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Artificial intelligence and machine learning methods in COVID-19 and related health diseases / / edited by Victor Chang, Harleen Kaur, Simon James Fong
| Artificial intelligence and machine learning methods in COVID-19 and related health diseases / / edited by Victor Chang, Harleen Kaur, Simon James Fong |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (254 pages) |
| Disciplina | 060 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico | Artificial intelligence - Medical applications |
| ISBN | 3-031-04597-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910735390603321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Catalyzing Development through ICT Adoption : The Developing World Experience / / edited by Harleen Kaur, Ewa Lechman, Adam Marszk
| Catalyzing Development through ICT Adoption : The Developing World Experience / / edited by Harleen Kaur, Ewa Lechman, Adam Marszk |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XII, 288 p. 32 illus., 20 illus. in color.) |
| Disciplina | 658.4038 |
| Soggetto topico |
Management information systems
Computers Development economics Business Information Systems Information Systems and Communication Service Development Economics |
| ISBN | 3-319-56523-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I – General and Multi-regional Studies -- 1 Information and Communication Technologies for Economic Development. Identifying the channels of impact -- 2 The impact of ICTs on women’s economic empowerment -- 3 Big Data Analytics for ICT Monitoring and Development -- 4 The role of ICT adoption in curbing corruption in developing countries -- 5 Internet, educational disparities and economic growth: differences between low-middle and high-income countries -- Part II – Asia -- 6 Strengthening the Public Sector Accounting through ICT The Experience of a Developing Country -- 7 Potentials and Challenges of using ICT for Climate Change Adaptation: A Study of Vulnerable Community in Riverine Islands of Bangladesh -- Part III – Africa and Middle East -- 8 Evaluation of E-Infrastructure Deployment in OECD and MENA Countries -- 9 Model for Constructing Institutional Framework for Scientific Knowledge Management Systems: Nigerian Institutional Repository Innovation Case Applicable to Developing Countries -- 10 Linkages between Formal Institutions, ICT Adoption, and Inclusive Human Development in Sub Saharan Africa -- Part IV – Latin America -- 11 Inequalities in the appropriation of digital spaces in metropolitan areas of Latin America -- 12 Internet Use and Public Programs Participation: Evidence from Chile -- 13 E-commerce and Productivity: Evidence from Chile -- Part V – Europe -- 14 Assessing the Economic Potential of Big Data Industries -- 15 Is ICT the Solution of the Problem for Estonia?. |
| Record Nr. | UNINA-9910254909303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Condition-Based Maintenance and Residual Life Prediction
| Condition-Based Maintenance and Residual Life Prediction |
| Autore | Singh Chandan Deep |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2025 |
| Descrizione fisica | 1 online resource (296 pages) |
| Altri autori (Persone) |
SinghDavinder
SinghKanwal Jit KaurHarleen |
| ISBN |
9781119933151
1119933153 9781119933168 1119933161 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910985988203321 |
Singh Chandan Deep
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| Newark : , : John Wiley & Sons, Incorporated, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Factories of the future : technological advancements in the manufacturing industry / / edited by Chandan Deep Singh and Harleen Kaur
| Factories of the future : technological advancements in the manufacturing industry / / edited by Chandan Deep Singh and Harleen Kaur |
| Pubbl/distr/stampa | Hoboken, NJ : , : John Wiley & Sons, Inc. and Scrivener Publishing LLC, , [2023] |
| Descrizione fisica | 1 online resource (305 pages) |
| Disciplina | 670 |
| Soggetto topico |
Manufacturing industries - Technological innovations
Manufacturing industries - Management |
| ISBN |
1-119-86521-2
1-119-86520-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Factories of the Future -- 1.0 Introduction -- 1.1 Factory of the Future -- 1.1.1 Plant Structure -- 1.1.2 Plant Digitization -- 1.1.3 Plant Processes -- 1.1.4 Industry of the Future: A Fully Integrated Industry -- 1.2 Current Manufacturing Environment -- 1.3 Driving Technologies and Market Readiness -- 1.4 Connected Factory, Smart Factory, and Smart Manufacturing -- 1.4.1 Potential Benefits of a Connected Factory -- 1.5 Digital and Virtual Factory -- 1.5.1 Digital Factory -- 1.5.2 Virtual Factory -- 1.6 Advanced Manufacturing Technologies -- 1.6.1 Advantages of Advanced Manufacturing Technologies -- 1.7 Role of Factories of the Future (FoF) in Manufacturing Performance -- 1.8 Socio-Econo-Techno Justification of Factories of the Future -- References -- Chapter 2 Industry 5.0 -- 2.1 Introduction -- 2.1.1 Industry 5.0 for Manufacturing -- 2.1.1.1 Industrial Revolutions -- 2.1.2 Real Personalization in Industry 5.0 -- 2.1.3 Industry 5.0 for Human Workers -- 2.2 Individualized Human-Machine-Interaction -- 2.3 Industry 5.0 is Designed to Empower Humans, Not to Replace Them -- 2.4 Concerns in Industry 5.0 -- 2.5 Humans Closer to the Design Process of Manufacturing -- 2.5.1 Enablers of Industry 5.0 -- 2.6 Challenges and Enablers (Socio-Econo-Techno Justification) -- 2.6.1 Social Dimension -- 2.6.2 Governmental and Political Dimension -- 2.6.3 Interdisciplinarity -- 2.6.4 Economic Dimension -- 2.6.5 Scalability -- 2.7 Concluding Remarks -- References -- Chapter 3 Machine Learning - A Survey -- 3.1 Introduction -- 3.2 Machine Learning -- 3.2.1 Unsupervised Machine Learning -- 3.2.2 Variety of Unsupervised Learning -- 3.2.3 Supervised Machine Learning -- 3.2.4 Categories of Supervised Learning -- 3.3 Reinforcement Machine Learning -- 3.3.1 Applications of Reinforcement Learning.
3.3.2 Dimensionality Reduction -- 3.4 Importance of Dimensionality Reduction in Machine Learning -- 3.4.1 Methods of Dimensionality Reduction -- 3.4.1.1 Principal Component Analysis (PCA) -- 3.4.1.2 Linear Discriminant Analysis (LDA) -- 3.4.1.3 Generalized Discriminant Analysis (GDA) -- 3.5 Distance Measures -- 3.6 Clustering -- 3.6.1 Algorithms in Clustering -- 3.6.2 Applications of Clustering -- 3.6.3 Iterative Distance-Based Clustering -- 3.7 Hierarchical Model -- 3.8 Density-Based Clustering -- 3.8.1 DBSCAN -- 3.8.2 OPTICS -- 3.9 Role of Machine Learning in Factories of the Future -- 3.10 Identification of the Probable Customers -- 3.11 Conclusion -- References -- Chapter 4 Understanding Neural Networks -- 4.1 Introduction -- 4.2 Components of Neural Networks -- 4.2.1 Neurons -- 4.2.2 Synapses and Weights -- 4.2.3 Bias -- 4.2.4 Architecture of Neural Networks -- 4.2.5 How Do Neural Networks Work? -- 4.2.6 Types of Neural Networks -- 4.2.6.1 Artificial Neural Network (ANN) -- 4.2.6.2 Recurrent Neural Network (RNN) -- 4.2.6.3 Convolutional Neural Network (CNN) -- 4.2.7 Learning Techniques in Neural Network -- 4.2.8 Applications of Neural Network -- 4.2.9 Advantages of Neural Networks -- 4.2.10 Disadvantages of Neural Network -- 4.2.11 Limitations of Neural Networks -- 4.3 Back-Propagation -- 4.3.1 Working of Back-Propagation -- 4.3.2 Types of Back-Propagation -- 4.3.2.1 Static Back-Propagation -- 4.3.2.2 Recurrent Back-Propagation -- 4.3.2.3 Advantages of Back-Propagation -- 4.3.2.4 Disadvantages of Back-Propagation -- 4.4 Activation Function (AF) -- 4.4.1 Sigmoid Active Function -- 4.4.1.1 Advantages -- 4.4.1.2 Disadvantages -- 4.4.2 RELU Activation Function -- 4.4.2.1 Advantages -- 4.4.2.2 Disadvantages -- 4.4.3 TANH Active Function -- 4.4.3.1 Advantages -- 4.4.3.2 Disadvantages -- 4.4.4 Linear Function -- 4.4.5 Advantages -- 4.4.6 Disadvantages. 4.4.7 Softmax Function -- 4.4.8 Advantages -- 4.5 Comparison of Activation Functions -- 4.6 Machine Learning -- 4.6.1 Applications of Machine Learning -- 4.7 Conclusion -- References -- Chapter 5 Intelligent Machining -- 5.1 Introduction -- 5.2 Requirements for the Developments of Intelligent Machining -- 5.3 Components of Intelligent Machining -- 5.3.1 Intelligent Sensors -- 5.3.1.1 Features of Intelligent Sensors -- 5.3.1.2 Functions of Intelligent Sensors -- 5.3.1.3 Data Acquisition and Management System to Process and Store Signals -- 5.3.2 Machine Learning and Knowledge Discovery Component -- 5.3.3 Database Knowledge Discovery -- 5.3.4 Programmable Logical Controller (PLC) -- 5.3.5 Role of Intelligent Machining for Implementation of Green Manufacturing -- 5.3.6 Information Integration via Knowledge Graphs -- 5.4 Conclusion -- References -- Chapter 6 Advanced Maintenance and Reliability -- 6.1 Introduction -- 6.2 Condition-Based Maintenance -- 6.3 Computerized Maintenance Management Systems (CMMS) -- 6.4 Preventive Maintenance (PM) -- 6.5 Predictive Maintenance (PdM) -- 6.6 Reliability Centered Maintenance (RCM) -- 6.6.1 RCM Principles -- 6.7 Condition Monitoring and Residual Life Prediction -- 6.8 Sustainability -- 6.8.1 Role of Sustainability in Manufacturing -- 6.9 Concluding Remarks -- References -- Chapter 7 Digital Manufacturing -- 7.1 Introduction -- 7.2 Product Life Cycle and Transition -- 7.3 Digital Thread -- 7.4 Digital Manufacturing Security -- 7.5 Role of Digital Manufacturing in Future Factories -- 7.6 Digital Manufacturing and CNC Machining -- 7.6.1 Introduction to CNC Machining -- 7.6.2 Equipment's Used in CNC Machining -- 7.6.3 Analyzing Digital Manufacturing Design Considerations -- 7.6.4 Finishing of Part After Machining -- 7.7 Additive Manufacturing -- 7.7.1 Objective of Additive Manufacturing -- 7.7.2 Design Consideration. 7.8 Role of Digital Manufacturing for Implementation of Green Manufacturing in Future Industries -- 7.9 Conclusion -- References -- Chapter 8 Artificial Intelligence in Machine Learning -- 8.1 Introduction -- 8.2 Case Studies -- 8.3 Advantages of A.I. in ML -- 8.4 Artificial Intelligence - Basics -- 8.4.1 History of A.I. -- 8.4.2 Limitations of Human Mind -- 8.4.3 Real Artificial Intelligence -- 8.4.4 Artificial Intelligence Subfields -- 8.4.5 The Positives of A.I. -- 8.4.6 Machine Learning -- 8.4.7 Machine Learning Models -- 8.4.8 Neural Networks -- 8.4.9 Constraints of Machine Learning -- 8.4.10 Different Kinds of Machine Learning -- 8.5 Application of Artificial Intelligence -- 8.5.1 Expert Systems -- 8.5.2 Natural Language Processing -- 8.5.3 Speech Recognition -- 8.5.4 Computer Vision -- 8.5.5 Robotics -- 8.6 Neural Networks (N.N.) Basics -- 8.6.1 Application of Neural Networks -- 8.6.2 Architecture of Neural Networks -- 8.6.3 Working of Artificial Neural Networks -- 8.7 Convolution Neural Networks -- 8.7.1 Working of Convolutional Neural Networks -- 8.7.2 Overview of CNN -- 8.7.3 Working of CNN -- 8.8 Image Classification -- 8.8.1 Concept of Image Classification -- 8.8.2 Type of Learning -- 8.8.3 Features of Image Classification -- 8.8.4 Examples of Image Classification -- 8.9 Text Classification -- 8.9.1 Text Classification Examples -- 8.9.2 Phases of Text Classification -- 8.9.3 Text Classification API -- 8.10 Recurrent Neural Network -- 8.10.1 Type of Recurrent Neural Network -- 8.11 Building Recurrent Neural Network -- 8.12 Long Short Term Memory Networks (LSTMs) -- References -- Chapter 9 Internet of Things -- 9.1 Introduction -- 9.2 M2M and Web of Things -- 9.3 Wireless Networks -- 9.4 Service Oriented Architecture -- 9.5 Complexity of Networks -- 9.6 Wireless Sensor Networks -- 9.7 Cloud Computing -- 9.8 Cloud Simulators. 9.9 Fog Computing -- 9.10 Applications of IoT -- 9.11 Research Gaps and Challenges in IoT -- 9.12 Concluding Remarks -- References -- Chapter 10 Product Life Cycle -- 10.1 Introduction -- 10.2 Product Lifecycle Management (PLM) -- 10.2.1 Why Product Lifecycle Management? -- 10.2.2 Biological Product Lifecycle Stages -- 10.2.3 An Example Related to Stages in Product Lifecycle Management -- 10.2.4 Advanced Stages in Product Lifecycle Management -- 10.2.5 Strategies of Product Lifecycle Management -- 10.3 High and Low-Level Skimming Strategies/Rapid or Slow Skimming Strategies -- 10.3.1 Considerations in High and Low-Level Pricing -- 10.3.2 Penetration Pricing Strategy -- 10.3.3 Example for Penetration Pricing Strategy -- 10.3.4 Considerations in Penetration Pricing -- 10.4 How Do Product Lifecycle Management Work? -- 10.5 Application Process of Product Lifecycle Management (PLM) -- 10.6 Role of Unified Modelling Language (UML) -- 10.6.1 UML Activity Diagrams -- 10.7 Management of Product Information Throughout the Entire Product Lifecycle -- 10.8 PDM System in an Organization -- 10.8.1 Benefits of PDM -- 10.8.2 How Does the PDM Work? -- 10.8.3 The Services of Product Data Management -- 10.9 System Architecture -- 10.9.1 Process of System Architecture -- 10.10 Concepts of Model-Based System Engineering (MBSE) -- 10.10.1 Benefits of Model-Based System Engineering (MBSE) -- 10.11 Challenges of Post-COVID 19 in Manufacturing Sector -- 10.12 Recent Updates in Product Life Cycle -- 10.13 Conclusion -- References -- Chapter 11 Case Studies -- 11.1 Case Study in a Two-Wheeler Manufacturing Industry -- 11.1.1 Company Strategy -- 11.1.2 Initiatives Towards Technological Advancement -- 11.1.3 Management Initiatives -- 11.1.4 Sustainable Development Goals -- 11.1.5 Growth Framework with Customer Needs -- 11.1.6 Vision for the Future. 11.2 Case Study in a Four-Wheeler Manufacturing Unit. |
| Record Nr. | UNINA-9910830556703321 |
| Hoboken, NJ : , : John Wiley & Sons, Inc. and Scrivener Publishing LLC, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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ICTs and the Millennium Development Goals : A United Nations Perspective / / edited by Harleen Kaur, Xiaohui Tao
| ICTs and the Millennium Development Goals : A United Nations Perspective / / edited by Harleen Kaur, Xiaohui Tao |
| Edizione | [1st ed. 2014.] |
| Pubbl/distr/stampa | New York, NY : , : Springer US : , : Imprint : Springer, , 2014 |
| Descrizione fisica | 1 online resource (273 p.) |
| Disciplina |
004
005.7 303.4834 502.85 |
| Soggetto topico |
Computers
Information technology Business—Data processing Medical informatics Information Systems and Communication Service IT in Business Health Informatics |
| ISBN | 1-4899-7439-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Learning, Communication and Interaction via Wiki: An Australian Perspective -- ICTs Diffusion Trajectories and Economic Development -- An Empirical Analysis of Gendered Differences in MDG Awareness Across Sources of Information -- Global Evidence of Age-Structured Differences in MDG Awareness Among Users of Personal Computers -- Finding Weighted Positive Influence Dominating Set to Make Impact to Negatives -- A Conceptual Interdisciplinary Plug-and-Play Cyber Security Framework -- Mobile Phone and Development: Synthesis on New Misuse Perspective -- Incorporating ICTs in Schools for Effective Education -- Implementing ICT in Schools in a Developing Country -- Information and Communication Technology (ICT) Applications for Customer Relationship Management (CRM) -- Information Retrieval Using Rough Set Approximations -- The Role of ICTs in Poverty Eradication -- ICT-Based Trade Facilitation and the MDGs -- A Case Study: From Game-Programming to ICTs -- Challenges for Mobile Governance in India. |
| Record Nr. | UNINA-9910299045503321 |
| New York, NY : , : Springer US : , : Imprint : Springer, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Metaverse Technologies, Security, and Applications for Healthcare
| Metaverse Technologies, Security, and Applications for Healthcare |
| Autore | Vyas Ajay Kumar |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2025 |
| Descrizione fisica | 1 online resource (411 pages) |
| Disciplina | 610.285 |
| Altri autori (Persone) |
KaurHarleen
SharmaSourabh AlankarBhavya |
| Soggetto topico |
Virtual reality in medicine
Metaverse |
| ISBN |
1-394-30527-3
1-394-30529-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgments -- Part I: Metaverse Technology -- Chapter 1 Introduction to Metaverse for Healthcare -- 1.1 Introduction of Metaverse -- 1.2 Metaverse in Healthcare -- 1.3 Potential Uses of Metaverse in Healthcare -- 1.3.1 Telemedicine and Virtual Consultations -- 1.3.2 Medical Education and Training -- 1.3.3 Patient Education and Engagement -- 1.3.4 Mental Health -- 1.3.5 Rehabilitation -- 1.4 Technological Infrastructure -- 1.4.1 Technologies -- 1.4.2 Wearable and Hardware -- 1.5 Benefits and Opportunities -- 1.5.1 Improved Accessibility -- 1.5.2 Enhanced Patient Experience -- 1.5.3 Cost Reduction -- 1.6 Challenges and Risks -- 1.6.1 Hardware -- 1.6.2 Ethical Concerns -- 1.6.3 Privacy and Data Security -- 1.6.4 Identity Hacking -- 1.6.5 Addiction and Mental Health -- 1.6.6 Regulatory and Legal Issues -- 1.6.7 Currency and Digital Payment -- 1.6.8 Technical Challenges -- 1.7 Metaverse's Prospects for the Future in Healthcare -- 1.7.1 Predictions for the Future -- 1.7.2 Potential Technological Advancements -- 1.7.3 Long-Term Implications -- 1.8 Conclusion -- References -- Chapter 2 Metaverse and Virtual Healthcare: Opportunities and Challenges -- 2.1 Introduction -- 2.2 Metaverse Enabling Technologies -- 2.2.1 Extended Reality -- 2.2.2 Blockchain -- 2.2.3 Internet of Things -- 2.2.4 Spatial and Edge Computing -- 2.2.5 3D Modeling and Reconstruction -- 2.2.6 Brain-Computer Interface -- 2.2.7 Artificial Intelligence -- 2.2.8 Advanced Wi-Fi Technology -- 2.3 Application in Healthcare -- 2.3.1 Metaverse in Surgeries -- 2.3.2 Education and Training -- 2.3.3 Medical Diagnosis and Consultation -- 2.3.4 Metaverse in Pain Management -- 2.3.5 Medical Health Data Management -- 2.4 Limitations and Challenges -- 2.4.1 Privacy and Security -- 2.4.2 Health Concerns.
2.4.3 Dependence on the Internet -- 2.4.4 Interoperability -- 2.4.5 High Cost of Technology -- 2.4.6 Environmental Impact -- 2.5 Conclusion -- References -- Chapter 3 Innovation and Accountability: An Ethical Perspective on Metaverse Healthcare -- 3.1 Introduction -- 3.2 Methodology -- 3.2.1 Medical Training Metaverse -- 3.2.1.1 OSSO VR -- 3.2.1.2 MediVizor -- 3.2.2 Virtual Clinical Trials -- 3.3 Discussion -- Conclusion and Future Scope -- References -- Chapter 4 The Healthcare Metaverse: Utilizations, Obstacles, and Prospects -- Introduction -- Metaverse -- Metaverse Components -- AR/VR Technologies -- Digital Avatars -- 3D Virtual Environments -- Blockchain and Cryptocurrencies -- Issues Faced by Healthcare Industries -- Applications of Metaverse in Healthcare Industry -- Limitation of AR/VR in Healthcare -- Challenges of Metaverse in Healthcare -- Future Directions -- Conclusion -- References -- Chapter 5 Creating The Healthcare of Tomorrow: The Metaverse's Opportunities and Challenges -- 5.1 Introduction -- 5.2 Analysis: Metaverse and Healthcare -- 5.3 Discussion and Synthesis -- 5.4 Conclusion -- References -- Chapter 6 The Role of Metaverse, AI, and 5G in Modernizing Healthcare Platforms -- 6.1 Introduction -- 6.1.1 Metaverse -- 6.1.2 AI -- 6.1.3 5G and Beyond -- 6.2 Application of Metaverse in Healthcare -- 6.3 5G and AI Integration with Metaverse -- 6.4 Conclusion and Future Scope -- References -- Chapter 7 Metaverse Makeover: Transforming Patient Care and Wellness in Virtual Realms -- 7.1 Introduction -- 7.2 The Evolution of Healthcare in Virtual Environments -- 7.3 Applications of the Metaverse in Patient Care -- 7.4 Improving Healthcare Education and Training -- 7.5 Challenges and Considerations -- 7.6 Future Directions and Opportunities -- 7.7 Conclusion -- References -- Chapter 8 Metaverse in Medical Training and Education. 8.1 Introduction -- 8.2 Virtual Reality -- 8.3 Augmented Reality -- 8.4 The Technology -- 8.4.1 Augmented Reality (AR) -- 8.4.2 Virtual Reality (VR) -- 8.5 Market of AR and VR in Healthcare Practice -- 8.6 Case Studies -- 8.7 Future Directions -- 8.8 Conclusion -- References -- Part II: Security for Metaverse -- Chapter 9 Securing Healthcare in the Metaverse: Advance Deep Learning Algorithms for Non-TATA Promoter Classification in Genome Sequencing -- 9.1 Introduction -- 9.2 Literature Review -- 9.3 Methodology -- 9.3.1 Preprocessing -- 9.3.2 Sequence Modeling -- 9.3.3 Convolutional Models -- 9.3.4 Combining Sequence Modeling and Feature Extraction -- 9.3.5 WaveNet -- 9.4 Experimental Setup -- 9.4.1 Data Collection -- 9.5 Evaluation Metrics -- 9.6 Training Parameters -- 9.7 Results and Discussion -- 9.7.1 LSTM -- 9.7.2 CNN -- 9.7.3 ConvoLSTM -- 9.7.4 WaveNet -- 9.8 Conclusion -- References -- Chapter 10 Data Protection Regulation for E-Health Devices -- 10.1 Introduction to E-Health Devices -- 10.1.1 Definition of E-Health Devices -- 10.1.2 Scope and Trends in E-Health Devices -- 10.1.2.1 Scope of E-Health Devices -- 10.1.2.2 Trends in E-Health Devices -- 10.1.3 E-Health Devices in Healthcare and Important Roles -- 10.1.3.1 Patient Empowerment and Self- Management -- 10.1.3.2 Healthcare Provider Efficiency and Effectiveness -- 10.1.3.3 Healthcare System Optimization -- 10.2 Importance of Data Protection Regulations -- 10.2.1 Overview of General Data Protection Regulation (GDPR) -- 10.2.2 Health Insurance Portability and Accountability Act (HIPAA) -- 10.2.3 Accountability Act and Relevant Regulations (CCPA and PIPEDA) -- 10.2.4 Important Guidelines and International Standards -- 10.3 Security Principles and Data Privacy -- 10.3.1 Overview of Data Minimization -- 10.3.2 Data Integrity -- 10.3.3 Data Confidentiality. 10.3.4 Transparency and Accountability of Data Privacy -- 10.3.4.1 Transparency -- 10.3.4.2 Rights of Data Security -- 10.4 Regulatory Requirements and Compliance Framework -- 10.4.1 Data Preprocessing, Retention, and Storage -- 10.4.1.1 Data Preprocessing -- 10.4.1.2 Data Retention -- 10.4.1.3 Data Storage -- 10.4.2 Data-Sharing Access -- 10.4.3 Risk Assessment of E-Health Devices -- 10.4.4 Data Protection and Privacy -- 10.4.5 Security Mechanisms for Regulatory Requirements -- 10.5 Data Transfer and Standard Regulations -- 10.5.1 Global Data Transfer and Legal Frameworks -- 10.5.2 Binding Corporate Rules (BCR) -- 10.5.3 Standard Contractual Clauses (SCC) -- 10.5.4 Decision-Making for Data Transfer -- 10.6 Future Data Protection for the E-Health Sector -- 10.6.1 Future Technologies and Impact of the E-Health Sector -- 10.6.2 Emerging Technologies in Data Protection -- 10.6.2.1 AI and Machine Learning in Data Protection -- 10.6.2.2 Role of Blockchain in Data Protection Management -- 10.6.2.3 Data Protection Regulatory Evaluation -- 10.6.3 Security Measures and Ethical Considerations -- 10.6.4 Enhancing the Protection Control over Personal Health Data -- 10.6.5 Industry Standards in Data-Sharing Mechanisms -- 10.6.6 Future Challenges and Solutions for Data Protection -- 10.6.7 Summary of the Data Protection -- 10.6.7.1 Applications of Data Privacy and Security in E-Health -- 10.6.7.2 Future Trends in Data Protection for E-Health -- References -- Chapter 11 An Extensive Review of Current Cybersecurity Trends in the Healthcare Sector -- 11.1 Introduction -- 11.2 Related Work -- 11.3 Findings from the Review -- 11.4 Limitations and Suggestions for Future Research -- 11.5 Conclusion -- References -- Chapter 12 Implementation of Metaverse Technologies and Its Security -- 12.1 Introduction -- 12.2 Unpacking the Metaverse and Its Key Ingredients. 12.2.1 Virtual Reality (VR) -- 12.2.2 Augmented Reality (AR) -- 12.2.3 Mixed Reality (MR) -- 12.2.4 Metaverse Enables in Health Space -- 12.2.5 Telemedicine and Remote Consultations -- 12.3 Patient Engagement and Therapy in the Metaverse -- 12.3.1 Virtual Reality Treatment -- 12.3.2 Involved Patients and Personalized Therapy -- 12.3.3 Establishing Networks and Communities -- 12.4 Case Study for the Global Health Initiative -- 12.5 Ethical Factors in VR Therapy -- 12.5.1 Informed Consent -- 12.5.2 Individualized -- 12.5.3 Constant Monitoring -- 12.6 Technological Challenges and Solutions -- 12.6.1 The Metaverse's Potential for Healthcare -- 12.6.2 Prospective Applications in the Future -- 12.6.3 Potential Limitations and Challenges -- 12.7 Conclusion -- References -- Chapter 13 Metaverse Technologies, Security, and Applications for Healthcare -- 13.1 Introduction to the Metaverse -- 13.2 Metaverse Technologies: Back to the Basics and Beyond -- 13.2.1 Virtual Reality (VR) and Augmented Reality (AR) -- 13.2.2 Blockchain and Decentralized Technologies -- 13.2.3 AI and ML -- 13.2.4 5G and Edge Computing -- 13.2.5 Innovations in Human-Computer Interaction (HCI) -- 13.3 Security Challenges in the Metaverse for Healthcare -- 13.3.1 Data Privacy and Confidentiality -- 13.3.2 Identity Management and Authentication -- 13.3.3 Cybersecurity Threats and Attack Vectors -- 13.3.4 Data Integrity and Reliability -- 13.3.5 Compliance with Regulatory Requirements -- References -- Chapter 14 Leading-Edge Key Management Techniques in the Cryptography: The Metaverse-Driven Strategy -- 14.1 Introduction -- 14.2 Association of Sections -- 14.3 Significant and Consequence of the Leading-Edge Key Management -- 14.4 Recommended Approaches -- 14.5 An Extremely Efficient Encipher/Decipher Suggested Algorithm -- 14.5.1 Essential Key Elements. 14.5.2 Approaches in the Process of Encipher/Decipher. |
| Record Nr. | UNINA-9911019180603321 |
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Vyas Ajay Kumar
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| Newark : , : John Wiley & Sons, Incorporated, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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