Note: Preface -- About This Book -- Contents -- Part I Computational Modelling -- 1 Computational Management-An Overview -- 1.1 Introduction -- 1.2 Computational Intelligence Techniques -- 1.2.1 Fuzzy Logic -- 1.2.2 Artificial Neural Networks -- 1.2.3 Evolutionary Computing -- 1.2.4 Learning Theories -- 1.2.5 Probabilistic Methods -- 1.3 Computational Aspects of Business Management -- 1.3.1 Marketing -- 1.3.2 Sales -- 1.3.3 Customer Relationship Management (CRM) -- 1.3.4 Finance -- 1.3.5 Human Resources -- 1.3.6 Manufacturing -- 1.3.7 Maintenance and Service -- 1.3.8 Research and Development -- 1.4 Benefits and Limitations of Computational Intelligence in Business -- 1.5 Applications of Computational Intelligence in Business -- 1.5.1 Applications of Computational Intelligence in the Field of Marketing -- 1.5.2 Computational Intelligence and Human Resource -- 1.5.3 Computational Intelligence and Finance -- 1.5.4 Computational Intelligence in Operations Management -- 1.6 Conclusion and Future Scope -- References -- 2 Mathematical and Computational Approaches for Stochastic Control of River Environment and Ecology: From Fisheries Viewpoint -- 2.1 Introduction -- 2.2 Stochastic Control -- 2.2.1 Stochastic Differential Equation -- 2.2.2 Performance Index and Value Function -- 2.2.3 HJB Equation -- 2.2.4 Remarks -- 2.3 Specific Problems -- 2.3.1 "Non-renewable" Fishery Resource Management -- 2.3.2 Dam-Reservoir System Management -- 2.3.3 Algae Growth Management -- 2.3.4 Sediment Storage Management -- 2.4 Coupled Problem -- 2.4.1 Overview -- 2.4.2 Control Problem -- 2.4.3 Numerical Scheme -- 2.4.4 Computational Conditions -- 2.4.5 Numerical Computation -- 2.5 Conclusions -- References -- 3 Models and Tools of Knowledge Acquisition -- 3.1 Introduction -- 3.1.1 Knowledge Economy -- 3.2 Literature Review -- 3.2.1 The Role and Importance of Knowledge Acquisition. , 3.2.2 Digitizing Knowledge Acquisition -- 3.3 Knowledge Management and Firm Strategy -- 3.3.1 Strategic Knowledge-An Internal and External Perspective -- 3.3.2 Competitive Intelligence -- 3.4 Knowledge Acquisition: Sources and Techniques -- 3.4.1 External Sources of Knowledge -- 3.4.2 Techniques of Knowledge Acquisition -- 3.5 Role of Technology in Knowledge Acquisition and Management -- 3.5.1 The Emergence of API Economy -- 3.5.2 Artificial Intelligence -- 3.6 Conclusion -- References -- 4 Profits Are in the Eyes of the Beholder: Entropy-Based Volatility Indicators and Portfolio Rotation Strategies -- 4.1 Introduction -- 4.2 Entropy and Its Applications to the VIX -- 4.3 Literature Review -- 4.4 Research Objectives -- 4.5 Theoretical Framework -- 4.6 Data Variables, Measurements, and Sources -- 4.7 Methods and Measures -- 4.8 Empirical Results -- 4.9 Formulation and Testing of Trading Strategies -- 4.10 Summary and Concluding Remarks -- Appendix 1: Trading Strategies Using India VIX Change and the Entropies (Both Approximate and Sample Entropies) Tested Through Simulations -- References -- 5 Asymmetric Spillovers Between the Stock Risk Series: Case of CESEE Stock Markets -- 5.1 Introduction -- 5.2 Related Literature Review -- 5.2.1 (M)GARCH Approaches to Modelling -- 5.2.2 Causality Testing and Cointegration -- 5.2.3 Spillover Methodology Approach -- 5.3 Methodology Description -- 5.3.1 VAR Models and Spillover Index -- 5.3.2 Asymmetric Spillovers -- 5.4 Empirical Results -- 5.4.1 Variable Description -- 5.4.2 Static Results -- 5.4.3 Dynamic Analysis -- 5.4.4 Robustness Checking -- 5.4.5 Simulation of Investment Strategies -- 5.5 Discussion and Conclusion -- Appendix -- References -- 6 Millennial Customers and Hangout Joints: An Empirical Study Using the Kano Quantitative Model -- 6.1 Introduction -- 6.1.1 Motivations of the Study. , 6.1.2 Background of the Study -- 6.2 Literature Review -- 6.3 Model Development -- 6.3.1 Research Gap -- 6.3.2 Research Objectives -- 6.3.3 The Kano Model -- 6.3.4 Research Design -- 6.3.5 Survey Instrument -- 6.4 Results and Discussion -- 6.4.1 Exploratory Factor Analysis Results -- 6.4.2 Reliability Analysis Results -- 6.4.3 Kano Quantitative Analysis Results -- 6.5 Conclusions and Future Scope -- 6.5.1 Conclusions -- 6.5.2 Future Scope -- References -- 7 The Effects of Oil Shocks on Macroeconomic Uncertainty: Evidence from a Large Panel Dataset of US States -- 7.1 Introduction -- 7.2 Data and Methodology -- 7.3 Results and Analysis -- 7.3.1 Linear Impulse Responses -- 7.3.2 Responses of Uncertainty Contingent on High- Versus Low-Oil Dependence States -- 7.3.3 Responses of Uncertainty at Different Horizons Conditioning on Aggregate US Uncertainty Spillovers -- 7.4 Conclusion -- Appendix -- References -- 8 Understanding and Predicting View Counts of YouTube Videos Using Epidemic Modelling Framework -- 8.1 Introduction -- 8.1.1 Literature Review -- 8.2 Building Block for Proposed Epidemic Modelling -- 8.2.1 Epidemic Modelling -- 8.2.2 Assumptions -- 8.2.3 Modelling Information Diffusion as Susceptibility Process -- 8.2.4 Modeling Viewing as Infection Process -- 8.2.5 Particular Case -- 8.3 Numerical Illustration -- 8.4 Results and Interpretation -- References -- 9 Gross Domestic Product Modeling Using ``Panel-Data'' Concept -- 9.1 Introduction -- 9.2 Materials -- 9.3 Statistical Preliminaries and Methods -- 9.4 Results -- 9.5 Concluding Remarks -- References -- 10 Supply Chain Scheduling Using an EOQ Model for a Two-Stage Trade Credit Financing with Dynamic Demand -- 10.1 Introduction -- 10.2 Literature Review -- 10.3 Assumptions and Notations -- 10.3.1 Assumptions: -- 10.3.2 Notations -- 10.4 Mathematical Formulation -- 10.5 Numerical Illustrations. , 10.6 Graphical Representations -- 10.7 Conclusion and Managerial Implications -- References -- 11 Software Engineering Analytics-The Need of Post COVID-19 Business: An Academic Review -- 11.1 Introduction -- 11.2 COVID19-Effects in Business -- 11.2.1 Tourism and Hospitality -- 11.2.2 Airlines and Aviation -- 11.2.3 Oil and Gas -- 11.2.4 Automotive Manufacturing -- 11.2.5 Consumer Products -- 11.2.6 Education -- 11.2.7 Software Industry -- 11.3 Research Methodology -- 11.4 Software Development Life Cycle (SDLC) -- 11.4.1 Software Requirements Analysis -- 11.4.2 Software Design -- 11.4.3 Software Implementation -- 11.4.4 Software Testing -- 11.4.5 Software Deployment -- 11.4.6 Software Maintenance -- 11.5 Software Analytics -- 11.5.1 Literature Analysis -- 11.5.2 Journal Publications with Frequency -- 11.5.3 Citations/Year -- 11.5.4 Software Engineering Analytics: Connotes -- 11.6 Conclusion -- References -- 12 The Rise and Fall of the SCOR Model: What After the Pandemic? -- 12.1 Introduction: The SCOR Model as a Supply Chain Management Foundation -- 12.2 The Evolution of Supply Chain Management -- 12.3 The SCOR Model-A Foundation for Supply Chain Management -- 12.3.1 Supply Chain Optimisation in the Digital Supply Chain Era -- 12.4 Is the Scor Model Still Relevant? -- 12.4.1 The Evolution of the Scor Model -- 12.4.2 The Fall of the Scor Model -- 12.4.3 Is the Resurrection of the Scor Model Possible? -- 12.5 Re-designing the Future of Supply Chains Using Scor -- 12.5.1 Re-designing for Supply Chain Reliability -- 12.5.2 Re-designing for Supply Chain Agility and Responsiveness -- 12.5.3 Re-designing for Supply Chain Asset Management -- 12.6 Concluding Remarks -- References -- Part II Management Optimization -- 13 A Comparative Study on Multi-objective Evolutionary Algorithms for Tri-objective Mean-Risk-Cardinality Portfolio Optimization Problems. , 13.1 Introduction -- 13.2 Portfolio Optimization -- 13.3 Multi-objective Evolutionary Algorithms -- 13.4 Multi-objective Evolutionary Algorithms for Portfolio Optimization Problems-A Literature Review -- 13.4.1 Mean-Variance Portfolio Optimization Using MOEAs -- 13.4.2 Mean-Risk Portfolio Optimization Using MOEAs -- 13.4.3 Three-Objective Portfolio Optimization Using MOEAs -- 13.5 Experimental Results -- 13.6 Conclusion -- References -- 14 Portfolio Insurance and Intelligent Algorithms -- 14.1 Introduction -- 14.2 Portfolio Insurance -- 14.2.1 Multi-period Portfolio Insurance Under Transaction Costs -- 14.3 Intelligent Algorithms -- 14.3.1 Beetle Antennae Search Algorithm -- 14.3.2 Popular Meta-Heuristic Algorithms -- 14.3.3 Multi-objective Optimization -- 14.3.4 The Main Algorithm for the MPMCPITC Problem -- 14.4 Portfolios' Applications with Real-World Data -- 14.4.1 Application in 4 Stocks' Portfolio -- 14.4.2 Application in 8 Stocks' Portfolio -- 14.4.3 Application in 12 Stocks' Portfolio -- 14.4.4 Application in 16 Stocks' Portfolio -- 14.4.5 Results and Performance Comparison of BAS, BA, FA and GA -- 14.5 Conclusion -- References -- 15 On Interval-Valued Multiobjective Programming Problems and Vector Variational-Like Inequalities Using Limiting Subdifferential -- 15.1 Introduction -- 15.2 Definitions and Preliminaries -- 15.3 Relationship Between (GMVVLI), (GSVVLI) and (IVMPP) -- 15.4 Relationship Between (WGMVVLI), (WGSVVLI) and (IVMPP) -- 15.5 Existence Results for (GMVVLI) and (GSVVLI) -- 15.6 Conclusions -- References -- 16 Portfolio Optimization Using Multi Criteria Decision Making -- 16.1 Introduction -- 16.2 An Overview of Multi Criteria Decision Making (MCDM) Process -- 16.3 Classification of Multi Criteria Decision Making Processes -- 16.4 Quantitative Techniques Applied for the MCDM -- 16.5 Financial Decision Problem. , 16.6 Risk Modeling and SWOT Analysis.

Note: Intro -- ICAIT-2021 Organization -- Preface -- Contents -- About the Editors -- Part I Invited Papers -- 1 Utilization of the Open-Source Arduino Platform to Control Based on Logic Eτ -- 1.1 Introduction -- 1.2 Theoretical Reference -- 1.2.1 Irrigation System -- 1.2.2 Irrigation Methods and Systems -- 1.2.3 Localized Irrigation -- 1.2.4 Paraconsistent Logic -- 1.2.5 Paraconsistent Annotated Evidential Logic Eτ -- 1.2.6 Para-Analyser Algorithm -- 1.2.7 Arduino -- 1.3 Methodology -- 1.4 Results -- 1.5 Conclusion -- References -- 2 Ontology Implementation of OPC UA and AutomationML: A Review -- 2.1 Introduction -- 2.2 Research Method -- 2.3 Results Analysis -- 2.4 Discussions -- 2.5 Conclusions -- References -- Part II Regular Papers -- 3 Airport Cab Scheduling Model Based on Queuing Theory -- 3.1 Problem Restatement -- 3.1.1 Problem Background -- 3.1.2 Problem Requirements -- 3.2 Model Assumptions -- 3.3 Symbol Description -- 3.4 Problem Analysis -- 3.4.1 Problem One Analysis -- 3.4.2 Problem Two Analysis -- 3.4.3 Problem Three Analysis -- 3.4.4 Problem Four Analysis -- 3.5 Model Building and Solving -- 3.5.1 Give the Taxi Driver's Decision Model in the Two Choices of A and B -- 3.5.2 Analyze the Rationality of the Model Through the Relevant Data of a Domestic Airport and Its City Taxi -- 3.5.3 How to Set the "Boarding Point" to Maximize the Efficiency of the Ride -- 3.5.4 A Theoretical Analysis of the Scale of "Boarding Points" and Lane Sides -- 3.5.5 According to the Difference in the Mileage of Different Taxis, Develop a "Priority" Arrangement Plan to Maximize Time and Revenue -- References -- 4 Machine Reading Comprehension Model Based on Multi-head Attention Mechanism -- 4.1 Introduction -- 4.2 Related Work -- 4.2.1 DuReader Dataset -- 4.2.2 DuReader Baseline Model -- 4.2.3 Multi-headed Attention Mechanism -- 4.3 Multi-head Attention Mechanism. , 4.3.1 Multi-head Attention Presidential Structure -- 4.3.2 Scaled Dot-Product Attention -- 4.4 Model Structure -- 4.4.1 Task Definition -- 4.4.2 Embedded Layer -- 4.4.3 Coding Layer -- 4.4.4 Matching Layer -- 4.4.5 Modeling Layer -- 4.4.6 Output Layer -- 4.5 Experiments and Results -- 4.5.1 Evaluation Criteria -- 4.5.2 Dataset -- 4.5.3 Experiments and Results -- 4.6 Conclusion -- References -- 5 Design of Military Physical Fitness Evaluation System Based on Big Data Clustering Algorithm -- 5.1 Introduction -- 5.2 Hardware Unit Design of Military Physical Fitness Evaluation System -- 5.3 Software Module Design of Military Physical Fitness Evaluation System -- 5.3.1 Construction Module of Military Physical Fitness Evaluation Index System -- 5.3.2 Application Module of Big Data Clustering Algorithm -- 5.3.3 Database Building Module -- 5.4 Experiment and Result Analysis -- 5.4.1 Construction of Experimental Environment -- 5.4.2 Experimental Data Analysis -- 5.4.3 Acquisition of Experimental Results -- 5.5 Conclusion -- References -- 6 ResNet-Based Multiscale U-Net for Human Parsing -- 6.1 Introduction -- 6.2 Related Work -- 6.3 Our Proposed Method -- 6.3.1 Encoder -- 6.3.2 Decoder -- 6.3.3 Multiscale Feature Fusion -- 6.4 Experiments -- 6.4.1 Datasets -- 6.4.2 Evaluation Metrics -- 6.4.3 Results -- 6.5 Conclusion -- References -- 7 Short-Term Electricity Price Forecast Based on SSA-SVM Model -- 7.1 The Introduction -- 7.2 SSA -- 7.3 SVM -- 7.4 The SSA-SVM Model -- 7.5 Example Analysis -- 7.5.1 Data Processing -- 7.5.2 Data Normalization -- 7.5.3 Evaluation Indicators -- 7.5.4 Analysis of Prediction Results -- 7.6 Conclusion -- References -- 8 Research on Mobile Advertising Click-Through Rate Estimation Based on Neural Network -- 8.1 Pricing and Placement of Advertisements -- 8.2 The AUC Indicators. , 8.3 Estimating Click-Through Rates of Mobile Ads Based on Neural Networks -- 8.3.1 Model -- 8.3.2 Objective Function and Algorithm -- 8.3.3 Key Points of Optimization -- 8.3.4 Result Analysis -- 8.4 Conclusion -- References -- 9 Research on Macroeconomic Prediction Technology Based on Wavelet Neural Network -- 9.1 Prediction Technology -- 9.2 Optimized Wavelet Neural Network Model -- 9.3 Case Study -- 9.3.1 Specific Introduction -- 9.3.2 Training of Learning Samples -- 9.3.3 Analyze the Macroeconomic Forecast Results -- 9.4 Conclusion -- References -- 10 Design Research on Financial Risk Control Model Based on CNN -- 10.1 Risk Control Model in Unbalanced Data Environment -- 10.1.1 Features of Financial Data -- 10.1.2 Pretreatment -- 10.1.3 Risk Control Model -- 10.2 Convolutional Neural Network (CNN) is Used to Build a Financial Risk Control Model -- 10.2.1 Design Network Structure -- 10.2.2 Result Analysis -- 10.2.3 Innovative Analysis -- 10.3 Conclusion -- References -- 11 Application of Multi-objective Optimization Algorithm in Financial Market Portfolio -- 11.1 Genetic Algorithm Analysis of Multi-objective Programming -- 11.2 Analysis of Portfolio Optimization Model Based on Genetic Algorithm -- 11.2.1 Model Framework -- 11.2.2 Factor Analysis -- 11.2.3 Risk Indicators -- 11.3 Application Results -- 11.3.1 Data Processing -- 11.3.2 Optimal Solution of Investment Portfolio -- 11.3.3 Comparative Analysis -- 11.4 Conclusion -- References -- 12 Research on Success Factors of Long Rental Apartment Based on SEM-ANN -- 12.1 Introduction -- 12.2 Methods -- 12.2.1 SEM Model -- 12.2.2 ANN Model -- 12.2.3 Research Model Based on SEM-ANN -- 12.3 Result Analysis -- 12.4 Conclusion -- References -- 13 T-AGP: A Kind of Music-Researching Method Based on Data-Driven Comprehensive System of Network Analysis -- 13.1 Introduction. , 13.2 Structure and General Description -- 13.3 The Influencer Network and Influence Analysis -- 13.3.1 Influence Measures -- 13.3.2 Subnetwork Analysis -- 13.4 Similarity Measure -- 13.4.1 The Exploration of Core Features -- 13.4.2 Micro-Similarity Between Two Pieces of Music -- 13.4.3 Macro-Similarity Between Two Genres -- 13.5 Similarity and Difference Between Genres -- 13.5.1 Genre Similarity Analysis -- 13.5.2 Genre Influence Analysis -- 13.5.3 What Distinguishes a Genre -- 13.5.4 Relationships Between Genres -- 13.5.5 Genres' Changes Over Time -- 13.6 The Mechanism of Influence from Influencer to Follower in Music -- 13.7 Dynamic Analysis Over Time and Identification of Major Leaps in Music -- 13.7.1 Dynamic Analysis of the Network -- 13.7.2 Music Characteristics' Evolution Over Time -- 13.8 Cultural Influence on Music -- 13.8.1 Influence from Technology -- 13.8.2 Influence from Social and Political Revolution -- 13.9 Conclusions and Prospects -- 13.9.1 Conclusions -- 13.9.2 Weakness -- 13.9.3 Prospects -- References -- 14 Application of Improved Algorithm of BP Neural Network -- 14.1 Model Analysis of BP Neural Network -- 14.2 Improve the Algorithm -- 14.3 Specific Application -- 14.3.1 PI Parameter Tuning of Valve Positioner -- 14.3.2 Shipboard Navigation System -- 14.4 Conclusion -- References -- 15 Application of Improved Harmony Search Algorithm in Photovoltaic MPPT Under Partial Shadow Conditions -- 15.1 Introduction -- 15.2 Analysis of Output Characteristics of Photovoltaic Cells Array in Partial Shadow -- 15.3 Harmony Search (HS) Algorithm -- 15.3.1 Traditional Harmony Search Algorithm -- 15.3.2 Improvement of Traditional HS Algorithm -- 15.3.3 MPPT Control Method Based on IHS Algorithm -- 15.4 Simulation Experiment Analysis -- 15.5 Conclusion -- References -- 16 A Traditional Butterfly Optimization Algorithm MPPT Method. , 16.1 Introduction -- 16.2 Multi-peak Output Characteristics of Photovoltaic Cells Under Local Shade -- 16.2.1 Mathematical Models of Multiple Photovoltaic Cells -- 16.2.2 Multi-peak Output Characteristics -- 16.3 MPPT Flow Chart Based on BOA -- 16.4 Simulation and Result Analysis -- 16.4.1 Simulation -- 16.4.2 Result Analysis -- 16.5 The Conclusion -- 1. References -- 17 Crops Plantation Problem in Uncertain Environment -- 17.1 Introduction -- 17.1.1 Motivation -- 17.1.2 Literature Review -- 17.1.3 Proposed Approaches -- 17.2 Basic Principles -- 17.3 Uncertain Crops Plantation Problem -- 17.4 Method -- 17.5 Conclusion -- References -- 18 Simplified Full-Newton Step Method with a Kernel Function -- 18.1 Introduction -- 18.2 Preliminaries -- 18.2.1 The Central Path of the Perturbed Problems -- 18.2.2 Search Directions -- 18.2.3 The Iterative Process of the Algorithm -- 18.3 The Properties of Simple Function and the Proximity Function -- 18.4 Algorithm Analysis -- 18.4.1 The Feasibility Step -- 18.4.2 Upper Bounds for paralleldxfparallel -- 18.4.3 Values of θ and τ -- 18.4.4 Centering Steps -- 18.4.5 Total Number of Main Iterations -- 18.5 Conclusion -- References -- 19 Marine Ship Identification Algorithm Based on Object Detection and Fine-Grained Recognition -- 19.1 Introduction -- 19.2 Overall Process -- 19.3 Design Scheme -- 19.3.1 Construction of Data Sets -- 19.3.2 Target Detection Network -- 19.3.3 Fine-Grained Identification Network -- 19.4 Experimental Verification -- 19.5 Conclusions and Prospects -- References -- 20 Automatic Detection of Safety Helmet Based on Improved YOLO Deep Model -- 20.1 Introduction -- 20.2 YOLOv5 Network Model -- 20.2.1 Input -- 20.2.2 Backbone -- 20.2.3 Neck -- 20.2.4 Output -- 20.3 Improvements -- 20.3.1 Anchor Boxes and Detection Scale -- 20.3.2 Loss Function -- 20.4 Experimental Result and Analysis. , 20.4.1 Dataset.

Note: Intro -- Waste Management in the Fashion and Textile Industries -- Copyright -- Contents -- Contributors -- Part One: Introduction -- Chapter 1: Fashion waste management problem and sustainability: A developing country perspective -- 1.1. Introduction -- 1.2. Waste management -- 1.2.1. 3R approach -- 1.2.2. Exchange and renting -- 1.2.3. Upcycling concept -- 1.2.4. Controlling waste by lean concepts -- 1.2.4.1. Minimizing process waste -- 1.2.4.2. Minimizing material waste -- 1.2.5. Effluent treatment -- 1.2.6. Fashion consumption and consumer attitude -- 1.2.7. Product life cycle assessment -- 1.2.8. Recyclability -- 1.3. Recycling of plastics (polyester and nylon) -- 1.4. Survey findings -- 1.5. Conclusions and future directions -- Acknowledgment -- References -- Chapter 2: Hazards of fashion and textile waste: Approaches for effective waste management -- 2.1. Introduction -- 2.2. Problems and hazards associated with raw material types -- 2.3. Hazards of wasteful utilization of toxic chemicals-Land, water, and air pollution -- 2.3.1. Problems and hazards associated with toxic chemicals -- 2.3.2. Problems and hazards associated with water and air pollution -- 2.3.3. Problems and hazards associated with soil infertility and degradation -- 2.4. Problems and hazards caused by textile and fashion waste -- 2.4.1. Textile waste and associated hazards -- 2.4.2. Hazards and waste from fashion industry -- 2.4.3. Hazards of overproduction in fashion industry -- 2.4.4. Deleterious impacts of fast fashion on environment -- 2.4.5. Hazards due to transport and shipment of fashion merchandise -- 2.4.6. Hazards due to improper buying and usage behavior of consumers -- 2.4.7. Hazards due to problematic recycling -- 2.4.8. Hazards associated with fashion waste -- 2.5. Waste management strategies to combat textile and fashion hazards. , 2.5.1. Role of designers in waste management -- 2.5.2. Waste management at the raw material procurement stage -- 2.5.3. Role of manufacturers in waste management -- 2.5.4. Waste management by minimal and effective utilization of chemicals and water -- 2.5.5. Waste management by effective utilization of water -- 2.5.6. Wastewater recycling and treatment -- 2.5.6.1. Wastewater treatment -- 2.5.7. Waste elimination at source and waste minimization -- 2.5.7.1. Product changes as means of waste minimization -- 2.5.7.2. Process changes as means of waste minimization -- 2.5.8. Waste management by recycling and regeneration -- 2.5.8.1. Recycling and regeneration techniques -- 2.5.9. Innovative approaches by fashion industry for waste management -- 2.5.9.1. Emergence of smart fashion -- 2.5.9.2. Introducing the concept of slow fashion -- 2.5.9.3. Principle of sharing economy -- 2.5.9.4. Extended producer responsibility (EPR) and in-store collection -- 2.5.9.5. Endorsing closed loop system -- 2.5.9.6. Raising consumer awareness -- 2.5.10. Role of brands in waste management -- 2.5.11. Role of consumers in waste management -- 2.5.12. Disposal ecology for waste management -- 2.6. Conclusions -- Further reading -- Part Two: Waste management technologies in manufacturing -- Chapter 3: Management of spinning and weaving wastes -- 3.1. Introduction -- 3.2. Classification of waste -- 3.3. Waste in spinning -- 3.3.1. Blow room -- 3.3.2. Carding -- 3.3.3. Draw frame -- 3.3.4. Combing -- 3.3.5. Simplex -- 3.3.6. Ring frame -- 3.3.7. Winding -- 3.4. Waste in weaving -- 3.4.1. Warping -- 3.4.2. Sizing -- 3.4.3. Knotting -- 3.4.4. Gaiting/tying-in wastage -- 3.4.5. Selvedge -- 3.4.6. Chindi -- 3.4.7. Beam residual wastage -- 3.5. Recycling of spinning and weaving waste -- 3.6. Machine for waste management -- 3.6.1. Willow machine -- 3.6.2. Marzoli trash analyzer. , 3.6.3. Marzoli recycling waste reopener (RWR) -- 3.6.4. Roving stripping and opening machine -- 3.6.5. Thread extractor (Bhatia, 2017) -- 3.6.6. Garnetting machine -- 3.7. Conclusions -- Acknowledgment -- References -- Chapter 4: Management of wastes in garment manufacturing -- 4.1. Introduction -- 4.2. The importance of marker planning and fabric waste management -- 4.3. Recycling fiber, yarn, and fabric wastes and recent trends -- 4.4. Bangladesh using cotton waste as a source of biogas -- 4.5. Solid waste from the Ethiopian leather sector -- 4.6. The control measures in waste management -- 4.6.1. What can be done to minimize wastes? -- Garneting -- Web preparation -- 3D weaving -- Composite manufacturing -- Compression molding -- Seamless garments -- 4.7. Conclusions and future directions -- References -- Chapter 5: Technologies for the management of wastewater generated in wet processing -- 5.1. Introduction -- 5.2. Control of effluent quality -- 5.2.1. Equalization -- 5.2.2. Recovery of by-products -- 5.2.3. Process modification -- 5.2.4. Loss of chemicals -- 5.2.5. Segregation -- 5.3. Effluent treatment methods -- 5.3.1. Coagulation, flocculation, and precipitation -- 5.3.2. Adsorption methods -- 5.3.3. Synthetic ion exchangers -- 5.3.3.1. Fiber-based synthetic bioabsorbents -- 5.3.4. Biological treatments -- 5.3.5. Oxidation techniques -- 5.3.6. Membrane separation -- 5.3.6.1. Microfiltration (MF) -- 5.3.6.2. Ultrafiltration (UF) -- 5.3.6.3. Nanofiltration (NF) -- 5.3.6.4. Hyperfiltration (HF)/reverse osmosis (RO) -- 5.3.7. Electrochemical processes -- 5.3.7.1. Electrodialysis -- 5.4. Effluent treatment plant -- 5.5. Conclusions -- References -- Chapter 6: Management of air quality -- 6.1. Introduction -- 6.2. Effluent gas -- 6.2.1. CO2 removal -- 6.2.1.1. Amine scrubbing -- 6.2.1.2. CO2 storage -- 6.2.2. SOx removal -- 6.2.3. NOx removal. , 6.2.4. Mercury removal -- 6.3. Volatile organic compounds (VOCs) -- 6.4. Activated carbon fibers -- 6.5. Alternative technologies -- 6.6. Conclusions -- Funding -- References -- Part Three: Retail and consumer waste management technologies -- Chapter 7: Packaging waste and their management technologies -- 7.1. Introduction -- 7.2. Packaging defined -- 7.3. Functions of packaging -- 7.4. Materials used for packaging -- 7.5. Consumer attitudes -- 7.6. Managing package waste -- 7.6.1. Recycle -- 7.6.2. Waste prevention or material minimization -- 7.6.3. Reuse -- 7.6.4. Compostable -- 7.6.5. Energy recovery -- 7.7. Conclusions and future directions -- References -- Chapter 8: End of life clothes and their management -- 8.1. Introduction -- 8.2. Collection of used clothing -- 8.3. Reuse of secondhand clothing -- 8.4. Redesign and remanufacturing -- 8.5. Recycling -- 8.5.1. Mechanical recycling -- 8.5.2. Thermal recycling -- 8.5.3. Chemical recycling -- 8.6. Energy recovery -- 8.7. Disposal to landfill -- 8.8. Conclusions -- References -- Chapter 9: Organizations and standards related to textile and fashion waste management and sustainability -- 9.1. Introduction -- 9.1.1. Waste management and sustainability -- 9.1.1.1. Green manufacturing and recycling in fashion -- Organic cotton -- Organic cotton production across the globe -- The opportunities and setting standards for organic cotton -- 9.1.1.2. Green distribution -- 9.1.1.3. Green retailing -- 9.2. Organizations for waste management and sustainability -- 9.2.1. Fashion brands -- 9.2.1.1. HandM -- 9.2.1.2. Marks and Spencer -- 9.2.1.3. Patagonia -- 9.2.1.4. Nike -- 9.2.2. Few other fashion brands -- 9.3. Standards for waste management and sustainability -- 9.3.1. Global organic textile standards (GOTS) -- 9.3.2. Sustainable textile production (STeP) by OEKO-TEX. , 9.3.3. Eco-label certification such as STANDARD 100 by OEKO-TEX -- 9.3.4. Bluesign -- 9.3.5. Cradle to cradle -- 9.3.6. International standards organization -- 9.3.7. Higg index and sustainable apparel coalition -- 9.4. Other organizations and events -- 9.4.1. Zero discharge of hazardous chemicals (ZDHC) -- 9.4.2. UNGC code of conduct for the fashion and textile industry -- 9.4.3. Copenhagen fashion summit -- 9.4.4. Dow Jones sustainability world index -- 9.4.5. Fashion transparency index -- 9.4.6. Youth fashion summit -- 9.4.7. Specific codes of conduct in Australia -- 9.4.8. Specific codes of conduct in Germany -- 9.5. Extended producer responsibility (EPR) for textiles -- 9.5.1. EPR program for postconsumer textiles and clothing recovery -- 9.6. Challenges and opportunities in waste management with Indian paradigms -- 9.6.1. Upasana studio, Auroville, India -- 9.6.1.1. Tsunamika -- 9.6.1.2. Small steps -- 9.6.2. Fabric Monde, Bengaluru -- 9.6.3. Pratibha Syntex, Indore -- 9.6.4. Stylumia, Bengaluru -- 9.7. Conclusions and future directions -- 9.7.1. Significant findings -- 9.7.2. Future directions -- References -- Part Four: Other waste management technologies -- Chapter 10: Automotive waste management technologies -- 10.1. Introduction -- 10.2. Automotive waste -- 10.2.1. Recycling and energy recovery -- 10.2.2. Mechanical recycling -- 10.2.3. Argon process -- 10.2.4. Thermal treatment process -- 10.2.4.1. Pyrolysis process -- 10.2.4.2. Sequential gasification and combustion -- 10.2.5. Injecting molding with automobile shredder residue -- 10.3. Recycling automotive composites and components -- 10.4. End of life (EOL) -- 10.5. Other applications -- 10.6. Conclusions -- Funding -- References -- Chapter 11: Waste management in coated and laminated textiles -- 11.1. Introduction -- 11.2. Coated and laminated textiles -- 11.2.1. Coated textiles. , 11.2.2. Nanomaterial incorporated coated textiles.

Note: Intro -- Preface -- Acknowledgements -- Contents -- Editors and Contributors -- Decision Support System -- Recommended Model of Pollution Information Based on Collaborative Filtering Algorithm -- 1 Introduction -- 2 Calculation of the Similarity of Pollution Information -- 3 Default Prediction Complement -- 4 Obtaining the Similarity Matrix Between Users -- 5 The Solution of the Model -- 6 Analysis of Model Results -- References -- Research on the Evaluation of TCM Service Level in Various Regions of China -- 1 Introduction -- 2 Data Sources and Methods -- 2.1 Data Sources -- 2.2 Methods -- 3 Results -- 3.1 Principal Component Analysis -- 3.2 Cluster Analysis -- 4 Discussion -- 4.1 Regional Disparities in TCM Service Levels -- 4.2 The Effect of Health Services is not Commensurate with the Level of Economic Development -- References -- A Method for Evaluating Health Status of Rail Transit Signaling Equipment Based on Group Decision -- 1 Introduction -- 2 Related Work -- 3 Establishing Rules for an Evaluation System -- 3.1 Defining an Evaluation Organization -- 3.2 Defining the Evaluation Scope -- 3.3 Establishing the Weight Coefficient Vector -- 3.4 Establishing Alarm Rules to Monitor Equipment Faults -- 3.5 Setting Parameters for an Equipment Type -- 4 Implementation of an Evaluation System -- 4.1 Fault Monitoring Cycle -- 4.2 Health Evaluation Cycle -- 5 Conclusion -- References -- Intelligent Decision Support System for Precision Medicine (IDSS 4 PM) -- 1 Introduction -- 2 Theoretical Foundation-Simon's Model of Decision-Making -- 3 Intelligent Decision Support Systems (IDSSs) -- 4 Precision Medicine: An Emerging Approach in Medical Decision-Making -- 5 How Technologies Are Advancing Precision Medicine? -- 5.1 Business Analytics -- 5.2 Cognitive Computing -- 6 Theory Practice and Discussion -- 7 Characteristics of IDSS 4 PM -- 8 Conclusion. , References -- A Study of Result-Oriented Performance Appraisal-Taking Huawei as an Example -- 1 Introduction -- 2 Increasing Flexibility of Bonus Package -- 2.1 Reducing Long-Term Returns and Increasing Short-Term Returns -- 2.2 Widening the Gap and Clarifying the Hierarchy -- 2.3 Awarding the Current Contribution Immediately -- 3 Abandoning the Cumbersome Human Resource Assessment -- 3.1 Assessment by Objectives -- 3.2 Avoiding Establishing KPI Indicators in Isolation for Each Department -- 4 Taking the Responsibility and Result-Oriented Method -- 4.1 Good Performance and Good Return -- 4.2 Combination of Performance Evaluation and Reverse Evaluation -- 4.3 Eliminating Pretending Hard-Working -- 5 The Conclusion -- References -- Under a Management Perspective: Analysis of the Relationship Between Trust and Behavior Decision-Making -- 1 Introduction -- 2 Data and Measurement -- 2.1 Data Sources -- 2.2 Variable Description and Reliability Validity Test -- 3 Data Analysis and Discussion -- 3.1 The Difference of Public Trust Under Different Demographic Variables -- 3.2 The Differences in the Ways of Public Behavior Decision-Making Under Different Demographic Variables -- 3.3 The Relationship Between Trust and Behavior Decision-Making -- 4 Conclusion -- References -- Research on the Regulation of Industrial Structure in the Mid-Southern Liaoning Urban Agglomeration from the Perspective of Spatial Connection -- 1 Introduction -- 2 Research Area and Data Sources -- 2.1 Overview of the Study Area -- 2.2 Data Sources -- 3 Research Method -- 3.1 Spatial Shift-Share Model -- 3.2 Determination and Improvement of Spatial Weight -- 4 Result Analysis -- 4.1 Analysis of the Temporal and Spatial Pattern of Urban Spatial Interaction -- 4.2 Analysis of Shift Share of Industrial Structure -- 5 Conclusions -- References. , Research on the Influence Mechanism of Family-Supportive Supervisor Behaviors on Employees' Intention to Stay from the Perspective of Dual Scenario Embeddedness -- 1 Introduction -- 2 Theoretical Basis and Research Hypothesis -- 2.1 FSSB and Employees' Intention to Stay -- 2.2 The Mediating Role of Dual Scenario Embeddedness -- 2.3 The Moderating Role of Employees' Gratitude as a Trait -- 3 Study Design -- 3.1 Participants and Survey Methods -- 3.2 Variable Measurement -- 4 Research Results -- 4.1 Descriptive Statistical Analysis -- 4.2 Discrimination Validity Analysis and Common Method Test -- 4.3 Hypothesis Testing -- 5 Conclusion -- 5.1 Theoretical Contribution -- 5.2 Management Implications -- 5.3 Research Limitations and Prospects -- References -- Policy Burden, Industry Competition, and Corporate Risk-Taking -- 1 Introduction -- 2 Theoretical Analysis and Research Hypothesis -- 2.1 Policy Burden and Corporate Risk-Taking -- 2.2 The Regulating Effect of Industry Competition -- 3 Research Design -- 3.1 Sample Selection and Data Sources -- 3.2 Variable Selection and Model Design -- 4 Empirical Results -- 4.1 Descriptive Statistics -- 4.2 Analysis of Regression Results -- 5 Endogenous Control and Robustness Test -- 5.1 Endogenous Problems -- 5.2 Robustness Analysis -- 6 Research Conclusions -- References -- Blended Teaching Mode of Tourism English Based on TPACK -- 1 Introduction -- 2 TPACK Theory -- 3 ESP and Tourism English -- 4 Research Design -- 4.1 Design Concept -- 4.2 Problem Design -- 4.3 Subjects and Teaching Contents -- 4.4 Research Steps -- 5 Experimental Conclusion -- References -- Technology and Innovation Management -- Research on Privacy Protection of Internet of Things Search Data Based on Fine-Grained Authorization -- 1 Introduction -- 2 Background Knowledge -- 2.1 Secret Search -- 2.2 Attribute-Based Encryption Scheme. , 3 System Program -- 3.1 System Architecture -- 3.2 Program Process -- 4 Safety and Performance Analysis -- 4.1 Security Analysis -- 4.2 Performance Analysis -- 5 Concluding Remarks -- References -- Design of Emergency Rescue Deduction System for Bus Fire Accident Based on Virtual Reality -- 1 Introduction -- 2 The Functional Requirements of Deducing System -- 3 The Design of Deduce System Architecture -- 4 Function Design of Deducing System -- 4.1 Scene Editing Module -- 4.2 Deduce Management Module -- 4.3 Client Operation Module -- 5 Composition of the Deduction System -- 6 Conclusion -- References -- Application of Game Theory in the Field of Technology Innovation -- 1 Introduction -- 2 The Application of Oligopoly Model in Technological Innovations -- 2.1 The Development of Cournot Model in Technological Innovations -- 2.2 Application and Development of Stackelberg in Technological Innovations -- 2.3 Application of Option Game Oligopoly Model in Technology Innovations -- 3 Research on Evolutionary Game Model in Technological Innovations -- 3.1 The Application of Evolutionary Game in Technological Innovations -- 3.2 The Development of Evolutionary Game Model in Technological Innovations -- 4 The Development Direction of Game Theory in Technological Innovations -- References -- Research on Innovation Mechanism of Corporate Volunteering in China -- 1 Introduction -- 2 The Concept and Connotation of Corporate Volunteering -- 3 The Status Quo of Volunteering in Chinese Enterprises -- 3.1 The Integration of Business Objectives Is Important for the Business Development Plan -- 3.2 Win the Sense of Belonging of Employees and the Identity of External Customers -- 3.3 Corporate Public Services Take from Society and Use for Society -- 3.4 Volunteering of Different Enterprises Vary Greatly -- 3.5 Long-Term Development of Volunteering Projects. , 3.6 Undertaking Government Public Service -- 4 Problems in the Development of Enterprise Volunteering in China -- 4.1 Insufficient Government Guidance -- 4.2 Information Guidance is not Strong -- 4.3 Lack of Corporate Volunteering Standards -- 4.4 Imbalance Between Long-Term and Short-Term Benefits -- 5 Development Trend of Corporate Volunteering -- 5.1 Internetization of Corporate Volunteering -- 5.2 Normalization of Corporate Volunteering -- 5.3 Diversification of Corporate Volunteering -- 5.4 Establish Self-organization of Corporate Volunteers -- 5.5 Corporate Volunteering Are Becoming More Standardized and Strict -- 6 Innovation of Corporate Volunteering Mechanism -- 6.1 Building Communication Network and Innovating Corporate Volunteering Mechanism -- 6.2 Taxation Policy -- 6.3 Expense Subsidies -- 6.4 Performance Evaluation -- 6.5 Establish a Sound Education and Training Mechanism -- 6.6 Establish a Sound Guarantee Mechanism to Protect the Volunteering of Enterprises -- References -- Research on the Differential Incentive Effect of Patent Pool on Specific Technology Learning -- 1 Research Background -- 2 Theoretical Analysis and Research Hypothesis -- 2.1 The Impact of Patent Pool Formation on Specific Technology Learning -- 3 Research Design -- 3.1 Data and Samples -- 3.2 Variables and Their Measurement -- 4 Empirical Results and Analysis -- 4.1 Descriptive Statistical Analysis -- 4.2 Hypothesis Testing -- 5 Conclusion and Inspiration -- 5.1 Research Conclusion -- 5.2 Management Suggestions -- References -- Research on Present Situation and the Countermeasure Analysis of Football Training in University -- 1 Introduction -- 2 The Present Situation of Campus Football Training in China -- 3 Problems in the Development of Campus Football Activities in China -- 3.1 Students' Poor Awareness for Football Activities. , 3.2 Unreasonable Arrangement of Football Activities.

Note: Intro -- Preface -- Contents -- About the Editors -- Mechatronics -- 1 Simulation of Off-Wheel Problem of Triangle Tracked Vehicle Based on RecurDyn -- Abstract -- 1 Introduction -- 2 Structure and Relevant Technical Parameters of Triangular Track -- 3 Simulation Test -- 3.1 Virtual Prototype Modeling -- 3.2 Simulation Test on off-Wheel Problem of Track -- 3.3 Simulation Test on Vehicle S Bend -- 4 Conclusion -- References -- 2 Brief Design Requirements of Screen Printing Stencil -- Abstract -- 1 Introduction -- 2 Stencil Design -- 2.1 Frame Design of Circuit Board Stencil -- 2.2 Design of Stencil Tension Net -- 2.3 Mark Point Design of Stencil -- 2.4 Aperture Design of Stencil -- 2.5 Thickness Design of Stencil -- 3 Requirements for Opening Size and Shape of Stencil -- 3.1 Chip Components-Resistors, Inductors, Capacitors -- 3.2 Power MOSFET -- 3.3 QFP, SOP, QFN, IC -- 3.4 BGA -- 4 Conclusion -- References -- 3 Review of Improved Collaborative Filtering Recommendation Algorithms -- Abstract -- 1 Introduction -- 2 Overview of Traditional Collaborative Filtering Algorithms -- 2.1 User-Based Collaborative Filtering Recommendation Algorithm -- 2.2 Item-Based Collaborative Filtering Recommendation Algorithm -- 2.3 Model-Based Collaborative Filtering Recommendation Algorithm -- 3 Improvement and Application of Collaborative Filtering Algorithm -- 3.1 The New Theory Is Introduced into Collaborative Filtering -- 3.2 Data Dynamic Analysis Combined with Collaborative Filtering -- 3.3 Combination of Data Rule Mining and Collaborative Filtering -- 4 Conclusion -- References -- 4 A Preliminary Study on the Application of Computer Technology in Physical Education -- Abstract -- 1 Introduction -- 2 Design of Instructional Model of Autonomous Physical Education Based on Computer Technology -- 2.1 Part Before Class -- 2.2 Part in Class -- 2.3 Part After Class. , 3 Application Analysis of Physical Education Teaching Model Based on Computer Technology -- 3.1 Experimental Subject -- 3.2 Experimental Procedure -- 3.3 Experimental Method -- 3.4 Experimental Result -- 4 Conclusion -- References -- Intelligent Systems -- 5 Design of Archives Management System for Teaching -- Abstract -- 1 Introduction -- 2 Requirement Analysis of System and Database Design -- 2.1 Requirement Analysis -- 2.2 System Functional Structure Design -- 2.3 Database Design -- 3 System Function Realization -- 3.1 Login Module Design -- 3.2 Registration Module Design -- 4 System Test and Operation Result Analysis -- 5 Conclusion -- Acknowledgements -- References -- 6 An Algorithm for Distinguishing Between Speech and Music -- Abstract -- 1 Introduction -- 2 Audio-Related Features -- 3 Algorithm Steps -- 4 Experimental Result -- 5 Summary -- Acknowledgements -- References -- 7 Research on Multiple Overlapping Speakers Number Recognition Based on X-Vector -- Abstract -- 1 Introduction -- 2 Approach -- 2.1 X-Vector -- 2.2 Data Preprocessing -- 2.3 Improving of Feature Extraction -- 3 Experimental Results -- 4 Conclusions -- References -- 8 Discussion on Production Technology and Testing Technology of 1553B Bus Cable Net for Satellite -- Abstract -- 1 Introduction -- 2 Composition of 1553B Bus Cable -- 2.1 1553B Cable Structure -- 2.2 Composition of 1553B Bus Cable -- 3 1553B Bus Cable Network Assembly Process -- 4 1553B Bus Cable Network Installation Quality Test -- 4.1 Bus Cable Net Appearance Inspection -- 4.2 1553B Bus Cable Network Static Performance Test -- 4.3 1553B Bus Cable Network Dynamic Performance Test -- 5 Conclusion -- References -- 9 Feasibility Analysis of Venture Capital Committee in the Innovative Design of Class Management in Colleges and Universities -- Abstract -- 1 Introduction. , 2 Major Pain Points of Class Management in Colleges and Universities -- 2.1 Different Opinions About Head Teacher's Impact on Class -- 2.2 Weak Initiative of Class Cadre -- 2.3 A General Lack of Class Fee -- 2.4 Little Contact with Classes After Graduation -- 3 Pain Points Analysis of Class Management in Colleges and Universities -- 3.1 Urgent Need of System Construction Innovation -- 3.2 Difference in Value Proposition -- 3.3 Foundation -- 3.4 Repulsion and Practical Difficulties -- 4 Innovative Design of Class Management in Colleges and Universities -- 4.1 Description of Class Management Tools -- 4.2 The Feasibility Analysis of Innovative Design -- 5 Conclusions -- Acknowledgements -- References -- 10 A Survey and Study on Satisfaction and Influencing Factors Using Ant Credit Pay via Intelligent Processing -- Abstract -- 1 Introduction -- 2 Literature Review -- 3 Data Analysis Method and Theoretical Basis -- 3.1 Chi-Square Test Principle -- 3.2 Principle of Correlation Analysis -- 3.3 Satisfaction Principle -- 3.4 Establishing the Satisfaction Index System -- 4 Analysis on the Satisfaction and Influencing Factors -- 4.1 Reliability Analysis and Validity Analysis of Data -- 4.2 Analysis of College Students' Satisfaction with Using "Ant Credit Pay" -- 4.3 Analysis of College Students' Satisfaction -- 4.4 Analysis of Influencing Factors -- 5 Some Suggestions -- 5.1 Individual Consumption Needs to Be Tailored -- 5.2 Pay Attention to Self-credit and Enhance Self-protection Consciousness -- 5.3 Appropriately Reduce the Withdrawal Procedure Rate and Expand the Use of "Ant Credit Pay" in Daily Life -- References -- 11 A Review on Main Optimization Method of ALBERT in Natural Language Processing -- Abstract -- 1 Introduction -- 2 Recent Development -- 3 Solve the Problem of Insufficient Text Word Vector Learning by Classifying the Output Features of ALBERT. , 4 Solve the Problem of Gradient Explosion and Disappearance in the Process of Long Text Training by Combining the Bi-LSTM Model -- 5 By Combining CRF Model to Better Recognize Long Texts -- 6 By Combining the BiGRU Model to Maximize the Preservation of the Semantic Association of Word Vectors in Long Texts -- 7 Conclusion -- References -- 12 Study on the Influencing Factors of Customer Loyalty in Large Smart Home Furnishing Stores -- Abstract -- 1 Introduction -- 2 Related Theory of Influencing Factors of Customer Loyalty -- 2.1 Experience Marketing -- 2.2 Customer Satisfaction -- 2.3 Measurement of Customer Loyalty -- 3 Establishment of Influencing Factor Model of Customer Loyalty -- 3.1 Selection of Modeling Dimension -- 3.2 Research Hypothesis -- 3.3 Description of Research Model -- 4 Data Analysis on Influencing Factors of Customer Loyalty -- 4.1 Reliability Test -- 4.2 Correlation Analysis -- 4.3 Regression Analysis -- 5 Summary -- References -- 13 A Detection Algorithm of Lung Nodule Based on Faster R-CNN -- Abstract -- 1 Introduction -- 2 Deep Learning Detection Framework and Faster R-CNN -- 2.1 Feature Extraction Network -- 2.2 RPN -- 2.3 ROI Pooling -- 2.4 Classifier -- 3 Pulmonary Nodule Detection Network -- 3.1 Improvement of Feature Extraction Network -- 3.2 Modify Anchors -- 4 Experimental Data and Result Verification -- 4.1 Dataset -- 4.2 Evaluation Criterion -- 4.3 Experimental Result -- 5 Conclusion -- References -- 14 Information Extraction from Contract Based on BERT-BiLSTM-CRF -- Abstract -- 1 Introduction -- 2 Related Research -- 3 Algorithm Model -- 3.1 Contract-Based Language Model (BERT) -- 3.2 BiLSTM-CRF Method Based on Migration Optimization -- 4 Test Results and Analysis -- 5 Concluding Remarks -- References -- 15 Research on Linear Detection Technology for Massive MIMO in Wireless Communications -- Abstract. , 1 Introduction -- 2 Model of Massive MIMO Uplink System -- 3 Linear Detection Algorithm for Massive MIMO System -- 3.1 Linear Detection Algorithm -- 3.1.1 Maximum Ratio Combining Algorithm (MRC) -- 3.1.2 Zero-Forcing Algorithm (ZF) -- 3.1.3 Minimum Mean Square Error Detection Algorithm (MMSE) -- 3.2 Simulation -- 4 Conclusion -- References -- 16 Research on Intelligent Reconfiguration and Recognition Technology of Mobile Environment for Substation Operation -- Abstract -- 1 Introduction -- 2 Object Scanning and Modeling -- 3 Modeling and Scanning Modeling of Dynamic Complex Environment -- 4 Weak Supervision Instance Segmentation of Substation Equipment Based on RGB-T Self Labeling -- 5 Model Compression and Acceleration for Edge Devices -- 6 Research and Development of Environment Intelligent Reconfiguration and Recognition Prototype System for Mobile Side Software and Hardware Platform -- 7 Conclusion -- References -- 17 Development and Application of Power Grid Disaster Intelligent Perception and Emergency Command System -- Abstract -- 1 Introduction -- 2 Electric Power Disaster Emergency Situation Map and 3D Visual Command Technology -- 3 Research and Development of Power Grid Disaster Intelligent Perception and Emergency Command Prototype System -- 4 Conclusions -- Acknowledgements -- References -- 18 Research on State Perception of Power Grid Equipment Based on Intelligent Analysis of Multi-Spectral Data -- Abstract -- 1 Introduction -- 2 Feature Distribution and Time-Domain Correlation of PoWer Equipment Status Under Different Spectrums -- 3 Online Monitoring and Fault Warning of Electrical Equipment Status of Stations and Transmission Lines -- 4 Establish a Sample Library of Power Equipment Faults Based on Three-Light Fusion Imaging -- 5 Comprehensive Evaluation Method of Multi-Spectral Data Analysis Model -- 6 Conclusions -- Acknowledgements. , References.

Note: Intro -- Preface -- Contents -- About the Editors -- Intelligent and Cloud Computing -- M-Throttled: Dynamic Load Balancing Algorithm for Cloud Computing -- 1 Introduction -- 2 Literature Survey -- 3 Existing Algorithms -- 3.1 Throttled Load Balancing -- 3.2 Round-Robin Load Balancing -- 3.3 SJF Load Balancing -- 4 Proposed Algorithm: M-throttled -- 5 Implementation -- 6 Conclusion -- References -- iGateLink: A Gateway Library for Linking IoT, Edge, Fog, and Cloud Computing Environments -- 1 Introduction -- 2 Related Work -- 3 System Model and Architecture -- 3.1 Implementation Details -- 4 Case Studies -- 5 Conclusions and Future Work -- References -- Hetero Leach: Leach Protocol with Heterogeneous Energy Constraint -- 1 Introduction -- 2 Routing Algorithm -- 2.1 LEACH -- 2.2 Hetero Leach -- 3 Simulation and Result -- 4 Conclusion -- References -- A Semantic Matchmaking Technique for Cloud Service Discovery and Selection Using Ontology Based on Service-Oriented Architecture -- 1 Introduction -- 2 Service-Oriented Computing -- 2.1 Service-Oriented Architecture -- 3 Proposed Model -- 3.1 Client Request -- 3.2 Cloud Service Discovery -- 3.3 Cloud Service Selection -- 3.4 Cloud Ontology Triple Store -- 4 Proposed Matchmaking Technique -- 5 Conclusion and Future Work -- References -- An Intelligent Approach to Detect Cracks on a Surface in an Image -- 1 Introduction -- 2 Literature Review -- 3 Min-Max Gray Level Discrimination Method -- 4 Proposed Model for Crack Detection -- 5 Conclusion -- References -- A Study of Machine Learning Techniques in Short Term Load Forecasting Using ANN -- 1 Introduction -- 2 ANN in STLF -- 2.1 Multilayer Perceptron Network (MLP) -- 2.2 Learning -- 2.3 Generalization -- 2.4 MLP Organizes in Burden Estimating -- 3 Proposed Work -- 3.1 Back Propagation (BP) by ANN -- 3.2 Fuzzy Logic by ANN. , 3.3 Hereditary Calculation (HC) by ANN -- 3.4 Particle Swarm Optimization (PSO) by ANN -- 4 Conclusion -- References -- A Review for the Development of ANN Based Solar Radiation Estimation Models -- 1 Introduction -- 2 Basics of Artificial Neural Network (ANN) -- 3 ANN for Solar Radiation Estimation -- 4 Review of Global Radiation Estimation Using ANN -- 5 Comparative Study of All the Models -- 6 Identified Research Gap in Solar Radiation Estimation -- 7 Conclusion -- References -- Analysis and Study of Solar Radiation Using Artificial Neural Networks -- 1 Introduction -- 2 ANN Fundamentals -- 2.1 What is ANN? -- 2.2 Nodal Configuration -- 2.3 ANN Types -- 2.4 Learning Stuff -- 3 ANN Working Principle and Architecture -- 3.1 Introduction -- 4 Applications, Advantages, and Disadvantages -- 4.1 Applications -- 4.2 Advantages -- 4.3 Disadvantages -- 5 Methodology -- 5.1 ANN for Predicting Solar Radiation -- 5.2 Data Considered -- 5.3 Operating Stages -- 5.4 Performance -- 6 Comparison Between ANN-Based and Existing Modeling -- 7 Conclusion -- References -- A Scheme to Enhance the Security and Efficiency of MQTT Protocol -- 1 Introduction -- 2 Literature Review -- 2.1 Security Requirements of IoT -- 2.2 Privacy Concerns in IoT -- 2.3 MQ Telemetry Transport (MQTT) -- 2.4 Architecture of MQTT -- 2.5 MQTT Quality of Service -- 2.6 Security Issues with MQTT -- 2.7 Hash Functions and Digital Signatures -- 2.8 Channel Encryption -- 2.9 Summary of Findings -- 2.10 Problem Statement -- 3 Proposed Scheme -- 3.1 Registration Process -- 4 Result and Discussions -- 5 Conclusions -- References -- Software Fault Prediction Using Random Forests -- 1 Introduction -- 1.1 Random Forests (RF) -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Datasets -- 3.2 Evaluation Criteria -- 4 Implementation and Results -- 5 Conclusion -- References. , A Power Optimization Technique for WSN with the Help of Hybrid Meta-heuristic Algorithm Targeting Fog Networks -- 1 Introduction -- 2 Related Works -- 3 Proposed Solution Methodology -- 3.1 Design Efficient WSN Nodes -- 3.2 Clusterization of the Target Area -- 3.3 Deployment of WSN Nodes Using Spiral Pattern WSN Node Deployment Policy -- 4 Numerical Result Analysis -- 5 Conclusion and Future Work -- References -- A Model for Probabilistic Prediction of Paddy Crop Disease Using Convolutional Neural Network -- 1 Introduction -- 2 Literature Survey -- 3 Paddy Crop Disease Classification -- 3.1 Brown Spot -- 3.2 Bacterial Leaf Blight -- 3.3 Leaf Smut -- 4 Implementation of the Model -- 4.1 Image Generation and Augmentation -- 4.2 Convolution Steps -- 4.3 Pooling Step -- 4.4 Fully Connected Layers -- 4.5 Disease Prediction -- 4.6 Process Flow Model -- 5 Algorithm of the Model -- 6 Experimental Results -- 7 Conclusions and Future Work -- References -- A Hybridized ELM-Elitism-Based Self-Adaptive Multi-Population Jaya Model for Currency Forecasting -- 1 Introduction -- 2 Methodology Adopted -- 2.1 ELM -- 2.2 Jaya -- 3 Dataset Description -- 4 Experimental Analysis -- 4.1 Abstract View of the Proposed Model -- 4.2 Proposed ELM-ESAMPJ Algorithm for Exchange Rate Analysis -- 4.3 Result Analysis -- 5 Discussions -- 6 Conclusion and Future Work -- References -- A Fruit Fly Optimization-Based Extreme Learning Machine for Biomedical Data Classification -- 1 Introduction -- 2 Machine Learning Techniques for Biomedical Data Classification -- 2.1 Extreme Learning Machine (ELM) -- 2.2 Fruit Fly Optimization (FFO) -- 2.3 The Proposed FFO-ELM Models -- 3 Result and Discussion -- 3.1 Data Description -- 3.2 Performance Evaluation -- 3.3 Result Analysis -- 4 Conclusion -- References -- Partial Reconfiguration Feature in Crypto Algorithm for Cloud Application. , 1 Introduction -- 2 Generations of Crypto Core -- 3 State of the Art -- 4 Architecture and Implementation -- 4.1 Low Processing Platform (LP) -- 4.2 Fog -- 4.3 Cloud -- 5 Conclusion -- References -- Proactive Content Caching for Streaming over Information-Centric Network -- 1 Introduction -- 2 System Model -- 3 Proposed Solution -- 3.1 Content Store (CS) -- 3.2 Ant Colony Process -- 4 Experimental Results -- 5 Conclusion -- References -- Performance Analysis of ERWCA-Based FLANN Model for Exchange Rate Forecasting -- 1 Introduction -- 2 Methodology -- 2.1 FLANN Model -- 2.2 Evaporation Rate-Based Water Cycle Algorithm (ERWCA) -- 2.3 FLANN/ERWCA Model -- 3 Simulation Study -- 4 Conclusion -- References -- Multi-document Summarization Using Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 4 Experiment and Results Analysis -- 5 Conclusion -- References -- A Convolutional Neural Network Framework for Brain Tumor Classification -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 3.1 Input Image -- 3.2 Convolution Layer -- 3.3 Pooling Layer -- 3.4 Fully Connected Layer -- 3.5 Output Layer -- 4 Experimental Setup and Results -- 4.1 Dataset Description -- 4.2 Initial Kernel Weights -- 4.3 Activation Function -- 4.4 Loss Function Computation -- 4.5 Training -- 4.6 Model Parameters -- 4.7 Simulation Results -- 5 Conclusion -- References -- Load Balancing in Cloud Computing Environment Using CloudSim -- 1 Introduction -- 2 Related Work -- 3 Objective of Load Balancing in Cloud Computing -- 4 Necessity of Load Balancing -- 5 Verification of Load Balancing Using Cloud Simulator -- 5.1 Various Features of CloudSim Tool -- 5.2 Primary Elements of CloudSim Tool -- 5.3 Algorithm Utilized in CloudSim Tool for Load Balancing -- 6 Experimental Results -- 7 Conclusion -- References. , Assessment of Load in Cloud Computing Environment Using C-means Clustering Algorithm -- 1 Introduction -- 2 Literature Review -- 3 Proposed Approach -- 3.1 Resource Allocation -- 3.2 Algorithm -- 4 Result Analysis -- 5 Conclusion -- References -- Parallel Implementation of Algebraic Curve for Data Security in Cloud Computing Environment -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 3.1 Explicit Addition Formulation -- 4 Implementation -- 4.1 Sequential Implementation Methodology -- 4.2 Parallel Implementation Methodology -- 5 Experimental Results and Analysis -- 5.1 Sequential Implementation of Elliptic Curve Addition -- 5.2 Sequential Implementation of Hyperelliptic Curve Addition -- 5.3 Parallel Implementation of Hyperelliptic Curve Addition -- 6 Performance Comparison of Sequential and Parallel Implementation -- 7 Conclusion -- References -- A Design Towards an Energy-Efficient and Lightweight Data Security Model in Fog Networks -- 1 Introduction -- 2 Related Works -- 3 Background -- 4 Proposed Approach and Related Discussions -- 4.1 Lightweight Authentication Using CA Based Scheme -- 4.2 Lightweight Cryptography Using CA Based Scheme -- 5 Conclusions and Future Work -- References -- Fuzzification-Based Routing Protocol for Wireless Ad Hoc Network -- 1 Introduction -- 2 Related Works -- 3 Proposed Work -- 4 Simulation Analysis -- 5 Conclusion and Future Work -- References -- Fuzzy-Based Strategy Management in Wireless Ad Hoc Network -- 1 Introduction -- 2 Related Works -- 3 Proposed Work -- 4 Simulation Analysis -- 5 Conclusion and Future Work -- References -- A TWV Classifier Ensemble Framework -- 1 Introduction -- 2 Proposed TWV Classifier Ensemble -- 3 Experimental Setup and Result Analysis -- 4 Conclusion -- References -- Recent Advancements in Continuous Authentication Techniques for Mobile-Touchscreen-Based Devices. , 1 Introduction to Continuous Authentication (CA).

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 -- 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 -- AIVR 2022 Organization -- Preface -- Contents -- About the Editors -- Part I Invited Paper -- 1 Paraconsistency and Paracompleteness in AI: Review Paper -- 1.1 Introduction -- 1.1.1 Classical and Non-classical Logic -- 1.2 Paraconsistent and Paracomplete Logic -- 1.3 AI and Formal Systems -- 1.4 Paraconsistent Annotated Evidential Logic Eτ -- 1.5 Application in Robotics -- 1.5.1 Description of the Prototype -- 1.5.2 Development of the Paraconsistent Annotated Logic Algorithm -- 1.6 Multi-criteria Decision Analysis (MCDA) in Health Care -- 1.7 Conclusions -- References -- Part II Regular Papers -- 2 Decision Support Multi-agent Modeling and Simulation of Aeronautic Marine Oil Spill Response -- 2.1 Introduction -- 2.2 Modeling and Simulation -- 2.2.1 Marine Oil Spill Response Process -- 2.2.2 DEVS and Multi-agent Modeling -- 2.3 Response Plan Evaluation -- 2.3.1 Response Plan Agent -- 2.3.2 Evaluation Indicators System -- 2.4 Instance Analysis -- 2.4.1 Simulation Scenario -- 2.4.2 Simulation-Based Evaluation for Decision Support -- 2.5 Conclusion -- References -- 3 Transferring Dense Object Detection Models To Event-Based Data -- 3.1 Introduction -- 3.1.1 Contributions and Outline -- 3.2 Dataset and Frame Representation -- 3.2.1 KITTI Vision Dataset -- 3.2.2 Optical Event Data and Histograms -- 3.3 Implementation -- 3.3.1 Sparseconvnet Extensions -- 3.3.2 Asynet Extensions -- 3.3.3 Dataloader -- 3.4 Error Analysis -- 3.4.1 Sparse YOLO Versus Dense YOLO -- 3.4.2 Sparse Versus Dense Convolutions -- 3.4.3 Event-Window Size -- 3.5 Runtime Analysis -- 3.5.1 Dense Versus Sparse -- 3.5.2 Batch Size -- 3.5.3 Synchronous Versus Asynchronous -- 3.5.4 Asynchronous Sequence Count -- 3.5.5 Theoretical Runtime -- 3.6 Conclusion -- References. , 4 Diagnosing Parkinson's Disease Based on Voice Recordings: Comparative Study Using Machine Learning Techniques -- 4.1 Introduction -- 4.2 Related Research Work -- 4.2.1 Logistic Regression -- 4.2.2 Random Forest -- 4.2.3 SVM -- 4.2.4 KNN -- 4.2.5 Gradient-boosted Decision Trees -- 4.3 Dataset -- 4.4 Methodology -- 4.5 Results -- 4.6 Conclusion -- References -- 5 Elements of Continuous Reassessment and Uncertainty Self-awareness: A Narrow Implementation for Face and Facial Expression Recognition -- 5.1 Introduction -- 5.2 Proposed Solution -- 5.3 Data Set -- 5.4 Experiments -- 5.4.1 Trusted Accuracy Metrics -- 5.5 Results -- 5.6 Discussion, Conclusions, and Future Work -- References -- 6 Topic-Aware Networks for Answer Selection -- 6.1 Introduction -- 6.2 Related Works -- 6.2.1 Topic Embedding Generation -- 6.2.2 Answer Selection -- 6.3 Methodology -- 6.3.1 Topic Embedding -- 6.3.2 Topic-Aware Networks -- 6.3.3 Triplet Loss -- 6.4 Experiments -- 6.4.1 Dataset -- 6.4.2 Experiment Settings -- 6.4.3 Results and Discussion -- 6.5 Conclusion and Future Work -- References -- 7 Design and Implementation of Multi-scene Immersive Ancient Style Interaction System Based on Unreal Engine Platform -- 7.1 Introduction -- 7.2 Technical Basis -- 7.2.1 Lighting Model -- 7.2.2 From Physical Phenomena to BRDF -- 7.2.3 Physical-based Environment Lighting -- 7.3 Conceive Preparation -- 7.3.1 Research on the Current Situation of UE4 Used for Developing This Work -- 7.3.2 Storyboard -- 7.3.3 Design Process -- 7.4 The Main Scene Building Part -- 7.4.1 The Idea of Building a Scene of the Tang Dynasty -- 7.4.2 Collider -- 7.4.3 Light Effect of Dusk -- 7.4.4 Particle Effects -- 7.5 Functional Design -- 7.5.1 Sequence Animation in Scene -- 7.5.2 Release Kongming Lanterns -- 7.5.3 Large Amounts of Kongming Lanterns Take off -- 7.6 Artwork Display and Rendering Resource Analysis. , 7.6.1 Project Framework Diagram and Interactive Display Screenshots -- 7.6.2 Project Performance Analysis -- 7.6.3 Project Innovation -- 7.7 Conclusion -- 8 Auxiliary Figure Presentation Associated with Sweating on a Viewer's Hand in Order to Reduce VR Sickness -- 8.1 Introduction -- 8.2 Related Work -- 8.3 Experiment to Select Physiological Signal that Correlates with VR Sickness -- 8.3.1 Physiological Signals -- 8.3.2 Experiment Environment and Task -- 8.3.3 Result -- 8.3.4 Analyses and Discussions -- 8.4 Design of Auxiliary Figure Control System -- 8.5 Evaluation Experiment -- 8.5.1 Procedure and Task -- 8.5.2 Results -- 8.5.3 Discussions -- 8.6 Conclusions -- References -- 9 Design and Implementation of Immersive Display Interactive System Based on New Virtual Reality Development Platform -- 9.1 Introduction -- 9.2 System Methodology -- 9.2.1 Demand Analysis -- 9.2.2 Analysis of Our Developing Platform -- 9.2.3 Development Processing -- 9.3 Analysis of Key Technologies -- 9.3.1 Model Construction and Import -- 9.3.2 Real Shading in Unreal Engine 4 -- 9.3.3 Making Interactive Experiences -- 9.4 Conclusion -- References -- 10 360-Degree Virtual Reality Videos in EFL Teaching: Student Experiences -- 10.1 Introduction -- 10.2 Literature Review -- 10.2.1 Different VR Types -- 10.2.2 VR in Higher Education -- 10.2.3 VR Embedded Language Learning -- 10.3 Research Methods -- 10.3.1 Participants -- 10.3.2 Instruments -- 10.3.3 Procedures -- 10.3.4 Data Analysis -- 10.4 Results -- 10.4.1 Results of Two Interview Questions -- 10.5 Discussion -- 10.6 Conclusions -- References -- 11 Medical-Network (Med-Net): A Neural Network for Breast Cancer Segmentation in Ultrasound Image -- 11.1 Introduction -- 11.2 Related Work -- 11.3 Proposed Breast Ultrasound Segmentation Model (Med-Net) -- 11.3.1 Encoder Architecture -- 11.3.2 Attention Module. , 11.3.3 Decoder Architecture -- 11.3.4 Implementation Details -- 11.3.5 Dataset -- 11.4 Discussion -- 11.5 Conclusion -- References -- 12 Auxiliary Squat Training Method Based on Object Tracking -- 12.1 Introduction -- 12.2 Material and Methods -- 12.2.1 The Basic Force Arm of Deep Squat -- 12.2.2 Object Tracking -- 12.2.3 Action Analysis -- 12.3 Results -- 12.3.1 Sagittal Plane Motion Analysis -- 12.3.2 Coronal Plane Motion Analysis -- 12.4 Discussion -- 12.5 Conclusion -- References -- 13 Study on the Visualization Modeling of Aviation Emergency Rescue System Based on Systems Engineering -- 13.1 Introduction -- 13.2 Aviation Emergency Rescue System Architecture Analysis -- 13.2.1 Disaster Prevention and Early Warning Stage -- 13.2.2 Disaster Preparation Stage -- 13.2.3 Emergency Response Stage -- 13.2.4 Recovery and Reconstruction Stage -- 13.3 Aviation Emergency Rescue System Visualization Model -- 13.3.1 Operational Viewpoint DoDAF-Described Models -- 13.3.2 Capability Viewpoint DoDAF-Described Models -- 13.4 Conclusion -- References -- 14 An AI-Based System Offering Automatic DR-Enhanced AR for Indoor Scenes -- 14.1 Introduction -- 14.2 System Overview -- 14.2.1 Object Segmentation Component -- 14.2.2 Layout Estimation Component -- 14.2.3 Inpainting Component -- 14.2.4 Super-Resolution Component -- 14.2.5 Implementation and Orchestration -- 14.3 Experimental Setup Methodology -- 14.3.1 Component Ablation -- 14.3.2 User Study -- 14.4 Results and Discussion -- 14.4.1 Objective Evaluation -- 14.4.2 Subjective Evaluation -- 14.5 Conclusion -- References -- 15 Extending Mirror Therapy into Mixed Reality-Design and Implementation of the Application PhantomAR to Alleviate Phantom Limb Pain in Upper Limb Amputees -- 15.1 Introduction -- 15.2 Methods and Materials -- 15.2.1 Study Setup and Protocol -- 15.3 Gameplay and Technical Implementation. , 15.3.1 Game Design and Interaction Scenes -- 15.3.2 Spatial Mapping -- 15.3.3 Virtual Arm and Non-Anthropomorphic Feedback -- 15.3.4 Virtual Arm Movement -- 15.3.5 Virtual Hand Movement -- 15.3.6 Calibration -- 15.3.7 Interaction with Virtual Environment -- 15.3.8 Remote Connection for Therapeutic Intervention -- 15.4 Results -- 15.5 Discussion -- 15.6 Conclusion -- References -- 16 An Analysis of Trends and Problems of Information Technology Application Research in China's Accounting Field Based on CiteSpace -- 16.1 Questions Posed -- 16.2 Text Mining and Visual Analysis of Research Trends in Information Technology in the Field of Accounting in China -- 16.2.1 Research Tools -- 16.2.2 Source of Data -- 16.2.3 Text Mining and Visual Analysis of Related Research Based on Classification -- 16.3 A Review of Major Issues Discovered by Research and Analysis Regarding the Application of Information Technology in Accounting -- 16.3.1 Few Studies Have Been Conducted on the Application of Information Technology to Accounting in SMEs -- 16.3.2 The Number and Quality of Information-Based Accounting Education Research is Low and Declining -- 16.4 Conclusions and Recommendations of the Research on the Application of Information Technology in Accounting -- 16.4.1 Conclusions of the Research -- 16.4.2 Research Recommendations for Advancing the Application of Information Technology in Accounting -- References -- 17 Augmented Reality Framework and Application for Aviation Emergency Rescue Based on Multi-Agent and Service -- 17.1 Introduction -- 17.2 Framework of Augmented Reality System -- 17.2.1 System Framework -- 17.2.2 Service-Oriented Architecture -- 17.2.3 Multi-Agent Architecture -- 17.3 Construction of Aviation Emergency Rescue Augmented System -- 17.3.1 Construction of System -- 17.3.2 Services Development -- 17.3.3 Entity Development. , 17.4 Simulation of Aviation Emergency Rescue.

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.