Intro
Preface
Contents
Editors and Contributors
Improving River Streamflow Forecasting Utilizing Multilayer Perceptron-Based Butterfly Optimization Algorithm
1 Introduction
2 Study Area
3 Methodology
3.1 MLP
3.2 BOA
4 Results and Discussions
5 Conclusion
References
COVID-19 Contact Tracing Using Low Calibrated Transmission Power from BLE-Approach and Algorithm Experimentation
1 Introduction
2 Overcoming RSSI Shortcomings
2.1 Internal Factors
2.2 External Factors
3 Solution Approach-Experimentation and Results

3.1 Experimentation, Hardware and Software Set-Up
3.2 Experimentation Part One-Proof of Concept
3.3 Experimentation Part Two-Algorithm Test
3.4 Discussion
4 Conclusion
References
Monitoring Loud Commercials in Television Broadcast
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusion
References
Potential Customers Prediction in Bank Telemarketing
1 Introduction
2 Dataset and Preprocessing
2.1 Data Description
2.2 Data Correlation
2.3 Category Data Encoding
3 Experimental and Result
3.1 Data Mining Models
3.2 Result

4 Conclusion
References
Analysis and Implementation of Normalisation Techniques on KDD'99 Data Set for IDS and IPS
1 Introduction
2 Intrusion Detection System
2.1 Taxonomy of IDS
2.2 Intrusion Detection Methodologies
2.3 IDS and Their Functions
2.4 Data Sets for IDS
3 An Approaches of Machine Learning
3.1 Decision Tree
3.2 Naive Bayes
3.3 K-nearest Neighbour
3.4 Artificial Neural Network
3.5 Support Vector Machines
3.6 Fuzzy Logic
4 Proposed Research Work
5 Normalisation
5.1 Quick Overview of Normalisation Techniques
6 Literature Review

7 Proposed Work
8 Research Methodology
8.1 Evaluation Metrics
9 Result and Discussion
9.1 Comparition of Normalisation Techniques
10 Z-Score Implementation on KDD CUP '99
11 Conclusion
References
Deep Neural Networks Predicting Student Performance
1 Introduction
2 Methodology
2.1 Dataset and Data Processing
2.2 Deep Neural Network
3 Results and Discussions
4 Conclusion
References
An Efficient Group Signature Scheme Based on ECDLP
1 Introduction
2 Preliminaries
2.1 Background of Elliptic Curve Group
2.2 ECDLP Assumption

3 Proposed GS Scheme
3.1 KGC
3.2 Extract
3.3 GroupSign
3.4 GroupVerif
4 Security Analysis
5 Application
6 Conclusion
References
Sentiment Analysis of COVID-19 Tweets Using TextBlob and Machine Learning Classifiers
1 Introduction
2 Related Works
3 Design and Analysis
3.1 Data Extraction
3.2 Data Preprocessing
3.3 Visualization
3.4 Model Training
3.5 Support Vector Machine (SVM)
3.6 Classifier and Performance Measure
4 Finding and Discussion
5 Conclusion and Future Work
References
Reflection of Star Ratings on Online Customer Reviews