilience demand uncertainty

Abstract doi.org/10.14569/IJACSA.2024.0150533 PDF

34

Hardhat-YOLO: A YOLOv5-based Lightweight Hardhat-Wearing Detection Algorithm in Substation Sites

Author 1: Wanbo Luo Author 2: Ahmad Ihsan Mohd Yassin Author 3: Khairul Khaizi Mohd Shariff Author 4: Rajeswari Raju

Accidents at substation sites have occurred frequently in recent years due to workers violating power safety regulations by not wearing hardhats. Therefore, it is necessary to provide real-time warnings when detecting workers without hardhats. Nevertheless, the deployment of deep learning-based algorithms necessitates the utilization of a multitude of parameters and… Read full abstract & cite →

Hardhat-wearing detection You Only Look Once (YOLO) MobileNet Substation power Internet of Things (PIoT)

Abstract doi.org/10.14569/IJACSA.2024.0150534 PDF

35

Model for Responsive Agriculture Hub via e-Commerce to Sustain Food Security

Author 1: Wan Nurhayati Wan Ab. Rahman Author 2: Wan Nurfarah Wan Zulkifli Author 3: Nur Nabilah Zainuri Author 4: Hanis Amira Khairol Anwar

Ensuring food security in the face of evolving environmental, economic, and societal challenges requires innovative solutions that leverage emerging technologies. This paper proposes a model for a responsive agriculture hub facilitated through e-commerce platforms to address the dynamic demands of food production, distribution, and consumption. The model integrates data-driven decision-making… Read full abstract & cite →

Digital agriculture hub model digital value chain responsive agriculture hub food security multi-sided e-commerce

Abstract doi.org/10.14569/IJACSA.2024.0150535 PDF

36

Digital Public System of Urban Art: Navigating Human-Computer Interaction in Artistic Design for Innovative Urban Expressions

Author 1: Yuan Yao Author 2: Ying Liu

The convergence of digital technology and urban art has given rise to novel urban art digitalization systems. This paper investigates the relationship between Human-Computer Interaction (HCI) and creative design, particularly in the age of 3D printing, Virtual Reality (VR), and digital art. We highlight the transformative potential of these technologies… Read full abstract & cite →

Urban art digitalization human-computer interaction creative expression public art technological innovation

Abstract doi.org/10.14569/IJACSA.2024.0150536 PDF

37

Fusion Lightweight Steel Surface Defect Detection Algorithm Based on Improved Deep Learning

Author 1: Fei Ren Author 2: Jiajie Fei Author 3: HongSheng Li Author 4: Bonifacio T. Doma Jr

In industrial production, timely and accurate detection and identification of surface defects in steel materials were crucial for ensuring product quality, enhancing production efficiency, and reducing production costs. This study addressed the problem of surface defect detection in steel materials by proposing an algorithm based on an improved version of… Read full abstract & cite →

Deep learning improved YOLOv5 YOLOv5-mobilenet surface defects

Abstract doi.org/10.14569/IJACSA.2024.0150537 PDF

38

AdvAttackVis: An Adversarial Attack Visualization System for Deep Neural Networks

Author 1: DING Wei-jie Author 2: Shen Xuchen Author 3: Yuan Ying Author 4: MAO Ting-yun Author 5: SUN Guo-dao Author 6: CHEN Li-li Author 7: CHEN bing-ting

Deep learning has been widely used in various scenarios such as image classification, natural language processing, and speech recognition. However, deep neural networks are vulnerable to adversarial attacks, resulting in incorrect predictions. Adversarial attacks involve generating adversarial examples and attacking a target model. The generation mechanism of adversarial examples and… Read full abstract & cite →

Deep learning deep neural networks adversarial attacks adversarial examples interactive visualization

Abstract doi.org/10.14569/IJACSA.2024.0150538 PDF

39

Exploring the Impact of PCA Variants on Intrusion Detection System Performance

Author 1: CHENTOUFI Oumaima Author 2: CHOUKHAIRI Mouad Author 3: CHOUGDALI Khalid Author 4: ALLOUG Ilyas

Intrusion detection systems (IDS) play a critical role in safeguarding network security by identifying malicious activities within network traffic. However, the effectiveness of an IDS hinges on its ability to extract relevant features from the vast amount of data it collects. This study investigates the impact of different feature extraction… Read full abstract & cite →

Intrusion detection dimensionality reduction feature extraction KDDCup’99 NSL-KDD

Abstract doi.org/10.14569/IJACSA.2024.0150539 PDF

40

Enhancing Whale Optimization Algorithm with Differential Evolution and Lévy Flight for Robot Path Planning

Author 1: Rongrong TANG Author 2: Xuebang TANG Author 3: Hongwang ZHAO

Path planning is a prominent and essential part of mobile robot navigation in robotics. It allows robots to determine the optimal path from a given beginning point to a desired end goal. Additionally, it enables robots to navigate around obstacles, recognize secure pathways, and select the optimal route to follow… Read full abstract & cite →

Path planning mobile robot differential evolution Whale Optimization Algorithm lévy flight

Abstract doi.org/10.14569/IJACSA.2024.0150540 PDF

41

A Capacitance-base System Design for Measurement of Crude Oil Moisture

Author 1: ZhixueShi Author 2: Xudong Zhao

Challenges including difficulty in cleaning and low measurement accuracy widely exist in traditional methods for measuring moisture in crude oil. In order to solve these problems, a capacitance measurement device that combines PCAP01 and STM32 has been designed. PCAP01 is employed as the processing core of the sensor, which significantly… Read full abstract & cite →

Capacitance measurement crude oil moisture PCAP01 STM32 time-frequency domain

Abstract doi.org/10.14569/IJACSA.2024.0150541 PDF

42

SchemaLogix: Advancing Interoperability with Machine Learning in Schema Matching

Author 1: Mohamed Raoui Author 2: Mohammed Ennaouri Author 3: Moulay Hafid El Yazidi Author 4: Ahmed Zellou

Schema matching, a fundamental process in data integration, traditionally employs pairwise comparisons to discern semantic correspondences among elements in disparate schemas. However, recent developments underscore the necessity of concurrent matching of interconnected schemas, termed schema alignment, to reconcile heterogeneous elements. This paper presents SchemaLogix, an innovative machine learning-based approach for… Read full abstract & cite →

Interoperability data integration schema matching machine learning

Abstract doi.org/10.14569/IJACSA.2024.0150542 PDF

43

Image Segmentation in Complex Backgrounds using an Improved Generative Adversarial Network

Author 1: Mei Wang Author 2: Yiru Zhang

As technology advances, solving image segmentation challenges in complex backgrounds has become a key issue across various fields. Traditional image segmentation methods underperform in addressing these challenges, and existing generative adversarial networks (GANs) also face several problems when applied in complex environments, such as low generation quality and unstable model… Read full abstract & cite →

Generative Adversarial Networks (GANs) complex backgrounds image segmentation data augmentation feature dimensionality reduction encoding

Abstract doi.org/10.14569/IJACSA.2024.0150543 PDF

44

A Novel Quantum Orthogonal Frequency-Division Multiplexing Transmission Scheme

Author 1: Mohammed R. Almasaoodi Author 2: Abdulbasit M. A. Sabaawi Author 3: Sara El Gaily Author 4: Sándor Imre

Recently, extensive research attention has been dedicated to enabling Orthogonal Frequency-Division Multiplexing (OFDM) waveforms to be compatible with a modern communication system. Encoding data as OFDM wavelengths still has a lot of problems, like the peak-to-average power ratio (PAPR) and the cyclic prefix (CP), which are important factors that affect… Read full abstract & cite →

Discrete Fourier transform quantum Fourier transform orthogonal frequency-division multiplexing quantum channel

Abstract doi.org/10.14569/IJACSA.2024.0150544 PDF

45

Deep Learning-based Classification of MRI Images for Early Detection and Staging of Alzheimer's Disease

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

Alzheimer's disease (AD) poses a significant challenge to modern healthcare, as effective treatment remains elusive. Drugs may slow down the progress of the disease, but there is currently no cure for it. Early AD identification is crucial for providing the required medications before brain damage occurs. In this course of… Read full abstract & cite →

Alzheimer’s disease (AD) Convolution Neural Network (CNN) Deep Learning (DL) Transfer Learning (TL) imaging pre-processing

Abstract doi.org/10.14569/IJACSA.2024.0150545 PDF

46

Image Processing-based Performance Evaluation of KNN and SVM Classifiers for Lung Cancer Diagnosis

Author 1: Kavitha B C Author 2: Naveen K B

It is important to note that the cure rates in cases of advanced stages of lung cancer are remarkably low, which stresses out the importance for early detection as means to increase survival chances. A strong area of focus when it comes to increased research in the lung cancer diagnosis… Read full abstract & cite →

K-Nearest Neighbors lung cancer detection machine learning medical data performance metrics support vector machine

Abstract doi.org/10.14569/IJACSA.2024.0150546 PDF

47

Generative AI-Powered Predictive Analytics Model: Leveraging Synthetic Datasets to Determine ERP Adoption Success Through Critical Success Factors

Author 1: Koh Chee Hong Author 2: Abdul Samad Bin Shibghatullah Author 3: Thong Chee Ling Author 4: Samer Muthana Sarsam

Data scarcity is a significant problem in Enterprise Resource Planning (ERP) adoption prediction, limiting the accuracy and reliability of traditional predictive models. This study addresses this issue by integrating Generative Artificial Intelligence (AI) technologies, specifically Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), to generate synthetic data that supplements sparse… Read full abstract & cite →

ERP adoption predictive analytics generative AI synthetic data GANs VAEs Pearson's correlation coefficient random forest

Abstract doi.org/10.14569/IJACSA.2024.0150547 PDF

48

An Investigation of Scalability in EHRs using Healthcare 4.0 and Blockchain

Author 1: Ahmad Fayyaz Madni Author 2: Munam Ali Shah Author 3: Muhammad Al-Naeem

In the past decade, Electronic Health Records (EHRs) based on clouds have become popular in empowering remote patient monitoring. The rise of Health 4.0, which includes using system elements and cloud services to access health records remotely, has gained highest attention of the experts. Healthcare 4.0 requires the consistent collection… Read full abstract & cite →

EHRs secure cloud Healthcare 4.0 Blockchain scalability cyber threats medical information security

Abstract doi.org/10.14569/IJACSA.2024.0150548 PDF

49

Traffic Flow Prediction at Intersections: Enhancing with a Hybrid LSTM-PSO Approach

Author 1: Chaimaa CHAOURA Author 2: Hajar LAZAR Author 3: Zahi JARIR

The growing challenge of increasing traffic volumes presents a real challenge for road safety, emergency response and overall transport efficiency. Intelligent transportation systems play a fundamental role in solving these challenges, through accurate traffic prediction. In this study, we propose a hybrid model that combines the Long-Term Memory Algorithm (LSTM)… Read full abstract & cite →

Deep learning intersection congestion intelligent transport systems traffic flow prediction

Abstract doi.org/10.14569/IJACSA.2024.0150549 PDF

50

Remote Palliative Care: A Systematic Review of Effectiveness, Accessibility, and Patient Satisfaction

Author 1: Rihab El Sabrouty Author 2: Abdelmajid Elouadi Author 3: Mai Abdou Salifou Karimoune

Remote palliative care has emerged as a viable option to address the complex needs of patients facing life-limiting illnesses, particularly in the context of evolving healthcare landscapes and technological advancements. This systematic review aims to comprehensively examine the effectiveness, accessibility, and patient satisfaction of remote palliative care interventions. Through a… Read full abstract & cite →

Palliative care eHealth patient artificial intelligence well-being

Abstract doi.org/10.14569/IJACSA.2024.0150550 PDF

51

Enhancing SDN Anomaly Detection: A Hybrid Deep Learning Model with SCA-TSO Optimization

Author 1: Ahmed Mohanad Jaber ALHILO Author 2: Hakan Koyuncu

The paper explores the evolving landscape of network security, in Software Defined Networking (SDN) highlighting the challenges faced by security measures as networks transition to software-based control. SDN revolutionizes Internet technology by simplifying network management and boosting capabilities through the OpenFlow protocol. It also brings forth security vulnerabilities. To address… Read full abstract & cite →

SDN Intrusion Detection System deep learning CNN LSTM SCA TSO

Abstract doi.org/10.14569/IJACSA.2024.0150551 PDF

52

Comprehensive and Simulated Modeling of a Centralized Transport Robot Control System

Author 1: Murad Bashabsheh

This work proposes a new simulation model for a centralized transport robot control system that was created with the AnyLogic environment and a special blend of agent-based and discrete-event approaches. The model attempts to do a comprehensive analysis of the centralized request distribution algorithm among robots, gauging the effectiveness of… Read full abstract & cite →

Artificial intelligence centralized control system transport robots automatic system agent-based modeling AnyLogic Arduino microcontroller

Abstract doi.org/10.14569/IJACSA.2024.0150552 PDF

53

Estimating Stock Market Prices with Histogram-based Gradient Boosting Regressor: A Case Study on Alphabet Inc

Author 1: Shigen Li

One of the most important and common activities mentioned while discussing the financial markets is stock market trading. An investor is constantly searching for methods to estimate future trends to minimize losses and maximize profits due to the unavoidable volatility in stock prices. It is undeniable, nonetheless, that there is… Read full abstract & cite →

Alphabet Inc. market movement stock financial markets Histogram-based gradient boosting

Abstract doi.org/10.14569/IJACSA.2024.0150553 PDF

54

A Study on Wireless Sensor Node Localization and Target Tracking Based on Improved Locust Algorithm

Author 1: Tan SONGHE Author 2: Qin Qi

To improve the positioning accuracy of wireless sensor nodes and ensure the target tracking effect, a wireless sensor node positioning and target tracking method based on an improved locust algorithm is proposed. The DV Hop algorithm is used to calculate the minimum hops and average hops distance between the unknown… Read full abstract & cite →

Improved locust algorithm wireless sensors node localization target tracking target state unknown node position

Abstract doi.org/10.14569/IJACSA.2024.0150554 PDF

55

Toward Optimal Service Composition in the Internet of Things via Cloud-Fog Integration and Improved Artificial Bee Colony Algorithm

Author 1: Guixia Xiao

In the quest to delve deeper into the burgeoning realm of the service-oriented Internet of Things (IoT), the pressing challenge of smoothly integrating functionalities within smart objects emerges prominently. IoT devices, notorious for their resource constraints, often lean heavily on cloud infrastructures to function effectively. However, the emergence of fog… Read full abstract & cite →

Internet of Things (IoT) fog computing service composition Artificial Bee Colony (ABC) Algorithm Dynamic Reduction Mechanism

Abstract doi.org/10.14569/IJACSA.2024.0150555 PDF

56

Emotion-based Autism Spectrum Disorder Detection by Leveraging Transfer Learning and Machine Learning Algorithms

Author 1: I. Srilalita Sarwani Author 2: D. Lalitha Bhaskari Author 3: Sangeeta Bhamidipati

Autism Spectrum Disorder (ASD) presents as a neurodevelopmental condition impacting social interaction, communication, and behavior, underscoring the imperative of early detection and intervention to enhance outcomes. This paper introduces a novel approach to ASD detection utilizing facial features extracted from the Autistic Children Facial Dataset. Leveraging transfer learning models, including… Read full abstract & cite →

Autism Spectrum Disorder transfer learning image features VGG ResNet Inception

Abstract doi.org/10.14569/IJACSA.2024.0150556 PDF

57

Offensive Language Detection on Social Media using Machine Learning

Author 1: Rustam Abdrakhmanov Author 2: Serik Muktarovich Kenesbayev Author 3: Kamalbek Berkimbayev Author 4: Gumyrbek Toikenov Author 5: Elmira Abdrashova Author 6: Oichagul Alchinbayeva Author 7: Aizhan Ydyrys

This research paper addresses the critical issue of cyberbullying detection within the realm of social networks, employing a comprehensive examination of various machine learning and deep learning techniques. The study investigates the performance of these methodologies through rigorous evaluation using standard metrics, including Accuracy, Precision, Recall, F-measure, and AUC-ROC. The… Read full abstract & cite →

Machine learning deep learning hate speech CNN RNN LSTM

Abstract doi.org/10.14569/IJACSA.2024.0150557 PDF

58

A Deep Residual Network Designed for Detecting Cracks in Buildings of Historical Significance

Author 1: Zlikha Makhanova Author 2: Gulbakhram Beissenova Author 3: Almira Madiyarova Author 4: Marzhan Chazhabayeva Author 5: Gulsara Mambetaliyeva Author 6: Marzhan Suimenova Author 7: Guldana Shaimerdenova Author 8: Elmira Mussirepova Author 9: Aidos Baiburin

This research paper investigates the application of deep learning techniques, specifically convolutional neural networks (CNNs), for crack detection in historical buildings. The study addresses the pressing need for non-invasive and efficient methods of assessing structural integrity in heritage conservation. Leveraging a dataset comprising images of historical building surfaces, the proposed… Read full abstract & cite →

Crack detection historical buildings deep learning convolutional neural networks heritage conservation image analysis machine learning non-destructive testing preservation

Abstract doi.org/10.14569/IJACSA.2024.0150558 PDF

59

Mobile Application with Augmented Reality Applying the MESOVA Methodology to Improve the Learning of Primary School Students in an Educational Center

Author 1: Anthony Wilder Arias Vilchez Author 2: Tomas Silvestre Marcelo Lloclla Soto Author 3: Giancarlo Sanchez Atuncar

"The application was developed using the MESOVA methodology, employing technologies such as Unity, Vuforia, and Visual Studio with the purpose of enhancing the educational experience for elementary school students. This innovative tool integrates augmented reality with the pedagogical principles of MESOVA, standing out notably from other research. Focusing on topics… Read full abstract & cite →

Augmented reality mobile application MESOVA methodology Kolmogorov-Smirnov Wilcoxon education Vuforia

Abstract doi.org/10.14569/IJACSA.2024.0150559 PDF

60

An Improved MobileNet Model Integrated Spatial and Channel Attention Mechanisms for Tea Disease

Author 1: Li Zhang Author 2: Jiacheng Sun Author 3: Minghui Yang

Aiming at addressing the challenges of large model parameters, high computational cost, and low accuracy of the traditional tea disease identification model, an improved MobileNet model integrated spatial and channel attention mechanisms (MobileNet-SCA) was proposed for tea disease identification. Firstly, the tea disease identification dataset was augmented through random clipping… Read full abstract & cite →

Tea disease MobileNetV3 attention mechanism convolutional neural network component

Abstract doi.org/10.14569/IJACSA.2024.0150560 PDF

61

Tourist Attraction Recommendation Model Based on RFPAP-NNPAP Algorithm

Author 1: Jun Li

Driven by globalization and digitization, the tourism industry is facing new challenges and opportunities brought about by big data and artificial intelligence. The recommendation of tourist attractions, as an important part of the industry, has a direct influence on the tourist experience. However, with the diversification and personalization of tourism… Read full abstract & cite →

Tourist attractions recommendation model RF ANN FP-Growth

Abstract doi.org/10.14569/IJACSA.2024.0150561 PDF

62

Ontology Driven for Mapping a Relational Database to a Knowledge-based System

Author 1: Abdelrahman Osman Elfaki Author 2: Yousef H. Alfaifi

The mapping of a relational database system to a knowledge-based system is a key stage in developing an online analytical processing (OLAP) system. OLAP is a cornerstone in discovering hidden knowledge in any business. Hence, the existence of an OLAP system is one of the modern success factors in a… Read full abstract & cite →

Mapping knowledge ontology-based relational database online analytical processing

Abstract doi.org/10.14569/IJACSA.2024.0150562 PDF

63

A Novel Controlling System for Smart Farming-based Internet of Things (IoT)

Author 1: Dodi Yudo Setyawan Author 2: Warsito Author 3: Roniyus Marjunus Author 4: Sumaryo

The integration of IoT systems in agriculture has become a very important need amid the high population and increasingly limited farmland, which demands researchers to be more innovative in addressing these issues. Using IoT systems for automatic irrigation, fertilization, and cooling based on sensor values through internet networks. Poor internet… Read full abstract & cite →

IoT agriculture automation sustainability

Abstract doi.org/10.14569/IJACSA.2024.0150563 PDF

64

Method of Budding Detection with YOLO-based Approach for Determination of the Best Time to Plucking Tealeaves

Author 1: Kohei Arai Author 2: Yoho Kawaguchi

Method of budding detection with YOLO (You Only Look Once) for determination of the best time to plucking tealeaves is proposed. In order to get the best quality and quantity of tealeaves, it is very important to determine the best time to plucking date. It is most likely that the… Read full abstract & cite →

Budding YOLO plucking tealeaves quality quantity hyperparameter learning performance

Abstract doi.org/10.14569/IJACSA.2024.0150564 PDF

65

Road Accident Detection using SVM and Learning: A Comparative Study

Author 1: Fatima Qanouni Author 2: Hakim El Massari Author 3: Noreddine Gherabi Author 4: Maria El Badaoui

Everyday, a great deal of children and young adults (aged five to 29) lives are lost in road accidents. The most frequent causes are a driver’s behavior, the streets infrastructure is of lower quality and the delayed response of emergency services especially in rural areas. There is a need for… Read full abstract & cite →

Road accidents road traffic management machine learning SVM deep learning ensemble learning

Abstract doi.org/10.14569/IJACSA.2024.0150565 PDF

66

Recognition of Hate Speech using Advanced Learning Model-based Multi-Layered Approach (MLA)

Author 1: Puspendu Biswas Author 2: Donavalli Haritha

Hate speech becomes more complicated for the users of social media. Some users on online social networking sites (OSNS) create a lot of nonsense by uploading hate speech. OSNS applications developing many models to prevent this hate speech in terms of text and videos. However, these messages still need to… Read full abstract & cite →

Multi-Layered Approach (MLA) Deep Learning (DL) DistilBERT GloVe Bi-grams (2-grams)

Abstract doi.org/10.14569/IJACSA.2024.0150566 PDF

67

Method Resource Sharing in On-Premises Environment Based on Cross-Origin Resource Sharing and its Application for Safety-First Constructions

Author 1: Kohei Arai Author 2: Kodai Norikoshi Author 3: Mariko Oda

The method of resource sharing in an on-premises environment based on Cross-Origin Resource Sharing (CORS) is proposed for security reasons. However, using CORS entails several risks: Cross-Site Request Forgery (CSRF), difficulties in secure configuration, handling credentials, controlling complex requests, and restrictions associated with using wildcards. (1) To mitigate these risks… Read full abstract & cite →

Cross-Origin Resource Sharing: CORS CSRF (Cross-Site Request Forgery) SameSite withCredentials flag Access-Control-Allow-Credentials header safety first constructions

Abstract doi.org/10.14569/IJACSA.2024.0150567 PDF

68

A Raise of Security Concern in IoT Devices: Measuring IoT Security Through Penetration Testing Framework

Author 1: Abdul Ghafar Jaafar Author 2: Saiful Adli Ismail Author 3: Abdul Habir Author 4: Khairul Akram Zainol Ariffin Author 5: Othman Mohd Yusop

Despite the widespread adoption of IoT devices across different industries to enhance human activities, there is a pressing need to address the vulnerabilities associated with these devices, as they can potentially give rise to a plethora of cyber threats. Cyberattacks targeting IoT devices are predominantly attributed to inadequate patching and… Read full abstract & cite →

IoT Security IoT penetration testing security assessment automated penetration testing penetration testing framework

Abstract doi.org/10.14569/IJACSA.2024.0150568 PDF

69

Decision Making Systems for Pneumonia Detection using Deep Learning on X-Ray Images

Author 1: Zhadra Kozhamkulova Author 2: Elmira Nurlybaeva Author 3: Madina Suleimenova Author 4: Dinargul Mukhammejanova Author 5: Marina Vorogushina Author 6: Zhanar Bidakhmet Author 7: Mukhit Maikotov

This research paper investigates the application of Convolutional Neural Networks (CNNs) for the classification of pneumonia using chest X-ray images. Through rigorous experimentation and data analysis, the study demonstrates the model's impressive learning capabilities, achieving a notable accuracy of 96% in pneumonia classification. The consistent decrease in training and validation… Read full abstract & cite →

CNN machine learning pneumonia X-ray image analysis classification

Abstract doi.org/10.14569/IJACSA.2024.0150569 PDF

70

Data Security Optimization at Cloud Storage using Confidentiality-based Data Classification

Author 1: Dorababu Sudarsa Author 2: A. Nagaraja Rao Author 3: A. P. Sivakumar

Data is the most assets for any organization, stored either in individual systems, server, or cloud platform. Cloud, one of the trending storage systems being adapted now a day is the state-of-the-art of the advanced technology. The major concern with this technological growth is privacy and security of data. Hoisting… Read full abstract & cite →

Cloud storage data privacy data security data classification degree of confidentiality

Abstract doi.org/10.14569/IJACSA.2024.0150570 PDF

71

Optimal Trajectory Planning for Robotic Arm Based on Improved Dynamic Multi-Population Particle Swarm Optimization Algorithm

Author 1: Rong Wu Author 2: Yong Yang Author 3: Xiaotong Yao Author 4: Nannan Lu

In response to the problem of easy falling into local optima and low execution efficiency of the basic particle swarm optimization algorithm for 6-degree-of-freedom robots under kinematic constraints, a trajectory planning method based on an improved dynamic multi-population particle swarm optimization algorithm is proposed. According to the average fitness value… Read full abstract & cite →

Particle swarm optimization Gaussian mutation mixed particles levy flight greedy strategy

Abstract doi.org/10.14569/IJACSA.2024.0150571 PDF

72

Migration Learning and Multi-View Training for Low-Resource Machine Translation

Author 1: Jing Yan Author 2: Tao Lin Author 3: Shuai Zhao

This paper discusses the main challenges and solution strategies of low-resource machine translation, and proposes a novel translation method combining migration learning and multi-view training. In a low-resource environment, neural machine translation models are prone to problems such as insufficient generalization performance, inaccurate translation of long sentences, difficulty in processing… Read full abstract & cite →

Low-resource machine translation migration learning multi-view training continual pretraining multidimensional linguistic feature integration

Abstract doi.org/10.14569/IJACSA.2024.0150572 PDF

73

Visual Communication Design Based on Sparsity-Enhanced Image Processing Models

Author 1: Zheng Wang Author 2: Dongsik Hong

In the field of visual communication, image clarity and accuracy are the key to convey effective information. A new sparsity-enhanced image processing model is introduced to address the limitations of traditional image processing models in terms of image resolution and fidelity. This model combines a deep neural networks learning framework… Read full abstract & cite →

Deep neural networks convolutional neural networks sparsity dictionary learning image reinforcement processing

Abstract doi.org/10.14569/IJACSA.2024.0150573 PDF

74

Enhancing Age Estimation from Handwriting: A Deep Learning Approach with Attention Mechanisms

Author 1: Li Zhao Author 2: Xiaoping Wu Author 3: Xiaoming Chen

Currently, age estimation is a hot research topic in the field of forensic biology. Age estimation methods based on facial or brain features are easily affected by external factors. In contrast, handwriting analysis is a more reliable method for age estimation. This paper aims to improve the accuracy and efficiency… Read full abstract & cite →

Age estimation coordinate attention mechanism handwriting analysis accuracy

Abstract doi.org/10.14569/IJACSA.2024.0150574 PDF

75

Generation of Topical Educational Content by Estimation of the Number of Patents in the Digital Field

Author 1: Evgeny Nikulchev Author 2: Dmitry Ilin

Analysis of trends in the development of emerging technologies based on patents is a well-recognized approach. An increase in the number of patents precedes the extensive spread of technological solutions and their incorporation in production and professional activities, making it possible to perform predictive analysis. The field of digital technology… Read full abstract & cite →

Time series patent analysis parameter plane predictive analysis

Abstract doi.org/10.14569/IJACSA.2024.0150575 PDF

76

Enhancing Smart Contract Security Through Multi-Agent Deep Reinforcement Learning Fuzzing: A Survey of Approaches and Techniques

Author 1: Muhammad Farman Andrijasa Author 2: Saiful Adli Ismail Author 3: Norulhusna Ahmad Author 4: Othman Mohd Yusop

Multi-Agent Systems (MAS) and Deep Reinforcement Learning (DRL) have emerged as powerful tools for enhancing security measures, particularly in the context of smart contract security in blockchain technology. This literature review explores the integration of Multi-Agent DRL fuzzing techniques to bolster the security of smart contracts. The study delves into… Read full abstract & cite →

Smart contract security multi-agent systems deep reinforcement learning fuzzing techniques blockchain technology

Abstract doi.org/10.14569/IJACSA.2024.0150576 PDF

77

Exhaustive Insights Towards Social-Media Driven Disaster Management Approaches

Author 1: Nethravathy Krishnappa Author 2: D Saraswathi Author 3: Chandrasekar Chelliah

The manuscript presents discussion about the disaster management approaches using social media. It is noted that rising popularity of social media has been witnessed to significantly contribute towards information propagation and community participation to deal with the event of disaster. Different from conventional disaster management policies, the scope of inclusion… Read full abstract & cite →

Artificial intelligence disaster management information propagation social media community

Abstract doi.org/10.14569/IJACSA.2024.0150577 PDF

78

Network Security Evaluation Based on Improved Genetic Algorithm and Weighted Error Backpropagation Algorithm

Author 1: Jinlong Pang Author 2: Chongwei Liu

As the speed advancement of network technology and the popularization of applications, network security problems are becoming more and more prominent, all kinds of network attacks and security threats are increasing, and the demand for network security evaluation is becoming more and more urgent. To address the issues of long… Read full abstract & cite →

Genetic algorithm return propagation algorithm cybersecurity evaluation weighting network vulnerability

Abstract doi.org/10.14569/IJACSA.2024.0150578 PDF

79

Application Analysis of Network Security Situational Awareness Model for Asset Information Protection

Author 1: Yuemei Ren Author 2: Xianju Feng

The popularity of the Internet makes the network develop rapidly. However, the network security threat is more complex and hidden. The traditional network security alarm system has the problems of low accuracy and low efficiency when dealing with huge redundant data. Therefore, the research comprehensively considers the network security problems… Read full abstract & cite →

Asset information protection cyber security situational awareness knowledge graph attack scenarios

Abstract doi.org/10.14569/IJACSA.2024.0150579 PDF

80

Big Data Multi-Strategy Predator Algorithm for Passenger Flow Prediction

Author 1: Peng Guo

Faced with the rapidly recovering tourism market, accurate prediction of passenger flow can help local authorities achieve more effective resource regulation. Therefore, based on big data technology, a multi-strategy predator algorithm is proposed, which uses the Marine Predator Algorithm, combined with regularized extreme learning machines and Collaborative Filtering Algorithms, to… Read full abstract & cite →

Passemger Flow Prediction regularized extreme learning machine Collaborative Filtering Algorithm Marine Predator Algorithm

Abstract doi.org/10.14569/IJACSA.2024.0150580 PDF

81

Computer Simulation Study of Stiffness Variation of Stewart Platform under Different Loads

Author 1: Zhiqiang Zhao Author 2: Yuetao Liu Author 3: Changsong Yu Author 4: Peicen Jiang

The ability of Stewart platform to resist deformation is an important target for designing and optimizing the platform, and studying the variation rule of stiffness of Stewart platform under different loads can help us to understand the dynamic characteristics of the platform, guide the design and control of the platform… Read full abstract & cite →

Stewart different loads stiffness variation computer simulation

Abstract doi.org/10.14569/IJACSA.2024.0150581 PDF

82

Transforming Pixels: Crafting a 3D Integer Discrete Cosine Transform for Advanced Image Compression

Author 1: R. Rajprabu Author 2: T. Prathiba Author 3: Deepa Priya V. Author 4: Arthy Rajkumar Author 5: Rajkannan. C Author 6: P. Ramalakshmi

We propose an innovative technique for image compression based on the 3-dimensional Integer Discrete Cosine Transform (3D-Integer DCT), which will serve as an alternative to the existing DCT-based compression technique. If an image is encoded as cubes [row × column × temporal length] instead of blocks [row × column], higher… Read full abstract & cite →

Discrete cosine transform 3D integer DCT Image compression JPEG algorithm

Abstract doi.org/10.14569/IJACSA.2024.0150582 PDF

83

Real-Time Road Lane-Lines Detection using Mask-RCNN Approach

Author 1: Gulbakhram Beissenova Author 2: Dinara Ussipbekova Author 3: Firuza Sultanova Author 4: Karasheva Nurzhamal Author 5: Gulmira Baenova Author 6: Marzhan Suimenova Author 7: Kamar Rzayeva Author 8: Zhanar Azhibekova Author 9: Aizhan Ydyrys

This paper presents a novel approach to real-time road lane-line detection using the Mask R-CNN framework, with the aim of enhancing the safety and efficiency of autonomous driving systems. Through extensive experimentation and analysis, the proposed system demonstrates robust performance in accurately detecting and segmenting lane boundaries under diverse driving… Read full abstract & cite →

Lane lines detection classification segmentation Mask-RCNN deep learning

Abstract doi.org/10.14569/IJACSA.2024.0150583 PDF

84

Hybrid Convolutional Recurrent Neural Network for Cyberbullying Detection on Textual Data

Author 1: Altynzer Baiganova Author 2: Saniya Toxanova Author 3: Meruert Yerekesheva Author 4: Nurshat Nauryzova Author 5: Zhanar Zhumagalieva Author 6: Aigerim Tulendi

With the burgeoning use of social media platforms, online harassment and cyberbullying have become significant concerns. Traditional mechanisms often falter, necessitating advanced methodologies for efficient detection. This study presents an innovative approach to identifying cyberbullying incidents on social media sites, employing a hybrid neural network architecture that amalgamates Long Short-Term… Read full abstract & cite →

CNN RNN LSTM urban sounds impulsive sounds

Abstract doi.org/10.14569/IJACSA.2024.0150584 PDF

85

Studying the Behavior of a Modified Deep Learning Model for Disease Detection Through X-ray Chest Images

Author 1: Elma Zanaj Author 2: Lorena Balliu Author 3: Gledis Basha Author 4: Elunada Gjata Author 5: Elinda Kajo Meçe

In modern medical diagnostics, Deep Learning models are commonly used for illness diagnosis, especially over X-ray chest images. Deep Learning approaches provide unmatched promise for early identification, prognosis, and treatment evaluation across a range of illnesses, by combining sophisticated algorithms with large datasets. It is crucial to research these models… Read full abstract & cite →

Machine learning big data X-ray chest image CNN VGG19

Abstract doi.org/10.14569/IJACSA.2024.0150585 PDF

86

Establishment of Economic Analysis Model Based on Artificial Intelligence Technology

Author 1: Jiqing Shi

With the continuous evolution of artificial intelligence technology, its integration into economic analysis models is becoming increasingly prevalent. This paper employs the Lasso Back Propagation neural network method to conduct financial analysis and prediction for major global economies, focusing on total Gross Domestic Product, combined Gross Domestic Product growth rate… Read full abstract & cite →

Artificial intelligence lasso regression BP neural network economic analysis model major global economies multi-hidden layer variable analysis economic trends

Abstract doi.org/10.14569/IJACSA.2024.0150586 PDF

87

Deep Learning Approach to Classify Brain Tumors from Magnetic Resonance Imaging Images

Author 1: Asma Ahmed A. Mohammed

Brain tumor is one of the primary causes of mortality all over the globe, and it poses as one of the most complicated tasks in contemporary medicine when it comes to its proper diagnosis and classification into its many different types. Both benign and malignant tumors affect the lives of… Read full abstract & cite →

Deep learning brain tumor MRI images Convolutional Neural Networks (CNN) Xception VGG-16 ResNet50

Abstract doi.org/10.14569/IJACSA.2024.0150587 PDF

88

Multi-Objective Optimization of Oilfield Development Planning Based on Shuffled Frog Leaping Algorithm

Author 1: Jun Wei

Oilfield development planning is a complex task that involves multiple optimization objectives and constraints. Therefore, a study proposes an improved shuffled frog leaping algorithm to achieve multi-objective optimization tasks. In multi-objective problems, the fitness value of the algorithm is not adaptive to the memetic evolution, resulting in local search failures… Read full abstract & cite →

Shuffled frog leaping algorithm oilfield development multi-objective optimization improve

Abstract doi.org/10.14569/IJACSA.2024.0150588 PDF

89

Investigating an Ensemble Classifier Based on Multi-Objective Genetic Algorithm for Machine Learning Applications

Author 1: Zhiyuan LIU

Ensemble learning in machine learning applications is crucial because it leverages the collective wisdom of multiple models to enhance predictive performance and generalization. Ensemble learning is a method to provide a better approximation of an optimal classifier. A number of basic classifiers are used in ensemble learning. In order to… Read full abstract & cite →

Machine learning genetic algorithm ensemble classification classification error

Abstract doi.org/10.14569/IJACSA.2024.0150589 PDF

90

Automatic Detection of Ascaris Lumbricoides in Microscopic Images using Convolutional Neural Networks (CNN)

Author 1: Giovanni Gelber Martinez Pastor Author 2: Cesar Roberto Ancco Ruelas Author 3: Eveling Castro-Gutierrez Author 4: Victor Luis Vásquez Huerta

Parasites are disease-causing agents both in Peru and worldwide. In many contexts, diagnosis is done manually by observing microscopic images, where it's necessary to identify parasite eggs. However, this process is notably slow, and sometimes image clarity may be insufficient, making rapid and accurate identification challenging. This can be due… Read full abstract & cite →

Ascaris lumbricoides Convolutional Neural Networks OpenCV microscopic images moment-based detection

Abstract doi.org/10.14569/IJACSA.2024.0150590 PDF

91

Automatic Personality Recognition in Videos using Dynamic Networks and Rank Loss

Author 1: Nethravathi Periyapatna Sathyanarayana Author 2: Karuna Pandith Author 3: Manjula Sanjay Koti Author 4: Rajermani Thinakaran

There are a few difficulties with current automatic personality recognition technologies. Two of these are discussed in this article. They use of very brief video segments or individual frames to come to conclusion with personality factors rather than long-term behavior; and absence of techniques to record individuals' facial movements for… Read full abstract & cite →

Automatic personality recognition facial movements individual-specific representation personality factors convolutional neural networks

Abstract doi.org/10.14569/IJACSA.2024.0150591 PDF

92

Contrastive Learning and Multi-Choice Negative Sampling Recommendation

Author 1: Yun Xue Author 2: Xiaodong Cai Author 3: Sheng Fang Author 4: Li Zhou

Most existing recommendation models that directly model user interests on user-item interaction data usually ignore the natural noise present in the interaction data, leading to bias in the model's learning of user preferences during data propagation and aggregation. In addition, the currently adopted negative sampling strategy does not consider the… Read full abstract & cite →

Recommendation algorithms comparative learning negative sampling pruning strategies

Abstract doi.org/10.14569/IJACSA.2024.0150592 PDF

93

Development of Deep Learning Models for Traffic Sign Recognition in Autonomous Vehicles

Author 1: Zhadra Kozhamkulova Author 2: Zhanar Bidakhmet Author 3: Marina Vorogushina Author 4: Zhuldyz Tashenova Author 5: Bella Tussupova Author 6: Elmira Nurlybaeva Author 7: Dastan Kambarov

This research paper investigates the development of deep learning models for traffic sign recognition in autonomous vehicles. Leveraging convolutional neural networks (CNNs), the study explores various architectural configurations and evaluation methodologies to assess the efficacy of CNNs in accurately identifying and classifying traffic signs. Through a systematic evaluation process utilizing… Read full abstract & cite →

Traffic sign recognition machine learning deep learning computer vision image classification

Abstract doi.org/10.14569/IJACSA.2024.0150593 PDF

94

Enhanced U-Net Architecture for Lung Segmentation on Computed Tomography and X-Ray Images

Author 1: Gulnara Saimassay Author 2: Mels Begenov Author 3: Ualikhan Sadyk Author 4: Rashid Baimukashev Author 5: Askhat Maratov Author 6: Batyrkhan Omarov

In the expanding field of medical imaging, precise segmentation of anatomical structures is critical for accurate diagnosis and therapeutic interventions. This research paper introduces an innovative approach, building upon the established U-Net architecture, to enhance lung segmentation techniques applied to Computed Tomography (CT) images. Traditional methods of lung segmentation in… Read full abstract & cite →

Lung disease deep learning U-Net computed tomography segmentation diagnosis

Abstract doi.org/10.14569/IJACSA.2024.0150594 PDF

95

EfficientSkinCaSV2B3: An Efficient Framework Towards Improving Skin Classification and Segmentation

Author 1: Quy Lu Thanh Author 2: Triet Minh Nguyen

Ozone layer depletion has gained attention as a serious environmental issue. Because of its effects on human health especially skin cancer. Besides, Ultraviolet (UV) radiation is known to be a major risk factor for skin cancer. For instance, it can damage the DNA in skin cells leading to mutations that… Read full abstract & cite →

Skin cancer Convolutional Neural Network (CNN) transfer learning fine tuning classification segmentation EffecientNetB3V2

Abstract doi.org/10.14569/IJACSA.2024.0150595 PDF

96

Cross-Modal Fine-Grained Interaction Fusion in Fake News Detection

Author 1: Zhanbin Che Author 2: GuangBo Cui

The popularity of social media has significantly increased the speed and scope of news dissemination, making the emergence and spread of fake news easier. Current fake news detection methods often ignore the correlation between text and images, leading to insufficient modal interaction and fusion. To address these issues, a cross-modal… Read full abstract & cite →

Fake news detection attention mechanism multimodal feature fusion local similarity

Abstract doi.org/10.14569/IJACSA.2024.0150596 PDF

97

A Stepwise Discriminant Analysis and FBCSP Feature Selection Strategy for EEG MI Recognition

Author 1: YingHui Meng Author 2: YaRu Su Author 3: Duan Li Author 4: JiaoFen Nan Author 5: YongQuan Xia

Accurate decoding of brain intentions is a pivotal technology within Brain-Computer Interface (BCI) systems that rely on Motor Imagery (MI). The effective extraction of information features plays a critical role in the precise decoding of these brain intentions. However, there exists significant individual and environmental variability in signals, and the… Read full abstract & cite →

Stepwise discriminant analysis electroenceph alogram motor imagery sliding time window filter bank common spatial pattern

Abstract doi.org/10.14569/IJACSA.2024.0150597 PDF

98

Enhancing Sentiment Analysis on Social Media Data with Advanced Deep Learning Techniques

Author 1: Huu-Hoa Nguyen

This paper introduces a comprehensive methodology for conducting sentiment analysis on social media using advanced deep learning techniques to address the unique challenges of this domain. As digital platforms play an increasingly pivotal role in shaping public discourse, the demand for real-time sentiment analysis has expanded across various sectors, including… Read full abstract & cite →

Sentiment analysis deep learning hyperparameter feature extraction social media digital platform gridsearchcv BiLSTM TF-IDF word2vec glove Scikit-learn and Gensim

Abstract doi.org/10.14569/IJACSA.2024.0150598 PDF

99

An Integrated Generalized Linear Regression with Two Step-AS Algorithm for COVID-19 Detection

Author 1: Ahmed Hamza Osman Author 2: Hani Moetque Aljahdali Author 3: Sultan Menwer Altarrazi Author 4: Altyeb Taha

This research introduces a computer-aided intelligence model designed to automatically identify positive instances of COVID-19 for routine medical applications. The model, built on the Generalized Linear architecture, employs the TwoStep-AS cluster method with diverse screen relatives, Weight sharing and stripping characteristics automatically identify distinctive features in chest X-ray images. Unlike… Read full abstract & cite →

Generalized Linear model COVID-19 TwoStep-AS clustering X-ray images

Abstract doi.org/10.14569/IJACSA.2024.0150599 PDF

100

Local Path Planning of Mobile Robots Based on the Improved SAC Algorithm

Author 1: Ruihong Zhou Author 2: Caihong Li Author 3: Guosheng Zhang Author 4: Yaoyu Zhang Author 5: Jiajun Liu

This paper proposes a new EP-PER-SAC algorithm to solve the problems of slow training speed and low learning efficiency of the SAC (Soft Actor Critic) algorithm in the local path planning of mobile robots by introducing the Priority Experience Replay (PER) strategy and Experience Pool (EP) adjustment technique. This algorithm… Read full abstract & cite →

Mobile robots local path planning reinforcement learning SAC algorithm priority experience replay experience pool adjustment Robot Operating System (ROS)

Abstract doi.org/10.14569/IJACSA.2024.01505100 PDF

101

Exploring Music Style Transfer and Innovative Composition using Deep Learning Algorithms

Author 1: Sujie He

Automatic music generation represents a challenging task within the field of artificial intelligence, aiming to harness machine learning techniques to compose music that is appreciable by humans. In this context, we introduce a text-based music data representation method that bridges the gap for the application of large text-generation models in… Read full abstract & cite →

Deep learning style transfer innovative composition Generative Adversarial Networks

Abstract doi.org/10.14569/IJACSA.2024.01505101 PDF

102

Predictive Modeling of Yoga's Impact on Individuals with Venous Chronic Cerebrospinal System

Author 1: Sanjun Qiu

People leading a modern lifestyle often experience varicose veins, commonly attributed to factors associated with work and diet, such as prolonged periods of standing or excess weight. These disorders include elevated blood pressure in the lower extremities, especially the legs. An often-researched metric associated with these illnesses is the Vascular… Read full abstract & cite →

Yoga varicose veins Extra Tree Classification cheetah optimization algorithm Black Widow Optimizer

Abstract doi.org/10.14569/IJACSA.2024.01505102 PDF

103

Modified Artificial Bee Colony Algorithm for Load Balancing in Cloud Computing Environments

Author 1: Qian LI Author 2: Xue WANG

Task scheduling in cloud computing is a complex optimization problem influenced by the ever-changing user requirements and the different architectures of cloud systems. Efficiently distributing workloads across Virtual Machines (VMs) is critical to mitigate the negative consequences of inadequate and excessive workloads, such as higher power consumption and possible machine… Read full abstract & cite →

Resource utilization cloud computing task scheduling Artificial Bee Colony genetic algorithm

Abstract doi.org/10.14569/IJACSA.2024.01505103 PDF

104

Cloud Workload Prediction Based on Bayesian-Optimized Autoformer

Author 1: Biying Zhang Author 2: Yuling Huang Author 3: Zuoqiang Du Author 4: Zhimin Qiu

Accurate workload forecasting plays a pivotal role in the management of cloud computing resources, enabling significant enhancement in the performance of the cloud platform and effective prevention of resource wastage. However, the complexity, variability, and strong time dependencies of cloud workloads make prediction difficult. To address the challenge of enhancing… Read full abstract & cite →

Cloud computing deep learning workload prediction Autoformer Bayesian optimization

Abstract doi.org/10.14569/IJACSA.2024.01505104 PDF

105

A Systematic Review on Multi-Factor Authentication Framework

Author 1: Muhammad Syahreen Author 2: Noor Hafizah Author 3: Nurazean Maarop Author 4: Mayasarah Maslinan

In the new era of technology, where information can be accessed and gained at the push of a button, security concerns are raised about protecting the system and data privacy and confidentiality. Traditional ways of user authentication are vulnerable to multiple attacks across all platforms. Various studies propose the use… Read full abstract & cite →

Data privacy information multi-factor authentication security challenges

Abstract doi.org/10.14569/IJACSA.2024.01505105 PDF

106

Improved SegNet with Hybrid Classifier for Lung Cancer Segmentation and Classification

Author 1: Rathod Dharmesh Ishwerlal Author 2: Reshu Agarwal Author 3: K.S. Sujatha

Prompt diagnosis is crucial globally to save lives, underscoring the urgent need in light of lung cancer's status as a leading cause of death. While CT scans serve as a primary imaging tool for LC detection, manual analysis is laborious and prone to inaccuracies. Recognizing these challenges, computational techniques, particularly… Read full abstract & cite →

Improved SegNet LGXP MBN LSTM LinkNet lung cancer

Abstract doi.org/10.14569/IJACSA.2024.01505106 PDF

107

New 3D Shape Descriptor Extraction using CatBoost Classifier for Accurate 3D Model Retrieval

Author 1: Mohcine BOUKSIM Author 2: Fatima RAFII ZAKANI Author 3: Khadija ARHID Author 4: Azzeddine DAHBI Author 5: Taoufiq GADI Author 6: Mohamed ABOULFATAH

Given the wide application of 3D model analysis, covering domains such as medicine, engineering, and virtual reality, the demand for innovative content-based 3D shape retrieval systems capable of handling complex 3D data efficiently have significantly increased. This paper proposes a new 3D shape retrieval method that uses the CatBoost classifier… Read full abstract & cite →

3D object retrieval 3D shape retrieval 3D shape matching indexing descriptor CatBoost

Abstract doi.org/10.14569/IJACSA.2024.01505107 PDF

108

YOLO-T: Multi-Target Detection Algorithm for Transmission Lines

Author 1: Shengwen Li Author 2: Huabing Ouyang Author 3: Tian Chen Author 4: Xiaokang Lu Author 5: Zhendong Zhao

During UAV inspections of transmission lines, inspectors often encounter long distance and obstructed targets. However, existing detection algorithms tend to be less accurate when trying to detect these targets. Existing algorithms perform inadequately in handling long-distance and occluded targets, lacking effective detection capabilities for small objects and complex backgrounds. Therefore… Read full abstract & cite →

Transmission line inspection contextual transformer attention mechanism ghost convolution

Abstract doi.org/10.14569/IJACSA.2024.01505108 PDF

109

Identifying Competition Characteristics of Athletes Through Video Analysis

Author 1: Yuzhong Liu Author 2: Tianfan Zhang Author 3: Zhe Li Author 4: Mengshuang Ma

The vast repositories of training and competition video data serve as indispensable resources for athlete training and competitor analysis, providing a solid foundation for strategic competition analysis and tactics formulation. However, the effectiveness of these analyses hinges on the abundance and precision of data, often requiring costly professional systems for… Read full abstract & cite →

Video analysis technology scene recognition method athlete identification posture reconstruction table tennis competition feature extraction

Abstract doi.org/10.14569/IJACSA.2024.01505109 PDF

110

Differential Diagnosis of Attention-Deficit/Hyperactivity Disorder and Bipolar Disorder using Steady-State Visual Evoked Potentials

Author 1: Xiaoxia Li

Bipolar disorder and Attention-deficit/Hyperactivity disorder (ADHD) are two prevalent disorders whose symptoms are similar. In order to reduce the misdiagnosis between bipolar disorder and ADHD, a machine learning-based system using electroencephalography (EEG) and steady state potentials (i.e., steady-state visual evoked potential [SSVEP]) was evaluated to classify ADHD, bipolar disorder and… Read full abstract & cite →

Attention-deficit/Hyperactivity disorder (ADHD) bipolar disorder electroencephalography (EEG) steady-state visual evoked potential (SSVEP) machine learning classification

Abstract doi.org/10.14569/IJACSA.2024.01505110 PDF

111

Exploring Cutting-Edge Developments in Deep Learning for Biomedical Signal Processing

Author 1: Yukun Zhu Author 2: Haiyan Zhang Author 3: Bing Liu Author 4: Junyan Dou

Biomedical condition monitoring devices are progressing quickly by incorporating cost-effective and non-invasive sensors to track vital signs, record medical circumstances, and deliver meaningful responses. These sophisticated innovations rely on breakthrough technology to provide intelligent platforms for health monitoring, quick illness recognition, and precise treatment. Biomedical signal processing determines patterns of… Read full abstract & cite →

Biomedical signal processing health monitoring deep learning electrocardiography electromyography electroencephalography

Abstract doi.org/10.14569/IJACSA.2024.01505111 PDF

112

The Performance of a Temporal Multi-Modal Sentiment Analysis Model Based on Multitask Learning in Social Networks

Author 1: Lin He Author 2: Haili Lu

When conducting sentiment analysis on social networks, facing the challenge of temporal and multi-modal data, it is necessary to enable the model to deeply mine and combine information from various modalities. Therefore, this study constructs an emotion analysis model based on multitask learning. This model utilizes a comprehensive framework of… Read full abstract & cite →

Multi task learning multi-modal emotional analysis attention mechanism feature fusion

Abstract doi.org/10.14569/IJACSA.2024.01505112 PDF

113

Weighted Recursive Graph Color Coding for Enhanced Load Identification

Author 1: Li Zhang Author 2: Hengtao Ai Author 3: Yuhang Liu Author 4: Shiqing Li Author 5: Tao Zhang

In the pursuit of high-precision load identification, traditional methodologies grapple with significant drawbacks, including low recognition rates, intricate signature construction, and narrow applicability. This study introduces a novel approach employing weighted recursive graph (WRG) color coding to surmount these challenges. Power consumption data, procured from advanced load monitoring devices, undergo… Read full abstract & cite →

Non-Intrusive Load Monitoring (NILM) Weighted Recurrence Graph (WRG) color coding AlexNet neural network load signature

Abstract doi.org/10.14569/IJACSA.2024.01505113 PDF

114

Diagnosis of NEC using a Multi-Feature Fusion Machine Learning Algorithm

Author 1: Jiahe Li Author 2: Yue Han Author 3: Yunzhou Li Author 4: Jin Zhang Author 5: Ling He Author 6: Tao Xiong Author 7: Qian Gao

Necrotizing enterocolitis (NEC) is a severe gastrointestinal emergency in neonates, marked by its complex etiology, ambiguous clinical manifestations, and significant morbidity and mortality, profoundly affecting long-term pediatric health outcomes. The prevailing diagnostic approaches for NEC, including traditional manual auscultation of bowel sounds, suffer from limited sensitivity and specificity, leading to… Read full abstract & cite →

Diagnosis of necrotizing enterocolitis (NEC) bowel sound feature fusion machine learning

Abstract doi.org/10.14569/IJACSA.2024.01505114 PDF

115

Towards Optimal Image Processing-based Internet of Things Monitoring Approaches for Sustainable Cities

Author 1: Weiwei LIU Author 2: Guifeng CHEN

Population growth and urbanization demand innovative strategies for sustainable city management. This paper focuses on the integration of the Internet of Things (IoT) and image processing technologies for environmental monitoring in sustainable urban development. The IoT forms an integral part of the Information and Communication Technology (ICT) infrastructure in smart… Read full abstract & cite →

Sustainable cities Internet of Things image processing urban monitoring smart city

Abstract doi.org/10.14569/IJACSA.2024.01505115 PDF

116

Exploring Enhanced Object Detection and Classification Methods for Alstroemeria Genus Morado

Author 1: Yaru Huang Author 2: Yangxu Wang

As an important ornamental plant, the automatic detection and classification of the maturity of Alstroemeria Genus Morado flowers hold significant importance in precision agriculture. However, this task faces numerous challenges due to the diversity of morphological characteristics, complex growth environments, and factors such as occlusion and lighting variations. Currently, this… Read full abstract & cite →

Alstroemeria object detection maturity classification multi-scale feature fusion Convolutional Neural Network (CNN)

Abstract doi.org/10.14569/IJACSA.2024.01505116 PDF

117

Enhanced Arachnid Swarm-Tuned Convolutional Neural Network Model for Efficient Intrusion Detection

Author 1: Nishit Patil Author 2: Shubhlaxmi Joshi

Digital systems in the connected world of today bring convenience but also complicated cyber security challenges. The inadequacies of conventional intrusion detection techniques are exposed by the constant adaptation and exploitation of vulnerabilities by advanced cyber threats. Identifying dangers in massive data flows gets more difficult as networks grow, necessitating… Read full abstract & cite →

Intrusion Detection arachnid swarm optimization Convolutional Neural Network pre-processing arachnid swarm optimization

Abstract doi.org/10.14569/IJACSA.2024.01505117 PDF

118

Elevating Offensive Language Detection: CNN-GRU and BERT for Enhanced Hate Speech Identification

Author 1: M. Madhavi Author 2: Sanjay Agal Author 3: Niyati Dhirubhai Odedra Author 4: Harish Chowdhary Author 5: Taranpreet Singh Ruprah Author 6: Veera Ankalu Vuyyuru Author 7: Yousef A.Baker El-Ebiary

Upholding a secure and accepting digital environment is severely hindered by hate speech and inappropriate information on the internet. A novel approach that combines Convolutional Neural Network with GRU and BERT from Transformers proposed for enhancing the identification of offensive content, particularly hate speech. The method utilizes the strengths of… Read full abstract & cite →

Bidirectional encoder representations from transformers convolutional neural network Gated Recurrent Unit hate speech hugging face transformer

Abstract doi.org/10.14569/IJACSA.2024.01505118 PDF

119

Optimizing Resource Allocation in Cloud Environments using Fruit Fly Optimization and Convolutional Neural Networks

Author 1: Taviti Naidu Gongada Author 2: Girish Bhagwant Desale Author 3: Shamrao Parashram Ghodake Author 4: K. Sridharan Author 5: Vuda Sreenivasa Rao Author 6: Yousef A.Baker El-Ebiary

Cloud computing environments play a crucial role in modern computing infrastructures, offering scalability, flexibility, and cost-efficiency. However, optimizing resource utilization and performance in such dynamic and complex environments remains a significant challenge. This study addresses this challenge by proposing a novel framework that integrates Fruit Fly Optimization (FFO) with Convolutional… Read full abstract & cite →

Cloud computing resource utilization task scheduling Fruit Fly Optimization convolutional neural networks

Abstract doi.org/10.14569/IJACSA.2024.01505119 PDF

120

Explainable Artificial Intelligence Method for Identifying Cardiovascular Disease with a Combination CNN-XG-Boost Framework

Author 1: J Chandra Sekhar Author 2: T L Deepika Roy Author 3: K. Sridharan Author 4: Natrayan L Author 5: Dr.K.Aanandha Saravanan Author 6: Ahmed I. Taloba

Cardiovascular disease (CVD) is a globally significant health issue that presents with a multitude of risk factors and complex physiology, making early detection, avoidance, and effective management a challenge. Early detection is essential for effective treatment of CVD, and typical approaches involve an integrated strategy that includes lifestyle modifications like… Read full abstract & cite →

Cardiovascular disease CNN XGBoost traditional approaches explainable AI

Abstract doi.org/10.14569/IJACSA.2024.01505120 PDF

121

Utilizing Machine Learning Approach to Forecast Fuel Consumption of Backhoe Loader Equipment

Author 1: Poonam Katyare Author 2: Shubhalaxmi Joshi Author 3: Mrudula Kulkarni

This study addresses the challenge of forecasting fuel consumption for various categories of construction equipment, with a specific focus on Backhoe Loaders (BL). Accurate predictions of fuel usage are crucial for optimizing operational efficiency in the increasingly technology-driven construction industry. The proposed methodology involves the application of multiple machine learning… Read full abstract & cite →

Machine learning construction equipment fuel consumption

Abstract doi.org/10.14569/IJACSA.2024.01505121 PDF

122

Image Generation of Animation Drawing Robot Based on Knowledge Distillation and Semantic Constraints

Author 1: Dujuan Wang

With the development of robot technology, animation drawing robots have gradually appeared in the public eye. Animation drawing robots can generate many types of images, but there are also problems such as poor quality of generated images and long image drawing time. In order to improve the quality of images… Read full abstract & cite →

Knowledge distillation semantic constraints robot image generation

Abstract doi.org/10.14569/IJACSA.2024.01505122 PDF

123

Integrating AI and IoT in Advanced Optical Systems for Sustainable Energy and Environment Monitoring

Author 1: Shamim Ahmad Khan Author 2: Abdul Hameed Kalifullah Author 3: Kamila Ibragimova Author 4: Akhilesh Kumar Singh Author 5: Elangovan Muniyandy Author 6: Venubabu Rachapudi

The increasing demand for sustainable energy solutions and environmental monitoring necessitates advanced technologies. This work combines the capabilities of AI, in the form of a GRU-Auto encoder, with IoT-connected Advanced Optical Systems to create a comprehensive monitoring system. Current monitoring systems often face limitations in real-time analysis and adaptability. Conventional… Read full abstract & cite →

Auto encoder artificial intelligence Internet of Things gated recurrent unit sustainable energy environmental monitoring

Abstract doi.org/10.14569/IJACSA.2024.01505123 PDF

124

NLP-Based Automatic Summarization using Bidirectional Encoder Representations from Transformers-Long Short Term Memory Hybrid Model: Enhancing Text Compression

Author 1: Ranju S Kartha Author 2: Sanjay Agal Author 3: Niyati Dhirubhai Odedra Author 4: Ch Sudipta Kishore Nanda Author 5: Vuda Sreenivasa Rao Author 6: Annaji M Kuthe Author 7: Ahmed I. Taloba

When the amount of online text data continues to grow, the need for summarized text documents becomes increasingly important. Manually summarizing lengthy articles and determining the domain of the content is a time-consuming and tiresome process for humans. Modern technology can classify large amounts of text documents, identifying key phrases… Read full abstract & cite →

Automated text compression BERT-based extractive summarization LSTM-based abstractive summarization NLP-based hybrid approach Particle Swarm Optimization

Abstract doi.org/10.14569/IJACSA.2024.01505124 PDF

125

The Impact of Various Factors on the Convolutional Neural Networks Model on Arabic Handwritten Character Recognition

Author 1: Alhag Alsayed Author 2: Chunlin Li Author 3: Ahmed Fat’hAlalim Author 4: Mohammed Hafiz Author 5: Jihad Mohamed Author 6: Zainab Obied Author 7: Mohammed Abdalsalam

Recognizing Arabic handwritten characters (AHCR) poses a significant challenge due to the intricate and variable nature of the Arabic script. However, recent advancements in machine learning, particularly through Convolutional Neural Networks (CNNs), have demonstrated promising outcomes in accurately identifying and categorizing these characters. While numerous studies have explored languages like… Read full abstract & cite →

Arabic Handwritten Character Recognition (AHCR) Optical Character Recognition (OCR) Deep Learning (DL) Convolutional Neural Network (CNN) Characters Recognition (CR)

Abstract doi.org/10.14569/IJACSA.2024.01505125 PDF

126

Revolutionary AI-Driven Skeletal Fingerprinting for Remote Individual Identification

Author 1: Achraf BERRAJAA Author 2: Ayyoub El OUTMANI Author 3: Issam BERRAJAA Author 4: Nourddin SAIDOU

This research aims to devise a distinct mathematical key for individual identification and recognition. This key, represented through signals, is constructed using Lagrange polynomials derived from the skeletal points. Consequently, we present this key as a novel fingerprint categorized within physiological fingerprints. It’s crucial to highlight that the primary application… Read full abstract & cite →

Artificial intelligence recognition of individuals new fingerprint lagrange polynomials CNN

Abstract doi.org/10.14569/IJACSA.2024.01505126 PDF

127

Deep Learning Enhanced Hand Gesture Recognition for Efficient Drone use in Agriculture

Author 1: Phaitoon Srinil Author 2: Pattharaporn Thongnim

The use of deep learning in unmanned aerial vehicles (UAVs), or drones, has greatly improved various technologies by making complex tasks easier, faster, and requiring less human help. This study looks into how artificial intelligence (AI) can be used in farming, especially through creating a system where drones can be… Read full abstract & cite →

Deep learning Convolutional Neural Network hand gesture recognition drone agriculture

Abstract doi.org/10.14569/IJACSA.2024.01505127 PDF

128

Inclusive Smart Cities: IoT-Cloud Solutions for Enhanced Energy Analytics and Safety

Author 1: Abdulwahab Ali Almazroi Author 2: Faisal S. Alsubaei Author 3: Nasir Ayub Author 4: Noor Zaman Jhanjhi

Securing smart cities in the evolving Internet of Things (IoT) demands innovative security solutions that extend beyond conventional theft detection. This study introduces temporal convolutional networks and gated recurrent units (TCGR), a pioneering model tailored for the dynamic IoT-SM dataset, addressing eight distinct forms of theft. In contrast to conventional… Read full abstract & cite →

IoT Security theft detection smart cities cloud computing disability support

Abstract doi.org/10.14569/IJACSA.2024.01505128 PDF

129

Enhancing Diabetes Prediction: An Improved Boosting Algorithm for Diabetes Prediction

Author 1: Md. Shahin Alam Author 2: Most. Jannatul Ferdous Author 3: Nishat Sarkar Neera

Diabetes is increasing gradually due to the inability to effectively use the human body’s insulin, which threatens public health. People with diabetes who go undiagnosed at early stages or who have diabetes have a high risk of heart disease, kidney disease, eye problems, stroke, and nerve damage for which diabetes… Read full abstract & cite →

Diabetes prediction ensemble technique machine learning binary classification Moderated-AdaBoost

Abstract doi.org/10.14569/IJACSA.2024.01505129 PDF

130

Adaptive Learning Model for Detecting Wheat Diseases

Author 1: Mohammed Abdalla Author 2: Osama Mohamed Author 3: Elshaimaa M. Azmi

Nowadays, the wheat plant has been considered a crucial source of protein, energy, and micronutrients for people. The motivation behind this study comes from how to increase the wheat crop growth and prevent wheat diseases as this plant plays a significant impact on food security all over the world. Wheat… Read full abstract & cite →

Food security image recognition deep learning conventional neural networks digital agriculture agriculture sustainability

Abstract doi.org/10.14569/IJACSA.2024.01505130 PDF

131

Detecting Digital Image Forgeries with Copy-Move and Splicing Image Analysis using Deep Learning Techniques

Author 1: Divya Prathana Timothy Author 2: Ajit Kumar Santra

The proliferation of digitally altered images across social media platforms has escalated the urgency for robust image forgery detection systems. Traditional detection methodologies, while varied, often fall short in addressing the multifaceted nature of image forgeries in the digital landscape. Recognizing the need for advanced solutions, this paper introduces a… Read full abstract & cite →

Copy-move splicing deep learning image forgery detection

Abstract doi.org/10.14569/IJACSA.2024.01505131 PDF

132

An Improved Facial Expression Recognition using CNN-BiLSTM with Attention Mechanism

Author 1: Samanthisvaran Jayaraman Author 2: Anand Mahendran

In the recent years, Facial Expression Recognition is one of the hot research topics among the researchers and experts in the field of Computer Vision and Human Computer Interaction. Traditional deep learning models have found it difficult to process images that has occlusion, illumination and pose dimensional properties, and also… Read full abstract & cite →

Facial expression recognition occlusion attention mechanism convolution neural networks bidirectional long short time memory

Abstract doi.org/10.14569/IJACSA.2024.01505132 PDF

133

A Survey of Reversible Data Hiding in Encrypted Images

Author 1: Ghadeer Asiri Author 2: Atef Masmoudi

The creation and application of multimedia has undergone a revolution in the last several years. This is a result of the rise in internet-based communications, which involves the exchange of digital data in the forms of text files, audio files, video files, and image files. For this reason, multimedia has… Read full abstract & cite →

Reversible data hiding encrypted image

Abstract doi.org/10.14569/IJACSA.2024.01505133 PDF

134

HybridGCN: An Integrative Model for Scalable Recommender Systems with Knowledge Graph and Graph Neural Networks

Author 1: Dang-Anh-Khoa Nguyen Author 2: Sang Kha Author 3: Thanh-Van Le

Graph Neural Networks (GNNs) have emerged as a state-of-the-art approach in building modern Recommender Systems (RS). By leveraging the complex relationships among items, users, and their attributes, which can be represented as a Knowledge Graph (KG), these models can explore implicit semantic sub-structures within graphs, thereby enhancing the learning of… Read full abstract & cite →

Large-scale dataset processing recommender systems graph neural network knowledge graph construction data segmentation

Abstract doi.org/10.14569/IJACSA.2024.01505134 PDF

135

Transformer Meets External Context: A Novel Approach to Enhance Neural Machine Translation

Author 1: Mohammed Alsuhaibani Author 2: Kamel Gaanoun Author 3: Ali Alsohaibani

Most neural machine translation (NMT) systems rely on parallel data, comprising text in the source language and its corresponding translation in the target language. While it’s acknowledged that context enhances NMT models, this work proposes a novel approach by incorporating external context, specifically explanations of source text meanings, akin to… Read full abstract & cite →

Deep learning transformers context NMT neural machine translation natural language processing systems

Abstract doi.org/10.14569/IJACSA.2024.01505135 PDF

136

Mitigating Security Risks in Firewalls and Web Applications using Vulnerability Assessment and Penetration Testing (VAPT)

Author 1: Alanoud Alquwayzani Author 2: Rawabi Aldossri Author 3: Mounir Frikha

In today’s digital age, both organizations and individuals heavily depend on web applications for a wide range of activities. However, this reliance on the web also opens up opportunities for attackers to exploit security weaknesses present in these applications. Web Application Firewalls (WAFs) are typically the first line of defense… Read full abstract & cite →

Web Application Firewalls (WAFs) Vulnerability Assessment and Penetration Testing (VAPT) cybersecurity security vulnerabilities security misconfigurations network scanning tools vulnerability detection

Abstract doi.org/10.14569/IJACSA.2024.01505136 PDF

137

A Deep Learning Approach to Convert Handwritten Arabic Text to Digital Form

Author 1: Bayan N. Alshahrani Author 2: Wael Y. Alghamdi

The recognition of Arabic words presents considerable difficulties owing to the complex characteristics of the Arabic script, which encompasses letters positioned both above and below the baseline, hamzas, and dots. In order to address these intricacies, we provide a structured approach for transforming handwritten Arabic text into a digital format… Read full abstract & cite →

Deep learning convolutional neural networks bidirectional long short term memory connectional temporal classification Arabic handwriting recognition

Abstract doi.org/10.14569/IJACSA.2024.01505137 PDF

138

User-Friendly Privacy-Preserving Blockchain-based Data Trading

Author 1: Jiahui Cao Author 2: Junyao Ye Author 3: Junzuo Lai

As the digital economy flourishes, the use of blockchain technology for data trading has seen a surge in popularity. Yet, previous approaches have frequently faltered in harmonizing security with user experience, culminating in suboptimal transactional efficiency. This study introduces a personalized local differential privacy framework, adeptly tackling data security concerns… Read full abstract & cite →

Data trading blockchain personalized local differential privacy data security user-friendly

Abstract doi.org/10.14569/IJACSA.2024.01505138 PDF

139

AEGANB3: An Efficient Framework with Self-attention Mechanism and Deep Convolutional Generative Adversarial Network for Breast Cancer Classification

Author 1: Huong Hoang Luong Author 2: Hai Thanh Nguyen Author 3: Nguyen Thai-Nghe

Breast cancer remains a significant illness around the world, but it has become the most dangerous when faced with women. Early detection is paramount in improving prognosis and treatment. Thus, ultrasonography has appeared as a valuable diagnostic tool for breast cancer. However, the accurate interpretation of ultrasound images requires expertise… Read full abstract & cite →

Breast cancer classification Convolutional Neural Network (CNN) Vision Transformer (ViT) fine-tuning transfer learning self-attention

Abstract doi.org/10.14569/IJACSA.2024.01505139 PDF

140

An Optimal Knowledge Distillation for Formulating an Effective Defense Model Against Membership Inference Attacks

Author 1: Thi Thanh Thuy Pham Author 2: Huong-Giang Doan

A membership inference attack (MIA) on machine learning models aims to determine the sensitive data that has been used to train machine learning models. Machine learning-based applications (MLaaS—machine learning as a service) in finance, banking, healthcare, etc. are facing the risks of private data leaks by MIA. Several solutions have… Read full abstract & cite →

Knowledge distillation membership inference attack teacher model student model privacy-utility trade-off

Abstract doi.org/10.14569/IJACSA.2024.01505140 PDF

141

Audio Watermarking: A Comprehensive Review

Author 1: Mohammad Shorif Uddin Author 2: Ohidujjaman Author 3: Mahmudul Hasan Author 4: Tetsuya Shimamura

Audio watermarking has emerged as a potent technology for copyright protection, content authentication, content monitoring, and tracking in the digital age. This paper offers a comprehensive exploration of audio watermarking principles, techniques, applications, and challenges. Initially, it presents the fundamental concepts of digital watermarking, elucidating its key characteristics and functionalities… Read full abstract & cite →

Audio watermarking deep learning approach spread-spectrum method signal-processing attacks time domain transform domain

Abstract doi.org/10.14569/IJACSA.2024.01505141 PDF

142

ACNGCNN: Improving Efficiency of Breast Cancer Detection and Progression using Adversarial Capsule Network with Graph Convolutional Neural Networks

Author 1: Srinivasa Rao Pallapu Author 2: Khasim Syed

New diagnostic methods are needed to improve the accuracy and efficiency of breast cancer detection and progression. Although successful, current methods frequently lack precision, accuracy, and timeliness, especially in the early phases Of breast cancer progression. Our research proposes a new model using deep learning to improve breast cancer detection… Read full abstract & cite →

Breast cancer detection deep learning image pre-possessing disease progression recurrent neural networks

Abstract doi.org/10.14569/IJACSA.2024.01505142 PDF

143

Securing Networks: An In-Depth Analysis of Intrusion Detection using Machine Learning and Model Explanations

Author 1: Hoang-Tu Vo Author 2: Nhon Nguyen Thien Author 3: Kheo Chau Mui Author 4: Phuc Pham Tien

As cyber threats continue to evolve in complexity, the need for robust intrusion detection systems (IDS) becomes increasingly critical. Machine learning (ML) models have demon-strated their effectiveness in detecting anomalies and potential intrusions. In this article, we delve into the world of intrusion detection by exploring the application of four… Read full abstract & cite →

Intrusion detection systems machine learning models model interpretability cybersecurity LIME SHAP explain-able machine learning models

Abstract doi.org/10.14569/IJACSA.2024.01505143 PDF

144

Log Clustering-based Method for Repairing Missing Traces with Context Probability Information

Author 1: Huan Fang Author 2: Wenjie Su

In real business processes, low quality event logs due to outliers and missing values tend to degrade the performance of process mining related algorithms, which in turn affects the correct execution of decisions. In order to repair the missing values in event logs under the condition that the reference model… Read full abstract & cite →

Trace clustering log repairing process mining context semantics conditional probability

Abstract doi.org/10.14569/IJACSA.2024.01505144 PDF