Intro
Preface
Organization
Contents
Part I
Contents
Part II
Computing Methodologies
Analysis of Developers' Sentiments in Commit Comments
1 Introduction
2 Related Literature
3 Research Methodology
3.1 Research Data
3.2 Sentiment Analysis
4 Results
5 Threat to Validity
6 Conclusions
References
Design of UML Diagrams for Intervention for Autism Children (IAC System)
1 Introduction
2 Functionalities of the System
3 Proposed IAC System
3.1 System Architecture
3.2 Data Flow Diagram
4 UML Diagrams
4.1 UML Usecase Diagram

4.2 UML Class Diagram
4.3 UML Activity Diagram
4.4 UML Sequence Diagram
4.5 UML Collaboration Diagram
4.6 UML State Machine Diagram
4.7 UML Component Diagram
4.8 UML Deployment Diagram
5 Experimental Results
6 Conclusion and Future Enhancement
References
Data Analysis and Forecasting of COVID-19 Outbreak in India Using ARIMA Model
1 Introduction
2 Related Work
3 Methodology
3.1 Proposed Methodology
4 Result Analysıs
5 Conclusion
References
Analysis Paper on Different Algorithm, Dataset and Devices Used for Fundus Images
1 Introduction

2 Analysis Color Fundus Images
2.1 Image Pre-processing
2.2 Dataset
2.3 DRISHTI-GS
3 Partitioning
4 Fundus Photography Sustainability with the Latest Devices in Current Health-Care Also
5 Limitations in the Earlier Fundus Camera
6 Machine Learning Methods for Vessel Extraction
7 Conclusion
References
Fuzzy Controller for Indoor Air Quality Control: A Sport Complex Case Study
1 Introduction
2 Background
3 Model
4 Fuzzy Controller
5 Results
6 Conclusion
References
Cancer Prediction Using Novel Ranking Algorithms and Machine Learning

1 Introduction
2 Literature Survey
3 Research Methodology
3.1 Ranking Based Algorithms
3.2 MAR (Mean Accuracy Ranking)
3.3 CDR (Class Differential Ranking)
3.4 PCR (Per Class Ranking)
4 Experimentation and Results
4.1 Dataset
4.2 Evaluation Metrics
4.3 Applying Base Classifiers
4.4 Applying Ranking Based Algorithms
4.5 Final Model
4.6 Comparison of Results with Previous Work
5 Conclusion
References
Supervısed Learnıng Algorıthm: A Survey
1 Introduction
2 Methodologies Analysis in Supervised Learning
2.1 Logistic Regression

2.2 Support Vector Classifier
2.3 Decision Tree
2.4 Random Forest Classifiers
3 Related Work
4 Chart of References
5 Conclusıon and Future Scope
References
Searching Sub-classes Within Type Ia Supernova Using DBSCAN
1 Introduction
2 Data Set
3 Methodology
3.1 Validity of DBSCAN
4 Results
5 Conclusions
6 Scope of Study
References
Abnormality Detection Based on ECG Segmentation
1 Introduction
2 Literature Review
3 Proposed Model
3.1 Software Requirements
3.2 Our Methodology
4 Flowchart of the Proposed Model