Note: Intro -- ICAIHC Committee -- Preface -- Acknowledgements -- Contents -- About the Editors -- 1 An Adaptive Fuzzy-Based Clustering Model for Healthcare Wireless Sensor Networks -- 1.1 Introduction -- 1.1.1 Resource Management in WSN -- 1.2 Related Work -- 1.3 Proposed Model -- 1.3.1 Fuzzy Sets and Neuro-fuzzy Logic Theory -- 1.4 Simulation and Results -- 1.5 Conclusion and Future Work -- References -- 2 Artificial Pancreas (AP) Based on the JAYA Optimized PI Controller (JAYA-PIC) -- 2.1 Introduction -- 2.2 Problem Statements Formulations -- 2.2.1 Clinical Information -- 2.2.2 Simulation Model -- 2.2.3 MID -- 2.2.4 Patient Output -- 2.3 Control Algorithms -- 2.3.1 Development of JAYA-PIC -- 2.4 Results -- 2.4.1 JAYA-PIC Action in Patient -- 2.4.2 Analysis of Control Actions -- 2.5 Conclusions -- References -- 3 Security Issues and Solutions for Reliable WBAN-Based e-Healthcare Systems: A Systematic Review -- 3.1 Introduction -- 3.2 Methodology -- 3.3 Secured WBAN Requirements -- 3.3.1 Security Paradigms for WBAN -- 3.3.2 Security Needs in WBAN -- 3.4 Security Solutions -- 3.5 Case Studies on WBAN Prototypes -- 3.6 Conclusion -- References -- 4 Brain Tumour Detection by Multilevel Thresholding Using Opposition Equilibrium Optimizer -- 4.1 Introduction -- 4.2 Multilevel Thresholding Based on Entropy -- 4.2.1 Multilevel Thresholding: A Mathematical Approach -- 4.2.2 Entropy Functions -- 4.3 Opposition Equilibrium Optimizer (OEO) -- 4.4 Proposed Brain Tumour Detection Method Using OEO-Based Multilevel Thresholding Approach -- 4.5 Results and Discussion -- 4.6 Conclusion -- References -- 5 RescuePlus -- 5.1 Introduction -- 5.2 Literature Review -- 5.3 Existing Solution -- 5.4 Proposed Solution -- 5.5 Result -- 5.6 Future Scope -- 5.7 Conclusion -- References -- 6 Skeletal Bone Age Determination Using Deep Learning -- 6.1 Introduction -- 6.2 Methodology. , 6.2.1 Data Set Selection -- 6.2.2 Data Pre-processing -- 6.3 Custom Model -- 6.3.1 Model Architecture -- 6.3.2 Approaches -- 6.4 Experiments -- 6.4.1 Loss Functions -- 6.4.2 Comparing with Pre-trained Models -- 6.5 Conclusion -- References -- 7 Chimp Optimization Algorithm-Based Feature Selection for Cardiac Image-Based Heart Disease Diagnosis -- 7.1 Introduction -- 7.2 Chimp Optimization Algorithm-Based Feature Selection for Heart Disease Diagnosis -- 7.2.1 Pre-processing -- 7.2.2 Feature Extraction -- 7.2.3 Feature Selection Using ChOA -- 7.2.4 Classification Using SVNN -- 7.3 Results and Discussion -- 7.4 Conclusion -- References -- 8 The Hospitality Industry's Impact on the COVID-19 Epidemic: A Case Study of Ukraine -- 8.1 Introduction -- 8.2 Literature Review -- 8.3 Research Methods -- 8.4 Results -- 8.4.1 State and Legal Measures -- 8.5 Conclusion -- References -- 9 Society in Front of a COVID-19 Pandemic: India Versus Ukraine -- 9.1 Introduction -- 9.1.1 Research Background -- 9.2 Research Methods and Materials -- 9.3 Results -- 9.3.1 The Speed of Virus Spreading -- 9.3.2 The Risk and Danger Rate Estimation -- 9.4 The Level of Trust in the National Healthcare System and the Satisfaction of Government's Response to COVID-19 Situation -- 9.5 The Emotions and General Psychological State of Respondents -- 9.6 Conclusions -- Notes -- References -- 10 Breast Cancer Detection Using Concatenated Deep Learning Model -- 10.1 Introduction -- 10.2 Proposed Methodology -- 10.2.1 Convolutional Neural Network -- 10.2.2 LSTM -- 10.3 Result Analysis -- 10.3.1 Dataset Description -- 10.4 Conclusion -- References -- 11 Recommendation of Pesticides Based on Automation Detection of Citrus Fruits and Leaves Diseases Using Deep Learning -- 11.1 Introduction -- 11.2 Related Work -- 11.3 Proposed Work -- 11.3.1 Image Acquisition and Preprocessing. , 11.3.2 Image Segmentation -- 11.3.3 Diseases Prediction -- 11.3.4 Experimental Results -- 11.3.5 Fertilizer Recommendation -- 11.4 Conclusion -- References -- 12 Comprehensive Information Retrieval Using Fine-Tuned Bert Model and Topic-Assisted Query Expansion -- 12.1 Introduction -- 12.2 Review of Literature -- 12.3 Comprehensive Information Retrieval -- 12.3.1 BERT Model -- 12.3.2 Topic Modelling Using Latent Dirichlet Allocation -- 12.3.3 The Proposed CIR Architecture -- 12.4 The Proposed Approach -- 12.5 Experimental Results -- 12.5.1 Dataset -- 12.5.2 Evaluation Metrics -- 12.5.3 Performance Evaluations -- 12.5.4 Performance Comparison -- 12.5.5 Discussions -- 12.6 Conclusion -- References -- 13 Diabetic Retinopathy Detection Using CNN Model -- 13.1 Introduction -- 13.2 Related Work -- 13.3 Dataset Used -- 13.3.1 Overview -- 13.3.2 Augmentation -- 13.4 Defining CNN Model -- 13.4.1 Summary of Model Architecture -- 13.4.2 Model Layers -- 13.4.3 Loss Function -- 13.5 Result -- 13.6 Conclusion -- References -- 14 Digi-CANE-An IoT Savior for Visually Sensitive -- 14.1 Introduction -- 14.2 Literature Survey -- 14.3 Objective -- 14.4 General Flowchart -- 14.5 The Sensory Architecture -- 14.5.1 Emergency Sensor (Gyroscope) -- 14.5.2 Cane Module -- 14.5.3 Ultrasonic Sensor -- 14.5.4 Buzzer -- 14.5.5 Arduino Uno -- 14.5.6 Working -- 14.6 Circuit Diagram -- 14.6.1 Hardware Details -- 14.6.2 Working of Ultrasonic Sensor (HC-SR04) -- 14.6.3 Software Requirement Arduino IDE -- 14.7 Conclusion and Future Scope -- References -- 15 Link Performance in Community Detection Using Social Network -- 15.1 Introduction -- 15.2 Literature Review -- 15.3 Methods -- 15.4 Metrics -- 15.5 Experimental Results -- 15.6 Discussion -- 15.7 Conclusion -- References -- 16 Analyze Ego-Centric Nodes in Social Network Using Machine Learning Technique -- 16.1 Introduction. , 16.2 Review of Literature -- 16.3 Materials and Method -- 16.4 Link Influence Strategies -- 16.5 Result and Discussion -- 16.6 Conclusion -- 16.7 Future Enhancement -- References -- 17 5G Revolution Transforming the Delivery in Healthcare -- 17.1 Introduction -- 17.2 Literature Review -- 17.3 Features of 5G Technology -- 17.4 Problems Posed by Current Healthcare Industry -- 17.4.1 Lack of Universal Access -- 17.4.2 Long-Term Chronic Care Burden -- 17.4.3 Aging Population -- 17.4.4 Resource Constraints and Healthcare Disparities -- 17.5 Areas in Healthcare that 5G Will Boost -- 17.5.1 Imaging -- 17.5.2 Diagnostics -- 17.5.3 Data Analytics and Treatment -- 17.6 New Realms that 5G Will Enable -- 17.7 Real-World Trials -- 17.8 Positive Impacts of 5G on Our Healthcare System -- 17.9 Recommendations -- 17.10 Conclusion and Future Works -- References -- 18 A Systematic Review of AI Privileges to Combat Widen Threat of Flavivirus -- 18.1 Significance of AI in Flavivirus Disease Eradication -- 18.1.1 AI in Healthcare -- 18.1.2 Flavivirus-A Detailed Synopsis -- 18.1.3 Flavivirus Characteristics -- 18.1.4 Flavivirus Lifecycle -- 18.1.5 Flavivirus Epidemiology -- 18.2 Detection and Estimation of Flavivirus Disease with Machine Learning Models -- 18.3 Conclusions and Future Direction -- References -- 19 Early Detection of Sepsis Using LSTM Neural Network with Electronic Health Record -- 19.1 First Section -- 19.2 Method -- 19.2.1 Sepsis Data Preprocessing -- 19.2.2 LSTM Model -- 19.3 Result and Discussion -- 19.4 Conclusion -- References -- 20 Detection of COVID-19 Infection from Clinical Findings Using Machine Learning Algorithm -- 20.1 Introduction -- 20.2 Related Works -- 20.3 Materials and Methods -- 20.3.1 Medical Dataset Used -- 20.3.2 Data Preprocessing -- 20.3.3 Feature Selection -- 20.3.4 Classification Algorithms. , 20.4 Performance Evaluation and Results -- 20.4.1 Evaluation Measures -- 20.4.2 Results -- 20.5 Conclusion -- References -- 21 Development of Real-Time Cloud Based Smart Remote Healthcare Monitoring System -- 21.1 Introduction -- 21.2 System Framework -- 21.3 System Modeling -- 21.4 Results and Discussion -- 21.5 Conclusion -- References -- 22 Performance Analysis of Hyperparameters of Convolutional Neural Networks for COVID-19 X-ray Image Classification -- 22.1 Introduction -- 22.2 CNN and Its Optimizers -- 22.3 Experimental Results -- 22.4 Conclusion -- References -- 23 Sequence Rule Mining for Insulin Dose Prediction Using Temporal Dataset -- 23.1 Introduction -- 23.2 Literature Review -- 23.3 Definitions -- 23.3.1 Sequential Rule Mining -- 23.3.2 Support and Confidence -- 23.3.3 Sequence Rule Mining Algorithms -- 23.4 Methodology -- 23.5 Experiment Work -- 23.5.1 Dataset Used -- 23.5.2 Result and Discussion -- 23.6 Conclusion -- 23.7 Future Scope -- References -- 24 Ensemble Deep Learning Approach with Attention Mechanism for COVID-19 Detection and Prediction -- 24.1 Introduction -- 24.2 Related Work -- 24.3 Proposed Model -- 24.4 Data sets, Experiments, and Results -- 24.5 Conclusion and Future Scope -- References -- 25 Semantic Segmentation of Cardiac Structures from USG Images Using Few-Shot Prototype Learner Guided Deep Networks -- 25.1 Introduction -- 25.2 Proposed Work -- 25.2.1 Prototype Learner -- 25.2.2 Segmentor -- 25.3 Experiments -- 25.3.1 Dataset Description and Measures Used -- 25.3.2 Parameters -- 25.3.3 Results and Analysis -- 25.4 Conclusion -- References -- 26 Quantification of Homa Effect on Air Quality in NCR, India: Pollution and Pandemic Challenges in Cities and Healthcare Remedies -- 26.1 Introduction -- 26.1.1 Air Quality Global Challenge in Twenty-First Century -- 26.1.2 How Yajna and Vedic Rituals May Curb Pollution. , 26.2 Literature Review.

Note: Intro -- Preface -- Editorial -- Contents -- About the Editors -- 1 Introduction to Blockchain Evolution, Architecture and Application with Use Cases -- 1.1 Layman's Introduction to Blockchain -- 1.2 The Blockchain Technology -- 1.3 Types of Blockchain -- 1.4 Evolution of Blockchain -- 1.4.1 Blockchain 1.0: Programmable Money and Cryptocurrencies -- 1.4.2 Blockchain 2.0: Smart Contracts -- 1.4.3 Blockchain 3.0: Decentralised Web -- 1.5 Ledger System for Blockchain -- 1.5.1 Centralized Ledger Systems -- 1.5.2 Distributed Ledger Systems -- 1.6 Layers of Blockchain -- 1.6.1 Hardware or Infrastructure Layer -- 1.6.2 Data Layer -- 1.6.3 Network Layer -- 1.6.4 Consensus Layer -- 1.6.5 Application Layer -- 1.7 Use Cases and Applications of Blockchain -- 1.8 Development Tools for Blockchain -- 1.9 Summary -- References -- 2 Blockchain: A Technology in Search of Legitimacy -- 2.1 Introduction -- 2.2 Theoretical Background -- 2.3 Research Design and Methodology -- 2.4 Results -- 2.5 Discussion and Conclusion -- References -- 3 Using Blockchain in Intermittently Connected Network Environments -- 3.1 Introduction -- 3.2 Overview of Delay Tolerant Networks -- 3.2.1 Features -- 3.2.2 Architecture -- 3.2.3 Routing -- 3.2.4 Applications -- 3.3 Rudimentary Elements of Blockchain -- 3.3.1 Blocks -- 3.3.2 Transaction -- 3.3.3 Mining -- 3.3.4 Ethereum and Smart Contracts -- 3.4 Integration of Blockchain Technology with DTNs -- 3.4.1 System Components -- 3.4.2 Generation and Transmission of Shelter Needs -- 3.4.3 Need Validation and Creation of Local Blockchain -- 3.4.4 Block Conversion Through API -- 3.4.5 Mining Blocks and Deploying to Global Blockchain -- 3.5 Open Research Areas -- 3.6 Conclusion -- References -- 4 Slaying the Crypto Dragons: Towards a CryptoSure Trust Model for Crypto-economics -- 4.1 Introduction: Blockchain and the Right to Be Forgotten. , 4.2 The New 'Crypto-economy'-A Fraudsters' Playground? -- 4.3 Blockchain: Sceptical ICT Professionalism and Legal Due Diligence -- 4.4 The Need for Trusted Third Parties and for Probative Electronic Evidence -- 4.5 Towards a CryptoSure Trust Model for Crypto-economics -- 4.6 Conclusions: Blockchain Versus Trust-The Expert Issues in Disputes Over Crypto Assets -- 5 Decentralized Governance for Smart Contract Platform Enabling Mobile Lite Wallets Using a Proof-of-Stake Consensus Algorithm -- 5.1 Introduction -- 5.2 Preliminaries for Qtum Decentralized Blockchain Governance -- 5.3 Qtum Basic Requirement Sets for Decentralized Governance -- 5.3.1 UTXO Versus Account Model -- 5.3.2 Consensus Management -- 5.3.3 Mutualized Proof-of-Stake -- 5.3.4 AAL and EVM Integration -- 5.4 Scalability Extension of the Virtual Machine Through Decentralized Governance -- 5.4.1 Qtum Transaction Processing Using Virtual Machine -- 5.4.2 Decentralised Governance Protocol -- 5.5 Qtum Account Abstraction Layer -- 5.6 Discussion of the Technical Governance Realization -- 5.6.1 Hard fork Update -- 5.6.2 Qtum X86 Virtual Machine -- 5.7 Conclusions -- References -- 6 Blockchain Technology: Security and Privacy Issues -- 6.1 Introduction -- 6.2 Distributed Ledger Technology -- 6.2.1 Blockchain Benefits -- 6.2.2 How Blockchain Works -- 6.2.3 Consensus Algorithms -- 6.3 Blockchain Pros and Cons -- 6.4 Applications of Blockchain -- 6.4.1 Blockchain 1.0 -- 6.4.2 Blockchain 2.0 -- 6.5 Blockchain Security Issues -- 6.5.1 Cryptojacking Attacks -- 6.5.2 51% Attack -- 6.5.3 Smart Contract Attacks -- 6.6 Discussion -- 6.6.1 Voting and Blockchain -- 6.6.2 Energy and Blockchain -- 6.6.3 Web 3.0 and Blockchain -- 6.7 Conclusions -- References -- 7 Personal Data Protection in Blockchain with Zero-Knowledge Proof -- 7.1 Introduction -- 7.2 Related Works -- 7.3 Background About Blockchain. , 7.4 Personal Data Protection and Blockchain -- 7.5 Zero-Knowledge Proof on Blockchain -- 7.5.1 Zerocoin Protocol -- 7.5.2 Zerocash Protocol -- 7.5.3 Zcash and Zk-SNARK -- 7.6 Conclusion -- References -- 8 Design and Verification of Privacy Patterns for Business Process Models -- 8.1 Introduction -- 8.2 A Privacy-Aware System Using Blockchain -- 8.2.1 Scenario: A Cloud-Based Order System -- 8.3 GDPR Verification -- 8.3.1 Design Time Verification -- 8.3.2 Runtime Verification -- 8.4 Experimental Results -- 8.4.1 Evaluation of Design Time Verification -- 8.4.2 Evaluation of Runtime Verification -- 8.5 Conclusion -- References -- 9 Blockchain Technology in Energy Field: Opportunities and Challenges -- 9.1 Introduction -- 9.2 Blockchain Solutions for Energy Internet -- 9.3 Application Scenarios of Blockchain Technology in the Energy Industry -- 9.4 Challenges -- 9.5 Conclusions -- References -- 10 BlockChainTechnology for Energy Transition -- 10.1 Introduction -- 10.2 What Is the "Energy Transition"? -- 10.2.1 Business Models in the Energy Sector -- 10.2.2 New Business Models for Energy Transition -- 10.3 BlockChain and Smart Contracts in the Energy Sector -- 10.3.1 Types of Applications of BlockChain and Smart Contracts in the Energy Sector -- 10.3.2 New Business Models Enabled by BlockChain in the Energy Market -- 10.3.3 Risks and Issues Related to BlockChain and Smart Contracts -- 10.4 The Framework -- 10.4.1 The Business Model Canvas -- 10.4.2 The Use Case Selection -- 10.4.3 Impact Analysis of the Two Selected Use Cases -- 10.4.4 The Business Models for the Use Cases -- 10.4.5 Microgrid Business Model (Elaborated After the Workshop) -- 10.4.6 Discussion of the Results -- 10.5 Current Trends and Future Scenarios -- 10.5.1 P2P Distributed Energy Trading for Residential Microgrids. , 10.5.2 Bridging Industrial and Residential Microgrids Through Electric Vehicles -- 10.6 Conclusions -- References -- 11 The Feasibility and Significance of Employing Blockchain-Based Identity Solutions in Health Care -- 11.1 Introduction -- 11.2 A Brief History of Identities in the Digital Age -- 11.2.1 Fully Centralized Identity Management -- 11.2.2 Federated Identity Management -- 11.2.3 User-Centric Identity Management -- 11.3 The Main Ideas Behind Decentralized Identity Management -- 11.3.1 Decentralized Identifier Based on Blockchain -- 11.3.2 Zero-Knowledge Proof -- 11.3.3 Decentralized Blockchains and the Internet -- 11.4 The Technical Architecture of Decentralized Identity Management -- 11.4.1 Architecture Overview -- 11.4.2 Blockchain-Based DID Service -- 11.4.3 Standardization of DIDs -- 11.4.4 Examples of DID Frameworks -- 11.5 The Potential of Applying Blockchain-Based DID Solutions in Health Care -- 11.5.1 Addressing the Patient Mismatching Problem -- 11.5.2 Facilitating Patient Recruitment in Clinical Research Using DID -- 11.5.3 The Safer Use of Medical Devices -- 11.5.4 Limitations Facing Current Blockchain-Based DID Solutions -- 11.6 Conclusion -- References -- 12 Toward eHealth with Blockchain: Success Factors for Crowdfunding with ICOs -- 12.1 Introduction -- 12.2 Theoretical Background -- 12.2.1 eHealth -- 12.2.2 Initial Coin Offerings (ICOs) and Blockchain -- 12.2.3 Signaling Theory -- 12.3 Research Method -- 12.3.1 Related Work -- 12.4 Research Hypotheses -- 12.4.1 Data and Variables -- 12.5 Results and Discussion -- 12.5.1 Descriptive Statistics of the ICO Data -- 12.5.2 Multivariate Analysis of the Factors Influencing the Success -- 12.6 Discussion -- 12.7 Conclusion -- References -- 13 Blockchain Track and Trace System (BTTS) for Pharmaceutical Supply Chain -- 13.1 Introduction -- 13.2 Related Works. , 13.3 Overview of Bitcoin, Blockchain Platforms and Smart Contracts -- 13.4 The Proposal Model -- 13.4.1 Structure of Blockchain Track and Trace System (BTTS) -- 13.4.2 The Proposed Smart Contracts -- 13.5 Conclusion and Future Works -- References.

Note: Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- Data Science and Analytics -- Quality Index Evaluation Model Based on Index Screening Model -- 1 Introduction -- 2 Three-Parameter Interval Principal Component Analysis -- 2.1 Principal Component Analysis -- 2.2 Calculation Steps -- 2.3 M-PCA Three-Parameter Interval Principal Component Analysis -- 2.4 Calculation Steps -- 2.5 The Determination of Subjective Index Weight Based on Analytic Hierarchy Process -- 2.6 Index Evaluation -- 3 Analysis of Examples -- 4 Conclusion -- References -- Selection of Software Development Methodologies (SDMs) Using Bayesian Analysis -- 1 Introduction -- 2 Proposed Work -- 3 Proposed Model -- 3.1 Experimental Result -- 4 Conclusion -- 5 Future Scope -- References -- Role of Social Media in Employer Branding-A Study on Selected Engineering Colleges (Private) in Bhubaneswar -- 1 Introduction -- 2 Objective -- 3 Methodology -- 4 Literature Review -- 4.1 Employer Branding -- 5 Cases of Private Institute -- 5.1 Case 1: Institute of Technical Education and Research, SOA University, Bhubaneswar -- 5.2 Case 2: Centurion University of Technology and Management (CUTM), Bhubaneswar -- 5.3 Case 3: Silicon Institute of Technology -- 5.4 Case 4: Gandhi Engineering College (GEC) Bhubaneswar -- 5.5 Case 5: Hi-Tech Institute of Technology (HIT), Bhubaneswar -- 6 Conclusion of the Study -- References -- A Novel Approach for Artifact Removal from Brain Signal -- 1 Introduction -- 2 Overview of Proposed Method -- 2.1 Kurtosis -- 2.2 Multiscale Entropy (MSE) -- 2.3 Artifact Channel Identification -- 2.4 Artifact Denoising -- 3 Results and Discussion -- 4 Conclusion -- References -- A Novel Approach to Heterogeneous Multi-class SVM Classification -- 1 Introduction -- 2 Literature Review -- 3 Classification Problem -- 4 Proposed Novel Approach for Heterogeneous Data. , 5 Experimental Results -- 6 Conclusion -- References -- An Empirical Study of Big Data: Opportunities, Challenges and Technologies -- 1 Introduction -- 2 Importance of Big Data -- 2.1 Importance to National Development -- 2.2 Importance to Industrialized Upgrades -- 2.3 Importance to Technical Research -- 2.4 Importance to Interdisciplinary Research -- 2.5 Importance to Better Predict the Future -- 3 Big Data Characteristics -- 3.1 Volume -- 3.2 Velocity -- 3.3 Variety -- 3.4 Veracity -- 3.5 Validity -- 3.6 Volatility -- 3.7 Value -- 4 Hadoop: Way to Process Big Data -- 4.1 Hadoop Distributed File System -- 4.2 MapReduce -- 5 Challenges of Big Data -- 5.1 Data Challenges -- 5.2 Processing Challenges -- 5.3 Management Challenges -- 6 Big Data Techniques -- 7 Big Data Hadoop-Based Tools -- 7.1 Apache Hadoop -- 7.2 Apache Mahout -- 7.3 Storm -- 7.4 S4 -- 7.5 Apache Kafka -- 8 Conclusion -- References -- Forecasting World Petroleum Fuel Crisis by Nonlinear Autoregressive Network -- 1 Introduction -- 2 Data Sources -- 3 Methodology -- 3.1 Time Series Prediction Using Artificial Neural Network (ANN) -- 3.2 Comparisons of General Prediction Models -- 3.3 Predictive Model Flow Control Diagram -- 3.4 Predictive Model Structure -- 4 Performance Measurement -- 5 Result and Analysis -- 6 Comparison and Discussion -- 7 Hypothesis Testing -- 8 Conclusion -- References -- Stock Market Price Prediction Employing Artificial Neural Network Optimized by Gray Wolf Optimization -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Dataset -- 3.2 Normalization -- 3.3 Artificial Neural Network -- 3.4 Gray Wolf Optimization -- 4 Proposed Approach -- 5 Experimental Setup and Simulation Result -- 6 Conclusion -- References -- Analysis of Techniques for Credit Card Fraud Detection: A Data Mining Perspective -- 1 Introduction -- 2 Literature Review. , 2.1 Dataset Collection -- 2.2 Various Methodology of Fraud Detection in Credit Card -- 3 Challenges in Credit Card Fraud Detection -- 4 Conclusion -- References -- Predictive Analytics for Weather Forecasting Using Back Propagation and Resilient Back Propagation Neural Networks -- 1 Introduction -- 2 Related Works -- 3 Supervised Learning Algorithms -- 4 Artificial Neural Network -- 4.1 Back Propagation Algorithm -- 4.2 Resilient Back Propagation -- 5 Results and Discussion -- 5.1 Backprop and Rprop Implemented in RStudio -- 5.2 Receiver Operating Characteristic Curve (ROC) and Area Under Curve (AUC) -- 5.3 ggplot -- 6 Conclusion -- Appendix -- References -- Analysis of the Leadership of Undergraduate Freshmen in Military Schools from the Perspective of Space -- 1 Introduction -- 2 Research Methods -- 2.1 Research Tools -- 2.2 Research Procedures -- 3 The Results Analysis -- 3.1 Reliability and Validity Test -- 3.2 Overall Analysis of Leadership -- 3.3 Analysis of the Correlation Between Leadership and Per Capita Income -- 3.4 Analysis of the Correlation Between Leadership and Per Capita Income -- 4 Result Analysis -- 5 Concluding Remarks -- References -- Correlation Analysis for CSI300 Index Return and Realized Volatility -- 1 Introduction -- 2 Model Construction -- 2.1 Model Realized Estimate -- 2.2 Edge Distribution Model Construction -- 2.3 Construction of Time Change D-Vine Copula -- 3 Empirical Analysis -- 3.1 Characteristic Analysis -- 3.2 Parameter Estimation -- 3.3 Parameter Estimation for Continuous-Time Volatility and the Jump Volatility Models -- 3.4 Correlation Analysis -- 4 Conclusion -- References -- Prescription Basket Analysis: Identifying Association Rule Among Drugs in Prescription of Dentist in Bhubaneswar City -- 1 Introduction -- 2 Research Methodology -- 3 Data Analysis and Results -- 4 Conclusion -- References. , Decision Science and Management -- Impact of Decision Science on e-Governance: A Study on Odisha Land Records System -- 1 Introduction -- 1.1 e-Governance -- 1.2 Odisha Right to Public Services Act -- 2 Literature Review -- 2.1 Brainstorming -- 2.2 Committee Meetings -- 2.3 Delphi -- 2.4 Electronic Meeting -- 2.5 Survey -- 2.6 Decision Tree and Decision Tables -- 2.7 Game Theory -- 2.8 Simulation -- 3 Decision Science for e-Governance -- 3.1 Risk Analysis -- 3.2 Decision Analysis -- 3.3 Cost-Effectiveness Analysis -- 4 Key Findings of the Paper -- 5 Conclusion -- References -- HR Value Proposition Using Predictive Analytics: An Overview -- 1 Introduction -- 2 Data Analytics -- 2.1 Descriptive Analytics -- 2.2 Predictive Analytics -- 2.3 Prescriptive Analytics -- 3 Literature Review -- 3.1 HR Analytics -- 4 Findings and Discussion -- 4.1 Importance of Analytics in HR -- 5 Conclusions -- 6 Originality -- 7 Declaration -- References -- Determination of Time-Dependent Quadratic Demand by Using Optimal Ordering Policy, Salvage Value Under Partial Backlogging, Time-Proportional Deterioration, Time-Varying Holding Cost -- 1 Introduction -- 2 Assumptions -- 3 Modeling -- 3.1 Notations -- 3.2 Mathematical Formulation -- 4 Numerical Examples -- 5 Sensitivity Analysis -- 6 Conclusions -- References -- Inventory Control for Materials Management Functions-A Conceptual Study -- 1 Introduction -- 2 Review of the Literature -- 2.1 Inventory Management -- 2.2 Material Management -- 3 Conclusion -- References -- ACO-Based Secure Routing Protocols in MANETs -- 1 Introduction -- 2 Ant Colony Optimization -- 3 Security Aware ACO Routing Protocols -- 3.1 Secure Antnet Routing Algorithm for Scalable Ad Hoc Networks Using Elliptic Curve Cryptography -- 3.2 Secure Power Aware Ant Routing Algorithm -- 3.3 Swarm-Based Detection and Defence Technique. , 3.4 Detection and Prevention of Blackhole Attack in MANET Using ACO Routing -- 3.5 Autonomous Bio-inspired Public Key Management Protocol -- 3.6 ANT-Based Trustworthy Routing -- 3.7 Pair-Wise Key Agreement and Hop-by-Hop Authentication Protocol -- 4 Comparison and Analysis of Security Aware ACO Routing Protocols -- 5 Conclusion and Future Work -- References -- An Approach Toward Integration of Big Data into Decision Making Process -- 1 Introduction -- 2 Background -- 3 Challenges During Big Data Analytics for Decision Making -- 4 Integrated Framework of Big Data Analytics with Decision Making Process -- 4.1 Proposed Approach -- 5 Conclusion and Future Aspects -- References -- Big Data Analysis and Classification of Biomedical Signal Using Random Forest Algorithm -- 1 Introduction -- 2 Proposed Methodology -- 3 Preprocessing of the Signal -- 4 Feature Extraction -- 5 Random Forest -- 6 Classification Result -- 7 Conclusion -- References -- An Intelligent Framework for Analysing Terrorism Actions Using Cloud -- 1 Introduction -- 2 Motivation -- 3 Objective -- 4 Literature Review -- 5 Comparison of Models -- 6 Conclusion -- References -- Research on Optimization of J Company Warehouse Storage Process -- 1 Introduction -- 2 Analysis on the Current Situation of J Company -- 2.1 Warehouse Storage Process -- 2.2 Problems with Warehouse Storage Process -- 3 Optimized Warehouse Storage Process -- 4 Petri Net Model -- 5 Conclusion -- References -- The Influence of Psychological Contract on the Willingness to Share Tacit Knowledge -- 1 Introduction -- 2 Psychological Contract -- 2.1 Knowledge Sharing -- 2.2 Hypothesis -- 3 Method -- 3.1 Measurement Tools -- 4 Result -- 5 Hypothesis Testing -- 6 Discussion -- 7 Limitations and Future Research -- References -- Research on the Role of Government Management in Chinese Public Indemnificatory Housing System. , References.

Note: Intro -- Preface -- Contents -- About the Editors -- Internet of Things (IOT) -- An Energy-Efficient Data Routing in Weight-Balanced Tree-Based Fog Network -- 1 Introduction -- 1.1 Fog Computing -- 1.2 Tree-Based Architecture -- 1.3 Data Routing -- 1.4 Green Computing -- 2 Related Works -- 3 Proposed Architecture Towards Fog Networks -- 4 Discussions -- 5 Conclusions and Future Work -- References -- A Systematic Overview of Fault Tolerance in Cloud Computing -- 1 Introduction -- 2 Basic Components of Cloud Computing -- 3 Characteristics of Cloud Computing -- 4 Cloud Deployment Models -- 5 Cloud Service Models -- 6 Fault Tolerance -- 7 Fault Tolerance in Cloud Computing -- 7.1 Fault Tolerance Approaches -- 7.2 Fault Tolerance Parameters -- 8 Conclusion -- References -- An EPIC Mechanism for Advertising the Tourist Spots in Smart Cities -- 1 Introduction -- 2 Related Works -- 3 System Model and Problem Formulation -- 4 Tourist Spots Advertisement Problem: Posted Price Mechanism -- 4.1 Outline of PPM-TSAP -- 4.2 Detailing of PPM-TSAP -- 4.3 Illustrative Example -- 4.4 Running Time of PPM-TSAP -- 5 Conclusion and Future Work -- References -- Data Analysis and Prediction of Terror Component Using Web Services -- 1 Introduction -- 2 Background -- 2.1 Intrusion Detection System (IDS) -- 2.2 Vector Space Model -- 2.3 Receiver Operator Characteristic (ROC) Curve -- 3 Content-Based Detection of Terror-Related Activity -- 3.1 Detection Environment -- 4 Detection of Typical Terrorist Behavior -- 5 Experimental Settings -- 5.1 Evaluation Measure -- 6 Result Summarization -- 7 Deployment Issues -- 8 Conclusion -- References -- Facial Expression Recognition System (FERS): A Survey -- 1 Introduction -- 2 Related Work -- 3 Dataset Used -- 4 Discussion and Comparison of Results -- 5 Conclusion -- References. , Load Balancing of Tasks in Cloud Computing Using Fault-Tolerant Honey Bee Foraging Approach -- 1 Introduction -- 2 Literature Review -- 2.1 Load Balancing in Cloud Computing -- 2.2 Fault Tolerance in Cloud Computing -- 2.3 Honey Bee Behaviour Inspired Load Balancing -- 2.4 Motivation -- 3 Proposed Work and Implementation -- 4 Conclusion and Future Work -- References -- Flip Learning: A Novel IoT-Based Learning Initiative -- 1 Introduction -- 2 Related Works -- 3 Level-Based Approach -- 3.1 Collaborative Learning Within the Campus -- 3.2 Middle Product -- 3.3 Customized Learning Out of the Campus -- 4 Technical Aspects -- 4.1 Mix of IoT and Cloud -- 4.2 Information Management Framework -- 4.3 Content Delivery Network -- 4.4 Use of AI -- 4.5 Virtual and Augmented Reality -- 4.6 Data Security in Network -- 5 Conclusion -- References -- Improvement of Load Balancing in Shared-Memory Multiprocessor Systems -- 1 Introduction -- 2 Overview on Prior Algorithms and Techniques -- 2.1 Static Scheduling -- 2.2 Dynamic Scheduling -- 3 Result and Discussion -- 3.1 The Mandelbrot Set [3] -- 4 Conclusion -- References -- Building Amazon Web Services Infrastructure from the Scratch for an Organization -- 1 Introduction -- 2 Proposed Work and Implementation -- 3 Conclusion and Future Work -- References -- Fault Detection for VANET Using Vehicular Cloud -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Work -- 4 Simulation Result and Discussion -- 5 Conclusion and Future Scope -- References -- An Approach to Cohort Selection in Cloud for Face Recognition -- 1 Introduction -- 2 Literature Survey -- 3 Architecture of the Proposed Approach -- 4 Cohort Selection Mechanism -- 4.1 Feature Extraction -- 4.2 Finding of Match Score -- 5 Database and Results -- 6 Conclusion -- References. , Internet of Things (IoT) Framework Deployment Template for Cloud-Based Harbor Surveillance and Ferry Monitoring System -- 1 Introduction -- 2 Proposed System -- 3 Model Building -- 3.1 Data Set and Test -- 4 Discussions -- 5 Conclusion -- References -- Art of Style Transfer Using Convolutional Neural Network: A Deep Learning Approach -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset Used -- 2.2 Model for Image Classification -- 2.3 Convolutional Neural Network Training Process for Style Transfer -- 3 Experimental Results -- 3.1 Experimental Steps -- 4 Conclusion and Findings -- References -- Impact of Internet of Things (IoT) on 5G -- 1 Introduction -- 2 IoT Challenges -- 3 5G Challenges -- 4 5G Characteristics and Their Values/Applications -- 4.1 5G on IoT: A Single Network for Millions of Applications -- 4.2 The Importance of 5G on the IoT -- 4.3 Application of 5G Over IoT -- 5 The Impact of 5G on IoT -- 5.1 Establishing a 5G-IoT Ecosystem -- 5.2 Future of IoT -- 5.3 Aspects of IoT on Updated 5G Technologies -- 6 Conclusion -- References -- Prediction of Exchange Rate in a Cloud Computing Environment Using Machine Learning Tools -- 1 Introduction -- 2 Machine Learning Techniques Used for Prediction Modeling Data -- 2.1 Linear Regression -- 2.2 Regression Trees -- 2.3 Decision Tree Regression -- 2.4 Boosted Trees Regression -- 2.5 Random Forest Regression -- 2.6 Neural Network Regression -- 2.7 Cloud Computing Tools -- 3 Experimental Works -- 3.1 Data set Analysis -- 3.2 Result Analysis -- 4 Conclusion -- References -- Survey on Stock Price Forecasting Using Regression Analysis -- 1 Introduction -- 2 Literature Review -- 3 Regression -- 4 Regression Methodologies -- 4.1 Linear Regression -- 4.2 Polynomial Regression -- 4.3 Logistic Regression -- 4.4 Ridge Regression -- 4.5 Stepwise Regression -- 4.6 LASSO Regression. , 4.7 Elastic Net Regression -- 5 Conclusions -- References -- Intrusion Detection and Classification Using Decision Tree-Based Feature Selection Classifiers -- 1 Introduction -- 2 Intrusion Detection System -- 3 Data Mining-Based Approach -- 3.1 Decision Tree -- 3.2 Feature Selection -- 4 Dataset Used -- 5 Result Analysis -- 6 Conclusion -- References -- Role of Cloud Computing for Big Data: A Review -- 1 Introduction -- 2 Cloud Computing -- 2.1 Cloud Service Model -- 2.2 Cloud Deployment Model -- 2.3 Challenges and Issues of Cloud Computing -- 3 Big Data -- 3.1 Technologies Supported by Big Data -- 3.2 Challenges in Big Data -- 4 Conclusion -- References -- Role of Cloud Computing in Geotechnical Engineering -- 1 Introduction -- 2 Direct Role of Cloud Computing in Geotechnical Engineering -- 2.1 State-of-the-Art Cloud Computing -- 2.2 State of the Art Approaches for Geotechnical Cloud Computing -- 3 Cloud Computing and Parameter Identification Integrated in System Identification -- 3.1 System Identification -- 3.2 Component of SI -- 4 Inverse Analysis and Parameter Identification Supported by Cloud Computing -- 4.1 General Formulation of Parameter Identification Process -- 4.2 Inverse Analysis and Parameter Identification -- 5 Research Scope and Challenges -- 6 Conclusion -- References -- Energy-Efficient Clustering with Rotational Supporter in WSN -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Step 1-Clustering of Nodes -- 3.2 Step 2-Selection of CH -- 3.3 Step 3-Selection of NCH -- 3.4 Step 4-Selection of SCH -- 4 Simulation -- 5 Conclusion -- References -- A Review on Mobile Cloud Computing -- 1 Introduction -- 2 Need of MCC -- 3 Architecture -- 4 Background -- 4.1 Service Miniatures of MCC -- 4.2 Deployment Miniatures of MCC -- 5 Features of Mobile Cloud and Its Computing -- 5.1 Scalability -- 5.2 Mobility. , 5.3 Mobile Cyber Security with Privacy -- 5.4 Enhancing Reliability with Mobile Computing -- 5.5 Reduced Cost -- 5.6 Multiple Occupancy -- 5.7 Imbalance Web Transmission -- 6 Why Mobile Cloud Computing? -- 7 Issues in MCC -- 7.1 Scarcity of Mobile Appliances -- 7.2 Safety and Seclusion -- 7.3 Short Data Transferral Rate (Bandwidth) -- 7.4 Offloading -- 7.5 Quality of Communication and Broadcasting -- 8 Conclusion -- References -- Corroborating the Veracity of Body Fat Percentage and Classification of Sarcopenia Using Island Differential Evolution Algorithm -- 1 Introduction -- 2 Methodology -- 3 Optimization of the Formula and Techniques Used -- 4 Regression and Genetic Algorithm -- 5 Residuals and Goodness-of-Fit -- 6 Identification and Classification of Sarcopenia -- 7 Island Differential Evolution Algorithm -- 8 Results Obtained -- 9 Conclusion -- References -- Design of Compact Super-Wideband Monopole Antenna for Spectrum Sensing Applications -- 1 Introduction -- 2 Antenna Configuration -- 2.1 SWB QSCA -- 2.2 QSCA with Notch Bands -- 3 Results Discussion -- 4 Conclusion -- References -- Probabilistic and Distance-Aware Clustering Approach to Decrease the Effect of Hot Spot in WSN -- 1 Introduction -- 1.1 Wireless Sensor Network -- 1.2 WSN Challenges -- 1.3 Energy Efficiency -- 1.4 Clustering -- 1.5 LEACH -- 2 Distance Effect -- 2.1 Hot-Spot Effect -- 2.2 Residual-Energy-Based Clustering -- 3 Related Work -- 4 Proposed Protocol -- 5 Results -- 6 Conclusion -- References -- A Real-Time Sentiments Analysis System Using Twitter Data -- 1 Introduction -- 2 Literature Survey -- 3 Proposed System -- 3.1 Tweepy Stream Listener -- 3.2 Preprocessing -- 3.3 Sentimental Analysis -- 3.4 Representation -- 3.5 Tweet Storage -- 4 Case Studies -- 4.1 Qualifying 3-Spanish Grand Prix 2019 -- 4.2 Indian Election Results-2019 -- 5 Conclusion and Future Scope. , References.

Note: Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- Intelligent Computing -- 1 Global Stability of a Viral Dynamical Model -- Abstract -- 1 Introduction -- 2 Model -- 3 The Existence of Equilibria -- 4 The Global Stability of Equilibria -- Acknowledgements -- References -- 2 Research on Construction of the Software Technology Profession in Vocational Institutes Based on the External Vision -- Abstract -- 1 Introduction -- 2 Professional Construction Ideas Based on the External Vision -- 3 Versatile Teaching Team Construction Based on the Strengths of Teachers -- 4 Social Service Ability Construction Based on Demands of Social Markets -- 5 Construction of School Training Bases Integrated Into Occupation Job Elements and the Construction of the Public Off-Campus Training Bases -- Acknowledgements -- References -- 3 Numerical Study on the Expanded Mixed Covolume Method for One-Dimensional Sobolev Equation -- Abstract -- 1 The Expanded Mixed Covolume Method -- 1.1 The Semi-discrete Scheme -- 1.2 The Fully Discrete Scheme -- 2 Numerical Invariants -- 2.1 A Single Solitary Wave -- 2.2 Interaction of Two Solitary Waves -- References -- 4 Research on the Control Method of Coal Sample Blanking Based on the BP Neural Network and the PID Algorithm -- Abstract -- 1 Introduction -- 2 Control Method of Coal Sample Blanking Based on the BP Neural Network and the PID Algorithm -- 2.1 PID Control Algorithm -- 2.2 BP Neural Network Algorithm -- 3 Experimental Verification -- Acknowledgements -- References -- 5 A Practice on Neural Machine Translation from Indonesian to Chinese -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Lore Translator -- 4 Experiments -- 4.1 Corpus -- 4.2 Training -- 4.3 Experimental Results and Discussion -- 4.4 Demo System -- 5 Conclusion -- Acknowledgements -- References. , 6 Keyword-Based Indonesian Text Summarization -- Abstract -- 1 Introduction -- 2 Related Work -- 2.1 The Development of Automatic Summarization -- 2.2 Existing Systems -- 3 Keyword Contribution Method -- 3.1 Overall Architecture -- 3.2 Algorithm -- 4 Experiment -- 5 Conclusion -- Acknowledgements -- References -- 7 Automatic Decision Support for Public Opinion Governance of Urban Public Events -- Abstract -- 1 Introduction -- 2 Implementation -- 2.1 Data Collection Layer -- 2.2 Information Analysis Layer -- 2.3 Public Opinion Government Layer -- 3 Conclusion -- Acknowledgements -- References -- 8 Improved Local Morphology Fitting Active Contour with Weighted Data Term for Vessel Segmentation -- Abstract -- 1 Introduction -- 2 Related Local Region-Based Models -- 3 Proposed Method -- 4 Results -- 5 Conclusion -- References -- 9 3D Point Cloud Data Splicing Algorithm Based on Feature Corner Model -- Abstract -- 1 Introduction -- 2 3D Point Cloud Data Splicing Algorithm Based on Feature Corner Model -- 2.1 Model Innovation and Data Mining -- 2.2 The Overall Structure of the System -- 2.3 Point Cloud Data Splicing Algorithm -- 3 Conclusion -- Acknowledgements -- References -- 10 A Preliminary Study on Mobile Learning -- Abstract -- 1 The Concept, Characteristics, and Composition of Mobile Learning -- 2 The Feasibility of Mobile Learning -- 2.1 The Characteristics of Mobile Learning -- 2.2 The Inherent Advantages of the Network Environment -- 2.3 The Needs of Professional Construction -- 3 Potential Problems and Solutions in Mobile Learning -- 4 Conclusion -- References -- 11 Design and Implementation of Real-Time Inquiry System of the Stock Market -- Abstract -- 1 Introduction -- 2 Relative Technologies -- 2.1 Hadoop -- 2.2 HBase -- 3 Requirement Analysis and Design -- 3.1 System Function Analysis -- 3.2 Overall Design of the System. , 3.3 Database Design -- 4 Implementation of the Key Modules of the System -- 4.1 The Real-Time Prompt Module of Fuzzy Query of Stock Information -- 4.2 News Information Module -- 4.3 Query Module of Large Quantities of Historical Data -- 5 Conclusion -- Acknowledgements -- References -- 12 An Improved Feature Selection Algorithm for Fault Level Identification -- Abstract -- 1 Introduction -- 2 Basic Concepts of Ordinal Classification -- 3 Feature Selection Algorithm for Ordinal Classification -- 4 Feature Selection and Classification Results -- 5 Conclusions -- Acknowledgements -- References -- 13 Computing Model of Musical Multiple Perception Based on Memory Mapping Perception Inversion -- Abstract -- 1 Introduction -- 2 Fuzzy Perception of Music -- 2.1 Fuzziness of Music -- 2.2 Memory Mapping and Perception Inversion (MMPI) -- 3 Music Intelligence Based on Fuzzy Perception -- 3.1 Musical Feature Index -- 3.2 The Basic Type of Music Perception -- 4 Experimental Results -- 5 Conclusions -- Acknowledgements -- References -- 14 A Natural Immersive Closed-Loop Interaction Method for Human-Robot "Rock-Paper-Scissors" Game -- Abstract -- 1 Introduction -- 2 System Description -- 2.1 The Natural Interaction Implementation -- 2.2 The Real-Time Performance Implementation -- 2.3 The Immersion Mode Implementation -- 3 The Closed-Loop Characteristics -- 4 System Testing and Evaluation -- 5 Conclusion -- References -- 15 Capsule Network-Based Facial Expression Recognition Method for a Humanoid Robot -- Abstract -- 1 Introduction -- 2 Advantages and Properties of the Capsule Net -- 2.1 The Differences -- 2.2 The Properties of the Capsule Net -- 3 CK+ Dataset and NAO Robot Experiments -- 3.1 CK+ Dataset -- 3.2 NAO Robot -- 3.3 Experiments -- 4 Conclusions -- Acknowledgements -- References. , 16 Equipment Maintenance Mode Decision Based on Fuzzy Multi-attribute Decision Method -- Abstract -- 1 Introduction -- 2 Fuzzy Multi-attribute Decision Model -- 3 Fuzzy Multi-attribute Decision Process -- 4 Fuzzy Multi-attribute Decision Method -- 5 Example Analysis -- 6 Conclusion -- References -- 17 A Method for Facial Kinship Verification Based on Deep Learning -- Abstract -- 1 Introduction -- 2 Method -- 2.1 Channel Backbone Network -- 2.2 Multi-channel Model -- 2.2.1 Binary-Channel Model -- 2.2.2 Elastic Multi-channel Model -- 2.3 Training -- 3 Experiments and Results -- 4 Conclusion -- Acknowledgements -- References -- 18 A Domain-Adapting Word Representation Method for Word Clustering -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Frequently Co-occurring Entropy -- 3.2 Fuzzy Bag-of-Words Model -- 4 Experimental Results -- 5 Conclusion -- Acknowledgments -- References -- 19 Fitting Complex Nonlinear Function with Belief Rule Base -- Abstract -- 1 Introduction -- 1.1 The Basic BRB Model -- 1.2 BRB Inference Using ER Approach -- 2 Constructing BRB Model for Nonlinear Function -- 2.1 Nonlinear Function -- 2.2 Transformation Techniques for Quantitative Data -- 3 Parameter Training for BRB -- 4 Experiments Study -- 5 Conclusion -- References -- 20 Approximate Kernel Regression Based on Distributed ADMM Algorithm -- Abstract -- 1 Introduction -- 2 Method -- 2.1 Kernel Regression -- 2.2 ADMM Algorithm -- 2.3 Kernel Regression Based on ADMM Algorithm -- 2.4 Approximate Kernel Matrix -- 3 Experiments -- 4 Conclusion -- Acknowledgements -- References -- 21 Detection for Mixed-Characters Based on Machine Learning -- Abstract -- 1 Introduction -- 2 The Composition of the Detection System -- 3 Character Preprocessing -- 3.1 Binarization -- 3.2 Character Segmentation -- 3.3 The Character Normalization -- 4 Data Set Production. , 5 Neural Network Design -- 6 Experimental Results and Analysis -- 7 Conclusion -- References -- 22 Research on 3D Terminal Rendering Technology Based on Power Equipment Business Features -- Abstract -- 1 Introduction -- 2 3D Model High-Speed Rendering Technology -- 3 3D Model Real-Time High-Speed Rendering Technology for Terminal and Grid Business Application Requirements -- 3.1 Scene Organization -- 3.2 Rendering Process -- 3.3 3D Engine Cross-Platform Technology -- 4 Conclusions -- Acknowledgements -- References -- 23 Community Detection Based on Improved Bee Evolutionary Genetic Algorithm -- Abstract -- 1 Introduction -- 2 Algorithm Structure and Algorithm Description -- 3 Improved Bee Evolutionary Genetic Algorithm -- 3.1 Fitness Function -- 3.2 Encoding -- 3.3 Population Initialization -- 3.4 Crossover Operator -- 3.5 Mutation Operator -- 3.6 Selection Operator -- 3.7 Optimization of Random Population Size -- 4 Simulation and Analysis -- 4.1 Community Detection of the LFR Benchmark Network -- 4.2 Community Detection of the Karate Club Network -- 4.3 Community Detection of the dolphin Network -- 5 Conclusion -- Acknowledgments -- References -- 24 Named Entity Recognition for Chinese Management Case Texts -- Abstract -- 1 Introduction -- 2 Semi-supervised Learning Method -- 2.1 Bootstrapped Framework -- 2.2 BI-LSTM-CRF Model -- 2.3 Evaluating Rule -- 3 Experiment -- 3.1 Dataset -- 3.2 Results and Analysis -- 4 Conclusion and Discussion -- Acknowledgements -- References -- 25 Application of Virtual Simulation Platform in Basic Medical Teaching -- Abstract -- 1 Introduction -- 2 Significance of Basic Medical Virtual Simulation Experimental Platform -- 2.1 Reduce the Cost of Experiment -- 2.2 Provide an Open Experimental Environment -- 2.3 Enhance Classroom Fun -- 3 Construction of Basic Medical Virtual Simulation Platform. , 3.1 Functionality Virtual Simulation Experiment Platform.

Note: Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- Intelligent Computing -- Multi-SoftMax Convolutional Neural Network and Its Application in the Diagnosis of Planetary Gearbox Complicated Faults -- 1 Introduction -- 2 Fault Tree Structure and Muti-SoftMax Convolutional Neural Network -- 2.1 Fault Tree Structure -- 2.2 Working Parallel Structure -- 2.3 Structure of Multi-SoftMax Convolutional Neural Network -- 3 Process of Planetary Gearbox Fault Diagnosis -- 4 Example of Planetary Gearbox Fault Diagnosis -- 4.1 Structure of Convolutional Neural Network -- 4.2 Structure of Mutil-SoftMax Convolutional Neural Network -- 5 Experiment -- 6 Conclusion -- References -- Signal Complexity Measure Based on Construction Creep Rate in 3s Feature Space -- 1 Introduction -- 2 Methodology -- 2.1 0-1 Test for Chaos Review -- 2.2 New Algorithm (Spring Test) Block of 3s Plot and CC Rate -- 2.3 Two Equations as Test Cases -- 3 Results and Discussions -- 3.1 Results from pq-Plot of 0-1 Test to 3s Plot and CC Rate in Spring Test -- 3.2 Key Self-similarity Measure Threshold γ Locking in Max Complexity -- 4 Conclusions -- References -- Research on Partition Technology of Real-Time Database in Big Data Environment -- 1 The Introduction -- 2 Design of Tual-Time Partition Database System for Flow Computing -- 3 Implementation of Real-Time Partition System -- 4 Audit and Effect of System Effectiveness -- 5 Summary -- References -- RCS Sequence Period Estimation Method Based on Constant False Alarm Detection -- 1 Introduction -- 2 Periodic Movement Target Characteristics -- 3 Periodic Discriminant Method for Constant False Alarm Detection -- 3.1 Periodic Discriminant Method for Constant False Alarm Detection -- 3.2 Effectiveness Analysis -- 4 Experimental Verification -- References -- Target Recognition of RCS Sequence Based on Neural Network. , 1 Introduction -- 2 Build the Attitude Angle Template -- 3 Feature Extraction and Classifier Design -- 4 Neural Network Design -- References -- Encouraging Cooperation in Participatory Sensing with Reputation and Game Analysis -- 1 Introduction -- 2 System Model -- 3 Trust Model and Game Analysis -- 3.1 Trust Model -- 3.2 Game Model -- 3.3 Repeated Game Analysis -- 4 Conclusion -- References -- Multi-granularity Attribute Sentiment Analysis Based on Neural Network -- 1 Introduction -- 2 Related Work -- 3 Multi-granularity Sentiment Analysis Model -- 3.1 Task Definition -- 3.2 Model -- 3.3 Multi-granularity Attention Mechanism -- 3.4 Model Training -- 4 Experiment -- 4.1 Experimental Data and Parameter Configuration -- 4.2 Method Comparison -- 4.3 Analysis of Experimental Results -- 5 Conclusion -- References -- Study on Fuzzy Crop Planning Problems Based on Credibility Theory -- 1 Introduction -- 2 Basic Principles -- 3 Fuzzy Crop Planning Problem -- 3.1 Problem with Fuzzy Income Coefficients -- 3.2 Method -- 4 Conclusion -- References -- Empirical Research on the Antecedents of Enterprise IS Users' Voice Behavior Based on the Work Behavior Theory -- 1 Introduction -- 2 Theoretical Background and Hypotheses -- 3 Research Method -- 4 Research Results -- 5 Discussion and Conclusion -- References -- Image Fusion Based on Masked Online Convolutional Dictionary Learning with Surrogate Function Approach -- 1 Introduction -- 2 The Proposed Fused Algorithm -- 2.1 Masked Online Dictionary Learning Using Surrogate Function Approach with Sparse Matrix Computation -- 2.2 The Fusion Framework -- 3 Experimental -- 4 Conclusion -- References -- The Liquid Cooling Technique Based on Foam Metal Copper -- 1 Introduction -- 2 Liquid Cooling Module Design Optimization -- 2.1 Liquid Cooling Module -- 2.2 Liquid-Cooled Radiator -- 3 Liquid Cooling Module Testing. , 3.1 Comparison Test of Liquid Cooling Module Heat Dissipation Performance Based on Liquid Cooling System -- 3.2 Comparison Test of Heat Dissipation Performance of Liquid Cooling Module Based on Self-circulating Cooling System -- 4 Conclusion -- References -- Study on the Forecast of Driving Reaction Based on PNN and FCM -- 1 Introduction -- 2 Driving Reaction Relations -- 3 Driving Reaction Sample Unified Disposal -- 4 Driving Reaction Neural Network -- 5 Road Test Data Acquisition -- 6 Applying Analyses -- 7 Conclusions -- References -- Android Malware Detection via Behavior-Based Features -- 1 Introduction -- 2 Existing Malware Detection Technology -- 2.1 Static Testing Technology of the Existing Malware Detection -- 2.2 Existing Dynamic Malware Detection Technology -- 3 The Behavior-Based Feature Recognition of Detection Technology -- 3.1 The Overall Technical Program -- 3.2 User Operator Behavior Monitoring Module -- 3.3 Software Behavior Monitoring Module -- 3.4 The Malicious Behavior Feature Recognition Module -- 4 Conclusion -- References -- Analysis of the Power Converter Used in Wind Power Generator System -- 1 Introduction -- 2 Power Converter Topology for Wind Power System -- 2.1 Two-Level Voltage Source Converter -- 2.2 Multilevel Voltage Source Converter -- 2.3 Matrix Converter -- 2.4 Current Source Converter -- 3 Application Status of Converters in Variable Speed Constant Frequency Wind Power System -- 3.1 Converters Commonly Used in Medium and Low Voltage Wind Power Systems -- 3.2 Control Strategy of Common Converters in Wind Power System -- 4 Development Trend of Wind Power Converter -- 5 Conclusions -- References -- Evaluation of New Energy Theory Based on Data Recovery -- 1 Introduction -- 1.1 Research Background -- 1.2 Research Methods -- 2 Data Introduction -- 2.1 Data Sources -- 2.2 Data Processing. , 3 Theoretical Power Calculation -- 4 Conclusions -- References -- Summary, Reflection, and Prospect of Wind Power Development in China -- 1 Introduction -- 2 Wind Power Development History -- 3 Wind Power Consumption Situation -- 3.1 Wind Power Generation in Provinces -- 3.2 Accommodation Capacity Index -- 3.3 Abandoned Wind Power and Abandoned Rate -- 4 Development Summary -- 5 Suggestions -- References -- Time-Varying Probability Distribution Model of High Permeability Wind Power Considering Non-stationary Characteristics -- 1 Introduction -- 2 Time-Varying Characteristics of Wind Power Probability Distribution and Spatial Correlation Coefficient -- 2.1 Time-Varying Characteristics of Probability Distribution of Single Wind Farm -- 2.2 Time-Varying Characteristics of Rank Correlation Coefficients of Multi-wind Farms -- 3 Off-Line Conditional Dependence Model Set of Edge Probability Distribution and Rank Correlation Coefficient Matrix -- 3.1 Off-Line Conditional Dependence Model Set of Probability Distribution of Single Wind Farm -- 3.2 Off-Line Conditional Dependence Model Set of Rank Correlation Coefficient Matrix of Multi-wind Farms -- 4 Time-Varying Probability Distribution Sampling Algorithm -- 5 Validity Analysis of Time-Varying Probability Distribution Modeling -- 5.1 Simulation System -- 5.2 Effect of Time-Varying Characteristics on Wind Power Characteristic Modeling -- References -- An Adaptive T-Distribution Variation Based HS Algorithm for Power System ED -- 1 Introduction -- 2 The HS Based on Adaptive T-Distribution Mutation (t-LHS) -- 2.1 HS Algorithm -- 2.2 Variation Principle of T-Distribution -- 2.3 A HS Algorithm Based on Adaptive T-Distribution Mutation (t-LHS) -- 3 The Steps of t-LHS Algorithm for Solving ED Problems -- 4 Results and Comparison -- 4.1 3-Generator System -- 4.2 40-Generator System -- 5 Conclusions -- References. , Application of Improved Particle Swarm Optimization in Economic Dispatch of Power System -- 1 Introduction -- 2 Improved Particle Swarm Optimization (IMPSO) -- 2.1 Adjustment of Parameters -- 2.2 Optimal Learning Strategies -- 2.3 Objective Function -- 2.4 Constraints -- 2.5 Steps of IMPSO Algorithms for Solving ED Problems -- 3 Experimental Analysis and Results -- 4 Conclusions -- References -- Design of an Ultra-Short-Term Wind Power Forecasting Model Combined with CNN and LSTM Networks -- 1 Introduction -- 2 Related Works -- 2.1 Wind Power Generation Power -- 2.2 CNN Network -- 2.3 LSTM Network -- 3 The Description of the Experimental Progress -- 3.1 Data Preprocessing -- 3.2 CNN Layer -- 3.3 LSTM Layer -- References -- An Algorithm for Intelligent Attack Decision-Making -- 1 Introduction -- 2 Underlying Factors -- 3 Modeling for Intelligent Decision-Making -- 4 The Process of Intelligent Decision-Making -- 5 Achievement of the System -- 6 Conclusion -- References -- Wavelet Packet Energy Entropy Based Feature Analysis of Seismic Signals from Vehicle Targets -- 1 Foreword -- 2 Time-Frequency Feature of Seismic Signals from Vehicle Targets Based on Wavelet Packet Transformation -- 2.1 Test for Seismic Signals from Vehicle Targets -- 2.2 Wavelet Packet Transformation of Seismic Signals from Vehicle Targets -- 3 Energy Entropy Feature Extraction for Seismic Signals from Vehicle Targets Based on Wavelet Packet Transformation -- 3.1 Wavelet Packet Transformed Energy Entropy -- 3.2 Extraction of Energy Entropy Feature of Seismic Signals from Vehicle Targets Based on Wavelet Packet Transformation -- 4 Conclusion -- References -- Group Decision-Making Approach Under Interval-Valued Dual Hesitant Fuzzy Unbalanced Uncertain Linguistic Environments and Its Application to Community Tourism Resilience Evaluation -- 1 Introduction. , 2 Weighted Power Aggregation Operator with IVDHFUUBLS Information.

Note: Intro -- International Program Committee -- Honorary Chair -- General Chairs -- Organizing Chair -- International Advisory Chair -- Founder of IRNet China -- Co-founder of IRNet China -- TPC Members -- Sponsors -- Preface -- Contents -- About the Editors -- 1 Study Optimization of Thermal Analysis of Anisotropic Materials in 3D Field Based on One-Dimensional Heat Conduction Equation Model -- 1.1 Introduction -- 1.2 Heat Transfer Mode and Process Analysis -- 1.3 Optimization Model of Protective Clothing Design for High-Temperature Engineering Work -- 1.3.1 The Establishment of the Model and the Proposal of the Hypothesis Conditions -- 1.3.2 Optimization Model Based on Inversion Method -- 1.4 Conclusion -- References -- 2 Shape Retrieval for 3D Models Based on MRF -- 2.1 Introduction -- 2.2 Feature Descriptor -- 2.3 Framework of Retrieval -- 2.3.1 Notations -- 2.3.2 Formulation -- 2.3.3 Potential Function -- 2.4 Spatial Consistency Test -- 2.4.1 Training -- 2.4.2 Testing -- 2.4.3 Index Based on Random Forest -- 2.4.4 Measure Similarity -- 2.5 Experiments -- 2.6 Conclusions -- References -- 3 Numerical Conformal Mapping Based on Improved Hermitian and Skew-Hermitian Splitting Method -- 3.1 Introduction -- 3.2 Numerical Conformal Mapping Based on the Charge Simulation Method -- 3.3 Improved HSS Method Based on (k, j)-Padé Iteration Method -- 3.4 Numerical Examples -- 3.5 Conclusions -- References -- 4 Hierarchical Clustering-Based Video Summarization -- 4.1 Introduction -- 4.2 Feature Extraction -- 4.2.1 Color Feature -- 4.2.2 Texture Feature -- 4.3 The Proposed Algorithm -- 4.3.1 Hierarchical Clustering Method -- 4.3.2 Optimize Initial Clustering Results to Extract Video Summary Key Frames -- 4.4 Experimental Results and Discussion -- 4.4.1 Evaluation Standard -- 4.4.2 Experimental Results -- 4.5 Conclusion -- References. , 5 Research on Multi-objective Optimization Problem of Engineering Project in 3D Field Based on Improved Particle Swarm Optimization Algorithm -- 5.1 Introduction -- 5.2 IPSO Algorithms -- 5.3 Model -- 5.4 Engineering Calculation and the Result Analysis -- 5.5 Conclusions -- References -- 6 3D Path Planning Based on Improved Particle Swarm Optimization Algorithm -- 6.1 Introduction -- 6.2 Path Planning Environment Modeling and Fitness Function -- 6.2.1 Environmental Modeling -- 6.2.2 Fitness Function -- 6.3 Improved PSO Algorithm -- 6.3.1 Basic PSO Algorithm -- 6.3.2 BFO Algorithm -- 6.3.3 Hybrid Algorithm -- 6.4 Simulation Verification -- 6.5 Conclusion -- References -- 7 Improving Parallel Magnetic Resonance Imaging Reconstruction Using Nonlinear Time Series Analysis -- 7.1 Introduction -- 7.2 Background -- 7.3 Method -- 7.4 Experimental Results -- 7.5 Conclusion -- References -- 8 Low Computational Complexity Third-Order Tensor Representation Through Inverse Spectrum Pyramid -- 8.1 Introduction -- 8.2 Method for Third-Order Tensor Representation Through 3D Reduced ISP -- 8.2.1 Representation of a Tensor of Size 4 × 4 × 4 -- 8.2.2 Representation of the Tensor of Size N × N × N Through N-Level 3D-RISP -- 8.3 Characteristics of the Spectrum Tensor Representation -- 8.4 Conclusions -- References -- 9 Spectral Reconstruction Based on Bayesian Regulation Neural Network -- 9.1 Introduction -- 9.2 Principle of Spectral Reflectance Reconstruction -- 9.2.1 Polynomial Regression -- 9.2.2 Bayesian Regularization BP Neural Network Algorithm -- 9.3 Experimental Results and Analysis -- 9.3.1 Experiment Process -- 9.3.2 Analysis and Comparison of Results -- 9.4 Conclusion -- References -- 10 Loose Hand Gesture Recognition Using CNN -- 10.1 Introduction -- 10.2 The Proposed Method -- 10.2.1 Training Data Preparation. , 10.2.2 The Proposed Neural Network Architecture -- 10.2.3 Loss Function -- 10.3 Experiments -- 10.3.1 CNN with Input RGB-D Images -- 10.3.2 CNN with Multi-resolution Features -- 10.3.3 Compared with Other Popular CNN Models -- 10.4 Conclusions -- References -- 11 Multi-focus Image Fusion Method Based on NSST and BP Neural Network -- 11.1 Introduction -- 11.2 Image Fusion Method -- 11.2.1 NSST Transformation -- 11.2.2 Feature Extraction and NSST Contrast -- 11.2.3 BP Neural Network Training -- 11.2.4 Algorithm Framework and Steps -- 11.3 Experiments Results -- 11.4 Conclusions -- References -- 12 Classification of 3D Remote Sensing Images Through Dimensionality Reduction and Semantic Segmentation Network -- 12.1 Introduction -- 12.2 Proposed Method -- 12.2.1 The Whole Approach Framework -- 12.2.2 Rasterization -- 12.2.3 Normalization and Hat Transform -- 12.2.4 DSM Post-processing -- 12.2.5 Network for Classification -- 12.3 Experiment -- 12.3.1 Training Deeplabv3+ -- 12.3.2 Post-processing by NDSM -- 12.3.3 Visualization of 3D Remote Sensing Images -- 12.4 Conclusion -- References -- 13 Research on Deep Learning Algorithm and Application Based on Convolutional Neural Network -- 13.1 Introduction -- 13.2 Convolutional Neural Network -- 13.2.1 Local Connection of Convolutional Neural Networks -- 13.2.2 Weight Sharing in Convolutional Neural Networks -- 13.3 The Overall Structure of the Convolutional Neural Network -- 13.4 The Application of Deep Learning Algorithm Based on Convolutional Neural Network -- 13.4.1 Application in the Field of Natural Language Processing -- 13.4.2 Application in the Field of Image Recognition -- 13.4.3 Application in the Field of Speech Recognition -- 13.5 The Conclusion -- References -- 14 Object Attribute Recognition Based on Hard Negative Mining and Convolutional Neural Network -- 14.1 Introduction. , 14.2 Object Location Based on Improved Faster R-CNN Model -- 14.2.1 Hard Negative Mining Strategy -- 14.2.2 OHEM-Faster R-CNN Object Location Model -- 14.3 Object Attribute Recognition Method Based on Improved Cascade Convolution Neural Network Model CS-CNN Model -- 14.3.1 Improved Activation Function and Loss Function -- 14.3.2 Improved CS-CNN Model Object Attribute Recognition Method -- 14.4 Experimental Simulations -- 14.4.1 Model Parameters -- 14.4.2 Experimental Simulations of Object Location -- 14.4.3 Contrastive Experimental Simulations of Object Attribute Recognition -- 14.5 Conclusion -- References -- 15 Research on Intelligent Identification Method of Power Equipment Based on Deep Learning -- 15.1 Introduction -- 15.1.1 Background -- 15.1.2 Purpose and Significance -- 15.1.3 Summary of Research Level at Home and Abroad -- 15.2 Solutions and Key Technologies -- 15.2.1 Power Equipment Image Processing and Feature Extraction -- 15.2.2 Power Equipment Classification -- 15.2.3 Establish a Standardized Image Analysis Library -- 15.3 Conclusion -- References -- 16 Chinese Color Name Identification from Images Using a Convolutional Neural Network -- 16.1 Introduction -- 16.2 Color Vocabulary Labeled Data Set -- 16.3 The Model of Color Recognition -- 16.3.1 Design of Multi-label Convolutional Neural Networks -- 16.3.2 Evaluation Criteria -- 16.3.3 Choosing the Appropriate Threshold -- 16.4 Conclusion -- References -- 17 Research and Design of a Key Technology for Accelerating Convolution Computation for FPGA-Based CNN -- 17.1 Introduction to Relevant Theories -- 17.1.1 Introduction to Convolution Neural Network -- 17.1.2 The Training Process -- 17.2 SpNet Model -- 17.3 Research on Correlation Algorithm Research -- 17.3.1 Im2col Algorithm -- 17.3.2 Strassen Algorithm -- 17.3.3 Improved Strassen Algorithm. , 17.4 An Accelerated Convolution Calculation Scheme Based on FPGA -- 17.4.1 Design of Training Architecture of Convolutional Neural Network Based on FPGA -- 17.4.2 Design and Implementation of Convolution Computing Module -- 17.4.3 Testing the Convolutional Neural Network -- 17.5 Summary -- References -- 18 Research on Voice Mark Recognition Algorithms Based on Optimized BP Neural Network -- 18.1 Introduction -- 18.2 Wavelet Transform of Voice Signal -- 18.3 Basic Conception of BP-GA -- 18.3.1 Construction of BP Neural Network VoicePrint Recognition -- 18.4 Design of Genetic Algorithm -- 18.5 Simulation Analyses of an Example with BP-GA Algorithm -- 18.6 Conclusions -- References -- 19 Single Image Super Resolution via Deep Convolutional Dual Upscaling Branches with Different Focus -- 19.1 Introduction -- 19.2 Related Works -- 19.2.1 Variant Shortcuts -- 19.2.2 Skillfully Nesting Modules -- 19.3 Proposed Method -- 19.3.1 The Entire Structure -- 19.3.2 Residual Learning Branch -- 19.3.3 Planar Component Branch -- 19.3.4 Mathematical Formulation -- 19.4 Experimental Results -- 19.4.1 Datasets -- 19.4.2 Parameters Settings -- 19.4.3 Results and Comparisons -- 19.4.4 Ablation Analysis -- 19.5 Conclusions -- References -- 20 Human Heart Model Rendering Based on BRDF Algorithm -- 20.1 Introduction -- 20.2 Theoretical Research and Experimental Methods -- 20.2.1 Theoretical Research -- 20.2.2 Experimental Method -- 20.3 Experimental Results -- 20.3.1 Experimental Conditions -- 20.3.2 Rendering Results and Analysis -- 20.4 Conclusions and Discussion -- References -- 21 Level Set Segmentation Algorithm for Cyst Images with Intensity Inhomogeneity -- 21.1 Introduction -- 21.2 C-V Model -- 21.3 Improved C-V Level Set Model -- 21.3.1 Local Information -- 21.3.2 Speed Function -- 21.3.3 Overall Energy Functional -- 21.4 Experimental Results and Analysis. , 21.5 Conclusion.

Note: Intro -- Contents -- About the Editors -- Chapter 1: Cerebral Stroke: An Introduction -- 1.1 Introduction -- 1.2 Types of Stroke -- 1.2.1 Ischemic Stroke -- 1.2.2 Hemorrhagic Stroke -- 1.2.3 Transient Ischemic Attack -- 1.3 Stroke Pathophysiology -- 1.4 Current Treatment Option for Stroke Patients -- 1.5 Neuroprotective Agents in Preclinical and Clinical Trials -- 1.6 Stroke-Induced BBB Disruption -- 1.7 Ischemic Stroke-Induced ER Stress -- 1.8 The Emerging Role of mi-RNA in Stroke Pathophysiology -- 1.9 Neuroprotective Potential of Low-Frequency Electromagnetic Field -- 1.10 Stem Cell Therapies for Cerebral Stroke -- 1.11 Conclusion -- References -- Chapter 2: Inflammation, Oxidative Stress, and Cerebral Stroke: Basic Principles -- 2.1 Introduction -- 2.2 Inflammation -- 2.3 Inflammatory Role of Cytokines and Chemokines During Cerebral Stroke -- 2.4 Oxidative Stress -- 2.5 Treatment Strategy for Stroke -- 2.5.1 Targeting Antioxidant Enzyme as a Therapeutic Strategy for Ischemic Stroke -- 2.5.2 Regulation of Microglial Activation in Stroke -- 2.5.3 Targeting the Cholinergic Anti-inflammatory Pathway -- References -- Chapter 3: Stroke Induced Blood-Brain Barrier Disruption -- 3.1 Introduction -- 3.2 BBB Anatomy -- 3.3 BBB Junctional Complexes -- 3.3.1 Adherens Junctions (AJs) -- 3.3.2 Tight Junctions (TJs) -- 3.3.3 Gap Junctions -- 3.3.3.1 Junctional Adhesion Molecule (JAM) -- 3.3.3.2 Occludin -- 3.3.3.3 Claudins -- 3.3.4 Membrane-Associated Guanylate Kinase (MAGUK)-Like Proteins -- 3.3.5 Accessory Proteins -- 3.4 Calcium Modulation of TJ and TJ Proteins -- 3.5 Phosphorylation: A Novel Regulatory Mechanism of TJ Proteins -- 3.6 Impairment of BBB Integrity in Neuropathological Disorder -- 3.6.1 Alteration of BBB Integrity in Stroke Injury -- 3.7 Evaluation of BBB Disruption in Rodent Ischemic Stroke. , 3.8 Quantitative Evaluation of BBB in Ischemic Stroke Using Dynamic Contrast-Enhanced (DCE) MRI -- 3.9 Conclusion -- References -- Chapter 4: Ischemic Stroke-Induced Endoplasmic Reticulum Stress -- 4.1 Introduction -- 4.2 ER Stress, UPR, and Ischemia -- 4.2.1 Components of UPR in Ischemia -- 4.2.1.1 GRP78 -- 4.2.1.2 PERK -- 4.2.1.3 ATF6 -- 4.2.1.4 IRE1 -- 4.3 Chronic ER Stress, UPR, and Pro-apoptotic Signaling in IR Injury -- 4.3.1 CHOP -- 4.3.2 Caspase 12 -- 4.3.3 JNK -- 4.4 ER Stress and Autophagy in IR Injury -- 4.5 ER Stress and miRNAs in IR Injury -- 4.6 Conclusion -- References -- Chapter 5: The Role of Autophagy in Ischaemic Stroke: Friend or Foe? -- 5.1 Introduction -- 5.2 Pathophysiology of Ischaemic Stroke -- 5.3 Various Animal Models to Study IS -- 5.3.1 Intra-arterial Suture Middle Cerebral Arterial Occlusion Model -- 5.3.2 Craniotomy Model -- 5.3.3 Photothrombosis Model -- 5.3.4 Endothelin-I Model -- 5.3.5 Clot Embolic Model of Stroke -- 5.4 Autophagy and Its Machinery -- 5.5 Autophagy and Its Role in Cerebral Ischaemia -- 5.5.1 Autophagy Activation in Ischaemic Stroke Protects Neurons -- 5.5.2 Autophagy Is Also Responsible for Neuronal Death After Ischaemic Stroke -- 5.5.3 Degree of Autophagy Is Critical in Ischaemic Stroke -- 5.5.4 Autophagy Contributes to Ischaemic Tolerance After Preconditioning -- 5.5.5 Autophagy May Be Disrupted During Ischaemia -- 5.6 Concluding Remarks -- References -- Chapter 6: Critical Role of Mitochondrial Autophagy in Cerebral Stroke -- 6.1 Introduction -- 6.2 Autophagy -- 6.3 Nonselective Autophagy and Mitophagy -- 6.4 Mitochondria Dynamics: Fission and Fusion of Mitochondria -- 6.5 Molecular Mechanisms of Mitophagy -- 6.6 Mitophagy in Cerebral Ischemia -- 6.7 Effect of Cerebral Ischemia in Mitochondrial Dynamic Mediators -- 6.8 Mitophagy Regulation: An Anti-inflammation Approach in Cerebral Ischemia. , 6.9 Mitophagy Regulation: A Neuroprotective Approach in Cerebral Ischemia -- 6.10 Conclusion -- References -- Chapter 7: Application of Neuroimaging Tools in Identification of Pinpoint Location of Blockage -- 7.1 Introduction -- 7.2 Neuroimaging Modalities for Stroke Detection -- 7.3 Hardware-Based Imaging Modalities -- 7.3.1 Computed Tomography (CT) -- 7.3.2 Magnetic Resonance Imaging(MRI) -- 7.3.3 Microwave-Based Imaging(MW) -- 7.3.4 Single-Photon Emission Computed Tomography (SPECT) -- 7.3.5 Positron Emission Tomography (PET) -- 7.3.6 Cranial Ultrasound -- 7.4 Software-Based Image Processing Modalities -- 7.4.1 Image Filtering -- 7.4.2 Image Enhancement -- 7.4.3 Image Segmentation -- 7.4.4 Image Compression -- 7.5 Computer-Aided Automatic Detection -- 7.5.1 Graphical User Interface Based (GUI) -- 7.5.2 Computer-Aided Algorithm-Based Detection -- 7.6 Comparison of Neuroimaging Modalities -- 7.7 Conclusion -- References -- Chapter 8: Emerging Role of Electromagnetic Field Therapy in Stroke -- 8.1 Introduction -- 8.2 Importance of Electromagnetic Therapy -- 8.3 Physical Basis of the Generation of a Magnetic Field -- 8.3.1 Stationary Magnetic Field -- 8.3.2 Pulsed Electromagnetic Field -- 8.4 Primary Biological Effects of Magnetic Fields -- 8.4.1 Cell Proliferation and Cell Cycle Regulation -- 8.4.2 Genotoxic Effects -- 8.4.3 Effects on Cellular Membrane Permeability -- 8.5 Role of Electromagnetic Therapy in Ischemic Stroke -- 8.6 Conclusion -- Basic Terminology -- References -- Chapter 9: Stem Cell-Based Therapy for Ischemic Stroke -- 9.1 Introduction -- 9.2 Stem Cell Transplantation for Stroke -- 9.3 Neural Stem Cells -- 9.4 Embryonic Stem Cells -- 9.5 Mesenchymal Stem Cells -- 9.5.1 Bone Marrow-Derived Mesenchymal Stem Cells -- 9.5.2 Adipose Mesenchymal Stem Cells -- 9.5.3 Human Umbilical Cord Mesenchymal Stem Cells. , 9.5.4 Menstrual Blood-Derived Mesenchymal Stem Cells -- 9.6 Hematopoietic Stem Cells -- 9.7 Inducible Pluripotent Stem Cells -- 9.7.1 Reprogramming Methods for Human Somatic Cells into iPSCs -- 9.8 Preconditioning Strategy in Stem Cell Transplantation Therapy -- 9.9 Conclusion -- References -- Chapter 10: Emerging Role of microRNAs in Cerebral Stroke Pathophysiology -- 10.1 Introduction -- 10.2 MicroRNA Biogenesis -- 10.3 Current Therapy and the Possible Role of miRNA in Neuroprotection -- 10.4 Development of Therapeutic Approaches Using miRNA Mimics and Inhibitors -- 10.5 Techniques for miRNA Expression Analysis -- 10.6 Computational Target Gene Prediction -- 10.7 Experimental Approaches to miRNA Target Validation -- 10.8 miRNA as a Prognostic Biomarker in Ischemic Stroke -- 10.9 Circular RNA -- References -- Chapter 11: Therapeutic Aspects of Nanomedicines in Stroke Treatment -- 11.1 Introduction -- 11.2 Secondary Neuronal Damage After Stroke and BBB Breakdown -- 11.3 Existing Treatment of Stroke -- 11.4 Drug Delivery Through BBB During Stroke -- 11.5 NP-Based Drug Delivery -- 11.6 NP-Based Chemical Agents -- 11.7 A Hope: NPs as a Diagnostic Tool in Stroke -- 11.8 Composition of Nanocarrier Used in Stroke Therapy -- 11.9 Lipid Nanoparticles -- 11.10 Polymer Carriers -- 11.10.1 Inorganic-Based Nanocarriers -- 11.11 Nanocarriers-Based Thrombolytic Therapy: Preclinical Development -- 11.12 Streptokinase -- 11.13 Nanocarriers Loaded with SK -- 11.14 Urokinase (UK) -- 11.15 Urokinase-Loaded Nanocarriers -- 11.16 Tissue Plasminogen Recombinant (tPA, rtPA) -- 11.17 rtPA-Loaded Nanocarriers -- 11.18 Conclusion -- References -- Chapter 12: Neuroprotective Potential of Small Molecule Phytochemicals in Stroke Therapy -- 12.1 Introduction -- 12.2 Role of Molecular Mediators in Apoptotic, Necrotic, and Necroptotic Neuronal Cell Death. , 12.3 Impact of Neurodegeneration in Neurological Disorders Including Stroke -- 12.4 Small Molecule Bioactive Phytochemicals as Neuroprotective Agents in Ischemic Stroke -- 12.4.1 Flavonoids -- 12.4.2 Terpenoids -- 12.4.3 Alkaloids -- 12.4.4 Withanolides -- 12.5 Conclusion -- References -- Chapter 13: Post-Stroke Treatment Strategies, Management, and Rehabilitation: Where We Stand? -- 13.1 Introduction -- 13.2 Types of Stroke -- 13.3 Treatments -- 13.3.1 In hospital -- 13.3.1.1 Thrombolysis -- 13.3.1.1.1 Intravenous Thrombolytic Therapy -- 13.3.1.1.2 Intra-arterial Thrombolysis -- 13.3.1.2 Aspirin Treatment -- 13.3.1.3 Therapeutic Hypothermia -- 13.3.1.4 Blood Pressure Management -- 13.3.1.5 Antiplatelet Strategies -- 13.3.1.6 Surgery for Cerebral Edema -- 13.3.1.7 Antithrombotic Therapy -- 13.3.2 Post-discharge -- 13.3.2.1 Lifestyle Physical Activity -- 13.3.2.1.1 Smoking -- 13.3.2.1.2 Alcohol -- 13.3.2.1.3 Diet -- 13.3.2.1.4 Physical Activity -- 13.3.2.2 Blood Glucose Management -- 13.3.2.3 Cholesterol Management -- 13.3.2.4 Blood Pressure Management -- 13.3.2.5 Anticoagulation and Antiplatelet Therapy -- 13.3.2.6 Herbal Neuroprotective Intervention -- 13.4 Limitations of Treatment -- 13.5 Conclusion -- References.

Note: Intro -- International Program Committee -- Honorary Chair -- General Chairs -- Organizing Chair -- International Advisory Chair -- Founder of IRNet China -- Co-founder of IRNet China -- TPC Members -- Sponsors -- Preface -- Contents -- About the Editors -- 1 3D-DIC Technique for Strain Measurement in FRP Strip Externally Bonded to Concrete Specimens -- 1.1 Introduction -- 1.2 Basic Principle and Advantages of 3D-DIC System -- 1.2.1 Basic Principle and Test Setup of 3D-DIC System -- 1.2.2 Advantages -- 1.3 Operation Process of 3D-DIC -- 1.3.1 Speckle Marking -- 1.3.2 Operation Process -- 1.4 Specimens and Materials -- 1.5 Results and Analysis -- 1.5.1 Strain Distribution of FRP Strips -- 1.5.2 Bond-Slip Relation -- 1.6 Conclusions -- References -- 2 Establishment of Quality Detection and 3D Evaluation Model of Wool Fabric Based on Machine Vision -- 2.1 Introduction -- 2.2 Fluffy Surface Quality Measurement Principle -- 2.2.1 Measurement System Principle Introduction -- 2.2.2 Thickness Measurement Principle -- 2.3 Extraction of the Upper Edge of the Fluff and the Baseline -- 2.4 Villus Surface Quality Estimation Parameter Model -- 2.4.1 Selection of Parameter Model -- 2.5 Test -- 2.5.1 Test Platform -- 2.5.2 Test Data Analysis -- 2.6 Conclusion -- References -- 3 The Research and Design of Wage Supervision Service Platform for Migrant Workers Based on Big Data and Iris Recognition Technology -- 3.1 Background Introduction -- 3.2 Technology Introduction -- 3.2.1 Big Data Technology -- 3.2.2 Iris Recognition Technology -- 3.3 Functional Demand Analysis of Wage Supervision Platform -- 3.4 Logical Architecture Design of Wage Supervision Platform -- 3.5 Network Topology Structure Design of Wage Supervision Platform -- 3.6 Conclusion -- References -- 4 Research on Block Segmentation and Assembly Technology of 3D Printing Structure -- 4.1 Introduction. , 4.2 3D Printing Technology -- 4.2.1 Introduction to Three Technologies Commonly Used in 3D Printing -- 4.2.2 Four Common Data Formats for 3D Printing -- 4.2.3 Basic Requirements for 3D Printing STL Data Format -- 4.3 Block Segmentation and Assembly Technology of 3D Printing Component -- 4.3.1 Block Segmentation and Assembly Process of 3D Printing Component -- 4.3.2 Selection of 3D Printing Sub-block Direction and Position -- 4.4 Printing Cases -- 4.5 Conclusion -- References -- 5 A Study on 3D Reconstruction Method for Common View Field in Hybrid Vision System -- 5.1 Introduction -- 5.2 Hybrid Vision System -- 5.2.1 Introduction of Hybrid Vision System Model -- 5.2.2 The Imaging Principle of RGB-D Camera -- 5.2.3 The Imaging Principle of Panoramic Camera -- 5.3 The Feature Points 3D Reconstruction -- 5.3.1 SURF Feature Extraction -- 5.3.2 SURF Feature Matching -- 5.3.3 3D Reconstruction of Feature Points -- 5.4 Results -- 5.4.1 Feature Matching Point 3D Reconstruction -- 5.4.2 Discussion -- 5.5 Conclusion -- References -- 6 Three-Dimensional Characteristics Observation of Ocean Waves in Coastal Areas by Microwave Doppler Radar -- 6.1 Introduction -- 6.2 3D Spectrum Pre-processing -- 6.3 Radar Data -- 6.4 3D Characteristics of Ocean Wave -- 6.5 Conclusion -- References -- 7 Three-Dimensional Reconstruction Based on Left Right Objects -- 7.1 Research Background and Significance -- 7.2 Technical Route -- 7.2.1 Offline Calibration -- 7.2.2 Stereo Correspond -- 7.3 Results and Analysis -- 7.4 Conclusion -- References -- 8 Research on 3D Scene Dynamic Scanning Modeling Technology of Substation Based on Depth Vision -- 8.1 Introduction -- 8.2 Deep Visual 3D Scanning Modeling Algorithm for Indoor and Outdoor Environments of Substation Operations -- 8.2.1 Semi-dense SLAM Based on RGB-D in Complex Indoor Working Environment. , 8.2.2 Sparse SLAM Based on Binocular Camera in Complex Outdoor Working Environment -- 8.3 Hybrid Hierarchical Scanning Modeling for Large-Scale Scenes -- 8.4 Regional Learning and Substation Environment Understanding Under Scene Point Cloud -- 8.4.1 Point Cloud Pretreatment -- 8.4.2 Point Cloud Clustering -- 8.5 Conclusions -- References -- 9 Fusion and Localization Technology of 3D Model Attitude and Real Physical Environment Visualization Information of Power Inspection Site -- 9.1 Introduction -- 9.2 Binocular Posture and Visual Information Fusion Positioning Technology -- 9.3 Conclusions -- References -- 10 The Research and Design of Big Data Monitoring Platform for Enterprise Growth -- 10.1 Background Introduction -- 10.2 Introduction to Big Data Technology -- 10.3 Functional Demand Analysis -- 10.4 System Development and Design -- 10.4.1 Overall Architecture Design -- 10.4.2 System Functional Architecture Design -- 10.4.3 Network Topology Structure Design -- 10.5 Conclusion -- References -- 11 Application Analysis of Big Data in Library Management and Service -- 11.1 Introduction -- 11.2 Big Data Technology Overview -- 11.3 Analysis of Library Management Service Problems -- 11.3.1 Computational Ability Is Weak -- 11.3.2 Lack of Optimization of Network Resources -- 11.4 The Advantages of Big Data in Library Management and Services -- 11.4.1 Improve the Efficiency of Collection and Integration of Books and Resources -- 11.4.2 Optimize Library Service Projects -- 11.4.3 Promote Resource Sharing and Form a Library Sharing System -- 11.5 The Difficulties and Solutions of Big Data Applied to Libraries -- 11.5.1 The Library Big Data System Is not Perfect -- 11.5.2 Lack of Skills in Librarians -- 11.5.3 Management Mode Is Old Curing -- 11.6 The Conclusion -- References. , 12 Application of Virtual Reality Technology in the Teaching of 3D Animation Course -- 12.1 Virtual Reality Technology -- 12.2 Integration of Virtual Reality Technology and 3D Animation Technology -- 12.3 The Importance of Virtual Reality Technology to the Teaching of 3D Animation Courses -- 12.3.1 Innovation in Teaching Ideas -- 12.3.2 Abundance of Teaching Methods -- 12.3.3 Motivate Learners to Learn Independently -- 12.3.4 Implementation of Interactive Learning -- 12.4 The Importance of Virtual Reality Technology to the Teaching of 3D Animation Courses -- 12.4.1 Teaching of 3D Animation Course Theory -- 12.4.2 Teaching of 3D Animation Course Practice -- 12.5 Conclusion -- References -- 13 Study on Properties of Polymer Materials Based on 3D Printing Technology -- 13.1 Introduction -- 13.2 Experimental Methods -- 13.2.1 3D Printing Specimen -- 13.2.2 Tensile Test -- 13.3 Results and Discussions -- 13.4 Conclusion -- References -- 14 Improved SSD-Based Multi-scale Pedestrian Detection Algorithm -- 14.1 Introduction -- 14.2 Improved SSD Pedestrian Detection Model -- 14.2.1 Introduction of Context Information -- 14.2.2 SSD Improvement Layer Network Structure Design -- 14.3 Model Training and Analysis of Experimental Results -- 14.3.1 Data Preprocessing and Parameter Setting -- 14.3.2 Performance Evaluation Index -- 14.3.3 Experimental Results -- 14.4 Conclusion -- References -- 15 Activity Recognition System Optimisation Using Triaxial Accelerometers -- 15.1 Introduction -- 15.2 Related Works -- 15.3 Data Description -- 15.4 Results and Analysis -- 15.5 Conclusion -- References -- 16 Near-Duplicate Video Detection Based on Temporal and Spatial Key Points -- 16.1 Introduction -- 16.2 The Classic Key Frame Extraction and Video Shot Segmentation Technology -- 16.2.1 Video-Shot-Based Method -- 16.2.2 Visual-Feature-Based Method. , 16.2.3 Cluster-Based Method -- 16.3 Temporal and Visual Feature Extraction -- 16.3.1 Video Segmentation -- 16.3.2 Video Segment Feature Extraction -- 16.3.3 Video Segment Matching -- 16.4 Two Classification Methods -- 16.4.1 Similar Detection for Given Samples -- 16.4.2 Similar Video Automatic Classification -- 16.5 Experimental Results -- 16.5.1 Dataset Introduction and Experiment Procedure -- 16.5.2 Analysis of Results -- 16.6 Conclusion -- References -- 17 Surface Defect Detection Method for the E-TPU Midsole Based on Machine Vision -- 17.1 Introduction -- 17.2 Relevant Knowledge -- 17.2.1 E-TPU Material -- 17.2.2 The Theory of Second-Order Difference Method -- 17.3 Proposed Method -- 17.3.1 The Theory of Second-Time Difference -- 17.3.2 Detection Algorithm -- 17.4 Experiment and Analysis -- 17.4.1 Experimental Conditions and Methods -- 17.4.2 The Experiment Content and Result -- 17.4.3 Analysis of Experimental Results -- 17.5 Conclusion -- References -- 18 A Multi-view Learning Approach for Glioblastoma Image Contrast Enhancement -- 18.1 Introduction -- 18.2 Background -- 18.3 Proposed Method -- 18.4 Experimental Results -- 18.5 Conclusion -- References -- 19 Multi-focus Image Fusion Based on Convolutional Sparse Representation with Mask Simulation -- 19.1 Introduction -- 19.2 Convolutional BPDN Dictionary Learning with Mask Simulation -- 19.3 Proposed CSRMS-Based Fusion Method -- 19.3.1 Source Multi-focus Image Decomposition -- 19.3.2 Fusion of High-Frequency Components -- 19.3.3 Fusion of Low-Frequency Components -- 19.3.4 Image Reconstruction -- 19.4 Experiments and Analysis -- 19.5 Conclusion -- References -- 20 A Collaborative Sparse Representation-Based Approach for Pattern Classification -- 20.1 Introduction -- 20.2 Related Work -- 20.2.1 Sparse Representation-Based Classification. , 20.2.2 Weighted Group Sparse Representation Classification.