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Artificial Intelligence and Blockchain in Precision Medicine and Virology
| Artificial Intelligence and Blockchain in Precision Medicine and Virology |
| Autore | Chatterjee Jyotir Moy |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2025 |
| Descrizione fisica | 1 online resource (624 pages) |
| Disciplina | 610.285 |
| Altri autori (Persone) | SaxenaShailendra K |
| Collana | Medical Virology: from Pathogenesis to Disease Control Series |
| ISBN | 981-9689-19-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9911028753203321 |
Chatterjee Jyotir Moy
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| Singapore : , : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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A Roadmap for Enabling Industry 4. 0 by Artificial Intelligence
| A Roadmap for Enabling Industry 4. 0 by Artificial Intelligence |
| Autore | Chatterjee Jyotir Moy |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2023 |
| Descrizione fisica | 1 online resource (339 pages) |
| Altri autori (Persone) |
GargHarish
ThakurR. N |
| ISBN |
1-119-90514-1
1-119-90513-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Artificial Intelligence-The Driving Force of Industry 4.0 -- 1.1 Introduction -- 1.2 Methodology -- 1.3 Scope of AI in Global Economy and Industry 4.0 -- 1.3.1 Artificial Intelligence-Evolution and Implications -- 1.3.2 Artificial Intelligence and Industry 4.0-Investments and Returns on Economy -- 1.3.3 The Driving Forces for Industry 4.0 -- 1.4 Artificial Intelligence-Manufacturing Sector -- 1.4.1 AI Diversity-Applications to Manufacturing Sector -- 1.4.2 Future Roadmap of AI-Prospects to Manufacturing Sector in Industry 4.0 -- 1.5 Conclusion -- References -- Chapter 2 Industry 4.0, Intelligent Manufacturing, Internet of Things, Cloud Computing: An Overview -- 2.1 Introduction -- 2.2 Industrial Transformation/Value Chain Transformation -- 2.2.1 First Scenario: Reducing Waste and Increasing Productivity Using IIoT -- 2.2.2 Second Scenario: Selling Outcome (User Demand)-Based Services Using IIoT -- 2.3 IIoT Reference Architecture -- 2.4 IIoT Technical Concepts -- 2.5 IIoT and Cloud Computing -- 2.6 IIoT and Security -- References -- Chapter 3 Artificial Intelligence of Things (AIoT) and Industry 4.0-Based Supply Chain (FMCG Industry) -- 3.1 Introduction -- 3.2 Concepts -- 3.2.1 Internet of Things -- 3.2.2 The Industrial Internet of Things (IIoT) -- 3.2.3 Artificial Intelligence of Things (AIoT) -- 3.3 AIoT-Based Supply Chain -- 3.4 Conclusion -- References -- Chapter 4 Application of Artificial Intelligence in Forecasting the Demand for Supply Chains Considering Industry 4.0 -- 4.1 Introduction -- 4.2 Literature Review -- 4.2.1 Summary of the First Three Industrial Revolutions -- 4.2.2 Emergence of Industry 4.0 -- 4.2.3 Some of the Challenges of Industry 4.0 -- 4.3 Application of Artificial Intelligence in Supply Chain Demand Forecasting -- 4.4 Proposed Approach.
4.4.1 Mathematical Model -- 4.4.2 Advantages of the Proposed Model -- 4.5 Discussion and Conclusion -- References -- Chapter 5 Integrating IoT and Deep Learning-The Driving Force of Industry 4.0 -- 5.1 Motivation and Background -- 5.2 Bringing Intelligence Into IoT Devices -- 5.3 The Foundation of CR-IoT Network -- 5.3.1 Various AI Technique in CR-IoT Network -- 5.3.2 Artificial Neural Network (ANN) -- 5.3.3 Metaheuristic Technique -- 5.3.4 Rule-Based System -- 5.3.5 Ontology-Based System -- 5.3.6 Probabilistic Models -- 5.4 The Principles of Deep Learning and Its Implementation in CR-IoT Network -- 5.5 Realization of CR-IoT Network in Daily Life Examples -- 5.6 AI-Enabled Agriculture and Smart Irrigation System-Case Study -- 5.7 Conclusion -- References -- Chapter 6 A Systematic Review on Blockchain Security Technology and Big Data Employed in Cloud Environment -- 6.1 Introduction -- 6.2 Overview of Blockchain -- 6.3 Components of Blockchain -- 6.3.1 Data Block -- 6.3.2 Smart Contracts -- 6.3.3 Consensus Algorithms -- 6.4 Safety Issues in Blockchain Technology -- 6.5 Usage of Big Data Framework in Dynamic Supply Chain System -- 6.6 Machine Learning and Big Data -- 6.6.1 Overview of Shallow Models -- 6.6.1.1 Support Vector Machine (SVM) -- 6.6.1.2 Artificial Neural Network (ANN) -- 6.6.1.3 K-Nearest Neighbor (KNN) -- 6.6.1.4 Clustering -- 6.6.1.5 Decision Tree -- 6.7 Advantages of Using Big Data for Supply Chain and Blockchain Systems -- 6.7.1 Replenishment Planning -- 6.7.2 Optimizing Orders -- 6.7.3 Arranging and Organizing -- 6.7.4 Enhanced Demand Structuring -- 6.7.5 Real-Time Management of the Supply Chain -- 6.7.6 Enhanced Reaction -- 6.7.7 Planning and Growth of Inventories -- 6.8 IoT-Enabled Blockchains -- 6.8.1 Securing IoT Applications by Utilizing Blockchain -- 6.8.2 Blockchain Based on Permission -- 6.8.3 Blockchain Improvements in IoT. 6.8.3.1 Blockchain Can Store Information Coming from IoT Devices -- 6.8.3.2 Secure Data Storage with Blockchain Distribution -- 6.8.3.3 Data Encryption via Hash Key and Tested by the Miners -- 6.8.3.4 Spoofing Attacks and Data Loss Prevention -- 6.8.3.5 Unauthorized Access Prevention Using Blockchain -- 6.8.3.6 Exclusion of Centralized Cloud Servers -- 6.9 Conclusions -- References -- Chapter 7 Deep Learning Approach to Industrial Energy Sector and Energy Forecasting with Prophet -- 7.1 Introduction -- 7.2 Related Work -- 7.3 Methodology -- 7.3.1 Splitting of Data (Test/Train) -- 7.3.2 Prophet Model -- 7.3.3 Data Cleaning -- 7.3.4 Model Implementation -- 7.4 Results -- 7.4.1 Comparing Forecast to Actuals -- 7.4.2 Adding Holidays -- 7.4.3 Comparing Forecast to Actuals with the Cleaned Data -- 7.5 Conclusion and Future Scope -- References -- Chapter 8 Application of Novel AI Mechanism for Minimizing Private Data Release in Cyber-Physical Systems -- 8.1 Introduction -- 8.2 Related Work -- 8.3 Proposed Mechanism -- 8.4 Experimental Results -- 8.5 Future Directions -- 8.6 Conclusion -- References -- Chapter 9 Environmental and Industrial Applications Using Internet of Things (IoT) -- 9.1 Introduction -- 9.2 IoT-Based Environmental Applications -- 9.3 Smart Environmental Monitoring -- 9.3.1 Air Quality Assessment -- 9.3.2 Water Quality Assessment -- 9.3.3 Soil Quality Assessment -- 9.3.4 Environmental Health-Related to COVID-19 Monitoring -- 9.4 Applications of Sensors Network in Agro-Industrial System -- 9.5 Applications of IoT in Industry -- 9.5.1 Application of IoT in the Autonomous Field -- 9.5.2 Applications of IoT in Software Industries -- 9.5.3 Sensors in Industry -- 9.6 Challenges of IoT Applications in Environmental and Industrial Applications -- 9.7 Conclusions and Recommendations -- Acknowledgments -- References. Chapter 10 An Introduction to Security in Internet of Things (IoT) and Big Data -- 10.1 Introduction -- 10.2 Allusion Design of IoT -- 10.2.1 Stage 1-Edge Tool -- 10.2.2 Stage 2-Connectivity -- 10.2.3 Stage 3-Fog Computing -- 10.2.4 Stage 4-Data Collection -- 10.2.5 Stage 5-Data Abstraction -- 10.2.6 Stage 6-Applications -- 10.2.7 Stage 7-Cooperation and Processes -- 10.3 Vulnerabilities of IoT -- 10.3.1 The Properties and Relationships of Various IoT Networks -- 10.3.2 Device Attacks -- 10.3.3 Attacks on Network -- 10.3.4 Some Other Issues -- 10.3.4.1 Customer Delivery Value -- 10.3.4.2 Compatibility Problems With Equipment -- 10.3.4.3 Compatibility and Maintenance -- 10.3.4.4 Connectivity Issues in the Field of Data -- 10.3.4.5 Incorrect Data Collection and Difficulties -- 10.3.4.6 Security Concern -- 10.3.4.7 Problems in Computer Confidentiality -- 10.4 Challenges in Technology -- 10.4.1 Skepticism of Consumers -- 10.5 Analysis of IoT Security -- 10.5.1 Sensing Layer Security Threats -- 10.5.1.1 Node Capturing -- 10.5.1.2 Malicious Attack by Code Injection -- 10.5.1.3 Attack by Fake Data Injection -- 10.5.1.4 Sidelines Assaults -- 10.5.1.5 Attacks During Booting Process -- 10.5.2 Network Layer Safety Issues -- 10.5.2.1 Attack on Phishing Page -- 10.5.2.2 Attacks on Access -- 10.5.2.3 Attacks on Data Transmission -- 10.5.2.4 Attacks on Routing -- 10.5.3 Middleware Layer Safety Issues -- 10.5.3.1 Attack by SQL Injection -- 10.5.3.2 Attack by Signature Wrapping -- 10.5.3.3 Cloud Attack Injection with Malware -- 10.5.3.4 Cloud Flooding Attack -- 10.5.4 Gateways Safety Issues -- 10.5.4.1 On-Boarding Safely -- 10.5.4.2 Additional Interfaces -- 10.5.4.3 Encrypting End-to-End -- 10.5.5 Application Layer Safety Issues -- 10.5.5.1 Theft of Data -- 10.5.5.2 Attacks at Interruption in Service -- 10.5.5.3 Malicious Code Injection Attack. 10.6 Improvements and Enhancements Needed for IoT Applications in the Future -- 10.7 Upcoming Future Research Challenges with Intrusion Detection Systems (IDS) -- 10.8 Conclusion -- References -- Chapter 11 Potential, Scope, and Challenges of Industry 4.0 -- 11.1 Introduction -- 11.2 Key Aspects for a Successful Production -- 11.3 Opportunities with Industry 4.0 -- 11.4 Issues in Implementation of Industry 4.0 -- 11.5 Potential Tools Utilized in Industry 4.0 -- 11.6 Conclusion -- References -- Chapter 12 Industry 4.0 and Manufacturing Techniques: Opportunities and Challenges -- 12.1 Introduction -- 12.2 Changing Market Demands -- 12.2.1 Individualization -- 12.2.2 Volatility -- 12.2.3 Efficiency in Terms of Energy Resources -- 12.3 Recent Technological Advancements -- 12.4 Industrial Revolution 4.0 -- 12.5 Challenges to Industry 4.0 -- 12.6 Conclusion -- References -- Chapter 13 The Role of Multiagent System in Industry 4.0 -- 13.1 Introduction -- 13.2 Characteristics and Goals of Industry 4.0 Conception -- 13.3 Artificial Intelligence -- 13.3.1 Knowledge-Based Systems -- 13.4 Multiagent Systems -- 13.4.1 Agent Architectures -- 13.4.2 JADE -- 13.4.3 System Requirements Definition -- 13.4.4 HMI Development -- 13.5 Developing Software of Controllers Multiagent Environment Behavior Patterns -- 13.5.1 Agent Supervision -- 13.5.2 Documents Dispatching Agents -- 13.5.3 Agent Rescheduling -- 13.5.4 Agent of Executive -- 13.5.5 Primary Roles of High-Availability Agent -- 13.6 Conclusion -- References -- Chapter 14 An Overview of Enhancing Encryption Standards for Multimedia in Explainable Artificial Intelligence Using Residue Number Systems for Security -- 14.1 Introduction -- 14.2 Reviews of Related Works -- 14.3 Materials and Methods -- 14.3.1 Multimedia -- 14.3.2 Artificial Intelligence and Explainable Artificial Intelligence -- 14.3.3 Cryptography. 14.3.4 Encryption and Decryption. |
| Record Nr. | UNINA-9910632498003321 |
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Chatterjee Jyotir Moy
|
||
| Newark : , : John Wiley & Sons, Incorporated, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Role of Artificial Intelligence, Telehealth, and Telemedicine in Medical Virology / / edited by Jyotir Moy Chatterjee, R. Sujatha, Shailendra K. Saxena
| Role of Artificial Intelligence, Telehealth, and Telemedicine in Medical Virology / / edited by Jyotir Moy Chatterjee, R. Sujatha, Shailendra K. Saxena |
| Autore | Chatterjee Jyotir Moy |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (324 pages) |
| Disciplina | 616.9101 |
| Altri autori (Persone) |
SujathaR
SaxenaShailendra K |
| Collana | Medical Virology: From Pathogenesis to Disease Control |
| Soggetto topico |
Microbiology
Virology Medical sciences Biomedical engineering Medical informatics Artificial intelligence Health Sciences Medical and Health Technologies Health Informatics Artificial Intelligence |
| ISBN |
9789819729388
9819729386 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Transforming Healthcare: The Synergy of Telemedicine, Telehealth, and Artificial Intelligence -- Chapter 2. Role of AI in diagnosis of Viral Infection -- Chapter 3. The Influence of Artificial Intelligence in Drug Discovery and Development -- Chapter 4. Transformative effect on the role of telehealth during pandemic -- Chapter 5. Effective Cloud Infrastructure for Optimal Telehealth Service -- Chapter 6. Advancements of Telemedicine using Blockchain and Deep Learning for Smart Healthcare -- Chapter 7. Impact of Telehealth during Pandemic in Remote Locations -- Chapter 8. A Terrific Structure for City Dengue Predictive Recommender Analytics -- Chapter 9. Machine Learning for Intelligent Healthcare Across Decentralized Patient Databases Using Federated Learning -- Chapter 10. Cancer Disease Prediction Using an Integrated Ensemble Technique with ReliefF and FP -- Chapter 11. AI Managed Hospital Workforce -- Chapter 12. Healthcare Data Security in Multi-Cloud Infrastructure using Heuristic Algorithms. |
| Record Nr. | UNINA-9910977984803321 |
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Chatterjee Jyotir Moy
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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