IJACSA Vol. 15 Issue 9 (2024)

1

Evolving Software Architectures from Monolithic Systems to Resilient Microservices: Best Practices, Challenges and Future Trends

Author 1: Martin Kaloudis

Microservice architecture has emerged as a widely adopted methodology in software development, addressing the inherent limitations of traditional monolithic and Service-Oriented Architectures (SOA). This paper examines the evolution of microservices, emphasising their advantages in enhancing flexibility, scalability, and fault tolerance compared to legacy models. Through detailed case studies, it explores… Read full abstract & cite →

Service-Orientated Architecture SOA microservices monolithic architecture migration

Abstract doi.org/10.14569/IJACSA.2024.0150901 PDF

2

The Effects of IDS/IPS Placement on Big Data Systems in Geo‑Distributed Wide Area Networks

Author 1: Michael Hart Author 2: Eric Richardson Author 3: Rushit Dave

Geographically-distributed wide-area networks (WANs) offer expansive distributed and parallel computing capabilities. This includes the ability to advance Wide-Area Big Data (WABD). As data streaming traverses foreign networks, intrusion detection systems (IDSs) and intrusion prevention systems (IDSs) play an important role in securing information. The authors anticipate that securing WAN network… Read full abstract & cite →

Information security network topology wide-area big data wide-area networks wide-area streaming

Abstract doi.org/10.14569/IJACSA.2024.0150902 PDF

3

STAR, a Universal, Repeatable, Strategic Model of Corporate Innovation for Industry Domination

Author 1: Ronald Berman Author 2: Nicholas Markette Author 3: Robert Vera Author 4: Tim Gehle

Within an existing organization, internal expertise, staffing, compensation, information systems, and market focus may complicate the introduction of new ideas while culture and aversion to risk may completely derail the organizations’ ability to innovate. The STAR model for corporate innovation provides a theoretical model on how to develop and execute… Read full abstract & cite →

Corporate entrepreneurship innovation model market dominance competitive advantage

Abstract doi.org/10.14569/IJACSA.2024.0150903 PDF

4

Control-Driven Media: A Unifying Model for Consistent, Cross-platform Multimedia Experiences

Author 1: Ingar M. Arntzen Author 2: Njal T. Borch Author 3: Anders Andersen

Many media providers offer complementary prod-ucts on different platforms to target a diverse consumer base. Online sports coverage, for instance, may include professionally produced audio and video channels, as well as Web pages and native apps offering live statistics, maps, data visualizations, social commentary and more. Many consumers also engage… Read full abstract & cite →

Multi-platform media control continuous media data-driven media interactive media orchestrated media

Abstract doi.org/10.14569/IJACSA.2024.0150904 PDF

5

AI-Assisted Academic Writing: A Comparative Study of Student-Crafted and ChatGPT-Enhanced Critiques in Ubiquitous Computing

Author 1: Edward R Sykes

This study examines the impact of Large Language Models (LLMs), such as ChatGPT, on the development of academic critique skills among fourth-year Computer Science undergraduates enrolled in a Ubiquitous Computing course. The research systematically evaluates the differences between student-authored critiques and those revised with the aid of ChatGPT, utilizing established… Read full abstract & cite →

AI in higher education AI in academic writing readability metrics LLM ethical considerations

Abstract doi.org/10.14569/IJACSA.2024.0150905 PDF

6

A Natural Language Processing Model for the Development of an Italian-Language Chatbot for Public Administration

Author 1: Antonio Piizzi Author 2: Donatello Vavallo Author 3: Gaetano Lazzo Author 4: Saverio Dimola Author 5: Elvira Zazzera

Natural Language Processing models (NLP) are used in chatbots to understand user input, interpret its meaning, and generate conversational responses to provide immediate and consistent assistance. This reduces problem-solving time and staff workload and increases user satisfaction. There are both rule-based chatbots, which use decision trees and are programmed to… Read full abstract & cite →

Natural Language Processing chatbot BERT transformer Italian language

Abstract doi.org/10.14569/IJACSA.2024.0150906 PDF

7

Deep Neural Network and Human-Computer Interaction Technology in the Field of Art Design

Author 1: Lan Guo Author 2: Lisha Luo Author 3: Weiquan Fan

Traditional art design is usually based on the designer’s intuitive creativity. Limited by individual experience, knowledge and imagination, it is difficult to create more abundant and higher quality works, and the workload is huge, which limits the production efficiency of artworks. Through deep neural networks and human-computer interaction technology, the… Read full abstract & cite →

Deep neural network human-computer interaction Cycle Generative Adversarial Networks art design image generation

Abstract doi.org/10.14569/IJACSA.2024.0150907 PDF

8

Development of Real Time Meteorological Grade Monitoring Stations with AI Analytics

Author 1: Adrian Kok Eng Hock Author 2: Chan Yee Kit Author 3: Koo Voon Chet

Air pollution comes in many forms and the basis of measure is the concentration of particles in the air. The quality of air depends on the quantity of pollution measured by a particle sensor that is accurate down to micron-meter consistencies. The size of the pollutants will be ingested by… Read full abstract & cite →

Air pollution air particles PM2.5 PM10 real time light scattering sensor neural networks AI machine learning R2 IoT WSM

Abstract doi.org/10.14569/IJACSA.2024.0150908 PDF

9

CNN-Based Salient Target Detection Method of UAV Video Reconnaissance Image

Author 1: Li Na

In order to address the challenges of image complexity, capturing subtle information, fluctuating lighting, and dynamic background interference in drone video reconnaissance, this paper proposes a salient object detection method based on convolutional neural network (CNN). This method first preprocesses the drone video reconnaissance images to remove haze and improve… Read full abstract & cite →

Regional convolutional neural network K-means clustering UAV reconnaissance image salient target detection task loss function

Abstract doi.org/10.14569/IJACSA.2024.0150909 PDF

10

Construction of Image Retrieval Module for Ethnic Art Design Products Based on DF-CNN

Author 1: Yaru He

With the increasing interest of consumers in ethnic art, more design products with ethnic art characteristics are being displayed. In order to help users easily retrieve related art products, an image retrieval model that can effectively extract data is proposed. The research method strengthens the depth of data mining through… Read full abstract & cite →

Image retrieval main characteristics local features deep forest convolutional neural network bar attention mechanism residual module

Abstract doi.org/10.14569/IJACSA.2024.0150910 PDF

11

Application of Speech Recognition Technology Based on Multimodal Information in Human-Computer Interaction

Author 1: Yuan Zhang

Multimodal human-computer interaction is an important trend in the development of human-computer interaction field. In order to accelerate the technological change of human-computer interaction system, the study firstly fuses Connectionist Temporal Classification algorithm and attention mechanism to design a speech recognition architecture, and then further optimizes the end-to-end architecture of… Read full abstract & cite →

Multimodal information speech recognition intelligent optimization algorithm multimodal human-computer interaction CTC attention mechanisms artificial bee colony algorithms

Abstract doi.org/10.14569/IJACSA.2024.0150911 PDF

12

Application of Fuzzy Decision Support System Based on GNN in Anomaly Detection and Incident Response Service of Intelligent Security

Author 1: Tao Chen Author 2: Xiaoqian Wu

This paper introduces a fuzzy decision support system (FDSS) based on a graph neural network (GNN) for anomaly detection and intelligent security. The primary aim is to develop a robust system capable of accurately identifying anomalies and providing timely incident response services. GNNs are utilized to capture the complex relationships… Read full abstract & cite →

GNN fuzzy decision support system intelligent security anomaly detection incident response service

Abstract doi.org/10.14569/IJACSA.2024.0150912 PDF

13

Using Combined Data Encryption and Trusted Network Methods to Improve the Network Security of the Internet of Things Applications

Author 1: Yudan Zhao

With the integration of big data and artificial intelligence, the Internet of Things has rapidly developed as the foundation for collecting data. The data collected by Internet of Things devices is mostly sensitive information, but limited resources can easily lead to data leakage. Therefore, this study adopts a combination of… Read full abstract & cite →

Security protocols Encryption Internet of Things Resource constraints SM9

Abstract doi.org/10.14569/IJACSA.2024.0150913 PDF

14

Application and Effectiveness of Improving Retrieval Systems Based on User Understanding in Smart Archive Management Systems

Author 1: Chao Yan

In traditional archive management systems, keyword-based retrieval systems often fail to meet users' personalized and precise retrieval needs. To solve this problem, a knowledge graph is first constructed using bidirectional long short-term memory networks and conditional random fields and combined with user understanding-based semantic retrieval to obtain an improved personalized… Read full abstract & cite →

Knowledge graph user understanding retrieval system smart archive management BiLSTM-CRF

Abstract doi.org/10.14569/IJACSA.2024.0150914 PDF

15

Automatic Recognition and Labeling of Knowledge Points in Learning Test Questions Based on Deep-Walk Image Data Mining

Author 1: Ying Chang Author 2: Qinghua Zhu

This paper deeply studies and discusses the application of image data mining technology based on the Deep-Walk algorithm in automatic recognition and annotation of knowledge points in learning test questions. With the rapid development of educational informatization, how to effectively mine and label the knowledge points in learning test questions… Read full abstract & cite →

Deep-walk image data mining study test questions knowledge point recognition

Abstract doi.org/10.14569/IJACSA.2024.0150915 PDF

16

Heart-SecureCloud: A Secure Cloud-Based Hybrid DL System for Diagnosis of Heart Disease Through Transformer-Recurrent Neural Network

Author 1: Talal Saad Albalawi

Cardiovascular disease (CVD) has rapidly increased after COVID-19. Several computerized systems have been developed in the past to diagnose CVD disease. However, the high computing expenses of deep learning (DL) models and the complexity of architectures are significant issues. Therefore, to resolve these issues, an accurate diagnosis of CVD disease… Read full abstract & cite →

Heart disease diagnosis deep learning cloud computing feature extraction data security hyperparameter optimization encryption

Abstract doi.org/10.14569/IJACSA.2024.0150916 PDF

17

Pre-Encryption Ransomware Detection (PERD) Taxonomy, and Research Directions: Systematic Literature Review

Author 1: Mujeeb Ur Rehman Shaikh Author 2: Mohd Fadzil Hassan Author 3: Rehan Akbar Author 4: Rafi Ullah Author 5: K.S. Savita Author 6: Ubaid Rehman Author 7: Jameel Shehu Yalli

Today’s era is witnessing an alarming surge in ransomware attacks, propelled by the increasingly sophisticated obfuscation tools deployed by cybercriminals to evade conventional antivirus defenses. Therefore, there is a need to better detect and obfuscate viruses. This analysis embarks on a comprehensive exploration of the intricate landscape of ransomware threats… Read full abstract & cite →

Cybersecurity ransomware detection static and dynamic analysis machine learning cyber-attacks security

Abstract doi.org/10.14569/IJACSA.2024.0150917 PDF

18

Texture Feature and Mel-Spectrogram Analysis for Music Sound Classification

Author 1: M. E. ElAlami Author 2: S. M. K. Tobar Author 3: S. M. Khater Author 4: Eman. A. Esmaeil

The categorization of music has received substantial interest in the management of large-scale databases. However, the sound of music classification (MC) is poorly interesting, making it a big challenge. For this reason, this paper has proposed a new robust combining method based on texture feature with Mel-spectrogram to classify Arabic… Read full abstract & cite →

Mel-spectrograms ML texture features MC

Abstract doi.org/10.14569/IJACSA.2024.0150918 PDF

19

DeeplabV3+ Model with CBAM and CSPM Attention Mechanism for Navel Orange Defects Segmentation

Author 1: Guo Jinmei Author 2: Wan Nurshazwani Wan Zakaria Author 3: Wei Bisheng Author 4: Muhammad Azmi Bin Ayub

Accurate defect detection of navel oranges is the key to ensuring the quality of navel oranges and extending their storage life. An improved DeeplabV3+ model integrating attention mechanism is proposed to increase the current low recognition accuracy and slow detection speed of defect detection in navel oranges grading and sorting… Read full abstract & cite →

Navel oranges defect detection DeeplabV3+ HECA-MobileNetV3 CBAM attention mechanism CSPM mechanism

Abstract doi.org/10.14569/IJACSA.2024.0150919 PDF

20

A Framework for Capturing Quality Requirements by Integrating the Requirement Engineering Elements in Agile Software Development Methods

Author 1: Yuli Fitrisia Author 2: Rosziati Ibrahim

The early phase of Agile Software Development (ASD) methods is Requirement Engineering (RE). Quality Requirement (QR) is a type of RE that needs to be captured at the initial development phase to reduce rework, time, and maintenance costs. However, QR is one of the issues mentioned in ASD, namely the… Read full abstract & cite →

Quality requirement requirement engineering ASD framework ASD practitioners

Abstract doi.org/10.14569/IJACSA.2024.0150920 PDF

21

Data Mining for the Analysis of Student Assessment Results in Engineering by Applying Active Didactic Strategy

Author 1: César Baluarte-Araya Author 2: Oscar Ramirez-Valdez Author 3: Ernesto Suarez-Lopez Author 4: Percy Huertas-Niquén

To make improvements in the teaching-learning process in educational institutions such as universities, it is necessary to analyse the results obtained and recorded from applying Active Didactic Strategies and, based on this, to propose improvements that will help to achieve the Student Outcomes established for the subject in question; the… Read full abstract & cite →

Student outcome problem based learning assessment performance indicator data mining

Abstract doi.org/10.14569/IJACSA.2024.0150921 PDF

22

Compactness-Weighted KNN Classification Algorithm

Author 1: Bengting Wan Author 2: Zhixiang Sheng Author 3: Wenqiang Zhu Author 4: Zhiyi Hu

The K-Nearest Neighbor (KNN) algorithm is a widely used classical classification tool, yet enhancing the classification ac-curacy for multi-feature large datasets remains a challenge. The paper introduces a Compactness-Weighted KNN classification algorithm using a weighted Minkowski distance (CKNN) to address this. Due to the variability in sample distribution, a method… Read full abstract & cite →

K-nearest neighbors feature weight Minkowski distance com-pactness

Abstract doi.org/10.14569/IJACSA.2024.0150922 PDF

23

SIEM and Threat Intelligence: Protecting Applications with Wazuh and TheHive

Author 1: Jumiaty Author 2: Benfano Soewito

The consequences of cyberattacks on enterprises are highly varied. DDoS assaults can render an organization's website inaccessible; SQL attacks can compromise the integrity of data in a database, and Brute Force attacks can lead to unauthorized users gaining control over a server or application. Hence, it is crucial for enterprises… Read full abstract & cite →

Application server security application vulnerability threat detection SIEM Wazuh TheHive Telegram and CVSS

Abstract doi.org/10.14569/IJACSA.2024.0150923 PDF

24

Dynamic Priority-Based Round Robin: An Advanced Load Balancing Technique for Cloud Computing

Author 1: Parupally Venu Author 2: Pachipala Yellamma Author 3: Yama Rupesh Author 4: Yerrapothu Teja Naga Eswar Author 5: Maruboina Mahiddar Reddy

An imbalance of load is an essential problem in cloud computing where the division of work between virtual machines is not well-optimized. Performance bottlenecks result from this unequal resource allocation, which keeps the system from operating at its full capability. Managing this load-balancing issue becomes critical to improving overall efficiency… Read full abstract & cite →

Load balancer traffic distribution cloud computing resource utilization scalability Dynamic Priority Based Round Robin (DPBRR)

Abstract doi.org/10.14569/IJACSA.2024.0150924 PDF

25

Enhancing BLDC Motor Speed Control by Mitigating Bias with a Variation Model Filter

Author 1: Abdul Rahman Abdul Majid

Brushless DC motors (BLDC) are integral to a wide array of applications, from electric vehicles to industrial machinery, due to their superior efficiency, reliability, and performance. Effective control of BLDC motors is essential to leverage their full potential and ensure optimal operation. Traditional PID controllers often fall short in handling… Read full abstract & cite →

EV’s motors brushless direct current (BLDC) motor active disturbances rejection control (ADRC) disturbance rejection bias estimation Variation Model Filter (VMF)

Abstract doi.org/10.14569/IJACSA.2024.0150925 PDF

26

Dynamic Monitoring of Bridge Structures via an Integrated Cloud and Edge Computing System

Author 1: Guoqi Zhang Author 2: Pengcheng Zhang Author 3: Xingwang Li Author 4: Yizhe Yang

Traditional bridge monitoring techniques, which predominantly rely on centralized data processing, often exhibit slow and inflexible responses when managing large-scale sensor network data. This study proposes an integrated edge and cloud computing approach to enhance the response time and data processing efficiency of dynamic bridge structure monitoring systems, thereby improving… Read full abstract & cite →

Dynamic monitoring of bridge structures edge computing cloud computing data processing modal analysis

Abstract doi.org/10.14569/IJACSA.2024.0150926 PDF

27

Optimized Fertilizer Dispensing for Sustainable Agriculture Through Secured IoT-Blockchain Framework

Author 1: B. C. Preethi Author 2: G. Sugitha Author 3: T. B. Sivakumar

Precision farming is essential for optimizing resource use and improving crop yields to attain sustainable agriculture. However, challenges like data insecurity, fertilizer costs, and inadequate consideration of soil health pose a hindrance to achieving these goals. To overcome these issues, the proposed work presents a novel approach for optimizing fertilizer… Read full abstract & cite →

Fertilizer dispensing IoT sensors blockchain deep learning convolutional neural network greenhouse management and decentralized application

Abstract doi.org/10.14569/IJACSA.2024.0150927 PDF

28

A Capacity-Influenced Approach to Find Better Initial Solution in Transportation Problems

Author 1: Md. Toufiqur Rahman Author 2: A R M Jalal Uddin Jamali Author 3: Momta Hena Author 4: Mohammad Mehedi Hassan Author 5: Md Rafiul Hassan

Finding an Initial Basic Feasible Solution (IBFS) is the first and essential step in obtaining the optimal solution for any Transportation Problem. Numerous approaches are available in the literature to determine the IBFS; however, many of these methods are modifications of Vogel's Approximate Method (VAM) and/or the Least Cost Method… Read full abstract & cite →

Transportation problem least cost method Vogel’s approximate method cost matrix transportation tableau node capacity route capacity-influenced weighted opportunity cost

Abstract doi.org/10.14569/IJACSA.2024.0150928 PDF

29

RSS-LSTM: A Metaheuristic-Driven Optimization Approach for Efficient Text Classification

Author 1: Muhammad Nasir Author 2: Noor Azah Samsudin Author 3: Shamsul Kamal Ahmad Khalid Author 4: Souad Baowidan Author 5: Humaira Arshad Author 6: Wareesa Sharif

The digital data consumed by the average user daily is huge now and is increasing daily all over the world, which requires sophisticated methods to automatically process data, such as retrieving, searching, and formatting the data, particularly for classifying text data. Long Short-Term Memory (LSTM) is a prominent deep learning… Read full abstract & cite →

Deep learning text classification Long Short-Term Memory Ringed Seal Search metaheuristic algorithms Part Swarm Optimization Genetic Algorithm Firefly Algorithm hyperparameter optimization

Abstract doi.org/10.14569/IJACSA.2024.0150929 PDF

30

Construction of Image Retrieval Module for Cultural and Creative Products Based on DF-CNN

Author 1: Meng Jiang

With the growth of the cultural and creative product industry, more and more cultural and creative products have been designed and published in different channels. A method based on image retrieval module is proposed to address the search problem of Chinese creative products in online channels. During the process, a… Read full abstract & cite →

Image retrieval class vector extreme gradient enhancement Chinese creative products layer by layer processing

Abstract doi.org/10.14569/IJACSA.2024.0150930 PDF

31

Method for Mission Analysis Using ToT-Based Prompt Technology Utilized Generative AI

Author 1: Kohei Arai

Method for mission analysis using ToT: Tree of Thought-based prompt technology utilized generative analysis AI is proposed. Mission analysis needs methods for simulation of the supposed images which will be acquired with the imaging mission instruments, and the other mission instruments. In order to create simulation images, ToT-based prompt technology… Read full abstract & cite →

CoT ToT AI Mission analysis prompt technology generative AI SaganSat-0 remote sensing satellite 720-degree camera thermal infrared camera Geiger counter

Abstract doi.org/10.14569/IJACSA.2024.0150931 PDF

32

IoT-Based Integrated Heads-Up Display for Motorcycle Helmet

Author 1: L. Raj Author 2: M. Batumalay Author 3: C. Batumalai Author 4: Prabadevi B

The prevalence of visual impairment among the global population is a growing concern, with rates continuing to rise at an alarming pace. According to statistics from the World Health Organization (WHO), an estimated 2.2 billion people globally live with some form of visual impairment. Several methods exist to aid the… Read full abstract & cite →

Heads-up display motorcycle helmet Internet of Things (IoT) android application Raspberry Pi product innovation

Abstract doi.org/10.14569/IJACSA.2024.0150932 PDF

33

A Robust Wrapper-Based Feature Selection Technique Using Real-Valued Triangulation Topology Aggregation Optimizer

Author 1: Li Pan Author 2: Wy-Liang Cheng Author 3: Sew Sun Tiang Author 4: Kim Soon Chong Author 5: Chin Hong Wong Author 6: Abhishek Sharma Author 7: Touseef Sadiq Author 8: Aasam Karim Author 9: Wei Hong Lim

Feature selection is a critical preprocessing technique used to remove irrelevant and redundant features from datasets while maintaining or improving the accuracy of machine learning models. Recent advancements in this area have primarily focused on wrapper-based feature selection methods, which leverage metaheuristic search algorithms (MSAs) to identify optimal feature subsets… Read full abstract & cite →

Classification exploration exploitation feature selection metaheuristic search algorithm machine learning optimization triangulation topology aggregation optimizer

Abstract doi.org/10.14569/IJACSA.2024.0150933 PDF

34

Mixed Integer Programming Model Based on Data Algorithms in Sustainable Supply Chain Management

Author 1: Shaobin Dong Author 2: Aihua Li

With the deepening of globalization and increasing demands for environmental sustainability, modern supply chains are faced with increasingly complex management challenges. To reduce management costs and enhance efficiency, an experimental approach is proposed based on a Mixed Integer Programming Model, integrating heuristic algorithms with adaptive genetic algorithms. The objective is… Read full abstract & cite →

Mixed Integer Programming Model sustainable supply chain management heuristic algorithm adaptive genetic algorithm

Abstract doi.org/10.14569/IJACSA.2024.0150934 PDF

35

DBRF: Random Forest Optimization Algorithm Based on DBSCAN

Author 1: Wang Zhuo Author 2: Azlin Ahmad

The correlation and redundancy of features will directly affect the quality of randomly selected features, weakening the convergence of random forests (RF) and reducing the performance of random forest models. This paper introduces an improved random forest algorithm—A Random Forest Algorithm Based on DBSCAN (DBRF). The algorithm utilizes the DBSCAN… Read full abstract & cite →

Random forest DBSCAN feature selection feature redundancy classification algorithm

Abstract doi.org/10.14569/IJACSA.2024.0150935 PDF

36

Enhancing Emergency Response: A Smart Ambulance System Using Game-Building Theory and Real-Time Optimization

Author 1: Guneet Singh Bhatia Author 2: Azhar Hussain Mozumder Author 3: Saied Pirasteh Author 4: Satinder Singh Author 5: Moin Hasan

Dispatching ambulances early and efficiently is paramount and difficult in the field of emergency medical services. In this regard, the paper designs a smart ambulance system based on game-building theory. The system employs an advanced Negamax algorithm for optimizing the dispatch of ambulances during emergencies. Besides traditional methods, real-time traffic… Read full abstract & cite →

Emergency medical services ambulance dispatch optimization advanced game theory Negamax algorithm real-time optimization predictive analytics

Abstract doi.org/10.14569/IJACSA.2024.0150936 PDF

37

Deep Reinforcement Learning-Based Carrier Tuning Algorithm for Mobile Communication Networks

Author 1: Weimin Zhang Author 2: Xinying Zhao

With the evolution of mobile communication networks towards 5G and beyond to 6G, managing network resources presents unprecedented challenges, particularly in scenarios demanding high data rates, low latency, and extensive connectivity. Traditional resource allocation methods struggle with network dynamics and complexity, including user mobility, varying network loads, and diverse Quality… Read full abstract & cite →

DRL mobile network carrier tuning

Abstract doi.org/10.14569/IJACSA.2024.0150937 PDF

38

Human-Computer Interaction Standardization and Systematization Development

Author 1: Xiaoling Lyu Author 2: Hongmiao Yuan Author 3: Zhao Zhang

Amidst the information technology boom, this study harnesses IT and human-computer interaction to revolutionize English education. Our model, grounded in literature review and fieldwork, implemented teaching experiments that enhanced students' English proficiency by 25%, particularly in listening and speaking. Student engagement and interest surged by 30%, underscoring the effectiveness of… Read full abstract & cite →

Human-computer interaction information technology English education standardization systematization

Abstract doi.org/10.14569/IJACSA.2024.0150938 PDF

39

Eavesdropping Interference in Wireless Communication Networks Based on Physical Layer Security

Author 1: Mingming Chen Author 2: Yuzhi Chen

Effective communication security protection can protect people's privacy from being violated. To raise the communication security of wireless communication networks, a collaborative eavesdropping interference scheme with added artificial noise is proposed by combining physical layer security and clustering scenarios to protect the communication security of wireless sensor networks. This scheme… Read full abstract & cite →

Wireless communication sensors network security eavesdropping interference clustering scenario

Abstract doi.org/10.14569/IJACSA.2024.0150939 PDF

40

Development of a Hybrid Quantum Key Distribution Concept for Multi-User Networks

Author 1: Begimbayeva Y Author 2: Zhaxalykov T Author 3: Makarov M Author 4: Ussatova O Author 5: Tynymbayev S Author 6: Temirbekova Zh

This paper investigates the increasing concerns related to the vulnerability of contemporary security solutions in the face of quantum-based attacks, which pose significant challenges to existing cryptographic methods. Most current Quantum Key Distribution (QKD) protocols are designed with a focus on point-to-point communication, limiting their application in broader network environments… Read full abstract & cite →

Quantum key distribution quantum communication multi-user networks network security quantum-based attacks cryptography point-to-point protocols resource efficiency cryptography information security

Abstract doi.org/10.14569/IJACSA.2024.0150940 PDF

41

The Role of Artificial Intelligence in Enhancing Business Intelligence Capabilities for E-Commerce Platforms

Author 1: Sinek Mehuli Br Perangin-Angin Author 2: David Jumpa Malem Sembiring Author 3: Asprina Br Surbakti Author 4: Soleh Darmansyah

This research focuses on the application of BERT (Bidirectional Encoder Representations from Transformers) and Graph Neural Networks (GNNs) to improve business intelligence (BI) capabilities on e-commerce platforms. The main aim of the research is to develop automation methods for the classification of customer interactions and to create a more effective… Read full abstract & cite →

Bidirectional Encoder Representations from Transformers (BERT) Graph Neural Networks (GNNs) business intelligence e-commerce product recommendation

Abstract doi.org/10.14569/IJACSA.2024.0150941 PDF

42

Elevating Grape Detection Precision and Efficiency with a Novel Deep Learning Model

Author 1: Xiaoli Geng Author 2: Yaru Huang Author 3: Yangxu Wang

In the domain of modern agricultural automation, precise grape detection in orchards is pivotal for efficient harvesting operations. This study introduces the Grapes Enhanced Feature Detection Network (GEFDNet), leveraging deep learning and convolutional neural networks (CNN) to enhance target detection capabilities specifically for grape detection in orchard environments. GEFDNet integrates… Read full abstract & cite →

Computer vision deep learning Convolutional Neural Networks (CNN) real-time object detection dual-path detection structure

Abstract doi.org/10.14569/IJACSA.2024.0150942 PDF

43

Vehicular Traffic Congestion Detection System and Improved Energy-Aware Cost Effective Task Scheduling Approach for Multi-Objective Optimization on Cloud Fog Network

Author 1: Praveen Kumar Mishra Author 2: Amit Kumar Chaturvedi

A current research area called fog computing aims to extend the advantages of cloud computing to network edges. Task scheduling is a crucial problem for fog device data processing since a lot of data from the sensor or Internet of Things layer is generated at the fog layer. This research… Read full abstract & cite →

IoT fog computing task scheduling multi objective Model iFogSim tool

Abstract doi.org/10.14569/IJACSA.2024.0150943 PDF

44

Deep Learning with IoT-Based Solar Energy System for Future Smart Agriculture System

Author 1: Vidya M S Author 2: Ravi Kumar B. N Author 3: Anil G. N Author 4: Ambika G. N

Agriculture has a considerable contribution to the economy. Agriculture automation is a serious issue that is becoming more prevalent around the world. Farmers' traditional practices were insufficient to achieve these objectives. Artificial Intelligence (A1) and the Internet of Things (IoTs) are being used in agriculture to improve crop yield and… Read full abstract & cite →

Precision agriculture smart monitoring Internet of Things Radial Basis Function Networks Elephant Search Algorithm (ESA)

Abstract doi.org/10.14569/IJACSA.2024.0150944 PDF

45

Subjectivity Analysis of an Enhanced Feature Set for Code-Switching Text

Author 1: Emaliana Kasmuri Author 2: Halizah Basiron

The phenomenon of code-switching has posed a new challenge to the linguistic computing area. Conventionally, the computer will process monolingual text or multilingual text. However, code-switching is different from this kind of text. Two or more languages are used to construct a piece of code-switching text, particularly a code-switching sentence… Read full abstract & cite →

Subjectivity analysis code-switching enhanced feature sets Malay-English text

Abstract doi.org/10.14569/IJACSA.2024.0150945 PDF

46

A Lightweight Privacy Preservation Protocol for IOT

Author 1: Ahmed Mahmoud Al-Badawy Author 2: Mohammed Belal Author 3: Hala Abbas

Due to rapid evolution of Internet of things (IOT) in terms of hardware, software and communication leads to widespread expansion across many domains and sectors. This expansion consequently results in sensitive data transfer increase for purposes of complex calculations and decision making which in turn leads to increase of data… Read full abstract & cite →

IOT data privacy lightweight protocols end to end protection data and metadata protection

Abstract doi.org/10.14569/IJACSA.2024.0150946 PDF

47

Basira: An Intelligent Mobile Application for Real-Time Comprehensive Assistance for Visually Impaired Navigation

Author 1: Amal Alshahrani Author 2: Areej Alqurashi Author 3: Nuha Imam Author 4: Amjad Alghamdi Author 5: Raghad Alzahrani

Individuals with visual impairments face numerous challenges in their daily lives, with navigating streets and public spaces being particularly daunting. The inability to identify safe crossing locations and assess the feasibility of crossing significantly restricts their mobility and independence. The profound impact of visual impairments on daily activities underscores the… Read full abstract & cite →

Visual impairment mobility application computer vision object detection obstacle detection

Abstract doi.org/10.14569/IJACSA.2024.0150947 PDF

48

Machine Translation-Based Language Modeling Enables Multi-Scenario Applications of English Language

Author 1: Shengming Liu

Traditional machine translation models suffer from problems such as long training time and insufficient adaptability when dealing with multiple English language scenarios. At the same time, some models often struggle to meet practical translation needs in complex language environments. A translation model that combines the feed-forward neural network decoder and… Read full abstract & cite →

Machine translation decoder English language multi-scene attention mechanism

Abstract doi.org/10.14569/IJACSA.2024.0150948 PDF

49

Detecting Malware of Windows OS Using AI Classification for Image of Extracted Behavior Features

Author 1: Kang Dongshik Author 2: Noor Aldeen Alhamedi

Malware detection is crucial for protecting digital environments. Traditional methods involve static and dynamic analysis, but recent advancements leverage artificial intelligence (AI) to enhance detection accuracy. This study aims to improve malware detection by integrating dynamic malware analysis with AI-driven techniques. The primary challenge addressed is accurately classifying and detecting… Read full abstract & cite →

Malware analysis dynamic-based analysis image classification malware behavior extraction text

Abstract doi.org/10.14569/IJACSA.2024.0150949 PDF

50

Dynamic Path Planning for Autonomous Robots in Forest Fire Scenarios Using Hybrid Deep Reinforcement Learning and Particle Swarm Optimization

Author 1: N. K. Thakre Author 2: Divya Nimma Author 3: Anil V Turukmane Author 4: Akhilesh Kumar Singh Author 5: Divya Rohatgi Author 6: Balakrishna Bangaru

The growing frequency of forest area fires poses critical challenges for emergency response, necessitating progressive solutions for effective navigation and direction planning in dynamic environments. This study investigates an adaptive technique to enhance the performance of autonomous robots deployed in forest area fireplace scenarios. The primary objective is to develop… Read full abstract & cite →

Adaptive path planning deep reinforcement learning disaster environments drone rescuing particle swarm optimization forest fire

Abstract doi.org/10.14569/IJACSA.2024.0150950 PDF

51

A Convolutional Neural Network-Based Predictive Model for Assessing the Learning Effectiveness of Online Courses Among College Students

Author 1: Xuehui Zhang Author 2: Lin Yang

With the development of artificial intelligence (AI) technology, higher education institutions usually consider both online courses and offline classrooms in the course design process. To verify the effectiveness of online courses, this study designed a deep learning model to analyze the learning behavior of online course users (college students) and… Read full abstract & cite →

Convolutional neural network nutcracker optimization algorithm assessment of learning effectiveness college students online courses

Abstract doi.org/10.14569/IJACSA.2024.0150951 PDF

52

Forensic Facial Reconstruction from Sketch in Crime Investigation

Author 1: Doaa M. Mohammed Author 2: Mostafa Elgendy Author 3: Mohamed Taha

Many crimes are committed every day all over the world, and one of them is a criminal offense that includes a wide range of illegal acts such as murder, theft, assault, rape, kidnapping, fraud, and others. Criminals pose a threat to security, which harms the public interest. In this case… Read full abstract & cite →

Sketch-to-Face facial features Sketch-to-Face CycleGAN victim's identification criminal offense

Abstract doi.org/10.14569/IJACSA.2024.0150952 PDF

53

Artificial Intelligence-Driven Decision Support Systems for Sustainable Energy Management in Smart Cities

Author 1: Ning MA

Due to the ongoing urbanization trend, smart cities are critical to designing a sustainable future. Urban sustainability involves action-oriented approaches for optimizing resource usage, ecological impact reduction, and overall efficiency enhancement. Energy management is one of the main concerns in urban, residential, and building planning. Artificial Intelligence (AI) uses data… Read full abstract & cite →

Smart cities artificial intelligence decision support systems sustainable energy management urban resilience interdisciplinary collaboration

Abstract doi.org/10.14569/IJACSA.2024.0150953 PDF

54

Exploring Multimedia Movement Through Spatio-Temporal Indexing and Double-Cache Schemes

Author 1: Zhen QIN Author 2: Lin ZHANG

Conventional IP/TCP designs encounter several safety and scalability concerns with the growing demand for application services. A novel Internet design, like a Content Center Network (CCN), was introduced to address these issues comprehensively. Every hub within a CCN is responsible for data storage. The collaboration guarantees users quick data retrieval… Read full abstract & cite →

Multimedia digital art double-cache collaboration distributed indexing spatio-temporal data content center network

Abstract doi.org/10.14569/IJACSA.2024.0150954 PDF

55

A Secure and Efficient Framework for Multi-User Encrypted Cloud Databases Supporting Single and Multiple Keyword Searches

Author 1: J V S Arundathi Author 2: K V V Satyanarayana

Multi-user encrypted cloud databases have become essential for secure data storage and retrieval, especially when supporting both single and multiple keyword searches. Ensuring data confidentiality, integrity, and efficient access within such systems is paramount, particularly when dealing with multiple data owners and users. This paper presents a Secure Encrypted Trie-based… Read full abstract & cite →

Secure keyword search encrypted search multi-user framework encrypted cloud database single and multiple key users

Abstract doi.org/10.14569/IJACSA.2024.0150955 PDF

56

Exploring the Application of Neural Networks in the Learning and Optimization of Sports Skills Training

Author 1: Dazheng Liu

Sports skills training is a crucial component of sports education, significantly contributing to the development of athletic abilities and overall physical literacy. It is essential to utilized neural networks to optimize traditional training methods that are inefficient and rely on subjective assessments. This paper develops methods for sports action recognition… Read full abstract & cite →

Deep neural network action recognition 2D pose prediction pose estimation sports skill training attention mechanism

Abstract doi.org/10.14569/IJACSA.2024.0150956 PDF

57

Birth Certificates Delivery, Traceability and Authentication Using Blockchain Technology

Author 1: Tankou Tsomo Maurice Eddy Author 2: Bell Bitjoka Georges Author 3: Ngohe Ekam Paul Salomon Author 4: Ekani Mebenga Vianney Boniface

Now-a-days, the vast majority of birth certificate registration systems are paper-based and managed independently by administrative communities. This means that birth information only exists at the place where the birth is registered, which facilitates the counterfeiting or falsification of such identity documents. Therefore, the implementation of a system for the… Read full abstract & cite →

Birth certificates blockchain security traceability authentication counterfeiting falsification hyperledger fabric

Abstract doi.org/10.14569/IJACSA.2024.0150957 PDF

58

Optimizing Customer Interactions: A BERT and Reinforcement Learning Hybrid Approach to Chatbot Development

Author 1: K. R. Praneeth Author 2: Taranpreet Singh Ruprah Author 3: J Naga Madhuri Author 4: A L Sreenivasulu Author 5: Syed Shareefunnisa Author 6: Vuda Sreenivasa Rao

In the case of chatbots massive progress has been made, but problems remain in handling the complexity of the sentence and in context relevance. Traditional models can be rather insufficient when it comes to providing various levels of detail in the responses to the end-users’ questions, particularly when referring to… Read full abstract & cite →

Chatbots BERT (Bidirectional Encoder Representations from Transformers) RL (Reinforcement Learning) customer service responsiveness

Abstract doi.org/10.14569/IJACSA.2024.0150958 PDF

59

Liver and Tumour Segmentation Using Anchor Free Mechanism-Based Mask Region Convolutional Neural Network

Author 1: Sangi Narasimhulu Author 2: Ch D V Subba Rao

An accurate liver tumour segmentation helps acquire the measurable biomarkers for decision support systems and Computer-Aided Diagnosis (CAD). However, most existing approaches fail to effectively segment tumours in the liver due to the overlapping of liver with any other organ in the image. To solve this problem, this research proposes… Read full abstract & cite →

Anchor free computer-aided diagnosis deep neural network EfficientNetB2 liver and tumor segmentation masked region-based convolutional neural network

Abstract doi.org/10.14569/IJACSA.2024.0150959 PDF

60

Efficient Task Offloading Using Ant Colony Optimization and Reptile Search Algorithms in Edge Computing for Things Context

Author 1: Ting Zhang Author 2: Xiaojie Guo

The widespread use of Internet of Things (IoT) technology has triggered unparalleled data creation and processing needs, necessitating effective computation offloading solutions. Conventional edge computing approaches have difficulties in dealing with rising energy usage issues and task allocation delays. This study introduces a novel hybrid metaheuristic algorithm called ACO-RSA, which… Read full abstract & cite →

Task offloading edge computing ant colony optimization reptile search algorithm Internet of Things energy efficiency

Abstract doi.org/10.14569/IJACSA.2024.0150960 PDF

61

Bubble Detection in Glass Manufacturing Images Using Generative Adversarial Networks, Filters and Channel Fusion

Author 1: Md Ezaz Ahmed Author 2: Mohammad Khalid Imam Rahmani Author 3: Surbhi Bhatia Khan

With the increasing production of glassware products, the detection of bubble defects has been of vital importance. The manual inspection of glass bubble defects is considered to be tedious and inefficient way due to the increasing volume of images, and the high probability of human error. Computer vision-based methods provide… Read full abstract & cite →

Computer vision Generative Adversarial Network Information-Preserving Feature Aggregation Conflict Information Suppression Feature Fusion Module Fine-Grained Aggregation Module deep learning

Abstract doi.org/10.14569/IJACSA.2024.0150961 PDF

62

Dimensionality Reduction Evolutionary Framework for Solving High-Dimensional Expensive Problems

Author 1: SONGWei Author 2: ZOUFucai

Most of improvement strategies for surrogate-assisted optimiza-tion algorithms fail to help the population quickly locate satis-factory solutions. To address this challenge, a novel framework called dimensionality reduction surrogate-assisted evolutionary (DRSAE) framework is proposed. DRSAE introduces an effi-cient dimensionality reduction network to create a low-dimensional search space, allowing some individuals to… Read full abstract & cite →

Dimensionality reduction high-dimensional expensive optimiza-tion Surrogate-assisted model

Abstract doi.org/10.14569/IJACSA.2024.0150962 PDF

63

Optimization of the Energy-Saving Data Storage Algorithm for Differentiated Cloud Computing Tasks

Author 1: Peichen Zhao

This study presents a novel energy-saving data storage algorithm designed to enhance data storage efficiency and reduce energy consumption in cloud computing environments. By intelligently discerning and categorizing various cloud computing tasks, the algorithm dynamically adapts data storage strategies, resulting in a targeted optimization methodology that is both devised and… Read full abstract & cite →

Energy-saving data storage algorithm differentiated task recognition cloud computing intelligent storage strategy data classification and distribution

Abstract doi.org/10.14569/IJACSA.2024.0150963 PDF

64

Advancing Quantum Cryptography Algorithms for Secure Data Storage and Processing in Cloud Computing: Enhancing Robustness Against Emerging Cyber Threats

Author 1: Devulapally Swetha Author 2: Shaik Khaja Mohiddin

The rise of cloud computing has transformed data storage and processing but introduced new vulnerabilities, especially with the impending threat of quantum computing. Traditional cryptographic methods, though currently effective, are at risk of being compromised by quantum attacks. This research aims to develop a quantum-resistant security framework for cloud environments… Read full abstract & cite →

Quantum key distribution cloud computing cyber threats lattice based cryptography E91 future-proof security paradigm python quantum computing

Abstract doi.org/10.14569/IJACSA.2024.0150964 PDF

65

Advancements and Challenges in Geospatial Artificial Intelligence, Evaluating Support Vector Machines Models for Dengue Fever Prediction: A Structured Literature Review

Author 1: Hetty Meileni Author 2: Ermatita Author 3: Abdiansah Author 4: Nyayu Latifah Husni

This review examines recent advancements and ongoing challenges in applying Support Vector Machines within Geospatial Artificial Intelligence, specifically for dengue fever prediction. Recent developments in Support Vector Machines include the introduction of advanced kernel methods, such as Radial Basis Function and polynomial kernels, which enhance the model’s ability to handle… Read full abstract & cite →

Support vector machines geospatial artificial intelligence kernel methods dengue fever prediction real-time data analytics

Abstract doi.org/10.14569/IJACSA.2024.0150965 PDF

66

Multimedia Network Data Fusion System Integrating SSA and Reinforcement Learning

Author 1: Fangrui Li

To improve the performance and efficiency of multimedia network data fusion system, this study proposes an improved sparrow search algorithm on the ground of reinforcement learning algorithm and sparrow search algorithm, and improves the multimedia network data fusion model on the ground of this algorithm. A performance comparison experiment was… Read full abstract & cite →

Sparrow search algorithm reinforcement learning multimedia network data fusion performance improvement

Abstract doi.org/10.14569/IJACSA.2024.0150966 PDF

67

Application of U-Net Network Algorithm in Electronic Information Field

Author 1: Liang Wang

This rapidly evolving landscape, which includes the field of medical diagnostics, has integrated with the electronic data (E-Data) field to provide precise and efficient treatment for complex medical conditions. The research field has further catapulted its reach to include various data types, including image, video, medical expert diagnostic type, and… Read full abstract & cite →

U-Net attention calibrated U-Net convolutional neural network deep learning digital data accuracy

Abstract doi.org/10.14569/IJACSA.2024.0150967 PDF

68

Natural Disaster Clustering Using K-Means, DBSCAN, SOM, GMM, and Mean Shift: An Analysis of Fema Disaster Statistics

Author 1: Ting Tin Tin Author 2: Yap Jia Hao Author 3: Yong Chang Yeou Author 4: Lim Siew Mooi Author 5: Goh Ting Yew Author 6: Temitope Olumide Olugbade Author 7: Ali Aitizaz

Natural disasters tend to ruin people’s lives and infrastructure, which requires comprehensive analysis and understanding to inform effective disaster management and response planning. This research addresses the lack of in-depth analysis of federally declared disasters in the United States using a dataset sourced from FEMA. Through the application of unsupervised… Read full abstract & cite →

Natural disasters disaster management unsupervised learning clustering disaster frequency disaster types mitigation strategies adaptation strategies

Abstract doi.org/10.14569/IJACSA.2024.0150968 PDF

69

Impact of Read Theory in Mobile-Assisted Language Learning on Engineering Freshmen's Reading Comprehension Using BI-LSTM

Author 1: E. Pearlin Author 2: S. Mercy Gnana Gandhi

The effect of Read Theory in Mobile-Assisted Language Learning (MALL) on reading comprehension is critical, especially for engineering freshmen who require excellent language abilities to navigate their complicated academic courses. Read Theory is a customized reading platform that offers adaptive reading activities based on the user's ability level, which is… Read full abstract & cite →

Read theory language learning Bi-LSTM mobile-assisted deep learning

Abstract doi.org/10.14569/IJACSA.2024.0150969 PDF

70

Advancing Natural Language Processing with a Combined Approach: Sentiment Analysis and Transformation Using Graph Convolutional LSTM

Author 1: Kedala Karunasree Author 2: P. Shailaja Author 3: T Rajesh Author 4: U. Sesadri Author 5: Choudaraju Neelima Author 6: Divya Nimma Author 7: Malabika Adak

Sentiment analysis is a key component of Natural Language Processing (NLP), taking into account the extraction of emotional cues from text. However, traditional strategies often fail to capture diffused feelings embedded in language. To deal with this, we advocate a novel hybrid model that complements sentiment analysis by way of… Read full abstract & cite →

Graph Convolutional Networks (GCN) Long Short-Term Memory (LSTM) Natural Language Processing (NLP) sentiment analysis emotions text classification machine learning

Abstract doi.org/10.14569/IJACSA.2024.0150970 PDF

71

ABC-Optimized CNN-GRU Algorithm for Improved Cervical Cancer Detection and Classification Using Multimodal Data

Author 1: Donepudi Rohini Author 2: M Kavitha

Cervical cancer is the second most common malignancy among women, making it a major public health problem worldwide. Early detection of cervical cancer is important because it increases the chances of effective treatment and survival. Regular screening and early management can prevent the growth of cervical cancer, thus reducing mortality… Read full abstract & cite →

Cervical cancer CNN-GRU Pap smear images Artificial Bee Colony Optimizer early detection

Abstract doi.org/10.14569/IJACSA.2024.0150971 PDF

72

Enhancing Student Well-Being Prediction with an Innovative Attention-LSTM Model

Author 1: Vinod Waiker Author 2: Janjhyam Venkata Naga Ramesh Author 3: Ajmeera Kiran Author 4: Pradeep Jangir Author 5: Ritwik Haldar Author 6: Padamata Ramesh Babu Author 7: E. Thenmozhi

This study introduces a groundbreaking method for predicting scholar well-being with the use of a sophisticated interest-primarily based Long Short-Term Memory (LSTM) version. Addressing the developing problem of intellectual health in academic settings, the studies pursuits to provide new insights and powerful techniques for reinforcing pupil mental well-being. The recognition… Read full abstract & cite →

Student mental health attention-based LSTM well-being enhancement predictive modelling innovative techniques

Abstract doi.org/10.14569/IJACSA.2024.0150972 PDF

73

A Hybrid Intelligent System for IP Traffic Classification

Author 1: Muhana Magboul Ali Muslam

The classification of IP traffic is important for many reasons, including network management and security, quality of service (QoS) monitoring and provisioning, and high hardware utilisation. Recently, many machine learning-based IP traffic classifiers have been developed. Unfortunately, most of them need to be trained on large datasets and thus require… Read full abstract & cite →

Internet application classification IP traffic classification machine learning machine learning techniques stacking classifier

Abstract doi.org/10.14569/IJACSA.2024.0150973 PDF

74

Deep Learning-Driven Localization of Coronary Artery Stenosis Using Combined Electrocardiograms (ECGs) and Photoplethysmograph (PPG) Signal Analysis

Author 1: Mohd Syazwan Md Yid Author 2: Rosmina Jaafar Author 3: Noor Hasmiza Harun Author 4: Mohd Zubir Suboh Author 5: Mohd Shawal Faizal Mohamad

The application of artificial intelligence (AI) to electrocardiograms (ECGs) and photoplethysmograph (PPG) for diagnosing significant coronary artery disease (CAD) is not well established. This study aimed to determine whether the combination of ECG and PPG signals could accurately identify the location of blocked coronary arteries in CAD patients. Simultaneous measurement… Read full abstract & cite →

Deep learning CNN LSTM ATTN simultaneous ECG and PPG coronary artery disease

Abstract doi.org/10.14569/IJACSA.2024.0150974 PDF

75

Increasing the Performance of Iceberg Query Through Summary Tables

Author 1: Gohar Rahman Author 2: Wajid Ali Author 3: Mehmood Ahmed Author 4: Hassan Jamil Sayed Author 5: Mohammad A. Saleh

One of the key challenging problems in data mining is data retrieval from large data repositories, as the sizes of data are growing very fast, to deal with this situation, there is a need for efficient data mining techniques. For efficient mining tasks number of queries have been emerged. Iceberg… Read full abstract & cite →

Threshold (TH) bitmap index aggregate function Iceberg Query (IB) anti-monotone non-anti-monotone aggregation

Abstract doi.org/10.14569/IJACSA.2024.0150975 PDF

76

Enhancing Supply Chain Transparency and Efficiency Through Innovative Blockchain Solutions for Optimal Operations Management

Author 1: Shamrao Parashram Ghodake Author 2: Vishal M. Tidake Author 3: Sanjit Singh Author 4: Elangovan Muniyandy Author 5: Mohit Author 6: Lakshmana Phaneendra Maguluri Author 7: John T Mesia Dhas

Blockchain technology holds the potential to revolutionize supply chain management by ensuring transparency, efficiency, and security. This paper presents a detailed examination of blockchain's implementation in supply chain systems, focusing on safeguarding confidential information and preserving supply chain integrity. The method involves extracting ‘sales order’ data from Walmart’s transactional database… Read full abstract & cite →

Blockchain supply chain management advanced encryption standard Ethereum blockchain data storage

Abstract doi.org/10.14569/IJACSA.2024.0150976 PDF

77

Enhanced Quantitative Financial Analysis Using CNN-LSTM Cross-Stitch Hybrid Networks for Feature Integration

Author 1: Taviti Naidu Gongada Author 2: B. Kumar Babu Author 3: Janjhyam Venkata Naga Ramesh Author 4: P. N. V. Syamala Rao M Author 5: K. Aanandha Saravanan Author 6: K Swetha Author 7: Mano Ashish Tripathi

This research paper provides innovative approaches to support financial prediction, or it is a different kind of economic prediction that extends over collecting different economic information. Financial prediction is a concept that has been employed. The present study offers a unique approach to predicting finances by integrating many financial issues… Read full abstract & cite →

Cross-Stitch Hybrid Networks predictive modelling LSTM networks convolutional neural networks financial analysis

Abstract doi.org/10.14569/IJACSA.2024.0150977 PDF

78

Enhanced Early Detection of Oral Squamous Cell Carcinoma via Transfer Learning and Ensemble Deep Learning on Histopathological Images

Author 1: Gurjot Kaur Author 2: Sheifali Gupta Author 3: Ashraf Osman Ibrahim Author 4: Salil bharany Author 5: Marwa Anwar Ibrahim Elghazawy Author 6: Hadia Abdelgader Osman Author 7: Ali Ahmed

Oral Squamous Cell Carcinoma (OSCC) is one main kind of oral cancer; early diagnosis is rather important to increase patient survival chances. This study investigates the application of advanced deep learning techniques including transfer learning and ensemble learning to increase the accuracy of oral squamous cell cancer (OSCC) diagnosis using… Read full abstract & cite →

Oral Squamous Cell Carcinoma (OSCC) histopathology images transfer learning ensemble learning EfficientNetB3 ResNet50 deep learning cancer detection medical image analysis

Abstract doi.org/10.14569/IJACSA.2024.0150978 PDF

79

Furniture Panel Processing Positioning Design Based on 3D Measurement and Depth Image Technology

Author 1: Binglu Chen Author 2: Guanyu Chen Author 3: Qianqian Hu

In recent years, furniture panel processing positioning based on computer vision technology has received increasing attention. A 3D measurement imaging technology based on laser scanning technology is proposed to address the significant environmental impact of traditional visual technology. Subsequently, deep image processing techniques are introduced to address the high image… Read full abstract & cite →

Laser scanning 3D measurement deep image processing positioning computer vision

Abstract doi.org/10.14569/IJACSA.2024.0150979 PDF

80

Research and Implementation of Facial Expression Recognition Algorithm Based on Machine Learning

Author 1: Xinjiu Xie Author 2: Jinxue Huang

Traditional information security management methods can provide a degree of personal information protection but remain vulnerable to issues such as data breaches and password theft. To bolster information security, facial expression recognition offers a promising alternative. To achieve efficient and accurate facial expression recognition, we propose a lightweight neural network… Read full abstract & cite →

Facial expression expression recognition convolutional neural network deep learning

Abstract doi.org/10.14569/IJACSA.2024.0150980 PDF

81

Enhancing Music Emotion Classification Using Multi-Feature Approach

Author 1: Affreen Ara Author 2: Rekha V

Emotions are a fundamental aspect of human expression, and music lyrics are a rich source of emotional content. Understanding the emotions conveyed in lyrics is crucial for a variety of applications, including music recommendation systems, emotion classification, and emotion-driven music composition. While extensive research has been conducted on emotion classification… Read full abstract & cite →

Emotion classification music lyrics feature extraction lexicon features

Abstract doi.org/10.14569/IJACSA.2024.0150981 PDF

82

Art Image Color Sequence Data Processing Method Based on Artificial Intelligence Technology

Author 1: Xujing Zhao Author 2: Xiwen Chen Author 3: Jianfei Shen

With the traditional quality enhancement methods cannot control the best field density range resulting in too large threshold value of colour difference in art works. Therefore, a research on art works quality enhancement based on image processing technology is proposed. The CIE L* a* b* color space model is established… Read full abstract & cite →

Artworks quality enhancement image processing technology color space model target separation experimental color target

Abstract doi.org/10.14569/IJACSA.2024.0150982 PDF

83

AI-Driven Prioritization Techniques of Requirements in Agile Methodologies: A Systematic Literature Review

Author 1: Aya M. Radwan Author 2: Manal A. Abdel-Fattah Author 3: Wael Mohamed

Software requirements are the foundation of a successful software development project, outlining the customer's expectations for the software's functionality. Conventional techniques of requirement prioritization present several challenges, such as scalability, customer satisfaction, efficiency, and dependency management. These challenges make the process difficult to manage effectively. Prioritizing requirements by setting criteria… Read full abstract & cite →

Requirement analysis requirement prioritization agile fuzzy logic machine learning optimization

Abstract doi.org/10.14569/IJACSA.2024.0150983 PDF

84

Intelligent Detection and Search Model for Communication Signals Based on Deep-Re-Hash Retrieval Technology

Author 1: Hui Liu Author 2: Xupeng Liu

With the explosive growth of image data, traditional image retrieval methods face challenges of low efficiency and insufficient accuracy. In view of this, the study first analyzed the traditional Deep-Re-Hash detection technology and constructed a general hash detection model. Secondly, Cauchy functions and Hadamard matrices were introduced to optimize the… Read full abstract & cite →

Deep-Re-Hash retrieval communication signals image data cauchy function hadamard matrix

Abstract doi.org/10.14569/IJACSA.2024.0150984 PDF

85

Content-Based Image Retrieval Using Transfer Learning and Vector Database

Author 1: Li Shuo Author 2: Lilly Suriani Affendey Author 3: Fatimah Sidi

Content-based image retrieval (CBIR) systems are essential for efficiently searching large image datasets using image features instead of text annotations. Major challenges include extracting effective feature representations to improve accuracy, as well as indexing them to improve the retrieval speed. The use of pre-trained deep learning models to extract features… Read full abstract & cite →

Content-based image retrieval (CBIR) image retrieval transfer learning convolutional neural networks VGG-16 vector database milvus feature extraction high-dimensional vectors real-time image search

Abstract doi.org/10.14569/IJACSA.2024.0150985 PDF

86

Towards Accurate Detection of Diabetic Retinopathy Using Image Processing and Deep Learning

Author 1: K. Kalindhu Navanjana De Silva Author 2: T. Sanduni Kumari Lanka Fernando Author 3: L. D. Lakshan Sandaruwan Jayasinghe Author 4: M.H.Dinuka Sandaruwan Jayalath Author 5: Kasun Karunanayake Author 6: B.A.P. Madhuwantha

Diabetic retinopathy (DR) is a critical complication of diabetes, characterized by pathological changes in retinal blood vessels. This paper presents an innovative software application designed for DR detection and staging using fundus images. The system generates comprehensive reports, facilitating treatment planning and improving patient outcomes. Our study aims to develop… Read full abstract & cite →

Diabetic retinopathy fundus images computer-assisted analysis deep learning image processing convolutional neural networks component

Abstract doi.org/10.14569/IJACSA.2024.0150986 PDF

87

Machine Learning Approaches for Predicting Occupancy Patterns and its Influence on Indoor Air Quality in Office Environments

Author 1: Amir Hamzah Mohd Shaberi Author 2: Sumayyah Dzulkifly Author 3: Wang Shir Li Author 4: Yona Falinie A. Gaus

It is normal for the modern population to spend 12 hours or more daily indoors where the level of comfort can be moderated. Yet, indoor occupants are similarly exposed to various air pollutants just as outdoors. Indoor air pollution could be detrimental toward the occupant's health noted by the United… Read full abstract & cite →

Indoor air quality occupancy patterns machine learning deep learning regression models Mean Squared Error Mean Absolute Error IAQ monitoring IAQ management

Abstract doi.org/10.14569/IJACSA.2024.0150987 PDF

88

Visualization of Personality and Phobia Type Clustering with GMM and Spectral

Author 1: Ting Tin Tin Author 2: Cheok Jia Wei Author 3: Ong Tzi Min Author 4: Lim Siew Mooi Author 5: Lee Kuok Tiung Author 6: Ali Aitizaz Author 7: Chaw Jun Kit Author 8: Ayodeji Olalekan Salau

Personality traits, the unique characteristics defining individuals, have intrigued philosophers and scholars for centuries. With recent advances in machine learning, there is an opportunity to revolutionize how we understand and differentiate personality traits. This study seeks to develop a robust cluster analysis approach (unsupervised learning) to efficiently and accurately classify… Read full abstract & cite →

Unsupervised learning learning opportunities clustering personality machine learning Gaussian mixture model spectral clustering

Abstract doi.org/10.14569/IJACSA.2024.0150988 PDF

89

A Comprehensive Study of BIM for Infrastructural Crack Detection and the Vital Strategies

Author 1: Samuel Adekunle Author 2: Opeoluwa Akinradewo Author 3: Babatunde Ogunbayo Author 4: Andrew Ebekozien Author 5: Clinton Aigbavboa

Building information modelling is one of the emerging technologies in the construction industry and is relevant to its productivity and efficiency. Application which affects the product and process of the industry. An underdeveloped area with less attention is its adoption for crack detection and visualisation for infrastructural maintenance. This study… Read full abstract & cite →

Developing country emerging technology facility management visualisation emerging technology South Africa

Abstract doi.org/10.14569/IJACSA.2024.0150989 PDF

90

The Adoption of Electronic Payments in Online Shopping: The Mediating Role of Customer Trust

Author 1: Nguyen Thi Phuong Giang Author 2: Thai Dong Tan Author 3: Le Huu Hung Author 4: Nguyen Binh Phuong Duy

This study investigates the factors influencing electronic payment in online shopping behavior among Ho Chi Minh City consumers. With the rapid advancement of technology, e-commerce has become a new trend, and understanding the intention to adopt electronic payment is crucial for online businesses. The research employs quantitative and qualitative methods… Read full abstract & cite →

Electronic payment Intention to use Online shopping

Abstract doi.org/10.14569/IJACSA.2024.0150990 PDF

91

Moving Beyond Traditional Incident Response: Combating APTs with Warfare-Enabled Continuous Response

Author 1: Abid Hussain Shah

Critically examining the cybersecurity management practices, it can be concluded that security management used by the organizations is mostly control-centered against a wide range of threats to information systems. This control-centered approach has matured to act as a shield to prevent against a large variety of attacks. Since threats against… Read full abstract & cite →

Information operations information warfare cyber security dynamic capabilities incident response capabilities warfare enabled capabilities

Abstract doi.org/10.14569/IJACSA.2024.0150991 PDF

92

Deep Learning-Based Image Recognition Technology for Wind Turbine Blade Surface Defects

Author 1: Zheng Cao Author 2: Qianming Wang

This paper proposes WindDefectNet, an image recognition system for surface defects of wind turbine blades, aiming at solving the key problems in wind turbine blade maintenance. At the beginning of the system design, the functional requirements and performance index requirements are clarified to ensure the realization of the functions of… Read full abstract & cite →

Wind turbine blades image recognition defect detection deep learning WindDefectNet

Abstract doi.org/10.14569/IJACSA.2024.0150992 PDF

93

Design of Intelligent Extraction Method for Key Electronic Information Based on Neural Networks

Author 1: Xiaoqin Chen Author 2: Xiaojun Cheng

With the rapid development of the Internet and other emerging media, how to find the needed information from massive electronic documents in time and accurately has become an urgent problem. A key electronic information extraction method based on neural network learning ideas has been proposed to solve the problems of… Read full abstract & cite →

Key electronic information intelligent extraction TextRank LSTM context

Abstract doi.org/10.14569/IJACSA.2024.0150993 PDF

94

Optimized Blockchain-Based Deep Learning Model for Cloud Intrusion Detection

Author 1: Sultan Alasmari

Cyberattacks are becoming increasingly complex and subtle. In many different types of networks, intrusion detection systems, or IDSs, are frequently employed to help in the prompt detection of intrusions. Blockchain technology has gained a lot of attention recently as a means of sharing data without a reliable third party. Specifically… Read full abstract & cite →

Intrusion detection system blockchain deep learning hybrid optimization cloud computing feature selection

Abstract doi.org/10.14569/IJACSA.2024.0150994 PDF

95

Deep Learning for Stock Price Prediction and Portfolio Optimization

Author 1: Ashy Sebastian Author 2: Veerta Tantia

Using deep learning for stock market predictions and portfolio optimizations is a burgeoning field of research. This study focuses on the stock market dynamics in developing countries, which are often considered less stable than their developed counterparts. The study is structured in two stages. In the first stage, the authors… Read full abstract & cite →

Deep learning long-short term memory stock price prediction portfolio optimization emerging markets Indian stock market

Abstract doi.org/10.14569/IJACSA.2024.0150995 PDF

96

An Efficient Hierarchical Mechanism for Handling Network Partitioning Over Mobile Ad Hoc Networks

Author 1: Ali Tahir Author 2: Fathe Jeribi

Mobile ad hoc networks exhibit distinctive challenges e.g., limited transmission range and dynamic mobility of the participating nodes. These challenges serve as the reasons for the frequent occurrence of network partitioning in mobile ad hoc networks. Network partitioning happens when a linked network topology is partitioned into two or more… Read full abstract & cite →

Mobile Ad Hoc networks network partitioning distributed hash tables logical cluster member node logical cluster leader logical network identifier

Abstract doi.org/10.14569/IJACSA.2024.0150996 PDF

97

A Proposed λ_Mining Model for Hierarchical Multi-Level Predictive Recommendations

Author 1: Yousef S. Alsahafi Author 2: Ayman E. Khedr Author 3: Amira M. Idrees

Delivering the most suitable products and services essentially relies on successfully exploring the potential relationship between customers and products. This immense need for intelligent exploration has led to the emergence of recommendation systems. In an environment where an immense variety exists, it is vital for buyers to own an intelligent… Read full abstract & cite →

Recommendation systems data mining features selection associations rules mining classification techniques

Abstract doi.org/10.14569/IJACSA.2024.0150997 PDF

98

Proposal of OptDG Algorithm for Solving the Knapsack Problem

Author 1: Matej Arlovic Author 2: Tomislav Rudec Author 3: Josip Miletic Author 4: Josip Balen

In a computational complexity theory, P, NP, NP-complete and NP-hard problems are divided into complexity classes which are used to emphasize how challenging it is to solve particular types of problems. The Knapsack problem is a well-known computational complexity theory and fundamental NP-hard optimization problem that has applications in a… Read full abstract & cite →

Dynamic programming Dantzig algorithm greedy algorithm knapsack problem linear programming NP-Problem optimization OptDG

Abstract doi.org/10.14569/IJACSA.2024.0150998 PDF

99

A Relevant Feature Identification Approach to Detect APTs in HTTPS Traffic

Author 1: Abdou Romaric Tapsoba Author 2: Tounwendyam Frederic Ouedraogo

This study addresses the significant challenges posed by Advanced Persistent Threats (APTs) in modern computer networks, particularly their use of DNS to establish covert communication via command and control (C&C) servers. The advent of TLS 1.3 encryption further complicates detection efforts, as critical data within DNS over HTTPS (DoH) traffic… Read full abstract & cite →

DNS over HTTPS advanced persistent threats machine learning cyber threat intelligence MITRE ATT&CK domain generation algorithms

Abstract doi.org/10.14569/IJACSA.2024.0150999 PDF

100

Multiclass Fruit Detection Using Improved YOLOv3 Algorithm

Author 1: Seema C. Shrawne Author 2: Jay Sawant Author 3: Omkar Chaubal Author 4: Karan Suryawanshi Author 5: Diven Sirwani Author 6: Vijay K. Sambhe

Manual interventions continue to be used in fruit-picking and billing at large-scale fruit storage facilities. Recent advances in deep in learning approaches, such as one-stage detectors like You Only Look Once (YOLO) and Single Stage Detector (SSD), as well as two-stage detectors like Faster RCNN and Mask RCNN, aim to… Read full abstract & cite →

Precision agriculture yield estimation fruit detection YOLOv3 feature concatenation spatial contexting

Abstract doi.org/10.14569/IJACSA.2024.01509100 PDF

101

A Meta-Heuristics-Based Solution for Multi-Objective Workflow Scheduling in Fog Computing

Author 1: Gyan Singh Author 2: Vivek Dubey

In recent years, there has been a significant increase in the volume of data generated by Internet of Things (IoT) applications, mostly driven by the rapid proliferation of IoT devices and advancements in communication technologies. The conventional cloud computing network was not specifically built to handle such a vast volume… Read full abstract & cite →

Fog computing DAG workflow applications makespan energy PSO

Abstract doi.org/10.14569/IJACSA.2024.01509101 PDF

102

Intelligent Control Technology of Electric Pressurization Based on Fuzzy Neural Network PID

Author 1: Yabing Li Author 2: Limin Su Author 3: Huili Guo

In this study, we delved deeply into the intelligent control technology of electrical pressurization, utilizing a fuzzy neural network-based PID approach. By meticulously crafting a fuzzy neural network model and optimizing the PID control algorithm, we achieved intelligent control of electrical pressurization systems, enhancing both system stability and response speed… Read full abstract & cite →

Frequency conversion PID control algorithm electrical pressurization system intelligent control technology

Abstract doi.org/10.14569/IJACSA.2024.01509102 PDF

103

An Open-Domain Search Quiz Engine Based on Transformer

Author 1: Xiaoling Niu Author 2: Ge Guo

As the volume of information on the Internet continues to grow exponentially, efficient retrieval of relevant data has become a significant challenge. Traditional keyword matching techniques, while useful, often fall short in addressing the complex and varied queries users present. This paper introduces a novel approach to automated question and… Read full abstract & cite →

Natural language processing deep learning transformer Bi-LSTM semantic understanding

Abstract doi.org/10.14569/IJACSA.2024.01509103 PDF

104

An Artificial Neural Network Model for Water Quality Prediction in the Amoju Hydrographic Subbasin, Cajamarca-Peru

Author 1: Alex Alfredo Huaman Llanos Author 2: Jeimis Royler Yalta Meza Author 3: Danicza Violeta Sanchez Cordova Author 4: Juan Carlos Chasquero Martinez Author 5: Lenin Quiñones Huatangari Author 6: Dulcet Lorena Quinto Sanchez Author 7: Roxana Rojas Segura Author 8: Alfredo Lazaro Ludeña Gutierrez

Water quality is crucial for sustaining life, and accurate prediction models are essential for effective management. This study introduces an Artificial Neural Network (ANN) model designed to predict the Water Quality Index (WQI) in the Amoju Hydrographic Subbasin, Cajamarca-Peru. The model was developed using key water quality parameters, including electrical… Read full abstract & cite →

Artificial neural networks hydrographic subbasin machine learning models water quality index water resource management

Abstract doi.org/10.14569/IJACSA.2024.01509104 PDF

105

Interactive ChatBot for PDF Content Conversation Using an LLM Language Model

Author 1: Ting Tin Tin Author 2: Seow Yu Xuan Author 3: Wong Man Ee Author 4: Lee Kuok Tiung Author 5: Ali Aitizaz

Natural Language Processing (NLP) leverages Artificial Intelligence (AI) to enable computer programs to understand and generate human language. ChatGPT has recently become popular in assignment accomplishment. This project aims to develop and improve an interactive PDF chat application using OpenAI's language model (LLM), specifically GPT-3.5, integrated with Streamlit and LangChain… Read full abstract & cite →

Natural language processing learning opportunities ChatGPT PDF

Abstract doi.org/10.14569/IJACSA.2024.01509105 PDF

106

Prototype of an Indoor Pathfinding Application with Obstacle Detection for the Visually Impaired

Author 1: Ken Gorro Author 2: Lawrence Roble Author 3: Mike Albert Magana Author 4: Rey Paolo Buot Author 5: Louis Severino Romano Author 6: Herbert Cando Author 7: Bonifacio Amper Author 8: Rhyan Jay Signe Author 9: Elmo Ranolo

This study presents an initial prototype for a project aimed at assisting visually impaired individuals using deep learning techniques. The proposed system utilizes the You Only Look Once (YOLOv8) algorithm to detect objects tagged as obstacles. Designed for indoor environments, the system employs a CCTV camera and a computer server… Read full abstract & cite →

Yolov8 A-star algorithm pathfinding deep learning

Abstract doi.org/10.14569/IJACSA.2024.01509106 PDF

107

Real-Time Road Damage Detection System on Deep Learning Based Image Analysis

Author 1: Bakhytzhan Kulambayev Author 2: Belik Gleb Author 3: Nazbek Katayev Author 4: Islam Menglibay Author 5: Zeinel Momynkulov

This research paper introduces a sophisticated deep learning-based system for real-time detection and segmentation of road damages, utilizing the Mask R-CNN framework to enhance road maintenance and safety. The primary objective was to develop a robust automated system capable of accurately identifying and classifying various types of road damages under… Read full abstract & cite →

Deep learning road damage detection Mask R-CNN image segmentation convolutional neural networks infrastructure management smart cities real-time analytics predictive maintenance urban planning

Abstract doi.org/10.14569/IJACSA.2024.01509107 PDF

108

Real-Time Sign Language Fingerspelling Recognition System Using 2D Deep CNN with Two-Stream Feature Extraction Approach

Author 1: Aziza Zhidebayeva Author 2: Gulira Nurmukhanbetova Author 3: Sapargali Aldeshov Author 4: Kamshat Zhamalova Author 5: Satmyrza Mamikov Author 6: Nursaule Torebay

This research paper introduces a novel sign language recognition system developed using advanced deep learning (DL) techniques aimed at enhancing communication capabilities between deaf and hearing individuals. The system leverages a convolutional neural network (CNN) architecture, optimized for the real-time interpretation of dynamic hand gestures that constitute sign language. A… Read full abstract & cite →

Deep learning sign language recognition convolutional neural networks real-time processing gesture recognition machine learning accessibility technology

Abstract doi.org/10.14569/IJACSA.2024.01509108 PDF