Neural Networks, Machine Learning, and Image Processing: Mathematical Modeling and Applications

English | 2022 | ISBN: 978-1032300146 | 202 Pages | PDF | 17 MB

SECTION I Mathematical Modeling and Neural Network’ Mathematical Essence

Chapter 1 Mathematical Modeling on Thermoregulation in Sarcopenia
1.1. Introduction
1.2. Discretization
1.3. Modeling and Simulation of Basal Metabolic Rate and Skin Layers Thickness
1.4. Mathematical Model and Boundary Conditions
1.5. Solution of the Model
1.6. Numerical Results and discussion
1.7. Conclusion
References

Chapter 2 Multi-objective University Course Scheduling for Uncertainly Generated Courses
2.1 Introduction
2.2 Literature review
2.3 Formulation of problem
2.4 Methodology
2.5 Numerical Example
2.6 Result and Discussion
2.7 Conclusion
References

Chapter 3 MChCNN : A Deep Learning Approach to Detect Text based Hate Speech
3.1. Introduction Background and Driving Forces

3.2. Related Work

3.3. Experiment and Results
3.4. Conclusion
References

Chapter 4 PSO Based PFC Cuk Converter fed BLDC Motor Drive for Automotive Applications
4.1. Introduction
4.2. Operation of Cuk converter fed BLDC motor drive system
4.3. Controller Operation
4.4. Result and Discussion
4.5. Conclusion
References

Chapter 5 Optimize Feature Selection for Condition based monitoring of Cylindrical bearing using Wavelet transform and ANN
5.1. Introduction
5.2. Methodology
5.3. Data Preparation
5.4. Result and Discussion
5.5. Conclusion
References

Chapter 6 SafeShop – An integrated system for safe pickup of items during COVID-19
6.1. Introduction
6.2. Literature Survey
6.3. Methodology
6.4. Result and Discussion
6.5. Conclusion
References

Chapter 7 Solution of First Order Fuzzy Differential Equation using Numerical Method
7.1. Introduction
7.2. Preliminaries
7.3. Methodology
7.4. Illustration
7.5. Conclusion
References

SECTION II Simulations in Machine Learning and Image Processing

Chapter 8 Multi-layer Encryption Algorithm for Data Integrity in Cloud Computing
8.1. Introduction
8.2. Related works
8.3. Algorithm description
8.4. Simulation and performance analysis
8.5. Conclusion and Future Work
References

Chapter 9 Anomaly detection using class of supervised and unsupervised learning algorithms
9. 1. Introduction
9.2. Adaptive threshold and regression techniques for anomaly detection
9.3. Unsupervised Learning techniques for anomaly detection
9.4. Description of the dataset

9.5 Results and Discussions
9.6. Conclusion
References

Chapter 10 Improving Support Vector Machine accuracy with Shogun’s multiple kernel learning
10. 1. Introduction
10. 2. Support Vector Machine Statistics
10.3. Experiment and Result
10.4 Conclusion
References

Chapter 11 An Introduction to Parallelisable String-Based SP-Languages
11.1. Introduction
11.2. Parallelisable string-based SP-languages
11.3. Parallel Regular Expression
11.4. Equivalence of Parallel Regular Expression and Branching Automaton
11.5. Parallelisable String-Based SP-Grammar
11.6. Parallelisable String-Based SP-Parallel Grammar
11.7. Conclusion
11.8. Applications
11.9. Future Scope
References

Chapter 12 Detection of Disease using Machine Learning
12.1. Introduction
12.2. Techniques Applied
12.3. GENERAL ARCHITECTURE OF AI/ML
12.4. EXPERIMENTAL OUTCOMES
12.5. Conclusion
References

Chapter 13 Driver Drowsiness Detection Using Eye Tracing System
13.1. Introduction
13.2. Literature Review
13.3. Research Method
13.4. Observations and Results
13.5. Conclusion
References

Chapter 14 An Efficient Image Encryption Scheme Combining Rubik Cube Principle with Masking
14.1 Introduction
14.2 Preliminary Section
14.3 Proposed Work
14. 4 Experimental Setup and Simulation Analysis
14.5 Conclusion
References