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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. 14 Issue 11 (2023)

Open Access | | 146 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

Sentiment-Driven Forecasting LSTM Neural Networks for Stock Prediction-Case of China Bank Sector

Author 1: Shangshang Jin

This study explores the predictive analysis of public sentiment in China's financial market, focusing on the banking sector, through the application of machine learning techniques. Specifically, it utilizes the Baidu Index and Long Short-Term Memory (LSTM) networks. The Baidu Index, akin to China's version of Google Trends, serves as a… Read full abstract & cite →

Machine learning LSTM sentiment forecasting banking sector
Abstract doi.org/10.14569/IJACSA.2023.0141101 PDF
2

Semantic Sampling: Enhancing Recommendation Diversity and User Engagement in the Headspace Meditation App

Author 1: Rohan Singh Rajput Author 2: Christabelle Pabalan Author 3: Akhil Chaturvedi Author 4: Prathamesh Kulkarni Author 5: Adam Brownell

In this paper, we present a clever approach to enhance the performance of sequential recommendation systems, specifically in the context of meditation recommendations within the Headspace app. Our method, termed “Semantic Sampling”, leverages the power of language embeddings and clustering techniques to introduce diversity and novelty in the recommen-dations. We… Read full abstract & cite →

Information retrieval machine learning recom-mender system
Abstract doi.org/10.14569/IJACSA.2023.0141102 PDF
3

State of the Art in Intent Detection and Slot Filling for Question Answering System: A Systematic Literature Review

Author 1: Anis Syafiqah Mat Zailan Author 2: Noor Hasimah Ibrahim Teo Author 3: Nur Atiqah Sia Abdullah Author 4: Mike Joy

A Question Answering System (QAS), also known as a chatbot, is a Natural Language Processing (NLP) application that automatically provides accurate responses to questions posed by humans in natural language. Intent Detection and Classification are crucial elements in NLP, especially in a task-oriented dialogue system. In this paper, we conduct… Read full abstract & cite →

Intent detection intent classification slot filling question answering system
Abstract doi.org/10.14569/IJACSA.2023.0141103 PDF
4

Enhancing Vehicle Safety: A Comprehensive Accident Detection and Alert System

Author 1: Jamil Abedalrahim Jamil Alsayaydeh Author 2: Mohd Faizal bin Yusof Author 3: Mohamad Amirul Aliff bin Abdillah Author 4: Ahmed Jamal Abdullah Al-Gburi Author 5: Safarudin Gazali Herawan Author 6: Andrii Oliinyk

This research pioneers a ground-breaking system meticulously engineered to swiftly detect vehicular accidents and dispatch immediate alerts to both emergency services and pre-assigned contacts. This symphony of cutting-edge technologies includes an accelerometer sensor attuned to detect acceleration in any vector, a dynamic Liquid-Crystal Display (LCD) display for rapid alert dissemination… Read full abstract & cite →

Vehicle accident detection microcontroller-based system accelerometer sensor Global Positioning System (GPS) localization Global System for Mobile (GSM) communication emergency response safety innovation
Abstract doi.org/10.14569/IJACSA.2023.0141104 PDF
5

Design of University Archives Business Data Push System Based on Big Data Mining Technology

Author 1: Zhongke Wang Author 2: Jun Li

Aiming at the problems of low accuracy, recall, coverage and push efficiency of university archives business data, a university archives business data push system based on big data mining technology is designed. Firstly, the overall architecture and topological structure of the university archives business data push system are designed, and… Read full abstract & cite →

Big data mining technology system design business data pus hidden markov model similarity
Abstract doi.org/10.14569/IJACSA.2023.0141105 PDF
6

Augmented Reality SDK Overview for General Application Use

Author 1: Suzanna Author 2: Sasmoko Author 3: Ford Lumban Gaol Author 4: Tanty Oktavia

Augmented Reality Software Development Kits, or as they are commonly called AR SDKs, are useful for developers to build digital objects in AR. This paper presents a comparative study of AR SDKs. This comparison is based on several significant criteria, to select the most suitable SDK. The evaluation used the… Read full abstract & cite →

Augmented reality software development kits AR SDK platform framework AR technology
Abstract doi.org/10.14569/IJACSA.2023.0141106 PDF
7

Automatic Extractive Summarization using GAN Boosted by DistilBERT Word Embedding and Transductive Learning

Author 1: Dongliang Li Author 2: Youyou Li Author 3: Zhigang ZHANG

Text summarization is crucial in diverse fields such as engineering and healthcare, greatly enhancing time and cost efficiency. This study introduces an innovative extractive text summarization approach utilizing a Generative Adversarial Network (GAN), Transductive Long Short-Term Memory (TLSTM), and DistilBERT word embedding. DistilBERT, a streamlined BERT variant, offers significant size… Read full abstract & cite →

Extractive text summarization generative adversarial network transductive learning long short-term memory DistilBERT
Abstract doi.org/10.14569/IJACSA.2023.0141107 PDF
8

Security in Software-Defined Networks Against Denial-of-Service Attacks Based on Increased Load Balancing Efficiency

Author 1: Ying ZHANG Author 2: Hongwei DING

The goal of software-oriented networks (SDNs), which enable centralized control by separating the control layer from the data layer, is to increase manageability and network compatibility. However, this form of network is vulnerable to the control layer going down in the face of a denial-of-service assault because of the centralized… Read full abstract & cite →

Security open balance denial-of-service attacks software-oriented networks
Abstract doi.org/10.14569/IJACSA.2023.0141108 PDF
9

Optimization of Unsupervised Neural Machine Translation Based on Syntactic Knowledge Improvement

Author 1: Aiping Zhou

Unsupervised Neural Machine Translation is a crucial machine translation method that can translate in the absence of a parallel corpus and opens up new avenues for intercultural dialogue. Existing unsupervised neural machine translation models still struggle to deal with intricate grammatical relationships and linguistic structures, which leads to less-than-ideal translation… Read full abstract & cite →

Unsupervised Neural network Machine translation Grammatical knowledge Transformer LSTM
Abstract doi.org/10.14569/IJACSA.2023.0141109 PDF
10

Construction of a Security Defense Model for the University's Cyberspace Based on Machine Learning

Author 1: Wang Bin

In order to ensure the security of university teachers and students using cyberspace, a machine learning based university cyberspace security defense model is constructed. Adopting a compression perception based data collection method for university cyberspace, the data information collection of university cyberspace is completed through sparse representation, compression measurement, and… Read full abstract & cite →

Machine learning University's cyberspace security defense construction of a model compressed sensing non-negative matrix
Abstract doi.org/10.14569/IJACSA.2023.0141110 PDF
11

Investigating Efficiency of Soil Classification System using Neural Network Models

Author 1: Pappala Mohan Rao Author 2: Kunjam Nageswara Rao Author 3: Sitaratnam Gokuruboyina Author 4: Neeli Koti Siva Sai Priyanka

Soil is a vital requirement for agricultural activities providing numerous functionalities restoring both abiotic and biotic materials. There are different types of soils, and each type of soil possesses distinctive characteristics and unique harvesting properties that impact agricultural development in various ways. Generally, farmers in the olden days used to… Read full abstract & cite →

Agricultural convolution neural network soil classification deep learning VGG16 VGG19 InceptionV3 multi-classification ResNet50
Abstract doi.org/10.14569/IJACSA.2023.0141111 PDF
12

An Empirical Study: Automating e-Commerce Product Rating Through an Analysis of Customer Review

Author 1: Uvaaneswary Rajendran Author 2: Salfarina Abdullah Author 3: Khairi Azhar Aziz Author 4: Sazly Anuar

e-Commerce today is a remarkable experience. However, finding and purchasing a right quality product based on numerous product reviews and manual rating in the e-commerce websites utilize much time among the consumers. This paper presents the problems faced by the consumers when buying products in e-commerce websites and a solution… Read full abstract & cite →

e-commerce website sentiment analysis technique manual product rating automated product rating product review
Abstract doi.org/10.14569/IJACSA.2023.0141112 PDF
13

Secure IoT Routing through Manifold Criterion Trust Evaluation using Ant Colony Optimization

Author 1: Afsah Sharmin Author 2: Rashidah Funke Olanrewaju Author 3: Burhan Ul Islam Khan Author 4: Farhat Anwar Author 5: S. M. A. Motakabber Author 6: Nur Fatin Liyana Mohd Rosely Author 7: Aisha Hassan Abdalla Hashim

The paper presents a simplified yet innovative computational framework to enable secure routing for sensors within a vast and dynamic Internet of Things (IoT) environment. In the proposed design methodology, a unique trust evaluation scheme utilizing a modified version of Ant Colony Optimization (ACO) is introduced. This scheme formulates a… Read full abstract & cite →

Internet of things (IoT) secure IoT routing manifold criterion trust evaluation ant colony optimization (ACO) bioinspired computing pheromone management
Abstract doi.org/10.14569/IJACSA.2023.0141113 PDF
14

Analyzing Sentiment in Terms of Online Feedback on Top of Users' Experiences

Author 1: Mohammed Alonazi

Since most businesses today are conducted online, it is crucial that each customer provide feedback on the various items offered. Evaluating online product sentiment and making suggestions using state-of-the-art machine learning and deep learning algorithms requires a comprehensive pipeline. Thus, this paper addresses the need for a comprehensive pipeline to… Read full abstract & cite →

Sentiment analysis product review machine learning recommendation system collaborative filtering exploratory data analysis
Abstract doi.org/10.14569/IJACSA.2023.0141114 PDF
15

Automatic Model for Postpartum Depression Identification using Deep Reinforcement Learning and Differential Evolution Algorithm

Author 1: Sunyuan Shen Author 2: Sheng Qi Author 3: Hongfei Luo

Postpartum depression (PPD) affects approximately 12% of new mothers, posing a significant health concern for both the mother and child. However, many women with PPD do not receive proper care. Preventative interventions are more cost-effective for high-risk women, but identifying those at risk can be challenging. To address this problem… Read full abstract & cite →

Postpartum depression deep reinforcement learning differential evolution algorithm weight initialization artificial neural network
Abstract doi.org/10.14569/IJACSA.2023.0141115 PDF
16

Secure Cloud-Connected Robot Control using Private Blockchain

Author 1: Muhammad Amzie Muhammad Fauzi Author 2: Mohamad Hanif Md Saad Author 3: Sallehuddin Mohamed Haris Author 4: Marizuana Mat Daud

With the increasing demand for remote operations and the challenges posed during the COVID-19 pandemic, industries across various sectors, including logistics, manufacturing, and education, have adopted virtual solutions. Cloud-based robot control has emerged as a viable approach for enabling safe remote operation of robots. However, along with the benefits, there… Read full abstract & cite →

Internet of Things (IoT) robot control cloud computing cybersecurity blockchain
Abstract doi.org/10.14569/IJACSA.2023.0141116 PDF
17

An Edge Computing-based Handgun and Knife Detection Method in IoT Video Surveillance Systems

Author 1: Haibo Liu Author 2: Zhubing HU

Real-time handgun and knife detection on edge devices within the Internet of Things (IoT) video surveillance systems hold paramount importance in ensuring public safety and security. Numerous methods have been explored for handgun and knife detection in video-based surveillance systems, with deep learning-based approaches demonstrating superior accuracy compared to other… Read full abstract & cite →

Real-time detection handgun and knife detection edge devices IoT video surveillance deep learning convolutional neural network
Abstract doi.org/10.14569/IJACSA.2023.0141117 PDF
18

Advanced Seismic Magnitude Classification Through Convolutional and Reinforcement Learning Techniques

Author 1: Qiuyi Lin Author 2: Jin Li

Earthquake Early Warning (EEW) systems are crucial in reducing the dangers associated with earthquakes. This paper delves into the realm of EEWs, focusing on rapidly determining earthquake magnitudes (EMs). Traditional methods for swift magnitude categorization often grapple with challenges such as data disparity and cumbersome processes. Our research introduces an… Read full abstract & cite →

Earthquake early warning the magnitude of the earthquake imbalanced classification artificial bee colony reinforcement learning
Abstract doi.org/10.14569/IJACSA.2023.0141118 PDF
19

Information Retrieval System for Scientific Publications of Lampung University by using VSM, K-Means, and LSA

Author 1: Rahman Taufik Author 2: Didik Kurniawan Author 3: Anie Rose Irawati Author 4: Dewi Asiah Shofiana

The Lampung University repository system is a repository of data related to study, community service, and other scientific works, currently has 37242 documents accessible through repository.lppm.unila.ac.id. Despite the amount of data, its optimal use as an information retrieval remains unrealized, hindering the effective promotion of Lampung University's scientific publication excellence… Read full abstract & cite →

Information retrieval Vector Space Model (VSM) k-means Latent Semantic Analysis (LSA) clustering topic identification scientific publication information
Abstract doi.org/10.14569/IJACSA.2023.0141119 PDF
20

Adaptive Gray Wolf Optimization Algorithm based on Gompertz Inertia Weight Strategy

Author 1: Qiuhua Pan

To solve the problems that the Gray Wolf Optimizer (GWO) convergence speed is not fast enough and the solution accuracy is not high enough, this paper proposes an Adaptive Gray Wolf Optimizer based on Gompertz inertia weighting strategy (GGWO). GGWO uses the characteristics of the Gompertz function to achieve nonlinear… Read full abstract & cite →

Gray wolf optimization algorithm inertia weight adaptive Gompertz function swarm intelligence algorithm
Abstract doi.org/10.14569/IJACSA.2023.0141120 PDF
21

Optimizing Shuttle-Bus Systems in Mega-Events using Computer Modeling: A Case Study of Pilgrims' Transportation System

Author 1: Mohamed S. Yasein Author 2: Esam Ali Khan

Mega-events are held in a city, or more, during a limited time, which requires special attention to the infrastructure and the offered services. The Hajj event, hosted in Makkah - Saudi Arabia, is considered as an excellent example of religious mega-events. The field of computer modeling and simulation is one… Read full abstract & cite →

Computer modeling simulation optimization shuttle-bus systems mega-events hajj
Abstract doi.org/10.14569/IJACSA.2023.0141121 PDF
22

Development of Nursing Process Expert System for Android-based Nursing Student Learning

Author 1: Aristoteles Author 2: Abie Perdana Kusuma Author 3: Anie Rose Irawati Author 4: Dwi Sakethi Author 5: Lisa Suarni Author 6: Dedy Miswar Author 7: Rika Ningtias Azhari

Nurses are professionals who provide health services using a scientific process called nursing. In nursing, problem-solving uses the nursing process which is a critical thinking method, nurses must analyze the data found in patients to diagnose and determine the results and appropriate intervention plans. Prospective nursing students are required to… Read full abstract & cite →

Classification expert system forward chaining blackbox testing android flutter nursing process
Abstract doi.org/10.14569/IJACSA.2023.0141122 PDF
23

Emotional State Prediction Based on EEG Signals using Ensemble Methods

Author 1: Norah Alrebdi Author 2: Amal A. Al-Shargabi

The emotional state is an essential factor that affects mental health. Electroencephalography (EEG) signal analysis is a promising method for detecting emotional states. Although multiple studies exist on EEG emotional signals classification, they have rarely considered processing time as a metric for classification model evaluation. Instead, they used either model… Read full abstract & cite →

Electroencephalograph mental health feature extraction random forest extreme gradient boosting adaptive boost
Abstract doi.org/10.14569/IJACSA.2023.0141123 PDF
24

Selection of a Trustworthy Technique for Fraud Prevention in the Digital Banking Sector

Author 1: Bandar Ali M. Al-Rami Al-Ghamdi

Digital banking fraud poses a threat to the global economy and fintech applications. Sustainable models are essential to address this issue and minimize its economic impact. Hybrid methods have been developed to assess strategies for preventing digital banking fraud, aiding global stakeholders in making well-informed judgments. However, many of these… Read full abstract & cite →

Digital banking fraud analytical network process intuitionistic fuzzy sets fraud prevention and detection
Abstract doi.org/10.14569/IJACSA.2023.0141124 PDF
25

Arabic Regional Dialect Identification (ARDI) using Pair of Continuous Bag-of-Words and Data Augmentation

Author 1: Ahmed H. AbuElAtta Author 2: Mahmoud Sobhy Author 3: Ahmed A. El-Sawy Author 4: Hamada Nayel

Author profiling is the process of finding characteristics that make up an author’s profile. This paper presents a machine learning-based author profiling model for Arabic users, considering the author’s regional dialect as a crucial characteristic. Various classification algorithms have been implemented: decision tree, KNN, multilayer perceptron, random forest, and support… Read full abstract & cite →

Dialect identification continuous Bag-of-Words data augmentation text classification.
Abstract doi.org/10.14569/IJACSA.2023.0141125 PDF
26

Advanced Metering Infrastructure Data Aggregation Scheme Based on Blockchain

Author 1: Hongliang TIAN Author 2: Naiqian ZHENG Author 3: Yuzhi JIAN

Smart grid stands as both the cornerstone of the modern energy system and the pivotal technology for addressing energy-related challenges. Advanced Metering Infrastructure constitute a critical component within the smart grid ecosystem, providing real-time energy consumption data to power utility companies. Advanced Metering Infrastructure enables these companies to make timely… Read full abstract & cite →

Smart grid blockchain advanced metering infrastructure data aggregation
Abstract doi.org/10.14569/IJACSA.2023.0141126 PDF
27

Predicting and Improving Behavioural Factors that Boosts Learning Abilities in Post-Pandemic Times using AI Techniques

Author 1: Jaya Gera Author 2: Ekta Bhambri Marwaha Author 3: Reema Thareja Author 4: Aruna Jain

Quantifying student academic performance has always been challenging as it hinges on several factors including academic progress, personal characteristics and behaviours relating to learning activities. Several research studies are therefore being conducted to identify the factors so that appropriate measures can be conducted by academic institutions, family and the student… Read full abstract & cite →

Academic performance machine learning chatbot educational data mining learning analytics
Abstract doi.org/10.14569/IJACSA.2023.0141127 PDF
28

Sentiment Analysis Predictions in Digital Media Content using NLP Techniques

Author 1: Abdulrahman Radaideh Author 2: Fikri Dweiri

In the current digital landscape, understanding sentiment in digital media is crucial for informed decision-making and content quality. The primary objective is to improve decision-making processes and enhance content quality within this dynamic environment. To achieve this, a comprehensive comparative analysis of NLP for tweet sentiment analysis was conducted, revealing… Read full abstract & cite →

Sentiment analysis digital media decision-making quality assurance NLP
Abstract doi.org/10.14569/IJACSA.2023.0141128 PDF
29

An Enhanced Approach for Realizing Robust Security and Isolation in Virtualized Environments

Author 1: Rawan Abuleil Author 2: Samer Murrar Author 3: Mohammad Shkoukani

Transitioning into the next generation of supercomputing resources, we’re faced with expanding user bases and diverse workloads, increasing the demand for improved security measures and deeper software compartmentalization. This is especially pertinent for virtualization, a key cloud computing component that’s at risk from attacks due to hypervisors’ integration into privileged… Read full abstract & cite →

Virtual Machine (VM) High-Performance Computing (HPC) cybersecurity hypervisor security
Abstract doi.org/10.14569/IJACSA.2023.0141129 PDF
30

Efficient Evaluation of SLAM Methods and Integration of Human Detection with YOLO Based on Multiple Optimization in ROS2

Author 1: Hoang Tran Ngoc Author 2: Nghi Nguyen Vinh Author 3: Nguyen Trung Nguyen Author 4: Luyl-Da Quach

In the realm of robotics, indoor robotics is an increasingly prominent field, and enhancing robot performance stands out as a crucial concern. This research undertakes a comparative analysis of various Simultaneous Localization and Mapping (SLAM) algorithms with the overarching objective of augmenting the navigational capabilities of robots. This is accomplished… Read full abstract & cite →

Indoor robotic SLAM ROS2 Robot model Human detection YOLO
Abstract doi.org/10.14569/IJACSA.2023.0141130 PDF
31

Optimizing Network Intrusion Detection with a Hybrid Adaptive Neuro Fuzzy Inference System and AVO-based Predictive Analysis

Author 1: Sweety Bakyarani. E Author 2: Anil Pawar Author 3: Sridevi Gadde Author 4: Eswar Patnala Author 5: P. Naresh Author 6: Yousef A. Baker El-Ebiary

Protecting data and computer systems, as well as preserving the accessibility, integrity, and confidentiality of vital information in the face of constantly changing cyberthreats, requires the vital responsibility of detecting network intrusions. Existing intrusion detection models have limits in properly capturing and interpreting complex patterns in network behavior, which frequently… Read full abstract & cite →

Network intrusion cyberthreats normalization African vulture optimization data cleaning
Abstract doi.org/10.14569/IJACSA.2023.0141131 PDF
32

Enhancing Style Transfer with GANs: Perceptual Loss and Semantic Segmentation

Author 1: A Satchidanandam Author 2: R. Mohammed Saleh Al Ansari Author 3: A L Sreenivasulu Author 4: Vuda Sreenivasa Rao Author 5: Sanjiv Rao Godla Author 6: Chamandeep Kaur

The goal of artistic style translation is to combine an image's substance with an equivalent image's spirit of innovation. Current approaches are unable to consistently capture complex stylistic elements and maintain uniform stylization over semantic segments, which results in artefacts. Also suggest a novel approach which blends subjective loss algorithms… Read full abstract & cite →

Artistic style transfer Generative Adversarial Networks (GANs) semantic segmentation visual fidelity deep Convolutional Neural Networks (deep-CNN)
Abstract doi.org/10.14569/IJACSA.2023.0141132 PDF
33

Securing Patient Medical Records with Blockchain Technology in Cloud-based Healthcare Systems

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

Blockchain technology presents a promising solution to myriad challenges pervasive in the healthcare domain, particularly concerning the secure and efficient management of burgeoning health information technology (HIT) data. This paper delineates a novel blockchain-based approach to enhance various aspects of healthcare management, including data accuracy, drug prescriptions, pregnancy data, supply… Read full abstract & cite →

Security blockchain cloud hyperledger
Abstract doi.org/10.14569/IJACSA.2023.0141133 PDF
34

Hyperchaotic Image Encryption System Based on Deep Learning LSTM

Author 1: Shuangyuan Li Author 2: Mengfan Li Author 3: Qichang Li Author 4: Yanchang Lv

This paper introduces an advanced method for enhancing the security of image transmission. It presents a novel color image encryption algorithm that combines hyperchaotic dynamics and deep learning medium and long short-term memory (LSTM) networks. Firstly, the chaotic sequence is generated using the Lorenz hyperchaotic system, then the Lorenz chaotic… Read full abstract & cite →

Image encryption Lorenz Chaotic System LSTM model deep learning DNA encoding
Abstract doi.org/10.14569/IJACSA.2023.0141134 PDF
35

Thai Finger-Spelling using Vision Transformer

Author 1: Kullawat Chaowanawatee Author 2: Kittasil Silanon Author 3: Thitinan Kliangsuwan

In this paper, we present a finger-spelling recognition system that is based on Thai Sign Language (TFS) and employs a deep learning model called vision transformer. We extracted the 15 characters of the Thai alphabet from publicly available and our collected datasets to establish the recognition system. To train the… Read full abstract & cite →

Thai finger-spelling vision transformer deep learning image recognition
Abstract doi.org/10.14569/IJACSA.2023.0141135 PDF
36

Investigation of Deep Learning Based Semantic Segmentation Models for Autonomous Vehicles

Author 1: Xiaoyan Wang Author 2: Huizong Li

Semantic segmentation plays a pivotal role in enhancing the perception capabilities of autonomous vehicles and self-driving cars, enabling them to comprehend and navigate complex real-world environments. Numerous techniques have been developed to achieve semantic segmentation. Still, the paper emphasizes the effectiveness of deep learning approaches because they have demonstrated impressive… Read full abstract & cite →

Semantic segmentation autonomous vehicles deep learning approaches performance analysis accuracy inference time
Abstract doi.org/10.14569/IJACSA.2023.0141136 PDF
37

Smart Cities, Smarter Roads: A Review of Leveraging Cutting-Edge Technologies for Intelligent Event Detection from Social Media

Author 1: Ebtesam Ahmad Alomari Author 2: Rashid Mehmood

The rapidly evolving landscape of smart cities and intelligent transportation systems makes the timely detection of traffic events a critical element for optimizing urban mobility. Furthermore, social media emerges as a valuable source of real-time information, with users acting as active sensors who spontaneously share observations and experiences related to… Read full abstract & cite →

Mobility smart cities event detection social media big data analytics
Abstract doi.org/10.14569/IJACSA.2023.0141137 PDF
38

A Proposed Roadmap for Optimizing Predictive Maintenance of Industrial Equipment

Author 1: Maria Eddarhri Author 2: Mustapha Hain Author 3: Jihad Adib Author 4: Abdelaziz Marzak

Now-a-days, the maintenance management of industrial equipment, particularly in the aeronautical industry, has evolved into a substantial challenge and a critical concern for the sector. Aeronautical wiring companies are currently grappling with escalating difficulties in equipment maintenance. This paper proposes an intelligent system for the automated detection of machine failures… Read full abstract & cite →

Predictive maintenance intelligent system aeronautical wiring companies machine learning IIoT
Abstract doi.org/10.14569/IJACSA.2023.0141138 PDF
39

Research on 3D Target Detection Algorithm Based on PointFusion Algorithm Improvement

Author 1: Jun Wang Author 2: Shuai Jiang Author 3: Linglang Zeng Author 4: Ruiran Zhang

With the continuous development of automatic driving technology, the requirements for the accuracy of 3D target detection in complex traffic scenes are getting higher and higher. To solve the problems of low recognition rate, long detection time, and poor robustness of traditional detection methods, this paper proposes a new method… Read full abstract & cite →

Neural network target detection autonomous driving PointFusion deep learning
Abstract doi.org/10.14569/IJACSA.2023.0141139 PDF
40

Beyond the Norm: A Modified VGG-16 Model for COVID-19 Detection

Author 1: Shimja M Author 2: K. Kartheeban

The outbreak of Coronavirus Disease 2019 (COVID-19) in the initial days of December 2019 has severely harmed human health and the world's overall condition. There are currently five million instances that have been confirmed, and the unique virus is continuing spreading quickly throughout the entire world. The manual Reverse Transcription-Polymerase… Read full abstract & cite →

Covid-19 coronavirus artificial intelligence deep learning transfer learning VGG-16 performance metrics
Abstract doi.org/10.14569/IJACSA.2023.0141140 PDF
41

Optimizing Crack Detection: The Integration of Coarse and Fine Networks in Image Segmentation

Author 1: Hoanh Nguyen Author 2: Tuan Anh Nguyen

In recent years, the automation of detecting structural deformities, particularly cracks, has become vital across a wide range of applications, spanning from infrastructure maintenance to quality assurance. While numerous methods, ranging from traditional image processing to advanced deep learning architectures, have been introduced for crack segmentation, reliable and precise segmentation… Read full abstract & cite →

Deep learning crack segmentation coarse-to-fine strategy image segmentation
Abstract doi.org/10.14569/IJACSA.2023.0141141 PDF
42

Enhanced Land Use and Land Cover Classification Through Human Group-based Particle Swarm Optimization-Ant Colony Optimization Integration with Convolutional Neural Network

Author 1: Moresh Mukhedkar Author 2: Chamandeep Kaur Author 3: Divvela Srinivasa Rao Author 4: Shweta Bandhekar Author 5: Mohammed Saleh Al Ansari Author 6: Maganti Syamala Author 7: Yousef A.Baker El-Ebiary

Reliable classification of Land Use and Land Cover (LULC) using satellite images is essential for disaster management, environmental monitoring, and urban planning. This paper introduces a unique method that combines a Convolutional Neural Network (CNN) with Human Group-based Particle Swarm Optimization (HPSO) and Ant Colony Optimization (ACO) algorithms to improve… Read full abstract & cite →

Land use and land cover human group-based particle swarm optimization ant colony optimization convolutional neural network satellite image
Abstract doi.org/10.14569/IJACSA.2023.0141142 PDF
43

IAM-TSP: Iterative Approximate Methods for Solving the Travelling Salesman Problem

Author 1: Esra’a Alkafaween Author 2: Samir Elmougy Author 3: Ehab Essa Author 4: Sami Mnasri Author 5: Ahmad S. Tarawneh Author 6: Ahmad Hassanat

TSP is a well-known combinatorial optimization problem with several practical applications. It is an NP-hard problem, which means that the optimal solution for huge numbers of examples is computationally impractical. As a result, researchers have focused their efforts on devising efficient algorithms for obtaining approximate solutions to the TSP. This… Read full abstract & cite →

Greedy algorithms TSP NP-Hard problems polynomial time algorithms combinatorial problems optimization methods
Abstract doi.org/10.14569/IJACSA.2023.0141143 PDF
44

An Overview of Different Deep Learning Techniques Used in Road Accident Detection

Author 1: Vinu Sherimon Author 2: Sherimon P. C Author 3: Alaa Ismaeel Author 4: Alex Babu Author 5: Sajina Rose Wilson Author 6: Sarin Abraham Author 7: Johnsymol Joy

Every year, numerous lives are tragically lost because of traffic accidents. While many factors may lead to these accidents, one of the most serious issues is the emergency services' delayed response. Often, valuable time is lost due to a lack of information or difficulty determining the location and severity of… Read full abstract & cite →

Deep learning road traffic road accident detection MLP CNN LSTM DenseNet RNN inception V3
Abstract doi.org/10.14569/IJACSA.2023.0141144 PDF
45

IoT-based Autonomous Search and Rescue Drone for Precision Firefighting and Disaster Management

Author 1: Shubeeksh Kumaran Author 2: V Aditya Raj Author 3: Sangeetha J Author 4: V R Monish Raman

Disaster management is a line of work that deals with the lives of people, such work requires utmost precision, accuracy, and tough decision-making under critical situations. Our research aims to utilize Internet of Things (IoT)-based autonomous drones to provide detailed situational awareness and assessment of these dangerous areas to rescue… Read full abstract & cite →

Search and rescue firefighting internet of things disaster management
Abstract doi.org/10.14569/IJACSA.2023.0141145 PDF
46

Contactless Palm Vein Recognition System with Integrated Learning Approach System

Author 1: Ram Gopal Musunuru Author 2: T Sivaprakasam Author 3: G Krishna Kishore

Palm Vein Recognition (PVR) is a new biometric authentication technology that provides both security and convenience. This paper describes a contactless PVR system (CPVR) that uses an integrated learning approach (ILA) to recognise the palm veins from the given input images while ensuring user comfort and ease of use. Contactless… Read full abstract & cite →

Palm Vein Recognition (PVR) Light Gradient Boosting Machine (LightGBM) Transfer Learning Integrated Learning Approach (ILA)
Abstract doi.org/10.14569/IJACSA.2023.0141146 PDF
47

Linear and Nonlinear Analysis of Photoplethysmogram Signals and Electrodermal Activity to Recognize Three Different Levels of Human Stress

Author 1: Yan Su Author 2: Yuanyuan Li Author 3: Shumin Zhang Author 4: Hui Wang

All human beings experience different levels of psychological stress during their daily activities, and stress is an integral part of human life. So far, few studies have attempted to identify different levels of stress by analyzing physiological signals. However, it should be noted that developing a practical system for detecting… Read full abstract & cite →

Stress detection biological signal linear analysis nonlinear analysis classification
Abstract doi.org/10.14569/IJACSA.2023.0141147 PDF
48

Development of a Framework for Classification of Impulsive Urban Sounds using BiLSTM Network

Author 1: Nazbek Katayev Author 2: Aigerim Altayeva Author 3: Bayan Abduraimova Author 4: Nurgul Kurmanbekkyzy Author 5: Zhumabay Madibaiuly Author 6: Bakhytzhan Kulambayev

Urban environments are awash with myriad sounds, among which impulsive noises stand distinct due to their brief and often disruptive nature. As cities evolve and expand, the accurate classification and management of these impulsive sounds become paramount for urban planners, environmental scientists, and public health advocates. This paper introduces a… Read full abstract & cite →

Impulsive sound machine learning deep learning CNN LSTM classification
Abstract doi.org/10.14569/IJACSA.2023.0141148 PDF
49

Research on Evaluation Method of Urban Human Settlement Environment Quality Based on Back Propagation Neural Network

Author 1: Siyuan Zhang Author 2: Wenbo Song

In order to improve people's living experience, a method for evaluating the quality of urban human settlements based on back propagation neural network is proposed. Firstly, the initial evaluation index system is constructed, the initial evaluation index system is screened, and the final evaluation index system is constructed by using… Read full abstract & cite →

Back propagation neural network urban human settlements quality evaluation morbidity index genetic algorithm
Abstract doi.org/10.14569/IJACSA.2023.0141149 PDF
50

Basketball Motion Recognition Model Analysis Based on Perspective Invariant Geometric Features in Skeleton Data Extraction

Author 1: Jiaojiao Lu

The study proposes a recognition method based on skeleton data to address the basketball action recognition, especially those posed by viewpoint changes in videos. The key of this method is to extract geometric features of viewpoint invariance and combine them with spatio-temporal feature fusion techniques. In addition, the study constructs… Read full abstract & cite →

Skeleton data perspective invariance geometric features basketball recognition spatio-temporal feature fusion
Abstract doi.org/10.14569/IJACSA.2023.0141150 PDF
51

Application of Data Mining Technology with Improved Clustering Algorithm in Library Personalized Book Recommendation System

Author 1: Xiao Lin Author 2: Wenjuan Guan Author 3: Ying Zhang

The information construction work of university libraries is becoming increasingly perfect. However, the massive amount of data poses significant challenges to the personalized recommendation of books. Cluster analysis has always been an important research topic in data mining technology, and it has a wide range of application fields. Clustering algorithm… Read full abstract & cite →

Peak density distance optimization warhill algorithm collaborative filtering book recommendations
Abstract doi.org/10.14569/IJACSA.2023.0141151 PDF
52

Workforce Planning for Cleaning Services Operation using Integer Programming

Author 1: Mandy Lim Man Yee Author 2: Rosshairy Abd Rahman Author 3: Nerda Zura Zaibidi Author 4: Syariza Abdul-Rahman Author 5: Norhafiza Mohd Noor

The cleaning services industry in Malaysia faces significant challenges in effectively managing its workforce. Workforce planning, a critical procedure that aligns employee skills with suitable positions at the right time, is becoming increasingly essential across various organizations, including postal delivery and cleaning services. However, the absence of proper workforce planning… Read full abstract & cite →

Workforce planning cleaning services industry optimization approach integer programming
Abstract doi.org/10.14569/IJACSA.2023.0141152 PDF
53

Tailored Expert Finding Systems for Vietnamese SMEs: A Five-step Framework

Author 1: Thi Thu Le Author 2: Xuan Lam Pham Author 3: Thanh Huong Nguyen

This study addresses the underexplored area of EFSs (EFS) tailored for business applications, with a specific focus on supporting Small and Medium Enterprises (SMEs). The principal objective of this research is to develop an EFS designed to cater to the needs of Vietnamese SMEs. The study methodology involves conducting in-depth… Read full abstract & cite →

Expert Finding System (EFS) Small and Medium-sized Enterprises (SMEs) experts Vietnamese expert resources business expertise identification
Abstract doi.org/10.14569/IJACSA.2023.0141153 PDF
54

A Zero-Trust Model for Intrusion Detection in Drone Networks

Author 1: Said OUIAZZANE Author 2: Malika ADDOU Author 3: Fatimazahra BARRAMOU

Today's worldwide introduction of drone fleets in a range of industrial applications has led to numerous network security issues, opening drones up to cyberthreats. In response to these challenges, an innovative approach has been proposed to protect drone fleet networks against potentially dangerous cyberattacks. Indeed, drones are considered as flying… Read full abstract & cite →

Fleet of drones security zero trust intrusions cybersecurity zero day Multi-Agent
Abstract doi.org/10.14569/IJACSA.2023.0141154 PDF
55

Flood Prediction using Hydrologic and ML-based Modeling: A Systematic Review

Author 1: A Fares Hamad Aljohani Author 2: Ahmad. B. Alkhodre Author 3: Adnan Ahamad Abi Sen Author 4: Muhammad Sher Ramazan Author 5: Bandar Alzahrani Author 6: Muhammad Shoaib Siddiqui

Flooding, caused by the overflow of water bodies beyond their natural boundaries, has severe environmental and socioeconomic consequences. To effectively predict and mitigate flood events, accurate and reliable flood modeling techniques are essential. This study provides a comprehensive review of the latest modeling techniques used in flood prediction, classifying them… Read full abstract & cite →

Flood prediction hydrologic model machine learning systematic review
Abstract doi.org/10.14569/IJACSA.2023.0141155 PDF
56

An Improved Depth Estimation using Stereo Matching and Disparity Refinement Based on Deep Learning

Author 1: Deepa Author 2: Jyothi K Author 3: Abhishek A Udupa

Stereo matching techniques are a vital subject in computer vision. It focuses on finding accurate disparity maps that find its use in several applications namely reconstruction of a 3D scene, navigation of robot, augmented reality. It is a method of obtaining corresponding matching point in stereo images to get disparity… Read full abstract & cite →

Census transform deep learning depth generative adversarial network occlusion stereo matching
Abstract doi.org/10.14569/IJACSA.2023.0141156 PDF
57

Federated-Learning Topic Modeling Based Text Classification Regarding Hate Speech During COVID-19 Pandemic

Author 1: Muhammad Kamran Author 2: Ammar Saeed Author 3: Ahmed Almaghthawi

One of the most challenging tasks in knowledge discovery is extracting the semantics of the content regarding emotional context from the natural language text. The COVID-19 pandemic gave rise to many serious concerns and has led to several controversies including spreading of false news and hate speech. This paper particularly… Read full abstract & cite →

Knowledge extraction text mining pandemics and society hate speech Islamophobia
Abstract doi.org/10.14569/IJACSA.2023.0141157 PDF
58

A Neural Network-based Approach for Apple Leaf Diseases Detection in Smart Agriculture Application

Author 1: Shengjie Gan Author 2: Defeng Zhou Author 3: Yuan Cui Author 4: Jing Lv

Plant diseases significantly harm agriculture, which has an impact on nations' economies and levels of food security. Early plant disease detection is essential in smart agriculture. For the diagnosis of plant diseases, a number of methods, including imaging, have been used recently. Some of the existing methods for plant disease… Read full abstract & cite →

Smart agriculture plant disease apple leaf disease image processing neural network
Abstract doi.org/10.14569/IJACSA.2023.0141158 PDF
59

The Use of Hand Gestures as a Tool for Presentation

Author 1: Hope Orovwode Author 2: John Amanesi Abubakar Author 3: Onuora Chidera Gaius Author 4: Ademola Abdullkareem

Our hands play a crucial role in daily activities, serving as a primary tool for interacting with technology. This paper explores using hand gestures to control presentations, offering a dynamic alternative to traditional devices like mice or keyboards. These conventional methods often limit presenters to a fixed position and depend… Read full abstract & cite →

Hand gesture linear classifier motion classifier LSTM interface
Abstract doi.org/10.14569/IJACSA.2023.0141159 PDF
60

SmishGuard: Leveraging Machine Learning and Natural Language Processing for Smishing Detection

Author 1: Saleem Raja Abdul Samad Author 2: Pradeepa Ganesan Author 3: Justin Rajasekaran Author 4: Madhubala Radhakrishnan Author 5: Hariraman Ammaippan Author 6: Vinodhini Ramamurthy

SMS facilitates the transmission of concise text messages between mobile phone users, serving a range of functions in personal and business domains such as appointment confirmation, authentication, alerts, notifications, and banking updates. It plays a vital role in daily communication due to its accessibility, reliability, and compatibility. However, SMS unintentionally… Read full abstract & cite →

Smishing phishing SMS machine learning natural language processing TF-IDF
Abstract doi.org/10.14569/IJACSA.2023.0141160 PDF
61

Sleep Apnea Detection Method Based on Improved Random Forest

Author 1: Xiangkui Wan Author 2: Yang Liu Author 3: Liuwang Yang Author 4: Chunyan Zeng Author 5: Danni Hao

Random forest (RF) helps to solve problems such as the detection of sleep apnea (SA) by constructing multiple decision trees, but there is no definite rule for the selection of input features in the model. In this paper, we propose a SA detection method based on fuzzy C-mean clustering (FCM)… Read full abstract & cite →

Sleep apnea fuzzy c-means backward feature elimination method random forest
Abstract doi.org/10.14569/IJACSA.2023.0141161 PDF
62

Graph Anomaly Detection with Graph Convolutional Networks

Author 1: Aabid A. Mir Author 2: Megat F. Zuhairi Author 3: Shahrulniza Musa

Anomaly detection in network data is a critical task in various domains, and graph-based approaches, particularly Graph Convolutional Networks (GCNs), have gained significant attention in recent years. This paper provides a comprehensive analysis of anomaly detection techniques, focusing on the importance and challenges of network anomaly detection. It introduces the… Read full abstract & cite →

Anomaly detection deep learning dynamic graphs Graph Convolutional Networks (GCNs) Graph Neural Networks (GNNs) network data
Abstract doi.org/10.14569/IJACSA.2023.0141162 PDF
63

Ascertaining Speech Emotion using Attention-based Convolutional Neural Network Framework

Author 1: Ashima Arya Author 2: Vaishali Arya Author 3: Neha Kohli Author 4: Namrata Sukhija Author 5: Ashraf Osman Ibrahim Author 6: Salil Bharany Author 7: Faisal Binzagr Author 8: Farkhana Binti Muchtar Author 9: Mohamed Mamoun

Conversation among people is a profuse form of interaction that also carries emotional information. Speech input has been the subject of numerous studies over the last ten years, and it is now crucial for human-computer connection, as well as for medical care, privacy, and stimulation. This research aims to evaluate… Read full abstract & cite →

Convolutional neural network emotions speech transfer learning models spectrogram
Abstract doi.org/10.14569/IJACSA.2023.0141163 PDF
64

Convolutional LSTM Network for Real-Time Impulsive Sound Detection and Classification in Urban Environments

Author 1: Aigerim Altayeva Author 2: Nurzhan Omarov Author 3: Sarsenkul Tileubay Author 4: Almash Zhaksylyk Author 5: Koptleu Bazhikov Author 6: Dastan Kambarov

In recent years, the escalating challenges of noise pollution in urban environments have necessitated the development of more sophisticated sound detection and classification systems. This research introduces a novel approach employing a Convolutional Long Short-Term Memory (ConvLSTM) network tailored for real-time impulsive sound detection in metropolitan landscapes. Impulsive sounds, characterized… Read full abstract & cite →

Deep learning CNN LSTM hybrid model ANN impulsive sound
Abstract doi.org/10.14569/IJACSA.2023.0141164 PDF
65

Breast Cancer Detection System using Deep Learning Based on Fusion Features and Statistical Operations

Author 1: Suleyman A. AlShowarah

Breast cancer is considered as the second cause of death for women. The earlier is diagnosed, the easier the patients can be recovered. The need for studies to detect this kind of cancer easily and accurately came from the growing rate of infected patents by breast cancer exponentially. This study… Read full abstract & cite →

Breast cancer detection breast cancer classification deep learning vgg-19 breast tumor
Abstract doi.org/10.14569/IJACSA.2023.0141165 PDF
66

Detecting Threats from Live Videos using Deep Learning Algorithms

Author 1: Rawan Aamir Mushabab AlShehri Author 2: Abdul Khader Jilani Saudagar

Threat detection is an important area of research, particularly in security and surveillance applications. The research is focused on developing a threat detection system using DL techniques. The system aims to detect potential threats in real-time video streams, enabling early identification and timely response to potential security risks. The study… Read full abstract & cite →

Deep learning machine learning object detection threat detection
Abstract doi.org/10.14569/IJACSA.2023.0141166 PDF
67

Developing an Improved Method to Remove Pectoral Muscle for Better Diagnosis of Breast Cancer in Mammography Images

Author 1: Golnoush Abaei Author 2: Zahra Rezaei Author 3: Usama Qasim Mian Author 4: Yasir Azhari Abdalgadir Abdalla Author 5: Nitin Mathew Author 6: Leong Yi Gan

Mammography is a non-invasive method to study breast tissues for abnormalities. Computer-aided diagnosis (CAD) can automate the process of diagnosing malignant and benign tumors accurately. However, accurate results can be hampered by the presence of the pectoral muscle, which has a similar opacity to the breast tissue area. Detecting and… Read full abstract & cite →

Breast cancer preprocessing pectoral muscle segmentation level set algorithm region growing algorithm
Abstract doi.org/10.14569/IJACSA.2023.0141167 PDF
68

Applying Machine Learning Models to Electronic Health Records for Chronic Disease Diagnosis in Kuwait

Author 1: Talal M. Alenezi Author 2: Taiseer H. Sulaiman Author 3: Amr M. AbdelAziz

The leading cause of death nowadays is chronic disease. As a result, personal wellbeing has received a considerable boost as a healthcare preventative strategy. A notable development in data-driven healthcare technology is the creation of a prediction model for chronic diseases. In this situation, computational intelligence is used to analyze… Read full abstract & cite →

Chronic diseases Electronic Health Records (EHR) machine learning classification
Abstract doi.org/10.14569/IJACSA.2023.0141168 PDF
69

Separability-based Quadratic Feature Transformation to Improve Classification Performance

Author 1: Usman Sudibyo Author 2: Supriadi Rustad Author 3: Pulung Nurtantio Andono Author 4: Ahmad Zainul Fanani

Feature transformation is an essential part of data preprocessing to improve the predictive performance of machine learning (ML) algorithms. Box-Cox transformation with the goal of separability is proven to align with the performance improvement of ML algorithms. However, the features mapped using Box-Cox transformation preserve the order of the data… Read full abstract & cite →

Separability feature transformation quadratic function fisher’s criterion fisher score
Abstract doi.org/10.14569/IJACSA.2023.0141169 PDF
70

Detecting Data Poisoning Attacks using Federated Learning with Deep Neural Networks: An Empirical Study

Author 1: Hatim Alsuwat

The advent of intelligent networks powered by machine learning (ML) methods over the past few years has dramatically facilitated various facets of human lives, including healthcare, transportation, and entertainment. However, the use of ML in intelligent networks raises serious concerns about privacy and security, particularly in the context of data… Read full abstract & cite →

Poisoning attacks deep learning network security data classification malicious data
Abstract doi.org/10.14569/IJACSA.2023.0141170 PDF
71

Strengthening AES Security through Key-Dependent ShiftRow and AddRoundKey Transformations Utilizing Permutation

Author 1: Tran Thi Luong

AES (Advanced Encryption Standard) is a widely applied block cipher standard in the United States, used in various security applications today. Currently, there are numerous research endeavors aimed at making AES block ciphers dynamic to improve their security against contemporary strong attacks. The most common dynamic approach involves the dynamization… Read full abstract & cite →

AES ShiftRow AddRoundKey dynamic AES key-dependent
Abstract doi.org/10.14569/IJACSA.2023.0141171 PDF
72

Selection of Unmanned Aircraft Development Model in Indonesia using the AHP Method

Author 1: Agus Bayu Utama Author 2: Siswo Hadi Sumantri Author 3: Romie Oktovianus Bura Author 4: Gita Amperiawan

Countries worldwide are attempting to acquire or create Class 3 unmanned aircraft as part of their armies’ primary weapons systems. The development of medium altitude long endurance (MALE) unmanned aircraft in Indonesia forms part of the national strategic program. Based on documentation studies, three alternative MALE-class unmanned aircraft development models… Read full abstract & cite →

Analytical Hierarchy Process (AHP) decision-making development model medium altitude long endurance (MALE) unmanned aircraft
Abstract doi.org/10.14569/IJACSA.2023.0141172 PDF
73

Unleashing the Potential of Artificial Bee Colony Optimized RNN-Bi-LSTM for Autism Spectrum Disorder Diagnosis

Author 1: Suresh Babu Jugunta Author 2: Yousef A.Baker El-Ebiary Author 3: K. Aanandha Saravanan Author 4: Kanakam Siva Rama Prasad Author 5: S. Koteswari Author 6: Venubabu Rachapudi Author 7: Manikandan Rengarajan

The diagnosis of Autism Spectrum Disorder (ASD) is a crucial, drawn-out, and sometimes subjective procedure that calls for a high level of knowledge. Automation of this diagnostic procedure appears to be possible because to recent developments in machine learning techniques. This paper presents a unique method for improving the performance… Read full abstract & cite →

Autism spectrum disorder artificial bee colony recurrent neural network bidirectional long short-term network artificial intelligence
Abstract doi.org/10.14569/IJACSA.2023.0141173 PDF
74

Exploring the Insights of Bat Algorithm-Driven XGB-RNN (BARXG) for Optimal Fetal Health Classification in Pregnancy Monitoring

Author 1: Suresh Babu Jugunta Author 2: Manikandan Rengarajan Author 3: Sridevi Gadde Author 4: Yousef A.Baker El-Ebiary Author 5: Veera Ankalu. Vuyyuru Author 6: Namrata Verma Author 7: Farhat Embarak

Pregnancy monitoring plays a pivotal role in ensuring the well-being of both the mother and the fetus. Accurate and timely classification of fetal health is essential for early intervention and appropriate medical care. This work presents a novel method for classifying fetal health optimally by combining the Bat Algorithm (BA)… Read full abstract & cite →

BAT fetal health pregnancy monitoring RNN XGBoost
Abstract doi.org/10.14569/IJACSA.2023.0141174 PDF
75

Efficiency Analysis of Firefly Optimization-Enhanced GAN-Driven Convolutional Model for Cost-Effective Melanoma Classification

Author 1: Lakshmi K Author 2: Sridevi Gadde Author 3: Murali Krishna Puttagunta Author 4: G. Dhanalakshmi Author 5: Yousef A. Baker El-Ebiary

Early identification is essential for successful treatment of melanoma, a potentially fatal type of skin cancer. This work takes a fresh approach to addressing the urgent need for an accurate and economical melanoma categorization system. Inaccuracy, efficiency, and resource usage are common problems with current techniques. A model that incorporates… Read full abstract & cite →

Melanoma cost effective analysis long short-term memory firefly optimization generative adversarial network
Abstract doi.org/10.14569/IJACSA.2023.0141175 PDF
76

Utilizing Multimodal Medical Data and a Hybrid Optimization Model to Improve Diabetes Prediction

Author 1: A. Leela Sravanthi Author 2: Sameh Al-Ashmawy Author 3: Chamandeep Kaur Author 4: Mohammed Saleh Al Ansari Author 5: K. Aanandha Saravanan Author 6: Veera Ankalu. Vuyyuru

Diabetes is a major health issue that affects people all over the world. Accurate early diagnosis is essential to enabling adequate therapy and prevention actions. Through the use of electronic health records and recent advancements in data analytics, there is growing interest in merging multimodal medical data to increase the… Read full abstract & cite →

Diabetes prediction multimodal medical data binary grey wolf optimization crow search optimization support vector machine
Abstract doi.org/10.14569/IJACSA.2023.0141176 PDF
77

A Hybrid Movies Recommendation System Based on Demographics and Facial Expression Analysis using Machine Learning

Author 1: Mohammed Balfaqih

Cinemas and digital platforms offer an extensive array of content requiring tailored filtering to cater to individual preferences. While recommender systems prove invaluable for this purpose, conventional movie recommendations tend to emphasize specific attributes, leading to a reduction in overall accuracy and reliability. Notably, the extraction process of facial temporal… Read full abstract & cite →

Recommender system movies recommendation emotion prediction k-means clustering deep learning
Abstract doi.org/10.14569/IJACSA.2023.0141177 PDF
78

Analysis of Ransomware Impact on Android Systems using Machine Learning Techniques

Author 1: Anfal Sayer M. Al-Ruwili Author 2: Ayman Mohamed Mostafa

Ransomware is a significant threat to Android systems. Traditional methods of detection and prediction have been used, but with the advancement of technology and artificial intelligence, new and innovative techniques have been developed. Machine learning (ML) algorithms are a branch of artificial intelligence that have several important advantages, including phishing… Read full abstract & cite →

Ransomware machine learning malware detection phishing detection spam filtering
Abstract doi.org/10.14569/IJACSA.2023.0141178 PDF
79

Self-Organizing Control Systems for Nonlinear Spacecraft in the Class of Structurally Stable Mappings

Author 1: Orisbay Abdiramanov Author 2: Daniyar Taiman Author 3: Mamyrbek Beisenbi Author 4: Mira Rakhimzhanova Author 5: Islam Omirzak

In recent developments within the domain of aerospace engineering, there is a burgeoning interest in the autonomous control of nonlinear spacecraft using advanced methodologies. The present research delves deep into the realm of self-organizing control systems tailored for such nonlinear spacecraft, emphasizing its application within the framework of structurally stable… Read full abstract & cite →

Impulsive sound machine learning deep learning CNN LSTM classification
Abstract doi.org/10.14569/IJACSA.2023.0141179 PDF
80

Offensive Language Detection on Online Social Networks using Hybrid Deep Learning Architecture

Author 1: Gulnur Kazbekova Author 2: Zhuldyz Ismagulova Author 3: Zhanar Kemelbekova Author 4: Sarsenkul Tileubay Author 5: Boranbek Baimurzayev Author 6: Aizhan Bazarbayeva

In the digital era, online social networks (OSNs) have revolutionized communication, creating spaces for vibrant public discourse. However, these platforms also harbor offensive language that can proliferates hate speech, cyberbullying, and discrimination, significantly undermining the quality of online interactions and posing severe social implications. This research paper introduces a sophisticated… Read full abstract & cite →

Offensive language machine learning deep learning social media detection classification
Abstract doi.org/10.14569/IJACSA.2023.0141180 PDF
81

Automated Detection of Driver and Passenger Without Seat Belt using YOLOv8

Author 1: Sutikno Author 2: Aris Sugiharto Author 3: Retno Kusumaningrum

The issue of traffic accident fatalities is a serious concern on a global scale, and one of the contributing factors is the failure of drivers to adhere to seat belt usage. A notable challenge arises from the limited availability of law enforcement personnel monitoring this particular issue. In this context… Read full abstract & cite →

Windshield detection passenger classification seat belt classification YOLOv8
Abstract doi.org/10.14569/IJACSA.2023.0141181 PDF
82

Enhancing Alzheimer's Disease Diagnosis: The Efficacy of the YOLO Algorithm Model

Author 1: Tran Quang Vinh Author 2: Haewon Byeon

The diagnosis and early detection of Alzheimer's Disease (AD) and other forms of dementia have become increasingly crucial as our aging population grows. In recent years, deep learning, particularly the You Only Look Once (YOLO) architecture, has emerged as a promising tool in the field of neuroimaging and machine learning… Read full abstract & cite →

Machine learning deep learning YOLO alzheimer’s disease dementia
Abstract doi.org/10.14569/IJACSA.2023.0141182 PDF
83

Enhancing IoT Security and Privacy with Claims-based Identity Management

Author 1: Mopuru Bhargavi Author 2: Yellamma Pachipala

The Internet of Things (IoT) has ushered in a new era of ubiquitous connectivity among devices, necessitating robust identity management (IdM) solutions to address privacy, security, and efficiency challenges. In this study, it delve into various IdM approaches in the context of IoT, examining their implications for privacy preservation, user… Read full abstract & cite →

Internet of Things (IoT) identity management privacy preservation access control security DCapBAC CP-ABE interconnected devices
Abstract doi.org/10.14569/IJACSA.2023.0141183 PDF
84

Speech Enhancement using Fully Convolutional UNET and Gated Convolutional Neural Network

Author 1: Danish Baloch Author 2: Sidrah Abdullah Author 3: Asma Qaiser Author 4: Saad Ahmed Author 5: Faiza Nasim Author 6: Mehreen Kanwal

Speech Enhancement aims to enhance audio intelligibility by reducing background noises that often degrade the quality and intelligibility of speech. This paper brings forward a deep learning approach for suppressing the background noise from the speaker's voice. Noise is a complex nonlinear function, so classical techniques such as Spectral Subtraction… Read full abstract & cite →

Speech enhancement speech denoising deep neural network raw waveform fully convolutional neural network gated linear unit
Abstract doi.org/10.14569/IJACSA.2023.0141184 PDF
85

Hotspot Identification Through Pick-Up and Drop-Off Analysis of Ride-Hailing Transport Service

Author 1: Ragil Saputra Author 2: Suprapto Author 3: Agus Sihabudin

It is important to extract hotspots in urban traffic networks to improve driver route efficiency. This research aims to identify hotspot pick-up and drop-off (PUDO) areas in ride-hailing transportation services using a clustering approach. However, there are challenges in applying clustering algorithms to trajectory data in the coordinates of the… Read full abstract & cite →

Hotspot identification ride-hailing transportation PUDO location clustering analysis
Abstract doi.org/10.14569/IJACSA.2023.0141185 PDF
86

Learning Engagement of Children with Dyslexia Through Tangible User Interface: An Experiment

Author 1: Siti Nurliana Jamali Author 2: Novia Admodisastro Author 3: Azrina Kamaruddin Author 4: Saadah Hassan

This paper presents the evaluation of a mobile application employing Tangible User Interface (TUI) technology to enhance the educational involvement of children experiencing dyslexia. The primary objective of this application is to assist these children in overcoming challenges related to reading, spelling, pronunciation, and writing, issues often associated with lower… Read full abstract & cite →

Dyslexia Tangible User Interface mobile application user centered design engagement
Abstract doi.org/10.14569/IJACSA.2023.0141186 PDF
87

FOREX Prices Prediction Using Deep Neural Network and FNF

Author 1: Asmaa M. Moustafa Author 2: Mohamed Waleed Fakhr Author 3: Fahima A. Maghraby

One of the largest financial markets on the planet is the foreign exchange (FOREX) market. Banks, retail traders, businesses, and individuals trade more than $5.1 trillion in FOREX daily. It is very challenging to predict prices in advance due to the market's complex, volatile, and highly fluctuating nature. In this… Read full abstract & cite →

FOREX prediction CNN normalization function SVR
Abstract doi.org/10.14569/IJACSA.2023.0141187 PDF
88

A New Steganography Method for Hiding Text into RGB Image

Author 1: AL-Hasan Amer Ibrahim Author 2: Ruaa Shallal Abbas Anooz Author 3: Mohammed Ghassan Abdulkareem Author 4: Musatafa Abbas Abbood Albadr Author 5: Fahad Taha AL-Dhief Author 6: Yaqdhan Mahmood Hussein Author 7: Hatem Oday Hanoosh Author 8: Mohammed Hasan Mutar

Now-a-days, the network has significant roles in transferring data and knowledge quickly and accurately from sender to receiver. However, the data is still not secure enough to transfer quite confidentially. Data protection is considered as one of the principal challenges in information sharing over communication. So, steganography techniques were proposed… Read full abstract & cite →

Steganography techniques color images XOR gate NOR gate huffman technique
Abstract doi.org/10.14569/IJACSA.2023.0141188 PDF
89

Bidirectional Long Short-Term Memory for Analysis of Public Opinion Sentiment on Government Policy During the COVID-19 Pandemic

Author 1: Intan Nurma Yulita Author 2: Ahmad Faaiz Al-Auza’i Author 3: Anton Satria Prabuwono Author 4: Asep Sholahuddin Author 5: Firman Ardiansyah Author 6: Indra Sarathan Author 7: Yusa Djuyandi

One of the initiatives adopted by the Indonesian government to combat the development of COVID-19 in Indonesia is Community Activities Restrictions Enforcement. Many public opinions emerged, both for and against this policy. There are so many comments every second that it is certainly not easy to analyze them by reading… Read full abstract & cite →

Sentiment analysis COVID-19 BiLSTM deep learning government policy
Abstract doi.org/10.14569/IJACSA.2023.0141189 PDF
90

New AHP Improvement using COMET Method Characteristic to Eliminate Rank Reversal Phenomenon

Author 1: Yulistia Author 2: Ermatita Author 3: Samsuryadi Author 4: Abdiansah

Rank Reversal in Multi-Criteria Decision Making (MCDM) is a phenomenon that occurs when an alternative is added or deleted because of a change in the order in which the result is ranked. The evaluation of the weight of criteria, which are established based on whether a decision maker considers them… Read full abstract & cite →

Method combination C-AHP rank reversal elimination
Abstract doi.org/10.14569/IJACSA.2023.0141190 PDF
91

Automated Detection and Classification of Soccer Field Objects using YOLOv7 and Computer Vision Techniques

Author 1: Jafar AbuKhait Author 2: Murad Alaqtash Author 3: Ahmad Aljaafreh Author 4: Waleed Othman

In the last two decades, many technologies have been deployed and utilized in Soccer games (Football) as a result to the huge investment of Federation of International Football Association (FIFA). These technologies aim to monitor and track all soccer match objects including players and the ball itself in order to… Read full abstract & cite →

Soccer game football YOLOv7 human detection and classification ball detection improved color coherence vector
Abstract doi.org/10.14569/IJACSA.2023.0141191 PDF
92

Quality In-Use of Mobile Geographic Information Systems for Data Collection

Author 1: Badr El Fhel Author 2: Ali Idri

Mobile Geographic Information Systems (GIS) plays a vital role in data collection, offering diverse functionalities for spatial data handling. Despite advancements, accurately determining the usage environment during development remains challenging. This study uses machine learning and natural language processing to automatically classify user reviews based on the ISO 25010 quality-in-use… Read full abstract & cite →

Mobile GIS for data collection machine learning software product quality ISO/IEC 25010 natural language processing user experience
Abstract doi.org/10.14569/IJACSA.2023.0141192 PDF
93

Bitcoin Optimized Signal Allocation Strategies using Decomposition

Author 1: Sherin M. Omran Author 2: Wessam H. El-Behaidy Author 3: Aliaa A. A. Youssif

Bitcoin is the first and most famous cryptocurrency. It is a virtual currency that is operated in a decentralized form using cryptographic strategies called blockchains. Although it has experienced significant market acceptance by traders and investors in recent years, it also suffers from volatility and riskiness. Technical analysis is one… Read full abstract & cite →

Bitcoin technical analysis decomposition particle swarm optimization MOEA/D
Abstract doi.org/10.14569/IJACSA.2023.0141193 PDF
94

A New Method for Revealing Traffic Patterns in Video Surveillance using a Topic Model

Author 1: Yao Wang

Research on video surveillance systems, for instance, in intelligent transportation systems, has advanced due to the growing requirement for monitoring, control, and intelligent management. One of the next issues is extracting patterns and automatically classifying them, given the volume of data produced by these systems. In this study, a theme… Read full abstract & cite →

Group thin topic coding QM_UL video optical flux traffic patterns
Abstract doi.org/10.14569/IJACSA.2023.0141194 PDF
95

Improving Deep Reinforcement Learning Training Convergence using Fuzzy Logic for Autonomous Mobile Robot Navigation

Author 1: Abdurrahman bin Kamarulariffin Author 2: Azhar bin Mohd Ibrahim Author 3: Alala Bahamid

Autonomous robotic navigation has become hotspot research, particularly in complex environments, where inefficient exploration can lead to inefficient navigation. Previous approaches often had a wide range of assumptions and prior knowledge. Adaptations of machine learning (ML) approaches, especially deep learning, play a vital role in the applications of navigation, detection… Read full abstract & cite →

Autonomous navigation deep reinforcement learning mobile robots neuro-symbolic Fuzzy Logic
Abstract doi.org/10.14569/IJACSA.2023.0141195 PDF
96

Brain Tumor Segmentation Algorithm Based on Asymmetric Encoder and Multimodal Cross-Collaboration

Author 1: Pengyue Zhang Author 2: Qiaomei Ma

To address the challenges of insufficient multimodal information fusion and insufficient long-range dependencies features extraction for brain tumor segmentation, this paper propose a novel network based on asymmetric encoder and multimodal cross-collaboration. The network employs an asymmetric encoder-decoder architecture. Firstly, the invert ConvNext split convolution (ICSC) block is used in… Read full abstract & cite →

Brain tumor multimodal cross-collaboration asymmetric encoder coordinate attention
Abstract doi.org/10.14569/IJACSA.2023.0141196 PDF
97

Blockchain Integrated Neural Networks: A New Frontier in MRI-based Brain Tumor Detection

Author 1: Subrata Banik Author 2: Nani Gopal Barai Author 3: F M Javed Mehedi Shamrat

Brain tumors originating from uncontrolled growth of abnormal cells in the brain, presents a significant challenge in healthcare due to their various symptoms and infrequency. While Magnetic Resonance Imaging (MRI) is essential for accurately identifying and diagnosing malignant tumors, manual interpretation is often complex and sensitive to mistakes. To address… Read full abstract & cite →

Brain tumor MRI imaging BrainTumorNet deep learning image classification augmentation
Abstract doi.org/10.14569/IJACSA.2023.0141197 PDF
98

Proposal of a Machine Learning-based Model to Optimize the Detection of Cyber-attacks in the Internet of Things

Author 1: Cheikhane Seyed Author 2: Jeanne roux BILONG NGO Author 3: Mbaye KEBE

In this article, we propose a model to optimize the detection of attacks in IoT. IoT network is a promising technology that connects living and non-living things around the world. Despite the increased development of these technologies, cyber-attacks remains a weakness, making it vulnerable to numerous cyber-attacks. Of course, automatic… Read full abstract & cite →

IoT Machine learning cyber-security detection of attacks weka tool classification quality and consistency
Abstract doi.org/10.14569/IJACSA.2023.0141198 PDF
99

Construction of an Intelligent Evaluation Model of Yield Risk Based on Empirical Probability Distribution

Author 1: Zhou Yanru Author 2: Yang Jing

In order to improve the accuracy of yield risk evaluation, an intelligent evaluation model of yield risk based on empirical probability distribution is constructed. The dimensionality reduction method of risk factor based on principal component analysis is adopted. After adjusting the multiple data dimensions of risk factors that affect the… Read full abstract & cite →

Empirical probability distribution yield risk intelligence evaluation principal component analysis clustering weight
Abstract doi.org/10.14569/IJACSA.2023.0141199 PDF
100

Enhancing Question Pairs Identification with Ensemble Learning: Integrating Machine Learning and Deep Learning Models

Author 1: Salsabil Tarek Author 2: Hatem M. Noaman Author 3: Mohammed Kayed

The effectiveness of machine learning (ML) and deep learning (DL) models on the Quora question pairs dataset is investigated in this study. ML models, including AdaBoost, reached 73.44% test accuracy, while ensemble learning approaches enhanced outcomes even further, with the Hard-Voting Ensemble achieving 76.13%. DL models, such as FCN, demonstrated… Read full abstract & cite →

Ensemble learning natural language processing deep learning machine learning
Abstract doi.org/10.14569/IJACSA.2023.01411100 PDF
101

The Fusion Method of Virtual Reality Technology and 3D Movie Animation Design

Author 1: Xiang Yuan Author 2: He Huixuan

To further improve the design effect of 3D film and television animation, integrating virtual reality technology with 3D film and television animation design is studied. This method uses 3Ds Max software in virtual reality technology to build 3D film and television animation scenes by manual modeling. Based on the established… Read full abstract & cite →

Virtual reality technology 3D film and television Animation design model optimization roaming interaction
Abstract doi.org/10.14569/IJACSA.2023.01411101 PDF
102

Classification Method of Traditional Art Painting Style Based on Color Space Transformation

Author 1: Xu Zhe

In order to improve the accuracy and efficiency of traditional art painting style classification, a classification method of traditional art painting style based on color space transformation is proposed. This method preprocesses the traditional artistic painting style, improves the contrast of the image, makes the color and details of the… Read full abstract & cite →

Color space traditional art painting style classification method fuzzy c-means
Abstract doi.org/10.14569/IJACSA.2023.01411102 PDF
103

Research on Image Algorithm for Face Recognition Based on Deep Learning

Author 1: Qiang Wu

As people's requirements for applications are getting higher and higher, the recognition of facial features has been paid more and more attention. The current facial feature recognition algorithm not only takes a long time, but also has problems such as large system resource consumption and long running time in practical… Read full abstract & cite →

Multi task deep learning face recognition convolution neural network multi task dimension
Abstract doi.org/10.14569/IJACSA.2023.01411103 PDF
104

A Model for Analyzing Employee Turnover in Enterprises Based on Improved XGBoost Algorithm

Author 1: Linzhi Nan Author 2: Han Zhang

To accurately predict the possibility of employee turnover during enterprise operation and improve the benefits created by talents in the enterprise, research based on the limit gradient enhancement algorithm has received widespread attention. However, with the exponential growth of various types of resignation reasons, this algorithm is not comprehensive enough… Read full abstract & cite →

Data preprocessing linear white noise root mean square error newton’s law of cooling step cooling curve
Abstract doi.org/10.14569/IJACSA.2023.01411104 PDF
105

Intelligent Design of Ethnic Patterns in Clothing using Improved DCGAN for Real-Time Style Transfer

Author 1: Yingjun Liu Author 2: Ming Wu

In view of the problems that traditional real-time style transmission technology requires a large number of sample map training, low image quality, lack of realism and detail, this study combines the improved generative adversarial network (GANs) with real-time style transfer technology, and enhances the real-time style transfer calculation with adaptive… Read full abstract & cite →

Computer vision improved DCGAN style transfer adaptive instance normalization intelligent design of patterns
Abstract doi.org/10.14569/IJACSA.2023.01411105 PDF
106

AI-Driven Optimization Approach Based on Genetic Algorithm in Mass Customization Supplying and Manufacturing

Author 1: Shereen Alfayoumi Author 2: Neamat Eltazi Author 3: Amal Elgammal

Numerous artificial intelligence (AI) techniques are currently utilized to identify planning solutions for supply chains, which comprise suppliers, manufacturers, wholesalers, and customers. Continuous optimization of these chains is necessary to enhance their performance. Manufacturing is a critical stage within the supply chain that requires continuous optimization. Mass Customization Manufacturing is… Read full abstract & cite →

Mass customization manufacturing metaheuriatic search genetic algorithm optimization supply chain management
Abstract doi.org/10.14569/IJACSA.2023.01411106 PDF
107

Application Model Construction of Emotional Expression and Propagation Path of Deep Learning in National Vocal Music

Author 1: Zhangcheng Tang

Emotional expression is important in Chinese national vocal music art. The emotional expression in national vocal music is based on the art of national vocal music, with distinct characteristics and requirements. The ultimate goal is to spread the expression of various emotions in the national vocal music art. Promoting the… Read full abstract & cite →

Deep learning national vocal music innovation emotion dissemination
Abstract doi.org/10.14569/IJACSA.2023.01411107 PDF
108

Using Generative Adversarial Networks and Ensemble Learning for Multi-Modal Medical Image Fusion to Improve the Diagnosis of Rare Neurological Disorders

Author 1: Bhargavi Peddi Reddy Author 2: K Rangaswamy Author 3: Doradla Bharadwaja Author 4: Mani Mohan Dupaty Author 5: Partha Sarkar Author 6: Mohammed Saleh Al Ansari

The research suggests a unique ensemble learning approach for precise feature extraction and feature fusion from multi-modal medical pictures, which may be applied to the diagnosis of uncommon neurological illnesses. The proposed method makes use of the combined characteristics of Convolutional Neural Networks and Generative Adversarial Networks (CNN-GAN) to improve… Read full abstract & cite →

Multi-modal medical images ensemble learning CNN GAN neurological disorders image-to-image method transfer learning feature extraction
Abstract doi.org/10.14569/IJACSA.2023.01411108 PDF
109

Creating a Framework for Care Needs Hub for Persons with Disabilities and Senior Citizens

Author 1: Guillermo V. Red Author 2: Thelma D. Palaoag Author 3: Vince Angelo E. Naz

Patient satisfaction is an assessment that assesses how effectively a company’s goods or services fulfil consumer expectations. This study aims to design an architectural framework for a care needs hub for people with disabilities and senior citizens. Using systems modelling for crafting architectural frameworks, the researchers used a 4+1 view… Read full abstract & cite →

Care need framework persons with disability CareAide 4+1 view model CareNeed
Abstract doi.org/10.14569/IJACSA.2023.01411109 PDF
110

Implementation of Cybersecurity Situation Awareness Model in Saudi SMEs

Author 1: Monerah Faisal Almoaigel Author 2: Ali Abuabid

Saudi Small and Medium-sized Enterprises (SMEs) are witnessing rapid growth in technology and innovation. However, this growth is accompanied by increased cybersecurity threats, which pose significant challenges for SMEs. Cyber threats are becoming more complex and sophisticated, with SMEs becoming prime targets due to their weaker cybersecurity defenses. Hence, there… Read full abstract & cite →

Cyber situation awareness cybersecurity control and precaution Saudi SMEs
Abstract doi.org/10.14569/IJACSA.2023.01411110 PDF
111

Network Security Detection Method Based on Abnormal Traffic Detection

Author 1: Tao Xiao Author 2: Yang Ke Author 3: Hu YiWen Author 4: Wang HongYa

To discover potential risks and vulnerabilities in the network in time and ensure the safe operation of the network, a network security detection method based on abnormal traffic detection is studied. Construct network security detection architecture from several aspects, including the front-end interface module, control center module, network status extraction… Read full abstract & cite →

Abnormal traffic network security detection data dimensionality reduction flow characteristics traffic capture alarm module
Abstract doi.org/10.14569/IJACSA.2023.01411111 PDF
112

ODFM: Abnormal Traffic Detection Based on Optimization of Data Feature and Mining

Author 1: Xianzong Wu

The booming of computer networks and software applications has led to an explosive growth in the potential damage caused by network attacks. Efficient detection of abnormal traffic in networks is appealing for facilely mastering the traffic tracking and locating for network usage at low resource cost. High quality abnormal traffic… Read full abstract & cite →

Abnormal traffic detection data mining feature dimension optimization network security
Abstract doi.org/10.14569/IJACSA.2023.01411112 PDF
113

Automatic Bangla Image Captioning Based on Transformer Model in Deep Learning

Author 1: Md. Anwar Hossain Author 2: Mirza AFM Rashidul Hasan Author 3: Ebrahim Hossen Author 4: Md Asraful Author 5: Md. Omar Faruk Author 6: AFM Zainul Abadin Author 7: Md. Suhag Ali

Indeed, Image Captioning has become a crucial aspect of contemporary artificial intelligence because it has tackled two crucial parts of the AI field: Computer Vision and Natural Language Processing. Currently, Bangla stands as the seventh most widely spoken language globally. Due to this, image captioning has gained recognition for its… Read full abstract & cite →

Bangla image captioning image processing natural language processing attention mechanism transformer model
Abstract doi.org/10.14569/IJACSA.2023.01411113 PDF
114

The Hybrid Jaro-Winkler and Manhattan Distance using Dissimilarity Measure for Test Case Prioritization Approach

Author 1: Siti Hawa Mohamed Shareef Author 2: Rabatul Aduni Sulaiman Author 3: Abd Samad Hasan Basari

Software product line (SPL) is a concept that has revolutionized the software development industry. It refers to a set of related software products that are developed from a common set of core assets but can be customized to meet specific customer requirements. Integrating SPL techniques into test case prioritization (TCP)… Read full abstract & cite →

Test case prioritization software product line dissimilarity-based technique string distance new enhanced hybrid
Abstract doi.org/10.14569/IJACSA.2023.01411114 PDF
115

A Novel CNN-based Model for Medical Image Registration

Author 1: Hui GAO Author 2: Mingliang LIANG

The registration of the deformable image is applied widely to image diagnosis, the monitoring of the disease, and the navigation of the surgery with the aim of learning the correspondence of the anatomist among an image of motion and an image of static. The procedure of the registration of an… Read full abstract & cite →

Image registration convolutional neural network Pyramid Registration (PR) encoder-decoder
Abstract doi.org/10.14569/IJACSA.2023.01411115 PDF
116

Recognition of Depression from Video Frames by using Convolutional Neural Networks

Author 1: Jianwen WANG Author 2: Xiao SHA

The disturbances of the mood are relevant to the emotions. Specifically, the behaviour of persons with disturbances of mood, like the depression of the unipolar, displays a powerful correlation of the temporal by the emotional girths of the arousal and the valence. Moreover, the psychiatrists and the psychologists take into… Read full abstract & cite →

Deep learning depression recognition Convolutional Neural Network (CNN) attention mechanism
Abstract doi.org/10.14569/IJACSA.2023.01411116 PDF
117

MG-CS: Micro-Genetic and Cuckoo Search Algorithms for Load-Balancing and Power Minimization in Cloud Computing

Author 1: Jun ZHOU Author 2: Youyou Li

Cloud computing has emerged as a transformative technology, offering remote access to various computing resources. However, efficiently managing these resources while curbing escalating energy consumption remains a critical challenge. In response, this paper presents the Micro-Genetic Algorithm with Cuckoo Search (MG-CS), a novel approach for enhancing cloud computing efficiency. MG-CS… Read full abstract & cite →

Resource utilization cloud computing energy consumption optimization
Abstract doi.org/10.14569/IJACSA.2023.01411117 PDF
118

A Focal Loss-based Multi-layer Perceptron for Diagnosis of Cardiovascular Risk in Athletes

Author 1: Chuan Yang

Cardiovascular diseases (CVDs) are a prevalent cause of heart failure around the world. This research was required in order to investigate potential approaches to treating the disease. The article presents a focal loss (FL)-based multi-layer perceptron called MLP-FL-CRD to diagnose cardiovascular risk in athletes. In 2012, 26,002 athletes were measured… Read full abstract & cite →

Cardiovascular diseases multi-layer perceptron focal loss artificial bee colony imbalanced classification
Abstract doi.org/10.14569/IJACSA.2023.01411118 PDF
119

Fuzzy Neural Network Algorithm Application in User Behavior Portrait Construction

Author 1: Peisen Song Author 2: Bengcheng Yu Author 3: Chen Chen

With the increasing number of online users, constructing user behavior profiles has received widespread attention from relevant scholars. In order to construct user behavior profiles more accurately, the research first designed an adaptive fuzzy neural network algorithm based on the momentum gradient descent method. It uses momentum gradient descent to… Read full abstract & cite →

User behavior profiling momentum gradient descent method adaptive fuzzy neural network error backpropagation algorithm least squares estimation method subtractive clustering
Abstract doi.org/10.14569/IJACSA.2023.01411119 PDF
120

Automated Classification of Multiclass Brain Tumor MRI Images using Enhanced Deep Learning Technique

Author 1: Faiz Ainur Razi Author 2: Alhadi Bustamam Author 3: Arnida L. Latifah Author 4: Shandar Ahmad

The brain is a vital organ, and the brain tumor is one of the most dangerous types of tumors in the world. Neuroimaging is an interesting and important discussion in diagnosing central nervous system tumors. Brain tumors have several types, namely meningioma, glioma, pituitary, schwannoma, and neurocytoma. A radiologist uses… Read full abstract & cite →

Brain tumor enhanced deep learning MRI multiclass neuroimaging
Abstract doi.org/10.14569/IJACSA.2023.01411120 PDF
121

Nature-Inspired Optimization for Virtual Machine Allocation in Cloud Computing: Current Methods and Future Directions

Author 1: Xiaoqing YANG

An expanding range of services is offered by cloud data centers. The execution of application tasks is facilitated by assigning (VMs) Virtual Machines to (PMs) Physical Machines. Speaking of VM allocation in the cloud service center, two key factors are taken into consideration: quality of service (QoS) and energy consumption… Read full abstract & cite →

Cloud computing virtualization virtual machine allocation optimization
Abstract doi.org/10.14569/IJACSA.2023.01411121 PDF
122

Investigating the Effectiveness of ChatGPT for Providing Personalized Learning Experience: A Case Study

Author 1: Raneem N. Albdrani Author 2: Amal A. Al-Shargabi

The demand for personalized learning experiences that cater to the unique needs of individual learners has increased with the emergence of data science. This paper investigates the potential use of ChatGPT, a generative AI tool, in providing personalized learning experiences for data science education, specifically focusing on Deep Learning. The… Read full abstract & cite →

Personalized learning data science education ChatGPT generative AI
Abstract doi.org/10.14569/IJACSA.2023.01411122 PDF
123

Securing Digital Data: A New Edge Detection and XOR Coding Approach for Imperceptible Image Steganography

Author 1: Hayat Al-Dmour

The rapid progress of digital devices and technol-ogy, coupled with the emergence of the internet has amplified the risks and perils associated with malicious attacks. Consequently, it becomes crucial to protect valuable information transmitted through the internet. Steganography is a tried-and-true technique for hiding information beneath digital content, such as… Read full abstract & cite →

Steganography information hidings bits modifica-tion decoding algorithm edge detection canny edge detection human visual system
Abstract doi.org/10.14569/IJACSA.2023.01411123 PDF
124

Incorporating News Tags into Neural News Recommendation in Indonesian Language

Author 1: Maxalmina Satria Kahfi Author 2: Evi Yulianti Author 3: Alfan Farizki Wicaksono

News recommendation system holds the potential to aid users in discovering articles that align with their interests, which is critical to alleviate user information overload. To generate effective news recommendations, one key capability is to accurately capture the contextual meaning of text in the news articles, since this is pivotal… Read full abstract & cite →

News recommendation recommendation systems news tags user modeling
Abstract doi.org/10.14569/IJACSA.2023.01411124 PDF
125

Telemedicine Adoption for Healthcare Delivery: A Systematic Review

Author 1: Taif Ghiwaa Author 2: Imran Khan Author 3: Martin White Author 4: Natalia Beloff

Telemedicine is the delivery of healthcare ser-vices using telecommunication and information technologies. The adoption of telemedicine has been promoted by advancements in technology, increased accessibility to the Internet, and the need for convenient and efficient healthcare delivery. Under-standing the theoretical foundations of telemedicine adoption among healthcare providers and patients is… Read full abstract & cite →

Telemedicine systematic review technology accep-tance model adoption telehealth healthcare provider patient
Abstract doi.org/10.14569/IJACSA.2023.01411125 PDF
126

Attention-based Cross-Modality Multiscale Fusion for Multispectral Pedestrian Detection

Author 1: Zhou Hui

Multispectral pedestrian detection has wide ap-plications in fields such as autonomous driving and intelli-gent surveillance. Mining complementary information between modalities is one of the most effective approaches to improve the performance of multispectral pedestrian detection. However, the inevitable introduction of redundant information between modalities during the fusion process leads to… Read full abstract & cite →

Pedestrian detection multispectral pedestrian detec-tion attention mechanism cross-modal fusion
Abstract doi.org/10.14569/IJACSA.2023.01411126 PDF
127

Deep Learning-Powered Mobile App for Fast and Accurate COVID-19 Detection from Chest X-rays

Author 1: Rahhal Errattahi Author 2: Fatima Zahra Salmam Author 3: Mohamed Lachgar Author 4: Asmaa El Hannani Author 5: Abdelhak Aqqal

The COVID-19 pandemic has imposed significant challenges on healthcare systems globally, necessitating swift and precise screening methods to curb transmission. Traditional screening approaches are time-consuming and prone to errors, prompting the development of an innovative solution - a mobile application employing machine learning for automated COVID- 19 screening. This application… Read full abstract & cite →

COVID-19 diagnosis computer vision deep learn-ing X-ray images mobile application
Abstract doi.org/10.14569/IJACSA.2023.01411127 PDF
128

Explicit Knowledge Database Interface Model System Based on Natural Language Processing Techniques and Immersive Technologies

Author 1: Luis Alfaro Author 2: Claudia Rivera Author 3: Jose Herrera Author 4: Antonio Arroyo Author 5: Lucy Delgado Author 6: Elisa Castaneda

This work is focused on the proposal and de-velopment of an interface system model, based on natural language processing, immersive technologies and natural user interfaces, for the interaction with Explicit Knowledge databases. Five phases were proposed: The user testing characterization, the establishment of the state of the art and the… Read full abstract & cite →

Knowledge management explicit knowledge databases natural language processing natural user interfaces Immersive technologies
Abstract doi.org/10.14569/IJACSA.2023.01411128 PDF
129

CESSO-HCRNN: A Hybrid CRNN With Chaotic Enriched SSO-based Improved Information Gain to Detect Zero-Day Attacks

Author 1: Dharani Kanta Roy Author 2: Ripon Patgiri

Hackers use the vulnerability before programmers have a chance to fix it, which is known as a zero-day attack. Zero-day attackers have a variety of abilities, including the ability to alter files, control machines, steal data, and install malware or adware. When a series of complex assaults uses one or… Read full abstract & cite →

Hackers vulnerability zero-day attack chaotic en-riched salp swarm optimization data cleaning normalization and MATLAB software
Abstract doi.org/10.14569/IJACSA.2023.01411129 PDF
130

Triggered Screen Restriction: Gamification Framework

Author 1: Majed Hariri Author 2: Richard Stone

The prevalence of sedentary lifestyles is increasingly becoming a significant public health concern, with numerous health risks ranging from obesity to heart disease. Several gamified interventions have been employed to counter sedentary behavior by promoting physical activity. However, the existing approaches have yielded mixed results, making it crucial to explore… Read full abstract & cite →

Gamification physical activity sedentary behavior Triggered Screen Restriction (TSR) framework
Abstract doi.org/10.14569/IJACSA.2023.01411130 PDF
131

A Particle Filter based Visual Object Tracking: A Systematic Review of Current Trends and Research Challenges

Author 1: Md Abdul Awal Author 2: Md Abu Rumman Refat Author 3: Feroza Naznin Author 4: Md Zahidul Islam

Visual object tracking is a crucial research area in computer vision because it can simulate a dynamic environment with non-linear motions and multi-modal non-Gaussian noises. However, This paper presents an overview of the recent devel-opments in particle filter-based visual object tracking algorithms and discusses the pros and cons of particle… Read full abstract & cite →

Particle filter visual object tracking On-Gaussian noises Kalman filter CNN
Abstract doi.org/10.14569/IJACSA.2023.01411131 PDF
132

Deep Speech Recognition System Based on AutoEncoder-GAN for Biometric Access Control

Author 1: Oussama Mounnan Author 2: Otman Manad Author 3: Abdelkrim El Mouatasim Author 4: Larbi Boubchir Author 5: Boubaker Daachi

Speech recognition-based biometric access control systems are promising solutions that have resolved many is-sues related to security and convenience. Speech recognition, as a biometric modality, offers unique advantages such as user-friendliness and non-intrusiveness, etc. However, developing robust and accurate speaker identification and authentication systems pose challenges due to variations in… Read full abstract & cite →

Speaker identification speech recognition biomet-ric access control authentication verification
Abstract doi.org/10.14569/IJACSA.2023.01411132 PDF
133

Estimation of Hazardous Environments Through Speech and Ambient Noise Analysis

Author 1: Andrea Veronica Porco Author 2: Kang Dongshik

In recent years, significant attention has been di-rected towards the development of artificial empathy within the engineering academic community. Replicating artificial empathy necessitates the capability of agents to discern human emotions and comprehend environmental risks. Analyzing acoustic data in real environments offers a higher level of non-invasive pri-vacy compared to… Read full abstract & cite →

Dangerous environment detection speech analysis acoustic audio analysis ambient noises variational autoencoder model empathetic systems
Abstract doi.org/10.14569/IJACSA.2023.01411133 PDF
134

D2-Net: Dilated Contextual Transformer and Depth-wise Separable Deconvolution for Remote Sensing Imagery Detection

Author 1: Huaping Zhou Author 2: Qi Zhao Author 3: Kelei Sun

Remote sensing-based object detection faces chal-lenges in arbitrary orientations, complex backgrounds, dense distributions, and large aspect ratios. Considering these issues, this paper introduces a novel method called D2-Net, which incorporates a transformer structure into a convolutional neural network. First, a new feature extraction module called dilated contextual transformer block is… Read full abstract & cite →

YOLOv7 dilated contextual transformer depth-wise separable deconvolution circular smooth label remote sensing
Abstract doi.org/10.14569/IJACSA.2023.01411134 PDF
135

Semantic Embeddings for Arabic Retrieval Augmented Generation (ARAG)

Author 1: Hazem Abdelazim Author 2: Mohamed Tharwat Author 3: Ammar Mohamed

In recent times, Retrieval Augmented Generation (RAG) models have garnered considerable attention, primarily due to the impressive capabilities exhibited by Large Language Models (LLMs). Nevertheless, the Arabic language, despite its significance and widespread use, has received relatively less research emphasis in this field. A critical element within RAG systems is… Read full abstract & cite →

Arabic NLP large language models retrieval aug-mented generation semantic embedding
Abstract doi.org/10.14569/IJACSA.2023.01411135 PDF
136

Elevating Android Privacy: A Blockchain-Powered Paradigm for Secure Data Management

Author 1: Bang Khanh Le Author 2: Ngan Thi Kim Nguyen Author 3: Khiem Gia Huynh Author 4: Phuc Trong Nguyen Author 5: Anh The Nguyen Author 6: Khoa Dand Tran Author 7: Trung Hoang Tuan Phan

The significance of medical test records in diagnos-ing and treating illnesses cannot be overstated. These records serve as the foundation upon which medical professionals craft precise treatment strategies tailored to a patient’s unique health condition and ailment. However, in several developing nations, such as Vietnam, a concerning trend persists: medical… Read full abstract & cite →

Medical test result blockchain smart contract NFT Ethereum Fantom Polygon Binance smart chain
Abstract doi.org/10.14569/IJACSA.2023.01411136 PDF
137

A Deep Transfer Learning Approach for Accurate Dragon Fruit Ripeness Classification and Visual Explanation using Grad-CAM

Author 1: Hoang-Tu Vo Author 2: Nhon Nguyen Thien Author 3: Kheo Chau Mui

Dragon fruit, known for its rich antioxidant content and low-calorie attributes, has garnered significant attention as a health-promoting fruit. Its economic value has also surged due to increasing consumer demand and its potential as an export commodity in various regions. The classification of dragon fruit ripeness is a pivotal task… Read full abstract & cite →

Dragon fruit classification ripeness classification densenet201 model Grad-CAM visualization guided grad-CAM visual interpretation Explainable AI XAI deep learning pre-trained models model fine-tuning transfer learning
Abstract doi.org/10.14569/IJACSA.2023.01411137 PDF
138

Identification of Air-Writing Tamil Alphabetical Vowel Characters

Author 1: Rukshani Puvanendran Author 2: Vijayanathan Senthooran

In recent years, there has been a lot of focus on gesture recognition because of its potential as a means of communication for cutting-edge gadgets. As a special category of gesture recognition, air-writing is the practice of forming letters or words in the air using one’s fingers or the move-ments… Read full abstract & cite →

Air-writing Tamil alphabetical vowel convolutional neural network feature extraction machine learning
Abstract doi.org/10.14569/IJACSA.2023.01411138 PDF
139

Emotional Speech Transfer on Demand based on Contextual Information and Generative Models: A Case Study

Author 1: Andrea Veronica Porco Author 2: Kang Dongshik

The automated generation of speech audio that closely resembles human emotional speech has garnered signif-icant attention from the society and the engineering academia. This attention is due to its diverse applications, including au-diobooks, podcasts, and the development of empathetic home assistants. In the scope of this study, it is introduced… Read full abstract & cite →

Emotion transfer contextual information speech processing generative models variational autoencoder conditional generative adversarial networks empathetic systems
Abstract doi.org/10.14569/IJACSA.2023.01411139 PDF
140

Imbalance Node Classification with Graph Neural Networks (GNN): A Study on a Twitter Dataset

Author 1: Alda Kika Author 2: Arber Ceni Author 3: Denada Collaku Author 4: Emiranda Loka Author 5: Ledia Bozo Author 6: Klesti Hoxha

Social networks produce a large volume of infor-mation, a part of which is fake. Social media platforms do a good job in moderating content and banning fake news spreaders, but a proactive solution is more desirable especially during global threats like COVID-19 pandemic and war. A proactive solution would be… Read full abstract & cite →

GNN imbalanced data Twitter social networks GCN GraphSage GAT GraphSMOTE ReNode
Abstract doi.org/10.14569/IJACSA.2023.01411140 PDF
141

Preventing Cyberbullying on Social Networks with Spanish Parental Control NLP System

Author 1: Gabriel A. Leon-Paredes Author 2: Omar G. Bravo-Quezada Author 3: Pedro P. Bermeo-Aguaysa Author 4: Maria J. Pelaez-Currillo Author 5: Ledys L. Jimenez-Gonzalez

The boom in social networks and digital communi-cation has given place to innovative forms of social interaction. However, it has also made possible new forms of harassment of others anonymously and without repercussions. Such is the case of cyberbullying, an increasingly common problem, especially among young people. Its effects on… Read full abstract & cite →

Cyberbullying control parental system natural lan-guage processing Spanish cyberbullying prevention system
Abstract doi.org/10.14569/IJACSA.2023.01411141 PDF
142

Mukh-Oboyob: Stable Diffusion and BanglaBERT enhanced Bangla Text-to-Face Synthesis

Author 1: Aloke Kumar Saha Author 2: Noor Mairukh Khan Arnob Author 3: Nakiba Nuren Rahman Author 4: Maria Haque Author 5: Shah Murtaza Rashid Al Masud Author 6: Rashik Rahman

Facial image generation from textual generation is one of the most complicated tasks within the broader topic of Text-to-Image (TTI) synthesis. It is relevant in several fields of scientific research, cartoon and animation development, online marketing, game development, etc. There have been extensive studies on Text-to-Face (TTF) synthesis in the… Read full abstract & cite →

Bangla text-to-face synthesis Natural Language Processing (NLP) Bangla NLP Computer Vision (CV) Generative Model stable diffusion BanglaBERT
Abstract doi.org/10.14569/IJACSA.2023.01411142 PDF
143

Generate Adversarial Attack on Graph Neural Network using K-Means Clustering and Class Activation Mapping

Author 1: Ganesh Ingle Author 2: Sanjesh Pawale

Graph Neural Networks (GNNs) have emerged as powerful tools for analyzing complex structured data, including social networks, biological networks, and recommendation sys-tems. However, their susceptibility to adversarial attacks poses a significant challenge, especially in critical tasks such as node classification and link prediction. Adversarial attacks on GNNs can introduce harmful… Read full abstract & cite →

Graph Neural Networks adversarial attacks K-Means clustering class activation mapping robustness defense mechanisms
Abstract doi.org/10.14569/IJACSA.2023.01411143 PDF
144

A Comprehensive Review of Deep Learning Approaches for Animal Detection on Video Data

Author 1: Prashanth Kumar Author 2: Suhuai Luo Author 3: Kamran Shaukat

Integrating deep learning techniques into computer vision application has ushered in a new era of automated analysis and interpretation of visual data. In recent years, a surge of interest has been witnessed in applying these methodologies towards detecting animals in video streams, promising transformative impacts on diverse fields such as… Read full abstract & cite →

Machine learning deep learning animal detection convolutional neural networks video-based deep learning models
Abstract doi.org/10.14569/IJACSA.2023.01411144 PDF
145

Studying the Security and Privacy Issues of Big Data in the Saudi Medical Sector

Author 1: Ramy Elnaghy Author 2: Hazem M. El-Bakry

In today’s era of Big Data, with the integration of data from various systems, devices, and machines used by healthcare service providers, health insurance companies, and their sub-sectors, maintaining privacy and security has become crucial. It is important to uphold the confidentiality and security of data exchanged between data service… Read full abstract & cite →

Security privacy healthcare medical data big data
Abstract doi.org/10.14569/IJACSA.2023.01411145 PDF
146

A Novel Deep Learning-Assisted SVD-based Method for Medical Image Watermarking

Author 1: Saima Kanwal Author 2: Feng Tao Author 3: Rizwan Taj

In the present era, the administration of medical images faces various security challenges that necessitate the authentication of image source and origin for accurate patient identification. With the increasing exchange of medical images between hospitals to facilitate informed decision-making, the adoption of digital watermarking techniques has emerged as an efficient… Read full abstract & cite →

Singular value decomposition medical image watermarking digital watermarking deep learning
Abstract doi.org/10.14569/IJACSA.2023.01411146 PDF
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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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