Machine Learning and Other Soft Computing Techniques: Biomedical and Related Applications

Preface
Contents
How to Estimate Unknown Unknowns: From Cosmic Light to Election Polls
	1 General Introduction
	2 First Case Study: Space Light
	3 Second Case Study: Election Polls
	4 Possible Explanation
	References
Why Bump Reward Function Works Well in Training Insulin Delivery Systems
	1 Formulation of the Problem
	2 Analysis of the Problem and the Resulting Explanation
	References
We Can Always Reduce a Non-linear Dynamical System to Linear—At Least Locally—But Does It Help?
	1 Formulation of the Problem
	2 Our Answers
	References
How to Best Retrain a Neural Network if We Added One More Input Variable
	1 Formulation of the Problem
	2 Analysis of the Problem
	3 Resulting Proposal
	4 Experiments
	References
Towards a Psychologically Natural Relation Between Colors and Fuzzy Degrees
	1 Formulation of the Problem
	2 Towards the Desired Natural Relation
	3 Discussion
	References
Algebraic Product Is the only ``And-Like\'\'-Operation for Which Normalized Intersection Is Associative:  A Proof
	1 Formulation of the Problem
	2 Main Result
	References
High Potential Negative Sampling for Drug Disease Association Prediction
	1 Introduction
	2 Related Work
	3 The Method
	4 Experiments
	5 Conclusions
	References
Cognitive States Prediction with KNN and TomekLinks
	1 Introduction
	2 Related Work
	3 The Method
	4 Experiments
	5 Conclusions
	6 Appendix
	References
Health Digital Twins with Clinical Decision Support and Medical Imaging
	1 Introduction
	2 Methods
	3 Results
	4 Discussion
	5 Conclusion
	References
Promoting STEM-Integrated Learning Through Engineering Design: High School Students\' Automatic Hand Washers
	1 Introduction
	2 Related Work
	3 Methods
		3.1 Description of Learning Tasks
		3.2 Building Rubric to Evaluate STEM Activities
	4 Experiment
		4.1 Experimental Object and Process
		4.2 Evaluation
		4.3 Discussion
	5 Conclusion
	References
KNN-SMOTE: An Innovative Resampling Technique Enhancing the Efficacy of Imbalanced Biomedical Classification
	1 Introduction
	2 Related Work
	3 The Method
	4 Experiments
		4.1 Datasets
		4.2 Evaluation Measures
		4.3 Classification Imbalance Learning Results
	5 Conclusions
	References
Human Detection in Video for Security Surveillance Systems
	1 Introduction
	2 Related Work
	3 Proposed Approach
		3.1 Yolov7 Detector
		3.2 Sequential Model
		3.3 VGG16 Transfer Learning
	4 Experiments
		4.1 Data Set
		4.2 Experimental Results
	5 Conclusion
	References
Fake Face Detection with Separable Convolutions
	1 Introduction
	2 Related Work
	3 Methods
		3.1 Dataset
		3.2 Deep Learning Architectures
		3.3 Separable Convolutions
	4 Experimental Results
		4.1 Environment Setting
		4.2 Results
	5 Conclusion
	References
A Classification System of Mammograms Based on Convolutional Neural Networks
	1 Introduction
	2 System Design
	3 Data Collection and Labeling
	4 Data Pre-processing
	5 Model Training and Evaluation
	6 Conclusions
	References
OAGRE: Outlier Attenuated Gradient Boosted Regression
	1 Introduction
	2 Method
		2.1 Implementation
		2.2 Evaluation
	3 Results
	4 Conclusion
	References
Improve the Effectiveness of Predicting Student Dropouts Based on Deep Learning and SMOTE Models
	1 Introduction
	2 Related Work
	3 The Method
		3.1 Datasets
		3.2 Data Imbalance Preprocessing
	4 Experiments
	5 Conclusions
	References
Data Processing and Feature Engineering for Stock Price Trend Prediction
	1 Introduction
	2 Data Collection
	3 Data Preparation
	4 Feature Engineering
	5 Model Development
	6 Experimental Results
		6.1 Feature Engineering and Non-feature Engineering
		6.2 Predicting Future Data
		6.3 Comparison with Results from Related Works
	7 Summary
	References
Distributed Computing in Training Machine Learning Models
	1 Introduction
	2 Distributed Computing Overview
		2.1 Data Parallelism Versus Model Parallelism
		2.2 Decentralized Asynchronous Systems
	3 Proposed Distributed Computing Method
		3.1 Communication Process with Socket Library in Python
		3.2 Data Parallelism Model Design and Deployment
	4 Experimentations
		4.1 Experimentation Results
		4.2 Insights and Experiences
	5 Discussion on Future Works
	6 Conclusion
	References
Fruit Calorie Determination System for Dieters and Athletes Using Deep Learning
	1 Introduction
	2 Related Work
	3 Proposed Approach
	4 Experiments
		4.1 Dataset
		4.2 Experimental Results
	5 Conclusion and Future Works
	References
An Approach to Instrumental Song Classification Utilizing Spectrogram and Convolutional Neural Networks
	1 Introduction
	2 Related Work
	3 Methods
		3.1 Data Collection and Division of Songs
		3.2 Transforming Audio Signal to Image with Spectrogram
		3.3 The Networks for Song Recognition
	4 Experimental Results
		4.1 Experimental Setup
		4.2 The Length of Pieces Extracted from the Song Can Affect the Song Detection Performance
		4.3 Data Augmentation on Songs
		4.4 Classification Algorithms Comparison
	5 Conclusion
	References
Heterogeneous Transfer Learning Using Pre-trained Feature Mapping and Exchange
	1 Introduction
	2 Related Works
	3 Proposed Method
		3.1 Stage 1: Matching
		3.2 Stage 2: Convolutional Transfer
		3.3 Stage 3: Fully-Connected Transfer
		3.4 Training with Feature Exchange
	4 Experimental Results
		4.1 Setup
		4.2 Using Cifar10, Cifar100, and PetImages Datasets
		4.3 Ablation Study
	5 Conclusion
	References
Usually, Either Left and Right Brains Are Equally Active or Only One of Them Is Active: First-Principles Explanation
	1 Formulation of the Problem
	2 Definitions and the Main Result
	3 Proofs
	References