International Conference on Innovative Computing and Communications: Proceedings of ICICC 2021, Volume 3

✍ Scribed by Ashish Khanna, Deepak Gupta, Siddhartha Bhattacharyya, Aboul Ella Hassanien, Sameer Anand, Ajay Jaiswal

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 889
• Series: Advances in Intelligent Systems and Computing
• Edition: 1
• Category: Library

✦ Synopsis

This book includes high-quality research papers presented at the Fourth International Conference on Innovative Computing and Communication (ICICC 2021), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on February 20–21, 2021. Introducing the innovative works of scientists, professors, research scholars, students and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.

✦ Table of Contents

ICICC-2021 Steering Committee Members
Preface
Contents
Editors and Contributors
Explanation-Based Serendipitous Recommender System (EBSRS)
1 Introduction
2 Literature Survey
3 Proposed Approach
3.1 Phase I: User Assessment Phase
4 Experiments, Evaluation and Comparative Analysis
5 Conclusion
References
Introduction of Feature Selection and Leading-Edge Technologies Viz. TENSORFLOW, PYTORCH, and KERAS: An Empirical Study to Improve Prediction Accuracy of Cardiovascular Disease
1 Introduction
2 Methods and Materials
3 Empirical Results and Discussion
3.1 Utilization of Leading-Edge Technologies Viz. TENSORFLOW, PYTORCH, and KERAS
4 Conclusion
References
Campus Placement Prediction System Using Deep Neural Networks
1 Introduction
2 Literature Review
3 Proposed Technique
4 Results and Discussion
5 Conclusion
References
Intensity of Traffic Due to Road Accidents in US: A Predictive Model
1 Introduction
2 Literature Review
3 Proposed Work
4 Experimentation and Results
4.1 Data Sources
4.2 Feature Selection
4.3 Exploratory Data Analysis
5 Machine Learning Modelling
6 Conclusions and Future Directions
References
Credit Card Fraud Detection Using Blockchain and Simulated Annealing k-Means Algorithm
1 Introduction
2 Related Works
3 Methodology
3.1 Blockchain
3.2 k-Means Clustering Algorithm
3.3 Simulated Annealing
4 Experimental Work
4.1 Dataset
4.2 Proposed Work
4.3 Results
5 Conclusion
References
Improving Accuracy of Deep Learning-Based Compression Techniques by Introducing Perceptual Loss in Industrial IoT
1 Introduction
2 Related Work
3 Proposed Method
3.1 Overall Architecture
3.2 Autoencoder Architecture
3.3 Loss Functions
3.4 Lossless Compression Algorithm
4 Experimental Results
5 Conclusion
References
Characterization and Prediction of Various Issue Types: A Case Study on the Apache Lucene System
1 Introduction
2 Related Work and Research Contribution
2.1 Related Work
2.2 Research Contribution
3 Experimental Details
4 Research Questions
4.1 RQ1: What is the Distribution of Different Categories (e.g., Bug, Documentation, Improvement, etc.) Among All the Issue Reports?
4.2 RQ2: Are There Any Distinguishing Terms that Differentiate Various Issue Categories?
4.3 RQ3: Is There Any Significant Difference Between Mean Time to Repair (MTTR) of Different Issue Categories?
4.4 RQ4: What is the Performance of Classic and Ensemble Classifiers for Issue-Type Classification
4.5 RQ5: How Much Time Do Classic and Ensemble Machine Learning Algorithms Take in Training and Prediction?
5 Conclusion and Future Work
References
Heart Disease Prediction Using Machine Learning Techniques: A Quantitative Review
1 Introduction
2 Machine Learning Algorithms Used in Heart Disease Prediction, Diagnosis, and Treatment
2.1 Decision Tree
2.2 Naïve Bayes
2.3 Support Vector Machine (SVM)
2.4 K-Nearest Neighbor
2.5 Random Forest (RF)
3 Literature Review
4 Discussion
4.1 Comparative Representation of Various Machine Learning Methodologies Based on Accuracy
5 Research Gaps/Problems Identified
6 Conclusion
References
Enhancing CNN with Pre-processing Stage in Illumination-Invariant Automatic Expression Recognition
1 Introduction
2 Image Pre-processing Techniques
2.1 Histogram Equalization
2.2 Discrete Cosine Transform Normalization
2.3 Rescaled DCT Coefficients
3 Convolutional Neural Network
4 Implementation and Result Discussion
5 Conclusion
References
An Expert Eye for Identifying Shoplifters in Mega Stores
1 Introduction
2 Related Work
3 Proposed Framework
3.1 Inception V3
3.2 Long Short Term Memory (LSTM)
4 Experimentation and Result Analysis
5 Conclusion
References
Sanskrit Stemmer Design: A Literature Perspective
1 Introduction
2 Background Study
2.1 NLP: Natural Language Processing
2.2 Stemming
2.3 Stemmer
2.4 Stem
2.5 Affix
2.6 Over-Stemming, Under-Stemming, Miss-Stemming
2.7 Sanskrit Stemmer
3 Literature Review
3.1 A Comparative Study of Stemming Algorithms ch11comparativestudy
3.2 A Fast Corpus-Based Stemmer ch11corpusBased
3.3 A Hybrid Inflectional and a Rule-Based Derivational Gujarati Stemmers ch11gujaratiStemmer
3.4 A Stemmer-Based Lemmatizer for Gujarati Text ch11stemmatizer
3.5 Text Stemming: Approaches, Applications, and Challenges ch11textStemmingApproaches
3.6 Stemmers for Indic Languages: A Comprehensive Analysis ch11comprehensiveAnalysisOfStemmers
3.7 Rule-Based Derivational Stemmer for Sindhi Devanagari Using Suffix Stripping Approach ch11sindhiDevanagiriScript
4 Proposed Sanskrit Stemmer Design
5 Conclusion and Future Scope
References
Predicting Prior Academic Failure of Students’ Using Machine Learning Approach
1 Introduction
2 Related Work
3 Research Methodology
3.1 Data and Sources of Data
3.2 Proposed Methodology
3.3 Pre-processing Techniques
3.4 Classification Techniques
4 Results and Discussion
4.1 Experimental Results
4.2 Comparison of Classification Techniques
5 Conclusion
References
Deep Classifier for News Text Classification Using Topic Modeling Approach
1 Introduction
2 Related Work
3 Research Methodology
3.1 Dataset
3.2 Proposed Methodology
3.3 Data Pre-processing
3.4 Feature Extraction
3.5 Classification Techniques
4 Results and Discussion
5 Conclusion
References
Forecasting Covid-19 Cases in India using Multivariate Hybrid CNN-LSTM Model
1 Introduction
2 Windowing
3 The Proposed Model
4 Dataset Description
5 Experimental Results and Discussion
5.1 COVID-19 Forecasting
6 Conclusion
References
Multi-resolution Video Steganography Technique Based on Stationary Wavelet Transform (SWT) and Singular Value Decomposition (SVD)
1 Introduction
2 Literature Review
3 Proposed Method
3.1 Stationary Wavelet Transform
3.2 Singular Value Decomposition
3.3 The Proposed Method
3.4 Embedding Process Steps
3.5 Extraction Process Steps
4 Experimental Results
4.1 Performance Criteria
4.2 Results and Discussion
5 Conclusion
References
A Novel Dual-Threshold Weighted Feature Detection for Spectrum Sensing in 5G Systems
1 Introduction
2 Proposed Dual-Threshold Weighted Feature Detection (DTWFD) System Model
3 SNR-Based Weighted Factor Algorithm for Double Threshold Weighted Feature Detection (DTWFD)
4 Performance Evaluation
5 Conclusion
References
A Systematic Review on Various Attack Detection Methods for Wireless Sensor Networks
1 Introduction
2 Background Study
2.1 Review on Attack Detection Techniques for WSNs
2.2 Review on Various Attack Detection Methods Based on Clustering Techniques for WSN
2.3 Review on Various Attack Detection Methods Based on Authentication Protocols for WSN
3 Issues from Existing Methods
4 Solution
5 Results and Discussion
6 Conclusion
References
Electronic Beam Steering in Timed Antenna Array by Controlling the Harmonic Patterns with Optimally Derived Pulse-Shifted Switching Sequence
1 Introduction
2 Theory and Mathematical Background
2.1 Switching Sequences
2.2 Cost Function Formulation
3 Numerical Results and Discussion
3.1 Case 1: Steered Patterns at ± 10°
3.2 Case 2: Steered Patterns at ± 20°
3.3 Case 3: Steered Patterns at ± 30°
4 Conclusion
References
Classification of Attacks on MQTT-Based IoT System Using Machine Learning Techniques
1 Introduction
2 Literature Review
3 Resources and Methods
3.1 Data Collection
3.2 Theoretical Considerations
3.3 Evaluation Criteria
4 Outcome of the Applied Model
4.1 Attack Classification Results and Analysis
4.2 Criteria for Detection
4.3 Detection Results
5 Conclusions and Future Scope
References
Encrypted Traffic Classification Using eXtreme Gradient Boosting Algorithm
1 Introduction
2 Literature Review
3 The Proposed System
4 Experiments and Results
5 Conclusion
References
Analyzing Natural Language Essay Generator Models Using Long Short-Term Memory Neural Networks
1 Introduction
2 Related Work
3 Methodology
3.1 Dataset Used and Data Preprocessing
3.2 Embeddings
3.3 Approach
4 Experiment
4.1 Experimental Settings
4.2 Evaluation Metrics
5 Experimental Result
6 Conclusion
References
Performance Evaluation of GINI Index and Information Gain Criteria on Geographical Data: An Empirical Study Based on JAVA and Python
1 Introduction
2 Decision Tree
3 Splitting Benchmarks
3.1 Information Gain
3.2 GINI Coefficient
4 Related Work
5 Dataset
5.1 Evaluation—Information Gain Versus GINI Index
5.2 Information Gain
5.3 GINI Coefficient
6 Decision Tree Implementation: An Empirical Examination of Python and Java
6.1 Implementation Using Information Gain
6.2 Implementation Using GINI Index
7 Minimum Descriptive Length (MDL) Pruning
8 Experimental Results and Performance Comparison
8.1 Performance: Python Versus Java
9 Conclusion and Future Work
References
Critical Analysis of Big Data Privacy Preservation Techniques and Challenges
1 Introduction
2 Privacy Concern in Big Data
3 Literature Review
4 Findings
5 Technological-Based Solutions
6 Conclusion and Future Work
References
Performance Improvement of Vector Control Permanent Magnet Synchronous Motor Drive Using Genetic Algorithm-Based PI Controller Design
1 Introduction
2 Inverter Model
2.1 Two-Level Voltage Source Inverter
3 PMSM Model
3.1 Vector Control Drive System
3.2 Tuning Methods of PI Controllers Gain Using GAs
4 Result and Analysis
4.1 Simulation Response of PMSM Drive at Change in Speed with Constant Load Without GAs
4.2 Simulation Response of Vector Control PMSM Drive with GAs
5 Conclusions
References
Monitoring and Protection of Induction Motors Against Abnormal Industrial Conditions Using PLC
1 Introduction
2 PLC as a System Controller
2.1 Proposed Hardware
2.2 Overvoltage Circuit
2.3 Under-Voltage Circuit
2.4 Over-Temperature Circuit
2.5 RPM Measurement Circuit
2.6 PLC Ladder Algorithm
3 Proposed Methodology
4 Results
4.1 Under-Voltage or Overvoltage Situations
4.2 Over-Current Conditions
4.3 Over-Temperature Condition
5 Conclusion
References
A Vision-Based Gait Dataset for Knee Osteoarthritis and Parkinson’s Disease Analysis with Severity Levels
1 Introduction
2 Related Work
3 Available Datasets on KOA and PD
3.1 Knee Osteoarthritis (KOA) Datasets
3.2 Parkinson’s Disease (PD) Datasets
4 Dataset Description: Scenario and Method
4.1 KOA Dataset Overview
4.2 PD Dataset Overview
4.3 Normal/Healthy Dataset
5 Conclusion
References
A Survey of Recommender Systems Based on Semi-supervised Learning
1 Introduction
2 Collaborative Recommender System
3 Content-Based Recommender System
4 Hybrid Filtering-Based Recommender System
5 Semi-supervised Learning-Based Recommender System
5.1 Semi-supervised Learning
5.2 Existing Work on Semi-supervised Learning
6 Conclusion
6.1 Challenges and Solutions
References
“Emerging Trends in Computational Intelligence to Solve Real-World Problems” Android Malware Detection Using Machine Learning
1 Introduction
2 Related Work
3 Proposed Approach
4 Implementation
5 Algorithms Discussion
5.1 Naive Bayes
5.2 Decision Tree
5.3 Random Forest
5.4 Support Vector Machine
6 Results
7 Discussion
8 Conclusion
References
A Novel Intrusion Detection System Using Deep Learning
1 Introduction
2 Literature Review
3 Intrusion Detection System
4 Experiment
4.1 Dataset
4.2 Architecture
5 Results
6 Conclusion
7 Future Work
References
Solution to OCT Diagnosis Using Simple Baseline CNN Models and Hyperparameter Tuning
1 Introduction
2 Literature
3 Methods and Materials
3.1 3 Layer Model
3.2 5 Layer Model
3.3 7 Layer Model
4 Results
5 Discussion
6 Future Work
References
Land Rights Documentation and Verification System Using Blockchain Technology
1 Introduction
2 Existing System
2.1 Related Works
2.2 The New Land Registry Business Process
2.3 Challenges to the Existing System of Land Registry
2.4 Challenges to the Existing Structure of the Land Registry
3 Methodology
3.1 Design Using Hyperledger Fabric
3.2 Verity
4 Implementation
4.1 Implementation Using Hyperledger Fabric
4.2 Technical Details
4.3 Chain Codes
4.4 Deployment
5 Evaluation and Results
5.1 Transaction Latency
5.2 Transaction Throughput
5.3 Execution Time
5.4 Result
6 Conclusion
References
Implication of Privacy Laws and Importance of ICTs to Government Vision of the Future
1 Introduction
2 Material and Methods
3 Results
3.1 Descriptive Statistics
3.2 Correlation Analysis
3.3 Regression Analysis
4 Conclusions
References
AI Approaches for Breast Cancer Diagnosis: A Comprehensive Study
1 Introduction
2 Breast Imaging
2.1 Mammograms
2.2 MRI
2.3 Computerized Tomography
2.4 Scintimammography
2.5 Histopathologist Images
2.6 Positron Emission Tomography (PET)
3 Related Work
4 Pre-processing Techniques of Breast Images
4.1 Use of Filters for Normalization
4.2 Channeling of Images
4.3 Conversion to 3 Channel Images
4.4 Morphological Operations
5 AI Approaches for Breast Cancer Diagnosis
5.1 Machine Learning
5.2 Deep Learning Approach
6 Techniques to Improve Performance of AI Approaches
6.1 Data Augmentation
6.2 Transfer Learning
7 Research Opportunities and Challenges
8 Conclusion
References
Energy-Efficient Lifetime and Network Performance Improvement for Mobility of Nodes in IoT
1 Introduction
2 Related Work
3 Problem Description and Objectives
3.1 Problem Statement
3.2 Objectives
4 Network Architecture
4.1 Network Model
4.2 Energy Model
5 Proposed Method and Algorithm
5.1 Methodology
5.2 Algorithm
6 Simulation Analysis and Result
6.1 Simulation Model
6.2 Simulation Settings
6.3 Result Analysis
7 Conclusion and Future Work
References
Design and Implementation of Electronic Voting Using KECCAK256 Algorithm on Ethereum Network
1 Introduction
1.1 Blockchain, Natïve, and Traditional Voting [4]
1.2 Ethereum and Smart Contract
1.3 History of Elections
2 Review of Related Works
2.1 Toward Secure E-Voting Using Ethereum Blockchain [7]
2.2 Blockchain-Based E-Voting System [8]
2.3 A Privacy-Preserving Voting Protocol on Blockchain [9]
2.4 An E-Voting with Blockchain: An E-Voting Protocol with Decentralisation and Voter Privacy [1]
2.5 A Secure End-to-End Verifiable E-Voting System Using Zero-Knowledge-Based Blockchain [10]
2.6 A Conceptual Secure Blockchain-Based Electronic Voting System [11]
2.7 A Solution Based on the Diffie–Hellman Process System [12]
2.8 A Blockchain-Based E-Voting System [13]
2.9 An E-voting System Based on Blockchain and Ring Signature [14]
2.10 A Survey on Feasibility and Suitability of Blockchain Techniques for the E-Voting Systems [4]
2.11 An Electronic Voting Machine Based on Blockchain Technology and Aadhar Verification [15]
2.12 A Secure Voting System Using Ethereum’s Blockchain Which They Called BroncoVote [16]
2.13 A Crypto-Voting, a Blockchain-Based e-Voting System [17]
3 Methodology
3.1 Hardware Requirements
3.2 Implementation Tools
4 System Implementation
5 Conclusion
References
VizAudi: A Predictive Audio Visualizer
1 Introduction
2 Related Work
2.1 Works on the Categorization of Sound
2.2 Works on UrbanSound8K Dataset
2.3 Work on Deaf Assistance System
3 Dataset and Features
3.1 Dataset
3.2 Features
4 Methodology
4.1 Background and Foreground Sound Segregation
4.2 Background Sound Classification
4.3 Visual Output
5 Conclusions and Future Work
References
Universal Quantitative Steganalysis Using Deep Residual Networks
1 Introduction
2 Related Work
3 Basic Concepts
3.1 Steganalysis
3.2 Deep Residual Network
4 Proposed Work
5 Experimental Work
6 Conclusion
References
Image-Based Forest Fire Detection Using Bagging of Color Models
1 Introduction
2 Proposed Method
2.1 Feature Extraction
2.2 Threshold and Bagging
3 Experimental Results
4 Discussion
5 Conclusion and Future Work
References
Machine Learning Techniques for Diagnosis of Type 2 Diabetes Using Lifestyle Data
1 Introduction
2 Literature Survey
3 Proposed System
3.1 Dataset Description
3.2 Data Preprocessing
3.3 Machine Learning Techniques
4 Experimental Results
5 Conclusion
References
Deep Learning-Based Recognition of Personality and Leadership Qualities (DeePeR-LQ): Review
1 Introduction
1.1 Computing Personality
1.2 Leadership Qualities
1.3 Organisation
2 Related Work
2.1 Single Modal
2.2 Bi-Modal
2.3 Tri-Modal/Multimodal
3 Personality Traits to Leadership Qualities
4 Proposed Research Agenda
4.1 Challenges Ahead and Future Directions
5 Conclusions
References
Sentence-Level Document Novelty Detection Using Latent Dirichlet Allocation with Auto-Encoders
1 Introduction
2 Related Work
2.1 State-of-the-Art in Novelty Detection
2.2 Background: Topic Modeling
3 Proposed Method
4 Experimental Setup
5 Results and Discussions
6 Conclusions and Future Work
References
Prediction of Environmental Diseases Using Machine Learning
1 Introduction
1.1 Senior Citizens
1.2 Additional Information Required by the Volume Editor
2 Related Works
3 Waterborne Disease
3.1 Urbanization
4 Big Data Analysis
4.1 Volume
4.2 Velocity
4.3 Veracity
4.4 Variety
4.5 Validity
4.6 Volatility
4.7 Value
5 Health Care Ecosystem and Performance Measures
5.1 Experimental Method
6 Results and Discussion
7 Comparison with Other Techniques
8 Conclusion
References
Frequent Itemset Mining Using Genetic Approach
1 Introduction
2 Related Work
2.1 Frequent Itemset Mining
2.2 Genetic Algorithms in Frequent Itemset Mining
3 Problem Definition
3.1 Preliminaries
3.2 Problem Statement
4 FIMGA—Frequent Itemset Mining Using Genetic Approach
4.1 Genset1
4.2 Crossover
5 A Running Example
5.1 Genset1
5.2 Crossover
6 Experimental Study
6.1 Limitation of the Study
7 Conclusion
References
Gesture-Based Media Controlling Using Haar Cascade
1 Introduction
2 Literature Review
3 Architecture of Multimedia Devices
4 Methodology
5 Results and Discussion
6 Conclusion
References
Comparative Analysis of Models for Abstractive Text Summarization
1 Introduction
2 Related Work
3 Techniques for Abstractive Text Summarization
3.1 Preprocessing
3.2 Abstractive Text Summarization
4 Experiment and Results
4.1 Data set
4.2 Experimental Setting and Results
4.3 Evaluation Metric
5 Conclusion and Future Scope
References
Polarity Detection Across the Globe Using Sentiment Analysis on COVID-19-Related Tweets
1 Introduction
1.1 Research Study and Objectives
1.2 Our Work
2 Research Procedure
2.1 Research Design
2.2 Study Dimensions
2.3 Tools and Instrument
3 Literature Review
4 Dataset
4.1 Data Gathering Procedure
4.2 Data Preparation
5 Model for Sentiment Analysis
5.1 Naive Bayes
5.2 Linear Regression
5.3 Support Vector Machines (SVM)
6 Results on Trending Hashtag #Twitter Data
7 Conclusion
References
FOG-EE Computing: Fog, Edge and Elastic Computing, New Age Cloud Computing Paradigms
1 Introduction
1.1 Fog Computing
1.2 Edge Computing
1.3 Elastic Computing
2 Literature Survey
3 Methodology
3.1 Flowchart
4 Results
5 Conclusion
References
Hybrid Filter for Dorsal Hand Vein Images
1 Introduction
2 Related Work
3 Proposed Filter
4 Simulation Results
5 Conclusion
References
Satellite Image Enhancement and Restoration Using RLS Adaptive Filter
1 Introduction
2 Literature Review
3 Methodology
3.1 About Adaptive Filters
3.2 RLS—Recursive Least Square Adaptive Filter
3.3 Image Denoising and Channel Estimation
4 Experimental Results
5 Discussion
6 Conclusion
References
Efficient Recommendation System Using Latent Semantic Analysis
1 Introduction
2 Related Work
3 Methodology
3.1 Traditional Recommender System Techniques
3.2 Dimension Reduction Techniques
3.3 K-Nearest Neighbor (KNN)
4 Experimental Analysis
4.1 Training Data and Testing Data
4.2 Accuracy Metrics
5 Results and Discussion
6 Conclusion and Future Scope
References
A Study of Machine Learning Techniques for Fake News Detection and Suggestion of an Ensemble Model
1 Introduction
2 Literature Survey
3 Experimental Design
3.1 Dataset Description
3.2 Feature Extraction
3.3 Models
4 Discussion of Results
5 Conclusion
References
Metric Learning with Deep Features for Highly Imbalanced Face Dataset
1 Introduction
2 Proposed Metric Learning with Deep Face Features
2.1 Deep Face Networks
2.2 Distance Metric Learning
2.3 Proposed Model
3 Results and Discussions
3.1 Dataset
3.2 Result Analysis
4 Conclusion
References
An Adaptable Ensemble Architecture for Malware Detection
1 Introduction
2 Related Work
3 Proposed Ensemble Architecture
3.1 Convolution Neural Network
3.2 K Nearest Neighbors
3.3 Ensembling
4 Experimental Setup
5 Dataset Description and Result Analysis
6 Conclusion
References
An Application of Deep Learning in Identification of Depression Among Twitter Users
1 Introduction
2 Literature Review
3 Dataset
4 Methodology
4.1 Data Preprocessing
4.2 Text Classification
5 Experimental Results
5.1 Baseline Model Training
5.2 BiLSTM + CNN Training
6 Conclusion
References
Performance Evaluation of LSB Sequential and Pixel Indicator Algorithms in Image Steganography
1 Introduction
2 Method Analysis
3 Algorithms
3.1 LSB Sequential Substitution
3.2 Pixel Indicator Method
3.3 Coded LSB Substitution
3.4 Tools and Simulation Environment
4 Encoding and Decoding
5 Comparative Analysis
5.1 Image Perceptibility
5.2 Image Capacity
5.3 Security
6 Conclusion
References
MATHS: Machine Learning Techniques in Healthcare System
1 Introduction
2 Problem Statement
3 Literature Survey
4 Methodology Adopted
4.1 Algorithm
4.2 Dataset Description
4.3 Feature Selection
4.4 Applying Machine Learning Algorithms
5 Experimental Setup
6 Results: Analysis and Discussion
7 Conclusion and Future Work
References
EnSOTA: Ensembled State of the Art Model for Enhanced Object Detection
1 Introduction
2 Existing Methods
2.1 You Only Look Once (YOLO)
2.2 Single Shot Detector (SSD)
2.3 Faster Region-Based Convolutional Neural Networks
2.4 Ensembling
3 Proposed Method
3.1 Weighted Boxes Fusion
4 Research Approach
4.1 Dataset
4.2 Training
4.3 Testing
4.4 Prediction Ensembling
5 Results and Discussion
5.1 Evaluation Metrics
5.2 Intersection Over Union (IOU)
5.3 Precision × Recall Curve
5.4 Average Precision
5.5 Recorded Metrics
6 Conclusion
7 Future Scope
References
A Coronavirus Herd Immunity Optimization (CHIO) for Travelling Salesman Problem
1 Introduction
2 TSP Definition
3 Coronavirus Herd Immunity Optimizer for Travelling Salesman Problem
3.1 CHIO Procedure
4 Experiments and Results
4.1 TSP Data Description
4.2 TSP Results and Comparisons
5 Conclusion and Future Work
References
System for Situational Awareness Using Geospatial Twitter Data
1 Introduction
2 Related Works
3 Proposed Work
3.1 Algorithm
4 Results and Analysis
5 Conclusions and Future Works
References
Classification of Malware Using Visualization Techniques
1 Introduction
2 Related Works
3 Methodology
3.1 Base Dataset Selection
3.2 Dataset Creation (Feature Extraction)
4 Results
5 Conclusion and Future Work
References
Classification and Activation Map Visualization of Banana Diseases Using Deep Learning Models
1 Introduction
2 Background
3 Methodology
4 Crop Disease Detection by Notable DL Models
4.1 AlexNet (2012)
4.2 VGG16 (2014)
4.3 GoogLeNet (2014)
5 Experiments
5.1 Pre-trained Models
5.2 Workstation Specifications and Deep Learning Framework
5.3 Dataset
5.4 Performance Metrics
5.5 DL Architecture with Pre-training Versus DL Architecture Without Pre-training
6 Symptom Visualization
6.1 Symptoms and Disease Lesion Detection Using DL
6.2 Visualization of Every Channel in Each Intermediate Activation Layer
7 Conclusion
References
Exploring Total Quality Management Implementation Levels in I.T. Industry Using Machine Learning Models
1 Introduction
1.1 IT Industry
1.2 TQM and TQM Elements
1.3 ISO Certification and Quality Awards
1.4 Machine Learning Algorithms
2 Statement of Problem
3 Objective of Study
4 Literature Review
5 Conceptual Framework
6 Methodology
7 Results and Discussion
8 Conclusion and Recommendations
9 Limitations and Scope for Future Study
References
Predicting an Indian Firm’s Sickness Using Artificial Neural Networks and Traditional Methods: A Comparative Study
1 Introduction
2 Literature Review
3 Data and Methodology
3.1 Data
3.2 Methodology
4 Empirical Results
4.1 Comparison of the Prediction Accuracy
4.2 Coefficients of Variables of the Two-Year Predictive Model
5 Discussion
6 Conclusion
References
Analysis of Change of Market Value of Bitcoin Using Econometric Approach
1 Introduction
2 Literature Review
3 Research Methodology
3.1 Data Sources
4 Data Analysis
4.1 Micro–Macro Model Decomposition—Empirical Analysis
4.2 Analysis of Macro-variables
4.3 Analysis of Micro-variables
5 Conclusion
6 Managerial Implication
7 Limitations and Future Research
References
Detection of COVID-19 Using Intelligent Computing Method
1 Introduction
1.1 Coronavirus Origin
1.2 Virus Evolution
2 Literature Survey
3 Signs and Symptoms of Virus Existence
3.1 Risk Factors and Diagnosis
3.2 Transmission and Its Significance for Stopping
4 Results and Discussion
5 Conclusion and Future Scope
References
Two-Line Defense Ontology-Based Trust Management Model
1 Introduction
2 Related Work
3 The Proposed Method
3.1 First Line of Defense
3.2 Second Line of Defense
4 Implementation Results
4.1 Computational Complexity of the Proposed Approach
5 Conclusion and Future Work
References
A Machine Learning-Based Data Fusion Model for Online Traffic Violations Analysis
1 Introduction
2 Research Methodology
2.1 Traffic Violation Dataset
2.2 Preprocessing
2.3 Classification
2.4 Evaluation Metrics
3 Modeling and Implementation
3.1 Modeling
3.2 Implementation
4 Results and Discussion
5 Conclusion
References
Review of IoT for COVID-19 Detection and Classification
1 Introduction
2 Internet of Things
3 COVID-19
4 Literature Review
5 Conclusions and Future Works
References
On the Implementation and Placement of Hybrid Beamforming for Single and Multiple Users in the Massive-MIMO MmWave Systems
1 Introduction
2 System Model
2.1 Deep Learning Based Hybrid Beamforming Optimization with Limited Feedback
2.2 Delay Calculations for Different Placements of Beamforming
3 Simulation Results
4 Conclusions and Future Works
References
Neural Network Based Windowing Scheme to Maximize the PSD for 5G and Beyond
1 Introduction
2 System Model
2.1 Deep Neural Network Based Window Selection
2.2 Adaptive Window Selection to Maximize the PSD
3 Simulation Results
4 Conclusions and Future Works
References
Author Index