IJACSA Vol. 14 Issue 12 (2023)

1

Computer Vision-based Efficient Segmentation Method for Left Ventricular Epicardium and Endocardium using Deep Learning

Author 1: A F M Saifuddin Saif Author 2: Trung Duong Author 3: Zachary Holden

Segmentation of the Left Ventricular Epicardium and Endocardium remains challenging and significant for valuable investigation of cardiac image classification. Previous research methods did not consider the flexibility of the heart area, so measurements needed to be more consistent and accurate. In addition, previous methods ignored the presence of affectability and… Read full abstract & cite →

Convolutional neural network segmentation computer vision deep learning

Abstract doi.org/10.14569/IJACSA.2023.0141201 PDF

2

Predicting Alzheimer's Progression in Mild Cognitive Impairment: Longitudinal MRI with HMMs and SVM Classifiers

Author 1: Deep Himmatbhai Ajabani

The number of elderly people has increased due to the huge growth in human life expectancy over the past few decades. As a result, age-related illnesses and ailments have become more prevalent, including Alzheimer's Disease (AD). A notable deterioration in cognitive functions, particularly memory and thinking skills, characterizes Mild Cognitive… Read full abstract & cite →

Alzheimer's disease image processing Magnetic Resonance Imaging Mild Cognitive Impairment machine learning

Abstract doi.org/10.14569/IJACSA.2023.0141202 PDF

3

Integrating Social Media Data and Historical Stock Prices for Predictive Analysis: A Reinforcement Learning Approach

Author 1: Mei Li Author 2: Ye Zhang

The reliance on data collection for assessing individual behavior and actions has intensified, particularly with the proliferation of digital platforms. People often use the Internet to express their opinions and experiences about various products and services on social media and personal websites. Concurrently, the stock market, a key driver of… Read full abstract & cite →

Social media stock market sentiment analysis unbalanced classification reinforcement learning differential equation long short-term memory

Abstract doi.org/10.14569/IJACSA.2023.0141203 PDF

4

Cloud Migration: Identifying the Sources of Potential Technical Challenges and Issues

Author 1: Nevena Staevsky Author 2: Silvia Gaftandzhieva

Digital Transformation is emerging as a crucial factor for successful adaptation to the modern digital world for all possible economic and social entities. In recent years, cloud migration, cloud services and computing solutions adoption have been popular enablers for the Digital Transformation. During the Digital Transformation process, organizations and institutions… Read full abstract & cite →

Digital transformation cloud cloud migration cloud models PaaS SaaS IaaS challenges

Abstract doi.org/10.14569/IJACSA.2023.0141204 PDF

5

Technology-Mediated Interventions for Autism Spectrum Disorder

Author 1: Mihaela Chistol Author 2: Mirela Danubianu Author 3: Adina-Luminita Barîla

According to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), Autism Spectrum Disorder (ASD) is a complex neurological and developmental condition characterized by impairments in social interaction and communication. Despite significant advancements in the research field, no pharmaceutical medication has been designed for ASD treatment. Therefore, ASD treatment relies… Read full abstract & cite →

Autism spectrum disorder technology-mediated interventions assistive technologies therapy cross-sectional study

Abstract doi.org/10.14569/IJACSA.2023.0141205 PDF

6

Drier Bed Adsorption Predictive Model with Enhancement of Long Short-Term Memory and Particle Swarm Optimization

Author 1: Marina Yusoff Author 2: Mohamad Taufik Mohd Sallehud-din Author 3: Nooritawati Md. Tahir Author 4: Wan Fairos Wan Yaacob Author 5: Nur Niswah Naslina Azid Author 6: Jasni Mohamad Zain Author 7: Putri Azmira R Azmi Author 8: Calvin Karunakumar

The drier bed adsorption processes remove moisture from gases and liquids by ensuring product quality, extending equipment lifespan, and enhancing safety in various applications. The longevity of adsorption beds is quantified by net loading capacity values that directly impact the effectiveness of the moisture removal process. Predictive modeling has emerged… Read full abstract & cite →

Adsorption Long Short-Term Memory net loading capacity Particle Swarm Optimization prediction

Abstract doi.org/10.14569/IJACSA.2023.0141206 PDF

7

A Deep Learning-based Approach for Vision-based Weeds Detection

Author 1: Yan Wang

Weed detection is an essential component of smart agriculture, and the use of remote sensing technologies has the potential to significantly improve weed management practices, reduce herbicide usage, and increase crop yields. This study proposed an approach to weed detection using computer vision and deep learning technologies. By utilizing remote… Read full abstract & cite →

Smart agriculture weed detection remote sensing deep learning computer vision

Abstract doi.org/10.14569/IJACSA.2023.0141207 PDF

8

Detection of Fruit using YOLOv8-based Single Stage Detectors

Author 1: Xiuyan GAO Author 2: Yanmin ZHANG

In the agricultural sector, the precise detection of fruits plays a pivotal role in optimizing harvesting procedures, minimizing waste, and ensuring the delivery of high-quality produce. Deep learning methods have consistently exhibited superior accuracy compared to alternative techniques, making them a focal point in fruit detection research. However, the ongoing… Read full abstract & cite →

Fruit detection agricultural sector deep learning YOLOv8 model precision agriculture

Abstract doi.org/10.14569/IJACSA.2023.0141208 PDF

9

Optimizing Mobile Ad Hoc Network Routing using Biomimicry Buzz and a Hybrid Forest Boost Regression - ANNs

Author 1: D Dhinakaran Author 2: S. M. Udhaya Sankar Author 3: S. Edwin Raja Author 4: J. Jeno Jasmine

A mobile ad hoc network (MANET) is a network of moving nodes that can interact with one another without the aid of a centrally located infrastructure. In MANETs, every node acts as a router and as a host, generating and consuming data. However, due to the mobility of nodes and… Read full abstract & cite →

MANET routing protocols optimized route selection regression machine learning Artificial Neural Networks

Abstract doi.org/10.14569/IJACSA.2023.0141209 PDF

10

Conceptualizing an Inductive Learning Situation in Online Learning Enabled by Software Engineering

Author 1: Ouariach Soufiane Author 2: Khaldi Maha Author 3: Khaldi Mohamed

Our work highlights the importance of adopting a systematic and methodical software engineering approach to the development of information technology projects for e-learning. We place particular emphasis on conceptualizing pedagogical scenarios and an inductive online learning situation. To ensure effective management of the information systems development process, we applied instructional… Read full abstract & cite →

Software engineering approach instructional design conceptualization scenario online learning situation inductive approach

Abstract doi.org/10.14569/IJACSA.2023.0141210 PDF

11

The Role of AI in Mitigating Climate Change: Predictive Modelling for Renewable Energy Deployment

Author 1: Nawaf Alharbe Author 2: Reyadh Alluhaibi

This study looks at how AI algorithms like Random Forest, Support Vector Machines (SVM), and Deep Boltzmann Machine (DBM) can be used for predictive modeling to make it easier to use renewable energy sources while reducing the negative effects of climate change. Predictive models based on Artificial Intelligence show possible… Read full abstract & cite →

Renewable energy climate change predictive models and Artificial Intelligence (AI)

Abstract doi.org/10.14569/IJACSA.2023.0141211 PDF

12

An Exploratory Analysis of using Chatbots in Academia

Author 1: Njood K Al-harbi Author 2: Amal A. Al-shargabi

With the advancement of technology in this era, chatbots have become more than just robots, as they used to conduct time-consuming and labor-intensive routine tasks. Now, it is more than just a robot for routine duties; it interacts and produces like a human. Despite the efficacy and productivity of chatbots… Read full abstract & cite →

AI chatbots ChatGPT GPT-4 bard ethics machine learning topic modeling

Abstract doi.org/10.14569/IJACSA.2023.0141212 PDF

13

A Comparative Study of Stemming Techniques on the Malay Text

Author 1: Rosmayati Mohemad Author 2: Nazratul Naziah Mohd Muhait Author 3: Noor Maizura Mohamad Noor Author 4: Nur Fadilla Akma Mamat

Text stemming, an essential preprocessing step in the development of Natural Language Processing (NLP) applications, involves the transformation of various word forms into their root words. Stemming plays a critical role in decreasing the volume of text, thereby enhancing the efficiency of various computational tasks such as information retrieval, text… Read full abstract & cite →

Algorithm ahmad algorithm malay language othman algorithm rule-based stemming stemmer

Abstract doi.org/10.14569/IJACSA.2023.0141213 PDF

14

Advanced Detection of COVID-19 Through X-ray Imaging using CovidFusionNet with Hybrid CNN Fusion and Multi-resolution Analysis

Author 1: Majdi Khalid

The rapid diagnosis of COVID-19 through imaging is crucial in the current pandemic scenario. This study introduces the CovidFusionNet, a novel model adapted for efficient COVID-19 image classification. By effectively combining fusing features from seven pre-trained convolutional neural networks (CNNs), our model presents better accuracy in detecting COVID-19 from X-ray… Read full abstract & cite →

COVID-19 diagnosis X-ray imaging wavelet transform Adaptive Histogram Equalization (AHE) oversampling image denoising image classification

Abstract doi.org/10.14569/IJACSA.2023.0141214 PDF

15

Implementation of a Convolutional Neural Network (CNN)-based Object Detection Approach for Smart Surveillance Applications

Author 1: Weiguo Ni

In the realm of smart surveillance systems, a fundamental technique for tracking and evaluating consumer behavior is object detection through video surveillance. While existing research underscores object detection through deep learning techniques, a notable gap exists in adapting these methods to effectively capture and recognize small, intricate objects. This study… Read full abstract & cite →

Smart surveillance lightweight object detection YOLOv7 small object recognition vision-based identification

Abstract doi.org/10.14569/IJACSA.2023.0141215 PDF

16

An Energy Efficient Routing Algorithm using Chaotic Grey Wolf with Mobile Sink-based Path Optimization for Wireless Sensor Networks

Author 1: Latifah Alharthi Author 2: Alaa E. S. Ahmed Author 3: Mostafa E. A. Ibrahim

The task of deploying an energy-conscious wireless sensor networks (WSNs) is challenging. One of the most effective methods for conserving WSNs energy is clustering. The deployed sensors are divided into groups by the clustering algorithm, and each group's cluster head (CH) is chosen to gather and combine data from other… Read full abstract & cite →

Wireless sensor network clustering algorithm grey wolf optimizer slime mould algorithm mobile sink

Abstract doi.org/10.14569/IJACSA.2023.0141216 PDF

17

Research on Qubit Mapping Technique Based on Batch SWAP Optimization

Author 1: Hui Li Author 2: Kai Lu Author 3: Ziao Han Author 4: Huiping Qin Author 5: Mingmei Ju Author 6: Shujuan Liu

The conventional approach for initial qubit mapping in the Noisy Intermediate-Scale Quantum (NISQ) era typically uses a static heuristic strategy, overlooking insufficient qubit neighborhood in subsequent operations, resulting in excess additional SWAP gates. To address this, we introduce a multifactor interaction cost function considering qubit distance, interaction time, and gate… Read full abstract & cite →

Quantum computing quantum circuit compilation initial qubit mapping Batch SWAP Optimization Strategy (BSOS) best SWAP choice Batch Update Technology (BUT)

Abstract doi.org/10.14569/IJACSA.2023.0141217 PDF

18

Identifying Factors in Congenital Heart Disease Transition using Fuzzy DEMATEL

Author 1: Raghavendra M Devadas Author 2: Vani Hiremani Author 3: Ranjeet Vasant Bidwe Author 4: Bhushan Zope Author 5: Veena Jadhav Author 6: Rohini Jadhav

The transition from pediatric to adult cardiology care is a pivotal moment in the healthcare journey of individuals with congenital heart conditions or childhood-onset heart diseases. This multifaceted process requires meticulous consideration of clinical, psychosocial, and logistical factors. This research aims to explore the critical criteria for transitioning pediatric patients… Read full abstract & cite →

DEMATEL Fuzzy DEMATEL factors pediatric patients heart disease

Abstract doi.org/10.14569/IJACSA.2023.0141218 PDF

19

Reliable and Efficient Model for Water Quality Prediction and Forecasting

Author 1: Azween Abdullah Author 2: Himakshi Chaturvedi Author 3: Siddhesh Fuladi Author 4: Nandhika Jhansi Ravuri Author 5: Deepa Natesan Author 6: M. K Nallakaruppan

Water quality is a crucial aspect of environmental and public health. Hence, its assessment is of paramount importance. This research paper aims to leverage machine learning models to classify water quality based on a comprehensive dataset. The dataset contains various water quality indicators, and the primary objective is to predict… Read full abstract & cite →

Random forest logistic regression feature importance decision trees support vector machines

Abstract doi.org/10.14569/IJACSA.2023.0141219 PDF

20

Data Mining Application Forecast of Business Trends of Electronic Products

Author 1: Kheo Chau Mui Author 2: Nhon Nguyen Thien

Sales forecasting is a pressing concern for companies amid rising consumer demand and intensifying competition, compounded by declining sales due to growing socio-economic challenges. Currently, many companies are having difficulty selling products due to a lack of management systems. To assist that, data mining techniques are introduced but it is… Read full abstract & cite →

Data mining sales forecasting clusters regression tree RMSE MSE k-prototypes

Abstract doi.org/10.14569/IJACSA.2023.0141220 PDF

21

Identification of Microaneurysms and Exudates for Early Detection of Diabetic Retinopathy

Author 1: G Indira Devi Author 2: D. Madhavi

Diabetic retinopathy (DR) is a condition that may be a complication of diabetes, and it can damage both the retina and other small blood vessels throughout the body. Microaneurysms (MA’s) and Hard exudates (HE’s) are two symptoms that occur in the early stage of DR. Accurate and reliable detection of… Read full abstract & cite →

Diabetic retinopathy microaneurysms hard exudates SVM LRC

Abstract doi.org/10.14569/IJACSA.2023.0141221 PDF

22

Gamers Intention Towards Purchasing Game Items in Virtual Community: Extending the Theory of Planned Behavior

Author 1: Abbi Nizar Muhammad Author 2: Achmad Nizar Hidayanto

Virtual communities serve as bustling marketplaces where gamers engage in transactions for in-game items, driving the digital economy's expansion. This research aims to illuminate the determinants of steering users' decisions within these online environments. Focusing on the constructs of Attitude, Subjective Norms, and Perceived Behavioral Control derived from the Theory… Read full abstract & cite →

Theory of planned behavior in-game items purchasing intention virtual community

Abstract doi.org/10.14569/IJACSA.2023.0141222 PDF

23

Deep Learning-based License Plate Recognition in IoT Smart Parking Systems using YOLOv6 Algorithm

Author 1: Ming Li Author 2: Li Zhang

License plate recognition (LPR) is pivotal for the seamless operation of Internet of things (IoT) and smart parking systems, ensuring the swift and effective identification and management of vehicles. Recent research has concentrated on refining LPR methods through deep learning approaches, proposing diverse strategies to enhance accuracy and reduce computation… Read full abstract & cite →

Internet of things deep learning smart parking system license plate recognition YOLOv6

Abstract doi.org/10.14569/IJACSA.2023.0141223 PDF

24

Influence of Membership Function and Degree on Sorghum Growth Prediction Models in Machine Learning

Author 1: Abdul Rahman Author 2: Ermatita Author 3: Dedik Budianta Author 4: Abdiansah

Rapid advances in science and technology have significantly changed plant growth modeling. The main contribution to this transformation lies in using Machine Learning (ML) techniques. This study focuses on sorghum, an important agricultural crop with significant economic implications. Crop yield studies include temperature, humidity, climate, rainfall, and soil nutrition. This… Read full abstract & cite →

Prediction MANFIS membership function organic fertilizer sorghum

Abstract doi.org/10.14569/IJACSA.2023.0141224 PDF

25

A Hybrid Double Encryption Approach for Enhanced Cloud Data Security in Post-Quantum Cryptography

Author 1: Manjushree C V Author 2: Nandakumar A N

Quantum computers and research on quantum computers are increasing due to the efficiency and speed required for critical applications. This scenario also kindles the vitality of data protection needed against threats from quantum computers. Research in post-quantum threats is very minimal so far, but it is much needed to protect… Read full abstract & cite →

Cloud data security double encryption Post-Quantum Cryptography (PQC) NTRU Encrypt AES Encryption

Abstract doi.org/10.14569/IJACSA.2023.0141225 PDF

26

Comprehensive Analysis of Topic Models for Short and Long Text Data

Author 1: Astha Goyal Author 2: Indu Kashyap

The digital age has brought significant information to the Internet through long text articles, webpages, and short text messages on social media platforms. As the information sources continue to grow, Machine Learning and Natural Language Processing techniques, including topic modeling, are employed to analyze and demystify this data. The performance… Read full abstract & cite →

Topic modeling Nonnegative Matrix Factorization (NMF) Latent Dirichlet Allocation (LDA) evaluation metrics short text mining long text mining

Abstract doi.org/10.14569/IJACSA.2023.0141226 PDF

27

Assessing User Requirements for e-Resources Interface Design in University Libraries

Author 1: Yuli Rohmiyati Author 2: Tengku Siti Meriam Tengku Wook Author 3: Noraidah Sahari Author 4: Siti Aishah Hanawi

e-Resources in the university library as learning resources are one of the primary services that promote learning and research to improve university productivity. At present, users find it difficult to access e-resources and require assistance in finding them. When using the system, users felt frustrated, confused, and lost. The e-resources… Read full abstract & cite →

User requirement interface design e-resources social presence university library element

Abstract doi.org/10.14569/IJACSA.2023.0141227 PDF

28

Multidimensional Private Information Portrait in Social Network Users

Author 1: Fangfang Shan Author 2: Mengyi Wang Author 3: Huifang Sun

In order to tackle the challenges of users' weak privacy awareness and frequent disclosure of private information in social network, this paper proposes a multidimensional privacy information portrait model of users in Chinese social networks. Because the TF-IDF (Term Frequency-Inverse Document Frequency, TF-IDF) algorithm does not consider the distribution of… Read full abstract & cite →

Social network personal privacy information privacy information portrait sensitivity privacy protection BERT

Abstract doi.org/10.14569/IJACSA.2023.0141228 PDF

29

Smart Fruit Identification and Counting using Machine Vision Approach

Author 1: Madhura R. Shankarpure Author 2: Dipti D. Patil

Estimating fruit yield holds significant importance for farmers as it enables them to make precise resource management decisions for fruit harvesting. The adoption of automated image processing technology not only reduces the human labor required but also enhances the accuracy of ripe fruit estimates. This research delves into the performance… Read full abstract & cite →

Image processing fruit multiphase approach counting

Abstract doi.org/10.14569/IJACSA.2023.0141229 PDF

30

Towards a Framework for Elevating the Usage of eLearning Technologies in Higher Education Institutions

Author 1: Naif Alzahrani Author 2: Hassan Alghamdi

Adopting eLearning technologies is no longer an option in Higher Education Institutions (HEIs) to support teaching and learning activities. However, despite steps taken by most of these institutions towards effective utilization of technologies, the current situation on the ground shows two significant challenges. First, the misalignment between institutions’ strategies and… Read full abstract & cite →

eLearning higher education business and IT alignment enterprise architecture

Abstract doi.org/10.14569/IJACSA.2023.0141230 PDF

31

A Novel Paradigm for IoT Security: ResNet-GRU Model Revolutionizes Botnet Attack Detection

Author 1: Jyotsna A Author 2: Mary Anita E. A

The rapid proliferation of the Internet of Things (IoT) has engendered substantial security apprehensions, chiefly due to the emergence of botnet attacks. This research study delves into the realm of Intrusion Detection Systems (IDS) by leveraging the IoT23 dataset, with a specific emphasis on the intricate domain of IoT at… Read full abstract & cite →

Internet of things federated learning Gated Recurrent Neural Networks Long Short Term Memory (LSTM)

Abstract doi.org/10.14569/IJACSA.2023.0141231 PDF

32

Hybrid Approach with VADER and Multinomial Logistic Regression for Multiclass Sentiment Analysis in Online Customer Review

Author 1: Murahartawaty Arief Author 2: Noor Azah Samsudin

Sentiment analysis is crucial for businesses to understand customer reviews and assess sentiment polarity. A hybrid technique combining VADER and Multinomial Logistic Regression was used to analyze customer sentiment in online customer review data. VADER is a lexicon-based approach that labels reviews with sentiment using a predefined lexicon, whereas Multinomial… Read full abstract & cite →

Hybrid approach multiclass sentiment analysis VADER multinomial logistic regression online customer review

Abstract doi.org/10.14569/IJACSA.2023.0141232 PDF

33

Artificial Intelligence-based Optimization Models for the Technical Workforce Allocation and Routing Problem Considering Productivity

Author 1: Mariam Alzeraif Author 2: Ali Cheaitou

Ensuring the reliability and availability of electric power networks is essential due to the increasing demands. An effective preventive maintenance strategy requires efficient resources allocation to perform the maintenance tasks, particularly the technical workforce. This paper introduces an innovative artificial intelligence-based approach to predict workforce productivity, aiming to optimize both… Read full abstract & cite →

Productivity workforce maintenance optimization allocation routing

Abstract doi.org/10.14569/IJACSA.2023.0141233 PDF

34

Development of Crack Detection and Crack Length Calculation Method using Image Processing

Author 1: Jewon Oh Author 2: Yutaka Matsumoto Author 3: Kohei Arai

To evaluate the integrity of a building, many experts and engineers have evaluated the damage classification of a building based on superficial visual information through field surveys. On-site surveys are hazardous and require several years of experience and expertise. In this study, a system for detecting the presence or absence… Read full abstract & cite →

Image processing crack detection length calculation color detection canny threshold OpenCV

Abstract doi.org/10.14569/IJACSA.2023.0141234 PDF

35

Urban Image Segmentation in Media Integration Era Based on Improved Sparse Matrix Generation of Digital Image Processing

Author 1: Dan Zheng Author 2: Yan Xie

Media integration integrates the resources of various media platforms, including audience, technical and human resources. In the era of media integration, media in various channels, at different levels and in different fields provide various choices for image communication and brand building of cities. The technology of image processing by computer… Read full abstract & cite →

Media integration digital image processing city image image segmentation improved sparse matrix generation

Abstract doi.org/10.14569/IJACSA.2023.0141235 PDF

36

Towards a Stacking Ensemble Model for Predicting Diabetes Mellitus using Combination of Machine Learning Techniques

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

Diabetes Mellitus (DM) is a chronic disease affecting the world's population, it causes long-term issues such as kidney failure, blindness, and heart disease, hurting one's quality of life. Diagnosing diabetes mellitus in an early stage is a challenge and a decisive decision for medical experts, as delay in diagnosis leads… Read full abstract & cite →

DM Diabetes Mellitus Stacking Ensemble learning Machine Learning Random Forest (RF) Logistic Regression (LR) Extreme Gradient Boosting model (XGBoost)

Abstract doi.org/10.14569/IJACSA.2023.0141236 PDF

37

Encryption Traffic Classification Method Based on ConvNeXt and Bilinear Attention Mechanism

Author 1: Xiaohua Feng Author 2: Yuan Liu

The rapid growth in internet traffic resulted to the emergence of network traffic categorization as a crucial area of research in network performance and management. This technological advancement has demonstrated its efficacy in aiding network administrators to identify anomalies within network behavior. However, the widespread adoption of encryption technology and… Read full abstract & cite →

Encryption traffic recognition end-to-end convolutional neural network bilinear attention module

Abstract doi.org/10.14569/IJACSA.2023.0141237 PDF

38

Energy-Aware Clustering in the Internet of Things using Tabu Search and Ant Colony Optimization Algorithms

Author 1: Mei Li Author 2: Jing Ai

The Internet of Things (IoT) significantly impacts communication systems' efficiency and the requirements for applications in our daily lives. Among the major challenges involved in data transmission over IoT networks is the development of an energy-efficient clustering mechanism. Recent methods are challenged by long transmission delays, imbalanced load distribution, and… Read full abstract & cite →

Internet of things clustering data transmission energy efficiency ant colony optimization algorithm

Abstract doi.org/10.14569/IJACSA.2023.0141238 PDF

39

Machine Learning-based Secure 5G Network Slicing: A Systematic Literature Review

Author 1: Meshari Huwaytim Alanazi

As the fifth-generation (5G) wireless networks continue to advance, the concept of network slicing has gained significant attention for enabling the provisioning of diverse services tailored to specific application requirements. However, the security concerns associated with network slicing pose significant challenges that demand comprehensive exploration and analysis. In this paper… Read full abstract & cite →

5G accuracy deep learning efficiency security machine learning network slicing scalability

Abstract doi.org/10.14569/IJACSA.2023.0141239 PDF

40

Comparison of the Application of Weighted Cosine Similarity and Minkowski Distance Similarity Methods in Stroke Diagnostic Systems

Author 1: Joko Purwadi Author 2: Rosa Delima Author 3: Argo Wibowo Author 4: Angelina Rumuy

Stroke is a critical medical condition requiring prompt intervention due to its multifaceted symptoms and causes influenced by various factors, including psychological aspects and the patient's lifestyle or daily habits that impact risk factors. The recovery process involves consistent medical care and lifestyle adjustments tailored to the individual case. Expert… Read full abstract & cite →

Expert system stroke case-based reasoning Minkowski Distance jaccard coefficient weighted cosine threshold accuracy diagnosis

Abstract doi.org/10.14569/IJACSA.2023.0141240 PDF

41

Optimal Cluster Head Selection in Wireless Sensor Network via Combined Osprey-Chimp Optimization Algorithm: CIOO

Author 1: Vikhyath K B Author 2: Achyutha Prasad N

The development of Wireless Sensor Network (WSN) has gained significant attention for smart systems due to their potential use in a wide range of areas. WSN consists of tiny, independently arranged sensor nodes that run on batteries. The resources and energy usage for sensor nodes are the major factors. Particularly… Read full abstract & cite →

Wireless sensor network clustering cluster head cluster head selection chimp optimization osprey optimization

Abstract doi.org/10.14569/IJACSA.2023.0141241 PDF

42

Deep Learning-based Pothole Detection for Intelligent Transportation: A YOLOv5 Approach

Author 1: Qian Li Author 2: Yanjuan Shi Author 3: Qing Liu Author 4: Gang Liu

Pothole detection plays a crucial role in intelligent transportation systems, ensuring road safety and efficient infrastructure management. Extensive research in the literature has explored various methods for pothole detection. Among these approaches, deep learning-based methods have emerged as highly accurate alternatives, surpassing other techniques. The widespread adoption of deep learning… Read full abstract & cite →

Pothole detection deep learning intelligent transportation systems YOLOv5

Abstract doi.org/10.14569/IJACSA.2023.0141242 PDF

43

Security and Privacy of Cloud Data Auditing Protocols: A Review, State-of-the-art, Open Issues, and Future Research Directions

Author 1: Muhammad Farooq Author 2: Mohd Rushdi Idrus Author 3: Adi Affandi Ahmad Author 4: Ahmad Hanis Mohd Shabli Author 5: Osman Ghazali

Cloud service providers offer a trustworthy and resistant-based storage environment for on-demand cloud services to outsource clients’ data. Several researchers and business entities currently adopt cloud services to store their data in remote cloud storage servers for cost-saving purposes. Cloud storage offers numerous advantages to users like scalability, low capital… Read full abstract & cite →

Cloud computing proof of possession data integrity auditing proof of retrievability public auditing proof of ownership

Abstract doi.org/10.14569/IJACSA.2023.0141243 PDF

44

Promises, Challenges and Opportunities of Integrating SDN and Blockchain with IoT Applications: A Survey

Author 1: Loubna Elhaloui Author 2: Mohamed Tabaa Author 3: Sanaa Elfilali Author 4: El habib Benlahmar

Security is a major issue in the IT world, and its aim is to maintain user confidence and the coherence of the entire information system. Various international and European research projects, as well as IT manufacturers, have proposed new solutions and mechanisms to solve the problem of security in the… Read full abstract & cite →

Internet of things SDN blockchain

Abstract doi.org/10.14569/IJACSA.2023.0141244 PDF

45

Application of Machine Learning in Learning Problems and Disorders: A Systematic Review

Author 1: Mario Aquino Cruz Author 2: Oscar Alcides Choquehuallpa Hurtado Author 3: Esther Calatayud Madariaga

Learning Disorders, which affect approximately 10% of the school population, represent a significant challenge in the educational field. The lack of proper diagnosis and treatment can have profound consequences, triggering psychological problems in those affected by disorders that impact reading, writing, numeracy and attention, among others. Notable among them are… Read full abstract & cite →

Machine learning learning disorder deep learning ADHD dyslexia learning impairment

Abstract doi.org/10.14569/IJACSA.2023.0141245 PDF

46

Durian Disease Classification using Vision Transformer for Cutting-Edge Disease Control

Author 1: Marizuana Mat Daud Author 2: Abdelrahman Abualqumssan Author 3: Fadilla ‘Atyka Nor Rashid Author 4: Mohamad Hanif Md Saad Author 5: Wan Mimi Diyana Wan Zaki Author 6: Nurhizam Safie Mohd Satar

The durian fruit holds a prominent position as a beloved fruit not only in ASEAN countries but also in European nations. Its significant potential for contributing to economic growth in the agricultural sector is undeniable. However, the prevalence of durian leaf diseases in various ASEAN countries, including Malaysia, Indonesia, the… Read full abstract & cite →

Vision transformer durian disease deep learning disease control

Abstract doi.org/10.14569/IJACSA.2023.0141246 PDF

47

The Construction of Campus Network Public Opinion Analysis Model Based on T-GAN Model

Author 1: Jianan Zhang

The advancement of information technology has made the internet and social media an indispensable part of modern life, but with it comes a flood of false information and rumors. The aim of this study is to develop a technology that can automatically identify campus network public opinion information, in order… Read full abstract & cite →

Public opinion analysis T-GAN feature extraction multi-scale convolutional neural network campus network

Abstract doi.org/10.14569/IJACSA.2023.0141247 PDF

48

Method for Hyperparameter Tuning of EfficientNetV2-based Image Classification by Deliberately Modifying Optuna Tuned Result

Author 1: Jin Shimazoe Author 2: Kohei Arai Author 3: Mari Oda

Method for hyperparameter tuning of EfficientNetV2-based image classification by deliberately modifying Optuna tuned result is proposed. An example of the proposed method for textile pattern quality evaluation (good or bad textile pattern fluctuation quality classification) is shown. When using the hyperparameters obtained by Optuna without changing them, the accuracy certainly… Read full abstract & cite →

Hyperparameter tuning EfficientNetV2 Optuna textile pattern optimal hyperparameter learning process pattern fluctuation

Abstract doi.org/10.14569/IJACSA.2023.0141248 PDF

49

A Novel Framework for Risk Prediction in the Health Insurance Sector using GIS and Machine Learning

Author 1: Prasanta Baruah Author 2: Pankaj Pratap Singh Author 3: Sanjiv kumar Ojah

Evaluation of risk is a key component to categorize the customers of the life insurance businesses. The underwriting technique is carried out by the industries to charge the policies appropriately. Due to the availability of data hugely, the automation of underwriting process can be done using data analytics technology. Due… Read full abstract & cite →

Risk prediction data analytics predictive analytics underwriting geographical information systems random forest artificial neural network decision tree

Abstract doi.org/10.14569/IJACSA.2023.0141249 PDF

50

Enhancing Underwater Object Recognition Through the Synergy of Transformer and Feature Enhancement Techniques

Author 1: Hoanh Nguyen Author 2: Tuan Anh Nguyen

Underwater object recognition presents a unique set of challenges due to the complex and dynamic characteristics of marine environments. This paper introduces a novel, multi-layered architecture that leverages the capabilities of Swin Transformer modules to process segmented image patches derived from aquatic scenes. A key component of our approach is… Read full abstract & cite →

Underwater object recognition swin transformer self-attention feature alignment

Abstract doi.org/10.14569/IJACSA.2023.0141250 PDF

51

A Computational Prediction Model of Blood-Brain Barrier Penetration Based on Machine Learning Approaches

Author 1: Deep Himmatbhai Ajabani

Within the field of medical sciences, addressing brain illnesses such as Alzheimer's disease, Parkinson's disease, and brain tumors poses significant difficulties. Despite thorough investigation, the search for truly successful neurotherapies continues to be challenging to achieve. The blood-brain barrier (BBB), which is currently a major area of research, restricts the… Read full abstract & cite →

Central Nervous System (CNS) Blood-Brain Barrier (BBB) Machine Learning (ML) Simplified Molecular Input Line Entry System (SMILES) Support Vector Machine (SVM) K-Nearest Neighbor (KNN) Logistic Regression (LR) Multi-Layer Perceptron (MLP) Light Gradient Boosting Machine (LightGBM) Random Forest (RF)

Abstract doi.org/10.14569/IJACSA.2023.0141251 PDF

52

Enhanced Atrial Fibrillation Detection-based Wavelet Scattering Transform with Time Window Selection and Neural Network Integration

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

Atrial Fibrillation (AF), a prevalent anomaly in cardiac rhythm, significantly impacts a substantial portion of the population, with projections indicating an escalation in its prevalence in the near future. This disorder manifests as irregular and accelerated heartbeats originating within the heart's upper chambers known as the atria. Neglecting to address… Read full abstract & cite →

Electrocardiogram (ECG) Atrial Fibrillation (AF) Wavelet Scattering Network (WSN) Artificial Neural Network (ANN)

Abstract doi.org/10.14569/IJACSA.2023.0141252 PDF

53

Advancing Road Safety: Precision Driver Detection System with Integrated Overspeed, Alcohol Detection, and Tracking Capabilities

Author 1: Jamil Abedalrahim Jamil Alsayaydeh Author 2: Mohd Faizal bin Yusof Author 3: Khivisha S. Mohan Author 4: A K M Zakir Hossain Author 5: Serhii Leoshchenko

In response to ongoing concerns about road accidents linked to overspeeding and drunk driving, this study introduces a groundbreaking solution: The Integrated Driver Safety system. It is a comprehensive vehicle safety system designed for real-time prevention. Crafted with cutting-edge components including ESP32, MQ3 sensor, relay, and GPS, this system operates… Read full abstract & cite →

Integrated driver safety overspeed detection system alcohol monitoring technology comprehensive vehicle security real-time accident prevention ESP32 GPS safety responsible driving solutions

Abstract doi.org/10.14569/IJACSA.2023.0141253 PDF

54

Towards a Reference Architecture for Semantic Interoperability in Multi-Cloud Platforms

Author 1: Norazian M Hamdan Author 2: Novia Admodisastro

This paper focuses on semantic interoperability as one of the most significant issues in multi-cloud platforms. Organizations and individuals that adopt the multi-cloud strategy often use various cloud services and platforms. On top of that, cloud service providers may offer a range of services with unique data formats, structures, and… Read full abstract & cite →

Cloud computing multi-cloud reference architecture semantic interoperability semantic technologies

Abstract doi.org/10.14569/IJACSA.2023.0141254 PDF

55

Pancreatic Cancer Detection Through Hyperparameter Tuning and Ensemble Methods

Author 1: Koteswaramma Dodda Author 2: G. Muneeswari

Computing techniques have brought about a significant transformation in the field of medical research. Machine learning techniques have facilitated the analysis of vast amounts of data, modeling of complex scenarios, and the ability to make well-informed decisions. This presents an opportunity to develop reliable and effective medical system implementations, which… Read full abstract & cite →

Pancreatic cancer Machine learning (ML) urinary biomarkers grid search hyper parameter tuning Random Forest (RF)

Abstract doi.org/10.14569/IJACSA.2023.0141255 PDF

56

An Efficient Honeycomb Lung Segmentation Network Combining Multi-Paradigms Representation and Cascade Attention

Author 1: Bingqian Yang Author 2: Xiufang Feng Author 3: Yunyun Dong

Honeycomb lung is a pulmonary manifestation that occurs in the terminal stage of various lung diseases, which greatly threatens patients. Due to the different locations and irregular shapes of lesions, the accurate segmentation of the honeycomb region is an essential and challenging problem. However, most deep learning methods struggle to… Read full abstract & cite →

Honeycomb lung attention convolutional neural network transformer image segmentation

Abstract doi.org/10.14569/IJACSA.2023.0141256 PDF

57

Efficient Deep Reinforcement Learning for Smart Buildings: Integrating Energy Storage Systems Through Advanced Energy Management Strategies

Author 1: Artika Farhana Author 2: Nimmati Satheesh Author 3: Ramya M Author 4: Janjhyam Venkata Naga Ramesh Author 5: Yousef A. Baker El-Ebiary

This study presents a novel and workable approach to solving the critical issue of improving energy management in smart buildings. Using a large dataset from a seven-story office building in Bangkok, Thailand, our work introduces a novel approach that combines Deep Q-network (DQN) algorithms with energy storage models and cost… Read full abstract & cite →

Deep q-network cost optimization smart building energy management peak demand

Abstract doi.org/10.14569/IJACSA.2023.0141257 PDF

58

Use of ANN, LSTM and CNN Classifiers for the New MSCC and BSCC Methods in the Detection of Parkinson's Disease by Voice Analysis

Author 1: Miyara Mounia Author 2: Boualoulou Nouhaila Author 3: Nsiri Benayad Author 4: Belhoussine Drissi Taoufiq

Parkinson's disease (PD) is a neurodegenerative condition that impacts a significant global population. The timely and precise identification of PD plays a pivotal role in facilitating early intervention and the efficient management of the condition. Recently, speech analysis has emerged as a promising non-invasive technique for the detection of PD… Read full abstract & cite →

Parkinson’s Disease (PD) Bark Spectrogram Cepstral Coefficients (BSCC) Mel Spectrogram Cepstral Coefficients (MSCC) Long-Term Memory Neural Networks (LSTM) Convolutional Neural Networks (CNN) Artificial Neural Networks (ANN)

Abstract doi.org/10.14569/IJACSA.2023.0141258 PDF

59

Artificial Intelligence for Confidential Information Sharing Based on Knowledge-Based System

Author 1: Bouchra Boulahiat Author 2: Salima Trichni Author 3: Mohammed Bougrine Author 4: Fouzia Omary

Ensuring the security of sensitive data and protecting user privacy remains one of the most significant challenges in our contemporary landscape. Organizations Companies cannot adopt a new technology without reassurance regarding data confidentiality. To address these challenges, we present an innovative system that draws upon extensive knowledge and expertise in… Read full abstract & cite →

IT security cryptography confidentiality Knowledge-Based system artificial intelligence

Abstract doi.org/10.14569/IJACSA.2023.0141259 PDF

60

Enhancing Software User Interface Testing Through Few Shot Deep Learning: A Novel Approach for Automated Accuracy and Usability Evaluation

Author 1: Aris Puji Widodo Author 2: Adi Wibowo Author 3: Kabul Kurniawan

Traditional user interface (UI) testing methods in software development are time-consuming and prone to human error, requiring more efficient and accurate approaches. Moreover, deep learning requires extensive data training to develop accurate automated UI software testing. This paper proposes an efficient and accurate method for automating UI software testing using… Read full abstract & cite →

Deep learning efficientnet few-shot software testing UI screen classification

Abstract doi.org/10.14569/IJACSA.2023.0141260 PDF

61

Optimizing Crop Yield Prediction in Precision Agriculture with Hyperspectral Imaging-Unmixing and Deep Learning

Author 1: Deeba K Author 2: O. Rama Devi Author 3: Mohammed Saleh Al Ansari Author 4: Bhargavi Peddi Reddy Author 5: Manohara H T Author 6: Yousef A. Baker El-Ebiary Author 7: Manikandan Rengarajan

The optimization of crop yield projections has arisen as a major problem in modern agriculture, due to the increasing demand for food supply and the necessity for effective resource management. Precision and scalability are hampered by the limits associated with conventional agricultural production prediction techniques, which mostly rely on observations… Read full abstract & cite →

Crop yield prediction hyper spectral image spectral unmixing resource management precision agriculture

Abstract doi.org/10.14569/IJACSA.2023.0141261 PDF

62

Optimizing Network Security and Performance Through the Integration of Hybrid GAN-RNN Models in SDN-based Access Control and Traffic Engineering

Author 1: Ganesh Khekare Author 2: K. Pavan Kumar Author 3: Kundeti Naga Prasanthi Author 4: Sanjiv Rao Godla Author 5: Venubabu Rachapudi Author 6: Mohammed Saleh Al Ansari Author 7: Yousef A. Baker El-Ebiary

By offering flexible and adaptable infrastructures Software-Defined Networking (SDN) has emerged as a disruptive technology that has completely changed network provisioning and administration. By seamlessly integrating Hybrid Generative Adversarial Network-Recurrent Neural Network (GAN-RNN) modeling into the foundation of SDN-based traffic engineering and accessibility control methods, this work presents a novel… Read full abstract & cite →

Software-defined networking generative adversarial networks recurrent neural networks traffic engineering

Abstract doi.org/10.14569/IJACSA.2023.0141262 PDF

63

The Contribution of Health Management Information Systems to Enhancing Healthcare Operations

Author 1: Majzoob K. Omer

Various strategies for enhancing quality have been implemented by developed and developing countries in light of the worldwide emphasis on bolstering healthcare systems. Many nations are currently directing their attention towards bolstering their existing information systems or establishing new ones, recognizing the critical role of information in the functioning of… Read full abstract & cite →

Health management information system cronbach alpha moderator information timelines

Abstract doi.org/10.14569/IJACSA.2023.0141263 PDF

64

A Sophisticated Deep Learning Framework of Advanced Techniques to Detect Malicious Users in Online Social Networks

Author 1: Sailaja Terumalasetti Author 2: Reeja S R

Malicious user detection is a cybersecurity exploration domain because of the emergent jeopardies of data breaches and cyberattacks. Malicious users have the potential to detriment the system by engaging in unauthorized actions or thieving sensitive data. This paper proposes the dual-powered CLM technique (Convolution neural networks and LSTM) and optimization… Read full abstract & cite →

Online social networks malicious user behavior convolution neural networks long short-term memory genetic algorithm

Abstract doi.org/10.14569/IJACSA.2023.0141264 PDF

65

Exploring a Novel Machine Learning Approach for Evaluating Parkinson's Disease, Duration, and Vitamin D Level

Author 1: Md. Asraf Ali Author 2: Md. Kishor Morol Author 3: Muhammad F Mridha Author 4: Nafiz Fahad Author 5: Md Sadi Al Huda Author 6: Nasim Ahmed

Parkinson's disease is an increasingly prevalent, degenerative neurological condition predominantly afflicting individuals aged 50 and older. As global life expectancy continues to rise, the imperative for a deeper comprehension of factors influencing the course and intensity of PD becomes more pronounced. This investigation delves into these facets, scrutinizing various parameters… Read full abstract & cite →

Parkinson's disease machine learning vitamin D severity disease duration

Abstract doi.org/10.14569/IJACSA.2023.0141265 PDF

66

Applying Big Data Analysis and Machine Learning Approaches for Optimal Production Management

Author 1: Sarsenkul Tileubay Author 2: Bayanali Doszhanov Author 3: Bulgyn Mailykhanova Author 4: Nurlan Kulmurzayev Author 5: Aisanim Sarsenbayeva Author 6: Zhadyra Akanova Author 7: Sveta Toxanova

In this research paper, we delve into the transformative potential of integrating Big Data analytics with machine learning (ML) techniques, orchestrating a paradigm shift in production management methodologies. Traditional production systems, often marred by inefficiencies stemming from data opacity, have encountered bottlenecks that throttle scalability and adaptability, particularly in complex… Read full abstract & cite →

Optimal production smart manufacturing machine learning big data management

Abstract doi.org/10.14569/IJACSA.2023.0141266 PDF

67

Development of an Intelligent Service Delivery System to Increase Efficiency of Software Defined Networks

Author 1: Serik Joldasbayev Author 2: Saya Sapakova Author 3: Almash Zhaksylyk Author 4: Bakhytzhan Kulambayev Author 5: Reanta Armankyzy Author 6: Aruzhan Bolysbek

The burgeoning complexity in network management has garnered considerable attention, specifically focusing on Software-Defined Networking (SDN), a transformative technology that addresses limitations inherent in traditional network infrastructures. Despite its advantages, SDN is often susceptible to bottlenecks and excessive load issues, underscoring the necessity for more robust load balancing solutions. Previous… Read full abstract & cite →

Load balancing machine learning server classification software

Abstract doi.org/10.14569/IJACSA.2023.0141267 PDF

68

A Comprehensive Review of Healthcare Prediction using Data Science with Deep Learning

Author 1: Asha Latha Thandu Author 2: Pradeepini Gera

Data science in healthcare prediction technology can identify diseases and spot even the smallest changes in the patient's health factors and prevent the diseases. Several factors make data science crucial to healthcare today the most important among them is the competitive demand for valuable information in the healthcare systems. The… Read full abstract & cite →

Data science deep belief network healthcare sparse auto encoder deep learning

Abstract doi.org/10.14569/IJACSA.2023.0141268 PDF

69

Enhancing Autism Severity Classification: Integrating LSTM into CNNs for Multisite Meltdown Grading

Author 1: Sumbul Alam Author 2: S Pravinth Raja Author 3: Yonis Gulzar Author 4: Mohammad Shuaib Mir

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social interaction, verbal and non-verbal communication, and is often associated with cognitive and neurobehavioral challenges. Timely screening and diagnosis of ASD are crucial for early educational planning, treatment, family support, and timely medical intervention. Manual diagnostic methods are… Read full abstract & cite →

Autism spectrum disorder mutilating meltdown convolution neural network long short term memory multisite meltdown video classification image classification

Abstract doi.org/10.14569/IJACSA.2023.0141269 PDF

70

Analysis of Synthetic Data Utilization with Generative Adversarial Network in Flood Classification using K-Nearest Neighbor Algorithm

Author 1: Wahyu Afriza Author 2: Mardhani Riasetiawan Author 3: Dyah Aruming Tyas

Indonesia is a country with a tropical climate that has high rainfall rates and is supported by the uncertainty of weather and climate conditions. With the uncertainty of weather and climate as well as flood events, minimal predictive information on flooding, and the lack of availability of data on the… Read full abstract & cite →

Classification rainfall synthetic data KNN GAN

Abstract doi.org/10.14569/IJACSA.2023.0141270 PDF

71

A Piano Single Tone Recognition and Classification Method Based on CNN Model

Author 1: Miaoping Geng Author 2: Ruidi He Author 3: Ziyihe Zhou

In order to improve the recognition and classification effect of piano single tone, this paper combines the CNN (Convolutional Neural Networks) model to construct the piano single tone recognition and classification model, and equalizes the uniformly irradiated parabolic tone transmission hardware. In this paper, the analytic method is used to… Read full abstract & cite →

CNN model piano single tone recognition classification

Abstract doi.org/10.14569/IJACSA.2023.0141271 PDF

72

Intelligent Evaluation and Optimization of Postgraduate Education Comprehensive Ability Training under the Mode of “One Case, Three Systems”

Author 1: Yong Xiang Author 2: Zeyou Chen Author 3: Liyu Lu Author 4: Yao Wei

This study aims to explore the intelligent evaluation and optimization methods for the comprehensive ability training of graduate students under the mode of "one case, three systems" to improve the quality and effect of graduate training. Firstly, a weighted clustering algorithm for mixed attributes is designed. Secondly, an evaluation model… Read full abstract & cite →

Comprehensive ability training of graduate students one case three systems feature weighted clustering algorithm sampling method ensemble learning

Abstract doi.org/10.14569/IJACSA.2023.0141272 PDF

73

A Novel Fusion Deep Learning Approach for Retinal Disease Diagnosis Enhanced by Web Application Predictive Tool

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

Retinal disorders such as age-related macular degeneration and diabetic macular edema can lead to permanent blindness. Optical coherence tomography (OCT) enables professionals to observe cross-sections of the retina, which aids in diagnosis. Manually analyzing images is time-consuming, difficult, and prone to mistakes. In the dynamic and constantly evolving domain of… Read full abstract & cite →

Retinal disease RetiNet hybrid model learning Web application gaussian blur histogram equalization

Abstract doi.org/10.14569/IJACSA.2023.0141273 PDF

74

Enhancing Production System Performance: Failure Detection and Availability Improvement with Deep Learning and Genetic Algorithm

Author 1: Artika Farhana Author 2: Shaista Sabeer Author 3: Ayasha Siddiqua Author 4: Afsana Anjum

A crucial component of industrial operations is the detection of production system failures, which aims to spot any problems before they get worse. By applying cutting-edge methods like deep learning and genetic algorithms, failure detection accuracy may be improved, allowing for preemptive actions to reduce downtime and maximize system availability… Read full abstract & cite →

Autoencoder availability enhancement convolutional neural network failure detection genetic algorithm

Abstract doi.org/10.14569/IJACSA.2023.0141274 PDF

75

Enhanced Multi-Object Detection via the Integration of PSO, Kalman Filtering, and CNN Compressive Sensing

Author 1: S. V. Suresh Babu Matla Author 2: S. Ravi Author 3: Muralikrishna Puttagunta

Many inventive techniques have been created in the field of machine vision to solve the challenging challenge of detecting and tracking one or more objects in the face of challenging conditions, such as obstacles, object motion, changes in light, shaking, and rotations. This research article provides a novel method that… Read full abstract & cite →

Multi-Object tracking object detection convolutional neural networks kalman filtering particle swarm optimization

Abstract doi.org/10.14569/IJACSA.2023.0141275 PDF

76

Comparative Analysis of Weighted Ensemble and Majority Voting Algorithms for Intrusion Detection in OpenStack Cloud Environments

Author 1: Pravin Patil Author 2: Geetanjali Kale Author 3: Nidhi Bivalkar Author 4: Agneya Kolhatkar

In the ever-evolving landscape of cybersecurity, the detection of malicious activities within cloud environments remains a critical challenge. This research aims to compare the effectiveness of two ensemble algorithms, the weighted ensemble algorithm and the majority voting algorithm, in the context of intrusion detection within an OpenStack cloud environment. To… Read full abstract & cite →

Intrusion detection ensemble algorithms cloud security openstack weighted ensemble majority voting

Abstract doi.org/10.14569/IJACSA.2023.0141276 PDF

77

Rural Homestay Spatial Planning and Design Based on Bert BiLSTM EIC Algorithm in the Background of Digital Ecology

Author 1: Zhibin Qiu Author 2: Junghoon Mok

There is a promising development prospect in the digital ecosystem. In this context, the spatial planning of rural homestays has also received widespread attention. The research aims to better explore the advantages and determine the development direction of rural homestays, while providing two-way demand support for consumers and managers. Therefore… Read full abstract & cite →

Rural homestay spatial planning deep learning emotional analysis bidirectional long short term memory network

Abstract doi.org/10.14569/IJACSA.2023.0141277 PDF

78

Robot Human-Machine Interaction Method Based on Natural Language Processing and Speech Recognition

Author 1: Shuli Wang Author 2: Fei Long

With the rapid development of artificial intelligence technology, robots have gradually entered people's lives and work. The robot human-machine interaction system for image recognition has been widely used. However, there are still many problems with robot human-machine interaction methods that utilize natural language processing and speech recognition. Therefore, this study… Read full abstract & cite →

Human-computer interaction speech recognition natural language processing lexical analysis syntactic analysis

Abstract doi.org/10.14569/IJACSA.2023.0141278 PDF

79

Investigating of Deep Learning-based Approaches for Anomaly Detection in IoT Surveillance Systems

Author 1: Jianchang HUANG Author 2: Yakun CAI Author 3: Tingting SUN

Anomaly detection plays a crucial role in ensuring the security and integrity of Internet of Things (IoT) surveillance systems. Nowadays, deep learning methods have gained significant popularity in anomaly detection because of their ability to learn and extract intricate features from complex data automatically. However, despite the advancements in deep… Read full abstract & cite →

Internet of Things surveillance systems anomaly detection deep learning video analysis

Abstract doi.org/10.14569/IJACSA.2023.0141279 PDF

80

A Graph-Cut Guided ROI Segmentation Algorithm with Lightweight Deep Learning Framework for Cervical Cancer Classification

Author 1: Shiny T L Author 2: Kumar Parasuraman

Cervical cancer classification has witnessed numerous advancements through deep learning methods; however, existing approaches often rely on multiple models for segmentation and classification, leading to heightened computational demands and prolonged training times. In this research, a lightweight deep learning framework for cervical cancer classification is presented. The framework comprises three… Read full abstract & cite →

Cervical cancer classification deep learning lightweight deep learning framework graph-cut guided ROI segmentation algorithm nuclei region isolation

Abstract doi.org/10.14569/IJACSA.2023.0141280 PDF

81

Advanced Techniques for Recognizing Emotions: A Unified Approach using Facial Patterns, Speech Attributes, and Multimedia Descriptors

Author 1: Kummari Ramyasree Author 2: Chennupati Sumanth Kumar

The inability to efficiently store distinguishing edges, local appearance-based textured descriptions generally have limited performance in detecting facial expression analysis. The existing technology has certain drawbacks, such as the potential for poor edge-related disturbance in face photos and the reliance on present sets of characteristics that might fail to adequately… Read full abstract & cite →

Local Difference Pattern (LDP) Mel-Frequency Cepstral Coefficients (MFCC) Long-Term Average Spectrum (LTAS) Self-Similarity Distance Matrix (SSDM) Support Vector Machine (SVM)

Abstract doi.org/10.14569/IJACSA.2023.0141281 PDF

82

Research on Efficient CNN Acceleration Through Mixed Precision Quantization: A Comprehensive Methodology

Author 1: Yizhi He Author 2: Wenlong Liu Author 3: Muhammad Tahir Author 4: Zhao Li Author 5: Shaoshuang Zhang Author 6: Hussain Bux Amur

To overcome challenges associated with deploying Convolutional Neural Networks (CNNs) on edge computing devices with limited memory and computing resources, we propose a mixed-precision CNN calculation method on a Field Programmable Gate Array (FPGA). This approach involves a collaborative design encompassing both software and hardware aspects. Initially, we devised a… Read full abstract & cite →

Convolutional Neural Networks (CNNs) edge computing technologies Field Programmable Gate Array (FPGA) accelerator mixed precision quantization loss variation

Abstract doi.org/10.14569/IJACSA.2023.0141282 PDF

83

Combining Unsupervised and Supervised Learning to Predict Poverty Households in Sakon Nakhon, Thailand

Author 1: Sutisa Songleknok Author 2: Suthasinee Kuptabut

Poverty is a problem that various government agencies are attempting to address accurately and precisely. This solution relies on data and analysis of features affecting poverty. Machine Learning is a technique to analyze and focus on poverty features encompassing five livelihood capitals: human, physical, economic, natural, and social capital to… Read full abstract & cite →

K-prototype decision tree feature selection Sakon Nakhon poverty households unsupervised learning supervised learning

Abstract doi.org/10.14569/IJACSA.2023.0141283 PDF

84

Network Oral English Teaching System Based on Speech Recognition Technology and Deep Neural Network

Author 1: Na He Author 2: Weihua Liu

With the development of computer technology, computer-aided instruction is being used more and more widely in the field of education. Based on speech recognition technology and deep neural network, this paper proposes an online oral English teaching system. Firstly, the speech recognition technology is introduced and its feature extraction is… Read full abstract & cite →

Deep neural network Markov model voice design technology Viterbi algorithm oral English teaching

Abstract doi.org/10.14569/IJACSA.2023.0141284 PDF

85

Recurrence Prediction and Risk Classification of COPD Patients Based on Machine Learning

Author 1: Xin Qi Author 2: Hong Chen

In response to the frequent recurrence and readmission of patients with chronic obstructive pulmonary disease, a machine learning based recurrence risk prediction and risk classification model for patients with chronic obstructive pulmonary disease is studied and constructed. Approach: This model first utilizes the optimized long short-term memory network to recognize… Read full abstract & cite →

Machine learning COPD BiLSTM XGBoost k-means recurrence risk classification

Abstract doi.org/10.14569/IJACSA.2023.0141285 PDF

86

Supply Chain Disturbance Management Scheduling Model Based on HPSO Algorithm

Author 1: Ling Wang

The continuous expansion of business has led to the development of enterprises from vertical integration to horizontal integration, and the interlocking of the supply chain system, but the influence of anti-production behavior factors and the frequent occurrence of disruption events lead to difficulties in supply chain scheduling, which affects the… Read full abstract & cite →

HPSO algorithm disturbance management supply chain system dynamics anti-production behavior

Abstract doi.org/10.14569/IJACSA.2023.0141286 PDF

87

Presentation of a New Method for Intrusion Detection by using Deep Learning in Network

Author 1: Hui MA

Intrusion detection in cyberspace is an important field for today's research on the scope of the security of computer networks. The purpose of designing and implementing the systems of intrusion detection is to accurately categorize the virtual users, the hackers and the network intruders based on their normal or abnormal… Read full abstract & cite →

Attack security on cyberspace classification intrusion detection deep learning

Abstract doi.org/10.14569/IJACSA.2023.0141287 PDF

88

The Application of Cognitive Decision-Making Algorithm in Cross-Border e-Commerce Digital Marketing

Author 1: Xuehui Wang

Extensive global research aims to improve digital marketing profits through pricing decision-making and optimization. A dual word-of-mouth diffusion pricing model is developed for cross-border e-commerce, addressing word-of-mouth accumulation and information diffusion effects. The traditional artificial bee colony algorithm is optimized with security domain search and information diffusion profiles, enhancing global… Read full abstract & cite →

Cross-border e-commerce decision-making pricing issues optimization algorithms ABO

Abstract doi.org/10.14569/IJACSA.2023.0141288 PDF

89

Planning and Expansion of the Transmission Network in the Presence of Wind Power Plants

Author 1: Hui Sun

The proliferation of renewable energy sources, particularly wind farms, is rapidly gaining momentum owing to their numerous benefits. Consequently, it is imperative to account for the impact of wind farms on transmission expansion planning (TEP), which is a crucial aspect of power system planning. This article presents a multi-objective optimization… Read full abstract & cite →

Wind farms Transmission Expansion Planning (TEP) multi-objective optimization model Shuffled Frog Leaping Algorithm (SFLA)

Abstract doi.org/10.14569/IJACSA.2023.0141289 PDF

90

LPDA: Cross-Project Software Defect Prediction Approach via Locality Preserving and Distribution Alignment

Author 1: Jin Xian Author 2: Jinglei Li Author 3: Quanyi Zou Author 4: Yunting Xian

Cross-Project Defect Prediction (CPDP) based on domain adaptation aims to achieve defect prediction tasks in an unlabeled target software project by borrowing the defect knowledge extracted from well-annotated source software projects. Most existing CPDP approaches enhance transferability between projects but struggle with misalignments due to limited exploration of class-specific features… Read full abstract & cite →

Cross Project Defect Prediction discriminative distribution alignment local preserving domain adaption

Abstract doi.org/10.14569/IJACSA.2023.0141290 PDF

91

Exploiting Deepfakes by Analyzing Temporal Feature Inconsistency

Author 1: Junlin Gu Author 2: Yihan Xu Author 3: Juan Sun Author 4: Weiwei Liu

In recent years, the rapid advancement of image generation technology has facilitated the creation of counterfeit images and videos, posing significant challenges for content authenticity verification. Malefactors can easily extract videos from social networks and generate their own deceptive renditions using state-of-the-art techniques. The latest Deepfake face forgery videos have… Read full abstract & cite →

Face forgery detection Convolutional Neural Net-work Long Short-Term Memory Network time consistency

Abstract doi.org/10.14569/IJACSA.2023.0141291 PDF

92

The PSR-Transformer Nexus: A Deep Dive into Stock Time Series Forecasting

Author 1: Nguyen Ngoc Phien Author 2: Jan Platos

Accurate stock market forecasting has remained an elusive endeavor due to the inherent complexity of financial systems dynamics. While deep neural networks have shown initial promise, robustness concerns around long-term dependencies persist. This research pioneers a synergistic fusion of nonlinear time series analysis and algorithmic advances in representation learning to… Read full abstract & cite →

Stock market forecasting deep learning chaos theory phase space reconstruction transformer neural networks time series analysis

Abstract doi.org/10.14569/IJACSA.2023.0141292 PDF

93

Efficient IoT Security: Weighted Voting for BASHLITE and Mirai Attack Detection

Author 1: Marwan Abu-Zanona

The increasing number of devices in the Internet of Things (IoT) has exposed various vulnerabilities, such as BASHLITE and Mirai attacks, making it easier for cyber threats to emerge. Due to these vulnerabilities, developing innovative detection and mitigation strategies is essential. Our proposed solution is an ensemble-based weighted voting model… Read full abstract & cite →

Internet of Things IoT security BASHLITE Mirai attacks ensemble learning

Abstract doi.org/10.14569/IJACSA.2023.0141293 PDF

94

Sentiment Analysis on Banking Feedback and News Data using Synonyms and Antonyms

Author 1: Aniruddha Mohanty Author 2: Ravindranath C. Cherukuri

Sentiment analysis is crucial for deciphering customers’ enthusiasm, frustration, and the market mood within the banking sector. This importance arises from financial data’s specialized and sensitive nature, enabling a deeper understanding of customer sentiments. In today’s digital and social marketing landscape within the banking and financial sector, sentiment analysis is… Read full abstract & cite →

ELECTRA Synonyms and antonyms sentiment analysis datasets sentiment score control distance

Abstract doi.org/10.14569/IJACSA.2023.0141294 PDF

95

Iterative Learning Control for High Relative Degree Discrete-Time Systems with Random Initial Shifts

Author 1: Dongjie Chen Author 2: Tiantian Lu Author 3: Zhenjie Yin

In this paper, an iterative learning control (ILC) strategy under compression mapping framework is presented for high relative degree discrete-time systems with random initial shifts. Firstly, utilizing the high relative degree of the system and difference term, a control law is designed and a p-order non-homogeneous linear difference equation is… Read full abstract & cite →

Relative degree iterative learning control random initial shifts difference equation discrete-time system

Abstract doi.org/10.14569/IJACSA.2023.0141295 PDF

96

A Memetic Algorithm to Solve the Two-Echelon Collaborative Multi-Centre Multi-Periodic Vehicle Routing Problem with Specific Constraints

Author 1: Camelia Snoussi Author 2: Abdellah El Fallahi Author 3: Sarir Hicham

The collaboration between distribution companies is gaining a great interest in the last years due to the benefit provided to reduce the cost of deliveries. In this work we study the centralized two-echelon collaborative multi-center multi-periodic vehicle routing problem with a specific constraints. In which each distribution center conserves its… Read full abstract & cite →

Collaborative vehicle routing problem two-echelon networks memetic algorithm Variable neighbourhood serach

Abstract doi.org/10.14569/IJACSA.2023.0141296 PDF

97

Speech Recognition Models for Holy Quran Recitation Based on Modern Approaches and Tajweed Rules: A Comprehensive Overview

Author 1: Sumayya Al-Fadhli Author 2: Hajar Al-Harbi Author 3: Asma Cherif

Speech is considered the most natural way to communicate with people. The purpose of speech recognition technology is to allow machines to recognize and understand human speech, enabling them to take action based on the spoken words. Speech recognition is especially useful in educational fields, as it can provide powerful… Read full abstract & cite →

Speech recognition acoustic models language model neural network deep learning quran recitation

Abstract doi.org/10.14569/IJACSA.2023.0141297 PDF

98

Improving the Classification of Airplane Accidents Severity using Feature Selection, Extraction and Machine Learning Models

Author 1: Rachid KAIDI Author 2: Mohammed AL ACHHAB Author 3: Mohamed LAZAAR Author 4: Hicham OMARA

Airplane mode of transportation is statistically the most secure means of travel. This is due to the fact that flights require several conditions and precautions because aviation accidents are most of the time fatal and have disastrous consequences. For this purpose, in this paper, the mean goal is to study… Read full abstract & cite →

Airplane accident severity flights safety machine learning KNN Random Forest (RF) Decision Tree (DT)

Abstract doi.org/10.14569/IJACSA.2023.0141298 PDF

99

Enhancing Safety and Multifaceted Preferences to Optimise Cycling Routes for Cyclist-Centric Urban Mobility

Author 1: Mohammed Alatiyyah

In order to optimise bicycle routes across a variety of multiple parameters, including safety, efficiency and subtle rider preferences, this work explores the difficult domain of the Bike Routing Problem (BRP) using a sophisticated Simulated Annealing approach. In this innovative structure, a wide range of limitations and inclinations are combined… Read full abstract & cite →

Bike routing dynamic vehicle routing inventory routing approximate dynamic programming

Abstract doi.org/10.14569/IJACSA.2023.0141299 PDF

100

Recognition and Translation of Ancient South Arabian Musnad Inscriptions

Author 1: Afnan Altalhi Author 2: Atheer Alwethinani Author 3: Bashaer Alghamdi Author 4: Jumanah Mutahhar Author 5: Wojood Almatrafi Author 6: Seereen Noorwali

Inscriptions play an important role in preserving historical information. As such, conservation of these inscriptions provides valuable insights into the history and cultural heritage of the region. Musnad inscriptions are considered one of the earliest forms of writing from the Arabian Peninsula, preceding the modern Arabic font; however, most Musnad… Read full abstract & cite →

Musnad inscriptions text recognition deep learning VGG16 ResNet-50 MobileNetV2

Abstract doi.org/10.14569/IJACSA.2023.01412100 PDF

101

Learnable Local Similarity for Face Forgery Detection and Localization

Author 1: Lingyun Leng Author 2: Jianwei Fei Author 3: Yunshu Dai

The emergence of many face forgery technologies has led to the widespread of forgery faces on the Internet, causing a series of serious social impacts, thus face forgery detection technology has attracted increasing attention. While many face forgery detection algorithms have demonstrated impressive performance against known manipulation methods, their efficacy… Read full abstract & cite →

Face forgery detection local similarity forgery localization generalized detection

Abstract doi.org/10.14569/IJACSA.2023.01412101 PDF

102

CLFM: Contrastive Learning and Filter-attention Mechanism for Joint Relation Extraction

Author 1: Zhiyuan Wang Author 2: Chuyuan Wei Author 3: Jinzhe Li Author 4: Lei Zhang Author 5: Cheng Lv

Relation extraction is a fundamental task in natural language processing, which involves extracting structured information from textual data. Despite the success of joint methods in recent years, most of them still have the propagation of cascade errors. Specifically, the error in former step will be accumulated into the final combined… Read full abstract & cite →

Natural language processing relation extraction attention mechanism contrastive learning multi-task learning

Abstract doi.org/10.14569/IJACSA.2023.01412102 PDF

103

Enhancing Airborne Disease Prediction: Integrating Deep Infomax and Self-Organizing Maps for Risk Factor Identification

Author 1: Bhakti S. Pimpale Author 2: Anala A. Pandit

Asthma poses a significant global public health concern, particularly in urban centers where environmental pollutants and variable weather patterns contribute to heightened prevalence and symptom exacerbation. The Deonar dumping ground, one of Mumbai’s largest landfills, releases a complex mix of particulate matter and hazardous gases, posing a serious threat to… Read full abstract & cite →

Asthma deepinfomax self organizing map risk factors air pollution

Abstract doi.org/10.14569/IJACSA.2023.01412103 PDF

104

Enhancing Assamese Word Recognition for CBIR: A Comparative Study of Ensemble Methods and Feature Extraction Techniques

Author 1: Naiwrita Borah Author 2: Udayan Baruah Author 3: Barnali Dey Author 4: Merin Thomas Author 5: Sunanda Das Author 6: Moumi Pandit Author 7: Bijoyeta Roy Author 8: Amrita Biswas

This study conducts a thorough assessment of ensemble machine learning methods, specifically focusing on the identification of Assamese words. This task is crucial for improving Content-Based Image Retrieval systems and safeguarding the digital heritage of Assamese culture. We analyze the efficacy of different algorithms, such as CatBoost, XGBoost, Gradient Boosting… Read full abstract & cite →

Assamese literary works automatic word recognition comparative analysis feature-based approaches intelligent assistive technology machine learning word image analysis

Abstract doi.org/10.14569/IJACSA.2023.01412104 PDF

105

A Hybrid Deep Learning Framework for Efficient Sentiment Analysis

Author 1: Asish Karthikeya Gogineni Author 2: S Kiran Sai Reddy Author 3: Harika Kakarala Author 4: Yaswanth Chowdary Gavini Author 5: M Pavana Venkat Author 6: Koduru Hajarathaiah Author 7: Murali Krishna Enduri

In the era of Microblogging and the rapid growth of online platforms, an exponential rise is shown in the volume of data generated by internet users across various domains. Additionally, the creation of digital or textual data is expanding significantly. This is because consumers respond to comments made on social… Read full abstract & cite →

Sentiment analysis LSTM GRU Convolutional Neural Networks (CNNs) BOW TF-IDF

Abstract doi.org/10.14569/IJACSA.2023.01412105 PDF

106

Predictive Modeling of Landslide Susceptibility in Soft Soil Canal Regions: A Focus on Early Warning Systems

Author 1: Dang Tram Anh Author 2: Luong Vinh Quoc Danh Author 3: Chi-Ngon Nguyen

The Mekong Delta (MD) has suffered significant losses in land resources, economic damage, and human and property casualties due to recent landslides. An early warning system for landslides is a valuable tool for identifying the effectiveness and timely detection of changes in the soil to promptly determine solutions and minimize… Read full abstract & cite →

Landslide early warning soft soil Mekong Delta long short-term memory

Abstract doi.org/10.14569/IJACSA.2023.01412106 PDF

107

Transformative Learning Through Augmented Reality Empowered by Machine Learning for Primary School Pupils: A Real-Time Data Analysis

Author 1: Abinaya M Author 2: Vadivu G

Academic performance and student engagement are constant challenges in the field of modern education. When it comes to engaging students, traditional teaching methods frequently fall short, so creative solutions are needed. The Transformative potential of Augmented Reality (AR) technology as a cutting-edge teaching strategy is examined in this study. AR… Read full abstract & cite →

Artificial intelligence augmented reality adaptive learning machine learning transformative learning

Abstract doi.org/10.14569/IJACSA.2023.01412107 PDF

108

Indonesian Twitter Emotion Recognition Model using Feature Engineering

Author 1: Rhio Sutoyo Author 2: Harco Leslie Hendric Spits Warnars Author 3: Sani Muhamad Isa Author 4: Widodo Budiharto

Twitter is a social media platform that has a large amount of unstructured natural language text. The content of Twitter can be utilized to capture human behavior via emphasized emotions located in tweets. In their tweets, people commonly express emotions to show their feelings. Hence, it is crucial to recognize… Read full abstract & cite →

Text classification feature engineering emotion recognition Indonesian tweet natural language processing

Abstract doi.org/10.14569/IJACSA.2023.01412108 PDF

109

Robust Extreme Learning Machine with Exponential Squared Loss via DC Programming

Author 1: Kuaini Wang Author 2: Xiaoxue Wang Author 3: Weicheng Zhan Author 4: Mingming Wang Author 5: Jinde Cao

Extreme learning machines (ELM) have recently attracted considerable attention because of its fast learning rate, simple model structure, and good generalization ability. However, classical ELM with least squares loss function is prone to overfitting and lack robustness in dealing with datasets containing noise and outliers in the real world. In… Read full abstract & cite →

Extreme learning machine exponential squared loss DC programming DCA robust regression

Abstract doi.org/10.14569/IJACSA.2023.01412109 PDF

110

Quality of Data (QoD) in Internet of Things (IOT): An Overview, State-of-the-Art, Taxonomy and Future Directions

Author 1: Jameel Shehu Yalli Author 2: Mohd Hilmi Hasan Author 3: Nazleeni Samiha Haron Author 4: Mujeeb Ur Rehman Shaikh Author 5: Nafeesa Yousuf Murad Author 6: Abdullahi Lawal Bako

The Internet of Things (IoT) data is the main component for finding the basis that allows decisions to be made intelligently and enables other services to be explored and used. Data originates from smart things that have the capabilities to connect and share data enormously with other things in the… Read full abstract & cite →

Quality of Data (QoD) Internet of Things (IoT) RFID WSN Taxonomy trustworthiness outlier anomaly confusion matrix QoD assurance technique

Abstract doi.org/10.14569/IJACSA.2023.01412110 PDF