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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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IJACSA Vol. 15 Issue 4 (2024)

Open Access | | 128 papers

Copyright Statement: This is an open access publication licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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1

A Comparative Analysis of Traditional and Machine Learning Methods in Forecasting the Stock Markets of China and the US

Author 1: Shangshang Jin

In the volatile and uncertain financial markets of the post-COVID-19 era, our study conducts a comparative analysis of traditional econometric models—specifically, the AutoRegressive Integrated Moving Average (ARIMA) and Holt's Linear Exponential Smoothing (Holt's LES)—against advanced machine learning techniques, including Support Vector Regression (SVR), Long Short-Term Memory (LSTM) networks, and Gated… Read full abstract & cite →

Machine learning Holt's LES SVR LSTM GRU
Abstract doi.org/10.14569/IJACSA.2024.0150401 PDF
2

Classification of Thoracic Abnormalities from Chest X-Ray Images with Deep Learning

Author 1: Usman Nawaz Author 2: Muhammad Ummar Ashraf Author 3: Muhammad Junaid Iqbal Author 4: Muhammad Asaf Author 5: Mariam Munsif Mir Author 6: Usman Ahmed Raza Author 7: Bilal Sharif

Most Chest X-Rays (CXRs) are used to spot the existence of chest diseases by radiologists worldwide. Examining multiple X-rays at the busiest medical facility may result in time and financial loss. Furthermore, in the detection of the disease, expert abilities and attention are needed. CXRs are usually used for the… Read full abstract & cite →

Localization classification ensemble learning YOLOV5 VINBigData thoracic abnormalities deep learning
Abstract doi.org/10.14569/IJACSA.2024.0150402 PDF
3

Assisted Requirements Selection by Clustering using an Analytical Hierarchical Process

Author 1: Shehzadi Nazeeha Saleem Author 2: Linda Mohaisen

This research investigates the fusion of the Analytic Hierarchy Process (AHP) with clustering techniques to enhance project outcomes. Two quantitative datasets comprising 20 and 100 software requirements are analyzed. A novel AHP dataset is developed to impartially evaluate clustering strategies. Five clustering algorithms (K-means, Hierarchical, PAM, GMM, BIRCH) are employed… Read full abstract & cite →

Requirements prioritization next release plan software product planning decision support MoSCoW AHP k-Means GMM BIRCH PAM hierarchical clustering clusters evaluation
Abstract doi.org/10.14569/IJACSA.2024.0150403 PDF
4

Comparative Analysis of Telemedicine in Media Coverage Pre- and Post-COVID-19 using Unsupervised Latent Dirichlet Topic Modeling

Author 1: Haewon Byeon

Telemedicine, driven by technology, has become a game-changer in healthcare, with the COVID-19 pandemic amplifying its significance by necessitating remote healthcare solutions. This study explores the evolution of telemedicine through news big data analysis. Our research encompassed a vast dataset from 51 media outlets (total 28,372 articles), including national and… Read full abstract & cite →

Telemedicine COVID-19 medical law healthcare transformation LDA topic modeling
Abstract doi.org/10.14569/IJACSA.2024.0150404 PDF
5

Distributed Optimization Scheduling Consistency Algorithm for Smart Grid and its Application in Cost Control of Power Grid

Author 1: Lihua Shang Author 2: Meijiao Sun Author 3: Cheng Pan Author 4: Xiaoqiang San

There are problems such as low scalability and low convergence accuracy in the economic dispatch of smart grids. To address these situations, this study considers various constraints such as supply-demand balance constraints, climb constraints, and capacity constraints based on the unified consensus algorithm of multi-agent systems. By using Lagrange duality… Read full abstract & cite →

Distributed consistency algorithm convex optimization economic dispatch smart grid
Abstract doi.org/10.14569/IJACSA.2024.0150405 PDF
6

Evaluating the Accuracy of Cloud-based 3D Human Pose Estimation Tools: A Case Study of MOTiO by RADiCAL

Author 1: Hamza Khalloufi Author 2: Mohamed Zaifri Author 3: Abdessamad Benlahbib Author 4: Fatima Zahra Kaghat Author 5: Ahmed Azough

The use of 3D Human Pose Estimation (HPE) has become increasingly popular in the field of computer vision due to its various applications in human-computer interaction, animation, surveillance, virtual reality, video interpretation, and gesture recognition. However, traditional sensor-based motion capture systems are limited by their high cost and the need… Read full abstract & cite →

3D human pose estimation animation evaluation motion tracking
Abstract doi.org/10.14569/IJACSA.2024.0150406 PDF
7

Optimizing Student Performance Prediction: A Data Mining Approach with MLPC Model and Metaheuristic Algorithm

Author 1: Qing Hai Author 2: Changshou Wang

Given the information stored in educational databases, automated achievement of the learner’s prediction is essential. The field of educational data mining (EDM) is handling this task. EDM creates techniques for locating data gathered from educational settings. These techniques are applied to comprehend students and the environment in which they learn… Read full abstract & cite →

Educational data mining multilayer perceptron classification pelican optimization algorithm crystal structure algorithm student performance
Abstract doi.org/10.14569/IJACSA.2024.0150407 PDF
8

DUF-Net: A Retinal Vessel Segmentation Method Integrating Global and Local Features with Skeleton Fitting Assistance

Author 1: Xuelin Xu Author 2: Ren Lin Author 3: Jianwei Chen Author 4: Huabin He

Assisted evaluation through retinal vessel segmentation facilitates the early prevention and diagnosis of retinal lesions. To address the scarcity of medical samples, current research commonly employs image patching techniques to augment the training dataset. However, the vascular features in fundus images exhibit complex distribution, patch-based methods frequently encounter the challenge… Read full abstract & cite →

Fundus image vessel segmentation skeleton fitting data augmentation patch classification
Abstract doi.org/10.14569/IJACSA.2024.0150408 PDF
9

Novel Approaches for Access Level Modelling of Employees in an Organization Through Machine Learning

Author 1: Priyanka C Hiremath Author 2: Raju G T

In the contemporary business landscape, organizational trustworthiness is of utmost importance. Employee behavior, a pivotal aspect of trustworthiness, undergoes analysis and prediction through data science methodologies. Simultaneously, effective control over employee access within an organization is imperative for security and privacy assurance. This research proposes an innovative approach to model… Read full abstract & cite →

Access control machine learning employee behavior modeling data analysis organizational performance
Abstract doi.org/10.14569/IJACSA.2024.0150409 PDF
10

Predicting Optimal Learning Approaches for Nursing Students in Morocco

Author 1: Samira Fadili Author 2: Merouane Ertel Author 3: Aziz Mengad Author 4: Said Amali

In nursing education, recognizing and accommodating diverse learning styles is imperative for the development of effective educational programs and the success of nursing students. This article addresses the crucial challenge of classifying the learning styles of nursing students in Morocco, where contextual studies are limited. To address this research gap… Read full abstract & cite →

Learning styles nursing students predictive modeling classification personalized education
Abstract doi.org/10.14569/IJACSA.2024.0150410 PDF
11

Automated Weeding Systems for Weed Detection and Removal in Garlic / Ginger Fields

Author 1: Tsubasa Nakabayashi Author 2: Kohei Yamagishi Author 3: Tsuyoshi Suzuki

The global agriculture industry has faced various problems, such as rapid population growth and climate change. Among several countries, Japan has a declining agricultural workforce. To solve this problem, the Japanese government aims to realize “Smart agriculture” that applies information and communication technology, artificial intelligence, and robotics. Smart agriculture requires… Read full abstract & cite →

Weed detection weeding mask R-CNN agriculture robot
Abstract doi.org/10.14569/IJACSA.2024.0150411 PDF
12

Enhancing Building Energy Efficiency: A Hybrid Meta-Heuristic Approach for Cooling Load Prediction

Author 1: Chenguang Wang Author 2: Yanjie Zhou Author 3: Libin Deng Author 4: Ping Xiong Author 5: Jiarui Zhang Author 6: Jiamin Deng Author 7: Zili Lei

The research tackles the complex problem of accurately predicting cooling loads in the context of energy efficiency and building management. It presents a novel approach that increases the precision of cooling load forecasts by utilizing machine learning (ML). The main objective is to incorporate a hybridization strategy into Radial Basis… Read full abstract & cite →

Building energy cooling load machine learning radial basis function self-adaptive bonobo optimizer differential squirrel search algorithm
Abstract doi.org/10.14569/IJACSA.2024.0150412 PDF
13

Securing IoT Environment by Deploying Federated Deep Learning Models

Author 1: Saleh Alghamdi Author 2: Aiiad Albeshri

The vast network of interconnected devices, known as the Internet of Things (IoT), produces significant volumes of data and is vulnerable to security threats. The proliferation of IoT protocols has resulted in numerous zero-day attacks, which traditional machine learning systems struggle to detect due to IoT networks' complexity and the… Read full abstract & cite →

Internet of Things (IoT) security breaches machine learning Deep Learning (DL)
Abstract doi.org/10.14569/IJACSA.2024.0150413 PDF
14

Review and Analysis of Financial Market Movements: Google Stock Case Study

Author 1: Yiming LU

A financial marketplace where shares of companies with public listings are bought and sold is called the stock market. It serves as a gauge of a nation's economic health by taking into account the operations of individual businesses as well as the general business climate. The relationship between supply and… Read full abstract & cite →

Stock future trend financial market investment machine learning algorithms Google stock
Abstract doi.org/10.14569/IJACSA.2024.0150414 PDF
15

Prediction of Financial Markets Utilizing an Innovatively Optimized Hybrid Model: A Case Study of the Hang Seng Index

Author 1: Xiaopeng YANG

Stock trading is a highly consequential and frequently discussed subject in the realm of financial markets. Due to the volatile and unpredictable nature of stock prices, investors are perpetually seeking methods to forecast future trends in order to minimize losses and maximize profits. Nevertheless, despite the ongoing investigation of various… Read full abstract & cite →

Financial markets stock future trend Hang Seng Index Gated Recurrent Units Aquila Optimizer
Abstract doi.org/10.14569/IJACSA.2024.0150415 PDF
16

Research on Diagnosis Method of Common Knee Diseases Based on Subjective Symptoms and Random Forest Algorithm

Author 1: Guangjun Wang Author 2: Mengxia Hu Author 3: Linlin Lv Author 4: Hanyuan Zhang Author 5: Yining Sun Author 6: Benyue Su Author 7: Zuchang Ma

Knee diseases are common diseases in the elderly, and timely and effective diagnosis of knee diseases is essential for disease treatment and rehabilitation training. In this study, we construct a diagnostic model of common knee diseases based on subjective symptoms and random forest algorithm to realize patients' self-initial diagnosis. In… Read full abstract & cite →

Knee diseases subjective symptoms random forest algorithm self-diagnosis
Abstract doi.org/10.14569/IJACSA.2024.0150416 PDF
17

Data Dynamic Prediction Algorithm in the Process of Entity Information Search for the Internet of Things

Author 1: Tianqing Liu

To address the issue of insufficient real-time capability in existing Internet search engines within the Internet of Things environment, this research investigates the architecture of Internet of Things search systems. It proposes a data dynamic prediction algorithm tailored for the process of entity information search in the Internet of Things… Read full abstract & cite →

Internet of Things sensors swinging door trending (SDT) support vector machine (SVM) data dynamic prediction
Abstract doi.org/10.14569/IJACSA.2024.0150417 PDF
18

Deep Learning-Powered Lung Cancer Diagnosis: Harnessing IoT Medical Data and CT Images

Author 1: Xiao Zhang Author 2: Xiaobo Wang Author 3: Tao Huang Author 4: Jinping Sheng

Currently, lung cancer poses a significant global threat, ranking among the most perilous and lethal ailments. Accurate early detection and effective treatments play pivotal roles in mitigating its mortality rates. Utilizing deep learning techniques, CT scans offer a highly advantageous imaging modality for diagnosing lung cancer. In this study, we… Read full abstract & cite →

Diagnosis CT images deep learning convolutional neural network lung cancer
Abstract doi.org/10.14569/IJACSA.2024.0150418 PDF
19

Transmission Line Monitoring Technology Based on Compressed Sensing Wireless Sensor Network

Author 1: Shuling YIN Author 2: Renping YU Author 3: Longzhi WANG

Given wireless sensor networks' significant data transmission requirements, conventional direct transmission often leads to bandwidth constraints and excessive network energy consumption. This paper proposes a transmission line monitoring technology based on compressed sensing wireless sensor networks to achieve real-time monitoring of ice-covered power lines. Grounded in compressed sensing theory, this… Read full abstract & cite →

Compressed sensing transmission line wireless sensor network orthogonal wavelet transform data reconstruction
Abstract doi.org/10.14569/IJACSA.2024.0150419 PDF
20

Implementation of Cosine Similarity Algorithm on Omnibus Law Drafting

Author 1: Aristoteles Author 2: Muhammad Umaruddin Syam Author 3: Tristiyanto Author 4: Bambang Hermanto

Drafting of Omnibus Laws presents a complex challenge in legal governance, often involving the integration and consolidation of disparate legal provisions into a unified framework. In this context, the application of advanced computational techniques becomes crucial for streamlining the drafting process and ensuring coherence across the law's various components. Cosine… Read full abstract & cite →

Cosine similarity FastAPI Laravel Omnibus Law
Abstract doi.org/10.14569/IJACSA.2024.0150420 PDF
21

Enhancing Particle Swarm Optimization Performance Through CUDA and Tree Reduction Algorithm

Author 1: Hussein Younis Author 2: Mujahed Eleyat

In this paper, we present an enhancement for Particle Swarm Optimization performance by utilizing CUDA and a Tree Reduction Algorithm. PSO is a widely used metaheuristic algorithm that has been adapted into a CUDA version known as CPSO. The tree reduction algorithm is employed to efficiently compute the global best… Read full abstract & cite →

Particle swarm optimization tree reduction algorithm parallel implementations CUDA GPU
Abstract doi.org/10.14569/IJACSA.2024.0150421 PDF
22

Underwater Video Image Restoration and Visual Communication Optimization Based on Improved Non Local Prior Algorithm

Author 1: Tian Xia

Underwater image processing should balance image clarity restoration and comprehensive display of underwater scenes, requiring image fusion and stitching techniques. The pixel level fusion method is based on pixels, and by fusing different image data, it eliminates stitching gaps and sudden changes in lighting intensity, preserves detailed information, and thus… Read full abstract & cite →

Improving non local prior algorithms underwater video images visual communication effect optical characteristic processing image quality
Abstract doi.org/10.14569/IJACSA.2024.0150422 PDF
23

Integrated Ensemble Model for Diabetes Mellitus Detection

Author 1: Abdulaziz A Alzubaidi Author 2: Sami M Halawani Author 3: Mutasem Jarrah

Diabetes Mellitus, commonly referred to as (DM), is a chronic illness that affects populations worldwide, leading to more complications such as renal failure, visual impairment, and cardiovascular disease, thus significantly compromising the individual's well-being of life. Detecting DM at an early stage is both challenging and a critical procedure for… Read full abstract & cite →

Diabetes mellitus machine learning deep learning stacking ensemble learning RF CNN-LSTM SDLs XGBoost
Abstract doi.org/10.14569/IJACSA.2024.0150423 PDF
24

Leveraging Machine Learning Methods for Crime Analysis in Textual Data

Author 1: Shynar Mussiraliyeva Author 2: Gulshat Baispay

The proposed research paper explores the application of machine learning techniques in crime analysis problem, specifically focusing on the classification of crime-related textual data. Through a comparative analysis of various machine learning models, including traditional approaches and deep learning architectures, the study evaluates their effectiveness in accurately detecting and categorizing… Read full abstract & cite →

Machine learning artificial intelligence crime analysis text processing natural language processing text analysis data-driven decision making
Abstract doi.org/10.14569/IJACSA.2024.0150424 PDF
25

Superframe Segmentation for Content-based Video Summarization

Author 1: Priyanka Ganesan Author 2: Senthil Kumar Jagatheesaperumal Author 3: Abirami R Author 4: Lekhasri K Author 5: Silvia Gaftandzhieva Author 6: Rositsa Doneva

Video summarization is a complex computer vision task that involves the compression of lengthy videos into shorter yet informative summaries that retain the crucial content of the original footage. This paper presents a content-based video summarization approach that utilizes superframe segmentation to identify and extract keyframes representing the most significant… Read full abstract & cite →

Video summarization deep learning super frame segmentation keyframes keyshot identification
Abstract doi.org/10.14569/IJACSA.2024.0150425 PDF
26

Training Model of High-Rise Building Project Management Talent under Multi-Objective Evolutionary Algorithm

Author 1: Pan QI

In order to meet the development needs of the construction engineering industry and further optimize and improve the talent training mode, this paper studies the talent training model of high-rise construction project management under the multi-objective evolutionary algorithm. The cognitive ability model of management talent is constructed, and the learning… Read full abstract & cite →

Multi-objective evolution high-rise building engineering project management personnel training skill proficiency project cost
Abstract doi.org/10.14569/IJACSA.2024.0150426 PDF
27

Development of a New Chaotic Function-based Algorithm for Encrypting Digital Images

Author 1: Dhian Sweetania Author 2: Suryadi MT Author 3: Sarifuddin Madenda

This paper discusses the development of a new chaotic function (proposed chaotic map) as a keystream generator to be used to encrypt and decrypt the image. The proposed chaotic function is obtained through the composition process of two chaotic functions MS map and Tent map, with the aim of increasing… Read full abstract & cite →

Chaotic function decryption encryption function composition key space MS tent map
Abstract doi.org/10.14569/IJACSA.2024.0150427 PDF
28

Transfer Learning-based CNN Model for the Classification of Breast Cancer from Histopathological Images

Author 1: Sumitha A Author 2: Rimal Isaac R S

Breast cancer can have significant emotional and physical repercussions for women and their families. The timely identification of potential breast cancer risks is crucial for prompt medical intervention and support. In this research, we introduce innovative methods for breast cancer detection, employing a Convolutional Neural Network (CNN) architecture and Transfer… Read full abstract & cite →

Breast cancer transfer learning ResNet152v2 medical image analysis ICAIR 2018 dataset
Abstract doi.org/10.14569/IJACSA.2024.0150428 PDF
29

Autoencoder and CNN for Content-based Retrieval of Multimodal Medical Images

Author 1: Suresh Kumar J S Author 2: Maria Celestin Vigila S

Content-Based Medical Image Retrieval (CBMIR) is a widely adopted approach for retrieving related images by the comparison inherent features present in the input image to those stored in the database. However, the domain of CBMIR specific to multiclass medical images faces formidable challenges, primarily stemming from a lack of comprehensive… Read full abstract & cite →

Medical image retrieval multiclass medical images artificial intelligence deep learning convolutional neural network autoencoder
Abstract doi.org/10.14569/IJACSA.2024.0150429 PDF
30

Optimizing Bug Bounty Programs for Efficient Malware-Related Vulnerability Discovery

Author 1: Semi Yulianto Author 2: Benfano Soewito Author 3: Ford Lumban Gaol Author 4: Aditya Kurniawan

Conventional security measures struggle to keep pace with the rapidly evolving threat of malware, which demands novel approaches for vulnerability discovery. Although Bug Bounty Programs (BBPs) are promising, they often underperform in attracting researchers, particularly in uncovering malware-related vulnerabilities. This study optimizes BBP structures to maximize engagement and target malware… Read full abstract & cite →

Bug bounty malware vulnerability discovery cyber defense
Abstract doi.org/10.14569/IJACSA.2024.0150430 PDF
31

ConvADD: Exploring a Novel CNN Architecture for Alzheimer's Disease Detection

Author 1: Mohammed G Alsubaie Author 2: Suhuai Luo Author 3: Kamran Shaukat

Alzheimer's disease (AD) poses a significant healthcare challenge, with an escalating prevalence and a forecasted surge in affected individuals. The urgency for precise diagnostic tools to enable early interventions and improved patient care is evident. Despite advancements, existing detection frameworks exhibit limitations in accurately identifying AD, especially in its early… Read full abstract & cite →

Alzheimer’s disease AD detection convolution neural network
Abstract doi.org/10.14569/IJACSA.2024.0150431 PDF
32

A Cost-Effective IoT-based Transcutaneous Electrical Nerve Stimulation (TENS): Proof-of-Concept Design and Evaluation

Author 1: Ahmad O. Alokaily Author 2: Meshael J. Almansour Author 3: Ahmed A. Aldohbeyb Author 4: Suhail S. Alshahrani

Transcutaneous electrical nerve stimulation (TENS) systems have been extensively used as a noninvasive and non-pharmaceutical approach for pain management and rehabilitation programs. Moreover, recent advances in telemedicine applications and the Internet of Things (IoT) have led to an increased interest in developing affordable systems that facilitate the remote monitoring of… Read full abstract & cite →

Electro-stimulator Internet of Things TENS pain management smart health IoT telemedicine
Abstract doi.org/10.14569/IJACSA.2024.0150432 PDF
33

An Intelligent Learning Approach for Improving ECG Signal Classification and Arrhythmia Analysis

Author 1: Sarah Allabun

The development of deep learning algorithms in recent years has shown promise in interpreting ECGs, as these algorithms can be trained on large datasets and can learn to identify patterns associated with different heart conditions. The advantage of these algorithms is their ability to process large amounts of data quickly… Read full abstract & cite →

Electrocardiogram cardiovascular diseases classification ResNet-50 Xception
Abstract doi.org/10.14569/IJACSA.2024.0150433 PDF
34

Multi-Discriminator Image Restoration Algorithm Based on Hybrid Dilated Convolution Networks

Author 1: Chunming Wu Author 2: Fengshuo Qi

With the continuous development of generative adversarial networks (GAN), many image restoration problems that are difficult to solve based on traditional methods have been given new research avenues. Nevertheless, there are still problems such as structural distortion and texture blurring of the complemented image in the face of irregular missing… Read full abstract & cite →

GAN image restoration hybrid dilated convolution attention mechanism two-stage network
Abstract doi.org/10.14569/IJACSA.2024.0150434 PDF
35

Research on Resource Sharing Method of Library and Document Center Under the Multimedia Background

Author 1: Jianhui Zhang

In order to improve the utilization effect of the resources of the book and document center and ensure the security of its resource sharing, the resource sharing methods of the book and document center under the multimedia background are studied. The resource layer of this method is based on multimedia… Read full abstract & cite →

Multimedia background library and reference center resource sharing virtual technology multimedia technology
Abstract doi.org/10.14569/IJACSA.2024.0150435 PDF
36

A Hybrid MCDM Model for Service Composition in Cloud Manufacturing using O-TOPSIS

Author 1: Syed Omer Farooq Ahmed Author 2: Adapa Gopi

The purpose of this research article was to define the current or future usage of Industry 4.0 technologies (Cloud Computing, IoT, etc.) to improve industrial manufacturing. The goal of this study is to rate the options using a hybrid CRITIC - O-TOPSIS Multi Criteria Decision Making model. The CRITIC technique… Read full abstract & cite →

Cloud manufacturing (CMFg) CRITIC method O-TOPSIS method service composition
Abstract doi.org/10.14569/IJACSA.2024.0150436 PDF
37

Comparative Analysis of Transformer Models for Sentiment Analysis in Low-Resource Languages

Author 1: Yusuf Aliyu Author 2: Aliza Sarlan Author 3: Kamaluddeen Usman Danyaro Author 4: Abdulahi Sani B A Rahman

The analysis of sentiments expressed on social media platforms is a crucial tool for understanding user opinions and preferences. The large amount of the texts found on social media are mostly in different languages. However, the accuracy of sentiment analysis in these systems faces different challenges in multilingual low-resource settings… Read full abstract & cite →

Sentiment analysis low-resource languages multilingual word-embedding transformer
Abstract doi.org/10.14569/IJACSA.2024.0150437 PDF
38

Influence of a Serious Video Game on the Behavior of Drivers in the Face of Automobile Incidents

Author 1: Bryan S. Diaz-Sipiran Author 2: Segundo E. Cieza-Mostacero

The primary objective of this research was to enhance driver behavior during incidents through the use of a serious video game. The study employed a true experimental design. The research population consisted of an unspecified number of drivers from the city of Trujillo. Sixty drivers from Trujillo were randomly selected… Read full abstract & cite →

Videogame serious behavior driving incidents
Abstract doi.org/10.14569/IJACSA.2024.0150438 PDF
39

A Genetic Artificial Bee Colony Algorithm for Investigating Job Creation and Economic Enhancement in Medical Waste Recycling

Author 1: El Liazidi Sara Author 2: Dkhissi Btissam

The effective management of end-of-life products, whether through recycling or incineration for electricity generation, holds pivotal significance amidst escalating concerns over economic, environmental, and social ramifications. While the economic and environmental dimensions often receive primary focus, the social aspect remains comparatively neglected within sustainability discourse. This paper undertakes a comprehensive… Read full abstract & cite →

Medical waste recycling social impacts genetic artificial bee colony algorithm job creation economic value
Abstract doi.org/10.14569/IJACSA.2024.0150439 PDF
40

Multimodal Feature Fusion Video Description Model Integrating Attention Mechanisms and Contrastive Learning

Author 1: Wang Zhihao Author 2: Che Zhanbin

To avoid the issue of significant redundancy in the spatiotemporal features extracted from multimodal video description methods and the substantial semantic gaps between different modalities within video data. Building upon the TimeSformer model, this paper proposes a two-stage video description approach (Multimodal Feature Fusion Video Description Model Integrating Attention Mechanism… Read full abstract & cite →

Multimodal feature fusion video description spatiotemporal attention comparative learning
Abstract doi.org/10.14569/IJACSA.2024.0150440 PDF
41

Permanent Magnet Motor Control System Based on Fuzzy PID Control

Author 1: Yin Sha Author 2: Huwei Chen

Although the traditional permanent magnet synchronous motor control system is simple and convenient, the control of speed and accuracy is often affected by external interference, which impacts the dynamic and static performance requirements. Therefore, this study attempts to introduce fuzzy rules to improve the proportional integral differential control method, and… Read full abstract & cite →

Permanent magnet motor fuzzy PID fuzzy control automatic control system artificial bee colony
Abstract doi.org/10.14569/IJACSA.2024.0150441 PDF
42

Impact of Contradicting Subtle Emotion Cues on Large Language Models with Various Prompting Techniques

Author 1: Noor Ul Huda Author 2: Sanam Fayaz Sahito Author 3: Abdul Rehman Gilal Author 4: Ahsanullah Abro Author 5: Abdullah Alshanqiti Author 6: Aeshah Alsughayyir Author 7: Abdul Sattar Palli

The landscape of human-machine interaction is undergoing a transformation with the integration of conversational technologies. In various domains, Large Language Model (LLM) based chatbots are progressively taking on roles traditionally handled by human agents, such as task execution, answering queries, offering guidance, and delivering social and emotional assistance. Consequently, enhancing… Read full abstract & cite →

Emotion cues prompt Large Language Model (LLM) Human Computer Interactions (HCI)
Abstract doi.org/10.14569/IJACSA.2024.0150442 PDF
43

Investigating Sampler Impact on AI Image Generation: A Case Study on Dogs Playing in the River

Author 1: Sanjay Deshmukh

AI image generation is a new and exciting field with many different uses. It is important to understand how different sampling techniques affect the quality of AI-generated images in order to get the best results. This study looks at how different sampling techniques affect the quality of AI-generated images of… Read full abstract & cite →

Artificial Intelligence image generation filter sampler Euler Heun
Abstract doi.org/10.14569/IJACSA.2024.0150443 PDF
44

Enhancing Ultimate Bearing Capacity Assessment of Rock Foundations using a Hybrid Decision Tree Approach

Author 1: Mei Guo Author 2: Ren-an Jiang

Accurately estimating the ultimate bearing capacity of piles embedded in rock is of paramount importance in the domains of civil engineering, construction, and foundation design. This research introduces an innovative solution to tackle this issue, leveraging a fusion of the Decision Tree method with two state-of-the-art optimization algorithms: the Zebra… Read full abstract & cite →

Ultimate bearing capacity decision tree zebra optimization algorithm coronavirus herd immunity optimizer
Abstract doi.org/10.14569/IJACSA.2024.0150444 PDF
45

Improving Prediction Accuracy using Random Forest Algorithm

Author 1: Nesma Elsayed Author 2: Sherif Abd Elaleem Author 3: Mohamed Marie

One of the latest studies in predicting bankruptcy is the performance of the financial prediction models. Although several models have been developed, they often do not achieve high performance, especially when using an imbalanced data set. This highlights the need for more exact prediction models. This paper examines the application… Read full abstract & cite →

Corporate bankruptcy feature selection financial ratios prediction models random forest
Abstract doi.org/10.14569/IJACSA.2024.0150445 PDF
46

StockBiLSTM: Utilizing an Efficient Deep Learning Approach for Forecasting Stock Market Time Series Data

Author 1: Diaa Salama Abd Elminaam Author 2: Asmaa M M. El-Tanany Author 3: Mohamed Abd El Fattah Author 4: Mustafa Abdul Salam

The article introduces a novel approach for forecasting stock market prices, employing a computationally efficient Bidirectional Long Short-Term Memory (BiLSTM) model enhanced with a global pooling mechanism. Based on the deep learning framework, this method leverages the temporal dynamics of stock data in both forward and reverse time frames, enabling… Read full abstract & cite →

Stock prediction Univariate LSTM models Deep learning financial forecasting Vanilla LSTM Stacked LSTM Bidirectional LSTM
Abstract doi.org/10.14569/IJACSA.2024.0150446 PDF
47

Segmentation Analysis for Brain Stroke Diagnosis Based on Susceptibility-Weighted Imaging (SWI) using Machine Learning

Author 1: Shaarmila Kandaya Author 2: Abdul Rahim Abdullah Author 3: Norhashimah Mohd Saad Author 4: Ezreen Farina Author 5: Ahmad Sobri Muda

Magnetic Resonance Imaging (MRI) plays a crucial role in diagnosing brain disorders, with stroke being a significant category among them. Recent studies emphasize the importance of swift treatment for stroke, known as "time is brain," as early intervention within six hours of stroke onset can save lives and improve outcomes… Read full abstract & cite →

Magnetic Resonance Imaging (MRI) diagnosis time is brain Susceptibility Weighted Imaging (SWI) and dice coefficient
Abstract doi.org/10.14569/IJACSA.2024.0150447 PDF
48

A Genetic Algorithm-based Approach for Design-level Class Decomposition

Author 1: Bayu Priyambadha Author 2: Nobuya Takahashi Author 3: Tetsuro Katayama

Software is always changed to accommodate environmental changes to preserve its existence. While changes happen to the software, the internal structure tends to decline in quality. The refactoring process is worth running to preserve the internal structure of the software. The decomposition process is a suitable refactoring process for Blob… Read full abstract & cite →

Genetic algorithm refactoring class decomposition blob smell software internal quality
Abstract doi.org/10.14569/IJACSA.2024.0150448 PDF
49

Analysis and Enhancement of Prediction of Cardiovascular Disease Diagnosis using Machine Learning Models SVM, SGD, and XGBoost

Author 1: Sandeep Tomar Author 2: Deepak Dembla Author 3: Yogesh Chaba

Cardiovascular disease (CVD), claiming 17.9 million lives annually, is exacerbated by factors like high blood pressure and obesity, prompting extensive data collection for deeper insights. Machine learning aids in accurate diagnosis, with techniques like SVM, SGD, and XGBoost proposed for heart disease prediction, addressing challenges such as data imbalance and… Read full abstract & cite →

CVD SVM SGD XGBoost classifiers machine learning ROC accuracy confusion matrix
Abstract doi.org/10.14569/IJACSA.2024.0150449 PDF
50

Towards a New Artificial Intelligence-based Framework for Teachers’ Online Continuous Professional Development Programs: Systematic Review

Author 1: Hamza Fakhar Author 2: Mohammed Lamrabet Author 3: Noureddine Echantoufi Author 4: Khalid El khattabi Author 5: Lotfi Ajana

In recent years, the Artificial Intelligence (AI) field has witnessed rapid growth, affecting diverse sectors, including education. In this systematic review of literature, we aimed to analyze studies concerning the integration of AI in the continuous professional development (CPD) of teachers in order to generate a global vision on its… Read full abstract & cite →

Artificial intelligent continuous professional development Moroccan in-service teacher digital teacher online training adaptive development
Abstract doi.org/10.14569/IJACSA.2024.0150450 PDF
51

Improvement of Social Skills in Children with Autism Spectrum Disorder Through the use of a Video Game

Author 1: Luis C. Soles-Núñez Author 2: Segundo E. Cieza-Mostacero

The main research objective was to improve social skills through a video game, the type of research was applied with a pure experimental design, with a sample of 60 children with autism spectrum disorder from the Christa McAuliffe school, randomly allocated 30 to the control group (CG) and 30 to… Read full abstract & cite →

Video games social skills autism spectrum disorder SUM methodology academic software
Abstract doi.org/10.14569/IJACSA.2024.0150451 PDF
52

Cinematic Curator: A Machine Learning Approach to Personalized Movie Recommendations

Author 1: B. Venkateswarlu Author 2: N. Yaswanth Author 3: A. Manoj Kumar Author 4: U. Satish Author 5: K. Dwijesh Author 6: N. Sunanda

This work suggests a sophisticated movie recommendation system that offers individualized recommendations based on user preferences by combining content-based filtering, collaborative filtering, and deep learning approaches. The system use natural language processing (NLP) to examine user-generated content, movie summaries, and reviews in order to get a sophisticated comprehension of thematic… Read full abstract & cite →

Machine learning algorithms decision tree random forest model-evaluation accuracy value precision value F1 score
Abstract doi.org/10.14569/IJACSA.2024.0150452 PDF
53

Sentiment Analysis of Pandemic Tweets with COVID-19 as a Prototype

Author 1: Mashail Almutiri Author 2: Mona Alghamdi Author 3: Hanan Elazhary

One of the most important applications of text mining is sentiment analysis of pandemic tweets. For example, it can make governments able to predict the onset of pandemics and to put in place safe policies based on people's feelings. Many research studies addressed this issue using various datasets and models… Read full abstract & cite →

COVID-19 deep learning machine learning sentiment analysis text mining tweets
Abstract doi.org/10.14569/IJACSA.2024.0150453 PDF
54

Automating Mushroom Culture Classification: A Machine Learning Approach

Author 1: Hamimah Ujir Author 2: Irwandi Hipiny Author 3: Mohamad Hasnul Bolhassan Author 4: Ku Nurul Fazira Ku Azir Author 5: SA Ali

Traditionally, the classification of mushroom cultures has conventionally relied on manual inspection by human experts. However, this methodology is susceptible to human bias and errors, primarily due to its dependency on individual judgments. To overcome these limitations, we introduce an innovative approach that harnesses machine learning methodologies to automate the… Read full abstract & cite →

Machine learning convolution neural networks mushroom cultivation rhizomorph mycelium
Abstract doi.org/10.14569/IJACSA.2024.0150454 PDF
55

Leather Image Quality Classification and Defect Detection System using Mask Region-based Convolution Neural Network Model

Author 1: Azween Bin Abdullah Author 2: Malathy Jawahar Author 3: Nalini Manogaran Author 4: Geetha Subbiah Author 5: Koteeswaran Seeranagan Author 6: Balamurugan Balusamy Author 7: Abhishek Chengam Saravanan

The leather industry is increasingly becoming one amongst the most important manufacturing industries in the world. Increasing demand has posed a great challenge as well as an opportunity for these industries. Quality of a leather product has been always the main factor in the setting of the market selling price… Read full abstract & cite →

Image leather classification leather defect detection Convolutional Neural Network CNN deep learning
Abstract doi.org/10.14569/IJACSA.2024.0150455 PDF
56

Prediction of Pigment Epithelial Detachment in Optical Coherence Tomography Images using Machine Learning

Author 1: T. M. Sheeba Author 2: S. Albert Antony Raj

Pigment Epithelial Detachment (PED) is an eye condition that can affect adults over 50 and eventually harm their central vision. The PED region is positioned between the Bruch's membrane (BM) and the RPE (Retinal Pigment Epithelium) layer. Due to PED, the RPE layer is elevated arc shaped. In this paper… Read full abstract & cite →

Artificial neural network k-nearest neighbor logistic regression layer segmentation naïve base optical coherence tomography pigment epithelial detachment
Abstract doi.org/10.14569/IJACSA.2024.0150456 PDF
57

Investigating the Effect of Small Sample Process Capability Index Under Different Bootstrap Methods

Author 1: Liyan Wang Author 2: Guihua Bo Author 3: Mingjuan Du

In the quality control of multi-variety and small-batch products, the calculation of the process capability index is particularly important. However, when the sample size is not enough, the process distribution cannot be judged, if the traditional method is still used to calculate the process capability index; there will be misapplication… Read full abstract & cite →

Process capability indices bootstrap confidence interval small samples
Abstract doi.org/10.14569/IJACSA.2024.0150457 PDF
58

Discovering the Global Landscape of Agri-Food and Blockchain: A Bibliometric Review

Author 1: Sharifah Khairun Nisa’ Habib Elias Author 2: Sahnius Usman Author 3: Suriayati Chuprat

The agri-food supply chain encompasses all the entities involved in the production and processing of food, from producers to consumers. Traceability is crucial in ensuring that food products are available, affordable, and accessible. Blockchain technology has been proposed as a way to improve traceability in the agri-food supply chain by… Read full abstract & cite →

Agri-food supply chain bibliometric blockchain traceability
Abstract doi.org/10.14569/IJACSA.2024.0150458 PDF
59

A Robust Hybrid Convolutional Network for Tumor Classification Using Brain MRI Image Datasets

Author 1: Satish Bansal Author 2: Rakesh S Jadon Author 3: Sanjay K. Gupta

Brain tumour detection is challenging for experts or doctors in the early stage. Many advanced techniques are used for the detection of different cancers and analysis using different medical images. Deep learning (DL) comes under artificial intelligence, which is used to analyse and characterisation medical image processing and also finds… Read full abstract & cite →

CNN SVM MRI images brain tumor deep learning
Abstract doi.org/10.14569/IJACSA.2024.0150459 PDF
60

Emotion Recognition with Intensity Level from Bangla Speech using Feature Transformation and Cascaded Deep Learning Model

Author 1: Md. Masum Billah Author 2: Md. Likhon Sarker Author 3: M. A. H. Akhand Author 4: Md Abdus Samad Kamal

Speech Emotion Recognition (SER) identifies and categorizes emotional states by analyzing speech signals. The intensity of specific emotional expressions (e.g., anger) conveys critical directives and plays a crucial role in social behavior. SER is intrinsically language-specific; this study investigated a novel cascaded deep learning (DL) model to Bangla SER with… Read full abstract & cite →

Bangla speech emotion recognition speech signal transformation convolutional neural network bidirectional long short-term memory
Abstract doi.org/10.14569/IJACSA.2024.0150460 PDF
61

Optimizing Deep Learning for Efficient and Noise-Robust License Plate Detection and Recognition

Author 1: Seong-O Shim Author 2: Romil Imtiaz Author 3: Safa Habibullah Author 4: Abdulrahman A. Alshdadi

Accurate license plate recognition (LPR) remains a crucial task in various applications, from traffic monitoring to security systems. However, noisy environments with challenging factors like blurred images, low light, and complex backgrounds can significantly impede traditional LPR methods. This work proposes a deep learning based LPR system optimized for performance… Read full abstract & cite →

De-noising image analysis image processing computer vision image restoration
Abstract doi.org/10.14569/IJACSA.2024.0150461 PDF
62

Crowdsourcing Requirements Engineering: A Taxonomy-based Review

Author 1: Ghadah Alamer Author 2: Sultan Alyahya Author 3: Hmood Al-Dossari

Interesting insights have been found by the research community indicating that early user involvement in Requirements Engineering (RE) has a considerable association with higher requirements quality, software project success and as well boosting user loyalty. In addition, traditional RE approaches confront scalability issues and would be time consuming and expensive… Read full abstract & cite →

Crowdsourcing requirements engineering crowdsourcing CrowdRE crowd
Abstract doi.org/10.14569/IJACSA.2024.0150462 PDF
63

An Effective Book Recommendation System using Weighted Alternating Least Square (WALS) Approach

Author 1: Kavitha V K Author 2: Sankar Murugesan

Book recommendation systems are essential resources for connecting people with the correct books, encouraging a love of reading, and sustaining a vibrant literary ecosystem in an era when information overload is a prevalent problem. With the emergence of digital libraries and large online book retailers, readers may no longer find… Read full abstract & cite →

Recommendation system user ratings matrix factorization alternating least square weighted matrix factorization
Abstract doi.org/10.14569/IJACSA.2024.0150463 PDF
64

Improving Predictive Maintenance in Industrial Environments via IIoT and Machine Learning

Author 1: Saleh Othman Alhuqayl Author 2: Abdulaziz Turki Alenazi Author 3: Hamad Abdulaziz Alabduljabbar Author 4: Mohd Anul Haq

Optimizing maintenance procedures is essential in today's industrial settings to reduce downtime and increase operational effectiveness. To improve predictive maintenance in industrial settings, this article investigates the combination of machine learning (ML) techniques and the Industrial Internet of Things (IIoT). The goal of this research is to advance predictive maintenance… Read full abstract & cite →

Predictive maintenance IIoT data visualization machine learning industrial systems
Abstract doi.org/10.14569/IJACSA.2024.0150464 PDF
65

Analyzing Privacy Implications and Security Vulnerabilities in Single Sign-On Systems: A Case Study on OpenID Connect

Author 1: Mohammed Al Shabi Author 2: Rashiq Rafiq Marie

Single Sign-On (SSO) systems have gained popularity for simplifying the login process, enabling users to authenticate through a single identity provider (IDP). However, their widespread adoption raises concerns regarding user privacy, as IDPs like Google or Facebook can accumulate extensive data on user web behavior. This presents a significant challenge… Read full abstract & cite →

Single Sign-On OpenID connect protocol vulnerabilities privacy third-party
Abstract doi.org/10.14569/IJACSA.2024.0150465 PDF
66

A Patrol Platform Based on Unmanned Aerial Vehicle for Urban Safety and Intelligent Social Governance

Author 1: Ying Yang Author 2: Rui Ma Author 3: Fengjiao Zhou

Urban patrols can detect emergencies in a timely manner and collect information, which helps to improve the quality of services in the city and enhance the comfort of residents. This study proposes the use of IoT-based drones for urban patrol tasks, aiming to explore the potential applications of drones in… Read full abstract & cite →

Patrol drones trajectory planning smart city governance crow search algorithm swarm intelligence algorithm
Abstract doi.org/10.14569/IJACSA.2024.0150466 PDF
67

Entity Relation Joint Extraction Method Based on Insertion Transformers

Author 1: Haotian Qi Author 2: Weiguang Liu Author 3: Fenghua Liu Author 4: Weigang Zhu Author 5: Fangfang Shan

Existing multi-module multi-step and multi-module single-step methods for entity relation joint extraction suffer from issues such as cascading errors and redundant mistakes. In contrast, the single-module single-step modeling approach effectively alleviates these limitations. However, the single-module single-step method still faces challenges when dealing with complex relation extraction tasks, such as… Read full abstract & cite →

Entity relation extraction tagging strategy joint extraction transformer
Abstract doi.org/10.14569/IJACSA.2024.0150467 PDF
68

Timber Defect Identification: Enhanced Classification with Residual Networks

Author 1: Teo Hong Chun Author 2: Ummi Raba’ah Hashim Author 3: Sabrina Ahmad

This study investigates the potential enhancement of classification accuracy in timber defect identification through the utilization of deep learning, specifically residual networks. By exploring the refinement of these networks via increased depth and multi-level feature incorporation, the goal is to develop a framework capable of distinguishing various defect classes. A… Read full abstract & cite →

Residual neural network convolutional neural network timber defect identification deep learning
Abstract doi.org/10.14569/IJACSA.2024.0150468 PDF
69

Enhancing Supply Chain Management Efficiency: A Data-Driven Approach using Predictive Analytics and Machine Learning Algorithms

Author 1: Shamrao Parashram Ghodake Author 2: Vinod Ramchandra Malkar Author 3: Kathari Santosh Author 4: L. Jabasheela Author 5: Shokhjakhon Abdufattokhov Author 6: Adapa Gopi

Contemporary firms rely heavily on the effectiveness of their supply chain management. Modern supply chains are complicated and unpredictable, and traditional methods frequently find it difficult to adjust to these factors. Increasing supply chain efficiency through improved supplier performance, demand prediction, inventory optimisation, and streamlined logistics processes may be achieved… Read full abstract & cite →

Supply chain management predictive analytics demand forecasting inventory management exploratory data analysis
Abstract doi.org/10.14569/IJACSA.2024.0150469 PDF
70

Advancing Prostate Cancer Diagnostics with Image Masking Techniques in Medical Image Analysis

Author 1: H. V. Ramana Rao Author 2: V RaviSankar

Prostate cancer is a prevalent health concern characterized by the abnormal and uncontrolled growth of cells within the prostate gland in men. This research paper outlines a standardized methodology for integrating medical slide images into machine learning algorithms, specifically emphasizing advancing healthcare diagnostics. The methodology involves thorough data collection, exploration… Read full abstract & cite →

Prostate cancer data exploration image analysis medical conditions background prediction techniques data preparation diagnostic accuracy dataset characteristics image dimensions deep learning statistical analysis prostate cancer detection advanced imaging modalities healthcare diagnostics medical image analysis machine learning target variables
Abstract doi.org/10.14569/IJACSA.2024.0150470 PDF
71

Deep Learning Network Optimization for Analysis and Classification of High Band Images

Author 1: Manju Sundararajan Author 2: S. J Grace Shoba Author 3: Y. Rajesh Babu Author 4: P N S Lakshmi

Examination and categorization of high-band pictures are used to describe the process of analysing and classifying photos that have been taken in many bands. Deep learning networks are known for their capacity to extract intricate information from images with a high bandwidth. The novelty lies in the integration of adaptive… Read full abstract & cite →

Deep learning networks Convolutional Neural Network (CNN) spectral-spatial transformer adaptive motion optimization high-band image analysis
Abstract doi.org/10.14569/IJACSA.2024.0150471 PDF
72

Lightweight Cryptographic Algorithms for Medical IoT Devices using Combined Transformation and Expansion (CTE) and Dynamic Chaotic System

Author 1: Abdul Muhammed Rasheed Author 2: Retnaswami Mathusoothana Satheesh Kumar

IoT is growing in prominence as a result of its various applications across many industries. They gather information from the real world and send it over networks. The number of small computing devices, such as RFID tags, wireless sensors, embedded devices, and IoT devices, has increased significantly in the last… Read full abstract & cite →

Internet of Things (IoT) data transmission data security medical IoT devices lightweight cryptography encryption decryption
Abstract doi.org/10.14569/IJACSA.2024.0150472 PDF
73

A Novel Graph Convolutional Neural Networks (GCNNs)-based Framework to Enhance the Detection of COVID-19 from X-Ray and CT Scan Images

Author 1: D. Raghu Author 2: Hrudaya Kumar Tripathy Author 3: Raiza Borreo

The constant need for robust and efficient COVID-19 detection methodologies has prompted the exploration of advanced techniques in medical imaging analysis. This paper presents a novel framework that leverages Graph Convolutional Neural Networks (GCNNs) to enhance the detection of COVID-19 from CT scan and X-Ray images. Hence, the GCNN parameters… Read full abstract & cite →

COVID-19 detection Graph Neural Networks X-ray CT scan images hybrid optimization medical imaging analysis diagnostic tools pandemic response
Abstract doi.org/10.14569/IJACSA.2024.0150473 PDF
74

A Smart AI Framework for Backlog Refinement and UML Diagram Generation

Author 1: Samia NASIRI Author 2: Mohammed LAHMER

In Agile development, it is crucial to refine the backlog to prioritize tasks, resolve problems quickly, and align development efforts with project goals. Automated tools can help in this process by generating Unified Modeling Language (UML) diagrams, allowing teams to work more efficiently with a clear understanding and communicate product… Read full abstract & cite →

Artificial intelligence NLP Agile methodology UML
Abstract doi.org/10.14569/IJACSA.2024.0150474 PDF
75

Challenges and Solutions of Agile Software Development Implementation: A Case Study Indonesian Healthcare Organization

Author 1: Ulfah Nur Mukharomah Author 2: Teguh Raharjo Author 3: Ni Wayan Trisnawaty

One healthcare organization in Indonesia has implemented Agile software development (ASD) to complete software development. The organization's problems are post-deployment system bugs, and some software development projects must carry over to the following year. This study aims to assess and provide recommendations for improving agile software development by identifying the… Read full abstract & cite →

Agile Software Development challenge solutions IT projects information technology application implementation healthcare organization Literature Review
Abstract doi.org/10.14569/IJACSA.2024.0150475 PDF
76

The Bi-Level Particle Swarm Optimization for Joint Pricing in a Supply Chain

Author 1: Umar Mansyuri Author 2: Andreas Tri Panudju Author 3: Helena Sitorus Author 4: Widya Spalanzani Author 5: Nunung Nurhasanah Author 6: Dedy Khaerudin

This study examines the integration of pricing and lot-sizing strategies within a system comprising only one producer and retailer. The adoption of a bi-level programming technique is justified in establishing a bi-level joint pricing model guided by the producer owing to the hierarchical nature of the supply chain. This problem… Read full abstract & cite →

Bi-Level algorithm joint pricing optimization particle swarm optimization supply chain
Abstract doi.org/10.14569/IJACSA.2024.0150476 PDF
77

Deep Learning Approach for Workload Prediction and Balancing in Cloud Computing

Author 1: Syed Karimunnisa Author 2: Yellamma Pachipala

Cloud Computing voted as one of the most revolutionized technologies serving huge user demand engrosses a prominent place in research. Despite several parameters that influence the cloud performance, factors like Workload prediction and scheduling are triggering challenges for researchers in leveraging the system proficiency. Contributions by practitioners given workload prophesy… Read full abstract & cite →

Task scheduling virtual machines optimization workload prediction migration QoS
Abstract doi.org/10.14569/IJACSA.2024.0150477 PDF
78

Estimating Coconut Yield Production using Hyperparameter Tuning of Long Short-Term Memory

Author 1: Niranjan Shadaksharappa Jayanna Author 2: Raviprakash Madenur Lingaraju

Coconut production is one of the significant and main sources of revenue in India. In this research, an Auto-Regressive Integrated Moving Average (ARIMA)-Improved Sine Cosine Algorithm (ISCA) with Long Short-Term Memory (LSTM) is proposed for coconut yield production using time series data. It is used for converting non-stationary data to… Read full abstract & cite →

Auto-regressive integrated moving average coconut yield production improved sine cosine algorithm long short-term memory time series
Abstract doi.org/10.14569/IJACSA.2024.0150478 PDF
79

Integrating Lesk Algorithm with Cosine Semantic Similarity to Resolve Polysemy for Setswana Language

Author 1: Tebatso Gorgina Moape Author 2: Oludayo O. Olugbara Author 3: Sunday O. Ojo

Word Sense Disambiguation (WSD) serves as an intermediate task for enhancing text understanding in Natural Language Processing (NLP) applications, including machine translation, information retrieval, and text summarization. Its role is to enhance the effectiveness and efficiency of these applications by ensuring the accurate selection of the appropriate sense for polysemous… Read full abstract & cite →

Word sense disambiguation Lesk algorithm cosine similarity Bidirectional Encoder Representations from Transformers (BERT)
Abstract doi.org/10.14569/IJACSA.2024.0150479 PDF
80

Design of Emotion Analysis Model IABC-Deep Learning-based for Vocal Performance

Author 1: Zhenjie Zhu Author 2: Xiaojie Lv

With the development of deep learning technology, and due to its potential in solving optimization problems with deep structures, deep learning technology is gradually being applied to sentiment analysis models. However, most existing deep learning-based sentiment analysis models have low accuracy issues. Therefore, this study focuses on the issue of… Read full abstract & cite →

Vocal performance deep learning Artificial Bee Colony (ABC) emotion analysis model Deep Neural Network (DNN)
Abstract doi.org/10.14569/IJACSA.2024.0150480 PDF
81

Enhancing the Diagnosis of Depression and Anxiety Through Explainable Machine Learning Methods

Author 1: Mai Marey Author 2: Dina Salem Author 3: Nora El Rashidy Author 4: Hazem ELBakry

Diagnosing depression and anxiety involves various methods, including referenda-based approaches that may lack accuracy. However, machine learning has emerged as a promising approach to address these limitations and improve diagnostic accuracy. In this scientific paper, we present a study that utilizes a digital dataset to apply machine learning techniques for… Read full abstract & cite →

Mental health Recursive Feature Elimination (RFE) machine learning Xgboost
Abstract doi.org/10.14569/IJACSA.2024.0150481 PDF
82

An Integrated Arnold and Bessel Function-based Image Encryption on Blockchain

Author 1: Abhay Kumar Yadav Author 2: Virendra P. Vishwakarma

Images store large amount of information that are used in visual representation, analysis, and expression of data. Storage and retrieval of images possess a greater challenge to researchers globally. This research paper presents an integrated approach for image encryption and decryption using an Arnold map and first-order Bessel function-based chaos… Read full abstract & cite →

Arnold transformation block encryption Bessel functions blockchain
Abstract doi.org/10.14569/IJACSA.2024.0150482 PDF
83

COOT-Optimized Real-Time Drowsiness Detection using GRU and Enhanced Deep Belief Networks for Advanced Driver Safety

Author 1: Gunnam Rama Devi Author 2: Hayder Musaad Al-Tmimi Author 3: Ghadir Kamil Ghadir Author 4: Shweta Sharma Author 5: Eswar Patnala Author 6: B Kiran Bala Author 7: Yousef A.Baker El-Ebiary

Drowsiness among drivers is a major hazard to road safety, resulting in innumerable incidents globally. Despite substantial study, existing approaches for detecting drowsiness in real time continue to confront obstacles, such as low accuracy and efficiency. In these circumstances, this study tackles the critical problems of identifying drowsiness and driver… Read full abstract & cite →

Drowsiness detection driver safety real-time monitoring gated recurrent units enhanced deep belief networks COOT optimization
Abstract doi.org/10.14569/IJACSA.2024.0150483 PDF
84

A Hybrid Approach with Xception and NasNet for Early Breast Cancer Detection

Author 1: Yassin Benajiba Author 2: Mohamed Chrayah Author 3: Yassine Al-Amrani

Breast cancer is the most common cancer in women, accounting for 12.5% of global cancer cases in 2020, and the leading cause of cancer deaths in women worldwide. Early detection is therefore crucial to reducing deaths, and recent studies suggest that deep learning techniques can detect breast cancer more accurately… Read full abstract & cite →

Breast Cancer CNN Hybrid Model: Xception NasNet
Abstract doi.org/10.14569/IJACSA.2024.0150484 PDF
85

Strengthening Sentence Similarity Identification Through OpenAI Embeddings and Deep Learning

Author 1: Nilesh B. Korade Author 2: Mahendra B. Salunke Author 3: Amol A. Bhosle Author 4: Prashant B. Kumbharkar Author 5: Gayatri G. Asalkar Author 6: Rutuja G. Khedkar

Discovering similarity between sentences can be beneficial to a variety of systems, including chatbots for customer support, educational platforms, e-commerce customer inquiries, and community forums or question-answering systems. One of the primary issues that online question-answering platforms and customer service chatbots have is the large number of duplicate inquiries that… Read full abstract & cite →

OpenAI embedding sentence similarity FastText Word2Vec CNN LSTM precision recall F1-score
Abstract doi.org/10.14569/IJACSA.2024.0150485 PDF
86

Event-based Smart Contracts for Automated Claims Processing and Payouts in Smart Insurance

Author 1: Araddhana Arvind Deshmukh Author 2: Prabhakar Kandukuri Author 3: Janga Vijaykumar Author 4: Anna Shalini Author 5: S. Farhad Author 6: Elangovan Muniyandy Author 7: Yousef A.Baker El-Ebiary

The combination of blockchain technology and smart contracts has become a viable way to expedite claims processing and payouts in the quickly changing insurance industry. Enhancing efficiency, transparency, and reliability for the industry may be achieved by automating certain procedures and initiating them on predetermined triggers, smart contracts that is… Read full abstract & cite →

Blockchain technology smart contracts event-based triggers automated claims processing transparency and trustworthiness
Abstract doi.org/10.14569/IJACSA.2024.0150486 PDF
87

Real-time Air Quality Monitoring in Smart Cities using IoT-enabled Advanced Optical Sensors

Author 1: Anushree A. Aserkar Author 2: Sanjiv Rao Godla Author 3: Yousef A.Baker El-Ebiary Author 4: Krishnamoorthy Author 5: Janjhyam Venkata Naga Ramesh

Air quality control has drawn a lot of attention from both theoretical research and practical application due to the air pollution problem's increasing severity. As urbanization accelerates, the need for effective air quality monitoring in smart cities becomes increasingly critical. Traditional methods of air quality monitoring often involve stationary monitoring… Read full abstract & cite →

Internet of Things (IoT) air quality control low-cost sensors ESP-WROOM-32 microcontroller Amazon Web Server (AWS)
Abstract doi.org/10.14569/IJACSA.2024.0150487 PDF
88

DeepCardioNet: Efficient Left Ventricular Epicardium and Endocardium Segmentation using Computer Vision

Author 1: Bukka Shobharani Author 2: S Girinath Author 3: K. Suresh Babu Author 4: J. Chenni Kumaran Author 5: Yousef A.Baker El-Ebiary Author 6: S. Farhad

In the realm of medical image analysis, accurate segmentation of cardiac structures is essential for accurate diagnosis and therapy planning. Using the efficient Attention Swin U-Net architecture, this study provides DEEPCARDIONET, a novel computer vision approach for effectively segmenting the left ventricular epicardium and endocardium. The paper presents DEEPCARDIONET, a… Read full abstract & cite →

DeepCardioNet attention swin U-Net ventricular epicardium endocardium computer vision approach
Abstract doi.org/10.14569/IJACSA.2024.0150488 PDF
89

Enhancing HCI Through Real-Time Gesture Recognition with Federated CNNs: Improving Performance and Responsiveness

Author 1: R. Stella Maragatham Author 2: Yousef A. Baker El-Ebiary Author 3: Srilakshmi V Author 4: K. Sridharan Author 5: Vuda Sreenivasa Rao Author 6: Sanjiv Rao Godla

To facilitate smooth human-computer interaction (HCI) in a variety of contexts, from augmented reality to sign language translation, real-time gesture detection is essential. In this paper, researchers leverage federated convolutional neural networks (CNNs) to present a novel strategy that tackles these issues. By utilizing federated learning, authors may cooperatively train… Read full abstract & cite →

Real-time gesture detection federated convolutional neural networks privacy-preserving machine learning adaptive learning rate scheduling Decentralized human-computer interaction
Abstract doi.org/10.14569/IJACSA.2024.0150489 PDF
90

Advancing Automated and Adaptive Educational Resources Through Semantic Analysis with BERT and GRU in English Language Learning

Author 1: V Moses Jayakumar Author 2: R. Rajakumari Author 3: Sana Sarwar Author 4: Darakhshan Mazhar Syed Author 5: Prema S Author 6: Santhosh Boddupalli Author 7: Yousef A.Baker El-Ebiary

Semantics describe how language and its constituent parts are understood or interpreted. Semantic analysis is the computer analysis of language to derive connections, meaning, and context from words and sentences. In English language learning, dynamic content generation entails developing instructional materials that adjust to the specific requirements of each student… Read full abstract & cite →

BERT Content Generation English Language Learning Gated Recurrent Unit Semantic Analysis
Abstract doi.org/10.14569/IJACSA.2024.0150490 PDF
91

Network Security Situation Prediction Technology Based on Fusion of Knowledge Graph

Author 1: Wei Luo

It is difficult to accurately reflect different network attack events in real time, which leads to poor performance in predicting network security situations. A knowledge graph-based entity recognition model and entity relationship extraction model was developed for enhancing the reliability and processing efficiency of secure data. Then a knowledge graph-based… Read full abstract & cite →

Knowledge graph network security situation gated recurrent unit Bayesian attack graph relationship extraction relationship recognition
Abstract doi.org/10.14569/IJACSA.2024.0150491 PDF
92

Hybrid Approach for Enhanced Depression Detection using Learning Techniques

Author 1: Ganesh D. Jadhav Author 2: Sachin D. Babar Author 3: Parikshit N. Mahalle

According to the World Health Organization (WHO), depression affects over 350 million people worldwide, making it the most common health problem. Depression has numerous causes, including fluctuations in business, social life, the economy, and personal relationships. Depression is one of the leading contributors to mental illness in people, which also… Read full abstract & cite →

Depression detection machine learning extended- distress analysis interview corpus ensemble-LSRG model mamdani fuzzy
Abstract doi.org/10.14569/IJACSA.2024.0150492 PDF
93

Sustainable Artificial Intelligence: Assessing Performance in Detecting Fake Images

Author 1: Othman A. Alrusaini

Detecting fake images is crucial because they may confuse and influence people into making bad judgments or adopting incorrect stances that might have disastrous consequences. In this study, we investigate not only the effectiveness of artificial intelligence, specifically deep learning and deep neural networks, for fake image detection but also… Read full abstract & cite →

Artificial intelligence image validation deep learning deep neural networks fake images image forgery image manipulations
Abstract doi.org/10.14569/IJACSA.2024.0150493 PDF
94

Federated Convolutional Neural Networks for Predictive Analysis of Traumatic Brain Injury: Advancements in Decentralized Health Monitoring

Author 1: Tripti Sharma Author 2: Desidi Narsimha Reddy Author 3: Chamandeep Kaur Author 4: Sanjiv Rao Godla Author 5: R. Salini Author 6: Adapa Gopi Author 7: Yousef A.Baker El-Ebiary

Traumatic Brain Injury (TBI) is a significant global health concern, often leading to long-term disabilities and cognitive impairments. Accurate and timely diagnosis of TBI is crucial for effective treatment and management. In this paper, we propose a novel federated convolutional neural network (FedCNN) framework for predictive analysis of TBI in… Read full abstract & cite →

Traumatic brain injury federated learning convolutional neural network grasshopper optimization algorithm health monitoring
Abstract doi.org/10.14569/IJACSA.2024.0150494 PDF
95

Enhancing Threat Detection in Financial Cyber Security Through Auto Encoder-MLP Hybrid Models

Author 1: Layth Almahadeen Author 2: Ghayth ALMahadin Author 3: Kathari Santosh Author 4: Mohd Aarif Author 5: Pinak Deb Author 6: Maganti Syamala Author 7: B Kiran Bala

Cyber-attacks have the potential to cause power outages, malfunctions with military equipment, and breaches of sensitive data. Owing to the substantial financial value of the information it contains, the banking sector is especially vulnerable. The number of digital footprints that banks have increases, increasing the attack surface available to hackers… Read full abstract & cite →

Financial cyber security auto encoder multilayer perceptron threat detection hybrid models
Abstract doi.org/10.14569/IJACSA.2024.0150495 PDF
96

Basketball Free Throw Posture Analysis and Hit Probability Prediction System Based on Deep Learning

Author 1: Yuankai Luo Author 2: Yan Peng Author 3: Juan Yang

With the continuous progress of basketball technology and tactics, educators need to adopt new teaching methods to cultivate high-quality athletes who meet the needs of modern basketball development. In basketball teaching, the accuracy of free throw techniques directly affects teaching effectiveness. Therefore, the automated prediction of free throw hits is… Read full abstract & cite →

Deep learning CBAM OpenPose Free throws Posture analysis
Abstract doi.org/10.14569/IJACSA.2024.0150496 PDF
97

Enhancing IoT Network Security: ML and Blockchain for Intrusion Detection

Author 1: N. Sunanda Author 2: K. Shailaja Author 3: Prabhakar Kandukuri Author 4: Krishnamoorthy Author 5: Vuda Sreenivasa Rao Author 6: Sanjiv Rao Godla

Given the proliferation of connected devices and the evolving threat landscape, intrusion detection plays a pivotal role in safeguarding IoT networks. However, traditional methodologies struggle to adapt to the dynamic and diverse settings of IoT environments. To address these challenges, this study proposes an innovative framework that leverages machine learning… Read full abstract & cite →

Intrusion detection IoT networks machine learning random forest red fox optimization blockchain technology
Abstract doi.org/10.14569/IJACSA.2024.0150497 PDF
98

Unveiling Spoofing Attempts: A DCGAN-based Approach to Enhance Face Spoof Detection in Biometric Authentication

Author 1: Vuda Sreenivasa Rao Author 2: Shirisha Kasireddy Author 3: Annapurna Mishra Author 4: R. Salini Author 5: Sanjiv Rao Godla Author 6: Khaled Bedair

Face spoofing attacks have become more dangerous as biometric identification has become more widely used. Through the utilisation of false facial photographs, attackers seek to fool systems in these assaults, endangering the security of biometric authentication devices and perhaps allowing unauthorized access to private information. Effectively recognizing and thwarting such… Read full abstract & cite →

Biometric authentication systems deep convolutional generative adversarial networks face spoof detection synthetic image generation unauthorized access
Abstract doi.org/10.14569/IJACSA.2024.0150498 PDF
99

A Novel Proposal for Improving Economic Decision-Making Through Stock Price Index Forecasting

Author 1: Xu Yao Author 2: Weikang Zeng Author 3: Lei Zhu Author 4: Xiaoxiao Wu Author 5: Di Li

The non-stationary, non-linear, and extremely noisy nature of stock price time series data, which are created from economic factors and systematic and unsystematic risks, makes it difficult to make reliable predictions of stock prices in the securities market. Conventional methods may improve forecasting accuracy, but they can additionally complicate the… Read full abstract & cite →

Hybrid model recurrent neural networks grey wolf optimization stock price prediction
Abstract doi.org/10.14569/IJACSA.2024.0150499 PDF
100

Optimization Method for Digital Twin Manufacturing System Based on NSGA-II

Author 1: Yu Ding Author 2: Longhua Li

In the wave of industrial modernization, a concept that comprehensively covers the product lifecycle has been proposed, namely the digital twin manufacturing system. The digital twin manufacturing system can conduct three-dimensional simulation of the workshop, thereby achieving dynamic scheduling and energy efficiency optimization of the workshop. The optimization of digital… Read full abstract & cite →

Multi-objective optimization NSGA-II Digital twin Production time Production energy consumption
Abstract doi.org/10.14569/IJACSA.2024.01504100 PDF
101

Keyword Acquisition for Language Composition Based on TextRank Automatic Summarization Approach

Author 1: Yan Jiang Author 2: Chunlin Xiang Author 3: Lingtong Li

It is important to extract keywords from text quickly and accurately for composition analysis, but the accuracy of traditional keyword acquisition models is not high. Therefore, in this study, the Best Match 25 algorithm was first used to preprocess the compositions and evaluate the similarity between sentences. Then, TextRank was… Read full abstract & cite →

Language composition keywords best match 25 textrank digests
Abstract doi.org/10.14569/IJACSA.2024.01504101 PDF
102

Investigating Cooling Load Estimation via Hybrid Models Based on the Radial Basis Function

Author 1: Sirui Zhang Author 2: Hao Zheng

To advance energy conservation in cooling systems within buildings, a pivotal technology known as cooling load prediction is essential. Traditional industry computational models typically employ forward or inverse modeling techniques, but these methods often demand extensive computational resources and involve lengthy procedures. However, artificial intelligence (AI) surpasses these approaches, with… Read full abstract & cite →

Cooling load estimation machine learning building energy consumption radial basis functions dynamic arithmetic optimization algorithm golden eagle optimization algorithm
Abstract doi.org/10.14569/IJACSA.2024.01504102 PDF
103

Adaptive Target Region Attention Network-based Human Pose Estimation in Smart Classroom

Author 1: Jianwen Mo Author 2: Guiyun Jiang Author 3: Hua Yuan Author 4: Zhaoyu Shou Author 5: Huibing Zhang

In smart classroom environments, problems such as occlusion and overlap make the acquisition of student pose information challenging. To address these problems, a lightweight human pose estimation model with Adaptive Target Region Attention based on Lite-HRNet is proposed for smart classroom scenarios. Firstly, the Deformable Convolutional Encoding Network (DCEN) module… Read full abstract & cite →

Human pose estimation smart classroom Lite-HRNet deformable convolutional encoding network target region attention
Abstract doi.org/10.14569/IJACSA.2024.01504103 PDF
104

Breast Cancer Classification through Transfer Learning with Vision Transformer, PCA, and Machine Learning Models

Author 1: Juan Gutierrez-Cardenas

Breast cancer is a leading cause of death among women worldwide, making early detection crucial for saving lives and preventing the spread of the disease. Deep Learning and Machine Learning techniques, coupled with the availability of diverse breast cancer datasets, have proven to be effective in assisting healthcare practitioners worldwide… Read full abstract & cite →

Breast cancer vision transformer transfer learning PCA machine learning
Abstract doi.org/10.14569/IJACSA.2024.01504104 PDF
105

Hybrid Algorithm using Rivest-Shamir-Adleman and Elliptic Curve Cryptography for Secure Email Communication

Author 1: Kwame Assa-Agyei Author 2: Kayode Owa Author 3: Tawfik Al-Hadhrami Author 4: Funminiyi Olajide

Email serves as the primary communication system in our daily lives, and to bolster its security and efficiency, many email systems employ Public Key Infrastructure (PKI). However, the convenience of email also introduces numerous security vulnerabilities, including unauthorized access, eavesdropping, identity spoofing, interception, and data tampering. This study is primarily… Read full abstract & cite →

RSA ECC Advanced Encryption Standard encryption decryption signature generation verification key exchange time hybrid encryption
Abstract doi.org/10.14569/IJACSA.2024.01504105 PDF
106

Federated Machine Learning for Epileptic Seizure Detection using EEG

Author 1: S. Vasanthadev Suryakala Author 2: T. R. Sree Vidya Author 3: S. Hari Ramakrishnans

Early seizure detection is difficult with epilepsy. This use of Electroencephalography (EEG) data has proven transformational, however standard centralized machine learning algorithms have privacy and generalization issues. A decentralized approach to epileptic seizure detection using Federated Machine Learning (FML) is presented in this research. The concentration of critical EEG data… Read full abstract & cite →

Federal Machine Learning (FML) electroencephalography epileptic seizure cross-decentralization health care sensitivity
Abstract doi.org/10.14569/IJACSA.2024.01504106 PDF
107

Impact of the IoT Integration and Sustainability on Competition Within an Oligopolistic 3PL Market

Author 1: Kenza Izikki Author 2: Aziz Ait Bassou Author 3: Mustapha Hlyal Author 4: Jamila El Alami

The third party logistics (3PL) sector holds a crucial role in modern supply chains, streamlining the movement of goods and optimizing logistics operations. The 3PL industry’s journey towards digitalization and sustainability reflects a crucial strategy to create an efficient and resilient supply chain. It is increasingly integrating Internet of Things… Read full abstract & cite →

Third party logistics internet of things sustainability oligopoly game theory
Abstract doi.org/10.14569/IJACSA.2024.01504107 PDF
108

Unified Approach for Scalable Task-Oriented Dialogue System

Author 1: Manisha Thakkar Author 2: Nitin Pise

Task-oriented dialogue (TOD) systems are currently the subject of extensive research owing to their immense significance in the fields of human-computer interaction and natural language processing. These systems assist users to accomplish certain tasks efficiently. However, most commercial TOD systems rely on handcrafted rules and offer functionalities in a single… Read full abstract & cite →

Task-oriented dialogue system unified adaptive multi-domain large language models prompts
Abstract doi.org/10.14569/IJACSA.2024.01504108 PDF
109

Day Trading Strategy Based on Transformer Model, Technical Indicators and Multiresolution Analysis

Author 1: Salahadin A. Mohammed

Stock prices are very volatile because they are affected by infinite number of factors, such as economical, social, political, and human behavior. This makes finding consistently profitable day trading strategy extremely challenging and that is why an overwhelming majority of stock traders loose money over time. Professional day traders, who… Read full abstract & cite →

Artificial neural network saudi stock exchange machine learning deep learning transformer model stock price prediction time series analysis technical analysis multiresolution analysis
Abstract doi.org/10.14569/IJACSA.2024.01504109 PDF
110

Multi-Granularity Feature Fusion for Enhancing Encrypted Traffic Classification

Author 1: Quan Ding Author 2: Zhengpeng Zha Author 3: Yanjun Li Author 4: Zhenhua Ling

Encrypted traffic classification, a pivotal process in network security and management, involves analyzing and categorizing data traffic that has been encrypted for privacy and security. This task demands the extraction of distinctive and robust feature representations from content-concealed data to ensure accurate and reliable classification. Traditional approaches have focused on… Read full abstract & cite →

Encrypted traffic classification BERT multi-granularity fusion
Abstract doi.org/10.14569/IJACSA.2024.01504110 PDF
111

Optimization of PID Controller Parameter using the Geometric Mean Optimizer

Author 1: Osama Abdellatif Author 2: Mohamed Issa Author 3: Ibrahim Ziedan

The PID controller is a crucial element in numerous engineering applications. However, a significant challenge with PID lies in selecting optimal parameter values. Conventional methods need extra tunning and may not yield the best performance. In this study, a recently introduced metaheuristic algorithm, Geometric Mean Optimizer (GMO), is employed to… Read full abstract & cite →

Metaheuristics PID controller GMO DC motor
Abstract doi.org/10.14569/IJACSA.2024.01504111 PDF
112

Blockchain-Driven Decentralization of Electronic Health Records in Saudi Arabia: An Ethereum-Based Framework for Enhanced Security and Patient Control

Author 1: Atef Masmoudi Author 2: Maha Saeed

In the rapidly evolving landscape of e-HealthCare in Saudi Arabia, enhancing the security and integrity of Electronic Health Records (EHRs) is imperative. Existing systems encounter challenges stemming from centralized storage, vulner-able data integrity, susceptibility to power failures, and issues of ownership by entities other than the patients themselves. Moreover, the… Read full abstract & cite →

Blockchain Ethereum smart contract Web 3.0 decentralized application electronic health records
Abstract doi.org/10.14569/IJACSA.2024.01504112 PDF
113

Automating Tomato Ripeness Classification and Counting with YOLOv9

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

This article proposes a novel solution to the long-standing issue of ripe (or manual) tomato monitoring and counting, often relying on visual inspection, which is both time-consuming, requires a lot of labor and prone to inaccuracies. By leveraging the power of artificial intelligence (AI) and image analysis techniques, a more… Read full abstract & cite →

Tomato monitoring manual counting Artificial Intelligence (AI) Image analysis techniques YOLO YOLOv9
Abstract doi.org/10.14569/IJACSA.2024.01504113 PDF
114

Harnessing AI to Generate Indian Sign Language from Natural Speech and Text for Digital Inclusion and Accessibility

Author 1: Parul Yadav Author 2: Puneet Sharma Author 3: Pooja Khanna Author 4: Mahima Chawla Author 5: Rishi Jain Author 6: Laiba Noor

Sign language is the fundamental mode of communication for those who are deaf and mute, as well as for individuals with hearing impairments. Regrettably, there has been a dearth of research on Indian Sign Language, primarily due to the lack of adequate grammar and regional variations in such language. Consequently… Read full abstract & cite →

Sign language generation automatic speech recognition speech-to-indian sign language indian sign language digital inclusion and accessibility
Abstract doi.org/10.14569/IJACSA.2024.01504114 PDF
115

Developing a Patient-Centric Healthcare IoT Platform with Blockchain and Smart Contract Data Management

Author 1: Duc B. T Author 2: Trung P. H. T Author 3: Trong N. D. P Author 4: Phuc N. T Author 5: Khoa T. D Author 6: Khiem H. G Author 7: Nam B. T Author 8: Bang L. K

The Internet of Things (IoT) has been rapidly integrated into various industries, with healthcare emerging as a key area of impact. A notable development in this sector is the IoHT-MBA system, a specialized Internet of Healthcare Things (IoHT) framework. This system utilizes a microservice approach combined with a brokerless architecture… Read full abstract & cite →

Medical test result blockchain smart contract NFT Ethereum Fantom polygon binance smart chain
Abstract doi.org/10.14569/IJACSA.2024.01504115 PDF
116

GROCAFAST: Revolutionizing Grocery Shopping for Seamless Convenience and Enhanced User Experience

Author 1: Abeer Hakeem Author 2: Layan Fakhurji Author 3: Raneem Alshareef Author 4: Elaf Aloufi Author 5: Manar Altaiary Author 6: Afraa Attiah Author 7: Linda Mohaisen

This paper presents the Smart Grocery Shopping system (GROCAFAST), a system for optimizing the grocery shopping experience and improving efficiency for shoppers. The GROCAFAST system consists of a mobile app and a server component. The mobile app allows shoppers to create, manage, and update grocery lists while providing store navigation… Read full abstract & cite →

Grocery shopping app route map grocery shopping experience dijkstra’s algorithm
Abstract doi.org/10.14569/IJACSA.2024.01504116 PDF
117

New Trust Management Scheme Based on Blockchain and KNN Reinforcement Learning Algorithm

Author 1: Ahdab Hulayyil Aljohani Author 2: Abdulaziz Al-shammri

There has been a continual rise in the quantity of smart and autonomous automobiles in recent decades. the effectiveness of communication among vehicles in Vehicular Ad-hoc Networks (VANET) is critical for ensuring the safety of drivers’ lives. the primary objective of VANET is to share critical information regarding life-threatening events… Read full abstract & cite →

Vehicular Ad hoc Networks (VANETs) Blockchain trust management reinforcement learning algorithm privacy preservation network security
Abstract doi.org/10.14569/IJACSA.2024.01504117 PDF
118

An Efficiency Hardware Design for Lane Detector Systems

Author 1: Duc Khai Lam

The Hough Transform (HT) algorithm is a popular method for lane detection based on the 'voting' process to extract complete lines. The voting process is derived from the HT algorithm and then executed in parameter space (ρ, θ) to identify the 'votes' with the highest count, meaning that image points… Read full abstract & cite →

FPGA Hough transform look up table lane detector autonomous vehicle
Abstract doi.org/10.14569/IJACSA.2024.01504118 PDF
119

Predictor Model for Chronic Kidney Disease using Adaptive Gradient Clipping with Deep Neural Nets

Author 1: Neeraj Sharma Author 2: Praveen Lalwani

This research aims to develop computer vision based predictive model for the three prominent kidney ailments namely Cyst, Stone, and Tumor which are common renal disorders that require timely medical intervention. This classification model is tested and trained using the multi-class CT Kidney Dataset which contains 12,446 images collected from… Read full abstract & cite →

CT Kidney VGG16 ResNet50 InceptionV3 gradient clipping image processing multiclass classification
Abstract doi.org/10.14569/IJACSA.2024.01504119 PDF
120

Development of an Educational Robot for Exploring the Internet of Things

Author 1: Zhumaniyaz Mamatnabiyev Author 2: Christos Chronis Author 3: Iraklis Varlamis Author 4: Meirambek Zhaparov

Educational robots, when integrated into STEM (Science, Technology, Engineering, and Mathematics) education across a range of age groups, serve to enhance learning experiences by facilitating hands-on activities. These robots are particularly instrumental in the realm of Internet of Things (IoT) education, guiding learners from basic to advanced applications. This paper… Read full abstract & cite →

Educational robots Internet of Things IoT Education Arduino for Education IoT Educational Kit
Abstract doi.org/10.14569/IJACSA.2024.01504120 PDF
121

Improving Potato Diseases Classification Based on Custom ConvNeXtSmall and Combine with the Explanation Model

Author 1: Huong Hoang Luong

Potatoes are short-term crops grown for harvesting tubers. It is a type of tuber that grows on roots and is the fourth most common crop after rice, wheat, and corn. Fresh potatoes can also be used in an incredible variety of dishes by baking, boiling, or frying them. Moreover, the… Read full abstract & cite →

Potato disease classification fine-tuning transfer learning Convolutional Neural Network (CNN) k-means clustering Gradient-weighted Class Activation Mapping (Grad-CAM)
Abstract doi.org/10.14569/IJACSA.2024.01504121 PDF
122

Dynamic Task Offloading Optimization in Mobile Edge Computing Systems with Time-Varying Workloads Using Improved Particle Swarm Optimization

Author 1: Mohammad Asique E Rasool Author 2: Anoop Kumar Author 3: Asharul Islam

Mobile edge computing (MEC) enables offloading of compute-intensive and latency-sensitive tasks from resource-constrained mobile devices to servers at the network edge. This paper considers the dynamic optimization of task offloading in multi-user multi-server MEC systems with time-varying task workloads. The arrival times and computational demands of tasks are modeled as… Read full abstract & cite →

Particle Swarm Optimization (PSO) Mobile Edge Computing (MEC) Multi-User Multi-Server systems dynamic load balancing
Abstract doi.org/10.14569/IJACSA.2024.01504122 PDF
123

On the Combination of Multi-Input and Self-Attention for Sign Language Recognition

Author 1: Nam Vu Hoai Author 2: Thuong Vu Van Author 3: Dat Tran Anh

Sign language recognition can be considered as a branch of human action recognition. The deaf-muted community utilizes upper body gestures to convey sign language words. With the rapid development of intelligent systems based on deep learn-ing models, video-based sign language recognition models can be integrated into services and products to… Read full abstract & cite →

Multi-input self-attention deep learning models video-based sign language sign language recognition
Abstract doi.org/10.14569/IJACSA.2024.01504123 PDF
124

Improving Chicken Disease Classification Based on Vision Transformer and Combine with Integrated Gradients Explanation

Author 1: Huong Hoang Luong Author 2: Triet Minh Nguyen

Chicken diseases are an important problem in the livestock industry, affecting the health and production performance of chicken flocks worldwide. These diseases can seriously damage the health of chickens, reduce egg production, or increase mortality, causing great economic losses to farmers. Therefore, detecting and preventing diseases in chickens is a… Read full abstract & cite →

Vision Transformer ViT16 classification chicken disease transfer learning fine-tuning image classification integrated gradients explanation
Abstract doi.org/10.14569/IJACSA.2024.01504124 PDF
125

Rigorous Experimental Analysis of Tabular Data Generated using TVAE and CTGAN

Author 1: Parul Yadav Author 2: Manish Gaur Author 3: Rahul Kumar Madhukar Author 4: Gaurav Verma Author 5: Pankaj Kumar Author 6: Nishat Fatima Author 7: Saqib Sarwar Author 8: Yash Raj Dwivedi

Synthetic data generation research has been progressing at a rapid pace and novel methods are being designed every now and then. Earlier, statistical methods were used to learn the distributions of real data and then sample synthetic data from those distributions. Recent advances in generative models have led to more… Read full abstract & cite →

Synthetic data generation tabular data generation data privacy conditional generative adversarial networks variational autoencoder
Abstract doi.org/10.14569/IJACSA.2024.01504125 PDF
126

Packet Loss Concealment Estimating Residual Errors of Forward-Backward Linear Prediction for Bone-Conducted Speech

Author 1: Ohidujjaman Author 2: Nozomiko Yasui Author 3: Yosuke Sugiura Author 4: Tetsuya Shimamura Author 5: Hisanori Makinae

This study proposes a suitable model for packet loss concealment (PLC) by estimating the residual error of the linear prediction (LP) method for bone-conducted (BC) speech. Instead of conventional LP-based PLC techniques where the residual error is ignored, we employ forward-backward linear prediction (FBLP), known as the modified covariance (MC)… Read full abstract & cite →

Autocorrelation method bone-conducted speech modified covariance method packet loss concealment residual error
Abstract doi.org/10.14569/IJACSA.2024.01504126 PDF
127

A Comprehensive Analysis of Network Security Attack Classification using Machine Learning Algorithms

Author 1: Abdulaziz Saeed Alqahtani Author 2: Osamah A. Altammami Author 3: Mohd Anul Haq

As internet usage and connected devices continue to proliferate, the concern for network security among individuals, businesses, and governments has intensified. Cybercriminals exploit these opportunities through various attacks, including phishing emails, malware, and DDoS attacks, leading to disruptions, data exposure, and financial losses. In response, this study investigates the effectiveness… Read full abstract & cite →

Machine learning cyber security intrusion detection network security cyber security
Abstract doi.org/10.14569/IJACSA.2024.01504127 PDF
128

Robust Extreme Learning Machine Based on p-order Laplace Kernel-Induced Loss Function

Author 1: Liutao Luo Author 2: Kuaini Wang Author 3: Qiang Lin

Since the datasets of the practical problems are usually affected by various noises and outliers, the traditional extreme learning machine (ELM) shows low prediction accuracy and significant fluctuation of prediction results when learning such datasets. In order to overcome this shortcoming, the l2 loss function is replaced by the correntropy… Read full abstract & cite →

p-order Laplace kernel-induced loss extreme learning machine robustness iterative reweighted
Abstract doi.org/10.14569/IJACSA.2024.01504128 PDF
IJACSA Journal Cover

Call for Papers - Important Dates

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