Innovations in Intelligent Computing and Communication : First International Conference, ICIICC 2022, Bhubaneswar, Odisha, India, December 16-17, 2022, Proceedings

This book contains the papers presented at the First International Conference on Innovations in Intelligent Computing and Communication, ICIICC 2021, held in Bhubaneswar, Odisha, India, in December, 2022. The 31 full papers presented were thoroughly reviewed and selected from 78 submissions. They are divided in three tracks with the following topics: ​Intelligent Computing; Communications; and Machine Learning and Data Analytics. Preface Organization Keynote Address Industry 4.0 Meets Data Science: The Pathway for Society 5.0 Continual Learning for Intelligent Systems in Changing Environments Where is the Research on Evolutionary Multi-objective Optimization Heading to? Designing a Software Framework Based on an Object Detection Model and a Fuzzy Logic System for Weed Detection and Pasture Assessment An Overview of Machine Learning Based Intelligent Computing and Applications Semisupervised Learning with Spatial Information and Granular Neural Networks IoT Based General Purpose Sensing Application for Smart Home Environment Emerging Topics in Wireless and Network Communications – A Standards Perspective Emerging Topics in Wireless and Network Communications – A Standards Perspective Contents Intelligent Computing Ensemble Learning Model for EEG Based Emotion Classification 1 Introduction 2 Related Works 3 System Model and Methodology 3.1 Feature Extraction 3.2 Deep Learning Model Implementation 4 Dataset Description 5 Experimental Setup and Results 6 Conclusion References Foundation for the Future of Higher Education or ‘Misplaced Optimism’? Being Human in the Age of Artificial Intelligence 1 Introduction 2 Education Using Artificial Intelligence (AIEd) 3 Methods 3.1 Search Strategy 3.2 Reliability of Agreement Amongst Raters 3.3 Collection, Codification, and Analysis of Data 3.4 Limitations 4 Results 4.1 Forecasting and Characterising 4.2 Curriculum Technology that Uses Artificial Intelligence 4.3 Constant Re-Evaluation 4.4 A System that May Change to Fit the USER’S Needs 5 Conclusion and Way Forward References AI Enabled Internet of Medical Things Framework for Smart Healthcare 1 Introduction 2 AI Based IoMT Health Domains 3 AI Enabled IoMT Architectures for Smart Healthcare Systems 4 Research Challenges of AI Enabled Smart Healthcare Systems 4.1 Data Accuracy 4.2 Data Security 4.3 System Efficiency 4.4 Quality of Service 5 Conclusion References Metaverse and Posthuman Animated Avatars for Teaching-Learning Process: Interperception in Virtual Universe for Educational Transformation 1 Introduction 2 Objectives of the Research and Knowledge Gap 3 Methods and Methodology 4 Results and Discussion 4.1 Educational Metaverse: A Categorical Analysis 4.2 A Wide Variety of Virtual Worlds for Use in Education 4.3 Situations for Learning, Tiers of Education, and VR Learning Environments 4.4 Students’ Avatars (Digital Personas) in the Metaverse 4.5 Alterations in Educational Multiverse 5 Conclusion and Way Forward References Tuning Functional Link Artificial Neural Network for Software Development Effort Estimation 1 Introduction 2 Functional Link ANN-based SDEE 2.1 Justification of the Use of Chebyshev Polynomial as the Orthogonal Basis Function 3 Swarm Intelligence-Based Learning Algorithms for the CFLANN 3.1 Classical PSO 3.2 Improved PSO Technique 3.3 Adaptive PSO 3.4 GA 3.5 BP 4 Performance Evaluation Metrics 5 Description of the Dataset 6 Experiments and Results 7 Conclusion and Future Work References METBAG – A Web Based Business Application 1 Introduction 2 Literature Review 2.1 Gaps and Solutions 2.2 Deep Neural Networks (DNN) and LSTM 3 Architecture of the System 3.1 Architecture of the User Side of the System 3.2 Architecture of the Admin Side of the System 4 Workflow Diagrams 5 Procedures 5.1 Procedure: Price Prediction 5.2 Procedure: Password Security 5.3 Procedure: Dashboard 6 Result Analysis 6.1 Price Prediction 6.2 Password Security 7 Conclusions and Future Work References Designing Smart Voice Command Interface for Geographic Information System 1 Introduction 1.1 Review of Literature on Voice Command Interface 2 Design and Implementation 2.1 Review of Literature on Voice Command Interface 2.2 Modules Used 2.3 Methodology 2.4 Implementation 3 Results and Discussion 3.1 Testing Model by Creating a War Zone like Environment 3.2 Spectrogram and Waveform Samples for Spoken Voice 3.3 Comparative Analysis Based on Word Error Rate 4 Conclusion References Smart Garbage Classification 1 Introduction 2 Literature Review 2.1 Gaps in Literature 3 System Details 3.1 Waste Scanning Through Camera 3.2 Waste is Segregated and the Lid Opens 3.3 Moving of Hands and Trash Being Put into Respective Compartment 4 Component Modules and Description 5 Algorithmic Steps 6 Result and Analysis 7 Conclusions References Optical Sensor Based on MicroSphere Coated with Agarose for Heavy Metal Ion Detection 1 Introduction 2 Sensing Principle 3 Sensor Design 4 Results and Discussions 5 Conclusion References Influential Factor Finding for Engineering Student Motivation 1 Introduction 2 Related Studies 3 Experiment 3.1 Logistic Regression 4 Discussion 5 Conclusion References Prediction of Software Reliability Using Particle Swarm Optimization 1 Introduction 2 Related Work 3 Reliability Prediction Algorithm Using PSO 4 Experimental Result and Comparison 5 Conclusions References An Effective Optimization of EMG Based Artificial Prosthetic Limbs 1 Introduction 2 Literature Review 3 Design and Manufacturing 3.1 Cad Model 3.2 Manufacturing and Assembly 4 Electrical Components and Design 4.1 Electromyography Sensing 5 Artificial Intelligence 5.1 Gesture Recognition 5.2 Grasping Capacity (According to Size) 5.3 Analysis of EMG Signals 6 Conclusion References Communications Performance Analysis of Fading Channels in a Wireless Communication 1 Introduction 2 Fading Channels 2.1 Performance Analysis of Rayleigh Fading 2.2 Description of the Performance of Rician Fading Channel 2.3 Performance Analysis of NAKAGAMI-M Fading Channel. 3 Experimentation and Result Analysis 3.1 Simulation and Discussion of Rayleigh Fading Channel 3.2 Simulation Results of Rician Fading Channel 3.3 Simulation Results of Nakagami-M Fading Channel 4 Conclusion References Power Conscious Clustering Algorithm Using Fuzzy Logic in Wireless Sensor Networks 1 Introduction 2 Related Works 3 Proposed Model 4 Simulation Setup and Evaluation 5 Conclusions References Cryptanalysis on ``An Improved RFID-based Authentication Protocol for Rail Transit'' 1 Introduction 1.1 Motivation and Contribution 1.2 Organization of the Paper 2 Preliminary 2.1 Secure Requirements 2.2 Threat Model 3 Review of Zhu et al.'s Protocol 3.1 Set up Phase 3.2 Authentication Phase 4 Weakness of Zhu et al.'s Protocol 4.1 Known Session-Specific Temporary Information Attack 4.2 Lack of Scalability 5 Conclusion References A Novel Approach to Detect Rank Attack in IoT Ecosystem 1 Introduction 2 Background 2.1 Generic IoT Network Architecture 2.2 RPL Protocol 2.3 Rank Attack in IoT 2.4 IDS for IoT Ecosystem 3 Related Work 4 Proposed Security Approach 4.1 Proposed Approach Assumption 4.2 Security Model 4.3 Proposed Rank Attack Detection Solution 5 Experiments and Results Analysis 5.1 Setup and Execution of Experiments 5.2 After Proposed Security Solution Implementation Performance Analysis 5.3 Comparison of the Suggested Security Solution to Similar Works 6 Conclusion References Energy Efficient Adaptive Mobile Wireless Sensor Network in Smart Monitoring Applications 1 Introduction 2 Related Works 3 Proposed Method 3.1 Mobile Sensor Node Architecture 4 Simulation and Result Analysis 4.1 Simulation Set Up 4.2 Experimental Analysis 5 Conclusion References Orthogonal Chirp Division Multiplexing: An Emerging Multi Carrier Modulation Scheme 1 Introduction 2 Compatibility with OFDM 3 Computational Complexity 3.1 Computational Complexity of OCDM 3.2 Computational Complexity of OFDM 4 Applications of OCDM 4.1 OCDM for Wireless Communication 4.2 OCDM for Optical Fiber Communication 4.3 OCDM for IM/DD Based Short Reach Systems 4.4 OCDM for Underwater Acoustic Communication 4.5 OCDM for Baseband Data Communication 4.6 OCDM for MIMO Communication 5 Simulation Results 6 Conclusion References Machine Learning and Data Analytics COVID-19 Outbreak Estimation Approach Using Hybrid Time Series Modelling 1 Introduction 2 Background 2.1 LSTM Network for Modelling Time Series 2.2 ARIMA Model 2.3 Seasonal ARIMA Model 3 Proposed Model 4 Implementation and Results Discussion 4.1 Prediction Using LSTM Model 4.2 Prediction Using ARIMA Model 4.3 Prediction Using Hybrid Model 5 Conclusion References Analysis of Depression, Anxiety, and Stress Chaos Among Children and Adolescents Using Machine Learning Algorithms 1 Introduction 1.1 Background 1.2 Motivation and Objective of the Work 2 Literature Review 3 Methodology 3.1 Data Set Description 3.2 Implementation 4 Results and Discussion 4.1 Classification Results for Depression 4.2 Classification Results for Anxiety 4.3 Classification Results for Stress 4.4 Cross-Validation Results for Depression, Anxiety, and Stress Behaviour 5 Future Work 6 Conclusions References Sentiment Analysis from Student Feedbacks Using Supervised Machine Learning Approaches 1 Introduction 2 Background 3 Machine Learning Approaches 3.1 Naive Bayes Model 3.2 Support Vector Machine (SVM) 3.3 N-gram Based Character Language Model 3.4 Maximum Entropy 4 Experimentation and Results 4.1 Data Corpus Description 4.2 Preprocessing 4.3 Feature Extraction 4.4 Evaluation Metrics 4.5 Result Analysis 5 Conclusion and Future Work References Machine Learning Algorithms for Diabetes Prediction 1 Introduction 2 Related Works 3 Proposed Methodology 3.1 Description of Dataset 3.2 Classification Algorithms 4 Results and Discussion 4.1 Performance Measure 5 Conclusion References CRODNM: Chemical Reaction Optimization of Dendritic Neuron Models for Forecasting Net Asset Values of Mutual Funds 1 Introduction 2 Methodologies 2.1 DNM 2.2 CRODNM Based Forecasting 3 Experiments, Outcomes and Analysis 3.1 Collection and Statistical Summary of Data 3.2 Model Input Preparation and Normalization 3.3 Experimental Design 3.4 Analysis of Experimental Results 4 Conclusions and Further Scope References Machine Learning Approaches and Particle Swarm Optimization Based Clustering for the Human Monkeypox Viruses: A Study 1 Introduction 2 Machine Learning for Monkey Pox Virus 2.1 Screening and Treatment 2.2 Contact Tracing 2.3 Prediction and Forecasting 2.4 Drug Design and Molecular Research 3 PSO Clustering for the Human Monkeypox Viruses 3.1 Introduction to Particle Swarm Optimization (PSO) 3.2 Clustering Based on PSO 4 Existing Challenges and Vaccination 5 Summary and Discussion 6 Conclusion References Machine Learning-Based Hybrid Feature Selection for Improvised Network Intrusion Detection 1 Introduction 1.1 Related Work 2 Materials and Methods 2.1 Dataset Description 2.2 Data Pre-processing 2.3 Dimension Reduction 2.4 Model Evaluation 2.5 Evaluation Metrics 3 Results and Discussion 3.1 Classifier Comparison 3.2 Analysing the Current State of Knowledge in Comparison to the Approach that Was Suggested 3.3 Evaluation of Performance Based on the Elimination of Unnecessary Features 4 Conclusion References Application of Efficient Feature Selection and Machine Learning Algorithms in Mental Health Disorder Identification 1 Introduction 2 Background 3 Data Exploration 4 Mathematical Modeling of Feature Selection 4.1 Feature Selection Using LASSO 4.2 Feature Selection Using RFECV 4.3 Feature Selection Using RFE 4.4 Feature Selection Using Associative Property of Union 4.5 Feature Selection Using Associative Property of Intersection 4.6 Feature Selection Using Distributive Property 5 Implementation of Classification Algorithms 5.1 Classification with LASSO 5.2 Classification with RFECV 5.3 Classification with RFE 5.4 Classification with Feature Selection Using Associative Property of Union 5.5 Classification with Feature Selection Using Associative Property of Intersection 5.6 Classification with Feature Selection Using Distributive Property 6 Results and Discussions 7 Conclusion References A Survey on Sentimental Analysis of Student Reviews Using Natural Language Processing (NLP) and Text Mining 1 Introduction 2 Related Work: A Literature Review 3 Methodology 3.1 Datasets 3.2 Approach 4 Research Challenges and Future Directions 5 Conclusions References Rice Yield Estimation Using Deep Learning 1 Introduction 2 Literature Review 3 Problem Statement 4 Proposed Model 5 Results and Discussion 6 Conclusion References: Sentiment Analysis on Movie Review Data Using Ensemble Machine Learning Approaches 1 Introduction to Sentiment Analysis 2 Recent Work 3 Proposed Methodology 3.1 Naïve Bayes Algorithm 3.2 Logistic Regression 3.3 Random Forest Classifier 3.4 Multinomial Naïve Bayes Classifier 3.5 Support Vector Machine 3.6 Stochastic Gradient Descent Classifier 4 Performance Measurement Parameter 5 Result Analysis 6 Conclusion and Future Work References Comparative Analysis of COVID 19 Detection from Cough Speech Using Machine Learning Classifiers 1 Introduction 1.1 Related Works 2 Methodology 2.1 Databases 2.2 Feature Extraction 2.3 Machine Learning Classifiers 2.4 Experimental Setup 3 Result and Discussion 4 Conclusion References Classification of High-Resolution Satellite Image with Content Based Image Retrieval and Local Binary Pattern 1 Introduction 2 Background and Related Work 3 System Model and Methodology 3.1 Color Feature Extraction 3.2 Image Pre-processing 3.3 Block Based CBIR 4 Result and Discussions 5 Conclusion References Author Index