Note: Intro -- Program Committee -- Preface -- Contents -- About the Editors -- Part I Computational Intelligence -- Deep Learning, Predictive Modelling and Nano/Bio-Sensing Technologies for Mitigation of the COVID-19 Pandemic -- 1 Introduction -- 2 Deep Learning-Based Chest Image Analysis for Early Diagnosis of COVID-19 Infections -- 2.1 Deep Learning with CT Images -- 2.2 Deep Learning with Chest X-Ray (CXR) Images -- 2.3 Deep Learning with Ultrasound Images -- 3 Predictive Modelling of COVID-19 Epidemiological Patterns -- 3.1 Mathematical Approaches-Compartmental Models -- 3.2 Mathematical Approaches-Logistical Models -- 3.3 Mathematical Approaches-Time Series Prediction Models -- 3.4 Machine Learning-Based Prediction Models -- 4 Nano/Bio-Sensing Technologies for Point-of-Care Testing of COVID-19 Symptoms -- 5 Coro-Lib: Computational Resources for COVID-19 Mitigation -- 6 Discussions and Conclusion -- References -- User Authentication Using Password and Hand Gesture with Leap Motion Sensor -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Experimental Analysis -- 4.1 Applying DTW Algorithm Results -- 4.2 Applying Naïve Bayes Algorithm Results -- 5 Conclusion -- References -- Exploiting Transfer Learning Ensemble for Visual Sentiment Analysis in Social Media -- 1 Introduction -- 2 Related Work -- 3 Proposed Framework -- 3.1 Image Preprocessing -- 3.2 Transfer Learning Using Pre-trained CNN Models -- 3.3 Model Training and Prediction -- 3.4 Fusion of Models Prediction -- 4 Experiments and Evaluation -- 4.1 Dataset Collection -- 4.2 Model Configuration -- 4.3 Experimental Results and Evaluation -- 4.4 Comparison to Different Approaches -- 4.5 Discussion and Error Analysis -- 5 Conclusion and Future Directions -- References -- Automated Sorting of Rotten or Defective Fruits and Vegetables Using Convolutional Neural Network -- 1 Introduction. , 2 Previous Works -- 3 Proposed Approach -- 4 Dataset -- 5 Experimentation, Results, and Analysis -- 6 Conclusion -- References -- Fuzzy Time Series Forecasting of COVID-2019 Outbreak: A Case Study of U.S. Population -- 1 Introduction -- 1.1 Motivations and Contributions -- 1.2 Dataset -- 1.3 Context Diagram of the Proposed Study -- 2 Background Study -- 3 Methodology -- 4 Result and Discussion -- 4.1 Abbasov and Mamedova FTS Model Development -- 4.2 Model Evaluation -- 4.3 Forecast of Next 45 days -- 4.4 Evaluation of Forecast Versus Observed Data -- 4.5 Discussion -- 5 Recommendation for Forecasting the COVID-19 Outbreak -- 6 Conclusion -- References -- Electrical Power Demand Forecasting of Smart Buildings: A Deep Learning Approach -- 1 Introduction -- 2 Proposed SBEMS Architecture -- 2.1 SBEMS Center -- 2.2 Smart Meter -- 3 Proposed Prediction Module -- 3.1 Data Preprocessing -- 3.2 Forecasting Model Construction -- 4 Dataset Description and Correlation Analysis -- 5 Experiments and Results -- 5.1 Experimental Setup -- 5.2 Performance Metric -- 5.3 Results -- 6 Conclusion -- References -- Improved Performance of Recommender System Based on Demographic Attributes -- 1 Introduction -- 2 Literature Review -- 3 Problem Statement -- 3.1 Methodology -- 4 Conclusion -- References -- A Novel Method for Hostility Management -- 1 Introduction -- 2 Related Works -- 3 Experimental Analysis -- 4 Result -- 5 Conclusion -- References -- Detection of Invasive Ductal Carcinoma from Breast Histopathology Image Using Deep Ensemble Neural Networks -- 1 Introduction -- 1.1 Context -- 1.2 Literature Survey -- 2 Proposed Ensemble DNN Model -- 2.1 Histopathology Database -- 2.2 Data Pre-processing -- 2.3 Architecture Details -- 2.4 Ensemble Learning -- 3 Results and Conclusion -- 3.1 Model Evaluation -- 3.2 Result Analysis -- 4 Conclusion and Scope for Future Work. , References -- Neural Network-Based Surface Corrosion Classification on Metal Articles -- 1 Introduction -- 2 Related Work -- 3 Experiment -- 3.1 Training Dataset Preparation -- 3.2 Model Setup and Transfer Learning -- 3.3 Model Evaluation -- 4 Results and Conclusions -- 5 Future Work -- References -- Automated Cockpit Voice Recorder Sound Classification Using MFCC Features and Deep Convolutional Neural Network -- 1 Introduction -- 2 Literature Review -- 3 Proposed Model -- 4 Experimental Setup and Results Analysis -- 5 Conclusion -- References -- Bondhu Tank: An Automated Smart Water Management System -- 1 Introduction -- 2 System Architecture -- 2.1 Components Used in the Model -- 2.2 Flowchart of the Proposed Architecture -- 3 Experimental Result Analysis -- 4 Conclusion -- References -- A Holistic Framework for Quality Evaluation of Fruits and Vegetables Suppliers -- 1 Introduction -- 2 Preliminaries -- 2.1 Principal Component Analysis -- 2.2 Fuzzy Set Theory -- 2.3 Technique for Order of Preference by Similarity to Ideal Solution -- 3 Proposed Framework -- 4 Identification of Criteria -- 5 A Case Study -- 6 Conclusion -- References -- Algorithm to Generate All Spanning Tree Structures of a Complete Graph -- 1 Introduction -- 2 Literature Survey -- 3 Our Contribution -- 3.1 Formula for Generating Some Common Structures of Spanning Trees for All n -- 3.2 Formula for Repetitive Spanning Tree Structures for Higher Values of n -- 3.3 Partitioning -- 4 The Algorithm at a Glance -- 5 Data Structure and Complexity -- 6 Experimental Results -- 7 Conclusions and Future Work -- References -- Size Invariant Ship Detection Using SAR Images -- 1 Introduction -- 2 Related Work -- 3 Dataset and Methodology -- 4 Result Analysis -- 5 Evaluation Measures -- 6 Conclusion -- References -- Generation of Simple Undirected Connected Random Graphs -- 1 Introduction. , 2 Literature Survey -- 3 The Proposed Algorithm, Random Connected Graph Generator (RCGG) -- 3.1 Algorithm Random Connected Graph GeneratorRCGG() -- 4 Data Structures and Complexity -- 4.1 Time Complexity -- 5 Illustration of RCGG with an Example -- 6 Experimental Results -- 7 Conclusions -- References -- Capsnet-VGG16 Architecture for Cassava Plant Disease Detection -- 1 Introduction -- 2 Related Work -- 3 Capsule Network -- 4 Dataset Overview -- 5 Proposed Method -- 6 Experimental Setup -- 7 Results and Discussion -- 8 Conclusion -- 9 Future Scope -- References -- Forecast Model Development of Some Selected Wholesale Price Index of India Using MLP -- 1 Introduction -- 2 Literature Review -- 3 Research Gap -- 4 Objectives of the Study -- 5 Methodology -- 5.1 Overview of Model Development -- 5.2 Data -- 5.3 Data Division -- 5.4 Feature Extraction -- 5.5 Feature-Based Index Grouping -- 5.6 Largest Group Identification -- 5.7 Proposed Model -- 5.8 Other Models -- 5.9 Evaluation Matrix -- 6 Data Analysis and Findings -- 7 Conclusion -- References -- Educational Data Mining and Students' Academic Performance Prediction -- 1 Introduction -- 2 Extensive Literature Review -- 3 Problem Statement -- 3.1 Preparation Process of Data -- 3.2 Modification of Data -- 4 Proposed System Architecture: (Basic Conceptual Architecture) -- 5 Results and Simulation -- 5.1 Model Results -- 6 Conclusions and Future Direction -- References -- Deep Learning Approaches to Improve Effectiveness and Efficiency for Time Series Prediction -- 1 Introduction -- 2 Literature Survey -- 3 Artificial Neural Networks -- 3.1 Recurrent Neural Networks (RNN) -- 3.2 Long Short-Term Memory Networks (LSTM) -- 3.3 Gated Recurrent Unit (GRU) -- 4 Methodology -- 4.1 Proposed Approach -- 4.2 Model Details -- 5 Experimental Results and Discussion -- 5.1 Brief Outline of Datasets. , 5.2 Evaluation Metrics and Results -- 5.3 Predictions Visualization -- 6 Conclusion -- References -- Genetic Algorithm-Based Imperceptible Image Steganography Technique with Histogram Distortion Minimization -- 1 Introduction -- 2 Proposed Steganography Technique -- 2.1 Parameters for Secret Data Insertion -- 2.2 Histogram Distortion Minimization (HDM) -- 2.3 Genetic Algorithm -- 2.4 Algorithm for Secret Message Insertion -- 2.5 Algorithm for Extracting Secret Data -- 3 Experimental Results and Discussion -- 4 Conclusion -- References -- A Machine Learning Approach Toward Fast Track Decision in Judicial System -- 1 Introduction -- 2 Related Work -- 3 Proposed Model/Framework for Solution: -- 4 Current Scenario -- 5 Conclusion -- 6 Future Work -- References -- Part II Computer Vision -- Detection of COVID-19 Using ResNet on CT Scan Image -- 1 Introduction -- 2 Previous Works -- 3 Methodologies Used -- 3.1 Dataset -- 3.2 Image Preprocessing -- 3.3 Residual Networks -- 3.4 Convolutional Neural Networks -- 3.5 Transfer Learning of the Residual Neural Network -- 4 Evaluation Metric -- 5 Result Discussion and Analysis -- 6 Conclusion -- References -- On Mitigation of False Positive Problem in Singular Value Decomposition-Based Digital Image Watermarking -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Discrete Cosine Stockwell Transform (DCST) -- 2.2 Singular Value Decomposition -- 2.3 Chaotic Logistics Map (CLM) -- 2.4 Encoder and Decoder -- 3 Results and Discussion -- 3.1 Imperceptibility Analysis -- 3.2 Robustness Analysis -- 3.3 False Positive Error Analysis -- 4 Conclusion -- References -- Image Registration with a Comparative Feature Matching Approach -- 1 Introduction -- 2 Grayscale Conversion -- 3 Feature Detection Using SURF -- 4 Feature Extraction -- 5 Feature Matching Using SURF, BRISK, and MSER -- 5.1 SURF Feature Matching. , 5.2 BRISK Feature Matching.

Note: Intro -- 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.

Note: Intro -- ICICC-2021 Steering Committee Members -- Preface -- Contents -- About the Editors -- Automatic Removal of Eye Blink Artefacts from EEG Data Using Spatio-Temporal Features -- 1 Introduction -- 2 Experimental Design and Data Acquisition -- 3 Proposed Enhanced Artefact Elimination Algorithm -- 3.1 EEG Data Pre-Processing -- 3.2 EEG Dataset Epoching -- 3.3 Independent Components Extraction and Artefact Removal Success Indicator Calculation -- 3.4 Artefact Removal and Success Indicator Calculation -- 4 Results -- 5 Conclusion -- References -- Autoencoder-Based Model for Detecting Accounting Statement Fraud -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 3.1 Data and Variables -- 4 Data Analysis and Interpretation -- 4.1 Artificial Neural Network -- 4.2 Autoencoder -- 4.3 Network Training -- 5 Fraud Detection -- 6 Discussion -- 7 Conclusion -- References -- Increase in Mental Health Cases Post COVID Outbreak -- 1 Introduction -- 2 Background Study -- 3 Methodology -- 3.1 About the Dataset -- 3.2 Environmental Setup -- 3.3 Libraries Used -- 4 Results and Discussion -- 4.1 Dataset Evaluation -- 4.2 Heat Map Comparison -- 4.3 KNN Result -- 5 Future Scope -- 6 Conclusion -- References -- An Efficient Approach to Predict Fear of Human's Mind During COVID-19 Outbreaks Utilizing Data Mining Technique -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Data Handling -- 3.4 Classifier Selection -- 4 Outcomes -- 5 Conclusion -- References -- Evolutionary Algorithms for Face Recognition with Mask -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 3 Data Augmentation -- 4 Feature Extraction and Normalization -- 5 Feature Selection -- 5.1 Crow Search Algorithm (CSA) -- 5.2 Cuttle Fish Algorithm (CFA) -- 5.3 Classification -- 6 Results -- 7 Conclusion and Future Scope. , References -- Stock Price Prediction Using Reinforcement Learning -- 1 Introduction -- 2 Related Works -- 3 Reinforcement Learning -- 4 Stock Price Prediction -- 5 Methodology -- 6 Experimental Work -- 7 Conclusion -- References -- Sentiment Analysis of Bangla Text Using Gated Recurrent Neural Network -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset Collection -- 3.2 Features Extraction -- 3.3 Dataset Training -- 3.4 Gated Recurrent Unit Network (GRU) -- 4 Result and Analysis -- 5 Conclusion -- References -- Leveraging User Comments in Tweets for Rumor Detection -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach of Leveraging User Comments for Rumor Detection -- 4 Results and Discussion -- 5 Conclusion -- References -- A Cost-Efficient QCA XOR Function Based Arithmetic Logic Unit for Nanotechnology Applications -- 1 Introduction -- 2 A Brief Oversight of Quantum-Dot Cellular Automata -- 2.1 Majority Gate -- 2.2 QCA Clocking -- 2.3 QCA Designer -- 3 QCA-based Proposed Logic Design -- 3.1 Reviews on XOR Gate -- 3.2 Proposed QCA Architecture of XOR Gate Topology -- 3.3 Proposed Full Adder Usıng Proposed XOR (N7) Gate -- 3.4 Proposed Full Subtractor Using Proposed XOR Gate (N7) -- 3.5 1-bit ALU Architecture -- 4 Simulation Result and Discussion -- 5 Conclusıon -- References -- Forecasting of PM10 Using Intelligent Crow Search Algorithm Tuned Feed-Forward Neural Network -- 1 Introduction -- 2 Intelligent Crow Search Algorithm -- 3 Construction of the Forecasting Architecture Model -- 4 Results -- 5 Conclusion -- References -- A Hybrid Fusion-Based Algorithm for Underwater Image Enhancement Using Fog Aware Density Evaluator and Mean Saturation -- 1 Introduction -- 2 Proposed Method -- 2.1 Multiscale Fusion -- 2.2 Gray World White Balancing Algorithm -- 2.3 Red-Compensated White Balancing Algorithm+Gray World Algorithm. , 2.4 Edge Preserving Decomposition-Based Single Image Haze Removal Algorithm -- 2.5 Fog Aware Density Evaluator -- 3 Results and Discussion -- 4 Conclusion -- References -- Application of Hybridized Whale Optimization for Protein Structure Prediction -- 1 Introduction -- 2 Protein Structure Prediction Problem (PSP) -- 2.1 Problem Formulation -- 3 Hybrid Whale Optimization Algorithm -- 4 Results -- 4.1 Wilcoxon Rank-Sum Test -- 4.2 Convergence Property Analysis -- 4.3 Box Plot Analysis -- 5 Conclusion -- References -- Clinical Named Entity Recognition Methods: An Overview -- 1 Introduction -- 2 Literature Review -- 2.1 Machine-Learning-Based Methods -- 2.2 Deep-Learning-Based Methods -- 2.3 Active-Learning-Based Methods -- 2.4 Other Clinical Named Entity Recognition Methods -- 3 Research Gap and Issues -- 4 Analysis and Discussion -- 4.1 Analysis Using Published year -- 4.2 Analysis Using Methods -- 4.3 Analysis Using Evaluation Metrics -- 4.4 Analysis Using Values of Performance Metrics -- 5 Conclusion -- References -- Mobile Phone SMS Notification Behavior Analysis Using Machine Learning Technique -- 1 Introduction and Background -- 2 Literature Review -- 3 Methodology -- 3.1 Overview of Dataset -- 3.2 Block Diagram -- 3.3 Dataset Preprocessing -- 3.4 Noise Reduction from Dataset -- 3.5 Classification Methods -- 4 Performance Analysis -- 4.1 Assessment Metric -- 4.2 Assessment Results -- 5 Conclusion -- References -- Computer Vision with Deep Learning Techniques for Neurodegenerative Diseases Analysis Using Neuroimaging: A Survey -- 1 Introduction -- 2 Neurodegenerative Diseases and Types -- 3 Neuroimaging in Disease Diagnosis -- 4 Computer Vision-Based Framework for Medical Image Analysis -- 5 Related Work -- 6 Challenges or Research Questions -- 7 Conclusion and Future Work -- References. , Breast Cancer Risk Prediction Using Different Clustering Techniques -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Instances and Dataset -- 3.2 Missing Data Handling -- 3.3 Find the Optimal Number of Clusters -- 3.4 Elbow Method (WCSS Method) -- 3.5 Dendrogram -- 3.6 Applying Principal Component Analysis (PCA) with Kernel -- 3.7 Radial Basis Function Kernel (RBF) -- 3.8 Applying Clustering -- 3.9 K-Means Cluster -- 3.10 Hierarchical Clustering (HC) -- 4 Experimented Analysis and Discussions -- 4.1 Accuracy (ACCR) -- 4.2 Precision (PRC) -- 4.3 Recall (Sensitivity) (RECL) -- 4.4 F1-Score -- 4.5 Specificity (SPE) -- 4.6 Explanation of the Analysis -- 5 Conclusion -- References -- Learner Model of Intelligent Tutoring System Based on Bayesian Network -- 1 Introduction -- 2 Overview of Intelligent Tutoring System -- 2.1 ITS Mechanisms -- 3 Learner Model of ITS Based on Bayesian Network -- 3.1 Bayesian Network -- 4 Bayesian Learner Model Assessment -- 5 Conclusion -- References -- CADBAIG: Context-Aware Dictionary-Based Automated Insight Generator -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach: CADBAIG (Context-Aware Dictionary-Based Automated Insight Generator) -- 4 Working of CADBAIG on a Sample Research Paper -- 5 Results and Comparative Analysis -- 6 Conclusion and Future Work -- References -- Human Depression Prediction Using Association Rule Mining Technique -- 1 Introduction -- 2 Existing Works -- 3 Methodology -- 3.1 Collection of Data -- 3.2 Data Preprocessing -- 3.3 Chi-Square Correlation -- 3.4 Association Rule Mining -- 3.5 Simulation Environment -- 3.6 R Packages -- 4 Outcomes -- 5 Conclusion -- References -- Implementation of A Smart Helmet with Alcohol and Fall Detection and Navigation System -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Fall Detection System -- 3.2 Alcohol Detection System. , 3.3 Navigation System -- 3.4 Microcontroller and Implementation -- 4 Algorithm -- 5 Analysis and Results -- 6 Conclusion -- References -- BlockFITS: A Federated Data Augmentation Modelling for Blockchain-Based IoVT Systems -- 1 Introduction -- 2 Literature Review -- 2.1 Internet of Vehicular Things (IoVT) -- 2.2 Blockchain -- 2.3 Federated Learning -- 2.4 Data Augmentation -- 3 System Model -- 3.1 Requisite Definitions -- 3.2 Workflow of the System -- 4 Conclusion -- References -- Comparative Analysis for Improving Accuracy of Image Classification Using Deep Learning Architectures -- 1 Introduction -- 1.1 Motivation -- 1.2 Problem Identification -- 1.3 Solution -- 2 Dataset -- 3 Related Architecture Work -- 4 Result Analysis -- 5 Model Compilation, Training, and Model Evaluation -- 6 Discussion and Comparison -- 7 Future Scope -- 8 Experiment Approach -- 9 Limitation and Precaution -- 10 Conclusion -- References -- Infrared Thermography-Based Facial Classification Using Machine Learning -- 1 Introduction -- 2 Infrared Thermography-Based Face Recognition -- 2.1 Discrete Wavelet Transform (DWT) -- 3 Feature Extraction -- 4 Feature Reduction and Selection -- 5 Results and Discussion -- 6 Conclusion -- References -- An Efficient Cluster Assignment Algorithm for Scaling Support Vector Clustering -- 1 Introduction -- 2 Background Literature -- 2.1 Background: Core Vector Machines -- 2.2 Background: Ball Vector Machine -- 3 Efficient Cluster Computation : Proposed Approach -- 3.1 Proposed Efficient Clustering Approach -- 3.2 Experimental Setup -- 4 Results and Discussions -- 5 Conclusions -- References -- In Silico Analysis of Plant-Derived Medicinal Compounds Against Spike Protein of SARS-CoV-2 and Ace2 -- 1 Introduction -- 2 Methodology -- 2.1 Data Collection and Preparation -- 2.2 Binding Site Selection and Preparation -- 2.3 Molecular Docking. , 3 Results.

Note: Intro -- DoSCI-2022 Steering Committee Members -- Preface -- Contents -- Editors and Contributors -- TransCRF-Hybrid Approach for Adverse Event Extraction -- 1 Introduction -- 1.1 Motivation -- 1.2 Contributions -- 2 Related Work -- 3 Proposed Method -- 3.1 Preprocessing and Feature Engineering -- 3.2 Phrase Extraction -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Metrics -- 4.3 Evaluation -- 5 Conclusions -- References -- Process of Recognition of Plant Diseases by Using Hue Histogram, K-Means Clustering and Forward-Propagation Deep Neural Networks -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Preprocessing -- 3.2 Hue-Based Disease Spot Identification -- 3.3 Hue Histogram and K-means-Based Segmentation -- 3.4 Features Extraction -- 3.5 Disease Classification Using FPNN -- 4 Experimental Results -- 4.1 Dataset -- 4.2 Result of Segmentation Algorithms -- 4.3 Neural Network Performance -- 5 Conclusions -- References -- Analysis of Variants of BERT and Big Bird on Question Answering Datasets in the Context of Scientific Research Article Reviews -- 1 Introduction -- 2 Related Works -- 3 BERT and Big Bird a Quick View -- 3.1 BERT -- 3.2 Big Bird -- 3.3 Question Answering Datasets -- 4 Evaluation and Comparison of Various BERT and Big Bird Models -- 5 Conclusions and Observations -- References -- Twitter Opinion Mining on COVID-19 Vaccinations by Machine Learning Presence -- 1 Introduction -- 1.1 Valence Aware Dictionary and Sentiment Reasoner (VADER) -- 1.2 Word to Vector (W-V) -- 1.3 Term Frequency-Inverse Document Frequency (TF-IDF) -- 2 Background Study -- 3 Methodologies -- 3.1 Data Collection (DC) -- 3.2 Text Preparation (TP) -- 3.3 Feature Engineering (FE) and Exploratory Data Analysis (EDA) -- 3.4 Sentiment Analysis (SA)/Opinion Mining (OM) -- 3.5 Sentiment Analysis (SA)/Opinion Mining (OM) with VADER. , 3.6 Lexicon-based Models -- 3.7 Function to Clean and Remove Noise -- 3.8 Summary of VADER Lexicon Analysis (SVLA) -- 3.9 Analysis of Time Based -- 3.10 Inference Based on Probability -- 3.11 VADER Sentiment Analysis -- 3.12 Exploratory Data Analysis -- 3.13 Probabilistic Inference (PI) -- 3.14 Analysis of Correlation -- 3.15 Analyses of Users -- 3.16 Analysis of Word Decomposition -- 3.17 Long Short-term Memory (LSTM) with Confusion Matrix -- 3.18 Matrix of Confusion -- 4 Conclusion -- References -- Blockchain-Based Efficient and Secured Framework for Logistic Management -- 1 Introduction -- 2 Background of Research -- 2.1 Overview of Blockchain -- 2.2 Properties of Blockchain -- 2.3 Types of Blockchain Network -- 3 Cryptographic Method Used in Blockchain -- 4 Blockchain Application in Different Domain -- 5 Review of Literature and Related Work -- 6 Research Problems -- 7 Research Questions -- 8 Research Objectives -- 9 Research Methodology -- 10 Expected Impact -- 11 Conclusion and Future Recommendation -- References -- Blockchain-Based Framework to Handle Security and Privacy for IoT System -- 1 Introduction -- 2 Literature Survey -- 2.1 An Overview of IoT -- 2.2 An Overview of Blockchain -- 3 Research Problem -- 3.1 Research Questions -- 3.2 Research Objectives -- 3.3 Research Methodology -- 4 Expected Impact -- 5 Conclusion -- References -- Knowledge Management Using Blockchain Technology for Digital Resources -- 1 Introduction -- 1.1 Introduction to Blockchain -- 1.2 Blockchain Technology's Characteristics -- 1.3 The Six-Layer Technical Model of the Blockchain -- 2 Research Problem -- 2.1 Research Questions -- 2.2 Research Objectives -- 3 Research Methodology -- 4 Expected Impact -- 5 Conclusion -- References -- Blockchain Mechanism for Resolving Privacy Issues in a Smart City -- 1 Introduction -- 1.1 A Subsection Sample -- 2 Literature Survey. , 2.1 Smart Cities -- 2.2 Security and Privacy Issues in Smart Cities -- 2.3 Blockchain -- 2.4 Types of Blockchain -- 2.5 Use Cases of Blockchain to Handle Security and Privacy in Different Domains -- 3 Research Problem -- 3.1 Research Questions -- 3.2 Research Objectives -- 3.3 Research Methodology -- 4 Expected Impact -- 5 Conclusion -- References -- Design and Analysis of 50 Channel by 40 Gbps DWDM-RoF System for 5G Communication Based on Fronthaul Scenario -- 1 Introduction -- 2 Previous Publications -- 3 Methodologies -- 4 The Proposed System -- 4.1 Tx Part -- 4.2 Transmission Part -- 4.3 Rx Part -- 5 Results and Discussion -- 6 Conclusion -- References -- A Semantic Approach to Data Integration from Clinical Polystore -- 1 Introduction -- 2 Background -- 2.1 R2RML and RML Data Mappings -- 2.2 Ontology -- 3 Related Work -- 4 Architecture for Semantic Data Integration -- 5 Clinical Data Integration Through Query Translation -- 5.1 Motivating Scenerio -- 5.2 Ontology-Based Clinical Data Integration -- 6 Conclusion -- References -- Service Matter Judgement Prediction Using Machine Learning -- 1 Introduction -- 2 Machine Learning Model -- 3 Judgement Prediction Model -- 4 Dataset and Feature Identification -- 5 Feature Impact Analysis -- 6 Experimental Results -- 7 Outcome Analysis and Discussion -- 8 Conclusion and Future Scope -- References -- Predicting Smart Building Occupancy Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Dataset and Machine Learning Model Used for Experiment -- 3.1 Dataset -- 3.2 Machine Learning Model -- 4 Result and Discussion -- 5 Conclusion and Future Scope -- References -- Formal Specification of Dynamic Load-Based Coordinator Selection Algorithm with Recovery in Distributed Systems -- 1 Introduction -- 2 Related Work -- 3 System Model -- 4 Formal Modeling Technique: Event-B. , 5 Formal Specification of the Proposed Algorithm Using Refinement Levels -- 6 Conclusion and Future Work -- References -- Smart Cities Population Classification Using Hadoop MapReduce -- 1 Introduction -- 1.1 Management of Big Data in Smart City -- 1.2 Hadoop MapReduce -- 2 Related Works -- 3 Problem Statement -- 4 Aim of Study and Objectives -- 5 Objectives -- 6 Proposed System -- 7 Methodology -- 7.1 First Experiment -- 7.2 Second Experiment -- 7.3 Third Experiment -- 7.4 Fourth Experiment -- 7.5 Fifth Experiment -- 8 Conclusion -- References -- Performance Evaluation of Optimizers in the Classification of Marble Surface Quality Using CNN -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset Collection and Preprocessing -- 2.2 Methodology -- 2.3 Model Training -- 3 Results -- 3.1 Analysis of Machine Learning Algorithms with Base and Augmented Dataset -- 4 Conclusion -- References -- Predictive Analysis on Customer Churn Using Machine Learning Algorithms -- 1 Introduction -- 2 Related Works -- 2.1 Data Mining Techniques -- 2.2 Churn Models Developed -- 3 Methodology -- 4 Result -- 4.1 Random Forest -- 4.2 XGBOOST Classifier -- 4.3 Hybrid Model -- 5 Conclusion -- References -- Data Fusion-Based Smart Condition Monitoring of Critically Applied Rotating Machines -- 1 Introduction -- 2 Methodology -- 3 Technique Used -- 3.1 Feature Extraction in the Time Domain -- 3.2 Feature Selection Techniques -- 3.3 Classification Techniques -- 4 Results and Discussion -- 5 Conclusion -- References -- Depression Level Determination Using Deep Learning to Help Students in the COVID-19 Pandemic Situation -- 1 Introduction -- 2 Background Study -- 3 Proposed System -- 4 Results and Analysis -- 5 Conclusion and Future Work -- References -- Recognition and Classification of Facial Expressions Using Artificial Neural Networks -- 1 Introduction -- 2 Related Works. , 3 State of the Art -- 3.1 Emotion Recognition -- 3.2 SFEW and Recognition -- 4 Generative Adversarial Networks -- 4.1 Good Representations of the Data -- 4.2 DCGAN's Work Contributes in Several Ways to the State of the Art -- 5 Datasets -- 5.1 FER 2013 -- 5.2 CASIA -- 5.3 CK+ -- 5.4 SFEW 2015 -- 6 Methodology -- 6.1 First Pre-processing Methodology -- 6.2 Second Pre-processing Methodology -- 7 Experimentation -- 7.1 Conventional Knowledge Transfer -- 7.2 Knowledge Transfer Using GANs -- 8 Results and Discussion -- 9 Conclusion -- References -- Maize Leaf Disease Detection Using Convolutional Neural Network -- 1 Introduction -- 2 Literature Review -- 3 Proposed System -- 3.1 Dataset Description -- 3.2 Convolutional Neural Network -- 3.3 Xception Architecture -- 3.4 Inception Architecture -- 4 Experimental Results and Discussion -- 5 Conclusion and Future Works -- References -- Yield Forecast of Soyabean Crop Using Peephole LSTM Framework -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 4 Dataset -- 5 Experimentation Settings -- 6 Results -- 7 Conclusion and Future Scope -- References -- Vehicle Object Detection Using Open CV -- 1 Introduction -- 2 Related Work on Vehicle Tracking -- 3 Related Works on Vehicle Detection -- 4 System Architecture -- 5 Vehicle Dataset -- 6 Proposed Methodology -- 6.1 YOLO for Object Detection -- 6.2 Open CV -- 6.3 Coco Dataset -- 7 Experimental Results -- 8 Conclusion and Future Scope -- References -- Using AI-Based Approaches in Health Care for Predicting Health Issues in Pregnant Women -- 1 Introduction -- 2 Literature Survey -- 3 Experimental Setup Used for the Research Work -- 4 Forecasting of Length of Stay Using Machine Learning Approaches -- 4.1 Building Classification Predictive Model -- 4.2 Experimentation -- 4.3 Dataset Used -- 4.4 Performance Analysis of Data Mining Models -- 5 Conclusion -- References. , Industrial IoT with Secure Authentication Mechanism Through Blockchain Technology.