Computational Methods and Data Engineering: Proceedings of ICCMDE 2021 (Lecture Notes on Data Engineering and Communications Technologies, 139)

Preface
Contents
About the Editors
A Graph-Based Extractive Assamese Text Summarization
	1 Introduction
	2 Related Work
	3 Motivation and Problem Statement
	4 Proposed Approach
		4.1 Stages of Proposed Approach
	5 Experimentation and Results
		5.1 Dataset
		5.2 Evaluation Using ROUGE
		5.3 Comparison with Other Approaches
	6 Conclusion
	References
Internet of Things (IoT) for Secure Data and M2M Communications—A Study
	1 Introduction
	2 Related Works
	3 Internet of Things and M2M Communications
	4 IoT Security Analysis
	5 Analysis of Various Categories of Attacks and Suggested Solutions
	6 Conclusions
	References
Development of Walking Assistants for Visually Challenged Person
	1 Introduction
	2 Literature Review
	3 Methodology
		3.1 Material Selection
		3.2 Programming and Calculation
		3.3 Working of the Device
	4 Results and Discussion
	5 Conclusion
	References
A Performance Study of Prediction Models for Diabetes Prediction Using Machine Learning
	1 Introduction
	2 Literature Survey
	3 Classification Algorithms Used in this Work
		3.1 Support Vector Machine (SVM)
		3.2 Naïve Bayes (NB)
		3.3 Random Forest (RF)
		3.4 Logistic Regression (LR)
		3.5 K-Nearest Neighbors (KNN)
		3.6 Gradient Boosting Classifier (GBC)
	4 Relative Work
	5 Framework for the Proposed Comparative Performance Study
		5.1 Proposed Experimental Setup
	6 Dataset Description
		6.1 Data Characteristics
	7 Conclusion
	References
Orthopantomogram (OPG) Image Analysis Using Bounding Box Algorithm
	1 Introduction
	2 Literature Review and Comparative Study
	3 Methodology
		3.1 OPG Image
		3.2 Machine Learning Model
		3.3 Diagnosis Report
		3.4 Cloud-Hosted Database
	4 Result Analysis
		4.1 Machine Learning Model
		4.2 Cloud-Hosted Database
	5 Conclusion and Future Scope
	References
Design and Analysis of an Improved Artificial Neural Network Controller for the Energy Efficiency Enhancement of Wind Power Plant
	1 Introduction
	2 Proposed Model of Wind Power Plant Station
	3 Design and Analysis of Wind Power Station
	4 Design of Proposed Variable Step-RBFN Algorithm
	5 Simulation Results and Analysis
	6 Conclusion
	References
Detection of Renal Calculi Using Convolutional Neural Networks
	1 Introduction
	2 Literature Survey
		2.1 Kidney Stone Detection with CT Images Using Neural Network [1]
		2.2 Renal Stone Detection and Analysis by Contour-Based Algorithm [2]
		2.3 Accurate Kidney Segmentation in CT Scans Using Deep Transfer Learning [3]
	3 Methods
		3.1 Convolutional Neural Networks
		3.2 ResNet and XResNet
		3.3 FasterRCNN
		3.4 Proposed Methodology
	4 Experimental Results
		4.1 Experimental Data
		4.2 Classification
		4.3 Localization
	5 Discussion
	6 Conclusion and Future Work
	References
Question Answering and Text Generation Using BERT and GPT-2 Model
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Model Architecture
	4 Training Procedure
	5 Results and Discussion
	6 Conclusions
	References
Improved LeNet Model for Flower Classification Using GPU Computing
	1 Introduction
	2 Convolutional Neural Networks
		2.1 Convolutional Layer
		2.2 Pooling Layer
		2.3 Flattening
		2.4 Fully Connected Layer
		2.5 Dropout
		2.6 LeNet-5 CNN Architecture
	3 Dataset
		3.1 Dataset Description
		3.2 Dataset Pre-processing
	4 Existing Approach
	5 Improved LeNet Model
	6 Results
	7 Conclusion
	References
Distributed Computing Meets Movable Wireless Communications in Next Generation Mobile Communication Networks (NGMCN)
	1 Introduction
	2 Related Work
	3 D-RAW with Afternoon Channel Status Information
	4 Proposed Methodology
		4.1 Round Trip Time and Split Connection Oriented Protocol Throughput
	5 Experimental Results
		5.1 Execution Improvement
	6 Conclusion
	References
The ELF Tribe: Redefining Primary Education in a Post-COVID Era
	1 Introduction
	2 Scope of the Work
	3 Literature Survey
		3.1 Evolution of Online Education
		3.2 National Education Policy 2020
	4 Design and Implementation
		4.1 Data Flow Diagram
		4.2 Schematic Diagram
		4.3 Programming Technologies
	5 Results and Discussions
		5.1 Snapshots
		5.2 Working
	6 Conclusion
	References
An Extreme Machine Learning Model for Evaluating Landslide Hazard Zonation in Nilgiris District, Causative Factors and Risk Assessment Using Earth Observation Techniques
	1 Introduction
	2 Study Area
	3 Dataset
	4 Landslide Influencing Factors
		4.1 Slope Degree
		4.2 Slope Aspect
		4.3 Land Use
		4.4 Geomorphology
		4.5 Distance to Road
		4.6 Drainage Density
		4.7 Lineament Density
	5 Landslide Susceptibility Modelling
		5.1 AdaBoost
		5.2 Random Forest Algorithm
		5.3 Gradient Boosting Decision Tree
	6 Model Performance Analysis and Accuracy Evaluation
	7 Model Validation and Comparison of Results
	8 Conclusion
	References
Analysis of Cross-Site Scripting Vulnerabilities in Various Day-To-Day Web Applications
	1 Introduction
	2 Literature Review
	3 Prevention and Mitigation Methods
	4 Analysis of XSS Attacks
	5 Implementation
		5.1 Burp Suite
		5.2 Vulnerability Scanning via Nessus and Burp Suite
		5.3 PayTM QC (Quality Control)
		5.4 Self-XSS Testing and Results
		5.5 Reflected-XSS Testing and Results
	6 Conclusion
	References
Detecting Cyberbullying with Text Classification Using 1DCNN and Glove Embeddings
	1 Introduction
		1.1 Types of Cyberbullying
	2 Related Work
	3 Proposed Approach
		3.1 Cyberbullying Detection Using 1DCNN
		3.2 Recurrent Neural Network
		3.3 Bert
	4 Conclusion and Future Work
	References
A Bayesian Network-Based Software Requirement Complexity Prediction Model
	1 Introduction
	2 Requirement Complexity
	3 Proposed Requirement Complexity Prediction Model
		3.1 Requirements and Expectations
		3.2 Parties Involved
		3.3 Development Characteristics
		3.4 Development Team
		3.5 Requirement Complexity Tree
		3.6 Requirement Complexity Tree
	4 Bayesian Network-Based Model for Requirement Complexity Prediction
		4.1 Introduction to Bayesian Networks
		4.2 The RCPM Model
	5 Validation of the RCPM model
	6 Conclusion
	References
Anomaly Detection Using Feature Selection and Ensemble of Machine Learning Models
	1 Introduction
		1.1 Cyber Attacks
		1.2 Anomaly Detection
	2 Literature Review
	3 Background
		3.1 Data Pre-processing
		3.2 Feature Selection
		3.3 Decision Tree
		3.4 Random Forest
		3.5 Support Vector Machine (SVM)
		3.6 Logistic Regression (LR)
		3.7 Ensemble Design Model
	4 Proposed Design
		4.1 Automatic Parameter Optimization
		4.2 Ensemble Classifiers
	5 Results
		5.1 Dataset Description
		5.2 Experimental Setup
		5.3 Evaluation Parameters
	6 Conclusion
	References
AutoNav: A Lane and Object Detection Model for Self-Driving Cars
	1 Introduction
	2 Materials and Methods
		2.1 Lane Detection
		2.2 Object Detection
		2.3 Autonomous Driving
	3 Results
		3.1 Lane Detection
		3.2 Object Detection
		3.3 Autonomous Driving
	4 Discussion
	5 Conclusion
	References
Using Natural Language Processing to Understand Reasons and Motivators Behind Customer Calls in Financial Domain
	1 Introduction
	2 Related Works
	3 Data
	4 Methodology
	5 Experimental Setup and Results
	6 Discussion
	7 Conclusion and Future Works
	References
Prediction of Indian Currency for Visually Impaired People Using Machine Learning
	1 Introduction
	2 Basic Concepts
		2.1 Machine Learning
		2.2 Image Processing
		2.3 Image Cropping and Resize
	3 Related Works
	4 Dataset Collection and Processing
		4.1 Dataset Optimization and Preprocessing
	5 Algorithm Used and It’s Flowchart
	6 Experimental Setup and Methodology
		6.1 Experimental Setup
		6.2 Choice of Machine Learning Algorithm
		6.3 Class Imbalance Problem
		6.4 Model Building
		6.5 Additions
		6.6 Model Accuracy
	7 Conclusion and Limitations
	References
Comparative Analysis of Different Machine Learning Prediction Models for Seasonal Rainfall and Crop Production in Cultivation
	1 Introduction
	2 Literature Review
	3 Methodology
		3.1 Linear Regression
		3.2 Bayesian Linear Regression
		3.3 Boosted Decision Tree Regression
		3.4 Decision Forest Regression
		3.5 Poisson Regression
	4 Evaluation Metrics
	5 Data Analysis
	6 Season Wise Comparative Models Results and Discussion
	7 Conclusion
	References
Fog-Enabled Energy-Efficient Smart Street Lamps using Machine Learning and IoT
	1 Introduction
	2 Related Work
	3 Smart Street Lamp
		3.1 The Smart Lamp
		3.2 Communication Infrastructure
		3.3 Control and Management Center
	4 Design and Implementation
		4.1 The Smart Lamp Construction
		4.2 Predictive Analysis
	5 Performance Evaluation
	6 Conclusion
	References
Sensing of Nitrogen and Temperature Using Chlorophyll Maps in Precision Agriculture
	1 Introduction
	2 Related Works
		2.1 Reflectance Field Measurements of Canopy
		2.2 Chlorophyll Canopy Content
		2.3 PROSAIL-D Model
		2.4 Vegetation Indices
	3 Materials and Methods
		3.1 Study Sites
		3.2 SPAD-503
		3.3 Field Sites Sampling
		3.4 Field Collection Data
		3.5 LLR Scaling Ratio of H and UH (Healthy and Unhealthy)
	4 Result and Discussion
	5 Conclusions
	References
A Decision Support System for Understanding the Importance of Two-Dosage Vaccination
	1 Introduction
	2 Related Researches
	3 Proposed System
	4 Implementation
		4.1 Data Description and Data Preprocessing
		4.2 Feature Selection
		4.3 Machine Learning Models
		4.4 Training the Model
		4.5 Performance from the Model
	5 Result
	6 Conclusion
	References
Sanskriti—A Distributed E-Commerce Site Implementation Using BlockChain
	1 Introduction
	2 Related Works
	3 Problem Statement
		3.1 Security Issue
		3.2 Ethical Practice
		3.3 Issues in Complete Shift to Blockchain
	4 Blockchain Technology Application in E-Commerce
		4.1 Metamask
		4.2 EVM and Solidity
		4.3 Ethereum
		4.4 Smart Contact
		4.5 Cryptocurrency
	5 Proposed System
		5.1 Features of Our System
	6 System Design
		6.1 Implemented Modules
	7 System Requirements
	8 Results and Discussion
	9 Conclusion and Future Work
	References
Classification of Animals Using MobileNet with SVM Classifier
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 MobileNet Architecture
		3.2 SVM
	4 Dataset
	5 Experimental Results
	6 Conclusion
	References
Performance Analysis of Different Matrices-Based SLM Techniques for Reducing PAPR in OFDM Systems
	1 Introduction
	2 Literature Survey
	3 Selective Mapping Technique
		3.1 Role of Phase Sequences
		3.2 Generation of Phase Sequences
	4 Hessenberg Matrices
		4.1 Orthogonal Upper Hessenberg Matrices
		4.2 Proposed Hessenberg Matrix-Based SLM Technique
	5 Simulation Results and Discussion
	6 Conclusion
	References
Fake News Detection in Mainstream Media Using BERT
	1 Introduction
	2 Related Works
	3 System Model
		3.1 Using Speech To Text Recognizer
		3.2 Using Image OCR
		3.3 BERT
	4 Implementation and Result
	5 Results
	6 Conclusion
	References
A General Approach of Plant Disease Identification and Detection from the Images Using Convolutional Neural Networks
	1 Introduction
	2 Rice Plant Diseases
	3 A Literature Review on Plant Disease Detection
	4 Deep Learning Methods Used in Identifying Disease
	5 Classification of Plant Disease Using Classifiers
	6 Conclusion and Research Direction
	References
Extreme Gradient Boosting for Toxic Comment Classification
	1 Introduction
	2 Literature Survey
	3 Proposed Methodology
		3.1 Corpus Creation and Text Preprocessing
		3.2 Corpus Sampling and Bag-of-Words Model
		3.3 Oversampling
		3.4 Gradient Boosting and XGBoost
		3.5 Model Evaluation
	4 Results and Discussion
	5 Future Work
	6 Conclusions
	References
Machine Learning Models for Predicting Customer Willingness to Buy Electric Vehicles
	1 Introduction
	2 Review of Literature
	3 Research Methodology
		3.1 Research Design
		3.2 Hypotheses
	4 Data Analysis
		4.1 Reliability Test and Factor Analysis
		4.2 Machine Learning Algorithms
		4.3 Sentiment Analysis
		4.4 Performance Measures of Different Algorithms Used
	5 Findings and Suggestions
	6 Scope and Limitation
	7 Conclusion
	References
A Data Science Approach in Quantitative Market Research
	1 Introduction
		1.1 Related Work
	2 Methodology
	3 Results and Discussions
		3.1 Analysis of Patterns Obtained from the Whole Market After Segmentation
		3.2 Analysis of an Individual Market Segment
	4 Conclusion
	References
Knowing Your Customers Using Customer Segmentation
	1 Introduction
	2 Type of Customer Segmentation
		2.1 Demographic
		2.2 Behavioral
		2.3 Psychographic
		2.4 Social Media Segmentation
	3 Customer Segmentation Models
		3.1 Recency, Frequency, Monetary (RFM)
		3.2 High-Value Customer (HVC)
		3.3 Customer Status
	4 Machine Learning Techniques for Customer Segmentation
		4.1 K-Means
		4.2 Support Vector Machine
		4.3 Regression
		4.4 Random Forest
		4.5 Neural Networks
		4.6 Optimization Methods
	5 Customer Segmentation Application
		5.1 Banking and Financial Services Fraud Detection
		5.2 E-commerce Cashback Model
		5.3 Social Media Marketing Planning
	6 Conclusion and Future Scope
	References
A Alzheimer’s Disease Detection and Classification Using Customised Convolutional Neural Network
	1 Introduction
	2 Related Work
	3 System Architecture
		3.1 Magnetic Resonance Imaging (MRI)
		3.2 Pre-processing
		3.3 Splitting of Data
		3.4 CCNN Learning Algorithm
		3.5 Pseudo Code of CNN Learning Algorithm
	4 Dataset and Experiment Results
		4.1 Different Challenges to AD Detection and Classification
	5 Conclusion
	References
A Deep Dive Comparison of Cache Replacement Strategies: The Quality of Experience Influencer
	1 Introduction
	2 Background Study
		2.1 The CCN Framework
		2.2 User’s Quality of Experience
	3 Motivation
		3.1 Caching Strategies
		3.2 Cache Replacement Strategies
	4 Results and Discussions
	5 Conclusion
	References
Unusual Event Detection from Surveillance
	1 Introduction
	2 Related Works
	3 Proposed Methodology
		3.1 CNN Architecture
	4 Conclusion
	References
Improved Mental Health Monitoring Using HappyOSN in Online Social Networks
	1 Introduction
	2 Related Works
	3 Working of HappyOSN Algorithm
	4 Design of Proposed HappyOSN Algorithm
		4.1 Research Objectives
		4.2 System Model
	5 Performance Evaluation
		5.1 Dataset Description
		5.2 Evaluation Results
		5.3 Performance Comparison
	6 Conclusion and Future Work
	References
Detection of Brain Tumor Using Neuro-Fuzzy Classifier
	1 Introduction
		1.1 Classification Utilizing Neuro-Fuzzy Classifier
	2 Module Description
		2.1 Fuzzy Neural Networks (FNN) with Neuro-Fuzzy Systems (NFS)
		2.2 Neuro-Fuzzy Systems
		2.3 Fuzzy Rule-Based Classification System (FRBCS)
		2.4 Fuzzy Interactive Dichotomizes 3
	3 Result and Discussion
		3.1 Efficiency
		3.2 Result
	4 Conclusion
	References
A Systematic Study About EEG Signal Data and Computer Aided Models for the Diagnosis of Alzheimer\'s Disease
	1 Introduction
	2 Diagnostic Tests on Alzheimer\'s Disease
	3 Study of EEG Signal
	4 Preprocessing Methods on EEG Data
	5 Feature Extraction Techniques
	6 Machine Learning (ML) and Deep Learning (DL) Methods
		6.1 Supervised Learning Algorithms
		6.2 Unsupervised Algorithms
		6.3 Deep Learning Techniques
	7 Experimental Results
	8 Conclusion
	References
Computer Vision Human Activity Recognition Using Cumulative Difference Energy Representation-Based Features and Employing Machine Learning Techniques
	1 Introduction
	2 Related Work
	3 Dataset
		3.1 KTH Human Action Dataset
	4 Cumulative Difference Energy Representation (CDER) for Human Action Recognition
		4.1 Preprocessing
		4.2 Motion Detection Using Frame Difference
		4.3 Proposed Target Action Detection Using Cumulative Difference
		4.4 Proposed CDER Feature Extraction Algorithm in KTH Database
	5 Machine Learning Techniques and Discussion
		5.1 K-nearest Neighbors (KNN) Classifier
		5.2 Support Vector Machine (SVM) Classifier
		5.3 Random Forest Classifier
		5.4 Naïve Bayes (NB) Classifier
		5.5 Decision Tree (J48) Classifier
	6 Numerical Experimental Analysis and Results
		6.1 Classification Results Using Proposed CDER Features with Various Machine Learning Techniques
		6.2 Comparison
	7 Conclusion and Future Work
	References
A Survey on Advancements of Real-Time Analytics Architecture Components
	1 Introduction
		1.1 Related Surveys on Real-Time Analytics Architecture Components
		1.2 Research Questions and Organization of the Article
	2 Advancements of Real-Time Analytics Architecture Components: Academic Perspective
		2.1 Collection
		2.2 Data Flow
		2.3 Processing
		2.4 Storage
		2.5 Delivery
	3 Advancements of Real-Time Analytics Architecture Components: Industrial Trends
		3.1 Transportation
		3.2 Health Care
		3.3 Smart Cities
		3.4 Miscellaneous
	4 Open Research Issues
	5 Conclusion
	References
Digital Video Steganography: An Overview
	1 Introduction
	2 Steganography
		2.1 Digital Video Steganography
	3 Quality Evaluation Techniques
	4 Conclusion
	References
Author Index