IJACSA Vol. 14 Issue 6 (2023)

1

A Fuzzy Reward and Punishment Scheme for Vehicular Ad Hoc Networks

Author 1: Rezvi Shahariar Author 2: Chris Phillips

Trust management is an important security approach for the successful implementation of Vehicular Ad Hoc Networks (VANETs). Trust models evaluate messages to assign reward or punishment. This can be used to influence a driver’s future behaviour. In the author’s previous work, a sender-side based trust management framework is developed which… Read full abstract & cite →

VANET Trust management fuzzy logic Markov chain reward and punishment driver behaviour model

Abstract doi.org/10.14569/IJACSA.2023.0140601 PDF

2

Investigating the User Experience and Evaluating Usability Issues in AI-Enabled Learning Mobile Apps: An Analysis of User Reviews

Author 1: Bassam Alsanousi Author 2: Abdulmohsen S. Albesher Author 3: Hyunsook Do Author 4: Stephanie Ludi

Integrating artificial intelligence (AI) has become crucial in modern mobile application development. However, the current integration of AI in mobile learning applications presents several challenges regarding mobile app usability. This study aims to identify critical usability issues of AI-enabled mobile learning apps by analyzing user reviews. We conducted a qualitative… Read full abstract & cite →

Human-Computer Interaction (HCI) Artificial Intelligence (AI) user reviews AI-Enabled Mobile Apps usability

Abstract doi.org/10.14569/IJACSA.2023.0140602 PDF

3

A Hybrid Method Based on Gravitational Search and Genetic Algorithms for Task Scheduling in Cloud Computing

Author 1: Xiuyan ZHANG

Cloud computing has emerged as a novel technology that offers convenient and cost-effective access to a scalable pool of computing resources over the internet. Task scheduling plays a crucial role in optimizing the functionality of cloud services. However, inefficient scheduling practices can result in resource wastage or a decline in… Read full abstract & cite →

Cloud computing task scheduling genetic algorithm gravitational search algorithm

Abstract doi.org/10.14569/IJACSA.2023.0140603 PDF

4

Shape Control of a Dual-Segment Soft Robot using Depth Vision

Author 1: Hu Junfeng Author 2: Zhang Jun

Pneumatic soft robots outperform rigid robots in complex environments due to the high flexibility of their redundant configurations, and their shape control is considered a prerequisite for applications in unstructured environments. In this paper, we propose a depth vision-based shape control method for a two-segment soft robot, which uses a… Read full abstract & cite →

Pneumatic soft robot shape control depth vision shape feature

Abstract doi.org/10.14569/IJACSA.2023.0140604 PDF

5

Fast Pasture Classification Method using Ground-based Camera and the Modified Green Red Vegetation Index (MGRVI)

Author 1: Boris Evstatiev Author 2: Tsvetelina Mladenova Author 3: Nikolay Valov Author 4: Tsenka Zhelyazkova Author 5: Mariya Gerdzhikova Author 6: Mima Todorova Author 7: Neli Grozeva Author 8: Atanas Sevov Author 9: Georgi Stanchev

The assessment of aboveground biomass is important for achieving rational usage of pasture resources and for maximizing the quantity and quality of milk and meat production. This study presents a method for fast approximation of pastures’ biomass. Unlike most similar studies, which rely on unmanned aerial vehicle and satellite obtained… Read full abstract & cite →

Pasture biomass MGRVI ground-based camera classification

Abstract doi.org/10.14569/IJACSA.2023.0140605 PDF

6

Instructional Digital Model to Promote Virtual Teaching and Learning for Autism Care Centres

Author 1: Norziana Yahya Author 2: Nazean Jomhari Author 3: Mohd Azahani Md Taib Author 4: Nahdatul Akma Ahmad

The COVID-19 pandemic has led to temporary school closures affecting over 90% of students worldwide. This has exacerbated educational inequality, particularly for students with learning disabilities such as autism spectrum disorder (ASD), whose routines, services, and support they rely on have been disrupted. To address this issue, it is important… Read full abstract & cite →

Instructional digital model virtual teaching and learning autism online learning pandemic

Abstract doi.org/10.14569/IJACSA.2023.0140606 PDF

7

Investigating OpenAI’s ChatGPT Potentials in Generating Chatbot's Dialogue for English as a Foreign Language Learning

Author 1: Julio Christian Young Author 2: Makoto Shishido

Lack of opportunities is a significant hurdle for English as a Foreign Language (EFL) for students during their learning journey. Previous studies have explored the use of chatbots as learning partners to address this issue. However, the success of chatbot implementation depends on the quality of the reference dialogue content… Read full abstract & cite →

ChatGPT chatbots as learning partners EFL chatbot system dialogue creation

Abstract doi.org/10.14569/IJACSA.2023.0140607 PDF

8

ConvNeXt-based Mango Leaf Disease Detection: Differentiating Pathogens and Pests for Improved Accuracy

Author 1: Asha Rani K P Author 2: Gowrishankar S

Mango farming is a key economic activity in several locations across the world. Mango trees are prone to various diseases caused by viruses and pests, which can substantially impair crops and have an effect on farmers' revenue. To stop the spread of these illnesses and to lessen the crop damage… Read full abstract & cite →

Mango disease pest pathogens machine learning deep learning convnext models

Abstract doi.org/10.14569/IJACSA.2023.0140608 PDF

9

A Fine-grained Access Control Model with Enhanced Flexibility and On-chain Policy Execution for IoT Systems

Author 1: Hoang-Anh Pham Author 2: Ngoc Nhuan Do Author 3: Nguyen Huynh-Tuong

Blockchain-based access control mechanisms have garnered significant attention in recent years due to their potential to address the security and privacy challenges in the Internet of Things (IoT) ecosystem. IoT devices generate massive amounts of data that are often transmitted to cloud-based servers for processing and storage. However, these devices… Read full abstract & cite →

Attribute-based Access Control (ABAC) Internet of Things (IoT) blockchain substrate framework

Abstract doi.org/10.14569/IJACSA.2023.0140609 PDF

10

DeLClustE: Protecting Users from Credit-Card Fraud Transaction via the Deep-Learning Cluster Ensemble

Author 1: Fidelis Obukohwo Aghware Author 2: Rume Elizabeth Yoro Author 3: Patrick Ogholoruwami Ejeh Author 4: Christopher Chukwufunaya Odiakaose Author 5: Frances Uche Emordi Author 6: Arnold Adimabua Ojugo

Fraud is the unlawful acquisition of valuable assets gained via intended misrepresentation. It is a crime committed by either an internal/external user, and associated with acts of theft, embezzlement, and larceny. The proliferation of credit cards to aid financial inclusiveness has its usefulness alongside it attracting malicious attacks for gains… Read full abstract & cite →

Fraud transactions fraud detection deep learning ensemble credit card fraud cluster modeling financial inclusion

Abstract doi.org/10.14569/IJACSA.2023.0140610 PDF

11

Proof of Spacetime as a Defensive Technique Against Model Extraction Attacks

Author 1: Tatsuki Fukuda

When providing a service that utilizes a machine learning model, the countermeasures against cyber-attacks are required. The model extraction attack is one of the attacks, in which an attacker attempts to replicate the model by obtaining a large number of input-output pairs. While a defense using Proof of Work has… Read full abstract & cite →

Proof of spacetime model extraction attacks machine learning security

Abstract doi.org/10.14569/IJACSA.2023.0140611 PDF

12

Deep Learning-based Intrusion Detection: A Novel Approach for Identifying Brute-Force Attacks on FTP and SSH Protocol

Author 1: Noura Alotibi Author 2: Majid Alshammari

As networks continue to expand rapidly, the number and diversity of cyberattacks are also increasing, posing a significant challenge for organizations worldwide. Consequently, brute-force attacks targeting FTP and SSH protocols have become more prevalent. IDSes offer an essential tool to detect these attacks, providing traffic analysis and system monitoring. Traditional… Read full abstract & cite →

Artificial neural networks machine learning deep ‎learning intrusion detection ‎system detecting brute ‎force attacks on SSH and FTP protocols

Abstract doi.org/10.14569/IJACSA.2023.0140612 PDF

13

Method for Characterization of Customer Churn Based on LightBGM and Experimental Approach for Mitigation of Churn

Author 1: Kohei Arai Author 2: Ikuya Fujikawa Author 3: Yusuke Nakagawa Author 4: Ryoya Momozaki Author 5: Sayuri Ogawa

A method for customer churn characterization based on LightBGM (Light Gradient Boosting Machine) is proposed. Additionally, experimental approaches for mitigation of churn are conducted through churn prediction. The experiments reveal several churn characteristics such as age dependency, gender dependency (with a high divorce rate among female customers), number of visits… Read full abstract & cite →

Churn LightBGM churn characteristics linear regression

Abstract doi.org/10.14569/IJACSA.2023.0140613 PDF

14

Artificial Intelligence-based Detection of Fava Bean Rust Disease in Agricultural Settings: An Innovative Approach

Author 1: Hicham Slimani Author 2: Jamal El Mhamdi Author 3: Abdelilah Jilbab

The traditional methods used to identify plant diseases mostly rely on expert opinion, which causes long waits and enormous expenses in the control of crop diseases and field activities, especially given that the majority of crop infections now in existence have tiny targets, occlusions, and looks that are similar to… Read full abstract & cite →

Fava bean disease deep learning YOLOv8 real-time detection

Abstract doi.org/10.14569/IJACSA.2023.0140614 PDF

15

Bidirectional Long-Short-Term Memory with Attention Mechanism for Emotion Analysis in Textual Content

Author 1: Batyrkhan Omarov Author 2: Zhandos Zhumanov

Emotion analysis in textual content plays a crucial role in various applications, including sentiment analysis, customer feedback monitoring, and mental health assessment. Traditional machine learning and deep learning techniques have been employed to analyze emotions; however, these methods often fail to capture complex and long-range dependencies in text. To overcome… Read full abstract & cite →

Deep learning emotion detection BiLSTM machine learning classification artificial intelligence

Abstract doi.org/10.14569/IJACSA.2023.0140615 PDF

16

Artificial Intelligence Enabled Mobile Chatbot Psychologist using AIML and Cognitive Behavioral Therapy

Author 1: Batyrkhan Omarov Author 2: Zhandos Zhumanov Author 3: Aidana Gumar Author 4: Leilya Kuntunova

In recent years, the demand for mental health services has increased exponentially, prompting the need for accessible, cost-effective, and efficient solutions. This paper introduces an Artificial Intelligence (AI) enabled mobile chatbot psychologist that leverages AIML (Artificial Intelligence Markup Language) and Cognitive Behavioral Therapy (CBT) to provide psychological support. The chatbot… Read full abstract & cite →

Chatbot artificial intelligence machine learning CBT AIML

Abstract doi.org/10.14569/IJACSA.2023.0140616 PDF

17

A Multi-branch Feature Fusion Model Based on Convolutional Neural Network for Hyperspectral Remote Sensing Image Classification

Author 1: Jinli Zhang Author 2: Ziqiang Chen Author 3: Yuanfa Ji Author 4: Xiyan Sun Author 5: Yang Bai

Hyperspectral image classification constitutes a pivotal research domain in the realm of remote sensing image processing. In the past few years, convolutional neural networks (CNNs) with advanced feature extraction capabilities have demonstrated remarkable performance in hyperspectral image classification. However, the challenges faced by classification methods are compounded by the difficulties… Read full abstract & cite →

Hyperspectral image classification convolutional neural network (CNN) multi-branch network feature fusion

Abstract doi.org/10.14569/IJACSA.2023.0140617 PDF

18

Socio Technical Framework to Improve Work Behavior During Smart City Implementation

Author 1: Eko Haryadi Author 2: Abdul Karim Author 3: Lizawati Salahuddin

Every organization uniquely adheres to security culture. Numerous studies have discovered that procrastinating, impulsive, forward-thinking, and risk-taking behaviors vary across organizations, which may help to explain why different organizations' adherence to security policies. This study describes the human aspect of a government organization in contributing to the successful implementation of… Read full abstract & cite →

Framework socio technical cybersecurity behavior threat smart city

Abstract doi.org/10.14569/IJACSA.2023.0140618 PDF

19

Detecting Malware with Classification Machine Learning Techniques

Author 1: Mohd Azahari Mohd Yusof Author 2: Zubaile Abdullah Author 3: Firkhan Ali Hamid Ali Author 4: Khairul Amin Mohamad Sukri Author 5: Hanizan Shaker Hussain

In today's digital landscape, the identification of malicious software has become a crucial undertaking. The ever-growing volume of malware threats renders conventional signature-based methods insufficient in shielding against novel and intricate attacks. Consequently, machine learning strategies have surfaced as a viable means of detecting malware. The following research report focuses… Read full abstract & cite →

Malware classification machine learning accuracy false positive rate

Abstract doi.org/10.14569/IJACSA.2023.0140619 PDF

20

Evaluation of the Accidents Risk Caused by Truck Drivers using a Fuzzy Bayesian Approach

Author 1: Imane Benallou Author 2: Abdellah Azmani Author 3: Monir Azmani

Road accidents cause hundreds of fatalities and injuries each year; due to their size and operating features, heavy trucks typically experience more severe accidents. Many factors are likely to cause such accidents; however, statistics mainly blame human error. This paper analyses the risk of accidents for heavy vehicles, focusing on… Read full abstract & cite →

Heavy truck vehicle road accident prevention risk management bayesian-fuzzy network analysis tree event

Abstract doi.org/10.14569/IJACSA.2023.0140620 PDF

21

Software Cost Estimation using Stacked Ensemble Classifier and Feature Selection

Author 1: Mustafa Hammad

Predicting the cost of the development effort is essential for successful projects. This helps software project managers to allocate resources, and determine budget or delivery date. This paper evaluates a set of machine learning algorithms and techniques in predicting the development cost of software projects. A feature selection algorithm is… Read full abstract & cite →

Software project management effort estimation prediction model machine learning

Abstract doi.org/10.14569/IJACSA.2023.0140621 PDF

22

An Algorithm Based on Self-balancing Binary Search Tree to Generate Balanced, Intra-homogeneous and Inter-homogeneous Learning Groups

Author 1: Ali Ben Ammar Author 2: Amir Abdalla Minalla

This paper presents an algorithm, based on the self-balancing binary search tree, to form learning groups. It aims to generate learning groups that are intra-homogeneous (student performance similarity within the group), inter-homogeneous (group performance similarity between groups), and of balanced size. The algorithm mainly uses the 2-3 tree and the… Read full abstract & cite →

Learning group formation balanced size groups homogeneous groups self-balancing binary search trees greedy algorithm

Abstract doi.org/10.14569/IJACSA.2023.0140622 PDF

23

Multi-Features Audio Extraction for Speech Emotion Recognition Based on Deep Learning

Author 1: Jutono Gondohanindijo Author 2: Muljono Author 3: Edi Noersasongko Author 4: Pujiono Author 5: De Rosal Moses Setiadi

The increasing need for human interaction with computers makes the interaction process more advanced, one of which is by utilizing voice recognition. Developing a voice command system also needs to consider the user's emotional state because the users indirectly treat computers like humans in general. By knowing the type of… Read full abstract & cite →

Deep learning multi-features extraction RAVDESS speech emotion recognition

Abstract doi.org/10.14569/IJACSA.2023.0140623 PDF

24

Hierarchical Convolutional Neural Networks using CCP-3 Block Architecture for Apparel Image Classification

Author 1: Natthamon Chamnong Author 2: Jeeraporn Werapun Author 3: Anantaporn Hanskunatai

In fashion applications, deep learning has been applied automatically to recognize and classify the apparel images under the massive visual data, emerged on social networks. To classify the apparel correctly and quickly is challenging due to a variety of apparel features and complexity of the classification. Recently, the hierarchical convolutional… Read full abstract & cite →

Convolutional neural networks (CNN) hierarchical CNN (H-CNN) CCP-3 block (two convolutional layers (CC) and one pooling layer (P) per block) apparel image classification fashion applications

Abstract doi.org/10.14569/IJACSA.2023.0140624 PDF

25

Towards Point Cloud Classification Network Based on Multilayer Feature Fusion and Projected Images

Author 1: Tengteng Song Author 2: YiZhi He Author 3: Muhammad Tahir Author 4: Jianbo Li Author 5: Zhao Li Author 6: Imran Saeed

Deep Learning (DL) based point cloud classification techniques now in use suffer from issues such as disregarding local feature extraction, missing connections between points, and failure to extract two-dimensional information features from point clouds. A point cloud classification network that utilizes multi-layer feature fusion and point cloud projection images is… Read full abstract & cite →

Point cloud classification graph convolution attention mechanism CLIP

Abstract doi.org/10.14569/IJACSA.2023.0140625 PDF

26

Early Detection of Autism Spectrum Disorder (ASD) using Traditional Machine Learning Models

Author 1: Prasenjit Mukherjee Author 2: Sourav Sadhukhan Author 3: Manish Godse Author 4: Baisakhi Chakraborty

Autism Spectrum Disorder (ASD) is a mental disorder among children that is difficult to diagnose at an early age of a child. People with ASD have difficulty functioning in areas such as communication, social interaction, motor skills, and emotional regulation. They may also have difficulty processing sensory information and have… Read full abstract & cite →

Support vector logistic regression cosine similarity K-nearest neighbor random forest

Abstract doi.org/10.14569/IJACSA.2023.0140626 PDF

27

Speaker Recognition Improvement for Degraded Human Voice using Modified-MFCC with GMM

Author 1: Amit Moondra Author 2: Poonam Chahal

Speaker’s audio is one of the unique identities of the speaker. Nowadays not only humans but machines can also identify humans by their audio. Machines identify different audio properties of the human voice and classify speaker from speaker’s audio. Speaker recognition is still challenging with degraded human voice and limited… Read full abstract & cite →

GMM artificial intelligence MFCC fundamental frequency melspectrum speaker recognition

Abstract doi.org/10.14569/IJACSA.2023.0140627 PDF

28

Application of Conv-1D and Bi-LSTM to Classify and Detect Epilepsy in EEG Data

Author 1: Chetana R Author 2: A Shubha Rao Author 3: Mahantesh K

EEG is used to study the electrical changes in the brain and can derive a conclusion as epileptic or not, using an automated method for accurate detection of seizures. Deep learning, a technique ahead of machine learning tools, can self-discover related data for the detection and classification of EEG analysis… Read full abstract & cite →

1D CNN bidirectional LSTM dataset (DS) deep learning electroencephalogram (EEG) LSTM

Abstract doi.org/10.14569/IJACSA.2023.0140628 PDF

29

A New Fuzzy Lexicon Expansion and Sentiment Aware Recommendation System in e-Commerce

Author 1: Manikandan. B Author 2: Rama. P Author 3: Chakaravarthi. S

Customers’ feedbacks are necessary for an online business to enrich themselves. The customers’ feedback reflects the quality of the products and the e-commerce services. The companies are in a position to concentrate more and analyze the customers’ feedback or reviews carefully by applying new techniques for predicting the current trends… Read full abstract & cite →

Classification e-commerce preprocessing recommendation system recurrent neural network sentiment analysis

Abstract doi.org/10.14569/IJACSA.2023.0140629 PDF

30

Information Technology Technical Support Success Factors in Higher Education: Principal Component Analysis

Author 1: Geeta Pursan Author 2: Timothy. T. Adeliyi Author 3: Seena Joseph

The use of information and communication technologies at higher education institutions is no longer an option, but rather a need. Information Technology support is an essential factor that entails giving end users assistance with hardware and software components. Technical support for information technology has been recognized as a crucial element… Read full abstract & cite →

Information technology technical support services key success factors principal component analysis higher education institutions

Abstract doi.org/10.14569/IJACSA.2023.0140630 PDF

31

Effect of Distance and Direction on Distress Keyword Recognition using Ensembled Bagged Trees with a Ceiling-Mounted Omnidirectional Microphone

Author 1: Nadhirah Johari Author 2: Mazlina Mamat Author 3: Yew Hoe Tung Author 4: Aroland Kiring

Audio surveillance can provide an effective alternative to video surveillance in situations where the latter is impractical. Nevertheless, it is essential to note that audio recording raises privacy and legal concerns that require unambiguous consent from all parties involved. By utilizing keyword recognition, audio recordings can be filtered, allowing for… Read full abstract & cite →

Distress speech ensemble bagged trees audio surveillance machine learning distance directions

Abstract doi.org/10.14569/IJACSA.2023.0140631 PDF

32

A Feature-based Transfer Learning to Improve the Image Classification with Support Vector Machine

Author 1: Nina Sevani Author 2: Kurniawati Azizah Author 3: Wisnu Jatmiko

In the big data era there are some issues regarding real-world classification problems. Some of the important challenges that still need to be overcome to produce an accurate classification model are the data imbalance, difficulties in labeling process, and differences on data distribution. Most classification problems are related to the… Read full abstract & cite →

Feature-transfer learning image feature selection weight distance

Abstract doi.org/10.14569/IJACSA.2023.0140632 PDF

33

Distributed Training of Deep Autoencoder for Network Intrusion Detection

Author 1: Haripriya C Author 2: Prabhudev Jagadeesh M. P

The amount of data being exchanged over the internet is enormous. Attackers are finding novel ways to evade rules, investigate network defenses, and launch successful attacks. Intrusion detection is one of the effective means to counter attacks. As the network traffic continues to grow, it can be challenging for network… Read full abstract & cite →

Network intrusion detection systems deep learning autoencoders cloud computing distributed training parallel computing

Abstract doi.org/10.14569/IJACSA.2023.0140633 PDF

34

An Arabic Intelligent Diagnosis Assistant for Psychologists using Deep Learning

Author 1: Asmaa Alayed Author 2: Manar Alrabie Author 3: Sarah Aldumaiji Author 4: Ghaida Allhyani Author 5: Sahar Siyam Author 6: Reem Qaid

Mental illnesses have increased in recent years, especially after Covid-19 pandemic. In Saudi Arabia, the number of psychiatric clinics is small compared to the population density. As a result, psychologists encounter a variety of difficulties at work. The main goal of the current research is to develop a system that… Read full abstract & cite →

Mental health psychologist mental illness diagnosis psychological test deep learning CNN algorithm

Abstract doi.org/10.14569/IJACSA.2023.0140634 PDF

35

The Evaluation of a Persuasive Learning Tool using Think-Aloud Protocol

Author 1: Muhammad Aqil Abd Rahman Author 2: Mohamad Hidir Mhd Salim Author 3: Nazlena Mohamad Ali

e-Learning has become a platform for students to gain and expand their knowledge through mobile applications or web-based systems. Even though e-learning systems usually aim to facilitate students' understanding of the subject, some fail to convey the underlying learning outcomes. These circumstances emerge as most e-learning methods or tools fail… Read full abstract & cite →

Learning technology persuasive technology persuasive learning persuasive design

Abstract doi.org/10.14569/IJACSA.2023.0140635 PDF

36

Real-Time Intrusion Detection of Insider Threats in Industrial Control System Workstations Through File Integrity Monitoring

Author 1: Bakil Al-Muntaser Author 2: Mohamad Afendee Mohamed Author 3: Ammar Yaseen Tuama

Industrial control systems (ICS) play a crucial role in various industries and ensuring their security is paramount for maintaining process continuity and reliability. In ICS, the most damaging cyber-attacks often come from trusted insiders rather than external threats or malware. Insiders have the advantage of bypassing security measures and staying… Read full abstract & cite →

Industrial control system insider threats intrusion detection file integrity monitoring SCADA security

Abstract doi.org/10.14569/IJACSA.2023.0140636 PDF

37

Clustering Based on Gray Wolf Optimization Algorithm for Internet of Things over Wireless Nodes

Author 1: Chunfen HU Author 2: Haifei ZHOU Author 3: Shiyun LV

The Internet of Things (IoT) creates an environment where things are permitted to act, hear, listen, and talk. IoT devices encompass a wide range of objects, from basic sensors to intelligent devices, capable of exchanging information with or without human intervention. However, the integration of wireless nodes in IoT systems… Read full abstract & cite →

Internet of things energy consumption clustering optimization gray wolf optimization

Abstract doi.org/10.14569/IJACSA.2023.0140637 PDF

38

Intelligent Moroccan License Plate Recognition System Based on YOLOv5 Build with Customized Dataset

Author 1: El Mehdi Ben Laoula Author 2: Marouane Midaoui Author 3: Mohamed Youssfi Author 4: Omar Bouattane

The rising number of automobiles has led to an increased demand for a reliable license plate identification system that can perform effectively in diverse conditions. This applies to local authorities, public organizations, and private companies in Morocco, as well as worldwide. To meet this need, a strong License Plate Recognition… Read full abstract & cite →

License plate recognition YOLOv5 intelligent region segmentation customized dataset Moroccan license plate issues fonts-based data

Abstract doi.org/10.14569/IJACSA.2023.0140638 PDF

39

Deep Learning for Personal Activity Recognition Under More Complex and Different Placement Positions of Smart Phone

Author 1: Bhagya Rekha Sangisetti Author 2: Suresh Pabboju

Personal Activity Recognition (PAR) is an indispensable research area as it is widely used in applications such as security, healthcare, gaming, surveillance and remote patient monitoring. With sensors introduced in smart phones, data collection for PAR made easy. However, PAR is non-trivial and difficult task due to bulk of data… Read full abstract & cite →

Human activity recognition deep learning CNN MHealth dataset artificial intelligence

Abstract doi.org/10.14569/IJACSA.2023.0140639 PDF

40

A Review on Security Techniques in Image Steganography

Author 1: Sami Ghoul Author 2: Rossilawati Sulaiman Author 3: Zarina Shukur

Given the increased popularity of the internet, the exchange of sensitive information leads to concerns about privacy and security. Techniques such as steganography and cryptography have been employed to protect sensitive information. Steganography is one of the promising tools for securely exchanging sensitive information through an unsecured medium. It is… Read full abstract & cite →

Image steganography data hiding steganographic security randomization encryption

Abstract doi.org/10.14569/IJACSA.2023.0140640 PDF

41

Automated Type Identification and Size Measurement for Low-Voltage Metering Box Based on RGB-Depth Image

Author 1: Pengyuan Liu Author 2: Xurong Jin Author 3: Shaokui Yan Author 4: Tingting Hu Author 5: Yuanfeng Zhou Author 6: Ling He Author 7: Xiaomei Yang

The low-voltage metering box is a critical piece of equipment in the power supply system. The automated inspection of metering boxes is important in their production, transportation, installation, operation and maintenance. In this work, an automated type identification and size measurement method for low-voltage metering boxes based on RGB-D images… Read full abstract & cite →

Low-voltage metering box RGB-D image processing automated size detection automated type detection inspection automation

Abstract doi.org/10.14569/IJACSA.2023.0140641 PDF

42

Data-driven Decision Making in Higher Education Institutions: State-of-play

Author 1: Silvia Gaftandzhieva Author 2: Sadiq Hussain Author 3: Slavoljub Hilcenko Author 4: Rositsa Doneva Author 5: Kirina Boykova

The paper highlights the importance of using data-driven decision-making tools in Higher Education Institutions (HEIs) to improve academic performance and support sustainable development. HEIs must utilize data analytics tools, including educational data mining, learning analytics, and business intelligence, to extract insights and knowledge from educational data. These tools can help… Read full abstract & cite →

Business intelligence data analytics tools decision-making framework decision-making support systems

Abstract doi.org/10.14569/IJACSA.2023.0140642 PDF

43

Semi-Dense U-Net: A Novel U-Net Architecture for Face Detection

Author 1: Ganesh Pai Author 2: Sharmila Kumari M

Face detection and localization has been a major field of study in facial analysis and computer vision. Several convolutional neural network-based architectures have been proposed in the literature such as cascaded approach, single-stage and two-stage architectures. Using image segmentation based technique for object/face detection and recognition have been an alternative… Read full abstract & cite →

Semi-Dense U-Net face detection segmentation U-Net

Abstract doi.org/10.14569/IJACSA.2023.0140643 PDF

44

End to End Text to Speech Synthesis for Malay Language using Tacotron and Tacotron 2

Author 1: Azrul Fahmi Abdul Aziz Author 2: Sabrina Tiun Author 3: Noraini Ruslan

Text-to-speech (TTS) technology is becoming increasingly popular in various fields such as education and business. However, the advancement of TTS technology for Malay language is slower compared to other language especially English language. The rise of artificial intelligence (AI) technology has sparked TTS technology into a new dimension. An end-to-end… Read full abstract & cite →

Text to speech end-to-end TTS Tacotron Tacotron 2 Malay language artificial intelligence mean opinion score (MOS) naturalness intelligibility

Abstract doi.org/10.14569/IJACSA.2023.0140644 PDF

45

A New Model for Blood Cancer Classification Based on Deep Learning Techniques

Author 1: Hagar Mohamed Author 2: Fahad Kamal Elsheref Author 3: Shrouk Reda Kamal

Artificial intelligence and deep learning algorithms have become essential fields in medical science. These algorithms help doctors detect diseases early, reduce the incidence of errors, and decrease the time required for disease diagnosis, thereby saving human lives. Deep learning models are widely used in Computer-Aided Diagnosis Systems (CAD) for the… Read full abstract & cite →

Deep learning convolutional neural networks (CNNs) leukemia lymphoma computer-aided diagnosis systems (CAD)

Abstract doi.org/10.14569/IJACSA.2023.0140645 PDF

46

Deep Feature Fusion Network for Lane Line Segmentation in Urban Traffic Scenes

Author 1: Hoanh Nguyen

As autonomous driving technology continues to advance at a rapid pace, the demand for precise and dependable lane detection systems has become increasingly critical. However, traditional methods often struggle with complex urban scenarios, such as crowded environments, diverse lighting conditions, unmarked lanes, curved lanes, and night-time driving. This paper presents… Read full abstract & cite →

Lane line segmentation deep learning convolutional neural network spatial and channel attention

Abstract doi.org/10.14569/IJACSA.2023.0140646 PDF

47

Enhancing Skin Diseases Classification Through Dual Ensemble Learning and Pre-trained CNNs

Author 1: Oussama El Gannour Author 2: Soufiane Hamida Author 3: Yasser Lamalem Author 4: Bouchaib Cherradi Author 5: Shawki Saleh Author 6: Abdelhadi Raihani

Skin diseases represent a variety of disorders that can affect the skin. In fact, early diagnosis plays a central role in the treatment of this type of disease. This scholarly article introduces a novel approach to classifying skin diseases by leveraging two ensemble learning techniques, encompassing multi-modal and multi-task methodologies… Read full abstract & cite →

Multi-modal approach multi-task approach transfer learning deep learning skin diseases classification

Abstract doi.org/10.14569/IJACSA.2023.0140647 PDF

48

Auto-Regressive Integrated Moving Average Threshold Influence Techniques for Stock Data Analysis

Author 1: Bhupinder Singh Author 2: Santosh Kumar Henge Author 3: Sanjeev Kumar Mandal Author 4: Manoj Kumar Yadav Author 5: Poonam Tomar Yadav Author 6: Aditya Upadhyay Author 7: Srinivasan Iyer Author 8: Rajkumar A Gupta

This study focuses on predicting and estimating possible stock assets in a favorable real-time scenario for financial markets without the involvement of outside brokers about broadcast-based trading using various performance factors and data metrics. Sample data from the Y-finance sector was assembled using API-based data series and was quite accurate… Read full abstract & cite →

Dickey-Fuller test case (DF-TC) recurrent neural network (RNN) root mean square error (RMSE) long short-term memory (LSTM) machine learning (ML) auto-regressive integrated moving average (ARIMA)

Abstract doi.org/10.14569/IJACSA.2023.0140648 PDF

49

Evaluations on Competitiveness of Service Sector in Yangtze River Economic Belt of China Based on Dual-core Diamond Model

Author 1: Ming Zhao Author 2: Qingjun Zeng Author 3: Dan Wang Author 4: Jiafu Su

By expanding and innovating Michael Porter Diamond Model, a Dual-core Diamond Model is developed in this paper with innovation and openness as the core factors in consideration of the actual needs of the development of service sector in the Yangtze River Economic Belt of China. This paper establishes an evaluation… Read full abstract & cite →

Dual-core diamond model service sector Yangtze river economic belt principal component

Abstract doi.org/10.14569/IJACSA.2023.0140649 PDF

50

Enhancing COVID-19 Diagnosis Through a Hybrid CNN and Gray Wolf Optimizer Framework

Author 1: Yechun JIN Author 2: Guanxiong ZHANG Author 3: Jie LI

Covid-19 is an infectious respiratory disorder brought about using a brand-new coronavirus first found in 2019. The severity of symptoms can vary from mild to life-threatening. No vaccine or specific treatment has been developed to address Covid-19. Hence the most effective preventive measure is to practice social distancing and adhere… Read full abstract & cite →

Covid-19 respiratory disorder medical imaging convolutional neural networks improved gray wolf algorithm

Abstract doi.org/10.14569/IJACSA.2023.0140650 PDF

51

Automated Epileptic Seizure Detection using Improved Crystal Structure Algorithm with Stacked Autoencoder

Author 1: Srikanth Cherukuvada Author 2: R. Kayalvizhi

Epilepsy can be referred to as a neurological disorder, categorized by intractable seizures with serious consequences. To forecast such seizures, Electroencephalogram (EEG) datasets should be gathered continuously. EEG signals were recorded by using numerous electrodes fixed on the scalp that cannot be worn by patients continuously. Neurostimulators can intervene in… Read full abstract & cite →

Deep learning EEG signals epileptic seizure detection hyperparameter tuning stacked autoencoders

Abstract doi.org/10.14569/IJACSA.2023.0140651 PDF

52

Evaluation of the Effects of 2D Animation on Business Law: Elements of a Valid Contract

Author 1: Sarni Suhaila Rahim Author 2: Nur Zulaiha Fadlan Faizal Author 3: Shahril Parumo Author 4: Hazira Saleh

This article presents an evaluation of Business Law 2D Animation: Elements of a Valid Contract. The developed application was produced to assist business law students to understand the contents of the topic Elements of a Valid Contract. An experiment was carried out to assess the usability of the application as… Read full abstract & cite →

2D Animation business law elements of a valid contract evaluation

Abstract doi.org/10.14569/IJACSA.2023.0140652 PDF

53

A Novel Approach to Multi-Layer-Perceptron Training using Quadratic Interpolation Flower Pollination Neural Network on Non-Binary Datasets

Author 1: Yulianto Triwahyuadi Polly Author 2: Sri Hartati Author 3: Suprapto Author 4: Bambang Sumiarto

Machine Learning (ML) algorithms are widely used in solving classification problems. The biggest challenge of classification lies in the robustness of the ML algorithm in various dataset characteristics. Quadratic Interpolation Flower Pollination Neural Network (QIFPNN) is categorised into ML algorithm. The new QIFPNN's extraordinary capabilities are measured on binary-type datasets… Read full abstract & cite →

Quadratic interpolation flower pollination algorithm neural network non-binary dataset multi-layer-perceptron

Abstract doi.org/10.14569/IJACSA.2023.0140653 PDF

54

Hamming Distance Approach to Reduce Role Mining Scalability

Author 1: Nazirah Abd Hamid Author 2: Siti Rahayu Selamat Author 3: Rabiah Ahmad Author 4: Mumtazimah Mohamad

Role-based Access Control has become the standard of practice for many organizations for restricting control on limited resources in complicated infrastructures or systems. The main objective of the role mining development is to define appropriate roles that can be applied to the specified security access policies. However, the mining scales… Read full abstract & cite →

Role-based Access Control role mining hamming distance data mining

Abstract doi.org/10.14569/IJACSA.2023.0140654 PDF

55

Towards Path Planning Algorithm Combining with A-Star Algorithm and Dynamic Window Approach Algorithm

Author 1: Kaiyu Li Author 2: Xiugang Gong Author 3: Muhammad Tahir Author 4: Tao Wang Author 5: Rajesh Kumar

In the Automated Guided Vehicle (AGV) warehouse automatic guided vehicle system, the path planning algorithm for intelligent logistics vehicles is a key factor to ensure the stable and efficient operation of the system. However, the existing planning algorithms have problems such as single designing a route and the inability to… Read full abstract & cite →

AGV path planning A* algorithm dynamic window approach

Abstract doi.org/10.14569/IJACSA.2023.0140655 PDF

56

Advances in Machine Learning and Explainable Artificial Intelligence for Depression Prediction

Author 1: Haewon Byeon

There is a growing interest in applying AI technology in the field of mental health, particularly as an alternative to complement the limitations of human analysis, judgment, and accessibility in mental health assessments and treatments. The current mental health treatment service faces a gap in which individuals who need help… Read full abstract & cite →

Depression LIME Explainable artificial intelligence Machine learning SHAP

Abstract doi.org/10.14569/IJACSA.2023.0140656 PDF

57

State of-the-Art Analysis of Multiple Object Detection Techniques using Deep Learning

Author 1: Kanhaiya Sharma Author 2: Sandeep Singh Rawat Author 3: Deepak Parashar Author 4: Shivam Sharma

Object detection has experienced a surge in interest due to its relevance in video analysis and image interpretation. Traditional object detection approaches relied on handcrafted features and shallow trainable algorithms, which limited their performance. However, the advancement of Deep learning (DL) has provided more powerful tools that can extract semantic… Read full abstract & cite →

Deep learning neural networks object detection YOLO

Abstract doi.org/10.14569/IJACSA.2023.0140657 PDF

58

Enhancing IoT Security with Deep Stack Encoder using Various Optimizers for Botnet Attack Prediction

Author 1: Archana Kalidindi Author 2: Mahesh Babu Arrama

The Internet of Things (IoT) connects different sensors, devices, applications, databases, services, and people, bringing improvements to various aspects of our lives, such as cities, agriculture, finance, and healthcare. However, guaranteeing the safety and confidentiality of IoT data which has become rich in its quality requires careful preparation and awareness… Read full abstract & cite →

Internet of things botnet attacks neural network methods N-BaIoT deep stack encoder Adam optimizer Adagrad optimizer Adadelta optimizer activation function

Abstract doi.org/10.14569/IJACSA.2023.0140658 PDF

59

Behavior Intention of Chronic Illness Patients in Malaysia to Use IoT-based Healthcare Services

Author 1: Huda Hussein Mohamad Jawad Author 2: Zainuddin Bin Hassan Author 3: Bilal Bahaa Zaidan

The Internet of Things (IoT) has emerged as a trend in the healthcare industry to develop innovative solutions that enhance patient outcomes and operational efficiency. Healthcare has become more accessible, affordable, and efficient to sensors, wearables, and health monitors. The healthcare industry's adoption of the Internet of Things is lagging… Read full abstract & cite →

Internet of things IoT chronic disease adoption theories adoption

Abstract doi.org/10.14569/IJACSA.2023.0140659 PDF

60

Dynamic Difficulty Adjustment of Serious-Game Based on Synthetic Fog using Activity Theory Model

Author 1: Fresy Nugroho Author 2: Puspa Miladin Nuraida Safitri Abdul Basid Author 3: Firma Sahrul Bahtiar Author 4: I. G. P. Asto Buditjahjanto

This study used the activity theory model to determine the dynamic difficulty adjustment of serious-game based on synthetic fog. The difference in difficulty levels was generated in a 3-dimensional game environment with changes determined by applying varying fog thickness. The activity theory model in serious-games aims to facilitate development analysis… Read full abstract & cite →

Dynamic difficulty adjustment serious-game activity theory model synthetic fog synthetic player

Abstract doi.org/10.14569/IJACSA.2023.0140660 PDF

61

Detection of Breast Cancer using Convolutional Neural Networks with Learning Transfer Mechanisms

Author 1: Victor Guevara-Ponce Author 2: Ofelia Roque-Paredes Author 3: Carlos Zerga-Morales Author 4: Andrea Flores-Huerta Author 5: Mario Aymerich-Lau Author 6: Orlando Iparraguirre-Villanueva

Breast cancer is the leading cause of mortality in women worldwide. One of the biggest challenges for physicians and technological support systems is early detection, because it is easier to treat and establish curative treatments. Currently, assistive technology systems use images to detect patterns of behavior with respect to patients… Read full abstract & cite →

Convolutional neural networks transfer learning deep learning classification breast cancer

Abstract doi.org/10.14569/IJACSA.2023.0140661 PDF

62

Zero-Watermarking for Medical Images Based on Regions of Interest Detection using K-Means Clustering and Discrete Fourier Transform

Author 1: Rodrigo Eduardo Arevalo-Ancona Author 2: Manuel Cedillo-Hernandez

Watermarking schemes ensure digital image security and copyright protection to prevent unauthorized distribution. Zero-watermarking methods do not modify the image. This characteristic is a requirement in some tasks that need image integrity, such as medical images. Zero-watermarking methods obtain specific features for the master share construction to protect the digital… Read full abstract & cite →

Zero-watermark ROI detection machine learning k-means image security copyright protection

Abstract doi.org/10.14569/IJACSA.2023.0140662 PDF

63

Kalman Filter-based Signal Processing for Robot Target Tracking

Author 1: Baofu Gong

In the field of computer vision, the signal tracking of moving objects is a highly representative problem. Therefore, how to accurately and quickly track the target unit has become the focus of the research. Based on this, a Cam Shift algorithm improved by Kalman filtering algorithm is introduced to realize… Read full abstract & cite →

Motion target tracking Kalman filter CamShift algorithm occlusion processing

Abstract doi.org/10.14569/IJACSA.2023.0140663 PDF

64

Vehicle Path Planning Based on Gradient Statistical Mutation Quantum Genetic Algorithm

Author 1: Hui Li Author 2: Huiping Qin Author 3: Zi’ao Han Author 4: Kai Lu

In the field of vehicle path planning, traditional intelligent optimization algorithms have the disadvantages of slow convergence, poor stability and a tendency to fall into local extremes. Therefore, a gradient statistical mutation quantum genetic algorithm (GSM-QGA) is proposed. Based on the dynamic rotation angle adjustment by the chromosome fitness value… Read full abstract & cite →

Quantum genetic algorithm path planning gradient descent adaptive mutation operator quantum rotation gate

Abstract doi.org/10.14569/IJACSA.2023.0140664 PDF

65

Apache Spark in Healthcare: Advancing Data-Driven Innovations and Better Patient Care

Author 1: Lalit Shrotriya Author 2: Kanhaiya Sharma Author 3: Deepak Parashar Author 4: Kushagra Mishra Author 5: Sandeep Singh Rawat Author 6: Harsh Pagare

The enormous amounts of data produced in the healthcare sector are managed and analyzed with the help of Apache Spark, an open-source distributed computing system. This case study examines how Spark is utilized in the healthcare industry to produce data-driven innovations and enhance patient care. The report gives a general… Read full abstract & cite →

Apache spark healthcare patient styling predictive analysis

Abstract doi.org/10.14569/IJACSA.2023.0140665 PDF

66

Weight Optimization Based on Firefly Algorithm for Analogy-based Effort Estimation

Author 1: Ayman Jalal AlMutlaq Author 2: Dayang N. A. Jawawi Author 3: Adila Firdaus Binti Arbain

Proper cost estimation is one of the vital tasks that must be achieved for software project development. Owing to the complexity and uncertainties of the software development process, this task is ambiguous and difficult. Recently, analogy-based estimation (ABE) has become one of the popular approaches in this field due to… Read full abstract & cite →

Analogy-based estimation firefly algorithm software cost estimation weight optimization

Abstract doi.org/10.14569/IJACSA.2023.0140666 PDF

67

Hierarchical and Efficient Identity-bsed Encryption Against Side Channel Attacks

Author 1: Qihong Yu Author 2: Jian Shen Author 3: Jiguo Li Author 4: Sai Ji

Hierarchical and identity-based encryption (HIBE) is very valuable and widely used in many occasions. In the Internet of Things based on cloud services, efficient HIBE is likely to be applied to cloud service scenarios for the limited computing ability of some terminal devices. What’s more, because of the insecurity of… Read full abstract & cite →

Identity-based encryption side channel attack hash proof system composite order group

Abstract doi.org/10.14569/IJACSA.2023.0140667 PDF

68

Image Specular Highlight Removal using Generative Adversarial Network and Enhanced Grey Wolf Optimization Technique

Author 1: Maddikera Krishna Reddy Author 2: J. C. Sekhar Author 3: Vuda Sreenivasa Rao Author 4: Mohammed Saleh Al Ansari Author 5: Yousef A.Baker El-Ebiary Author 6: Jarubula Ramu Author 7: R. Manikandan

Image highlight plays a major role in different interactive media and computer vision technology such as image fragmentation, recognition and matching. The original data will be unclear if the image contains highlights. Moreover, it may reduce the robustness in non-transparent as well as glassy objects and also it reduces accuracy… Read full abstract & cite →

Highlight detection optimization specular highlight detection GAN

Abstract doi.org/10.14569/IJACSA.2023.0140668 PDF

69

Developing a Security Policy for the Use of CCTV in the Northern Border University

Author 1: Ahmad Alshammari

The use of closed-circuit television (CCTV) in universities is a challenging task due to global strong opposition to its implementation at education institutions. The ministry of higher education of Kingdom of Saudi Arabia (KSA) has initiated a plan for monitoring educational institutes across the Kingdom. Therefore, this paper proposes a… Read full abstract & cite →

Closed circuit television security policy surveillance educational institutes

Abstract doi.org/10.14569/IJACSA.2023.0140669 PDF

70

Enhanced Gravitational Search Algorithm Based on Improved Convergence Strategy

Author 1: Norlina Mohd Sabri Author 2: Ummu Fatihah Mohd Bahrin Author 3: Mazidah Puteh

Gravitational search algorithm (GSA) is one of the metaheuristic algorithms that has been popularly implemented in solving various optimization problems. The algorithm could perform better in highly nonlinear and complex optimization problems. However, GSA has also been reported to have a weak local search ability and slow searching speed to… Read full abstract & cite →

Enhanced gravitational search algorithm variant improved convergence exploration exploitation

Abstract doi.org/10.14569/IJACSA.2023.0140670 PDF

71

Proposed Secure Activity Diagram for Software Development

Author 1: Madhuri N. Gedam Author 2: Bandu B. Meshram

Unified Modeling Language (UML) activity diagrams are derived from use case diagrams. It becomes essential to incorporate security features and maintain consistency in the diagrams during analysis phase of Software Development Life Cycle (SDLC). As part of current software development practices, software security must be a constant effort. The activity… Read full abstract & cite →

Unified modeling language activity diagram object constraint language SQL injection use case diagram

Abstract doi.org/10.14569/IJACSA.2023.0140671 PDF

72

An Efficient Vision-based Approach for Optimizing Energy Consumption in Internet of Things and Smart Homes

Author 1: LIU Chenguang

One of the primary forces for digital transformation is how quickly the world is changing. Additionally, and at a dizzying pace, the world economy is being transformed by digital technology. The billions of daily online connections between individuals, organizations, devices, data, and processes that generate economic activity are known as… Read full abstract & cite →

IoT Internet of things digital economics smart cities digitization machine vision YOLO YOLOv5n

Abstract doi.org/10.14569/IJACSA.2023.0140672 PDF

73

Application of Medical Brain CT/MRI Image Fusion Algorithm based on Neural Network

Author 1: Dan Yang

In recent years, fused images have been developed for fast processing of medical images, which provide a more reliable basis for reducing the burden on physicians because they can contain multiple times the image information. In order to achieve fast and accurate recognition results in medical image recognition, avoid similar… Read full abstract & cite →

Convolutional neural network image integration CT MRI

Abstract doi.org/10.14569/IJACSA.2023.0140673 PDF

74

Motion Path Planning of Wearable Lower Limb Exoskeleton Robot Based on Feature Description

Author 1: Ying Wang Author 2: Songyu Sui

Wearable lower extremity exoskeleton robot is a kind of training equipment designed for the disabled or powerless in the lower extremity. In order to improve the environmental adaptability of the robot and better meet the use habits of patients, it is necessary to plan and design the movement path, and… Read full abstract & cite →

Feature description wearable lower limb exoskeleton robot motion path planning least square identification geometric parameter

Abstract doi.org/10.14569/IJACSA.2023.0140674 PDF

75

Robust Analysis of IT Infrastructure's Log Data with BERT Language Model

Author 1: Deepali Arun Bhanage Author 2: Ambika Vishal Pawar

Now-a-days, failure detection and prediction have become a significant research focus on enhancing the reliability and availability of IT infrastructure components. Log analysis is an emerging domain aimed at diminishing downtime caused by IT infrastructure components' failure. However, it can be challenging due to poor log quality and large data… Read full abstract & cite →

System log log analysis BERT classification failure prediction failure detection

Abstract doi.org/10.14569/IJACSA.2023.0140675 PDF

76

Application of the Learning Set for the Detection of Jamming Attacks in 5G Mobile Networks

Author 1: Brou Médard KOUASSI Author 2: Vincent MONSAN Author 3: Abou Bakary BALLO Author 4: Kacoutchy Jean AYIKPA Author 5: Diarra MAMADOU Author 6: Kablan Jérome ADOU

Jamming attacks represent a significant problem in 5G mobile networks, requiring an effective detection mechanism to ensure network security. This study focused on finding effective methods for detecting these attacks using machine learning techniques. The effectiveness of Ensemble Learning and the XGBOOST-Ensemble Learning combination was evaluated by comparing their performance… Read full abstract & cite →

Jamming attacks 5G mobile networks ensemble learning XGBOOST-ensemble learning attack detection

Abstract doi.org/10.14569/IJACSA.2023.0140676 PDF

77

Hybrid Global Structure Model for Unraveling Influential Nodes in Complex Networks

Author 1: Mohd Fariduddin Mukhtar Author 2: Zuraida Abal Abas Author 3: Amir Hamzah Abdul Rasib Author 4: Siti Haryanti Hairol Anuar Author 5: Nurul Hafizah Mohd Zaki Author 6: Ahmad Fadzli Nizam Abdul Rahman Author 7: Zaheera Zainal Abidin Author 8: Abdul Samad Shibghatullah

In graph analytics, the identification of influential nodes in real-world networks plays a crucial role in understanding network dynamics and enabling various applications. However, traditional centrality metrics often fall short in capturing the interplay between local and global network information. To address this limitation, the Global Structure Model (GSM) and… Read full abstract & cite →

Centrality indices combination hybrid global structure model influential nodes

Abstract doi.org/10.14569/IJACSA.2023.0140677 PDF

78

Multi-Granularity Tooth Analysis via Faster Region-Convolutional Neural Networks for Effective Tooth Detection and Classification

Author 1: Samah AbuSalim Author 2: Nordin Zakaria Author 3: Salama A Mostafa Author 4: Yew Kwang Hooi Author 5: Norehan Mokhtar Author 6: Said Jadid Abdulkadir

In image classification, multi-granularity refers to the ability to classify images with different levels of detail or resolution. This is a challenging task because the distinction between subcategories is often minimal, needing a high level of visual detail and precise representation of the features specific to each class. In dental… Read full abstract & cite →

Dental informatics intra-oral image deep learning faster region-convolutional neural network classification granularity level tooth detection

Abstract doi.org/10.14569/IJACSA.2023.0140678 PDF

79

A Hybrid Approach for Underwater Image Enhancement using CNN and GAN

Author 1: Aparna Menon Author 2: R Aarthi

Underwater image-capturing technology has advanced over the years, and varieties of artificial intelligence-based applications have been developed on digital and synthetic images. The low-quality and low-resolution underwater images are challenging factors for use in existing image processing in computer vision applications. Degraded or low-quality photos are common issues in the… Read full abstract & cite →

Convolutional neural network (CNN) generative adversarial networks (GAN) enhancing underwater visual perception (EUVP) underwater images image enhancement computer vision artificial intelligence

Abstract doi.org/10.14569/IJACSA.2023.0140679 PDF

80

End-to-End Real-time Architecture for Fraud Detection in Online Digital Transactions

Author 1: ABBASSI Hanae Author 2: BERKAOUI Abdellah Author 3: ELMENDILI Saida Author 4: GAHI Youssef

The banking sector is witnessing a fierce concurrence characterized by changing business models, new entrants such as FinTechs, and new customer behaviors. Financial institutions try to adapt to this trend and invent new ways and channels to reach and interact with their customers. While banks are opening their services to… Read full abstract & cite →

Online fraud big data analytics fraud detection behavior analysis isolation forest

Abstract doi.org/10.14569/IJACSA.2023.0140680 PDF

81

Prediction of Anti-inflammatory Activity of Bio Copper Nanoparticle using an Innovative Soft Computing Methodology

Author 1: Dyuti Banerjee Author 2: G. Kiran Kumar Author 3: Farrukh Sobia Author 4: Subuhi Kashif Ansari Author 5: Anuradha. S Author 6: R. Manikandan

The objective of this work is to use a novel soft computing approach to predict the anti-inflammatory effect of bio copper nanoparticles. Using a modified technique, various doses of the Musa sapientum extract and copper nanoparticles were examined for their anti-inflammatory capabilities. Protein denaturation was evaluated, and an inhibition percentage… Read full abstract & cite →

Copper nanoparticles green synthesis prediction artificial neural network

Abstract doi.org/10.14569/IJACSA.2023.0140681 PDF

82

Automatic Essay Scoring for Arabic Short Answer Questions using Text Mining Techniques

Author 1: Maram Meccawy Author 2: Afnan Ali Bayazed Author 3: Bashayer Al-Abdullah Author 4: Hind Algamdi

Automated Essay Scoring (AES) systems involve using a specially designed computing program to mark students’ essays. It is a form of online assessment supported by natural language processing (NLP). These systems seek to exploit advanced technologies to reduce the time and effort spent on the exam scoring process. These systems… Read full abstract & cite →

Arabic language Automated Essay Scoring (AES) Automated Scoring (AS) Educational Technologies NLP

Abstract doi.org/10.14569/IJACSA.2023.0140682 PDF

83

Combination of Adaptive Neuro Fuzzy Inference System and Machine Learning Algorithm for Recognition of Human Facial Expressions

Author 1: B. Dhanalaxmi Author 2: B. Madhuravani Author 3: Yeligeti Raju Author 4: C. Balaswamy Author 5: A. Athiraja Author 6: G. Charles Babu Author 7: T. Samraj Lawrence

A face recognition system's initial three processes are face detection, feature extraction, and facial expression recognition. The initial step of face detection involves colour model skin colour detection, lighting adjustment to achieve uniformity on the face, and morphological techniques to maintain the necessary face region. To extract facial characteristics such… Read full abstract & cite →

ANFIS Image processing face recognition feature extraction fuzzy logic

Abstract doi.org/10.14569/IJACSA.2023.0140683 PDF

84

Comparative Analysis of DIDIM and IV Approaches using Double Least Squares Method

Author 1: Fadwa SAADA Author 2: David DELOUCHE Author 3: Karim CHABIR Author 4: Mohamed Naceur ABDELKRIM

Usually, identifying dynamic parameters for robots involves utilizing the Inverse Dynamic Model (IDM) which is linear in relation to the parameters being identified, alongside Linear Least Squares (LLS) methods. To implement this approach, precise measurements of both torque and position must be obtained at a high frequency. Additionally, velocities and… Read full abstract & cite →

Identification double least squares instrumental variable DIDIM method robotics dynamics

Abstract doi.org/10.14569/IJACSA.2023.0140684 PDF

85

Skin Cancer Classification using Delaunay Triangulation and Graph Convolutional Network

Author 1: Caroline Angelina Sunarya Author 2: Jocelyn Verna Siswanto Author 3: Grace Shirley Cam Author 4: Felix Indra Kurniadi

Oftentimes, many people or even medical workers misdiagnose skin cancer, which may lead to malpractice and thus, resulting in delayed recovery or life-threatening complications. In this research, a Graph Convolutional Network (GCN) method is proposed as a classification model and Delaunay triangulation as its feature extraction method to classify various… Read full abstract & cite →

Skin cancer Delaunay triangulation graph convolutional network GCN multilabel image classification convolutional neural network CNN

Abstract doi.org/10.14569/IJACSA.2023.0140685 PDF

86

Fertigation Technology Meets Online Market: A Multipurpose Mobile App for Urban Farming

Author 1: Jamil Abedalrahim Jamil Alsayaydeh Author 2: Mohd Faizal bin Yusof Author 3: Asyraf Salmi Author 4: Adam Wong Yoon Khang Author 5: Safarudin Gazali Herawan

In a world where smartphones dominate the market and provide opportunities to a vast population, this work introduces an innovative application that enables users to order irrigated vegetable crops from urban farmers. The application utilizes simple fertigation system technology, which can be easily implemented in small areas such as homes… Read full abstract & cite →

Vertical farming mobile application online market farm monitoring urban farmer agriculture supply chain

Abstract doi.org/10.14569/IJACSA.2023.0140686 PDF

87

Offensive Language Identification in Low Resource Languages using Bidirectional Long-Short-Term Memory Network

Author 1: Aigerim Toktarova Author 2: Aktore Abushakhma Author 3: Elvira Adylbekova Author 4: Ainur Manapova Author 5: Bolganay Kaldarova Author 6: Yerzhan Atayev Author 7: Bakhyt Kassenova Author 8: Ainash Aidarkhanova

Offensive language identification is a critical task in today's digital era, enabling the development of effective content moderation systems. However, it poses unique challenges in low resource languages where limited annotated data is available. This research paper focuses on addressing the problem of offensive language identification specifically in the context… Read full abstract & cite →

Offensive language natural language processing low resource language machine learning deep learning classification

Abstract doi.org/10.14569/IJACSA.2023.0140687 PDF

88

Query-Focused Multi-document Summarization Survey

Author 1: Entesar Alanzi Author 2: Safa Alballaa

With the exponential growth of textual information on the web and in multimedia, query-focused multi-document summarization (QFMS) has emerged as a critical research area. QFMS aims to generate concise summaries that address user queries and satisfy their information needs. This paper provides a comprehensive survey of state-of-the-art approaches in QFMS… Read full abstract & cite →

Text summarization query-based extractive text summarization multi-document graph-based approach clustering-based approach

Abstract doi.org/10.14569/IJACSA.2023.0140688 PDF

89

Ensuring Information Security of Web Resources Based on Blockchain Technologies

Author 1: Barakova Aliya Author 2: Ussatova Olga Author 3: Begimbayeva Yenlik Author 4: Ibrahim Sogukpinar

This project examines how blockchain technology can enhance data security and reliability for web applications. In this article, ways to improve data security on online course platforms that utilize blockchain technology are explored. To clarify, online course platforms are web-based applications that enable users to access course materials online. These… Read full abstract & cite →

Information security data security website protection blockchain network attacks hash functions web applications

Abstract doi.org/10.14569/IJACSA.2023.0140689 PDF

90

A Hybrid Multiple Indefinite Kernel Learning Framework for Disease Classification from Gene Expression Data

Author 1: Swetha S Author 2: Srinivasan G N Author 3: Dayananda P

In recent years, Machine Learning (ML) techniques have been used by several researchers to classify diseases using gene expression data. Disease categorization using heterogeneous gene expression data is often used for defining critical problems such as cancer analysis. A variety of evaluated factors known as genes are used to characterize… Read full abstract & cite →

Gene expression optimized kernel principle component analysis multiple indefinite kernel learning flow direction algorithm based support vector machine arithmetic optimization algorithm

Abstract doi.org/10.14569/IJACSA.2023.0140690 PDF

91

A 3D Processing Technique to Detect Lung Tumor

Author 1: Nabila ELLOUMI Author 2: Slim Ben CHAABANE Author 3: Hassan SEDDIK Author 4: TOUNSI Nadra

In this paper, the authors introduce a new segmentation technique based on U-NET algorithm from the deep learning used for lung cancer segmentation, which is the main challenge that medical Staff confront in their diagnosis process. The goal is to develop an ideal segmentation that enables medical personnel to distinguish… Read full abstract & cite →

Deep learning U-NET architecture 3D CT scan (computerized tomography) DICOM images (Digital Imaging and Communications in Medicine) 2D slices ROI (regions of interest)

Abstract doi.org/10.14569/IJACSA.2023.0140691 PDF

92

Prediction of Breast Cancer using Traditional and Ensemble Technique: A Machine Learning Approach

Author 1: Tamanna Islam Author 2: Amatul Bushra Akhi Author 3: Farzana Akter Author 4: Md. Najmul Hasan Author 5: Munira Akter Lata

Breast cancer is a prevalent and potentially life-threatening disease that affects millions of individuals worldwide. Early detection plays a crucial role in improving patient outcomes and increasing the chances of survival. In recent years, machine learning (ML) techniques have gained significant attention in the field of breast cancer detection and… Read full abstract & cite →

Breast cancer prediction machine learning algorithms ensemble models voting stacking

Abstract doi.org/10.14569/IJACSA.2023.0140692 PDF

93

Research on Settlement Prediction of Building Foundation in Smart City Based on BP Network

Author 1: Luyao Wei

In the construction process of high-rise buildings, it is necessary to predict the settlement and deformation of the foundation, and the current prediction methods are mainly based on empirical theoretical calculations and methods and more accurate numerical analysis methods. In the face of the interference of complex and ever-changing terrain… Read full abstract & cite →

Smart city intelligent architecture foundation settlement settlement prediction BP neural network parameter

Abstract doi.org/10.14569/IJACSA.2023.0140693 PDF

94

A Classified Warning Method for Heavy Overload in Distribution Networks Considering the Characteristics of Unbalanced Datasets

Author 1: Guohui Ren

In order to achieve heavy overload warning and capacity planning for the distribution network, it is necessary to classify the heavy overload warning of the distribution network. A distribution network with heavy overload classification warning method based on imbalanced dataset feature extraction is proposed. Screening the feature indicator set related… Read full abstract & cite →

Imbalanced data feature extraction distribution network overload classification warning

Abstract doi.org/10.14569/IJACSA.2023.0140694 PDF

95

A Novel Method for Myocardial Image Classification using Data Augmentation

Author 1: Qing kun Zhu

Myocarditis is an important public health concern since it can cause heart failure and abrupt death. It can be diagnosed with magnetic resonance imaging (MRI) of the heart, a non-invasive imaging technology with the potential for operator bias. The study provides a deep learning-based model for myocarditis detection using CMR… Read full abstract & cite →

Myocarditis generative adversarial network data augmentation differential evolution

Abstract doi.org/10.14569/IJACSA.2023.0140695 PDF

96

Design and Application of Online Courses under the Threshold of Smart Innovation Education

Author 1: Qin Wang Author 2: Anya Xiong Author 3: Huirong Zhu

With the rapid development of the Internet and the growing demand for education, a new online teaching mode, massive open online courses (MOOC), emerged in 2012. To address the problems of sparse data and poor recommendation effect in online course recommendation, this paper introduces deep learning into course recommendation and… Read full abstract & cite →

Massive open online courses (MOOC) deep learning collaborative neural network filtering model (FIONeu) course recommendation online learning recommendation system

Abstract doi.org/10.14569/IJACSA.2023.0140696 PDF

97

Object Detection-based Automatic Waste Segregation using Robotic Arm

Author 1: Azza Elsayed Ibrahim Author 2: Rasha Shoitan Author 3: Mona M. Moussa Author 4: Heba A. Elnemr Author 5: Young Im Cho Author 6: Mohamed S. Abdallah

Today's overpopulation and fast urbanization present a significant challenge for developing countries in the form of excessive garbage generation. Managing waste is essential in creating sustainable and habitable communities, but it remains an issue for developing countries. Finding an efficient smart waste management system is a challenge in current research… Read full abstract & cite →

Smart recycling inverse kinematics object detection 4 DOF robotic arm YOLOV6

Abstract doi.org/10.14569/IJACSA.2023.0140697 PDF

98

Diversity-based Test Case Prioritization Technique to Improve Faults Detection Rate

Author 1: Jamal Abdullahi Nuh Author 2: Tieng Wei Koh Author 3: Salmi Baharom Author 4: Mohd Hafeez Osman Author 5: Lawal Babangida Author 6: Sukumar Letchmunan Author 7: Si Na Kew

Regression testing is an important task in software development, but it is often associated with high costs and increased project expenses. To address this challenge, prioritizing test cases during test execution is essential as it aims to swiftly identify the hidden faults in the software. In the literature, several techniques… Read full abstract & cite →

Regression testing fault detection test case prioritization test case diversity test case coverage species diversity

Abstract doi.org/10.14569/IJACSA.2023.0140698 PDF

99

Exploring the Impact of Hybrid Recommender Systems on Personalized Mental Health Recommendations

Author 1: Idayati Mazlan Author 2: Noraswaliza Abdullah Author 3: Norashikin Ahmad

Personalized mental health recommendations are crucial in addressing the diverse needs and preferences of individuals seeking mental health support. This research aims to study the investigates the impact of hybrid recommender systems on the provision of personalized recommendations for mental health interventions. This paper explores the integration of various recommendation… Read full abstract & cite →

Recommender system mental health content-based filtering collaborative filtering hybrid recommender system

Abstract doi.org/10.14569/IJACSA.2023.0140699 PDF

100

Classification of Garlic Land Based on Growth Phase using Convolutional Neural Network

Author 1: Durrotul Mukhibah Author 2: Imas Sukaesih Sitanggang Author 3: Annisa

Indonesian Government needs to monitor the realization of garlic land with production plans in several production areas at growth season. A previous study, which used Sentinel-1A satellite imagery and Convolutional Neural Networks to classify garlic land, needed more information on growth phases. The study aims to address that limitation by… Read full abstract & cite →

Convolutional neural network garlic growth phase horticulture land classification Sentinel-2 VGG

Abstract doi.org/10.14569/IJACSA.2023.01406100 PDF

101

Evaluating Game Application Interfaces for Older Adults with Mild Cognitive Impairment

Author 1: Nita Rosa Damayanti Author 2: Nazlena Mohamad Ali

A digital game is software that is used as alternative entertainment for older adults for brain training. In this study, a digital game prototype for older adults with mild cognitive impairment has been developed called EmoGame and illustrated. The game is intended to assist older adults who experience emotional and… Read full abstract & cite →

System usability scale older adults mild cognitive impairment

Abstract doi.org/10.14569/IJACSA.2023.01406101 PDF

102

Intelligent Recommendation of Open Educational Resources: Building a Recommendation Model Based on Deep Neural Networks

Author 1: Zongkui Wang

Information overload is a challenge for the development of online education. To address the problem of intelligent recommendation of educational resources, the study proposes an intelligent recommendation model of educational resources based on deep neural networks. First, a deep neural network-based custom recommendation model for educational resources is constructed after… Read full abstract & cite →

Intelligent recommendation deep neural networks multilayer perceptron educational resources

Abstract doi.org/10.14569/IJACSA.2023.01406102 PDF

103

Role of Artificial Intelligence and Business Decision Making

Author 1: Anupama Prasanth Author 2: Densy John Vadakkan Author 3: Priyanka Surendran Author 4: Bindhya Thomas

Artificial Intelligence (AI) has emerged as a transformative technology with profound implications for various sectors, including business. In recent years, AI has revolutionized decision-making processes by providing organizations with advanced analytical capabilities, enabling them to extract valuable insights from vast amounts of data. The application of AI in businesses may… Read full abstract & cite →

Artificial intelligence business decision making efficiency accuracy innovation marketing strategy machine learning

Abstract doi.org/10.14569/IJACSA.2023.01406103 PDF

104

Unusual Human Behavior Detection System in Real-Time Video Systems

Author 1: Yanbin Bu Author 2: Ting Chen Author 3: Hongxiu Duan Author 4: Mei Liu Author 5: Yandan Xue

Abnormal behavior detection, in terms of importance, has become a necessity in real-time visual systems. The main problem is the ambiguity in the difference between the characteristics of abnormal and normal behavior, which its definition is usually different according to the previous context of images. In this research, three approaches… Read full abstract & cite →

Anomaly detection video sequence standard Convolutional Automatic Encoder (CAE) spatio-temporal structures LSTM

Abstract doi.org/10.14569/IJACSA.2023.01406104 PDF

105

A Comprehensive Study of DCNN Algorithms-based Transfer Learning for Human Eye Cataract Detection

Author 1: Omar Jilani Jidan Author 2: Susmoy Paul Author 3: Anirban Roy Author 4: Sharun Akter Khushbu Author 5: Mirajul Islam Author 6: S.M. Saiful Islam Badhon

This study presents a comparative analysis of different deep convolutional neural network (DCNN) architectures, including VGG19, NASNet, ResNet50, and MobileNetV2, with and without data augmentation, for the automatic detection of cataracts in fundus images. Utilizing hybrid architecture models, namely ResNet50-NASNet and ResNet50+MobileNetV2, which combine two state-of-the-art DCNNs, this research demonstrates… Read full abstract & cite →

Cataract detection eye disease ocular images deep convolutional neural network (DCNN) hybrid architecture

Abstract doi.org/10.14569/IJACSA.2023.01406105 PDF

106

System Dynamics Approach in Supporting The Achievement of The Sustainable Development on MSMEs: A Collection of Case Studies

Author 1: Julia Kurniasih Author 2: Zuraida Abal Abas Author 3: Siti Azirah Asmai Author 4: Agung Budhi Wibowo

Sustainable development in MSMEs is very important to encourage economic growth, improve the welfare of people, and ensure environmental sustainability. However, achieving sustainability in the MSME sector faces many challenges due to the complex interdependencies and dynamic interactions among various factors. The system dynamics approach makes it possible to model… Read full abstract & cite →

System dynamics sustainable development Micro Small and Medium Enterprises (MSMEs)

Abstract doi.org/10.14569/IJACSA.2023.01406106 PDF

107

A Precise Survey on Multi-agent in Medical Domains

Author 1: Arwa Alshehri Author 2: Fatimah Alshahrani Author 3: Habib Shah

Agent technology has provided many opportunities to improve the human standard of life in recent decades, starting from social life and moving on to business intelligence and tackling complicated communication, integration, and analysis challenges. These agents play an important role in human health from diagnosis to treatment. Every day, sophisticated… Read full abstract & cite →

Artificial intelligence agent systems multi-agent systems

Abstract doi.org/10.14569/IJACSA.2023.01406107 PDF

108

Technology Adoption and Usage Behaviors in Field Incident Management System Utilization

Author 1: Cory Antonio Buyan Author 2: Noelyn M. De Jesus Author 3: Eltimar T. Castro Jr

This study utilized the Unified Theory of Acceptance and Use of Technology (UTAUT) model to analyze the adoption and utilization of field incident management system (IMS) in a manufacturing organization. The study specifically focused on the role of behavior as a key factor in the adoption and utilization of incident… Read full abstract & cite →

UTAUT field incident management system (FIMS) regression analysis user intention and acceptance system adoption usage behavior manufacturing IMS effort expectancy performance expectancy social influence facilitating conditions behavioral intention ANOVA

Abstract doi.org/10.14569/IJACSA.2023.01406108 PDF

109

Damage Security Intelligent Identification of Wharf Concrete Structures under Deep Learning and Digital Image Technology

Author 1: Jinbo Zhu Author 2: Yuesong Li Author 3: Pengrui Zhu

Artificial Intelligence (AI) technology has quickly developed under the mighty computing power of computers. At this stage, there are many mature non-destructive testing methods in civil engineering, but they are generally only suitable for simple structures and evident damage characteristics. Therefore, it’s necessary for us to investigate the damage identification… Read full abstract & cite →

Structural damage identification deep learning neural network digital image concrete

Abstract doi.org/10.14569/IJACSA.2023.01406109 PDF

110

Application of Top-N Rule-based Optimal Recommendation System for Language Education Content based on Parallel Computing

Author 1: Nan Hu

In recent years personalized recommendation services have been applied to many areas of society, typically in the fields of e-commerce, short videos and so on. In response to the serious performance problems of the current online language education platform content recommendation, so in the face of the above opportunities and… Read full abstract & cite →

Data parallel computing cloud computing data crawlers top-N rules PRF algorithm

Abstract doi.org/10.14569/IJACSA.2023.01406110 PDF

111

A Novel ML Approach for Computing Missing Sift, Provean, and Mutassessor Scores in Tp53 Mutation Pathogenicity Prediction

Author 1: Rashmi Siddalingappa Author 2: Sekar Kanagaraj

Cancer is often caused by missense mutations, where a single nucleotide substitution leads to an amino acid change and affects protein function. This study proposes a novel machine learning (ML) approach to calculate missing values in the tp53 database for three computational methods: SIFT, Provean, and Mutassessor scores. The computed… Read full abstract & cite →

Decision tree (DT) deep neural networks (DNN) imputation k-nearest neighbor (KNN) logistic regression (LR) missense mutations Mutassessor pathogenicity Provean random forest (RF) SIFT support vector machine (SVM)

Abstract doi.org/10.14569/IJACSA.2023.01406111 PDF

112

An Empirical Deep Learning Approach for Arabic News Classification

Author 1: Roobaea Alroobaea

In this paper, we tackle the problem of Arabic news classification. A dataset of 5,000 news articles from various Saudi Arabian news sources were gathered, classified into six categories: business, entertainment, health, politics, sports, and technology. We conducted experiments using different pre-processing techniques, word embeddings, and deep learning architectures, including… Read full abstract & cite →

Deep learning (DL) machine-learning (ML) convolutional neural networks (CNNs) long short-term memory (LSTM)

Abstract doi.org/10.14569/IJACSA.2023.01406112 PDF

113

Application Methods of Image Design Based on Virtual Reality and Interaction

Author 1: Shasha Mao

The continuous improvement of virtual reality and interactive technology has led to a broader and deeper application in related fields, especially image design. In image design, creating usage scenarios for portable interactive experience products based on virtual reality and interactive technology can optimize and improve key parameters for real 3D… Read full abstract & cite →

Virtual reality interactive ANNs-DS information fusion algorithm image design

Abstract doi.org/10.14569/IJACSA.2023.01406113 PDF

114

Video Surveillance Vehicle Detection Method Incorporating Attention Mechanism and YOLOv5

Author 1: Yi Pan Author 2: Zhu Zhao Author 3: Yan Hu Author 4: Qing Wang

With the rising number of vehicle ownership nationwide and the consequent increase in traffic accidents, vehicle detection for traffic surveillance video is an effective method to reduce traffic accidents. However, existing video surveillance vehicle detection methods suffer from high computational load, low accuracy, and excessive reliance on large-scale computing servers… Read full abstract & cite →

Attention mechanism YOLOv5 vehicle detection image recognition deep learning

Abstract doi.org/10.14569/IJACSA.2023.01406114 PDF

115

Stroke Risk Prediction: Comparing Different Sampling Algorithms

Author 1: Qiuyang Yin Author 2: Xiaoyan Ye Author 3: Binhua Huang Author 4: Lei Qin Author 5: Xiaoying Ye Author 6: Jian Wang

Stroke is a serious disease that has a significant impact on the quality of life and safety of patients. Accurately predicting stroke risk is of great significance for preventing and treating stroke. In the past few years, machine learning methods have shown potential in predicting stroke risk. However, due to… Read full abstract & cite →

Stroke prediction data mining machine learning unbalanced data sampling algorithms classification algorithms

Abstract doi.org/10.14569/IJACSA.2023.01406115 PDF

116

Comparative Analysis using Various Performance Metrics in Imbalanced Data for Multi-class Text Classification

Author 1: Slamet Riyanto Author 2: Imas Sukaesih Sitanggang Author 3: Taufik Djatna Author 4: Tika Dewi Atikah

Precision, Recall, and F1-score are metrics that are often used to evaluate model performance. Precision and Recall are very important to consider when the data is balanced, but in the case of unbalanced data the F1-score is the most important metric. To find out the importance of these metrics, a… Read full abstract & cite →

Imbalanced data undersampling oversampling smote machine learning

Abstract doi.org/10.14569/IJACSA.2023.01406116 PDF

117

Multi-objective Task Scheduling Optimization Based on Improved Bat Algorithm in Cloud Computing Environment

Author 1: Dakun Yu Author 2: Zhongwei Xu Author 3: Meng Mei

In cloud computing environments, task completion time and virtual machine load balance are two critical issues that need to be addressed. To solve these problems, this paper proposes a Multi-objective Optimization Mutate Discrete Bat Algorithm (MOMDBA) that improves upon the traditional Bat algorithm (BA). The MOMDBA algorithm introduces a mutation… Read full abstract & cite →

Cloud computing task scheduling optimization bat algorithm meta-heuristics

Abstract doi.org/10.14569/IJACSA.2023.01406117 PDF

118

An Adaptive Testcase Recommendation System to Engage Students in Learning: A Practice Study in Fundamental Programming Courses

Author 1: Tien Vu-Van Author 2: Huy Tran Author 3: Thanh-Van Le Author 4: Hoang-Anh Pham Author 5: Nguyen Huynh-Tuong

This paper proposes a testcase recommendation system (TRS) to assist beginner-level learners in introductory programming courses with completing assignments on a learning management system (LMS). These learners often struggle to generate complex testcases and handle numerous code errors, leading to disengaging their attention from the study. The proposed TRS addresses… Read full abstract & cite →

Testcases recommendation system (TRS) learning management system (LMS) zone of proximal development (ZPD) singular value decomposition (SVD)

Abstract doi.org/10.14569/IJACSA.2023.01406118 PDF

119

Brain Tumor Semantic Segmentation using Residual U-Net++ Encoder-Decoder Architecture

Author 1: Mai Mokhtar Author 2: Hala Abdel-Galil Author 3: Ghada Khoriba

Image segmentation is considered one of the essential tasks for extracting useful information from an image. Given the brain tumor and its consumption of medical resources, the development of a deep learning method for MRI to segment the brain tumor of patients’ MRI is illustrated here. Brain tumor segmentation technique… Read full abstract & cite →

Brain tumor segmentation medical image segmentation BraTS U-Net U-Net++ residual network

Abstract doi.org/10.14569/IJACSA.2023.01406119 PDF

120

Multi-dimensional Data Aggregation Scheme Supporting Fault-Tolerant Mechanism in Smart Grid

Author 1: Yong Chen Author 2: Feng Wang Author 3: Li Xu Author 4: Zhongming Huang

With the large-scale deployment of smart grids, the scheme of smart grid data aggregation has gradually enriched in recent years. Based on the principle of protecting user privacy, existing schemes usually choose to introduce a trusted third party (TTP) to participate in the collaboration. However, this also increases the risk… Read full abstract & cite →

Cryptography fault tolerance privacy multi-dimensional data aggregation encryption smart grid

Abstract doi.org/10.14569/IJACSA.2023.01406120 PDF

121

SbChain+: An Enhanced Snowball-Chain Approach for Detecting Communities in Social Graphs

Author 1: Jayati Gulati Author 2: Muhammad Abulaish

In this paper, we present snowball-chain (SbChain+) approach, which is an improved version of SbChain community detection method in terms of precision with which communities are identified in a social graph. It exploits the topology of a social graph in terms of the connections of a node, i.e., its degree… Read full abstract & cite →

Clique clustering community detection graph mining snowball sampling social network analysis

Abstract doi.org/10.14569/IJACSA.2023.01406121 PDF

122

PaddyNet: An Improved Deep Convolutional Neural Network for Automated Disease Identification on Visual Paddy Leaf Images

Author 1: Petchiammal A Author 2: Murugan D Author 3: Briskline Kiruba S

Timely disease diagnosis in paddy is fundamental to preventing yield losses and ensuring an adequate supply of rice for a rapidly rising worldwide population. Recent advancements in deep learning have helped overcome the limitations of unsuper-vised learning methods. This paper proposes a novel PaddyNet model for enhanced accuracy in paddy… Read full abstract & cite →

Image annotation data augmentation deep learn-ing paddy leaf disease detection paddyNet

Abstract doi.org/10.14569/IJACSA.2023.01406122 PDF

123

Unmanned Aerial Vehicle-based Applications in Smart Farming: A Systematic Review

Author 1: El Mehdi Raouhi Author 2: Mohamed Lachgar Author 3: Hamid Hrimech Author 4: Ali Kartit

On one hand, the emergence of cutting-edge technologies like AI, Cloud Computing, and IoT holds immense potential in Smart Farming and Precision Agriculture. These technologies enable real-time data collection, including high-resolution crop imagery, using Unmanned Aerial Vehicles (UAVs). Leveraging these advancements can revolutionize agriculture by facilitating faster decision-making, cost reduction… Read full abstract & cite →

Artificial intelligence internet of things sensor big data cloud unmanned aerial vehicle smart farming

Abstract doi.org/10.14569/IJACSA.2023.01406123 PDF

124

Advanced Night time Object Detection in Driver-Assistance Systems using Thermal Vision and YOLOv5

Author 1: Hoang-Tu Vo Author 2: Luyl-Da Quach

Driver-assistance systems have become an indispensable component of modern vehicles, serving as a crucial element in enhancing safety for both drivers and passengers. Among the fundamental aspects of these systems, object detection stands out, posing significant challenges in low-light scenarios, particularly during nighttime. In this research paper, we propose an… Read full abstract & cite →

Driver-assistance systems object detection nighttime object detection thermal vision YOLOv5

Abstract doi.org/10.14569/IJACSA.2023.01406124 PDF

125

Hate Speech Detection in Bahasa Indonesia: Challenges and Opportunities

Author 1: Endang Wahyu Pamungkas Author 2: Divi Galih Prasetyo Putri Author 3: Azizah Fatmawati

This study aims to provide an overview of the current research on detecting abusive language in Indonesian social media. The study examines existing datasets, methods, and challenges and opportunities in this field. The research found that most existing datasets for detecting abusive language were collected from social media platforms such… Read full abstract & cite →

Abusive language hate speech detection machine learning social media

Abstract doi.org/10.14569/IJACSA.2023.01406125 PDF

126

MC-ABAC: An ABAC-based Model for Collaboration in Multi-Cloud Environment

Author 1: Mohamed Amine Madani Author 2: Abdelmounaim Kerkri Author 3: Mohammed Aissaoui

Collaborative systems allow a group of organizations to collaborate and complete shared tasks through distributed platforms. Organizations who collaborate often leverage cloud-based solutions to outsource their data and to benefit from the cloud capabilities. During such collaborations, tenants require access to and utilize resources held by other collaborating tenants, which… Read full abstract & cite →

ABAC model multi-tenant multi-cloud collaboration trust

Abstract doi.org/10.14569/IJACSA.2023.01406126 PDF

127

Type 2 Diabetes Mellitus: Early Detection using Machine Learning Classification

Author 1: Gowthami S Author 2: Venkata Siva Reddy Author 3: Mohammed Riyaz Ahmed

Type 2 Diabetes Mellitus (T2DM) is a growing global health problem that significantly impacts patient’s quality of life and longevity. Early detection of T2DM is crucial in preventing or delaying the onset of its associated complications. This study aims to evaluate the use of machine learning algorithms for the early… Read full abstract & cite →

Diabetes Mellitus Type II feature selection machine learning methods precision medicine

Abstract doi.org/10.14569/IJACSA.2023.01406127 PDF

128

A Novel Classification Approach for Grape Leaf Disease Detection Based on Different Attention Deep Learning Techniques

Author 1: S Phani Praveen Author 2: Rajeswari Nakka Author 3: Anuradha Chokka Author 4: Venkata Nagaraju Thatha Author 5: Sai Srinivas Vellela Author 6: Uddagiri Sirisha

Preventing and controlling grape diseases is essential for a good grape harvest. With the help of “single shot multi-box detectors”, “faster region based convolutional neural networks”, & “You only look once-X,” the study improved grape leaf disease detection accuracy with effective attention mechanisms, which includes convolutional block attention module, squeeze… Read full abstract & cite →

Grape leaves faster region-based convolutional neural networks you only look once (x) single shot detection attention techniques

Abstract doi.org/10.14569/IJACSA.2023.01406128 PDF

129

Predicting At-Risk Students’ Performance Based on LMS Activity using Deep Learning

Author 1: Amnah Al-Sulami Author 2: Miada Al-Masre Author 3: Norah Al-Malki

It is of great importance for Higher Education (HE) institutions to continuously work on detecting at-risk students based on their performance during their academic journey with the purpose of supporting their success and academic advancement. This is where Learning Analytics (LA) representing learners’ behaviour inside the Learning Management Systems (LMS)… Read full abstract & cite →

Predict at-risk student artificial neural network learning management system and educational data mining

Abstract doi.org/10.14569/IJACSA.2023.01406129 PDF

130

Parameter Identification of a Multilayer Perceptron Neural Network using an Optimized Salp Swarm Algorithm

Author 1: Mohamad Al-Laham Author 2: Salwani Abdullah Author 3: Mohammad Atwah Al-Ma’aitah Author 4: Mohammed Azmi Al-Betar Author 5: Sofian Kassaymeh Author 6: Ahmad Azzazi

Effort estimation in software development (SEE) is a crucial concern within the software engineering domain, as it directly impacts cost estimation, scheduling, staffing, planning, and resource allocation accuracy. In this scientific article, the authors aim to tackle this issue by integrating machine learning (ML) techniques with metaheuristic algorithms in order… Read full abstract & cite →

Software development effort estimation machine learning multilayer perceptron neural network salp swarm algorithm genetic algorithm

Abstract doi.org/10.14569/IJACSA.2023.01406130 PDF

131

A Novel Method for Diagnosing Alzheimer’s Disease from MRI Scans using the ResNet50 Feature Extractor and the SVM Classifier

Author 1: Farhana Islam Author 2: Md. Habibur Rahman Author 3: Nurjahan Author 4: Md. Selim Hossain Author 5: Samsuddin Ahmed

Alzheimer’s disease (AD), a chronic neurodegenerative brain disorder, caused by the accumulation of abnormal proteins called amyloid, is one of the prominent causes of mortality worldwide. Since there is a scarcity of experienced neurologists, manual diagnosis of AD is very time-consuming and error-prone. Hence, automatic diagnosis of AD draws significant… Read full abstract & cite →

Alzheimer’s disease brain images machine learning deep learning brain disorder ADNI dataset

Abstract doi.org/10.14569/IJACSA.2023.01406131 PDF

132

Uncertainty-Aware Traffic Prediction using Attention-based Deep Hybrid Network with Bayesian Inference

Author 1: Md. Moshiur Rahman Author 2: Abu Rafe Md Jamil Author 3: Naushin Nower

Traffic congestion has an adverse impact on the economy and quality of life and thus accurate traffic flow forecasting is critical for reducing congestion and enhancing transportation management. Recently, hybrid deep-learning approaches show promising contributions in prediction by handling various dynamic traffic features. Existing methods, however, frequently neglect the uncertainty… Read full abstract & cite →

Traffic flow prediction uncertainty deep learning Bayesian inference Dhaka city

Abstract doi.org/10.14569/IJACSA.2023.01406132 PDF

133

An Enhanced Variational AutoEncoder Approach for the Purpose of Deblurring Bangla License Plate Images

Author 1: Md. Siddiqure Rahman Tusher Author 2: Nakiba Nuren Rahman Author 3: Shabnaz Chowdhury Author 4: Anika Tabassum Author 5: Md. Akhtaruzzaman Adnan Author 6: Rashik Rahman Author 7: Shah Murtaza Rashid Al Masud

Automated License Plate Detection and Recognition (ALPDR) is a well-studied area of computer vision and a crucial activity in a variety of applications, including surveillance, law enforcement, and traffic management. Such a system plays a crucial role in the investigation of vehicle-related offensive activities. When an input image or video… Read full abstract & cite →

Image deblur bangla license plate deblur Variational AutoEncoder (VAE) computer vision

Abstract doi.org/10.14569/IJACSA.2023.01406133 PDF

134

Facial Image Generation from Bangla Textual Description using DCGAN and Bangla FastText

Author 1: Noor Mairukh Khan Arnob Author 2: Nakiba Nuren Rahman Author 3: Saiyara Mahmud Author 4: Md. Nahiyan Uddin Author 5: Rashik Rahman Author 6: Aloke Kumar Saha

The synthesis of facial images from textual descriptions is a relatively difficult subfield of text-to-image synthesis. It is applicable in various domains like Forensic Science, Game Development, Animation, Digital Marketing, and Metaverse. However, no work was found that generates facial images from textual descriptions in Bangla; the 5th most spoken… Read full abstract & cite →

Bangla Text-to-Face Synthesis Natural Language Processing(NLP) Computer Vision(CV) GAN Text encoders

Abstract doi.org/10.14569/IJACSA.2023.01406134 PDF

135

Microbial Biomarkers Identification for Human Gut Disease Prediction using Microbial Interaction Network Embedded Deep Learning

Author 1: Anushka Sivakumar Author 2: Syama K Author 3: J. Angel Arul Jothi

Human gut microorganisms are crucial in regulating the immune system. Disruption of the healthy relationship between the gut microbiota and gut epithelial cells leads to the development of diseases. Inflammatory Bowel Disease (IBD) and Colorectal Cancer (CRC) are gut-related disorders with complex pathophysiological mechanisms. With the massive availability of microbiome… Read full abstract & cite →

Biomarker discovery microbial interaction network graph embedding feature selection inflammatory bowel disease colorectal cancer

Abstract doi.org/10.14569/IJACSA.2023.01406135 PDF

136

Software Vulnerabilities’ Detection by Analysing Application Execution Traces

Author 1: Gouayon Koala Author 2: Didier Bassol´e Author 3: Telesphore Tiendrebeogo Author 4: Oumarou Si´e

Over the years, digital traces have proven to be significant for analyzing IT systems, including applications. With the persistent threats arising from the widespread proliferation of malware and the evasive techniques employed by cybercriminals, researchers and application vendors alike are concerned about finding effective solutions. In this article, we assess… Read full abstract & cite →

Execution traces events vulnerability detection malware applications

Abstract doi.org/10.14569/IJACSA.2023.01406136 PDF

137

Hybrid Encryption Algorithm for Information Security in Hadoop

Author 1: Youness Filaly Author 2: Fatna El mendili Author 3: Nisrine Berros Author 4: Younes El Bouzekri EL idrissi

Network security has gained importance in recent years. Information system security is greatly aided by the development of encryption as a solution. To safeguard the shared information, several strategies are required. Thanks to the cutting-edge Internet, networking corporations, health information, and cloud applications, our data is growing exponentially every minute… Read full abstract & cite →

Hadoop distributed file system (HDFS) big data security data encryption data decryption

Abstract doi.org/10.14569/IJACSA.2023.01406137 PDF

138

Review of Unsupervised Segmentation Techniques on Long Wave Infrared Images

Author 1: Mohammed Abuhussein Author 2: Aaron L. Robinson Author 3: Iyad Almadani

This paper studies the different unsupervised segmentation algorithms that have been proposed and their efficacy on thermal images. The scope of this research is to develop a generalized approach to blindly segment urban thermal imagery to assist the system in identifying regions by shape instead of pixel values. Most methods… Read full abstract & cite →

Unsupervised segmentation thermal images texture analysis pixel labeling Gabor GMM image analysis K-Means MRF Otsu’s DNN region-based clustering

Abstract doi.org/10.14569/IJACSA.2023.01406138 PDF

139

The Application of Intelligent Evaluation Method with Deep Learning in Calligraphy Teaching

Author 1: Yu Wang

Scientific and effective teaching quality evaluation (QE) is helpful to improve teaching mode and improve teaching quality. At present, calligraphy teaching (CT) QE methods are few in number and have poor evaluation effect. Aiming at these problems, deep learning (DL) is introduced to realize intelligent evaluation of CT quality. First… Read full abstract & cite →

Deep learning calligraphy teaching BPNN intelligent evaluation sparrow search algorithm

Abstract doi.org/10.14569/IJACSA.2023.01406139 PDF

140

Deep Learning-based Mobile Robot Target Object Localization and Pose Estimation Research

Author 1: Caixia He Author 2: Laiyun He

Two key technologies in robotic object grasping are target object localization and pose estimation (PE), respectively, and the addition of a robotic vision system can dramatically enhance the flexibility and accuracy of robotic object grasping. The study optimizes the classical convolutional structure in the target detection network considering the limited… Read full abstract & cite →

Mobile robot target object localization pose estimation YOLOv2 network FCN semantic segmentation network

Abstract doi.org/10.14569/IJACSA.2023.01406140 PDF

141

Character Representation and Application Analysis of English Language and Literature Based on Neural Network

Author 1: Yao Song

The development of computer technology has promoted the continuous progress of Natural language processing technology and the great development of ideology and culture, and also prompted literary workers to create a large number of literary works. This poses a new challenge to the application of Natural language processing technology. Text… Read full abstract & cite →

Neural network English literary image character vector similarity calculation

Abstract doi.org/10.14569/IJACSA.2023.01406141 PDF

142

NLPashto: NLP Toolkit for Low-resource Pashto Language

Author 1: Ijazul Haq Author 2: Weidong Qiu Author 3: Jie Guo Author 4: Peng Tang

In recent years, natural language processing (NLP) has transformed numerous domains, becoming a vital area of research. However, the focus of NLP studies has predomi-nantly centered on major languages like English, inadvertently neglecting low-resource languages like Pashto. Pashto, spoken by a population of over 50 million worldwide, remains largely unexplored… Read full abstract & cite →

NLP text processing word segmentation POS tagging BERT LLMs Pashto low-resource languages CRF CNNs RNNs

Abstract doi.org/10.14569/IJACSA.2023.01406142 PDF

143

Intelligent Traffic Video Retrieval Model based on Image Processing and Feature Extraction Algorithm

Author 1: Xiaoming Zhao Author 2: Xinxin Wang

Intelligent transportation is a system that combines data-driven information with traffic management to achieve intelligent monitoring and retrieval functions. In order to further improve the retrieval accuracy of the system model, a new retrieval model was designed. The functional requirements of the system were summarized, and the three stages of… Read full abstract & cite →

Matching extraction feature fusion image retrieval intelligent transportation

Abstract doi.org/10.14569/IJACSA.2023.01406143 PDF

144

The Mechanism of the Role of Big Data Knowledge Management in the Development of Enterprise Innovation

Author 1: Guangyu Yan Author 2: Rui Ma

The effectiveness and efficiency of enterprise knowledge management depends on the effectiveness and efficiency of the enterprise's implementation of knowledge management. Big data technology can collect, analyse and apply the massive amount of data in an organisation to support the implementation of knowledge management. Therefore, exploring the role of big-data… Read full abstract & cite →

Big data knowledge management BP neural network algorithm enterprise innovation development principal component analysis particle swarm optimization algorithm correlation analysis

Abstract doi.org/10.14569/IJACSA.2023.01406144 PDF

145

A Roadmap Towards Optimal Resource Allocation Approaches in the Internet of Things

Author 1: Jiyin Zhou

Introducing new technologies has facilitated people's lives more than ever. As one of these emerging technologies, the Internet of Things (IoT) enables objects we handle daily to interact with each other or humans and exchange information through the Internet by being equipped with sensors and communication technologies. IoT turns the… Read full abstract & cite →

Internet of things resource utilization resource allocation systematic review

Abstract doi.org/10.14569/IJACSA.2023.01406145 PDF

146

Social Media Mining to Detect Online Violent Extremism using Machine Learning Techniques

Author 1: Shynar Mussiraliyeva Author 2: Kalamkas Bagitova Author 3: Daniyar Sultan

In this paper, we explore the challenging domain of detecting online extremism in user-generated content on social media platforms, leveraging the power of Machine Learning (ML). We employ six distinct ML and present a comparative analysis of their performance. Recognizing the diverse and complex nature of social media content, we… Read full abstract & cite →

NLP machine learning social networks extremism detection textual contents

Abstract doi.org/10.14569/IJACSA.2023.01406146 PDF

147

Text Mining-based Enterprise Financial Performance Evaluation in the Context of Enterprise Digital Transformation

Author 1: Changrong Guo Author 2: Jing Xing

As enterprises gradually move towards digitalization, it is increasingly difficult to accurately evaluate changes in corporate financial performance. To improve this situation, the study uses a text mining algorithm based on the web crawler principle to extract keywords from corporate annual reports, select representative financial performance indicators through IF-FDP, and… Read full abstract & cite →

Web crawler text mining IF-FDP entropy method financial performance evaluation model

Abstract doi.org/10.14569/IJACSA.2023.01406147 PDF

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Study of the Drug-related Adverse Events with the Help of Electronic Health Records and Natural Language Processing

Author 1: Sarah Allabun Author 2: Ben Othman Soufiene

Surveillance of pharmacovigilance, also known as drug safety surveillance, involves the monitoring and evaluation of drug-related adverse events or side effects to ensure the safe and effective use of medications. Pharmacovigilance is an essential component of healthcare systems worldwide and plays a crucial role in identifying and managing drug safety… Read full abstract & cite →

Natural language processing surveillance of pharmacovigilance drug-related adverse

Abstract doi.org/10.14569/IJACSA.2023.01406148 PDF