Intro
Preface
Acknowledgements
About the Conference
Contents
Editors and Contributors
Captcha-Based Defense Mechanism to Prevent DoS Attacks
1 Introduction
2 Literature Survey
3 Working Methodology
4 Results and Discussion
5 Conclusion
References
Prognostic of Depression Levels Due to Pandemic Using LSTM
1 Introduction
2 Procedure
2.1 Importing All the Packages
2.2 Importing Datasets
2.3 Preprocessing and Feature Extraction
2.4 Working Principle
3 Flowchart
4 Results
5 Conclusion
6 Future Scope
References

An Efficient Design of 8 * 8 Wallace Tree Multiplier Using 2 and 3-Bit Adders
1 Introduction
2 Related Work
3 Basic Multiplication Practice
4 Proposed Work
4.1 Wallace Tree Multiplier
4.2 Wallace Tree 4 * 4 Multiplier
4.3 Wallace Tree 8 * 8 Multiplier
4.4 2-Bit Adder
4.5 3-Bit Adder
4.6 Ripple Carry Adder (RCA)
4.7 Look-Ahead Carry Adder
5 Experimental Results
5.1 8 * 8 Wallace Tree Multiplier
5.2 Power
5.3 Area
5.4 Delay
5.5 RTL Schematic View
5.6 Technology Schematic View
5.7 Package View

5.8 Investigation of Wallace Tree 8 * 8 Multiplier
6 Conclusion
References
Application of Rules and Authorization Key for Secured Online Training-A Survey
1 Introduction
2 Machine Learning
2.1 Overview
2.2 Security in Machine Learning
2.3 Authorization
2.4 Classification
3 Existing Systems
4 Access Control
5 Proposed Work
6 Expected Outcome
7 Conclusion
References
Detecting Semantically Equivalent Questions Using Transformer-Based Encodings
1 Introduction
2 Related Work
3 Dataset and Preprocessing
4 Proposed Methodology

5 Results and Discussion
6 Conclusion and Future Work
References
Detection and Monitoring of Alzheimer's Disease Using Serious Games-A Study
1 Introduction and Motivation
2 Findings and Methodology
3 Results and Discussions
4 Conclusion and Future Work
References
Factors Affecting the Online Travel Purchasing Decision: An Integration of Fuzzy Logic Theory
1 Introduction
2 Literature Review
3 Methodology
3.1 Fuzzy Inference System
3.2 Sampling and Procedures
3.3 Measures
4 Results and Discussion
4.1 Fuzzy Inference System Results
4.2 Discussion

5 Conclusion
References
An Empirical Study on the Occupancy Detection Techniques Based on Context-Aware IoT System
1 Introduction
2 Categorization of Occupancy Detection Techniques
2.1 Occupancy Detection via Sensors
2.2 Occupancy Detection via Sensor Fusion
2.3 Occupancy Detection via Wi-Fi and LAN
2.4 Occupancy Detection via Radio Frequency (RF) Signals
2.5 Occupation Detection Using Machine Learning Techniques
2.6 Other Types of Occupation Detection
3 Research Gaps and Issues
4 Result and Discussion
4.1 Analysis Based on Publication Year