Neural Networks, Machine Learning, and Image Processing
Description
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.
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Dr. Manoj Sahni is a dedicated and experienced Mathematics teacher and researcher with more than 17 and a half years of experience and currently serving as an Associate Professor and Head in the Department of Mathematics, School of Technology, Pandit Deendayal Energy University, Gandhinagar, Gujarat, India. He has an excellent academic background with M.Sc. (Mathematics with specialization in Computer Applications), from Dayalbagh Educational Institute (Deemed University), Agra, M. Phil. from I.I.T. Roorkee, and a Ph.D. degree in Mathematics from Jaypee Institute of Information Technology (Deemed University), Noida, India. He has published more than 70 research papers in peer-reviewed Journals (SCI/ SCIE/ ESCI/ Scopus), Conference Proceedings (Scopus Indexed), and book chapters (Scopus Indexed) and with reputed publishers like Springer, Elsevier, etc. He also serves as an Advisory board member, Technical committee member and reviewer for many international journals of repute and Conferences. He has organized 1st, 2nd and 3rd International Conferences on Mathematical Modeling, Computational Intelligence Techniques, and Renewable Energy (MMCITRE) on February 21 - 23, 2020, February 06 - 08, 2021 and March 04-06, 2022 respectively. He participated in the scientific committee of several International Conferences and associations and also delivered many expert talks at the National and International levels. He has organized many Seminars, Workshops, Short Term Training Programs at Pandit Deendayal Energy University (PDEU), and various other Universities. He has also organized Special Symposia in an International Conference (AMACS2018) on Fuzzy Set Theory: New Developments and Applications to Real-Life Problems held at London in 2018. In addition, he is a member of many international professional societies, including the American Mathematical Society (AMS), Society for Industrial and Applied Mathematics (SIAM), IEEE, Mathematical Association of America (MAA), Forum for Interdisciplinary Mathematics (FIM), Indian Mathematical Society (IMS), IAENG, and many more.
Dr. Ritu Sahni is a dedicated and experienced Mathematics teacher and researcher with more than 15 years experience who is actively involved with both undergraduate and postgraduate levels teaching students. She has a strong academic background by completing B.Sc. (Mathematics), M. Sc. (Mathematics with specialization in Computer Applications) from Dayalbagh Educational Institute, Agra, U. P., India, and Ph.D. from Jaypee Institute of Information Technology (JIIT), Noida, India. During her Ph.D., she also served her Institution (JIIT, Noida, India) by teaching undergraduate and postgraduate students and after the completion of her Doctorate degree she served various Institutions including Navrachna University, Vadodara, Gujarat, India, Institute of Advanced Research (IAR), Gandhinagar, India as an Assistant Professor, and presently she is working as a Visiting Faculty at Pandit Deendayal Energy University, Gandhinagar Gujarat, India. She worked with her students on various research-related problems and published their work in reputed Journals (SCI/ SCIE/ ESCI/ Scopus) such as Elsevier, Springer, etc. She has published more than 45 research papers in peer-reviewed International Journals and Conferences. She is the reviewer of many International Journals and is a member of the Indian Science Congress and many other well-renowned societies. She has also organized Seminar, Workshop, and also coordinated the 2nd and 3rd International Conferences on Mathematical Modelling, Computational Intelligence Techniques and Renewable Energy (MMCITRE) held from February 06 - 08, 2021 and March 04 - 06, 2022. She has delivered talks and presented many research articles in various International Conferences in India and Abroad. Her research field includes Fixed Point Theory and its Applications, Numerical Methods, Fuzzy Decision-Making Systems, and other allied areas. She is a devoted faculty member, committed researcher, and enthusiastic about striving to improve the institution's educational offerings and research fields for societal growth.
Prof. José M. Merigó Lindahl is a Professor at the School of Information, Systems & Modelling at the Faculty of Engineering and Information Technology at the University of Technology Sydney (Australia) and Part-Time Full Professor at the Department of Management Control and Information Systems at the School of Economics and Business at the University of Chile. Previously, he was a Senior Research Fellow at the Manchester Business School, University of Manchester (UK) and an Assistant Professor at the Department of Business Administration, University of Barcelona (Spain). He holds a Master and a Ph.D. degree in Business Administration from the University of Barcelona. He also holds a B.Sc. and M.Sc. degree from Lund University (Sweden). He has published more than 500 articles in journals, books and conference proceedings, including journals such as Information Sciences, IEEE Computational Intelligence Magazine, IEEE Transactions on Fuzzy Systems, European Journal of Operational Research, Expert Systems with Applications, International Journal of Intelligent Systems, Applied Soft Computing, Computers & Industrial Engineering and Knowledge-Based Systems. He has also published several books with Springer and with World Scientific. He is on the editorial board of several journals including Computers & Industrial Engineering, Applied Soft Computing, Technological and Economic Development of Economy, Journal of Intelligent & Fuzzy Systems, International Journal of Fuzzy Systems, Kybernetes and Economic Computation and Economic Cybernetics Studies and Research. He has also been a guest editor for several international journals, member of the scientific committee of several conferences and reviewer in a wide range of international journals. Recently, Thomson & Reuters (Clarivate Analytics) has distinguished him as a Highly Cited Researcher in Computer Science (2015-present). He is currently interested in Decision Making, Aggregation Operators, Computational Intelligence, Bibliometrics and Applications in Business and Economics.
Content
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
