Advances in Intelligent Computing Techniques and Applications

Name: Advances in Intelligent Computing Techniques and Applications | Intelligent Systems, Intelligent Health Informatics, Intelligent Big Data Analytics and Smart Computing, Volume 2
Brand: Springer
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Intelligent Systems, Intelligent Health Informatics, Intelligent Big Data Analytics and Smart Computing, Volume 2

Faisal Saeed Fathey Mohammed Yousef Fazea(Herausgeber*in)

Springer (Verlag)

1. Auflage

Erschienen am 10. Mai 2024

XIII, 320 Seiten

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Faisal Saeed is a Senior Lecturer at College of Computing and Digital Technology, Birmingham City University (BCU), UK. He is leading Smart Health Lab at Data Analytics and AI Research Group in BCU. Previously he worked as Assistant/Associate Professor at Taibah University, KSA from 2017-2021, and as Senior Lecturer at Faculty of Computing, Universiti Teknologi Malaysia (UTM), Malaysia from 2014-2017. Faisal received his BSc in Computers (Information Technology) from Cairo University, Egypt (2005), MSc in Information Technology Management and PhD in Computer Science from UTM in 2010 and 2013 respectively. He published several papers in indexed journals and international conferences. He served as general chair of ten international conferences and guest editor of several indexed Journals. His research interests are data science, artificial intelligence, machine learning, information retrieval and health informatic.

Fathey Mohammed is a Senior Lecturer at the Department of Business Analytics, Sunway University, Malaysia. With a dynamic academic journey, he obtained his B.Sc in Computer Engineering from the University of Isfahan, Iran in 2003, followed by an M.Sc in Information Technology from Tarbiat Modarres University, Tehran, Iran in 2005. In 2017, he completed his Ph.D in Information Systems at Universiti Teknologi Malaysia (UTM), Johor, Malaysia. His scholarly pursuits are deeply rooted in exploring the transformative power of technology innovation, particularly in realms such as cloud computing, social media, and blockchain applications. Dr. Mohammed's research extends beyond the technical realm, delving into the impacts of digital transformation on society, organizational dynamics, and individual behaviors. Dr. Mohammed's prolific contributions to academia are evident through his extensive publication record, comprising over 50 scientific papers. These works have found homes in prestigious journals and international conferences. Furthermore, his editorial expertise is demonstrated by his oversight of nine books published by Springer.

Yousef Fazea is an Assistant Professor at Marshall University's Department of Computer Sciences and Electrical Engineering. Holding a Ph.D. in Computer Science from the University Utara Malaysia, his academic prowess extends across various fronts. Dr. Fazea has authored over 60 peer-reviewed papers and serves as an editor for esteemed journals, including the Springer Lecture Notes on Data Engineering and Communications Technologies. His research, recognized with prestigious awards, focuses on next-gen computing, telecommunications, encryption, and network security. Actively engaged in professional societies like IEEE and ISOC, Dr. Fazea's contributions significantly enrich the landscape of computer science.

Inhalt

Intro
Preface
Organization
Contents
Software Bug Severity Prediction Using Convolutional Neural Network and BiLSTM Models
1 Introduction
2 Related Studies
3 Research Methodology
3.1 Data Set
3.2 Preprocessing of Summary Features
3.3 Word Tokenization
3.4 Stop Words Removal
3.5 Stemming
4 Proposed Models
4.1 Convolutional Neural Network (CNN)
4.2 A Bidirectional Long Short-Term Memory (BiLSTM)
5 Results and Discussion
6 Conclusion and Future Work
References
Facial Wash Products Recommendation System: Profile User-Based Using Fuzzy Analytical Hierarchy Process Approach
1 Introduction
2 Materials and Methods
3 Results
4 Recommendation System Design and Development
5 Conclusion
References
Securing Data in IoT-RFID-Based Systems Using Lightweight Cryptography Algorithm
1 Introduction
2 RFID Technology
2.1 RFID-Based System Components
3 RFID Security
3.1 Security Requirements for IoT-Based RFID System
4 Works Related to Securing RFID-Based Systems
5 The Proposed IoT-RFID Lightweight Security Framework(I-RFLSF)
5.1 Two-Level Registration Phase
5.2 Two-Level Authentication Phase
5.3 Secure Data Transmission Phase
6 Analysis
7 Conclusion
References
Employee Mental Workload Classification in Industrial Workplaces: A Machine Learning Approach
1 Introduction
2 Related Works
3 Research Methodology
3.1 Dataset Description
3.2 Data Preparation
3.3 Data Exploration
3.4 Modelling Using Supervised Machine Learning
3.5 Evaluation
4 Results and Analysis
5 Discussion and Conclusion
References
A Conceptual Framework for Malay-English Code-Switched Neural Machine Translation
1 Introduction
2 Literature Review
2.1 Code-Switching
2.2 Neural Machine Translation
2.3 Code-Switching in NMT: Challenges
3 Theoretical Framework
3.1 Data Preparation
3.2 Model Development
3.3 Performance Evaluation
4 Conclusion
References
Mobile Device Influence on SDN Controller Performance in IoT-Managed Software-Defined Wireless Networks
1 Introduction
2 Related Works
3 Methodology
3.1 Network Model
3.2 Analyses of SDN Controller Overhead
4 Performance Evaluation and Simulation Setup
4.1 Simulation Setup
4.2 Experimental Results and Discussion
5 Conclusion
References
Matrix Profile Unleashed: A Solution to IoT Data Redundancy Challenges
1 Introduction
2 Matrix Profile Overview
3 Methodology
4 Result and Discussion
5 Conclusion
References
Plants Monitoring API to Detect Tomato Leaf Diseases Using Deep-Learning Algorithms
1 Introduction
2 Related Works
3 CNN Model Development
3.1 Data Collection
3.2 Model Architecture Selection
3.3 Model Evaluation and Visualization
4 Deployment Strategy
5 Evaluation and Testing
6 Results Discussion
7 Limitations and Challenges
8 Conclusion
References
Sentiment Analysis and Innovative Recommender System: Enhancing Goodreads Book Discovery Using Hybrid Collaborative and Content Based Filtering
1 Introduction
2 Literature Review
2.1 Sentiment Analysis
2.2 Recommender Systems
3 Materials and Methods
3.1 Business Understanding
3.2 Data Understanding
3.3 Data Preparation
3.4 Sentiment Analysis Visualization
4 Modelling
5 Evaluation
6 Results and Analysis
7 Discussion
8 Conclusion
References
Comparative Analysis of Topic Modeling Algorithms Based on Arabic News Documents
1 Introduction
2 Related Work
3 Background
3.1 TF-IDF
3.2 Latent Semantic Indexing
3.3 Latent Dirichlet Allocation
3.4 Non-negative Matrix Factorization
3.5 BERTopic
4 Methodologies and Experiment
4.1 DataSet Description
4.2 Data Preprocessing
4.3 Comparative Analysis
5 Results and Discussion
6 Conclusion
References
Air Pollution Prediction Using Long Short-Term Memory Variants
1 Introduction
2 Related Works
3 Research Method
3.1 Data Collection
3.2 Data Preparation
3.3 Sliding Window
3.4 Hold-Out Validation
3.5 Long Short-Term Memory
3.6 Bidirectional Long Short-Term Memory
3.7 Stacked Long Short-Term Memory
3.8 Model Evaluation
3.9 Prediction
4 Results and Discussion
5 Conclusion
References
Comparative Analysis to Develop a Dimensionality Reduction Model for Classifying Intrusion Detection Systems
1 Introduction
2 Related Work
3 Methodology
3.1 Classification Algorithms
4 Results
5 Conclusion
References
Revolutionizing Airline Customer Satisfaction Analysis with Machine Learning Techniques
1 Introduction
2 Methodology
2.1 Data Retrieval
2.2 Exploratory Data Analysis (EDA)
2.3 Data Preprocessing
2.4 Data Performance Measurement
2.5 Proposed Machine Learning Models
2.6 Model Training and Evaluation
3 Results and Discussion
3.1 Experimental Environment
3.2 Exploratory Data Analysis (EDA)
3.3 Performance Metrics of All Models
3.4 Discussion
4 Conclusion
References
Android Malware Detection Using Machine Learning Technique
1 Introduction
2 Methodology
2.1 Feature Engineering
3 Implementation
3.1 Back-end Output and Code Snippets
3.2 Screenshot the Interface
4 Conclusions
References
An Ensemble Machine Learning Approach for Predicting Flood Based on Meteorological and Topographical Features: A Comparative Study in Kalu Ganga River Basin, Sri Lanka
1 Introduction
2 Literature Review
3 Methodology
4 Results and Discussion
4.1 Outlier Detection
4.2 Feature Selection
4.3 Machine Learning Models
5 Conclusion
References
A Review of IoT Applications in Smart Environments: From Smart Cities to Military Integration
1 Introduction
2 Smart City Applications
2.1 Smart Homes
2.2 Smart Parking Lots
2.3 Vehicular Traffic
2.4 Surveillance Systems
3 Smart Environmental applications
3.1 Weather and Water Systems
3.2 Smart Energy and Smart Grids
3.3 Environmental Pollution
3.4 Health Applications
4 Procurement Applications
5 Livestock Applications
5.1 Chickens
5.2 Cattle
6 Military Applications
7 Conclusion
References
Utilizing Deep Learning Technique for Arabic Image Captioning
1 Introduction
2 Arabic Image Captioning (AIC) Model
3 Results and Discussion
3.1 Experimental Settings
3.2 Obtained Results
4 Conclusion
References
Performance Analysis of Textured Contact Lens IRIS Detection Based on Manual Feature Engineering
1 Introduction
2 Existing Publicly Databases
3 Performance Evaluation Metrics
4 Existing CLIDs Based Hand-Crafted Feature Extraction
4.1 CLIDs-Based Spatial Domain
4.2 CLIDs-Based Transform Domain
5 Comparison of CLIDs Techniques
6 Conclusion
References
Proposed Model for QCNN-Based Sentimental Short Sentences Classification
1 Introduction
2 Background and Related Work
2.1 Quantum Computing
2.2 Quantum Machine Learning
2.3 Quantum Convolutional Neural Network
2.4 Related Work
3 Proposed Model
4 Conclusion and Future Work
References
An Anomaly Intrusion Detection Systems in IoT Based on Autoencoder: A Review
1 Introduction
2 Background of Autoencoder
3 Studies Characteristic and Discussion
3.1 Deep Autoencoder
3.2 Sparse Autoencoder
3.3 Variational Autoencoder
3.4 Combining Approaches
3.5 Technique Used
3.6 Datasets Used
4 Recommendations and Future Direction
5 Conclusion
References
Comparative Analysis of ResNet50, and VGG16 Architectures for Counterfeit Logo Identification
1 Introduction
2 Related Work
3 Methodology
3.1 Dataset Description
3.2 Data Preprocessing
3.3 Addressing Data Imbalance
3.4 Feature Selection
3.5 Applied Models
4 Results and Discussion
4.1 Performance of the ResNet50
4.2 Performance of the VGG16
4.3 Comparative Analysis
5 Conclusion
References
Assessing the Prioritization of Key Influencing Factors for Industrial IoT Readiness in SMEs
1 Introduction
2 Related Works
3 Methodology
4 Possible Influencing Factors for Industrial IoT Readiness in SMEs
5 Findings from Data Analysis
6 Conclusion
References
A Real-Time Hand Gesture Recognition Based on Media-Pipe and Support Vector Machine
1 Introduction
2 Methodology
2.1 Hand Model
2.2 Hand Gesture Recognition
2.3 Dataset
2.4 Image Processing
2.5 Feature Extraction
2.6 Support Vector Machine (SVM)
2.7 Visual Processing Algorithm
3 Results and Discussion
4 Conclusion
References
The Era of Industry 5.0: An Overview of Technologies, Applications, and Challenges
1 Introduction
2 Enabling Industry 5.0 Technologies
3 Applications of Industry 5.0
4 Challenges in Industry 5.0 and Future Directions
5 Conclusion
References
Overview of Cybersecurity Trends in Jordan's Financial Sector
1 Introduction
2 Background
2.1 The Digital Transformation of the Financial Sector in Jordan
2.2 Cybersecurity in the Financial Sector of Jordan
2.3 Regulatory Compliance in Jordan
2.4 Mobile and Fintech Applications in Jordan
3 Conclusion and Future Works
Appendix
References
Hybrid Filter Feature Selection for Improving Cancer Classification in High-Dimensional Microarray Data
1 Introduction
2 Related Works
3 Methodology
3.1 Data Collection
3.2 Data Preparation/Preprocessing
3.3 Modeling
3.4 Application of Machine Learning
3.5 Evaluation Metrics
4 Experiments
4.1 Lung Cancer Dataset
4.2 Ovarian Cancer Dataset
4.3 Mixed Lineage Leukemia (MLL)
4.4 Acute Myeloid Leukemia (AML)
5 Conclusion and Future Works
References
Machine Learning Techniques for Evaluating Student Performance
1 Introduction
2 Related Works
2.1 Machine Learning Approaches
2.2 Existing Methods and Approaches Using Deep Learning
3 Methodology
3.1 Dataset Description and Preprocessing
3.2 Model Development
3.3 Model Evaluation
4 Results and Discussion
4.1 Data Visualization
4.2 Experimental Results
5 Conclusion and Future Works
References
Author Index

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