1st Edition

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

Edited By Manoj Sahni, Ritu Sahni, Jose M Merigo Copyright 2023
220 Pages 63 Color & 24 B/W Illustrations
by CRC Press

220 Pages 63 Color & 24 B/W Illustrations
by CRC Press

Also available as eBook on:

The text comprehensively discusses the latest mathematical modelling techniques and their applications in various areas such as fuzzy modelling, signal processing, neural network, machine learning, image processing, and their numerical analysis. It further covers image processing techniques like Viola-Jones Method for face detection and fuzzy approach for person video emotion. It will serve as an ideal reference text for graduate students and academic researchers in the fields of mechanical engineering, electronics, communication engineering, computer engineering, and mathematics.

This book:

• Discusses applications of neural networks, machine learning, image processing, and mathematical modeling.
• Provides simulations techniques in machine learning and image processing-based problems.
• Highlights artificial intelligence and machine learning techniques in the detection of diseases.
• Introduces mathematical modeling techniques such as wavelet transform, modeling using differential equations, and numerical techniques for multi-dimensional data.
• Includes real-life problems for better understanding.

The book presents mathematical modeling techniques such as wavelet transform, differential equations, and numerical techniques for multi-dimensional data. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields such as mechanical, electronics and communication and computer.

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 Shogunâ€™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

Manoj Sahni