IJACSA Vol. 15 Issue 2 (2024)

1

Deep Neural Network-based Methods for Brain Image De-noising: A Short Comparison

Author 1: Keyan Rahimi Author 2: Noorbakhsh Amiri Golilarz

Various types of noise may affect the visual quality of images during capturing and transmitting procedures. Finding a proper technique to remove the possible noise and improve both quantitative and qualitative results is always considered as one of the most important and challenging pre-processing tasks in image and signal processing… Read full abstract & cite →

CNN Deep neural network de-noising MR image PSNR

Abstract doi.org/10.14569/IJACSA.2024.0150201 PDF

2

Assessing and Mitigating Network Vulnerabilities in Philips Hue and Nest Protect Smart Home Devices

Author 1: Arvind Sredhar Author 2: Adil Khan Author 3: Abdul Rehman Gilal Author 4: Aeshah Alsughayyir Author 5: Abdullah Alshanqiti Author 6: Bandeh Ali Talpur

The Internet of Things (IoT) has gained momentum across various sectors, particularly in the consumer market with the adoption of smart devices. IoT extends internet connectivity to physical devices, enabling control via smartphones, environmental sensing, and updates. However, smart home devices are susceptible to cyberattacks due to vulnerabilities, lack of… Read full abstract & cite →

Internet of Things (IoT) Smart Home Devices (SHDs) network vulnerability assessment Philips Hue Nest Protect

Abstract doi.org/10.14569/IJACSA.2024.0150202 PDF

3

Texture and Color Descriptor Features-based Vacant Parking Space Detection using K-Nearest Neighbors

Author 1: A F M Saifuddin Saif Author 2: Zainal Rasyid Mahayuddin

The importance of the detection of vacant parking spaces is increasing gradually. A system capable of detecting vacant parking spaces in real-time can play an important role in saving valuable time for motorists, decreasing traffic jams, and reducing air pollution. Vision-based parking space detection methods are advantageous in terms of… Read full abstract & cite →

Texture color descriptor k-nearest neighbors computer vision image processing

Abstract doi.org/10.14569/IJACSA.2024.0150203 PDF

4

SkySculptor: Intuitive Drone Control Through Ground-Integrated Radar and Foot Gestures in Smart Indoor Environments

Author 1: Alexandru-Ionut Siean

SkySculptor is a software application designed to optimize drone control in smart indoor environments. The primary focus is on using gesture input for drone control, particularly investigating mid-air free-foot interactions detected by radar sensing. This software application simplifies the process of controlling drones in smart indoor environments. Additionally, outcomes of… Read full abstract & cite →

Drone control gesture input ultra-wideband radar software application smart environments

Abstract doi.org/10.14569/IJACSA.2024.0150204 PDF

5

Classifying Motorcycle Rider Helmet on a Low Light Video Scene using Deep Learning

Author 1: John Paul Q. Tomas Author 2: Bonifacio T. Doma

For safety in transportation, it is important to always monitor the use of proper motorcycle helmet, especially at night. One way to enforce transportation rules and regulations in wearing proper motorcycle helmet is to use computer vision technology. This study focusses on classifying motorcycle rider helmet at low light video… Read full abstract & cite →

Artificial intelligence computer vision computer vision problems object detection YOLOv5 YOLOv7 Deep SORT deep learning

Abstract doi.org/10.14569/IJACSA.2024.0150205 PDF

6

China's Science and Technology Finance and Economic Corridor Development: A Coupling Relationship Analysis

Author 1: Rui Tian Author 2: Birong Xu

This study aims to explore the coupling relationship between science and technology finance and economic corridor development in my country based on the life cycle theory of industrial clusters. By analyzing the interaction between science and technology finance and the development of economic corridors, our degree of correlation and influence… Read full abstract & cite →

Technology finance regional economic development industrial clusters life cycle theory

Abstract doi.org/10.14569/IJACSA.2024.0150206 PDF

7

Correlation Analysis Between Student Psychological State and Grades Based on Data Mining Algorithms

Author 1: Zeng Daoyan Author 2: Chen Disi

As society has evolved and educational reform has become more profound, the psychological state and academic performance of vocational college students have become the focus of attention for educators. This study aims to construct a correlation model between the positive psychological state and academic performance of vocational college students based… Read full abstract & cite →

Data mining algorithms vocational students positive psychological state academic performance correlation model

Abstract doi.org/10.14569/IJACSA.2024.0150207 PDF

8

Physical Training in Higher Vocational Colleges Based on Sequencing Adaptive Genetic Algorithm

Author 1: Quanzhong Gao

This study is based on the sequencing adaptive genetic algorithm and conducts an in-depth discussion on optimization issues in the field of higher vocational sports training. By analyzing the shortcomings of traditional genetic algorithms in optimizing training plans, a new sequencing adaptive genetic algorithm is proposed to improve the optimization… Read full abstract & cite →

Sequencing adaptive genetic algorithm higher vocational colleges sports training convergence speed

Abstract doi.org/10.14569/IJACSA.2024.0150208 PDF

9

Packaging Beautification Design Based on Visual Image and Personalized Pattern Matching

Author 1: Deli Chen

Visual image technology is widely used in the field of product art design, enriching the visual beautification design effect of products. To improve the design effect of product packaging, a personalized packaging pattern matching technology is proposed based on computer vision image technology. Firstly, based on user needs, a pattern… Read full abstract & cite →

Visual images personalized patterns total variational model GrabCut model migration model

Abstract doi.org/10.14569/IJACSA.2024.0150209 PDF

10

Blockchain-based Cannabis Traceability in Supply Chain Management

Author 1: Piwat Nowvaratkoolchai Author 2: Natcha Thawesaengskulthai Author 3: Wattana Viriyasitavat Author 4: Pramoch Rangsunvigit

The typical cannabis supply chain is encountering obstacles with the traceability of product regulations and standards. It is a complex structure involving multiple organizations and healthcare products. Questionable products finding their way onto the legal market are potentially dangerous. The proportion of Tetrahydrocannabinol (THC)/Cannabidiol (CBD) and the source of the… Read full abstract & cite →

Blockchain cannabis traceability supply chain management polygon on-chain and off-chain

Abstract doi.org/10.14569/IJACSA.2024.0150210 PDF

11

Predictive Modeling of Kuwaiti Chronic Kidney Diseases (KCKD): Leveraging Electronic Health Records for Clinical Decision-Making

Author 1: Talal M. Alenezi Author 2: Taiseer H. Sulaiman Author 3: Mohamed Abdelrazek Author 4: Amr M. AbdelAziz

Chronic kidney disease (CDK) represents a significant public health concern globally, and its prevalence is on the rise. In the context of Kuwait, this study addresses the imperative of predicting CKD by leveraging the wealth of information embedded in electronic health records (EHRs). The primary objective is to develop a… Read full abstract & cite →

Chronic kidney diseases Electronic Health Records (EHR) classification machine learning

Abstract doi.org/10.14569/IJACSA.2024.0150211 PDF

12

Data Manipulation in Wireless Sensor Networks: Enhancing Security Through Blockchain Integration with Proposal Mitigation Strategy

Author 1: Ayoub Toubi Author 2: Abdelmajid Hajami

In recent years, Wireless Sensor Networks (WSNs) have become integral in various applications ranging from environmental monitoring to defense. However, the security and reliability of these networks remain a paramount concern due to their susceptibility to various types of cyber-attacks and failures. This paper proposes a novel integration of blockchain… Read full abstract & cite →

Wireless sensor networks blockchain technology network security data integrity

Abstract doi.org/10.14569/IJACSA.2024.0150212 PDF

13

Web-based Expert Bots System in Identifying Complementary Personality Traits and Recommending Optimal Team Composition

Author 1: Mysaa Fatani Author 2: Haneen Banjar

The use of web-based expert systems in the workplace has become increasingly common in recent years, with companies using these automated tools to streamline a range of tasks, from customer service to employee training. However, the potential of web-based expert bots systems to help build more effective teams by identifying… Read full abstract & cite →

Web-based expert system personality traits team composition workplace efficiency and chatbot integration

Abstract doi.org/10.14569/IJACSA.2024.0150213 PDF

14

Hybrid Intrusion Detection System Based on Data Resampling and Deep Learning

Author 1: Huan Chen Author 2: Gui-Rong You Author 3: Yeou-Ren Shiue

The growth of the internet has advanced information-sharing capabilities and vastly increased the importance of global network security. However, because new and inconspicuous abnormal behaviors are nearly impossible to detect in massive network access environments, modern intrusion detection systems have identified a high rate of false-positive (FP) and false-negative (FN)… Read full abstract & cite →

Intrusion detection deep learning random undersampling synthetic minority oversampling technique convolutional neural network transformer

Abstract doi.org/10.14569/IJACSA.2024.0150214 PDF

15

Addressing Imbalanced Data in Network Intrusion Detection: A Review and Survey

Author 1: Elham Abdullah Al-Qarni Author 2: Ghadah Ahmad Al-Asmari

The proliferation of internet-connected devices, including smartphones, smartwatches, and computers, has led to an unprecedented surge in data generation. The rapid rise in device connectivity points to an urgent need for robust cybersecurity measures to counter the mounting wave of cyber threats. Among the strategies aimed at establishing efficient network… Read full abstract & cite →

Network intrusion detection system data imbalance resampling data level techniques hybrid techniques

Abstract doi.org/10.14569/IJACSA.2024.0150215 PDF

16

Roadmap for Generative Models Redefining Learning in Egyptian Higher Education

Author 1: Laila Mohamed ElFangary

Artificial Intelligence (AI) Generative models have become powerful tools in all sciences, research, academia, and businesses. Egyptian Universities need to leverage those models while using them ethically and responsibly to survive in the current global market. This paper explains the evolution of those models, from basic natural language processing by… Read full abstract & cite →

Artificial intelligence generative models prompt engineering higher education Egyptian universities

Abstract doi.org/10.14569/IJACSA.2024.0150216 PDF

17

A Smart Framework for Enhancing Automated Teller Machines (ATMs) Fraud Prevention

Author 1: Mohamed Abdelsalam Ahmed Author 2: Nada Tarek Abbas Haleem Author 3: Amira M. Idrees

Over the past years, clients have largely depended on and trusted Automated Teller Machines (ATMs) to fulfill their banking needs and control their accounts easily and quickly. Despite the significant advantages of ATMs, fraud has become a very high risk and danger. As it leads to controlling all clients' accounts… Read full abstract & cite →

Automated Teller Machines (ATMs) digital banking image processing iris recognition One Time Password (OTP) machine learning fraud detection fraud prevention biometrics security banking

Abstract doi.org/10.14569/IJACSA.2024.0150217 PDF

18

A Combined Ensemble Model (CEM) for a Liver Cancer Detection System

Author 1: T. Sumallika Author 2: R. Satya Prasad

The liver is one of the most important organs in the human body. The liver's proper function is critical for overall health, and liver diseases or disorders can have serious consequences. Liver cancer is also known as hepatic cancer, which is divided into various types of cells that belong to… Read full abstract & cite →

Liver Cancer Hepatocellular Carcinoma (HCC) Combined Ensemble Model (CEM) RESNET50 Extreme Gradient Boosting (EGB) Recurrent Neural Network (RNN)

Abstract doi.org/10.14569/IJACSA.2024.0150218 PDF

19

Automatic Dust Reduction System: An IoT Intervention for Air quality

Author 1: Bosharah Makki Zakri Author 2: Ohoud Alzamzami Author 3: Amal Babour

Air quality is of great importance due to its direct impact on the environment, human health, and quality of life. It could be affected negatively by the presence of dust particles in the atmosphere. Thus, it is vital to purify air from dust and mitigate its impact on air quality… Read full abstract & cite →

Dust Suppression dust elimination digital dust sensor humidifier dust intensity

Abstract doi.org/10.14569/IJACSA.2024.0150219 PDF

20

Q-KGSWS: Querying the Hybrid Framework of Knowledge Graph and Semantic Web Services for Service Discovery

Author 1: Pooja Thapar Author 2: Lalit Sen Sharma

In the era of big data, Knowledge Graphs (KGs) have become essential tools for managing interconnected datasets across various domains. This paper introduces a novel RDF (Resource Description Framework) based Knowledge Graph of Semantic Web Services (KGSWS), designed to enhance service discovery. Leveraging the versatile SPARQL query language, the framework… Read full abstract & cite →

Ontologies knowledge graph semantic web services SPARQL query language OWLS data integration service discovery

Abstract doi.org/10.14569/IJACSA.2024.0150220 PDF

21

Rural Revitalization Evaluation using a Hybrid Method of BP Neural Network and Genetic Algorithm Based on Deep Learning Model

Author 1: Songmei Wang Author 2: Min Han

The rural revitalization strategy is a comprehensive plan for supporting rural revival in the new development stage while prioritizing agricultural and rural area development. Establishing a rural revitalization evaluation model will help monitor and guide the development of rural revitalization strategies and comprehensively deepen rural reforms. This research combines the… Read full abstract & cite →

The rural revitalization strategy deep learning model the GA-BP neural network evaluation model

Abstract doi.org/10.14569/IJACSA.2024.0150221 PDF

22

Sound Classification for Javanese Eagle Based on Improved Mel-Frequency Cepstral Coefficients and Deep Convolutional Neural Network

Author 1: Silvester Dian Handy Permana Author 2: T. K. Abdul Rahman

The Javanese Eagle is a rare and protected animal in Indonesia. These animals only live in a few species and are threatened with extinction. These birds need to be bred to avoid extinction. One form of communication between the Javanese eagles and each other is the sound of their tweets… Read full abstract & cite →

Improved MFCC deep convolutional neural network Javanese eagle sound sound classification

Abstract doi.org/10.14569/IJACSA.2024.0150222 PDF

23

Ethnicity Classification Based on Facial Images using Deep Learning Approach

Author 1: Abdul-aziz Kalkatawi Author 2: Usman Saeed

Race and ethnicity are terminologies used to describe and categorize humans into groups based on biological and sociological criteria. One of these criteria is the physical appearance such as facial traits which are explicitly represented by a person’s facial structure. The field of computer science has mostly been concerned with… Read full abstract & cite →

Vision transformer deep learning ethnicity race classification recognition

Abstract doi.org/10.14569/IJACSA.2024.0150223 PDF

24

A Driving Area Detection Algorithm Based on Improved Swin Transformer

Author 1: Shuang Liu Author 2: Ying Li Author 3: Huankun Sheng

Drivable area or free space detection is an essential part of the perception system of an autonomous vehicle. It helps intelligent vehicles understand road conditions and determine safe driving areas. Most of the driving area detection algorithms are based on semantic segmentation that classifies each pixel into its category, and… Read full abstract & cite →

CNNS driving area detection multiscale fusion semantic segmentation Swin Transformer

Abstract doi.org/10.14569/IJACSA.2024.0150224 PDF

25

Sky Pixel Detection in Outdoor Urban Scenes: U-Net with Transfer Learning

Author 1: Athar Ibrahim Alboqomi Author 2: Rehan Ullah Khan

The sky depicts a high visual importance in outdoor scenes, often appearing in video sequences and photos. Sky information is crucial for accurate sky detection in several computer vision applications, such as scene understanding, navigation, surveillance, and weather forecasting. The difficulty of detecting is clarified by variations in the sky's… Read full abstract & cite →

Computer vision transfer learning semantic segmentation sky detection U-Net machine learning

Abstract doi.org/10.14569/IJACSA.2024.0150225 PDF

26

Revolutionizing Plant Disease Detection in Leaves: An Innovative Hybrid ABOCNN Framework for Advanced and Accurate Identification

Author 1: V. Krishna Pratap Author 2: N. Suresh Kumar

Plant diseases are a persistent threat to the global agricultural economy, compromising food supply and security. Accurate and early diagnosis is vital for effective agricultural management. This study addresses this gap by introducing a better approach for identifying plant diseases in leaves: the Integrated Hybrid Attention-Based One-Class Neural Network (ABOCNN)… Read full abstract & cite →

Convolutional Neural Network (CNN) attention model leaf disease detection attention-based one-class neural network crop production

Abstract doi.org/10.14569/IJACSA.2024.0150226 PDF

27

AI-Enhanced Comprehensive Liver Tumor Prediction using Convolutional Autoencoder and Genomic Signatures

Author 1: G. Prabaharan Author 2: D. Dhinakaran Author 3: P. Raghavan Author 4: S. Gopalakrishnan Author 5: G. Elumalai

Liver tumor prediction plays a pivotal role in optimizing treatment strategies and improving patient outcomes. In our proposed work, we present an innovative AI-driven framework for liver tumor prediction, uniting cutting-edge techniques to enhance precision and depth of analysis. The framework integrates a Histological Convolutional Autoencoder (HistoCovAE) for meticulous tumor… Read full abstract & cite →

Liver tumor prediction autoencoder segmentation feature extraction genomics artificial intelligence

Abstract doi.org/10.14569/IJACSA.2024.0150227 PDF

28

Improved ORB Algorithm Through Feature Point Optimization and Gaussian Pyramid

Author 1: Rohmat Indra Borman Author 2: Agus Harjoko Author 3: Wahyono

Feature points obtained using traditional ORB methods often exhibit redundancy, uneven distribution, and lack scale invariance. This study enhances the traditional ORB algorithm by presenting an optimal technique for extracting feature points, thereby overcoming these challenges. Initially, the image is partitioned into several areas. The determination of the quantity of… Read full abstract & cite →

Feature point Gaussian pyramid image matching ORB algorithm scale invariance

Abstract doi.org/10.14569/IJACSA.2024.0150228 PDF

29

Performance-Optimised Design of the RISC-V Five-Stage Pipelined Processor NRP

Author 1: Hongkui Li Author 2: Chaoxia Jing Author 3: Jie Liu

The five-stage pipeline processor is a mature and stable processor architecture suitable for many applications in the field of computer hardware. Based on the RISC-V instruction set architecture, the five-stage pipeline processor has advantages in performance, functionality, and power consumption. This paper presents an optimized RV32I five-stage pipeline processor, NRP… Read full abstract & cite →

Architecture FPGA RISC-V RV32I Verilog HDL five-stage

Abstract doi.org/10.14569/IJACSA.2024.0150229 PDF

30

Enhancing Thyroid Cancer Diagnostics Through Hybrid Machine Learning and Metabolomics Approaches

Author 1: Meghana G Raj

Thyroid cancer, a prevalent endocrine malignancy, necessitates advanced diagnostic techniques for accurate and early detection. This study introduces an innovative approach that integrates hybrid Machine Learning (ML) algorithms with metabolomics, offering a novel pathway in thyroid cancer diagnostics. Our methodology employs a range of hybrid ML models, combining the strengths… Read full abstract & cite →

Thyroid cancer hybrid ML models metabolomics diagnostic accuracy

Abstract doi.org/10.14569/IJACSA.2024.0150230 PDF

31

Precision Insulin Delivery: Predictive Modelling for Bolus Insulin Injection in Real-Time

Author 1: V. K. R. Rajeswari Satuluri Author 2: Vijayakumar Ponnusamy

Insulin is recommended for patients with Diabetes Mellitus (DM). It is challenging for doctors to prescribe accurate bolus insulin before every meal due to real-time factors such as the size of the meal, skipping a previous meal, and physical activity, which can risk the patient towards hyperglycemia or hypoglycemia. Previous… Read full abstract & cite →

Continuous glucose monitoring bolus insulin prediction data curation data detersion diabetes mellitus exploratory data analysis feature selection machine learning pre-processing

Abstract doi.org/10.14569/IJACSA.2024.0150231 PDF

32

Cross-Modal Video Retrieval Model Based on Video-Text Dual Alignment

Author 1: Zhanbin Che Author 2: Huaili Guo

Cross-modal video retrieval remains a major challenge in natural language processing due to the natural semantic divide between video and text. Most approaches use a single encoder to extract video and text features separately, and train video-text pairs by means of contrastive learning, but this global alignment of video and… Read full abstract & cite →

Video-text alignment cross-modal contrastive learning similarity measure feature fusion

Abstract doi.org/10.14569/IJACSA.2024.0150232 PDF

33

Elevating Neuro-Linguistic Decoding: Deepening Neural-Device Interaction with RNN-GRU for Non-Invasive Language Decoding

Author 1: V Moses Jayakumar Author 2: R. Rajakumari Author 3: Kuppala Padmini Author 4: Sanjiv Rao Godla Author 5: Yousef A.Baker El-Ebiary Author 6: Vijayalakshmi Ponnuswamy

Exploring innovative pathways for non-invasive neural communication with language interfaces, this research delves into the interdisciplinary realm of neurolinguistic learning, merging neuroscience and machine learning. It scrutinizes the intricacies of decoding neural patterns associated with language comprehension. Leveraging advanced neural network architectures, specifically Deep Recurrent Neural Networks (RNN) and Gated… Read full abstract & cite →

Recurrent Neural Networks (RNN) Gated Recurrent Units (GRU) neurolinguistic learning neural devices brain machine interfaces

Abstract doi.org/10.14569/IJACSA.2024.0150233 PDF

34

Post Pandemic Tourism: Sentiment Analysis using Support Vector Machine Based on TikTok Data

Author 1: Norlina Mohd Sabri Author 2: Siti Nur Athira Muhamad Subki Author 3: Ummu Fatihah Mohd Bahrin Author 4: Mazidah Puteh

The tourism industry is one of the hard hit businesses during the Covid-19 pandemic and has been struggling for backup ever since. However, nowadays the industry has started to bloom again with the lifting of all of the restrictions of Covid-19. This research aims to analyze the sentiments of the… Read full abstract & cite →

Post pandemic tourism support vector machine sentiment classification TikTok data

Abstract doi.org/10.14569/IJACSA.2024.0150234 PDF

35

Investigating the Impact of Train / Test Split Ratio on the Performance of Pre-Trained Models with Custom Datasets

Author 1: Houda Bichri Author 2: Adil Chergui Author 3: Mustapha Hain

The proper allocation of data between training and testing is a critical factor influencing the performance of deep learning models, especially those built upon pre-trained architectures. Having the suitable training set size is an important factor for the classification model’s generalization performance. The main goal of this study is to… Read full abstract & cite →

Artificial intelligence classification MobileNetV2 ResNet50v2 sensitivity specificity train / test split ratio VGG19

Abstract doi.org/10.14569/IJACSA.2024.0150235 PDF

36

Action Recognition Method of Basketball Training Based on Big Data Technology

Author 1: Dongsheng CHEN Author 2: Zhen Ni

Aiming at the problem that improper posture of basketball players leads to not obvious sports effects, the present paper proposes an action recognition method combining computer vision and big data technology and applies it to athletes' daily training and competition. Firstly, based on the current mainstream motion recognition models, 3D… Read full abstract & cite →

Action recognition computer vision big data technology three-dimensional convolution channel and spatial attention mechanisms

Abstract doi.org/10.14569/IJACSA.2024.0150236 PDF

37

Explainable Multistage Ensemble 1D Convolutional Neural Network for Trust Worthy Credit Decision

Author 1: Pavitha N Author 2: Shounak Sugave

Banking is a dynamic industry that places significant importance on risk management, requiring accurate and interpretable AI models to make transparent lending decisions. This study introduces a groundbreaking approach that combines a multistage ensemble technique with a 1D convolutional neural network (CNN) architecture. The algorithm not only delivers superior classification… Read full abstract & cite →

Credit risk prediction explainable AI multistage ensemble 1D convolutional neural network interpretability transparency lending decisions financial institutions

Abstract doi.org/10.14569/IJACSA.2024.0150237 PDF

38

A New Weighted Ensemble Model to Improve the Performance of Software Project Failure Prediction

Author 1: Mohammad A. Ibraigheeth Author 2: Aws I. Abu Eid Author 3: Yazan A. Alsariera Author 4: Waleed F. Awwad Author 5: Majid Nawaz

The development of a software project is frequently influenced by various risk factors that can lead to project failure. Predicting potential software project failures early can aid organizations in making decisions regarding possible solutions and improvements. This paper proposes a software project failure prediction model based on a weighted ensemble… Read full abstract & cite →

Ensemble learning failure prediction base models project outcome

Abstract doi.org/10.14569/IJACSA.2024.0150238 PDF

39

Detection of Personal Protective Equipment (PPE) using an Anchor Free-Convolutional Neural Network

Author 1: Honggang WANG

In industrial environments, the utilization of Personal Protective Equipment (PPE) is paramount for safeguarding workers from potential hazards. While various PPE detection methods have been explored in the literature, deep learning approaches have consistently demonstrated superior accuracy in comparison to other methodologies. However, addressing the pressing research challenge in deep… Read full abstract & cite →

PPE detection deep learning YOLOv8 industrial environments real-time detection

Abstract doi.org/10.14569/IJACSA.2024.0150239 PDF

40

DeepBiG: A Hybrid Supervised CNN and Bidirectional GRU Model for Predicting the DNA Sequence

Author 1: Chai Wen Chuah Author 2: Wanxian He Author 3: De-Shuang Huang

Understanding the deoxyribonucleic acid (DNA) sequence is a major component of bioinformatics research. The amount of biological data increases tremendously. Hence, there is a need for effective approaches to handle the critical problem in the general computational framework of DNA sequence pre-diction and classification. Numerous deep learning languages can be… Read full abstract & cite →

DNA sequencing deep learning convolutional neural networks bidirectional gated recurrent k-mer tokenizing

Abstract doi.org/10.14569/IJACSA.2024.0150240 PDF

41

Actor Critic-based Multi Objective Reinforcement Learning for Multi Access Edge Computing

Author 1: Vishal Khot Author 2: Vallisha M Author 3: Sharan S Pai Author 4: Chandra Shekar R K Author 5: Kayarvizhy N

In recent times, large applications that need near real-time processing are increasingly being used on devices with limited resources. Multi access edge computing is a computing paradigm that provides a solution to this problem by placing servers as close to resource constrained devices as possible. However, the edge device must… Read full abstract & cite →

Edge computing reinforcement learning multi objective optimization neural networks deep learning

Abstract doi.org/10.14569/IJACSA.2024.0150241 PDF

42

A Review on Applications of Electroencephalogram: Includes Imagined Speech

Author 1: S. Santhakumari Author 2: Kamalakannan. J

In the last two decades, the Brain-Computer Interface system with EEG signals has assisted people in various ways. In particular, to patients with paralysis, epilepsy, and Alzheimer's disease, not only to the patient but also to physically, visually challenged people and Hard-of-Hearing people. One of the non-invasive methods that can… Read full abstract & cite →

Electroencephalogram brain signals invasive non-invasive imagined speech electrodes epilepsy

Abstract doi.org/10.14569/IJACSA.2024.0150242 PDF

43

Edge Detail Preservation Technique for Enhancing Speckle Reduction Filtering Performance in Medical Ultrasound Imaging

Author 1: Yasser M. Kadah Author 2: Ahmed F. Elnokrashy

Ultrasound imaging is a unique medical imaging modality due to its clinical versatility, manageable biological effects, and low cost. However, a significant limitation of ultrasound imaging is the noisy appearance of its images due to speckle noise, which reduces image quality and hence makes diagnosis more challenging. Consequently, this problem… Read full abstract & cite →

Edge detail preservation image quality metrics speckle reduction ultrasound imaging

Abstract doi.org/10.14569/IJACSA.2024.0150243 PDF

44

A Neuro-Genetic Security Framework for Misbehavior Detection in VANETs

Author 1: Ila Naqvi Author 2: Alka Chaudhary Author 3: Anil Kumar

Genetic Algorithm (GA) is an excellent optimization algorithm which has attracted the attention of researchers in various fields. Many papers have been published on works done on GA, but no single paper ever utilized this algorithm for misbehavior detection in VANETs. This is because GA requires manual definition of fitness… Read full abstract & cite →

VANET security genetic algorithm ANN fitness function misbehavior detection hybrid detection

Abstract doi.org/10.14569/IJACSA.2024.0150244 PDF

45

Method for Predictive Trend Analytics with SNS Information for Marketing

Author 1: Kohei Arai Author 2: Ikuya Fujikawa Author 3: Yusuke Nakagawa Author 4: Sayuri Ogawa

A method for predictive trend analytics with social media information is proposed for marketing. Through keyword analysis, page view analysis, access analysis, heat map analysis, Google Analytics, real time analysis, company and competitor analysis, trend analysis with the social media data derived from X (former tweeter), Instagram, Facebook, YouTube, TikTok… Read full abstract & cite →

X (former tweeter) Instagram Facebook YouTube TikTok market trend AWS Google analytics keyword analysis page view analysis access analysis heat map analysis

Abstract doi.org/10.14569/IJACSA.2024.0150245 PDF

46

Study on the Implementation of Multimodal Continuous Authentication in Smartphones: A Systematic Review

Author 1: Rahmad Syalevi Author 2: Aji Prasetyo Author 3: Rizal Fathoni Aji

Profound societal shifts result from the inception of the 4.0 age of the Industrial Revolution and rapid technological advancements. The widespread adoption of e-services has resulted in substantial reliance on smartphones to access diverse offerings. Even so, account breaches and data leaks are risks that users take when they rely… Read full abstract & cite →

Authentication continuous multimodal biometric authenticator smartphone

Abstract doi.org/10.14569/IJACSA.2024.0150246 PDF

47

Elevating Student Performance Prediction using Extra-Trees Classifier and Meta-Heuristic Optimization Algorithms

Author 1: Yangbo Li Author 2: Mengfan He

In the highly competitive landscape of academia, the study addresses the multifaceted challenge of analyzing voluminous and diverse educational datasets through the application of machine learning, specifically emphasizing dimensionality reduction techniques. This sophisticated approach facilitates educators in making data-informed decisions, providing timely guidance for targeted academic improvement, and enhancing the… Read full abstract & cite →

Student performance mathematics machine learning Extra-Trees Classifier Gorilla Troops Optimizer Reptile Search Algorithm

Abstract doi.org/10.14569/IJACSA.2024.0150247 PDF

48

Real-Time Airborne Target Tracking using DeepSort Algorithm and Yolov7 Model

Author 1: Yasmine Ghazlane Author 2: Ahmed El Hilali Alaoui Author 3: Hicham Medomi Author 4: Hajar Bnouachir

In light of the explosive growth of drones, it is more critical than ever to strengthen and secure aerial security and privacy. Drones are used maliciously by exploiting some gaps in artificial intelligence and cybersecurity. Airborne target detection and tracking tasks have gained paramount importance in various domains, encompassing surveillance… Read full abstract & cite →

Real-time detection target tracking anti-drone Artificial Intelligence Computer Vision

Abstract doi.org/10.14569/IJACSA.2024.0150248 PDF

49

Towards High Quality PCB Defect Detection Leveraging State-of-the-Art Hybrid Models

Author 1: Tuan Anh Nguyen Author 2: Hoanh Nguyen

The automatic detection of defects in printed circuit boards (PCBs) is a critical step in ensuring the reliability of electronic devices. This paper introduces a novel approach for PCB defect detection. It incorporates a state-of-the-art hybrid architecture that leverages both convolutional neural networks (CNNs) and transformer-based models. Our model comprises… Read full abstract & cite →

PCB defect detection hybrid neural network bottleneck transformer ghost convolution wise-IoU loss

Abstract doi.org/10.14569/IJACSA.2024.0150249 PDF

50

Advancing Parkinson's Disease Severity Prediction using Multimodal Convolutional Recursive Deep Belief Networks

Author 1: Shaikh Abdul Hannan

Parkinson's disease (PD), a progressive neurological ailment predominantly affecting individuals over the age of 60, involves the gradual loss of dopamine-producing neurons. The challenges associated with the subjectivity, resource intensity, and limited efficacy of current diagnostic methods, including the Unified Parkinson’s Disease Rating Scale (UPDRS), neuroimaging, and genetic analysis, underscore… Read full abstract & cite →

Parkinson's Disease (PD) Convolutional Neural Networks (CNN) Deep Belief Networks (DBN) Rat Swarm Optimization (RSO)

Abstract doi.org/10.14569/IJACSA.2024.0150250 PDF

51

Efficiency of Hybrid Decision Tree Algorithms in Evaluating the Academic Performance of Students

Author 1: Yanxin Xie

Educational institutions are anticipated to take substantial and proactive roles in guaranteeing students' successful program completion. Academic performance is conventionally employed to categorize and forecast students' future ability to confront post-graduation challenges. A student's academic accomplishments are instrumental in shaping exceptional individuals who may become future leaders. Using algorithms to… Read full abstract & cite →

Academic performance decision tree pelican optimization algorithm runge kutta optimization

Abstract doi.org/10.14569/IJACSA.2024.0150251 PDF

52

A Novel Robust Stacked Broad Learning System for Noisy Data Regression

Author 1: Kai Zheng Author 2: Jie Liu

Robust broad learning system (RBLS) demonstrates the generalization and robustness for solving uncertain data regression tasks. To enhance representation ability of RBLS, this paper aims at developing a novel robust stacked broad learning system for solving noisy data regression problems, termed as RSBLS. In our work, we expand traditional BLS… Read full abstract & cite →

Robust stacking broad learning system deep learning neural networks

Abstract doi.org/10.14569/IJACSA.2024.0150252 PDF

53

Deep Learning Augmented with SMOTE for Timely Alzheimer's Disease Detection in MRI Images

Author 1: P Gayathri Author 2: N. Geetha Author 3: M. Sridhar Author 4: Ramu Kuchipudi Author 5: K. Suresh Babu Author 6: Lakshmana Phaneendra Maguluri Author 7: B Kiran Bala

Timely diagnosis of Alzheimer's Disease (AD) is pivotal for effective intervention and improved patient outcomes, utilizing Magnetic Resonance Imaging (MRI) to unveil structural brain changes associated with the disorder. This research presents an integrated methodology for early detection of Alzheimer's Disease from Magnetic Resonance Imaging, combining advanced techniques. The framework… Read full abstract & cite →

Alzheimer's disease MRI scans Convolutional Neural Networks (CNNs) Synthetic Minority Over-sampling Technique (SMOTE) Spider Monkey Optimization (SMO)

Abstract doi.org/10.14569/IJACSA.2024.0150253 PDF

54

Load Balancing in DCN Servers Through Software Defined Network Machine Learning

Author 1: Gulbakhram Beissenova Author 2: Aziza Zhidebayeva Author 3: Zhadyra Kopzhassarova Author 4: Pernekul Kozhabekova Author 5: Bayan Myrzakhmetova Author 6: Mukhtar Kerimbekov Author 7: Dinara Ussipbekova Author 8: Nabi Yeshenkozhaev

In this research paper, we delve into the innovative realm of optimizing load balancing in Data Center Networks (DCNs) by leveraging the capabilities of Software-Defined Networking (SDN) and machine learning algorithms. Traditional DCN architectures face significant challenges in handling unpredictable traffic patterns, leading to bottlenecks, network congestion, and suboptimal utilization… Read full abstract & cite →

Software defined network DCN machine learning deep learning server load balancing software

Abstract doi.org/10.14569/IJACSA.2024.0150254 PDF

55

An Intelligent Fuzzy-PID Controller for Supporting Comfort Microclimate in Smart Homes

Author 1: Nazbek Katayev Author 2: Ainur Zhakish Author 3: Nurlan Kulmyrzayev Author 4: Assylzat Abuova Author 5: Sveta Toxanova Author 6: Aiymkhan Ostayeva Author 7: Gulsim Dossanova

Addressing the challenge of ensuring a comfortable indoor environment in both commercial and residential buildings through the use of heating, ventilation, and air conditioning (HVAC) systems is a critical issue. This challenge is intricately connected to the development of sophisticated multi-channel controllers to regulate temperature and humidity effectively. This academic… Read full abstract & cite →

HVAC Fuzzy logic energy management comfort management smart home

Abstract doi.org/10.14569/IJACSA.2024.0150255 PDF

56

Efficient Compression for Remote Sensing: Multispectral Transform and Deep Recurrent Neural Networks for Lossless Hyper-Spectral Imagine

Author 1: D. Anuradha Author 2: Gillala Chandra Sekhar Author 3: Annapurna Mishra Author 4: Puneet Thapar Author 5: Yousef A.Baker El-Ebiary Author 6: Maganti Syamala

Remote sensing technologies, which are essential for everything from environmental monitoring to disaster relief, enable large-scale multispectral data collection. In the field of hyper-spectral imaging, where high-dimensional data is required for precise analysis, effective compression techniques are critical for transmission and storage. In the field of hyper-spectral imaging, the development… Read full abstract & cite →

Multi-Spectral transform lossless compression hyper-spectral data deep recurrent neural network compression algorithms

Abstract doi.org/10.14569/IJACSA.2024.0150256 PDF

57

MR-FNC: A Fake News Classification Model to Mitigate Racism

Author 1: Muhammad Kamran Author 2: Ahmad S. Alghamdi Author 3: Ammar Saeed Author 4: Faisal S. Alsubaei

One of the most challenging tasks while processing natural language text is to authenticate the correctness of the provided information particularly for classification of fake news. Fake news is a growing source of apprehension in recent times for hate speech as well. For instance, the followers of various beliefs face… Read full abstract & cite →

Machine learning deep learning fake news detection social media

Abstract doi.org/10.14569/IJACSA.2024.0150257 PDF

58

i-Tech: Empowering Educators to Bring Experimental Learning to Classrooms

Author 1: Amani Alqarni Author 2: Jieyu Wang Author 3: Abdullah Abuhussein

The integration of technology in education has gained significant attention, with Virtual Reality (VR), Augmented Reality (AR), and 360° VR emerging as transformative tools for enhancing student learning experiences. Despite their potential benefits, these immersive technologies have not achieved widespread adoption in education. Educators face numerous challenges in finding suitable… Read full abstract & cite →

Virtual reality 360° video user behavior analysis content delivery immersive media education technology in education instructional design human-computer interaction

Abstract doi.org/10.14569/IJACSA.2024.0150258 PDF

59

A Lightweight Neural Network for Accurate Rice Panicle Detection and Counting in Field Conditions

Author 1: Wenchao Xu Author 2: Yangxu Wang

Monitoring rice spikelet yield is crucial for ensuring food security, but manual observations are tedious and subjective. Deep learning approaches for automated counting often require high device resources, limiting their applicability on low-cost edge devices. This paper presents the Rice Lightweight Feature Detection Network (RLFDNet). RLFDNet designed for the field… Read full abstract & cite →

Computer vision deep learning lightweight neural network architecture remote sensing

Abstract doi.org/10.14569/IJACSA.2024.0150259 PDF

60

Integrating Taguchi Method and Support Vector Machine for Enhanced Surface Roughness Modeling and Optimization

Author 1: Ashanira Mat Deris Author 2: Rozniza Ali Author 3: Ily Amalina Ahmad Sabri Author 4: Nurezayana Zainal

End milling process is widely used in various industrial applications, including health, aerospace and manufacturing industries. Over the years, machine technology of end milling has grown exponentially to attain the needs of various fields especially in manufacturing industry. The main concern of manufacturing industry is to obtain good quality products… Read full abstract & cite →

Support Vector Machine surface roughness end milling Taguchi method

Abstract doi.org/10.14569/IJACSA.2024.0150260 PDF

61

Image Retrieval Evaluation Metric for Songket Motif

Author 1: Nadiah Yusof Author 2: Amirah Ismail Author 3: Nazatul Aini Abd Majid Author 4: Zurina Muda

Songket is a fine art heritage specializing in promoting the unique features of Malay identity. Past studies have shown that hundreds of Songket motifs had been produced, but unfortunately, most were not stored digitally. However, the digital collection of image data and determining its ground truth data should be given… Read full abstract & cite →

Heritage songket motifs songket motifs retrieval ground truth data

Abstract doi.org/10.14569/IJACSA.2024.0150261 PDF

62

An Approach to Classifying X-Ray Images of Scoliosis and Spondylolisthesis Based on Fine-Tuned Xception Model

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

The vertebral column is a marvel of biological engineering and it considers a main part of the skeleton in vertebrate animals. In addition, it serves as the central axis of the human body comprising a series of interlocking vertebrae that provide structural support and flexibility. From basic works like bending… Read full abstract & cite →

Transfer learning fine tuning spondylolisthesis scoliosis classification Xception

Abstract doi.org/10.14569/IJACSA.2024.0150262 PDF

63

Toward Enhanced Customer Transaction Insights: An Apriori Algorithm-based Analysis of Sales Patterns at University Industrial Corporation

Author 1: Alex Alfredo Huaman Llanos Author 2: Lenin Quiñones Huatangari Author 3: Jeimis Royler Yalta Meza Author 4: Alexander Huaman Monteza Author 5: Orestes Daniel Adrianzen Guerrero Author 6: John Smith Rodriguez Estacio

The University Industrial Corporation (CIU) at the National University of Jaen offers a range of consumable products, encompassing nectar, water, coffee, chocolate, and chocoteja. However, its sales transactions function without a systematic analysis. To address this, the study gathered and analyzed sales data from March to November 2023, aiming to… Read full abstract & cite →

Apriori algorithm association rules Customer Relationship Management (CRM) decision making text mining

Abstract doi.org/10.14569/IJACSA.2024.0150263 PDF

64

Automated Detection of Autism Spectrum Disorder Symptoms using Text Mining and Machine Learning for Early Diagnosis

Author 1: Mihaela Chistol Author 2: Mirela Danubianu

Autism spectrum disorder (ASD) is a neurological condition whose etiology is still insufficiently understood. The heterogeneity of manifestations makes the diagnosis process difficult. Thus, many children are diagnosed too late, which leads to the loss of precious time that can be used for therapy. A viable solution could be to… Read full abstract & cite →

Text mining machine learning artificial intelligence assistive technologies Autism Spectrum Disorder early diagnosis screening

Abstract doi.org/10.14569/IJACSA.2024.0150264 PDF

65

A Novel Inter Patient ECG Arrhythmia Classification Approach with Deep Feature Extraction and 1D Convolutional Neural Network

Author 1: Mohamed Elmehdi Ait Bourkha Author 2: Anas Hatim Author 3: Dounia Nasir Author 4: Said El Beid Author 5: Assia Sayed Tahiri

The World Health Organization (WHO) sheds light on the escalating prevalence of heart diseases, foreseeing a substantial rise in the years ahead, impacting a vast global population. Swift and accurate early detection becomes pivotal in managing severe complications, underscoring the urgency of timely identification. While Ventricular Ectopic Beats (V) might… Read full abstract & cite →

Electrocardiogram (ECG) Cardiovascular Diseases (CVD) Wavelet Scattering Transform (WST) Convolutional Neural Network (CNN)

Abstract doi.org/10.14569/IJACSA.2024.0150265 PDF

66

Leveraging Machine Learning for Enhanced Cyber Attack Detection and Defence in Big Data Management and Process Mining

Author 1: Taviti Naidu Gongada Author 2: Amit Agnihotri Author 3: Kathari Santosh Author 4: Vijayalakshmi Ponnuswamy Author 5: Narendran S Author 6: Tripti Sharma Author 7: Yousef A.Baker El-Ebiary

The rapidly developing field of "Commercial Operation Divergence Analysis," this research seeks to identify and understand differences in commercial systems that exceed expected results. Approaches in this domain aim to identify the characteristics of process implementations that are associated with changes in process effectiveness. This entails identifying the features of… Read full abstract & cite →

Machine learning data mining cyber-attack detection big data support vector regression

Abstract doi.org/10.14569/IJACSA.2024.0150266 PDF

67

Utilizing Federated Learning for Enhanced Real-Time Traffic Prediction in Smart Urban Environments

Author 1: Mamta Kumari Author 2: Zoirov Ulmas Author 3: Suseendra R Author 4: Janjhyam Venkata Naga Ramesh Author 5: Yousef A. Baker El-Ebiary

Federated Learning (FL), a crucial advancement in smart city technology, combines real-time traffic predictions with the potential to enhance urban mobility. This paper suggests a novel approach to real-time traffic prediction in smart cities: a hybrid Convolutional Neural Network-Recurrent Neural Network (CNN-RNN) architecture. The investigation started with the systematic collection… Read full abstract & cite →

Federated Learning smart city convolutional neural network recurrent neural network traffic prediction

Abstract doi.org/10.14569/IJACSA.2024.0150267 PDF

68

Elevating Smart Industry Security: An Advanced IoT-Integrated Framework for Detecting Suspicious Activities using ELM and LSTM Networks

Author 1: Mohammad Eid Alzahrani

The proliferation of Internet of Things (IoT) devices in smart industrial contexts necessitates robust security measures to thwart potential threats. This study addresses the escalating security challenges arising from the widespread deployment of IoT devices in smart industrial environments. Focusing on the identification and categorization of potentially harmful activities, our… Read full abstract & cite →

Internet of Things (IoT) Smart Industries Extreme Learning Machine (ELM) Long Short-Term Memory (LSTM) Activity Recognition

Abstract doi.org/10.14569/IJACSA.2024.0150268 PDF

69

Enhancing Agricultural Yield Forecasting with Deep Convolutional Generative Adversarial Networks and Satellite Data

Author 1: D. Anuradha Author 2: Ramu Kuchipudi Author 3: B Ashreetha Author 4: Janjhyam Venkata Naga Ramesh Author 5: Ayadi Rami

Ensuring food security amidst growing global population and environmental changes is imperative. This research introduces a pioneering approach that integrates cutting-edge deep learning techniques. Deep Convolutional Generative Adversarial Networks (DCGANs) and Convolutional Neural Networks (CNNs) with high-resolution satellite imagery to optimize agricultural yield prediction. The model leverages DCGANs to generate… Read full abstract & cite →

Agricultural yield prediction DCGANs CNN satellite imagery data augmentation synthetic image generation

Abstract doi.org/10.14569/IJACSA.2024.0150269 PDF

70

Analyzing Multiple Data Sources for Suicide Risk Detection: A Deep Learning Hybrid Approach

Author 1: Saraf Anika Author 2: Swarup Dewanjee Author 3: Sidratul Muntaha

In the current digital landscape, social media’s extensive user-generated content presents a unique opportunity for identifying emotional distress signals. With suicide rates on the rise, this study takes aid of Natural Language Processing (NLP) and Sentiment Analysis to detect suicide risk. Centering primarily around deep learning (DL) architectures, including Convolutional… Read full abstract & cite →

BiGRU-CNN hybrid multisource dataset word embeddings NLP sentiment analysis cross-dataset testing

Abstract doi.org/10.14569/IJACSA.2024.0150270 PDF

71

Enhancing the Odia Handwritten Character and Numeral Recognition System's Performance with an Ensemble of Deep Neural Networks

Author 1: Mamatarani Das Author 2: Mrutyunjaya Panda Author 3: Soumya Sahoo

Offline handwritten character recognition (OHCR) is considered a challenging task in pattern recognition due to the inter-class similarity and intra-class variations among the symbols present in the alphabet set. In this work, a learning-based weighted average ensemble of deep neural network models (WEnDNN) is proposed to classify the 10 digits… Read full abstract & cite →

Odia language ensemble learning machine learning Gabor features CNN DNN

Abstract doi.org/10.14569/IJACSA.2024.0150271 PDF

72

Monitoring Student Attendance Through Vision Transformer-based Iris Recognition

Author 1: Slimane Ennajar Author 2: Walid Bouarifi

In the context of the ongoing digital transformation, the effective monitoring of student attendance holds paramount significance for educational establishments. This study presents an innovative approach using Vision Transformer technology for iris recognition to automate student attendance tracking. We fine-tuned Vision Transformer models, specifically ViT-B16, ViT-B32, ViT-L16, and ViT-L32, using… Read full abstract & cite →

Iris Recognition Vision transformer student attendance vision transformer models educational technology

Abstract doi.org/10.14569/IJACSA.2024.0150272 PDF

73

Employing a Hybrid Convolutional Neural Network and Extreme Learning Machine for Precision Liver Disease Forecasting

Author 1: Araddhana Arvind Deshmukh Author 2: R. V. V. Krishna Author 3: Rahama Salman Author 4: S Sandhiya Author 5: Balajee J Author 6: Daniel Pilli

This paper discusses the critical relevance of precise forecasting in liver disease, as well as the need for early identification and categorization for immediate action and personalized treatment strategies. The paper describes a unique strategy for improving liver disease classification using ultrasound image processing. The recommended technique combines the properties… Read full abstract & cite →

Liver disease prognosis convolutional neural network extreme learning machine grey wolf optimization patient care

Abstract doi.org/10.14569/IJACSA.2024.0150273 PDF

74

Personalized Recommendation Algorithm Based on Trajectory Mining Model in Intelligent Travel Route Planning

Author 1: Jingya Shi Author 2: Qianyao Sun

With the increasing demand for personalized travel, traditional travel route planning methods are no longer able to meet the diverse needs of users. In view of this, on the ground of the analysis of user trajectory data at the temporal and spatial levels, a new scenic spot recommendation model is… Read full abstract & cite →

Trajectory mining personalized recommendations travel routes genetic algorithm visiting sequence of scenic spots

Abstract doi.org/10.14569/IJACSA.2024.0150274 PDF

75

Animation Media Art Teaching Design Based on Big Data Fusion Technology

Author 1: Rongjuan Wang Author 2: Yiran Tao

Animation, as an ancient art expression form, still has vigorous development, and the need for animation talents in society is increasing daily. This study first introduces the definition of animation and the development of animation at home and abroad. After that, the classification regression tree algorithm's principle and function theorem… Read full abstract & cite →

Animation big data fusion classification regression tree algorithm media art teaching system

Abstract doi.org/10.14569/IJACSA.2024.0150275 PDF

76

Advancing Human Action Recognition and Medical Image Segmentation using GRU Networks with V-Net Architecture

Author 1: Dustakar Surendra Rao Author 2: L. Koteswara Rao Author 3: Vipparthi Bhagyaraju Author 4: P. Rohini

Human Action Recognition and Medical Image Segmentation study presents a novel framework that leverages advanced neural network architectures to improve Medical Image Segmentation and Human Action Recognition (HAR). Gated Recurrent Units (GRU) are used in the HAR domain to efficiently capture complex temporal correlations in video sequences, yielding better accuracy… Read full abstract & cite →

Human action recognition medical image segmentation grated rectifier unit V-net architecture neural network

Abstract doi.org/10.14569/IJACSA.2024.0150276 PDF

77

Occupancy Measurement in Under-Actuated Zones: YOLO-based Deep Learning Approach

Author 1: Ade Syahputra Author 2: Yaddarabullah Author 3: Mohammad Faiz Azhary Author 4: Aedah Binti Abd Rahman Author 5: Amna Saad

The challenge of accurately detecting and identifying individuals within under-actuated zones presents a relevant research problem in occupant detection. This study aims to address the challenge of occupant detection in under-actuated zones through the utilization of the You Only Look Once version 8 (YOLO v8) object detection model. The research… Read full abstract & cite →

YOLO HVAC system occupant’s position occupant calculation under-actuated zone

Abstract doi.org/10.14569/IJACSA.2024.0150277 PDF

78

Efficient Simulation of Light Scattering Effects in the Atmosphere

Author 1: Huiling Guo Author 2: Xiliang Ren Author 3: Jing Zhao Author 4: Yong Tang

Atmospheric light scattering encompasses intricate physical process, including diverse scattering mechanisms and optical parameters. Addressing the challenges posed by the computationally intensive task of deciphering this phenomenon, this study introduces an efficient real-time simulation strategy. The proposed approach employs a physics-driven atmospheric modeling, leveraging a unified phase function to emulate… Read full abstract & cite →

Light scattering ray marching jittered sampling color synthesis real-time rendering

Abstract doi.org/10.14569/IJACSA.2024.0150278 PDF

79

Semantic Information Classification of IoT Perception Data Based on Density Peak Fast Search Clustering Algorithm

Author 1: Lin Chen Author 2: Jinli Hu Author 3: Weisheng Wang

In the rapidly developing field of the Internet of Things today, effective processing and analysis of perceptual data has become crucial. The perception data of the Internet of Things is usually large, diverse, and presents high-dimensional characteristics, which poses new challenges to data clustering algorithms. This study utilizes the K-center… Read full abstract & cite →

Clustering algorithm Internet of Things perceived data classification peak density semantic information

Abstract doi.org/10.14569/IJACSA.2024.0150279 PDF

80

Structure-Aware Scheduling Algorithm for Deadline-Constrained Scientific Workflows in the Cloud

Author 1: Ali Al-Haboobi Author 2: Gabor Kecskemeti

Cloud computing provides pay-per-use IT services through the Internet. Although cloud computing resources can help scientific workflow applications, several algorithms face the problem of meeting the user’s deadline while minimising the cost of workflow execution. In the cloud, selecting the appropriate type and the exact number of VMs is a… Read full abstract & cite →

Workflow scheduling workflow structure cloud computing resource provisioning deadline constrained infrastructure as a service

Abstract doi.org/10.14569/IJACSA.2024.0150280 PDF

81

Prominent Security Vulnerabilities in Cloud Computing

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

This research study examines the significant security vulnerabilities and threats in cloud computing, analyzes their potential consequences for enterprises, and proposes effective solutions for mitigating these vulnerabilities. This paper discusses the increasing significance of cloud security in a time characterized by rapid data expansion and technological progress. The paper examines… Read full abstract & cite →

Cloud computing vulnerabilities cloud security cloud misconfigurations data loss threats

Abstract doi.org/10.14569/IJACSA.2024.0150281 PDF

82

DDoS Attacks Detection in IoV using ML-based Models with an Enhanced Feature Selection Technique

Author 1: Ohoud Ali Albishi Author 2: Monir Abdullah

The Internet of Vesicles (IoV) is an open and integrated network system with high reliability and security control capabilities. The system consists of vehicles, users, in-frastructure, and related networks. Despite the many advantages of IoV, it is also vulnerable to various types of attacks due to the continuous and increasing… Read full abstract & cite →

Random forest IoV DDoS feature selection

Abstract doi.org/10.14569/IJACSA.2024.0150282 PDF

83

A Review on DDoS Attacks Classifying and Detection by ML/DL Models

Author 1: Haya Malooh Alqahtani Author 2: Monir Abdullah

Internet security is under serious threat due to Distributed Denial of Service (DDoS) attacks. These attacks inflict considerable damage by disrupting network services, resulting in the impairment and complete disablement of system functions. The accurate classification and detection of DDoS attacks is extremely important. We provide a review of different… Read full abstract & cite →

Classification DDoS attacks machine learning cybersecurity detection

Abstract doi.org/10.14569/IJACSA.2024.0150283 PDF

84

TPMN: Texture Prior-Aware Multi-Level Feature Fusion Network for Corrugated Cardboard Parcels Defect Detection

Author 1: Xing He Author 2: Haoxiang Fan Author 3: Cuifeng Du Author 4: Xingyu Zhu Author 5: Yuyu Zhou Author 6: Renzhang Chen Author 7: Zhefu Li Author 8: Guihua Zheng Author 9: Yuansheng Zhong Author 10: Changjiang Liu Author 11: Jiandan Yang Author 12: Quanlong Guan

Surface defect detection is the task of identifying and localizing defects on the surface of an object, which is a widely applied task in various industries. In the logistics industry, logistics companies need to monitor the condition of goods for potential defects throughout the entire logistics process for effective logistics… Read full abstract & cite →

Logistics surface defect detection multi-level feature fusion prior attention corrugated cardboard boxes

Abstract doi.org/10.14569/IJACSA.2024.0150284 PDF

85

An Ensemble Dynamic Model and Bio-Inspired Feature Selection Method-based Decision Support System for Predicting Multiple Organ Dysfunction Syndrome in the ICU

Author 1: Anas Maach Author 2: El Houssine El Mazoudi Author 3: Jamila Elalami Author 4: Noureddine Elalami

Multiple Organ Dysfunction Syndrome (MODS) is one of the most common and severe conditions affecting patients admitted to intensive care units (ICUs). It is characterized by the simultaneous failure or dysfunction of at least two organ systems. Although no specific remedy for MODS has been identified to date, early diagnosis… Read full abstract & cite →

Ensemble dynamic model MODS prediction decision support system Bio-Inspired feature selection

Abstract doi.org/10.14569/IJACSA.2024.0150285 PDF

86

Cephalometric Landmarks Identification Through an Object Detection-based Deep Learning Model

Author 1: Idriss Tafala Author 2: Fatima-Ezzahraa Ben-Bouazza Author 3: Aymane Edder Author 4: Oumaima Manchadi Author 5: Mehdi Et-Taoussi Author 6: Bassma Jioudi

In the field of orthodontics, the accurate identification of cephalometric landmarks in dental radiography plays a crucial role in ensuring precise diagnoses and efficient treatment planning. Previous studies have demonstrated the impressive capabilities of advanced deep learning models in this particular domain. However, due to the ever-changing technological landscape, it… Read full abstract & cite →

Cephalometry YOLOv8 landmark detection orthodontics

Abstract doi.org/10.14569/IJACSA.2024.0150286 PDF

87

A Robust License Plate Detection and Recognition Framework for Arabic Plates with Severe Tilt Angles

Author 1: Khaled Hefnawy Author 2: Ahmed Lila Author 3: Elsayed Hemayed Author 4: Mohamed Elshenawy

This paper addresses the challenge of accurately detecting and recognizing Arabic license plates, particularly those subjected to severe tilt angles. It presents a robust license plate detection and recognition framework that consists three main steps: plate detection and segmentation, plate perspective correction, and vehicle number recognition. In the first step… Read full abstract & cite →

License plate detection license plate recognition feature extraction Mask R-CNN object detection

Abstract doi.org/10.14569/IJACSA.2024.0150287 PDF

88

Future Iris Imaging with Advanced Fuzzified Histogram Equalization

Author 1: Nurul Amirah Mashudi Author 2: Norulhusna Ahmad Author 3: Rudzidatul Akmam Dziyauddin Author 4: Norliza Mohd Noor

Images captured under low lighting frequently exhibit low brightness, low contrast, and a small grayscale. These features can affect the individual’s view and severely limit the performance of machine vision systems, particularly when data annotation is involved. Hence, the issues motivate this study to examine the effectiveness of advanced fuzzified… Read full abstract & cite →

Image enhancement fuzzy logic histogram equalization CLAHE iris recognition

Abstract doi.org/10.14569/IJACSA.2024.0150288 PDF

89

IMEO: Anomaly Detection for IoT Devices using Semantic-based Correlations

Author 1: Seungmin Oh Author 2: Jihye Hong Author 3: Daeho Kim Author 4: Eun-Kyu Lee Author 5: Junghee Jo

In the Internet of Things (IoT) security, anomalies due to attacks or device malfunctions can have serious consequences in our daily lives. Previous solutions have been struggling with high rates of false alarms and missing many actual anomalies. They also take a long time to detect anomalies even if they… Read full abstract & cite →

Security anomaly detection semantics Internet of Things attack

Abstract doi.org/10.14569/IJACSA.2024.0150289 PDF

90

Cross-Modal Sentiment Analysis Based on CLIP Image-Text Attention Interaction

Author 1: Xintao Lu Author 2: Yonglong Ni Author 3: Zuohua Ding

Multimodal sentiment analysis is a traditional text-based sentiment analysis technique. However, the field of multi-modal sentiment analysis still faces challenges such as inconsistent cross-modal feature information, poor interaction capabilities, and insufficient feature fusion. To address these issues, this paper proposes a cross-modal sentiment model based on CLIP image-text attention interaction… Read full abstract & cite →

Multi-modal image-text interaction multi-head attention mechanism sentiment analysis cross-modal fusion

Abstract doi.org/10.14569/IJACSA.2024.0150290 PDF

91

Automation Process for Learning Outcome Predictions

Author 1: Minh-Phuong Han Author 2: Trung-Tung Doan Author 3: Minh-Hoan Pham Author 4: Trung-Tuan Nguyen

This paper presents a comprehensive study on the evaluation of algorithms for automating learning outcome predictions, with a focus on the application of machine learning techniques. We investigate various predictive models (logistic regression, random forest, gaussian naive bayes, k-nearest neighbors and support vector regression) to assess their efficacy in forecasting… Read full abstract & cite →

Machine learning predictive learning outcomes education logistic regression k-nearest neighbors Gaussian Naive Bayes Random Forest support vector regression

Abstract doi.org/10.14569/IJACSA.2024.0150291 PDF

92

Enhancing K-means Clustering Results with Gradient Boosting: A Post-Processing Approach

Author 1: Mousa Alzakan Author 2: Hissah Almousa Author 3: Arwa Almarzoqi Author 4: Mohammed Alghasham Author 5: Munirah Aldawsari Author 6: Mohammed Al-Hagery

As the volume and complexity of data continue to grow exponentially, finding efficient and accurate clustering algorithms has become crucial for many applications. K-means clustering is a widely used unsupervised machine learning technique for data analysis and pattern recognition. Despite its popularity, k-means suffers from certain limitations, such as sensitivity… Read full abstract & cite →

K-means gradient boosting post-processing mis-classification machine learning

Abstract doi.org/10.14569/IJACSA.2024.0150292 PDF

93

Optimizing Grape Leaf Disease Identification Through Transfer Learning and Hyperparameter Tuning

Author 1: Hoang-Tu Vo Author 2: Kheo Chau Mui Author 3: Nhon Nguyen Thien Author 4: Phuc Pham Tien Author 5: Huan Lam Le

Grapes are a globally cultivated fruit with significant economic and nutritional value, but they are susceptible to diseases that can harm crop quality and yield. Identifying grape leaf diseases accurately and promptly is vital for effective disease management and sustainable viticulture. To address this challenge, we employ a transfer learning… Read full abstract & cite →

Grape disease recognition disease identification transfer learning hyperparameter optimization hyperband strat-egy fine-tuning deep learning

Abstract doi.org/10.14569/IJACSA.2024.0150293 PDF

94

An Internet of Things-based Predictive Maintenance Architecture for Intensive Care Unit Ventilators

Author 1: Oumaima Manchadi Author 2: Fatima-Ezzahraa BEN-BOUAZZA Author 3: Zineb El Otmani Dehbi Author 4: Aymane Edder Author 5: Idriss Tafala Author 6: Mehdi Et-Taoussi Author 7: Bassma Jioudi

Intensive care units commonly utilize mechanical ventilators to treat patients with different medical conditions, which are crucial for patient care and survival. ICU ventilators have evolved through four distinct generations, each displaying unique features. Despite progress made since the 1940s, contemporary designs are insufficient to meet the increasing needs of… Read full abstract & cite →

Internet of things predictive maintenance embed-ded Machine learning data analytics failure modes mechanical ventilator

Abstract doi.org/10.14569/IJACSA.2024.0150294 PDF

95

Predicting Aircraft Engine Failures using Artificial Intelligence

Author 1: Asmae BENTALEB Author 2: Kaoutar TOUMLAL Author 3: Jaafar ABOUCHABAKA

Nowadays, the aviation sector continues to develop especially with the emergence of new technologies, and solutions. Hence, there is an increasing demand for enhanced safety and operational efficiency in the aviation industry. As to guarantee this safety, the aircraft’s engines must be monitored, controlled and maintained, however in an efficient… Read full abstract & cite →

Aircraft engine failures machine learning predic-tive maintenance C-MAPSS aviation safety

Abstract doi.org/10.14569/IJACSA.2024.0150295 PDF

96

A Hybrid Model for Ischemic Stroke Brain Segmentation from MRI Images using CBAM and ResNet50-Unet

Author 1: Fathia ABOUDI Author 2: Cyrine DRISSI Author 3: Tarek KRAIEM

Ischemic stroke is the most prevalent type of stroke and a leading cause of mortality and long-term impairment globally. Timely identification, precise localization, and early detection of ischemic stroke lesions brain are critical in healthcare. Various modalities are employed for detection, and magnetic resonance imaging stands out as the most… Read full abstract & cite →

Medical image segmentation ischemic stroke disease UNet ResNet50 convolution block attention module magnetic resonance imaging transfer learning

Abstract doi.org/10.14569/IJACSA.2024.0150296 PDF

97

Optimizing Bandwidth Reservation Decision Time in Vehicular Networks using Batched LSTM

Author 1: Abdullah Al-khatib Author 2: Klaus Moessner Author 3: Holger Timinger

Time-sensitive and safety-critical networked vehicular applications, such as autonomous driving, require deterministic guaranteed resources. This is achieved through advanced individual bandwidth reservations. The efficient timing of a vehicle decision to place a cost-efficient reservation request is crucial, as vehicles typically lack sufficient information about future bandwidth resource availability and costs… Read full abstract & cite →

Networked vehicular application time-sensitive net-working network reservation batched LSTM

Abstract doi.org/10.14569/IJACSA.2024.0150297 PDF

98

An Algorithm Based on Priority Rules for Solving a Multi-drone Routing Problem in Hazardous Waste Collection

Author 1: Youssef Harrath Author 2: Jihene Kaabi Author 3: Eman Alaradi Author 4: Manar Alnoaimi Author 5: Noor Alawadhi

This research investigates the problem of assigning pre-scheduled trips to multiple drones to collect hazardous waste from different sites in the minimum time. Each drone is subject to essential restrictions: maximum flying capacity and recharge operation. The goal is to assign the trips to the drones so that the waste… Read full abstract & cite →

Drones trip assignment priority rules flying capacity load balance

Abstract doi.org/10.14569/IJACSA.2024.0150298 PDF

99

The Management System of IoT Informatization Training Room Based on Improved YOLOV4 Detection and Recognition Algorithm

Author 1: Huiling Hu

In response to the problems of low recognition rate and long system operation time in equipment detection management in the existing IoT information training room management system. A research has proposed an IoT information training room equipment detection management system on the ground of an improved YOLOV4 detection and recognition… Read full abstract & cite →

YOLOV4 algorithm Internet of Things informatization training room management system detection and recognition

Abstract doi.org/10.14569/IJACSA.2024.0150299 PDF

100

Diagnosing Autism Spectrum Disorder in Pediatric Patients via Gait Analysis using ANN and SVM with Electromyography Signals

Author 1: Rozita Jailani Author 2: Nur Khalidah Zakaria Author 3: M. N. Mohd Nor Author 4: Heru Supriyono

Autism Spectrum Disorder (ASD) is a permanent neurological maturation condition that impacts communication, social interaction, and behavior. It is also associated with atypical walking patterns. This study aims to create an automated classification model to distinguish ASD children during walking based on the muscles Electromyography (EMG) signals. The study involved… Read full abstract & cite →

Autism Spectrum Disorder Electromyography signals Artificial Neural Network Support Vector Machine precision health

Abstract doi.org/10.14569/IJACSA.2024.01502100 PDF

101

Improving Load Balance in Fog Nodes by Reinforcement Learning Algorithm

Author 1: Hongwei DING Author 2: Ying ZHANG

Fog computing is a distributed computing concept that brings cloud services out to the network's edge. Real-time user queries and data streams are processed by cloud nodes. Tasks should be evenly divided among fog nodes in order to maximize speed and efficiency, optimize resource efficiency, and reaction time. Real-time user… Read full abstract & cite →

Fog computing resource allocation reinforcement learning delay load balancing fog nodes

Abstract doi.org/10.14569/IJACSA.2024.01502101 PDF

102

Construction of an Art Education Teaching System Assisted by Artificial Intelligence

Author 1: Xianyu Wang Author 2: Xiaoguang Sun

With the continuous progress of art education and artificial intelligence technology, traditional music teaching models are facing transformation. This article aims to construct an art education and teaching system based on artificial intelligence, especially for teaching music sound recognition. Through in-depth research, we have designed a music sound recognition system… Read full abstract & cite →

Feature extraction BP neural network Tone recognition smart art teaching MEL frequency cepstral coefficient MFCC algorithm time frequency characteristics

Abstract doi.org/10.14569/IJACSA.2024.01502102 PDF

103

Design of Big Data Task Scheduling Optimization Algorithm Based on Improved Deep Q-Network

Author 1: Fu Chen Author 2: Chunyi Wu

Big data analysis can provide valuable insights not easily obtained from traditional data scales. However, addressing scheduling issues in big data can be challenging due to the vast amount and diverse nature of the data. To overcome this, a scheduling model based on Markov decision process is proposed. The deep… Read full abstract & cite →

Big data Task scheduling Policy gradient Deep Q-network

Abstract doi.org/10.14569/IJACSA.2024.01502103 PDF