Advanced Network Technologies and Intelligent Computing: Second International Conference, ANTIC 2022 Varanasi, India, December 22–24, 2022 Proceedings, Part II

Description

This book constitutes the refereed proceedings of the Second International Conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2022, held in Varanasi, India, during December 22–24, 2022.  The 68 full papers and 11 short papers included in this book were carefully reviewed and selected from 443 submissions. They were organized in two topical sections as follows: Advanced Network Technologies and Intelligent Computing. Preface Organization Contents – Part II Contents – Part I Intelligent Computing ADASEML: Hospitalization Period Prediction of COVID-19 Patients Using ADASYN and Stacking Based Ensemble Learning 1 Introduction 2 Literature Review 3 Proposed Methodology 3.1 Dataset Details and Preprocessing 3.2 Exploratory Data Analysis 3.3 Class Balancing Using ADASYN 3.4 ML Classifiers for Classification 3.5 Feature Importance Scores Calculation 4 Result and Discussion 5 Conclusion References A Novel Weighted Visibility Graph Approach for Alcoholism Detection Through the Analysis of EEG Signals 1 Introduction 2 Related Work 3 Methodology 3.1 Phase I: EEG Signal to Weighted Visibility Graph (WVG) 3.2 Phase II: Complex Network Feature Extraction 3.3 Classification 4 Experimental Study and Discussion 4.1 Dataset 4.2 Analysis of Individual Channels 4.3 Analysis of the Group of Significant Channels 5 Conclusion References A Dehusked Areca Nut Classification Algorithm Based on 10-Fold Cross-Validation of Convolutional Neural Network 1 Introduction 2 Literature Review 3 Dataset Description 4 Methodology 4.1 Data Augmentation 4.2 Convolutional Neural Network 4.3 MobileNet model 5 Results and Analysis 6 Conclusion References Customer Segmentation Based on RFM Analysis and Unsupervised Machine Learning Technique 1 Introduction 2 Existing Approaches 2.1 The Proposed System 2.2 Data Pre-processing 2.3 RFM Analysis 2.4 Selecting Optimum Number of Clusters 2.5 K Means Clustering 2.6 Data Visualisation and Analysis 3 Results and Analysis 4 Future Work 5 Conclusion References Manifold D-CNN Architecture for Contrastive Disease Classification Based on Respiratory Sounds 1 Introduction 2 Related Background 3 Proposed Framework 4 Results and Discussion 5 Conclusion and Future Work References A Pipelined Framework for the Prediction of Cardiac Disease with Dimensionality Reduction 1 Introduction 2 Related Work 3 The Proposed Methodology 3.1 Attributes Description and Dataset 3.2 Proposed Framework 4 Results 4.1 Comparative Study 5 Conclusion References Prediction of Air Quality Index of Delhi Using Higher Order Regression Modeling 1 Introduction 2 Literature Review 3 Methodology 3.1 Dataset Description 3.2 Handling Missing Values 3.3 Exploratory Data Analysis 3.4 Comparison of AQI Distribution Year Wise, Quarter Wise, Month Wise, and Week Wise 3.5 Feature Selection 3.6 Data Standardization 3.7 Data Splitting 3.8 Regression Techniques 4 Results 4.1 K-fold Cross-Validation 4.2 R2score 4.3 Mean Squared Error 4.4 Mean Absolute Error 4.5 Final Prediction 4.6 Comparative Analysis 5 Conclusion and Future Enhancement References Deep Learning for the Classification of Cassava Leaf Diseases in Unbalanced Field Data Set 1 Introduction 2 Methods 2.1 Dataset 2.2 Pre-processing 2.3 Model Architecture 2.4 Training 3 Results 4 Discussion 5 Conclusions References Image Classification with Information Extraction by Evaluating the Text Patterns in Bilingual Documents Abstract 1 Introduction 2 Text Patterns in Bi-lingual Document Processing Paradigms 2.1 Text Processing in Bilingual Documents 2.2 Document Mining with Images and Non-Images 2.3 Content Embedding and Structuring 2.4 Script Discrimination and Language Discrimination 2.5 Text Presentation and Style in Image Documents 2.6 A Case Scenario: Text Combinations with English-Hindi Pair 2.7 Application Categories for SLD and TPS Paradigms 3 Thematic Background on Bi-lingual Processing Systems 4 Proposed Bilingual Image Classification with Information Extraction 5 A Case Study on Image Classification with Information Extraction 5.1 Word Image Extraction and Character Segmentation 5.2 Word Association and Image Recognition 5.3 Classification Findings and Information Extraction 6 Conclusion and Future Recommendations References Probabilistic Forecasting of the Winning IPL Team Using Supervised Machine Learning 1 Introduction 1.1 Motivation 1.2 Organization of the Report 2 Related Works 3 System Design 3.1 Data Preprocessing, Aggregation and Feature Extraction-I 3.2 Preprocessing and Feature Extraction-II 3.3 Algorithm 3.4 Implementing the Models in a Real-Time Scenario 3.5 Web Application 4 Result and Discussion 5 Conclusion and Future Work References Diversified Licence Plate Character Recognition Using Fuzzy Image Enhancement and LPRNet: An Experimental Approach 1 Introduction 2 System Model 2.1 Fuzzy Image Contrast Enhancement 2.2 Licence Plate Object Detection 2.3 Character Recognition 3 Results and Discussion 3.1 Experimental Setup 3.2 System Training Model 3.3 Test Case 3.4 Performance Analysis 4 Conclusion References High Blood Pressure Classification Using Meta-heuristic Based Data-Centric Hybrid Machine Learning Model 1 Introduction 2 Literature Review 3 Methods 3.1 Data Set Details 3.2 Methodology Used to Extract the Rules 3.3 Pseudo Code of the Proposed Model 4 Results 5 Discussion 5.1 Limitations 6 Conclusion and Future Work References Implementing Machine Vision Process to Analyze Echocardiography for Heart Health Monitoring 1 Introduction 2 Literature Review 3 Analysis 4 Proposed Work 4.1 U-Net Model Architecture 4.2 Web Application System Architecture 5 Result and Discussion 6 Future Work 7 Conclusion References Social Media Bot Detection Using Machine Learning Approach 1 Introduction 2 Literature Review 3 Existing Social Media Bot Detection Technologies 4 Methodology 4.1 Data Set 4.2 Methods 5 Experimental Results References Detection of Homophobia & Transphobia in Malayalam and Tamil: Exploring Deep Learning Methods 1 Introduction 2 Related Work 3 Dataset Description 3.1 Data Pre-processing 4 Experimental Setup 4.1 CNN 4.2 LSTM 4.3 mBERT 4.4 IndicBERT 5 Results 5.1 Comparison with Existing Studies 6 Conclusion References Coffee Leaf Disease Detection Using Transfer Learning*-12pt 1 Introduction 2 Literature Review 3 Materials and Methods 3.1 Dataset 3.2 Data Prepossessing 3.3 Proposed Model 4 Experiments and Results 4.1 Software Setup 4.2 Evaluation Metrics 4.3 Results 5 Conclusion and Future Scope References Airline Price Prediction Using XGBoost Hyper-parameter Tuning 1 Introduction 2 Literature Review 3 Exploratory Data Analysis 4 Methodologies 4.1 Linear Regression 4.2 Random Forest Regressor 4.3 XGBoost Regressor 5 Results 5.1 Evaluation Metrics 5.2 Accuracy Comparison of Models 6 Conclusion References Exploring Deep Learning Methods for Classification of Synthetic Aperture Radar Images: Towards NextGen Convolutions via Transformers 1 Introduction 2 Related Work 3 Dataset 4 The Explored Models 4.1 BiT 4.2 ConvNext 4.3 DenseNet121 4.4 MobileNetV3 4.5 ViT 4.6 Xception 5 Experimental Setup 5.1 Model Compilation 6 Results 7 Conclusion References Structure for the Implementation and Control of Robotic Process Automation Projects 1 Introduction 2 Methodology 3 Articles Analysis 3.1 Synthesis Results 4 Implementation and Control RPA Projects: Framework Proposal 4.1 Identify the Objectives of the Business Area 4.2 Define Your Company's RPA Goals 4.3 Define the Necessary Actions (Internal or External to Your Organization) 4.4 Organizational Structure of the Teams 4.5 Governance Frameworks 5 Conclusion References Shrinkable Cryptographic Technique Using Involutory Function for Image Encryption 1 Introduction 1.1 Multimedia Data and Security 2 Literature Review 2.1 Limitations and Drawbacks of Traditional Cryptographic Techniques 3 Research Methodology 4 Result and Discussion 4.1 Pseudo Random Number Generator 4.2 Image Encryption and Decryption 5 Statistical Analysis 5.1 Histogram Analysis 5.2 NIST Statistical Analysis 5.3 Correlation Coefficient (C.F.) Analysis 5.4 Comparison of Encryption Time 6 Conclusion References Implementation of Deep Learning Models for Real-Time Face Mask Detection System Using Raspberry Pi 1 Introduction 2 Literature Survey 3 Raspberry Pi Based Face Mask Detection 3.1 Data Set Collection 3.2 Image Preprocessing 3.3 Data Augmentation 3.4 Model Fitting 3.5 Head-Model 4 Face Detection and Classification 4.1 Experimental Setup 4.2 Results 5 Conclusion References Depression Detection on Twitter Using RNN and LSTM Models*-12pt 1 Introduction 2 Literature Survey 3 Methodology 3.1 Data Exploration and Collection 3.2 Data Cleaning 3.3 Data Preprocessing 3.4 Deep Learning Models 4 Model Evaluation and Validation 5 Conclusion and Future Scope References Performance Assessment of Machine Learning Techniques for Corn Yield Prediction*-12pt 1 Introduction 2 Related Work 3 Data Set 3.1 Data Collection 3.2 Data Pre-processing 3.3 Data Visualization 3.4 Data Set Partitioning 4 Methodology 5 Results and Discussion 6 Conclution and Future Scope References Detection of Bird and Frog Species from Audio Dataset Using Deep Learning 1 Introduction 2 Literature Survey 3 Dataset Desrciption 4 Methodologies 4.1 Preprocessing 4.2 Generating Spectrograms 4.3 Evaluation 4.4 Experimental Setup 4.5 Models Implemented 5 Result 5.1 Result Analysis 6 Conclusion 7 Future Work References Lifestyle Disease Influencing Attribute Prediction Using Novel Majority Voting Feature Selection 1 Introduction 1.1 Biological Link Between Heart Disease and Diabetes 1.2 Limitations of Prior Work 1.3 Motivation of the Proposed Model 1.4 Research Contributions 1.5 Organization of This Proposed Work 2 State-of -Art Analysis of LSD Prediction 3 Proposed Methodology 3.1 Novel Majority Voting Ensemble Feature Selection (NMVEFS) 3.2 Feature Selection Techniques Used in NMVEFS 3.3 Modified Deep Neural Network (MDNN) 4 Experimental Result of LSD Prediction Model 4.1 Dataset Description 4.2 Performance Metrics of the LSD Prediction Model 4.3 Experimental Results of NMVEFS – MDNN Classifier 4.4 Comparative Analysis of NMVEFS-MDNN Model 5 Conclusion References Sample Size Estimation for Effective Modelling of Classification Problems in Machine Learning*-12pt 1 Introduction 2 Methodology 2.1 Bird-eye View of the Process 2.2 Datasets 2.3 Machine Learning Algorithms 2.4 Experimental Setup 3 Results 4 Discussion 5 Conclusion References A Generative Model Based Chatbot Using Recurrent Neural Networks 1 Introduction 2 Preliminaries 2.1 Recurrent Neural Networks 2.2 LSTM Networks 2.3 Sequence to Sequence Models 2.4 Attention Models 3 Related Work 4 Proposed Approach 4.1 Procedure 4.2 Design and Implementation 5 Evaluation of the Proposed Approach 5.1 Turing Test 5.2 Sample Conversations with the Model 5.3 Comparison with Cleverbot 6 Conclusion References Pixel Attention Based Deep Neural Network for Chest CT Image Super Resolution 1 Introduction 2 Existing SISR Techniques 3 Proposed Model: MediSR Network 3.1 Pixel Attention Mechanism 3.2 Network Design 3.3 Working of Proposed Network 4 Experimental Results 4.1 Datasets Details 4.2 Performance Metric 4.3 Training Details 4.4 Comparative Results 5 Conclusion References Evaluation of Various Machine Learning Based Existing Stress Prediction Support Systems (SPSSs) for COVID-19 Pandemic 1 Introduction 2 Literature Review 3 Research Gaps 4 Proposed Methodology 5 Statistical Discussions and Performance Assessments 6 Conclusions and Future Directions References Machine Learning Approaches for the Detection of Schizophrenia Using Structural MRI 1 Introduction 2 Methods and Models 2.1 Pre-processing 2.2 Classifiers 2.3 Cross Validation Method 3 Analysis and Discussion of Results 3.1 Dataset and Pre-processing 3.2 Performance Metrics 3.3 Discussion 4 Conclusion References A Hybrid Model for Fake News Detection Using Clickbait: An Incremental Approach 1 Introduction 1.1 Study of the Existing Solutions 1.2 Research Gap/Problems Found with Existing Solutions 2 Literature Review 2.1 Clickbait Detection 2.2 Fake News Prediction 2.3 Proposed System and Its Requirements 2.4 Assumption and Dependencies 2.5 Advantages Offered by Proposed System 3 Design 3.1 System Architecture 3.2 Data Dictionaries 4 Implementation 4.1 Clickbait Detection 4.2 Implementing Fake News Detector 4.3 A Hybrid Model of Fake News Detection with Clickbait Detection 5 Results and Comparison 6 Conclusion References Building a Multi-class Prediction App for Malicious URLs 1 Introduction 2 Literature Review 3 Proposed Methodology 3.1 Data Preprocessing and Feature Engineering 3.2 Deep Learning and Ensemble Algorithm Selection 3.3 Experimental Procedures and Model Performance Validation 3.4 Build Web Predictor for URL Categorization 3.5 Experimental Settings 4 Visualization, Performance Evaluation and Results 4.1 Datasets 4.2 Experiment with Lexical Features (Dataset1) 4.3 Experiment with Domain and Lexical Features (Dataset2) 4.4 Web Application for Prediction 5 Analysis and Results 6 Conclusion References Comparative Performance of Maximum Likelihood and Minimum Distance Classifiers on Land Use and Land Cover Analysis of Varanasi District (India) 1 Introduction 2 Literature Review 3 Materials and Methods 3.1 Image Data Sets 3.2 Image Data Processing 3.3 Image Classification 4 Experimental Results and Discussions 5 Conclusion References Recent Trends and Open Challenges in Blind Quantum Computation 1 Introduction 2 Preliminaries 3 Quantum Cryptography 3.1 Blind Quantum Computation 3.2 Single-Server Protocols 3.3 Multi-server Protocols 3.4 Verification in Blind Quantum Computation 3.5 Authentication in Blind Quantum Computation 3.6 Circuit-Based Blind Quantum Computation 3.7 Hybrid Models of Computation 3.8 Application of Blind Quantum Computing in Newer Domains 4 Conclusion References Driving Style Prediction Using Clustering Algorithms 1 Introduction 2 Literature Review 3 Design Details and Proposed Algorithm 4 Model Construction and Implementation 5 Results and Discussion 6 Conclusion and Future Work References Analyzing Fine-Tune Pre-trained Models for Detecting Cucumber Plant Growth 1 Introduction 2 Related Work 3 Proposed Models 3.1 Transfer Learning 3.2 Fine Tuned/Proposed Models 4 Results and Discussions 4.1 Dataset 4.2 Results 5 Conclusion and Future Work References Home Occupancy Estimation Using Machine Learning 1 Introduction 2 Methodology 2.1 Data Preprocessing and Scaling 2.2 Machine Learning Algorithms 3 Experiments and Results 3.1 Logistic Regression 3.2 K-Nearest Neighbor 3.3 Support Vector Machine (RBF Kernel) 3.4 Support Vector Machine (Linear Kernel) 3.5 Naive Bayes 3.6 Decision Tree 3.7 Random Forest 4 Conclusion and Future Scope References A Prediction Model with Multi-Pattern Missing Data Imputation for Medical Dataset 1 Introduction 1.1 Motivation 2 Contribution 2.1 Background 3 Materials and Methods 3.1 Dataset Description 3.2 Proposed Method 4 Results and Discussion 4.1 Experimental Setting 4.2 Evaluation of Experiment 5 Conclusion References Impact Analysis of Hello Flood Attack on RPL 1 Introduction 1.1 RPL Overview 2 Literature Review 3 Attacks on RPL Protocol 3.1 Type of Attack on RPL 4 Experimental Tool and Simulation Environment 4.1 Simulation Scenario 5 Result Analysis and Discussion 6 Conclusion References Classification of Quora Insincere Questionnaire Using Soft Computing Paradigm 1 Introduction 2 Literature Review 3 Problem Formulation 4 Experimental and Results 5 Conclusions and Future Work References Conventional Feature Engineering and Deep Learning Approaches to Facial Expression Recognition: A Brief Overview 1 Introduction 2 Related Work 3 Review Analysis of Facial Expression Dataset 4 Review of Feature Engineering Technique 4.1 Gaussian Mixture Model 4.2 Local Binary Pattern (LBP) Based Features 4.3 Gabor Filter Feature Extraction Technique 4.4 SIFT-Scale Invariant Feature Transform 4.5 Histogram of Oriented Gradient (HOG) Feature Extraction 4.6 Discrete Wavelet Transform (DWT) 4.7 Principle Component Analysis (PCA) 4.8 Deep-Learning Feature Engineering 5 Performance Analysis of Different FER Systems 5.1 Conventional Learning-Based FER Analysis 5.2 Deep Learning-Based FER Analysis 6 Conclusions References Forecasting of Rainfall Using Neural Network and Traditional Almanac Models 1 Introduction 2 NARNN Model 2.1 Activation Functions 3 Activation Functions Based Hybrid NARNN Model for Rainfall Data 4 Result and Discussion 5 Conclusion References Retinal Blood Vessel Segmentation Based on Modified CNN and Analyze the Perceptional Quality of Segmented Images 1 Introduction 2 Related Work 3 Material and Methods 3.1 Preprocessing and Image Augmentation 3.2 Feature Extraction Using Modified Gaussian Filter 3.3 Segmentation Using U-Net Architecture 3.4 Classification 4 Performance Metrics 5 Result Analysis 6 Comparative Analysis 7 Conclusion and Future Scope References Heuristics for K-Independent Total Traveling Salesperson Problem 1 Introduction 2 Problem Definition 3 Proposed Heuristics for KITTSP 3.1 First Heuristic (H1) 3.2 Second Heuristic (H2) 3.3 Third Heuristic (H3) 3.4 Fourth Heuristic (H4) 3.5 Fifth Heuristic (H5) 3.6 Sixth Heuristic (H6) 4 Computational Results 5 Conclusion and Future Work References A Comparative Study and Analysis of Time Series Forecasting Techniques for Indian Summer Monsoon Rainfall (ISMR) 1 Introduction 2 Data-Set Description and Statistical Analysis 3 Time Series Based Forecasting of ISMR with Deep Learning 4 Model Architecture 4.1 Multi-layer Perceptron 4.2 Convolutional Neural Networks 4.3 Long Short Term Memory 4.4 Deep and Wide Monsoon Rainfall Prediction Model(DWRPM) 5 Experimental Setup 5.1 Data Preprocessing 5.2 Implementation Details 5.3 Training and Test Sets 5.4 Evaluation Metrics 5.5 Model Training 6 Results 6.1 Multi-layer Perceptron 6.2 Convolutional Neural Networks 6.3 Long Short Term Memory 6.4 Deep and Wide Monsoon Rainfall Prediction Model 7 Conclusion and Future Work 7.1 Scope of Further Work References YOLOv4 Vs YOLOv5: Object Detection on Surveillance Videos 1 Introduction 2 Related Work 2.1 Region-Based Approach 2.2 Region-Free Approach 3 Methods 3.1 YOLOv4 3.2 YOLOv5 4 Experimental-Setup 4.1 Data Annotations 4.2 Training and Validation 4.3 Evaluation Metrics 4.4 Results 5 Conclusion and Future Scope References Author Index