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

Cover
Half Title
Title Page
Copyright Page
Table of Contents
Preface
Editors
Contributors
Part I: Mathematical modeling and neural network’s mathematical essence
1 Mathematical modeling on thermoregulation in sarcopenia
1.1 Introduction
1.2 Discretization
1.3 Modeling and simulation of basal metabolic rate and skin layer thickness
1.3.1 Basal metabolic rate model
1.3.2 Skin layer thickness model
1.4 Mathematical model and boundary conditions
1.4.1 Mathematical model
1.4.2 Boundary conditions
1.4.2.1 Boundary condition at x = 0 (skin surface)
1.4.2.2 Boundary condition at x = L[sub(3)] (body core)
1.5 Solution of the model
1.6 Numerical results and discussion
1.6.1 Temperature results
1.7 Conclusions
References
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
2.4.1 MOUSPUGC with linear membership function
2.4.2 MOUSPUGC with nonlinear membership function
2.5 Numerical example
2.6 Results and discussion
2.7 Conclusions
References
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 Experiments and results
3.3.1 Input layer
3.3.2 Embedding layer
3.3.3 Convolutional layers
3.4 Conclusions
References
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 Results and discussion
4.5 Conclusions
References
5 Optimized feature selection for condition-based monitoring of cylindrical bearing using wavelet transform and ANN
5.1 Introduction
5.2 Methodology
5.2.1 Advanced signal processing
5.2.2 Feature extraction
5.3 Data acquisition
5.3.1 Data preparation
5.3.2 Data mining
5.4 Results and discussion
5.5 Conclusions
References
6 SafeShop – an integrated system for safe pickup of items during COVID-19
6.1 Introduction
6.2 Literature survey
6.2.1 Face mask detector
6.2.2 Mobile application and social distance algorithm
6.3 Methodology
6.3.1 Face mask detector
6.3.2 Mobile application
6.4 Results and discussion
6.4.1 Face mask detector
6.4.2 Mobile application and social distancing algorithm
6.5 Conclusions
Acknowledgements
References
7 Solution to first-order fuzzy differential equation using numerical methods
7.1 Introduction
7.2 Preliminaries
7.2.1 H-differentiability
7.2.2 Strongly generalized differentiability
7.2.3 Fuzzy set (FS)
7.2.4 α-Level of fuzzy set
7.2.5 Triangular fuzzy number
7.2.6 Intuitionistic fuzzy set (IFS)
7.2.7 α, β-Level of intuitionistic fuzzy set
7.2.8 Triangular intuitionistic fuzzy set
7.3 Methodology
7.3.1 Solution to first-order differential equation in fuzzy environment using Euler’s method
7.3.2 Solution to first-order differential equation in intuitionistic fuzzy environment using Euler’s method
7.3.3 Solution to first-order differential equation in fuzzy environment using modified Euler’s method
7.3.4 Solution to first-order differential equation in intuitionistic fuzzy environment using modified Euler’s method
7.4 Illustration
7.5 Conclusions
References
Part II: Simulations in machine learning and image processing
8 Multi-layer encryption algorithm for data integrity in cloud computing
8.1 Introduction
8.2 Related works
8.3 Algorithm description
8.3.1 Encryption algorithm
8.3.1.1 Encryption rules
8.3.1.2 Second phase
8.3.1.3 Third phase
8.3.1.4 Encryption example
8.3.2 Decryption Algorithm
8.3.2.1 Algorithm analysis
8.4 Simulation and performance analysis
8.4.1 Performance analysis
8.5 Conclusions and future work
References
9 Anomaly detection using a class of supervised and unsupervised learning algorithms
9.1 Introduction
9.2 Adaptive threshold and regression techniques for anomaly detection
9.2.1 Artificial neural networks
9.2.2 Long short-term memory recurrent neural network
9.3 Unsupervised learning techniques for anomaly detection
9.3.1 Isolation forest
9.3.2 K-means clustering
9.4 Description of the dataset
9.5 Results and discussion
9.6 Conclusions
References
10 Improving support vector machine accuracy with Shogun’s multiple kernel learning
10.1 Introduction
10.2 Support vector machine statistics
10.2.1 Separable case
10.2.2 Non-separable case
10.2.2.1 Kernel method
10.2.2.2 Multiple kernel learning
10.3 Experiment and results
10.4 Conclusions
References
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 Conclusions
11.8 Applications
11.9 Future scope
References
12 Detection of disease using machine learning
12.1 Introduction
12.2 Techniques applied
12.2.1 Overall system architecture
12.2.2 Working of overall system
12.3 General architecture of AI/ML
12.3.1 Corona detection
12.3.2 Malaria detection
12.4 Experimental outcomes
12.5 Conclusions
References
13 Driver drowsiness detection system using eye tracing system
13.1 Introduction
13.2 Literature review
13.3 Research methods
13.3.1 Video acquisition using web camera
13.3.2 Non-separable case
13.3.2.1 Haar cascade algorithm
13.3.3 Flowchart representation of the procedure
13.4 Observations and results
13.4.1 Face detection
13.4.2 Eye Tracking
13.4.3 Morphological operation
13.4.4 Feature extraction and tracking of pupil
13.4.5 Mean shift algorithm
13.4.6 Detection of eye closure
13.4.7 Activation of alert sounds
13.5 Conclusions
References
14 An efficient image encryption scheme combining Rubik’s cube principle with masking
14.1 Introduction
14.2 Preliminary section
14.2.1 Chaotic maps
14.2.2 Masking
14.3 Proposed work
14.3.1 Rubik’s cube encryption
14.3.2 Rubik’s cube encryption algorithm
14.3.3 Rubik’s cube decryption algorithm
14.3.4 Encryption using masking
14.3.5 Proposed algorithm
14.4 Experimental setup and simulation analysis
14.4.1 Key space analysis
14.4.2 Analysis of key sensitivity
14.4.3 Histogram analysis
14.4.4 Variance
14.4.5 Information entropy
14.4.6 Correlation coefficient
14.4.7 Differential attack
14.4.8 Time analysis
14.4.9 Performance comparison
14.5 Conclusions
References
Index