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MARC Lista (tabellare)
Decentralized Systems and Distributed Computing
Decentralized Systems and Distributed Computing
Autore Avasthi Sandhya
Edizione [1st ed.]
Pubbl/distr/stampa Newark : , : John Wiley & Sons, Incorporated, , 2024
Descrizione fisica 1 online resource (401 pages)
Disciplina 005.75/8
Altri autori (Persone) TripathiSuman Lata
DhandaNamrata
VermaSatya Bhushan
Collana Decentralized systems and next generation internet
Soggetto topico Electronic data processing - Distributed processing
ISBN 1-394-20512-0
1-394-20511-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Introduction to Next-Generation Internet and Distributed Systems -- 1.1 Introduction -- 1.2 Traditional Network -- 1.3 Next-Generation Internet -- 1.3.1 Next-Generation Internet Protocol -- 1.3.1.1 IPv6 -- 1.3.1.2 Tunneling -- 1.3.2 Quality of Service (QoS) -- 1.4 Network Middleware -- 1.5 Software-Defined Network (SDN) -- 1.5.1 Necessity of Software-Defined Network -- 1.6 Edge Cloud-Based Next-Generation Internet -- 1.6.1 Edge Cloud -- 1.6.2 Content Distribution Networks (CDNs) -- 1.7 Network Architecture -- 1.7.1 Some Proposed Architectures -- 1.7.1.1 Security Architecture for Networked Enterprises (SANE) -- 1.7.1.2 Swarming Architecture -- 1.7.1.3 Flexible Internet Architecture (FlexNGIA) -- 1.7.1.4 Architecture for Mobility Support -- 1.7.1.5 The Data-Oriented Network Architecture (DONA) -- 1.7.1.6 MILSA (Mobility and Multihoming Supporting Identifier-Locator Split Architecture) -- 1.7.1.7 Delay/Disruption Tolerant Networks (DTN) and Related Architectures -- 1.7.2 Challenges for Architecture -- 1.7.2.1 Network Services -- 1.7.2.2 Network Management -- 1.7.2.3 Network Performance -- 1.7.2.4 Diversity and Change -- 1.8 Security and Safety -- 1.9 Distributed Systems -- 1.9.1 Concept of Distributed System -- 1.9.2 Terminologies -- 1.9.2.1 Grouping of Autonomous Computer Components -- 1.9.2.2 Single Coherent System -- 1.10 Distributed System Design -- 1.10.1 Significance of a Certain Design -- 1.10.2 Scale and Scalability -- 1.10.2.1 Definition of Scale -- 1.10.2.2 Scalability Analysis -- 1.11 Distributed System Monitoring -- 1.11.1 Idea of Monitoring System -- 1.12 Security in Distributed Systems -- 1.12.1 Reasons for Not Using Encryption -- 1.12.2 Authorization -- 1.13 Blockchain and Distributed Systems -- 1.13.1 Decentralization.
1.13.2 Peer-to-Peer Networks (P2P) -- 1.14 Blockchain-Based Distributed Control Systems -- 1.14.1 Control System -- 1.14.1.1 To Handle Complicated Processes -- 1.14.1.2 Pre-Defined Function Blocks -- 1.14.1.3 Scalable Platform -- 1.15 Blockchain for Distributed System Security -- 1.15.1 Fault-Tolerant Consensus in a Distributed System -- 1.15.2 Complications while Using Blockchain for Distributed Computing -- 1.16 Conclusion and Future Scope -- References -- Chapter 2 Decentralized System in Education and Research -- 2.1 Introduction -- 2.2 History of Decentralization in the Education System -- 2.3 Advantages and Challenges of Decentralization of the Education System -- 2.3.1 Advantages -- 2.3.2 Challenges -- 2.4 Impact of Decentralization in Education and Research -- 2.5 Current Approaches -- 2.5.1 World Scenario -- 2.5.1.1 Finland Education System -- 2.5.1.2 Brazil, Federal Universities -- 2.5.1.3 The United States, National Science Foundation -- 2.5.1.4 Mexico, CONACYT -- 2.5.2 Indian Scenario -- 2.5.2.1 Kerala Model of Decentralization Implementation in Education and Research -- 2.6 Development Trend Towards Education and Research -- 2.7 Future Scope and Recommendations -- 2.8 Conclusion -- References -- Chapter 3 Architecture of Blockchain-Enabled Decentralized Systems -- 3.1 Introduction -- 3.2 What is a Decentralized System? -- 3.2.1 Centralized System vs. Decentralized System -- 3.2.2 Merits and Demerits of a Decentralized System -- 3.3 Blockchain -- 3.3.1 What is Blockchain? -- 3.3.2 Structure of Blockchain -- 3.3.3 Requirements of Blockchain -- 3.3.4 Merits and Demerits of Blockchain -- 3.4 Smart Contracts and Its Examples -- 3.5 Blockchain-Enabled Decentralized System -- 3.5.1 Role of Blockchain -- 3.5.2 Types of Decentralization in Blockchain -- 3.5.3 Types of Blockchain Architecture -- 3.5.4 Requirements -- 3.5.5 Pros and Cons.
3.6 Architecture for the Blockchain-Enabled Decentralized System -- 3.6.1 The Network -- 3.6.2 The Consensus Protocol -- 3.6.3 The Data Structure -- 3.7 Decentralized Todo App with Blockchain -- 3.8 Blockchain-Enabled Decentralized System Development and Challenges -- 3.9 Future of the Blockchain-Enabled Decentralized System -- 3.10 Conclusion -- References -- Chapter 4 Mobile Edge Computing for Decentralized Systems -- 4.1 Introduction -- 4.2 Edge Computing -- 4.3 Benefits of Edge Computing -- 4.4 Classification of Attacks in a 5G IoT System -- 4.5 Decentralized Dynamic Computation Offloading Method -- 4.6 Conclusion -- References -- Chapter 5 Blockchain in Education -- 5.1 Introduction -- 5.2 Benefits of Blockchain in Education -- 5.2.1 Blockchain Can Enhance Learner Data Privacy and Security, Allowing Learners to Maintain Control Over Their Personal Information -- 5.2.2 Blockchain Can Enable Lifelong Learning Tracking, Creating a Comprehensive and Immutable Record of a Learner's Achievements and Skills -- 5.2.2.1 Blockchain as a Distributed and Immutable Record-Keeping System -- 5.2.2.2 Benefits of Blockchain-Enabled Lifelong Learning Tracking -- 5.3 Challenges of Blockchain in Education -- 5.3.1 Concerns Related to Data Privacy, Security, and Compliance with Data Protection Regulations -- 5.3.1.1 Data Privacy Concerns -- 5.3.1.2 Compliance with Data Protection Regulations -- 5.3.1.3 Security Concerns -- 5.3.1.4 Collaboration with Industry Experts and Auditors -- 5.3.2 Potential Resistance to Change and Adoption Barriers in the Education Sector -- 5.4 Use Cases of Blockchain in Education -- 5.5 Conclusion -- References -- Chapter 6 Pattern Recognition Applications in Distributed Systems and Distributed Machine Learning -- 6.1 Introduction -- 6.1.1 What is Pattern Recognition? -- 6.1.2 Distributed Computing Environment.
6.1.3 Basic Model of the Pattern Recognition System -- 6.2 Data Generation and Preprocessing -- 6.3 Feature Selection -- 6.3.1 What is Feature Selection? -- 6.3.2 Filter Models of Feature Selection -- 6.3.3 Wrapper Models of Feature Selection -- 6.4 Design of Classifier -- 6.4.1 Conventional Classifiers in Distributed Environment -- 6.4.2 Neural Network Classifiers in a Distributed Environment -- 6.5 Designing Machine Learning Models for Distributed Environment -- 6.6 Role of Distributed Computing in Pattern Recognition -- 6.7 Conclusion -- References -- Chapter 7 Next-Generation Distributed Computing for Cancer Detection -- 7.1 Introduction -- 7.2 Research Motivation -- 7.3 Cancer Statistics -- 7.4 Modern Cancer Diagnosis and Treatment Methods -- 7.5 Methodology -- 7.6 Technical Challenges -- 7.7 Future Directions -- 7.8 Conclusion -- References -- Chapter 8 Benefits and Challenges of Decentralization in Education for Resource Optimization and Improved Performance -- 8.1 Introduction -- 8.1.1 Decentralized Systems in Education and Research -- 8.1.2 Connect Between Democracy and Education -- 8.2 The Centralization and Decentralization Concepts -- 8.3 Decentralized Systems in Education and Research: Policies and Practices -- 8.3.1 Open Educational Resources (OER) Policy -- 8.3.2 Collaborative Research Networks -- 8.3.3 Self-Directed Learning -- 8.3.4 Peer Review -- 8.3.5 Open Data -- 8.3.6 Equity and Inclusion -- 8.3.7 Quality Assurance -- 8.4 Building Capacity Across and Between Levels Within Education Systems -- 8.5 Developing Accountability Measures and Systems in Implementing a Decentralized Education Policy -- 8.5.1 Establish Clear and Quantifiable Policy Objectives -- 8.5.2 Create Performance Indicators and Benchmarks -- 8.5.3 Assign Roles and Responsibilities -- 8.5.4 Build Effective Monitoring and Evaluation Systems.
8.5.5 Encourage Transparency and Involvement -- 8.5.6 Establish Redressal Mechanisms -- 8.6 Developing Local-Level Capacity Across All Education System Levels and Sectors -- 8.7 Education Policies in India to Achieve Decentralization in Education Systems -- 8.7.1 National Education Policy (NEP) 2020 -- 8.7.2 Rashtriya Madhyamik Shiksha Abhiyan (RMSA) -- 8.7.3 RUSA (Rashtriya Uchchatar Shiksha Abhiyan) -- 8.8 Research and Development Policies in India and Promoting Decentralization in R& -- D -- 8.8.1 Atal Innovation Mission (AIM) -- 8.8.2 The National Initiative for Developing and Harnessing Innovations (NIDHI) -- 8.8.3 National Science, Technology, and Innovation Policy (STI) 2020 -- 8.8.4 Council of Scientific and Industrial Research (CSIR) -- 8.8.5 Department of Science and Technology (DST) -- References -- Chapter 9 Blockchain in Data Security and Transparency in Business Transactions -- 9.1 Introduction -- 9.2 Dimensions and Requirements of Data Security -- 9.3 Security Issues in Conventional Data Security -- 9.4 Diversity of Attacks in Conventional Data Security -- 9.5 Blockchain: The Complete Solution -- 9.6 The Decentralized and Immutable Approach -- 9.7 Comparison of ECC and RSA -- 9.8 Digital Signature Algorithm -- 9.9 Blockchain Technology Ensures Transparency -- 9.10 Blockchain Solutions for Traditional Data Security -- 9.11 Blockchain Types -- 9.12 Conclusion -- References -- Chapter 10 A Comparative Study of Ad Hoc and Wireless Sensor Networks -- 10.1 Introduction -- 10.2 Ad Hoc Network -- 10.2.1 Ad Hoc Network Types -- 10.2.2 Ad Hoc Routing Protocol -- 10.2.3 Ad Hoc Security Attack -- 10.3 Wireless Sensor and Network -- 10.3.1 Types of Wireless Network -- 10.3.2 Mobility in WSN -- 10.3.3 Routing Protocol -- 10.4 Challenges, Applications, and Limitations -- 10.5 Conclusion -- References.
Chapter 11 Content Filtering-Based Movie Recommendation System Using Deep Learning.
Record Nr. UNINA-9910877294603321
Avasthi Sandhya  
Newark : , : John Wiley & Sons, Incorporated, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Design and development of efficient energy systems / / editors, Suman Lata Tripathi [et al.]
Design and development of efficient energy systems / / editors, Suman Lata Tripathi [et al.]
Pubbl/distr/stampa Hoboken, NJ : , : Wiley : , : Scrivener Publishing, , [2021]
Descrizione fisica 1 online resource (384 pages)
Disciplina 621.317
Collana Artificial Intelligence and Soft Computing for Industrial Transformation
Soggetto topico Artificial intelligence - Industrial applications
Electric power supplies to apparatus - Energy conservation - Data processing
Soggetto genere / forma Electronic books.
ISBN 1-5231-4332-0
1-119-76178-6
1-119-76177-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- 1 Design of Low Power Junction Less Double-Gate MOSFET -- 1.1 Introduction -- 1.2 MOSFET Performance Parameters -- 1.3 Comparison of Existing MOSFET Architectures -- 1.4 Proposed Heavily Doped Junction-Less Double Gate MOSFET (AJ-DGMOSFET) -- 1.5 Heavily Doped JL-DG MOSFET for Biomedical Application -- 1.6 Conclusion -- References -- 2 VLSI Implementation of Vedic Multiplier -- 2.1 Introduction -- 2.2 8x8 Vedic Multiplier -- 2.3 The Architecture of 8x8 Vedic Multiplier (VM) -- 2.3.1 Compressor Architecture -- 2.4 Results and Discussion -- 2.4.1 Instance Power -- 2.4.2 Net Power -- 2.4.3 8-Bit Multiplier -- 2.4.4 16-Bit Multiplier -- 2.4.5 Applications of Multiplier -- 2.5 Conclusion -- References -- 3 Gas Leakage Detection from Drainage to Offer Safety for Sanitary Workers -- 3.1 Introduction -- 3.1.1 IOT-Based Sewer Gas Detection -- 3.1.2 Objective -- 3.1.3 Contribution of this Chapter -- 3.1.4 Outline of the Chapter -- 3.2 Related Works -- 3.2.1 Sewer Gas Leakage Detection -- 3.2.2 Crack Detection -- 3.3 Methodology -- 3.3.1 Sewer Gas Detection -- 3.3.2 Crack Detection -- 3.3.3 Experimental Setup -- 3.4 Experimental Results -- 3.5 Conclusion -- References -- 4 Machine Learning for Smart Healthcare Energy-Efficient System -- 4.1 Introduction -- 4.1.1 IoT in the Digital Age -- 4.1.2 Using IoT to Enhance Healthcare Services -- 4.1.3 Edge Computing -- 4.1.4 Machine Learning -- 4.1.5 Application in Healthcare -- 4.2 Related Works -- 4.3 Edge Computing -- 4.3.1 Architecture -- 4.3.2 Advantages of Edge Computing over Cloud Computing -- 4.3.3 Applications of Edge Computing in Healthcare -- 4.3.4 Edge Computing Advantages -- 4.3.5 Challenges -- 4.4 Smart Healthcare System -- 4.4.1 Methodology -- 4.4.2 Data Acquisition and IoT End Device.
4.4.3 IoT End Device and Backend Server -- 4.5 Conclusion and Future Directions -- References -- 5 Review of Machine Learning Techniques Used for Intrusion and Malware Detection in WSNs and IoT Devices -- 5.1 Introduction -- 5.2 Types of Attacks -- 5.3 Some Countermeasures for the Attacks -- 5.4 Machine Learning Solutions -- 5.5 Machine Learning Algorithms -- 5.6 Authentication Process Based on Machine Learning -- 5.7 Internet of Things (IoT) -- 5.8 IoT-Based Attacks -- 5.8.1 Botnets -- 5.8.2 Man-in-the-Middle -- 5.9 Information and Identity Theft -- 5.10 Social Engineering -- 5.11 Denial of Service -- 5.12 Concerns -- 5.13 Conclusion -- References -- 6 Smart Energy-Efficient Techniques for Large-Scale Process Industries -- 6.1 Pumps Operation -- 6.1.1 Parts in a Centrifugal Pump -- 6.1.2 Pump Efficiency -- 6.1.3 VFD -- 6.1.4 VFD and Pump Motor -- 6.1.5 Large HT Motors -- 6.1.6 Smart Pumps -- 6.2 Vapour Absorption Refrigeration System -- 6.2.1 Vapour Compression Refrigeration -- 6.2.2 Vapour Absorption Refrigeration -- 6.3 Heat Recovery Equipment -- 6.3.1 Case Study -- 6.3.2 Advantages of Heat Recovery -- 6.4 Lighting System -- 6.4.1 Technical Terms -- 6.4.2 Introduction -- 6.4.3 LED Lighting -- 6.4.4 Energy-Efficiency Techniques -- 6.4.5 Light Control with IoT -- 6.4.6 EU Practices -- 6.5 Air Conditioners -- 6.5.1 Technical Terms -- 6.5.2 Types of Air Conditioners -- 6.5.3 Star Rating of BEE -- 6.5.4 EU Practices -- 6.5.5 Energy-Efficiency Tips -- 6.5.6 Inverter Air Conditioners -- 6.5.7 IoT-Based Air Conditioners -- 6.6 Fans and Other Smart Appliances -- 6.6.1 BLDC Fan Motors -- 6.6.2 Star Ratings -- 6.6.3 Group Drive of Fans -- 6.6.4 Other Smart Appliances -- 6.7 Motors -- 6.7.1 Motor Efficiency -- 6.7.2 Underrated Operation -- 6.7.3 Energy-Efficient Motors -- 6.7.4 Retrofit of Standard Motors with Energy-Efficient Motors.
6.7.5 Other Salient Points -- 6.7.6 Use of Star-Delta Starter Motor -- 6.8 Energy-Efficient Transformers -- 6.8.1 IEC Recommendation -- 6.8.2 Super Conducting Transformers -- References -- 7 Link Restoration and Relay Node Placement in Partitioned Wireless Sensor Network -- 7.1 Introduction -- 7.2 Related Work -- 7.2.1 Existing Techniques -- 7.3 Proposed K-Means Clustering Algorithm -- 7.3.1 Homogenous and Heterogeneous Network Clustering Algorithms -- 7.3.2 Dynamic and Static Clustering -- 7.3.3 Flow Diagram -- 7.3.4 Objective Function -- 7.4 System Model and Assumption -- 7.4.1 Simulation Parameters -- 7.5 Results and Discussion -- 7.6 Conclusions -- References -- 8 Frequency Modulated PV Powered MLI Fed Induction Motor Drive for Water Pumping Applications -- 8.1 Introduction -- 8.2 PV Panel as Energy Source -- 8.2.1 Solar Cell -- 8.3 Multi-Level Inverter Topologies -- 8.3.1 Types of Inverters Used for Drives -- 8.3.2 Multi-Level Inverters -- 8.4 Experimental Results and Discussion -- 8.4.1 PV Powered H Bridge Inverter-Fed Drive -- 8.4.2 PV Powered DCMLI Fed Drive -- 8.5 Conclusion and Future Scope -- References -- 9 Analysis and Design of Bidirectional Circuits for Energy Storage Application -- 9.1 Introduction -- 9.2 Modes of Operation Based on Main Converters -- 9.2.1 Single-Stage Rectification -- 9.2.2 Single-Stage Inversion -- 9.2.3 Double-Stage Rectification -- 9.2.4 Double-Stage Inversion -- 9.3 Proposed Methodology for Three-Phase System -- 9.3.1 Control Block of Overall System -- 9.3.2 Proposed Carrier-Based PWM Strategy -- 9.3.3 Experiment Results -- 9.4 Conclusion -- References -- 10 Low-Power IOT-Enabled Energy Systems -- 10.1 Overview -- 10.1.1 Conceptions -- 10.1.2 Motivation -- 10.1.3 Methodology -- 10.2 Empowering Tools -- 10.2.1 Sensing Components -- 10.2.2 Movers -- 10.2.3 Telecommunication Technology.
10.2.4 Internet of Things Information and Evaluation -- 10.3 Internet of Things within Power Region -- 10.3.1 Internet of Things along with Vitality Production -- 10.3.2 Smart Metropolises -- 10.3.3 Intelligent Lattice Network -- 10.3.4 Smart Buildings Structures -- 10.3.5 Powerful Usage of Vitality in Production -- 10.3.6 Insightful Transport -- 10.4 Difficulties Relating Internet of Things -- 10.4.1 Vitality Ingestion -- 10.4.2 Synchronization via Internet of Things through Sub-Units -- 10.4.3 Client Confidentiality -- 10.4.4 Safety Challenges -- 10.4.5 IoT Standardization and Architectural Concept -- 10.5 Upcoming Developments -- 10.5.1 IoT and Block Chain -- 10.5.2 Artificial Intelligence and IoT -- 10.5.3 Green IoT -- 10.6 Conclusion -- References -- 11 Efficient Renewable Energy Systems -- Introduction -- 11.1 Renewable-Based Available Technologies -- 11.1.1 Wind Power -- 11.1.2 Solar Power -- 11.1.3 Tidal Energy -- 11.1.4 Battery Storage System -- 11.1.5 Solid Oxide Energy Units for Enhancing Power Life -- 11.2 Adaptability Frameworks -- 11.2.1 Distributed Energy Resources (DER) -- 11.2.2 New Age Grid Connection -- 11.3 Conclusion -- References -- 12 Efficient Renewable Energy Systems -- 12.1 Introduction -- 12.1.1 World Energy Scenario -- 12.2 Sources of Energy: Classification -- 12.3 Renewable Energy Systems -- 12.3.1 Solar Energy -- 12.3.2 Wind -- 12.3.3 Geothermal -- 12.3.4 Biomass -- 12.3.5 Ocean -- 12.3.6 Hydrogen -- 12.4 Solar Energy -- 12.5 Wind Energy -- 12.6 Geothermal Energy -- 12.7 Biomass -- 12.7.1 Forms of Biomass -- 12.8 Ocean Power -- 12.9 Hydrogen -- 12.10 Hydro Power -- 12.11 Conclusion -- References -- 13 Agriculture-IoT-Based Sprinkler System for Water and Fertilizer Conservation and Management -- 13.1 Introduction -- 13.1.1 Novelty of the Work -- 13.1.2 Benefit to Society -- 13.2 Development of the Proposed System.
13.3 System Description -- 13.3.1 Study of the Crop Under Experiment -- 13.3.2 Hardware of the System -- 13.3.3 Software of the System -- 13.4 Layers of the System Architecture -- 13.4.1 Application Layer -- 13.4.2 Cloud Layer -- 13.4.3 Network Layer -- 13.4.4 Physical Layer -- 13.5 Calibration -- 13.6 Layout of the Sprinkler System -- 13.7 Testing -- 13.8 Results and Discussion -- 13.9 Conclusion -- References -- 14 A Behaviour-Based Authentication to Internet of Things Using Machine Learning -- 14.1 Introduction -- 14.2 Basics of Internet of Things (IoT) -- 14.2.1 The IoT Reference Model -- 14.2.2 Working of IoT -- 14.2.3 Utilization of Internet of Things (IoT) -- 14.3 Authentication in IoT -- 14.3.1 Methods of Authentication -- 14.4 User Authentication Based on Behavioral-Biometric -- 14.4.1 Machine Learning -- 14.4.2 Machine Learning Algorithms -- 14.5 Threats and Challenges in the Current Security Solution for IoT -- 14.6 Proposed Methodology -- 14.6.1 Collection of Gait Dataset -- 14.6.2 Gait Data Preprocessing -- 14.6.3 Reduction in Data Size -- 14.6.4 Gaits Feature -- 14.6.5 Classification -- 14.7 Conclusion and Future Work -- References -- 15 A Fuzzy Goal Programming Model for Quality Monitoring of Fruits during Shipment Overseas -- 15.1 Introduction -- 15.2 Proposed System -- 15.2.1 Problem Statement -- 15.2.2 Overview -- 15.2.3 System Components -- 15.3 Work Process -- 15.3.1 System Hardware -- 15.3.2 Connections and Circuitry -- 15.4 Optimization Framework -- 15.4.1 Fuzzy Goal Description -- 15.4.2 Characterizing Fuzzy Membership Function -- 15.4.3 Construction of FGP Model -- 15.4.4 Definition of Variables and Parameters -- 15.4.5 Fuzzy Goal Description -- 15.5 Creation of Database and Website -- 15.5.1 Hosting PHP Application and Creation of MySQL Database -- 15.5.2 Creation of API (Application Programming Interfaces) Key.
15.6 Libraries Used and Code Snipped.
Record Nr. UNINA-9910555117803321
Hoboken, NJ : , : Wiley : , : Scrivener Publishing, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Design and development of efficient energy systems / / editors, Suman Lata Tripathi [et al.]
Design and development of efficient energy systems / / editors, Suman Lata Tripathi [et al.]
Pubbl/distr/stampa Hoboken, NJ : , : Wiley : , : Scrivener Publishing, , [2021]
Descrizione fisica 1 online resource (384 pages)
Disciplina 621.317
Collana Artificial Intelligence and Soft Computing for Industrial Transformation
Soggetto topico Artificial intelligence - Industrial applications
Electric power supplies to apparatus - Energy conservation - Data processing
ISBN 1-5231-4332-0
1-119-76178-6
1-119-76177-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- 1 Design of Low Power Junction Less Double-Gate MOSFET -- 1.1 Introduction -- 1.2 MOSFET Performance Parameters -- 1.3 Comparison of Existing MOSFET Architectures -- 1.4 Proposed Heavily Doped Junction-Less Double Gate MOSFET (AJ-DGMOSFET) -- 1.5 Heavily Doped JL-DG MOSFET for Biomedical Application -- 1.6 Conclusion -- References -- 2 VLSI Implementation of Vedic Multiplier -- 2.1 Introduction -- 2.2 8x8 Vedic Multiplier -- 2.3 The Architecture of 8x8 Vedic Multiplier (VM) -- 2.3.1 Compressor Architecture -- 2.4 Results and Discussion -- 2.4.1 Instance Power -- 2.4.2 Net Power -- 2.4.3 8-Bit Multiplier -- 2.4.4 16-Bit Multiplier -- 2.4.5 Applications of Multiplier -- 2.5 Conclusion -- References -- 3 Gas Leakage Detection from Drainage to Offer Safety for Sanitary Workers -- 3.1 Introduction -- 3.1.1 IOT-Based Sewer Gas Detection -- 3.1.2 Objective -- 3.1.3 Contribution of this Chapter -- 3.1.4 Outline of the Chapter -- 3.2 Related Works -- 3.2.1 Sewer Gas Leakage Detection -- 3.2.2 Crack Detection -- 3.3 Methodology -- 3.3.1 Sewer Gas Detection -- 3.3.2 Crack Detection -- 3.3.3 Experimental Setup -- 3.4 Experimental Results -- 3.5 Conclusion -- References -- 4 Machine Learning for Smart Healthcare Energy-Efficient System -- 4.1 Introduction -- 4.1.1 IoT in the Digital Age -- 4.1.2 Using IoT to Enhance Healthcare Services -- 4.1.3 Edge Computing -- 4.1.4 Machine Learning -- 4.1.5 Application in Healthcare -- 4.2 Related Works -- 4.3 Edge Computing -- 4.3.1 Architecture -- 4.3.2 Advantages of Edge Computing over Cloud Computing -- 4.3.3 Applications of Edge Computing in Healthcare -- 4.3.4 Edge Computing Advantages -- 4.3.5 Challenges -- 4.4 Smart Healthcare System -- 4.4.1 Methodology -- 4.4.2 Data Acquisition and IoT End Device.
4.4.3 IoT End Device and Backend Server -- 4.5 Conclusion and Future Directions -- References -- 5 Review of Machine Learning Techniques Used for Intrusion and Malware Detection in WSNs and IoT Devices -- 5.1 Introduction -- 5.2 Types of Attacks -- 5.3 Some Countermeasures for the Attacks -- 5.4 Machine Learning Solutions -- 5.5 Machine Learning Algorithms -- 5.6 Authentication Process Based on Machine Learning -- 5.7 Internet of Things (IoT) -- 5.8 IoT-Based Attacks -- 5.8.1 Botnets -- 5.8.2 Man-in-the-Middle -- 5.9 Information and Identity Theft -- 5.10 Social Engineering -- 5.11 Denial of Service -- 5.12 Concerns -- 5.13 Conclusion -- References -- 6 Smart Energy-Efficient Techniques for Large-Scale Process Industries -- 6.1 Pumps Operation -- 6.1.1 Parts in a Centrifugal Pump -- 6.1.2 Pump Efficiency -- 6.1.3 VFD -- 6.1.4 VFD and Pump Motor -- 6.1.5 Large HT Motors -- 6.1.6 Smart Pumps -- 6.2 Vapour Absorption Refrigeration System -- 6.2.1 Vapour Compression Refrigeration -- 6.2.2 Vapour Absorption Refrigeration -- 6.3 Heat Recovery Equipment -- 6.3.1 Case Study -- 6.3.2 Advantages of Heat Recovery -- 6.4 Lighting System -- 6.4.1 Technical Terms -- 6.4.2 Introduction -- 6.4.3 LED Lighting -- 6.4.4 Energy-Efficiency Techniques -- 6.4.5 Light Control with IoT -- 6.4.6 EU Practices -- 6.5 Air Conditioners -- 6.5.1 Technical Terms -- 6.5.2 Types of Air Conditioners -- 6.5.3 Star Rating of BEE -- 6.5.4 EU Practices -- 6.5.5 Energy-Efficiency Tips -- 6.5.6 Inverter Air Conditioners -- 6.5.7 IoT-Based Air Conditioners -- 6.6 Fans and Other Smart Appliances -- 6.6.1 BLDC Fan Motors -- 6.6.2 Star Ratings -- 6.6.3 Group Drive of Fans -- 6.6.4 Other Smart Appliances -- 6.7 Motors -- 6.7.1 Motor Efficiency -- 6.7.2 Underrated Operation -- 6.7.3 Energy-Efficient Motors -- 6.7.4 Retrofit of Standard Motors with Energy-Efficient Motors.
6.7.5 Other Salient Points -- 6.7.6 Use of Star-Delta Starter Motor -- 6.8 Energy-Efficient Transformers -- 6.8.1 IEC Recommendation -- 6.8.2 Super Conducting Transformers -- References -- 7 Link Restoration and Relay Node Placement in Partitioned Wireless Sensor Network -- 7.1 Introduction -- 7.2 Related Work -- 7.2.1 Existing Techniques -- 7.3 Proposed K-Means Clustering Algorithm -- 7.3.1 Homogenous and Heterogeneous Network Clustering Algorithms -- 7.3.2 Dynamic and Static Clustering -- 7.3.3 Flow Diagram -- 7.3.4 Objective Function -- 7.4 System Model and Assumption -- 7.4.1 Simulation Parameters -- 7.5 Results and Discussion -- 7.6 Conclusions -- References -- 8 Frequency Modulated PV Powered MLI Fed Induction Motor Drive for Water Pumping Applications -- 8.1 Introduction -- 8.2 PV Panel as Energy Source -- 8.2.1 Solar Cell -- 8.3 Multi-Level Inverter Topologies -- 8.3.1 Types of Inverters Used for Drives -- 8.3.2 Multi-Level Inverters -- 8.4 Experimental Results and Discussion -- 8.4.1 PV Powered H Bridge Inverter-Fed Drive -- 8.4.2 PV Powered DCMLI Fed Drive -- 8.5 Conclusion and Future Scope -- References -- 9 Analysis and Design of Bidirectional Circuits for Energy Storage Application -- 9.1 Introduction -- 9.2 Modes of Operation Based on Main Converters -- 9.2.1 Single-Stage Rectification -- 9.2.2 Single-Stage Inversion -- 9.2.3 Double-Stage Rectification -- 9.2.4 Double-Stage Inversion -- 9.3 Proposed Methodology for Three-Phase System -- 9.3.1 Control Block of Overall System -- 9.3.2 Proposed Carrier-Based PWM Strategy -- 9.3.3 Experiment Results -- 9.4 Conclusion -- References -- 10 Low-Power IOT-Enabled Energy Systems -- 10.1 Overview -- 10.1.1 Conceptions -- 10.1.2 Motivation -- 10.1.3 Methodology -- 10.2 Empowering Tools -- 10.2.1 Sensing Components -- 10.2.2 Movers -- 10.2.3 Telecommunication Technology.
10.2.4 Internet of Things Information and Evaluation -- 10.3 Internet of Things within Power Region -- 10.3.1 Internet of Things along with Vitality Production -- 10.3.2 Smart Metropolises -- 10.3.3 Intelligent Lattice Network -- 10.3.4 Smart Buildings Structures -- 10.3.5 Powerful Usage of Vitality in Production -- 10.3.6 Insightful Transport -- 10.4 Difficulties Relating Internet of Things -- 10.4.1 Vitality Ingestion -- 10.4.2 Synchronization via Internet of Things through Sub-Units -- 10.4.3 Client Confidentiality -- 10.4.4 Safety Challenges -- 10.4.5 IoT Standardization and Architectural Concept -- 10.5 Upcoming Developments -- 10.5.1 IoT and Block Chain -- 10.5.2 Artificial Intelligence and IoT -- 10.5.3 Green IoT -- 10.6 Conclusion -- References -- 11 Efficient Renewable Energy Systems -- Introduction -- 11.1 Renewable-Based Available Technologies -- 11.1.1 Wind Power -- 11.1.2 Solar Power -- 11.1.3 Tidal Energy -- 11.1.4 Battery Storage System -- 11.1.5 Solid Oxide Energy Units for Enhancing Power Life -- 11.2 Adaptability Frameworks -- 11.2.1 Distributed Energy Resources (DER) -- 11.2.2 New Age Grid Connection -- 11.3 Conclusion -- References -- 12 Efficient Renewable Energy Systems -- 12.1 Introduction -- 12.1.1 World Energy Scenario -- 12.2 Sources of Energy: Classification -- 12.3 Renewable Energy Systems -- 12.3.1 Solar Energy -- 12.3.2 Wind -- 12.3.3 Geothermal -- 12.3.4 Biomass -- 12.3.5 Ocean -- 12.3.6 Hydrogen -- 12.4 Solar Energy -- 12.5 Wind Energy -- 12.6 Geothermal Energy -- 12.7 Biomass -- 12.7.1 Forms of Biomass -- 12.8 Ocean Power -- 12.9 Hydrogen -- 12.10 Hydro Power -- 12.11 Conclusion -- References -- 13 Agriculture-IoT-Based Sprinkler System for Water and Fertilizer Conservation and Management -- 13.1 Introduction -- 13.1.1 Novelty of the Work -- 13.1.2 Benefit to Society -- 13.2 Development of the Proposed System.
13.3 System Description -- 13.3.1 Study of the Crop Under Experiment -- 13.3.2 Hardware of the System -- 13.3.3 Software of the System -- 13.4 Layers of the System Architecture -- 13.4.1 Application Layer -- 13.4.2 Cloud Layer -- 13.4.3 Network Layer -- 13.4.4 Physical Layer -- 13.5 Calibration -- 13.6 Layout of the Sprinkler System -- 13.7 Testing -- 13.8 Results and Discussion -- 13.9 Conclusion -- References -- 14 A Behaviour-Based Authentication to Internet of Things Using Machine Learning -- 14.1 Introduction -- 14.2 Basics of Internet of Things (IoT) -- 14.2.1 The IoT Reference Model -- 14.2.2 Working of IoT -- 14.2.3 Utilization of Internet of Things (IoT) -- 14.3 Authentication in IoT -- 14.3.1 Methods of Authentication -- 14.4 User Authentication Based on Behavioral-Biometric -- 14.4.1 Machine Learning -- 14.4.2 Machine Learning Algorithms -- 14.5 Threats and Challenges in the Current Security Solution for IoT -- 14.6 Proposed Methodology -- 14.6.1 Collection of Gait Dataset -- 14.6.2 Gait Data Preprocessing -- 14.6.3 Reduction in Data Size -- 14.6.4 Gaits Feature -- 14.6.5 Classification -- 14.7 Conclusion and Future Work -- References -- 15 A Fuzzy Goal Programming Model for Quality Monitoring of Fruits during Shipment Overseas -- 15.1 Introduction -- 15.2 Proposed System -- 15.2.1 Problem Statement -- 15.2.2 Overview -- 15.2.3 System Components -- 15.3 Work Process -- 15.3.1 System Hardware -- 15.3.2 Connections and Circuitry -- 15.4 Optimization Framework -- 15.4.1 Fuzzy Goal Description -- 15.4.2 Characterizing Fuzzy Membership Function -- 15.4.3 Construction of FGP Model -- 15.4.4 Definition of Variables and Parameters -- 15.4.5 Fuzzy Goal Description -- 15.5 Creation of Database and Website -- 15.5.1 Hosting PHP Application and Creation of MySQL Database -- 15.5.2 Creation of API (Application Programming Interfaces) Key.
15.6 Libraries Used and Code Snipped.
Record Nr. UNINA-9910830773703321
Hoboken, NJ : , : Wiley : , : Scrivener Publishing, , [2021]
Materiale a stampa
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Electric vehicle design : design, simulation and applications / / edited by Krishan Arora, Suman Lata Tripathi and Himanshu Sharma
Electric vehicle design : design, simulation and applications / / edited by Krishan Arora, Suman Lata Tripathi and Himanshu Sharma
Edizione [1st ed.]
Pubbl/distr/stampa Hoboken, NJ : , : John Wiley & Sons, Inc.
Descrizione fisica 1 online resource (358 pages)
Disciplina 629.22/93
Altri autori (Persone) TripathiSuman Lata
SharmaHimanshu
Soggetto topico Electric vehicles - Design and construction
ISBN 9781394205080
1394205082
9781394205097
1394205090
9781394205073
1394205074
9781394204373
139420437X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Development of Braking Systems in Fuel Cell Electric Vehicles -- 1.1 Introduction -- 1.2 Historical Background of Fuel Cell -- 1.3 ADVISOR -- 1.4 Why Hydrogen is Preferred -- 1.5 What is a Fuel Cell? -- 1.6 Working of Fuel Cells -- 1.7 Types of Fuel Cells -- 1.7.1 Direct Methanol Fuel Cell (DMFC) -- 1.7.2 Phosphoric Acid Fuel Cell (PAFC) -- 1.7.3 Alkaline Fuel Cell (AFC) -- 1.7.4 Solid Oxide Fuel Cell (SOFC) -- 1.7.5 Molten Carbonate Fuel Cell (MCFC) -- 1.8 Block Diagram of Vehicle on MATLAB/Simulink -- 1.9 Braking System in Vehicle -- 1.10 Regenerative Braking System -- 1.11 Anti-Lock Braking System (ABS) -- 1.11.1 Component of ABS -- 1.11.1.1 Wheel Speed Sensor -- 1.11.1.2 Valves -- 1.11.1.3 Pumps -- 1.11.1.4 Electronic Control Unit -- 1.11.2 Types of the ABS Model -- 1.11.3 Anti-Lock Braking System Plot -- 1.12 Conclusion -- References -- Chapter 2 Design and Applications of Fuel Cells -- 2.1 Introduction -- 2.2 Types of Electric Vehicles -- 2.2.1 Battery Electric Vehicles (BEVs) -- 2.2.2 Hybrid Electric Vehicles (HEVs) -- 2.2.3 Plug-In Hybrid Electric Vehicles (PHEVs) -- 2.2.4 Fuel Cell Electric Vehicles (FCEVs) -- 2.3 Design Equations of Fuel Cells -- 2.3.1 Nernst Equation -- 2.3.2 Ohm's Law -- 2.3.3 Power Output -- 2.3.4 Efficiency Equation -- 2.3.5 Kinetic Current Density Equation -- 2.3.6 Over-Potential Equation -- 2.3.7 Heat Generation Equation -- 2.4 Designing of Fuel Cells -- 2.5 Types of Fuel Cells -- 2.6 Solid Oxide FCs (SOFCs) -- 2.6.1 Working of SOFCs -- 2.6.2 Advantages of SOFCs -- 2.6.3 Disadvantages of SOFCs -- 2.6.4 Applications of SOFCs -- 2.7 Alkaline Fuel Cells (AFCs) -- 2.7.1 Working of AFCs -- 2.7.2 Advantages of AFCs -- 2.7.3 Disadvantages of AFCs -- 2.7.4 Applications of AFCs -- 2.8 Molten Carbonate Fuel Cell (MCFC) -- 2.8.1 Working of MCFC.
2.8.2 Advantages of MCFCs -- 2.8.3 Disadvantages of MCFCs -- 2.8.4 Applications of MCFCs -- 2.9 Phosphoric Acid Fuel Cells (PAFCs) -- 2.9.1 Working of PAFCs -- 2.9.2 Advantages of PAFCs -- 2.9.3 Disadvantages of PAFCs -- 2.9.4 Applications of PAFCs -- 2.10 Polymer Electrolyte Membrane Fuel Cell (PEMFC) -- 2.10.1 Working of PEMFC -- 2.10.2 Advantages of PEMFCs -- 2.10.3 Advantages of PEMFCs -- 2.10.4 Applications of PEMFCs -- 2.11 Direct Methanol Fuel Cells (DMFCs) -- 2.11.1 Working of DFMC -- 2.11.2 Advantages of DMFCs -- 2.11.3 Disadvantages of DMFCs -- 2.11.4 Applications of DMFCs -- 2.12 Parameters Affecting the Performance of FCs -- References -- Chapter 3 Smart Energy Management and Monitoring System for Electric Vehicles with IoT Integration -- 3.1 Introduction -- 3.2 The Control of Electric Vehicles Using IoT -- 3.2.1 Battery Management System -- 3.2.2 Safe and Intelligent Driving -- 3.2.3 System for Fault Alert and Preventative Maintenance -- 3.2.4 Data from Telemetry -- 3.2.4.1 Battery Usage Information -- 3.2.4.2 Report on Charging -- 3.2.4.3 Notify About Nearby Charging Stations -- 3.2.4.4 Data on Driver Behavior -- 3.3 IoT Management Issues with Electric Vehicles -- 3.3.1 Internet Safety -- 3.3.2 Higher Price -- 3.3.3 Considering the Challenges and Advantages -- 3.4 Monitoring and Management Benefits of IoT -- 3.4.1 IoT and Battery Management Systems -- 3.4.2 IoT for Safe and Intelligent Driving -- 3.4.3 Theft Prevention -- 3.4.4 Detection of Falling or Crashes -- 3.4.5 Battery Leasing Made Simple -- 3.5 Predictive Maintenance System with Fault Alerts -- 3.6 IoT Management and Monitoring Issues with Electric Vehicles -- 3.6.1 Threat from Cyber Attacks -- 3.6.2 Electric Car Prices are Quite High -- 3.6.3 Technological Difficulty -- 3.6.4 Connectivity and Reliance on Power -- 3.6.5 Battery Management and Monitoring System.
3.6.6 Prototype of a Battery Charge Control and Monitoring System -- 3.6.7 Scenario for the Battery Monitoring and Management System -- 3.7 Microcontroller -- 3.7.1 DC Current Sensor -- 3.7.2 Fuel Gauge Module for Li-Lon Batteries -- 3.8 IoT-Based Systems for Battery Management and Monitoring -- 3.9 Design of Battery Charge Control and Monitoring System -- 3.10 Results and Discussion -- 3.11 Conclusions -- 3.12 Future Scope of IoT in Electric Vehicles -- References -- Chapter 4 A Review of Electric Vehicles: Technologies and Challenges -- 4.1 Introduction -- 4.2 Electric Motors -- 4.2.1 DC Series Motor -- 4.2.2 Brushless DC Motors -- 4.2.2.1 Out-Runner-Type BLDC Motor -- 4.2.2.2 In-Runner-Type BLDC Motor -- 4.2.3 Permanent Magnet Synchronous Motor -- 4.2.4 Three-Phase AC Induction Motors -- 4.2.5 Switched Reluctance Motors -- 4.3 Power Electronic Converters -- 4.3.1 Bi-Directional DC-DC Converter -- 4.3.1.1 Non-Isolated Converters -- 4.3.1.2 Isolated Converters -- 4.4 Battery in Electric Vehicles -- 4.4.1 Types of Battery in Electric Vehicles -- 4.4.2 Traditional Battery Charging Approach -- 4.4.2.1 Constant Current (CC) Charging Approach -- 4.4.2.2 Constant Voltage (CV) Charging Approach -- 4.4.2.3 Constant Current-Constant Voltage (CC-CV) Charging Approach -- 4.4.2.4 Multi-Stage Constant Current (MCC) Approach -- 4.5 Conclusion -- References -- Chapter 5 Electric Vehicle and Design Using MATLAB -- List of Abbreviations -- 5.1 Introduction -- 5.2 Motivation -- 5.2.1 History of EVs -- 5.3 Basic Fundamentals of EVs -- 5.4 Why Electric Vehicles? -- 5.5 Comparison Between ICV and EV -- 5.6 Classification of EVs -- 5.7 Design and Structure of EV -- 5.7.1 HEV -- 5.7.2 FCEV -- 5.7.3 PHEV -- 5.7.4 Basic Design of EV -- 5.8 Mathematical Model of an Electric Vehicle -- 5.9 Control Strategy of EVs -- 5.10 Design Methodology for Electric Vehicles (EVs).
5.11 Latest Emerging Technology in EV -- 5.12 Performance Valuation of BLDC Motor and Induction Motor for Electric Vehicle Propulsion Application -- 5.12.1 A Mathematical Model for a Brushless DC (BLDC) Motor-Driven Electric Vehicle -- 5.12.2 Induction Motor -- 5.12.3 Mathematical Model for an Induction Motor-Driven Electric Vehicle -- 5.12.4 Induction Motor Design with Their Specifications -- 5.13 Conclusion -- References -- Chapter 6 Model Order Reduction of Battery for Smart Battery Management System -- 6.1 Introduction -- 6.2 Problem Formulation -- 6.3 Modeling of Battery -- 6.4 Methodology for Model Order Reduction -- 6.5 Result and Discussion -- 6.6 Conclusion -- Appendix -- References -- Chapter 7 Power Electronic Converters for Electric Vehicle Application -- 7.1 Introduction -- 7.2 Types of Electrical Vehicle and Role of Power Electronic Converter -- 7.2.1 Battery Electric Vehicles (BEVs) -- 7.2.1.1 Power Electronics in BEVs -- 7.2.2 Plug-In Hybrid Electric Vehicles (Plug-In HEVs) -- 7.2.2.1 Power Electronics in Plug-In Hybrid Electric Vehicles (Plug-In HEV) -- 7.2.3 Hybrid Electric Vehicles (HEVs) -- 7.2.3.1 Series Hybrid Electric Vehicles (SHEVs) -- 7.2.3.2 Parallel Hybrid Electric Vehicles (PHEVs) -- 7.2.3.3 Series-Parallel Hybrid Electric Vehicles (SPHEVs) -- 7.2.3.4 Power Electronics in Hybrid Electric Vehicles (HEVs) -- 7.2.4 Fuel Cell Electric Vehicles (FCEVs) -- 7.2.4.1 Power Electronics in Fuel Cell Electric Vehicles (FCEVs) -- 7.2.5 Solar Cell Electric Vehicles (SCEVs) -- 7.2.5.1 Power Electronics in Solar Cell Electric Vehicles (SCEVs) -- 7.3 Recent Development in Power Electronic Converter -- 7.4 Power Electronic Converters in Electric, Hybrid, and Fuel Cell Vehicles -- 7.4.1 Power Electronic Converters in EVs -- 7.4.2 Categorization of Power Electronic Converters -- 7.5 Challenges in Power Electronic Vehicular System.
7.5.1 Efficiency -- 7.5.2 Longevity -- 7.5.3 Performance of EV -- 7.5.4 Luxurious Features -- 7.5.5 Safety -- 7.5.6 Overall Cost -- 7.5.7 Noise -- 7.6 Conclusion -- References -- Chapter 8 Integrating Electric Vehicles Into Smart Grids Through Data Analytics: Challenges and Opportunities -- 8.1 Introduction -- 8.2 Smart Grid and Electric Vehicle -- 8.3 Impact of Electric Vehicle-Based Data Analytics for Smart Grids -- 8.4 Importance of Resource Availability, Price, and Load for EV -- 8.5 Electric-Tariff Design Based on Impact of Electric Vehicle Usage -- 8.6 Data Analytics for Electric Vehicles -- 8.7 Machine Learning for EV Analytics -- 8.8 What are the Different ML Algorithms Used by Authors for EV Analytics? -- 8.9 Importance of Data Analysis in the EV Industry Using an Open Source Data -- 8.10 Description of the Dataset -- 8.11 Features and Factors That Influence the Prices of EVs -- 8.12 Price Prediction of EVs -- 8.13 Random Forest-Based Price Prediction of Electric Vehicles -- 8.14 Machine Learning Model -- 8.15 Electric Vehicle Usage in India -- 8.16 The Challenges of Adopting EV in India -- 8.17 How to Increase Renewable Energy in India to Meet EV Demand -- Conclusion -- References -- Chapter 9 Hybrid Electrical Vehicle Designs -- 9.1 Introduction -- 9.2 Plug-In Hybrid Electric Vehicles -- 9.3 Classification of HEVs -- 9.3.1 Series Hybrid -- 9.3.2 Parallel Hybrid -- 9.3.3 Series-Parallel Hybrid -- 9.4 Fuel Cell Electric Vehicles (FCEVs) -- 9.4.1 Micro-Hybrids -- 9.4.2 Mild Hybrids -- 9.4.3 Full Hybrids -- 9.5 Hybrid Electric Vehicle System Design and Analysis -- 9.6 Control Strategy in Series Hybrid Drivetrain Configuration -- 9.6.1 Modes of Operation -- 9.6.2 Max. SoC-of-PPS Control Strategy -- 9.7 Design of Fuel Cell Electric Vehicles with Fuel Economy -- 9.7.1 Traction Mode -- 9.8 Conclusion -- References.
Chapter 10 EV Battery Charging System.
Record Nr. UNINA-9910877989303321
Hoboken, NJ : , : John Wiley & Sons, Inc.
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Electrical and electronic devices, circuits, and materials : technological challenges and solutions / / editors, Suman Lata Tripathi, Parvej Ahmad Alvi, Umashankar Subramaniam
Electrical and electronic devices, circuits, and materials : technological challenges and solutions / / editors, Suman Lata Tripathi, Parvej Ahmad Alvi, Umashankar Subramaniam
Pubbl/distr/stampa Hoboken, NJ : , : Wiley : , : Scrivener Publishing, , [2021]
Descrizione fisica 1 online resource (614 pages)
Disciplina 621.3815
Soggetto topico Electronic apparatus and appliances
Soggetto genere / forma Electronic books.
ISBN 1-119-75510-7
1-119-75509-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Part I: DESIGN AND ANALYSIS -- 1 Strain Engineering in Modern Field Effect Transistors -- 1.1 Introduction -- 1.2 Theory of Strain Technology -- 1.2.1 Stress and Strain -- 1.2.2 Stress Matrix for Biaxial and Uniaxial Stress -- 1.2.3 Impact of Strain on MOSFET Parameters -- 1.3 Simulation Studies in Strain Technology -- 1.4 Experimental Studies on Strain Technology -- 1.5 Summary and Future Scope -- Future Scope -- Acknowledgement -- References -- 2 Design and Optimization of Heterostructure Double Gate Tunneling Field Effect Transistor for Ultra Low Power Circuit and System -- 2.1 Introduction -- 2.2 Fundamental of Device Physics -- 2.2.1 Basic Working Principles of TFET -- 2.2.2 Kane's Model -- 2.3 Analysis Approach and Device Parameters -- 2.4 Switching Behavior of TFET -- 2.5 Results and Discussion -- 2.6 Conclusion -- Acknowledgement -- References -- 3 Polymer Electrolytes: Development and Supercapacitor Application -- 3.1 Introduction -- 3.1.1 The Basic Principle and Types of Supercapacitors -- 3.1.2 Key Characteristics of the Electrolyte -- 3.1.3 Polymer Electrolytes and Types -- 3.1.4 Modification Strategies for Polymer Electrolytes -- 3.2 Preparation and Characterization Techniques -- 3.3 Latest Developments -- 3.4 Summary -- References -- 4 Tunable RF/Microwave Filter with Fractal DGS -- Tunable RF/Microwave Filter with Fractal DGS -- 4.1 Introduction -- 4.2 Literature Review -- 4.2.1 Planar Reconfigurable Filters -- 4.3 Proposed Work -- 4.3.1 Design of Hairpin Bandpass Filter -- 4.3.2 Design of Hairpin Bandpass Filter with Fractal DGS -- 4.3.3 Design of Tunable Hairpin Bandpass Filter with Fractal DGS -- 4.4 Conclusion -- Acknowledgement -- References.
5 GaN High Electron Mobility Transistor Device Technology for RF and High-Power Applications -- 5.1 Introduction -- 5.2 HEMT Structures -- 5.2.1 GaAs-Based HEMTs -- 5.2.2 InP-Based HEMTs -- 5.2.3 GaN-Based HEMTs -- 5.3 Polarization Impact and Creation of 2DEG in GaN HEMT -- 5.3.1 Polarization Effect -- 5.3.2 Formation of 2DEG -- 5.4 GaN-Based HEMT Performance Affecting Factors -- 5.4.1 Surface Passivation -- 5.4.2 Parasitic Effects -- 5.4.3 Field Plate Engineering Technique -- 5.4.4 Impact of Barrier Layer -- 5.5 Conclusion -- References -- 6 Design and Analyses of a Food Protein Sensing System Based on Memristive Properties -- 6.1 Introduction -- 6.2 Background -- 6.2.1 Principle of a Memristor -- 6.2.2 Bio-Memristors -- 6.2.3 Applications of Memristors -- 6.3 Motivation -- 6.4 Experimental Set-Up -- 6.5 Experimental Methodology and Preliminary Validation -- 6.5.1 Experimental Methodology -- 6.5.2 Preliminary Validation -- 6.6 Sensitivity Parameters -- 6.6.1 Resistance-Based Sensitivity (Sr) -- 6.6.2 Point Slope-Based Sensitivity (Sm) -- 6.6.3 Hysteresis-Line Slope Sensitivity -- 6.7 Results and Discussion -- 6.7.1 Category I: Egg Albumin and Milk -- 6.7.2 Category II: Protein Blend -- 6.8 Conclusions and Prospects -- References -- 7 Design of Low-Power DRAM Cell Using Advanced FET Architectures -- 7.1 Introduction -- 7.2 1T-DRAM (MOS) -- 7.3 1T-DRAM (CNT-FET) -- 7.4 1T-DRAM (FinFET) -- 7.5 1-T DRAM (TFET) -- 7.6 Conclusion -- References -- 8 Application of Microwave Radiation in Determination of Quality Sensing of Agricultural Products -- 8.1 Microwave Heating and its Applications to Agricultural Products -- 8.1.1 Principle of Microwave Heating -- 8.1.2 Moisture Sensing -- 8.1.3 Promoting Germination -- 8.1.4 Food Processing -- 8.1.5 Weeds, Insects and Pests Control -- 8.1.6 Product Conditioning -- 8.1.7 Microwave Drying.
8.1.8 Quality Sensing in Fruits and Vegetables -- 8.2 Measurement Techniques -- 8.2.1 Open-Ended Coaxial Probe - Network Analyzer Technique -- 8.2.2 Network Analyzer -- 8.3 Dielectric Spectroscopy of Agricultural Products at Different Temperatures -- 8.4 Correlation of Dielectric Properties with Nutrients -- 8.5 Conclusion -- References -- 9 Solar Cell -- Introduction -- 9.1 History of Solar Cell -- 9.2 Constructional Features of Solar Cell [2] -- 9.3 Criteria for Materials to Be Used in Manufacturing of Solar Cell -- 9.4 Types of Solar Cells [5] -- 9.5 Process of Making Crystals for Solar Cell Manufacturing [2] -- 9.6 Glass -- 9.7 Cell Combinations -- 9.7.1 Series Combination of Solar Cells [4] -- 9.7.2 Parallel Combination of Solar Cells [4] -- 9.7.3 Series-Parallel Combination of Solar Cells [4] -- 9.8 Solar Panels -- 9.9 Working of Solar Cell [3] -- 9.10 Solar Cell Efficiency -- 9.11 Uses/Applications of Solar Cells -- Conclusion -- References -- 10 Fabrication of Copper Indium Gallium Diselenide (Cu(In,Ga)Se2) Thin Film Solar Cell -- 10.1 Introduction -- 10.2 Device Structure of CIGS Thin Film Solar Cell -- 10.3 Fabrication and Characterization of CIGS Thin Film Solar Cell -- 10.3.1 Effect of Thermally Evaporated CdS Film Thickness on the Operation of CIGS Solar Cell -- 10.3.2 Effect of Heat Soaks on CIGS/CdS Hetero-Junction -- 10.3.3 Effect of Flash Evaporated CdS Film Thickness on the Performance of CIGS Solar Cell -- 10.3.4 Effect of i-ZnO Film Thickness on the Performance of CIGS Solar Cell -- 10.4 Conclusion -- References -- 11 Parameter Estimation of Solar Cells: A Multi-Objective Approach -- 11.1 Introduction -- 11.2 Problem Statement -- 11.2.1 SDM -- 11.2.2 DDM -- 11.3 Methodology -- 11.4 Results and Discussions -- 11.4.1 Results for the Single-Diode Model -- 11.4.2 Results for Double-Diode Model -- 11.5 Conclusions -- References.
12 An IoT-Based Smart Monitoring Scheme for Solar PV Applications -- 12.1 Introduction -- 12.2 Solar PV Systems -- 12.2.1 Solar Photovoltaic (PV) Systems -- 12.2.2 Concentrates Solar Power (CSP) -- 12.2.3 Solar Water Heater Systems -- 12.2.4 Passive Solar Design -- 12.2.5 Solar Microgrid System -- 12.2.6 Battery -- 12.2.7 MPPT -- 12.2.8 Inverters & -- Other Electronic Equipment -- 12.2.9 Charge Controller -- 12.2.10 Additional Systems Equipment -- 12.3 IoT -- 12.3.1 Artificial Intelligence (AI) and Machine Learning -- 12.3.2 Big Data and Cloud Computing -- 12.3.3 Smart Sensors -- 12.3.4 Additional Devices for Control and Communication -- 12.3.5 Renewable Energy and IoT in Energy Sector -- 12.3.6 Application of IoT -- 12.4 Remote Monitoring Methods of Solar PV System -- 12.4.1 Wireless Monitoring -- 12.4.2 Physical/Wired Monitoring -- 12.4.3 SCADA Monitoring -- 12.4.4 Monitoring Using Cloud Computing -- 12.4.5 Monitoring Using IOT -- 12.5 Challenges and Issues of Implementation of IoT on Renewable Energy Resources -- 12.5.1 Challenges -- 12.5.2 Solutions -- 12.6 Conclusion -- References -- 13 Design of Low-Power Energy Harvesting System for Biomedical Devices -- 13.1 Introduction -- 13.2 Investigation on Topologies of DC-DC Converter -- 13.2.1 Hybrid Source Architecture Based on Synchronous Boost Converter -- 13.2.2 Hybrid Source Architecture Using Single-Inductor Dual-Input Single-Output Converter -- 13.2.3 Hybrid Source Architecture Employing a Multi-Input DC Chopper -- 13.3 Hardware Results -- 13.4 Conclusion -- References -- 14 Performance Analysis of Some New Hybrid Metaheuristic Algorithms for HighDimensional Optimization Problems -- 14.1 Introduction -- 14.2 An Overview of Proposed Hybrid Methodologies -- 14.3 Experimental Results and Discussion -- 14.4 Conclusions -- References.
15 Investigation of Structural, Optical and Wettability Properties of Cadmium Sulphide Thin Films Synthesized by Environment Friendly SILAR Technique -- 15.1 Introduction -- 15.2 Experimental Details -- 15.3 Results and Discussion -- 15.3.1 Film Formation Mechanism -- 15.3.2 Thickness Measurement -- 15.3.3 Structural Studies -- 15.3.4 Raman Spectroscopy -- 15.3.5 Scanning Electron Microscopy -- 15.3.6 Optical Studies -- 15.3.7 Wettability Studies -- 15.4 Conclusion -- 15.5 Acknowledgement -- References -- Part II: DESIGN, IMPLEMENTATION ANDAPPLICATIONS -- 16 Solar Photovoltaic Cells -- 16.1 Introduction -- 16.2 Need for Solar Cells -- 16.3 Structure of Solar Cell -- 16.4 Solar Cell Classification -- 16.4.1 First-Generation Solar Cells -- 16.4.2 Second-Generation Solar Cells -- 16.4.3 Third-Generation Solar Cells -- 16.5 Solar PV Cells -- 16.6 Solar Cell Working -- 16.7 Mathematical Modelling of Solar Cell -- 16.8 Solar Cell Connection Methods -- 16.9 Types of Solar PV System -- 16.10 Conclusion -- References -- 17 An Intelligent Computing Technique for Parameter Extraction of Different Photovoltaic (PV) Models -- 17.1 Introduction -- 17.2 Problem Formulation -- 17.2.1 Single-Diode Model -- 17.2.2 Double-Diode Model -- 17.2.3 Three-Diode Model -- 17.3 Proposed Optimization Technique -- 17.3.1 Various Phases of Optimization of Harris Hawks -- 17.4 Results and Discussions -- 17.5 Conclusions -- References -- 18 Experimental Investigation on Wi-Fi Signal Loss by Scattering Property of Duranta Plant Leaves -- 18.1 Introduction -- 18.1.1 Duranta Golden Plant -- 18.1.2 Foliage Loss -- 18.2 Measurement and Calculation -- 18.2.1 Scattering Feasibility -- 18.2.2 Comparison with Tree Shadowing Effect -- 18.3 Result and Discussion -- 18.4 Conclusions -- References -- 19 Multi-Quantum Well-Based Solar Cell -- 19.1 Introduction.
19.2 Theoretical Aspects of Solar Cell.
Record Nr. UNINA-9910555076403321
Hoboken, NJ : , : Wiley : , : Scrivener Publishing, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Electrical and electronic devices, circuits, and materials : technological challenges and solutions / / editors, Suman Lata Tripathi, Parvej Ahmad Alvi, Umashankar Subramaniam
Electrical and electronic devices, circuits, and materials : technological challenges and solutions / / editors, Suman Lata Tripathi, Parvej Ahmad Alvi, Umashankar Subramaniam
Pubbl/distr/stampa Hoboken, NJ : , : Wiley : , : Scrivener Publishing, , [2021]
Descrizione fisica 1 online resource (614 pages)
Disciplina 621.3815
Soggetto topico Electronic apparatus and appliances
ISBN 1-119-75510-7
1-119-75509-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Part I: DESIGN AND ANALYSIS -- 1 Strain Engineering in Modern Field Effect Transistors -- 1.1 Introduction -- 1.2 Theory of Strain Technology -- 1.2.1 Stress and Strain -- 1.2.2 Stress Matrix for Biaxial and Uniaxial Stress -- 1.2.3 Impact of Strain on MOSFET Parameters -- 1.3 Simulation Studies in Strain Technology -- 1.4 Experimental Studies on Strain Technology -- 1.5 Summary and Future Scope -- Future Scope -- Acknowledgement -- References -- 2 Design and Optimization of Heterostructure Double Gate Tunneling Field Effect Transistor for Ultra Low Power Circuit and System -- 2.1 Introduction -- 2.2 Fundamental of Device Physics -- 2.2.1 Basic Working Principles of TFET -- 2.2.2 Kane's Model -- 2.3 Analysis Approach and Device Parameters -- 2.4 Switching Behavior of TFET -- 2.5 Results and Discussion -- 2.6 Conclusion -- Acknowledgement -- References -- 3 Polymer Electrolytes: Development and Supercapacitor Application -- 3.1 Introduction -- 3.1.1 The Basic Principle and Types of Supercapacitors -- 3.1.2 Key Characteristics of the Electrolyte -- 3.1.3 Polymer Electrolytes and Types -- 3.1.4 Modification Strategies for Polymer Electrolytes -- 3.2 Preparation and Characterization Techniques -- 3.3 Latest Developments -- 3.4 Summary -- References -- 4 Tunable RF/Microwave Filter with Fractal DGS -- Tunable RF/Microwave Filter with Fractal DGS -- 4.1 Introduction -- 4.2 Literature Review -- 4.2.1 Planar Reconfigurable Filters -- 4.3 Proposed Work -- 4.3.1 Design of Hairpin Bandpass Filter -- 4.3.2 Design of Hairpin Bandpass Filter with Fractal DGS -- 4.3.3 Design of Tunable Hairpin Bandpass Filter with Fractal DGS -- 4.4 Conclusion -- Acknowledgement -- References.
5 GaN High Electron Mobility Transistor Device Technology for RF and High-Power Applications -- 5.1 Introduction -- 5.2 HEMT Structures -- 5.2.1 GaAs-Based HEMTs -- 5.2.2 InP-Based HEMTs -- 5.2.3 GaN-Based HEMTs -- 5.3 Polarization Impact and Creation of 2DEG in GaN HEMT -- 5.3.1 Polarization Effect -- 5.3.2 Formation of 2DEG -- 5.4 GaN-Based HEMT Performance Affecting Factors -- 5.4.1 Surface Passivation -- 5.4.2 Parasitic Effects -- 5.4.3 Field Plate Engineering Technique -- 5.4.4 Impact of Barrier Layer -- 5.5 Conclusion -- References -- 6 Design and Analyses of a Food Protein Sensing System Based on Memristive Properties -- 6.1 Introduction -- 6.2 Background -- 6.2.1 Principle of a Memristor -- 6.2.2 Bio-Memristors -- 6.2.3 Applications of Memristors -- 6.3 Motivation -- 6.4 Experimental Set-Up -- 6.5 Experimental Methodology and Preliminary Validation -- 6.5.1 Experimental Methodology -- 6.5.2 Preliminary Validation -- 6.6 Sensitivity Parameters -- 6.6.1 Resistance-Based Sensitivity (Sr) -- 6.6.2 Point Slope-Based Sensitivity (Sm) -- 6.6.3 Hysteresis-Line Slope Sensitivity -- 6.7 Results and Discussion -- 6.7.1 Category I: Egg Albumin and Milk -- 6.7.2 Category II: Protein Blend -- 6.8 Conclusions and Prospects -- References -- 7 Design of Low-Power DRAM Cell Using Advanced FET Architectures -- 7.1 Introduction -- 7.2 1T-DRAM (MOS) -- 7.3 1T-DRAM (CNT-FET) -- 7.4 1T-DRAM (FinFET) -- 7.5 1-T DRAM (TFET) -- 7.6 Conclusion -- References -- 8 Application of Microwave Radiation in Determination of Quality Sensing of Agricultural Products -- 8.1 Microwave Heating and its Applications to Agricultural Products -- 8.1.1 Principle of Microwave Heating -- 8.1.2 Moisture Sensing -- 8.1.3 Promoting Germination -- 8.1.4 Food Processing -- 8.1.5 Weeds, Insects and Pests Control -- 8.1.6 Product Conditioning -- 8.1.7 Microwave Drying.
8.1.8 Quality Sensing in Fruits and Vegetables -- 8.2 Measurement Techniques -- 8.2.1 Open-Ended Coaxial Probe - Network Analyzer Technique -- 8.2.2 Network Analyzer -- 8.3 Dielectric Spectroscopy of Agricultural Products at Different Temperatures -- 8.4 Correlation of Dielectric Properties with Nutrients -- 8.5 Conclusion -- References -- 9 Solar Cell -- Introduction -- 9.1 History of Solar Cell -- 9.2 Constructional Features of Solar Cell [2] -- 9.3 Criteria for Materials to Be Used in Manufacturing of Solar Cell -- 9.4 Types of Solar Cells [5] -- 9.5 Process of Making Crystals for Solar Cell Manufacturing [2] -- 9.6 Glass -- 9.7 Cell Combinations -- 9.7.1 Series Combination of Solar Cells [4] -- 9.7.2 Parallel Combination of Solar Cells [4] -- 9.7.3 Series-Parallel Combination of Solar Cells [4] -- 9.8 Solar Panels -- 9.9 Working of Solar Cell [3] -- 9.10 Solar Cell Efficiency -- 9.11 Uses/Applications of Solar Cells -- Conclusion -- References -- 10 Fabrication of Copper Indium Gallium Diselenide (Cu(In,Ga)Se2) Thin Film Solar Cell -- 10.1 Introduction -- 10.2 Device Structure of CIGS Thin Film Solar Cell -- 10.3 Fabrication and Characterization of CIGS Thin Film Solar Cell -- 10.3.1 Effect of Thermally Evaporated CdS Film Thickness on the Operation of CIGS Solar Cell -- 10.3.2 Effect of Heat Soaks on CIGS/CdS Hetero-Junction -- 10.3.3 Effect of Flash Evaporated CdS Film Thickness on the Performance of CIGS Solar Cell -- 10.3.4 Effect of i-ZnO Film Thickness on the Performance of CIGS Solar Cell -- 10.4 Conclusion -- References -- 11 Parameter Estimation of Solar Cells: A Multi-Objective Approach -- 11.1 Introduction -- 11.2 Problem Statement -- 11.2.1 SDM -- 11.2.2 DDM -- 11.3 Methodology -- 11.4 Results and Discussions -- 11.4.1 Results for the Single-Diode Model -- 11.4.2 Results for Double-Diode Model -- 11.5 Conclusions -- References.
12 An IoT-Based Smart Monitoring Scheme for Solar PV Applications -- 12.1 Introduction -- 12.2 Solar PV Systems -- 12.2.1 Solar Photovoltaic (PV) Systems -- 12.2.2 Concentrates Solar Power (CSP) -- 12.2.3 Solar Water Heater Systems -- 12.2.4 Passive Solar Design -- 12.2.5 Solar Microgrid System -- 12.2.6 Battery -- 12.2.7 MPPT -- 12.2.8 Inverters & -- Other Electronic Equipment -- 12.2.9 Charge Controller -- 12.2.10 Additional Systems Equipment -- 12.3 IoT -- 12.3.1 Artificial Intelligence (AI) and Machine Learning -- 12.3.2 Big Data and Cloud Computing -- 12.3.3 Smart Sensors -- 12.3.4 Additional Devices for Control and Communication -- 12.3.5 Renewable Energy and IoT in Energy Sector -- 12.3.6 Application of IoT -- 12.4 Remote Monitoring Methods of Solar PV System -- 12.4.1 Wireless Monitoring -- 12.4.2 Physical/Wired Monitoring -- 12.4.3 SCADA Monitoring -- 12.4.4 Monitoring Using Cloud Computing -- 12.4.5 Monitoring Using IOT -- 12.5 Challenges and Issues of Implementation of IoT on Renewable Energy Resources -- 12.5.1 Challenges -- 12.5.2 Solutions -- 12.6 Conclusion -- References -- 13 Design of Low-Power Energy Harvesting System for Biomedical Devices -- 13.1 Introduction -- 13.2 Investigation on Topologies of DC-DC Converter -- 13.2.1 Hybrid Source Architecture Based on Synchronous Boost Converter -- 13.2.2 Hybrid Source Architecture Using Single-Inductor Dual-Input Single-Output Converter -- 13.2.3 Hybrid Source Architecture Employing a Multi-Input DC Chopper -- 13.3 Hardware Results -- 13.4 Conclusion -- References -- 14 Performance Analysis of Some New Hybrid Metaheuristic Algorithms for HighDimensional Optimization Problems -- 14.1 Introduction -- 14.2 An Overview of Proposed Hybrid Methodologies -- 14.3 Experimental Results and Discussion -- 14.4 Conclusions -- References.
15 Investigation of Structural, Optical and Wettability Properties of Cadmium Sulphide Thin Films Synthesized by Environment Friendly SILAR Technique -- 15.1 Introduction -- 15.2 Experimental Details -- 15.3 Results and Discussion -- 15.3.1 Film Formation Mechanism -- 15.3.2 Thickness Measurement -- 15.3.3 Structural Studies -- 15.3.4 Raman Spectroscopy -- 15.3.5 Scanning Electron Microscopy -- 15.3.6 Optical Studies -- 15.3.7 Wettability Studies -- 15.4 Conclusion -- 15.5 Acknowledgement -- References -- Part II: DESIGN, IMPLEMENTATION ANDAPPLICATIONS -- 16 Solar Photovoltaic Cells -- 16.1 Introduction -- 16.2 Need for Solar Cells -- 16.3 Structure of Solar Cell -- 16.4 Solar Cell Classification -- 16.4.1 First-Generation Solar Cells -- 16.4.2 Second-Generation Solar Cells -- 16.4.3 Third-Generation Solar Cells -- 16.5 Solar PV Cells -- 16.6 Solar Cell Working -- 16.7 Mathematical Modelling of Solar Cell -- 16.8 Solar Cell Connection Methods -- 16.9 Types of Solar PV System -- 16.10 Conclusion -- References -- 17 An Intelligent Computing Technique for Parameter Extraction of Different Photovoltaic (PV) Models -- 17.1 Introduction -- 17.2 Problem Formulation -- 17.2.1 Single-Diode Model -- 17.2.2 Double-Diode Model -- 17.2.3 Three-Diode Model -- 17.3 Proposed Optimization Technique -- 17.3.1 Various Phases of Optimization of Harris Hawks -- 17.4 Results and Discussions -- 17.5 Conclusions -- References -- 18 Experimental Investigation on Wi-Fi Signal Loss by Scattering Property of Duranta Plant Leaves -- 18.1 Introduction -- 18.1.1 Duranta Golden Plant -- 18.1.2 Foliage Loss -- 18.2 Measurement and Calculation -- 18.2.1 Scattering Feasibility -- 18.2.2 Comparison with Tree Shadowing Effect -- 18.3 Result and Discussion -- 18.4 Conclusions -- References -- 19 Multi-Quantum Well-Based Solar Cell -- 19.1 Introduction.
19.2 Theoretical Aspects of Solar Cell.
Record Nr. UNINA-9910829928203321
Hoboken, NJ : , : Wiley : , : Scrivener Publishing, , [2021]
Materiale a stampa
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Explainable machine learning models and architectures / / edited by Suman Lata Tripathi and Mufti Mahmud
Explainable machine learning models and architectures / / edited by Suman Lata Tripathi and Mufti Mahmud
Edizione [1st ed.]
Pubbl/distr/stampa Hoboken, NJ : , : John Wiley & Sons, Inc., , [2023]
Descrizione fisica 1 online resource (273 pages)
Disciplina 006.3
Soggetto topico Computational intelligence
Artificial intelligence
Big data
ISBN 1-394-18657-6
1-394-18656-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910830639403321
Hoboken, NJ : , : John Wiley & Sons, Inc., , [2023]
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Green energy : solar energy, photovoltaics, and smart cities / / editors, Suman Lata Tripathi, Sanjeevikumar Padmanaban
Green energy : solar energy, photovoltaics, and smart cities / / editors, Suman Lata Tripathi, Sanjeevikumar Padmanaban
Pubbl/distr/stampa Hoboken, NJ : , : John Wiley & Sons, Incorporated
Descrizione fisica 1 online resource (640 pages) : illustrations
Disciplina 333.7923091732
Soggetto topico Renewable energy sources
Green technology
Clean energy
Soggetto genere / forma Electronic books.
ISBN 1-5231-3685-5
1-119-76078-X
1-119-76080-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910555246303321
Hoboken, NJ : , : John Wiley & Sons, Incorporated
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Green energy : solar energy, photovoltaics, and smart cities / / editors, Suman Lata Tripathi, Sanjeevikumar Padmanaban
Green energy : solar energy, photovoltaics, and smart cities / / editors, Suman Lata Tripathi, Sanjeevikumar Padmanaban
Pubbl/distr/stampa Hoboken, NJ : , : John Wiley & Sons, Incorporated
Descrizione fisica 1 online resource (640 pages) : illustrations
Disciplina 333.7923091732
Soggetto topico Renewable energy sources
Green technology
Clean energy
ISBN 1-5231-3685-5
1-119-76078-X
1-119-76080-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910830949403321
Hoboken, NJ : , : John Wiley & Sons, Incorporated
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Industrial Control Systems
Industrial Control Systems
Autore Pal Vipin Chandra
Edizione [1st ed.]
Pubbl/distr/stampa Newark : , : John Wiley & Sons, Incorporated, , 2024
Descrizione fisica 1 online resource (336 pages)
Altri autori (Persone) TripathiSuman Lata
GanguliSouvik
ISBN 1-119-82943-7
1-119-82942-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Title Page -- Copyright Page -- Contents -- List of Contributors -- Preface -- Part 1 Advanced Control Techniques -- Chapter 1 Introduction: Industrial Control System -- 1.1 Types of Industry -- 1.1.1 The Primary Sector -- 1.1.2 The Secondary Sector -- 1.1.3 The Tertiary Sector -- 1.2 Historical Perspective in Terms of Control -- 1.2.1 First Industrial Revolution -- 1.2.2 Second Industrial Revolution -- 1.2.3 Third Industrial Revolution -- 1.2.4 Fourth Industrial Revolution -- 1.3 Future of Industry -- 1.3.1 Edge Computing -- 1.3.2 Additive Manufacturing -- 1.3.3 5G -- 1.3.4 Artificial Intelligence -- 1.3.5 Cybersecurity -- References -- Chapter 2 Industrial Boiler Safety Monitoring System -- 2.1 Introduction -- 2.2 Boiler Definition -- 2.2.1 Steam-Raising Plant and Boilers -- 2.2.2 Factors Affecting Safe Operation of Boilers -- 2.2.3 Need for Boiler -- 2.2.4 Applications of Boiler -- 2.2.5 Useful Terms -- 2.3 Classification of Boiler -- 2.3.1 Types of Fuels Used in Boilers -- 2.4 Proposed System -- 2.4.1 Transmitter Section -- 2.4.2 Receiver Section -- 2.5 Hardware Components -- 2.5.1 ATMEGA 328 Controller -- 2.5.1.1 Features of ATmega 328/P Microcontroller -- 2.5.2 Thermocouples -- 2.5.2.1 Construction -- 2.5.2.2 Factors Impacting Accuracy of Thermocouple Readings -- 2.5.2.3 Thermocouple Characteristics -- 2.5.2.4 Industrial Thermocouples -- 2.5.3 Pressure Sensors -- 2.5.3.1 Monitoring Process Flows -- 2.5.3.2 Estimating Safe Levels in Liquid Tanks -- 2.5.3.3 Managing Control Loops -- 2.6 Conclusion and Future Scope -- References -- Chapter 3 Robust Control of Industrial Rotary System -- 3.1 Introduction -- 3.2 Controller Design -- 3.2.1 Finite Dimentional Robust Repetitive Controller Using a Multiloop Approach -- 3.3 Problem Formulation -- 3.4 LMI Formulation for Robust Stabilization Criteria -- 3.5 Plant Model -- 3.6 Simulation Study.
3.7 Processor in Loop (PIL) Simulation -- 3.8 Conclusion -- References -- Chapter 4 Proctored Secure Face Lock System -- 4.1 Introduction -- 4.1.1 The Need for Technology -- 4.2 Background -- 4.3 Proctored Secure Face Lock System -- 4.3.1 Methodology -- 4.3.2 Hardware Requirements -- 4.3.2.1 Overview of Raspberry Pi Version 3B+ Module -- 4.3.2.2 Overview of PI Camera -- 4.3.2.3 PIR Sensor Overview -- 4.3.2.4 Applications of the Components -- 4.3.3 Power Supply -- 4.3.3.1 Transformer -- 4.3.3.2 Rectifier -- 4.3.3.3 Filter -- 4.4 Implementation of Proctored Face Lock System Using Python -- 4.5 Analysis and Discussion -- 4.6 Conclusion and Future Work -- References -- Chapter 5 Advanced Adaptive Control of Nonlinear Plants -- 5.1 Introduction -- 5.2 Model Reference Adaptive Control -- 5.3 Dynamic Inversion -- 5.4 U-Model -- 5.5 Single Inverted Pendulum -- 5.6 Performance Analysis -- 5.6.1 MRAC Employing MIT Rule -- 5.6.2 MRAC Employing LYAPUNOV Stability Method -- 5.6.3 MRAC Augmented with PID Method -- 5.6.4 Dynamic Inversion -- 5.6.5 U-Model Design Technique -- 5.6.5.1 Pole Placement Based Controller -- 5.6.5.2 U-Model Based Pole Placement -- 5.6.5.3 U-Model Based MRAC Technique with MIT Rule -- 5.7 Conclusion -- References -- Chapter 6 Design and Performance Analysis of Multiobjective Optimization Using PSO and SVM for PSS Tuning in SMIB System -- 6.1 Introduction -- 6.2 Small Signal Stability Analysis of SMIB System -- 6.3 Real Time Simulation of SMIB -- 6.3.1 dSPACE Simulated Flux Linkage Model of Synchronous Generator -- 6.3.2 dSPACE Simulation of Synchronous Generator's State Space Model (SSP) -- 6.4 Application of Optimization Techniques -- 6.4.1 Particle Swarm Optimization -- 6.4.2 Support Vector Machine Algorithm -- 6.5 Real-Time Simulation of Single Machine System Using PSO-PSS -- 6.6 Conclusion -- References.
Chapter 7 Modelling and Control of PMSM Drives -- 7.1 Introduction -- 7.2 A Proposed Technique for Modelling and Control -- 7.3 Results and Discussions -- 7.4 Conclusions -- References -- Chapter 8 VI System for Power Management of DC Microgrid -- 8.1 Introduction -- 8.2 Related Work -- 8.3 Proposed System -- 8.3.1 Microgrid Architecture -- 8.3.2 Microgrid Hardware -- 8.4 Microgrid Power Management and Metering Software -- 8.5 Experimental Work and Results -- 8.6 Conclusion -- References -- Part 2 Control Strategies for Practical Systems -- Chapter 9 Execution of a Portable Fuzzy Controller for Speed Regulator Brushless DC Motors -- 9.1 Introduction -- 9.2 Related Works -- 9.3 Materials and Methods -- 9.3.1 Scientific Model for BLDC Motor -- 9.3.2 Inverter Topology for BLDC Motor -- 9.3.2.1 Adaptive Fuzzy Optimal Power Control (AFOPC) Based Speed Control of BLDCM -- 9.3.2.2 Adaptive Fuzzy Optimal Power Control (AFOPC) -- 9.4 Result and Argument -- 9.5 Conclusions -- References -- Chapter 10 Fuzzy Fractional Order PID Controller Design for Single Link Robotic Arm Manipulator -- 10.1 Introduction -- 10.2 Fuzzy Logic Control -- 10.2.1 Mamdani Type Fuzzy System -- 10.3 Fractional Order Proportional Integral Derivative (FOPID) Controller -- 10.3.1 Introduction to Fractional-Order Calculus -- 10.3.1.1 Fractional-Order Differintegral Operator -- 10.3.1.2 Laplace Transform of Fractional Differintegrator -- 10.3.1.3 Approximation Methods of Fractional-Order Laplace Transform -- 10.3.2 Fractional-Order PID Controller-FOPID -- 10.3.2.1 Podlubny's FOPID (PIë Dì) Controller -- 10.3.2.2 Internal Mode Control (IMC) Based FOPID Controller -- 10.3.2.3 Effects of Fractional-Orders in Controller Performance -- 10.4 Modelling of Robotic Manipulator -- 10.4.1 Modelling of Single-Link Manipulator -- 10.4.2 Modelling of Dynamics of Servo Motor.
10.4.3 Modelling of Manipulator Dynamics -- 10.5 Proposed Design of Fuzzy Fractional-Order PID Controller -- 10.5.1 Implementation of Fuzzy Logic for Gain Scheduling of FOPID -- 10.5.2 Structure of the Proposed Fuzzy Inference System -- 10.5.2.1 Inputs -- 10.5.2.2 Outputs -- 10.5.2.3 Rule-Base -- 10.5.2.4 Inference and Defuzzification Technique -- 10.5.3 Proposed Controller Structure -- 10.6 Simulation Study of Proposed FFOPID Controller -- 10.6.1 Analysis of Step Response -- 10.7 Conclusion -- References -- Chapter 11 Prototype Development of an Electromagnetic Levitation System for Maglev Vehicle -- 11.1 Introduction -- 11.1.1 Maglev Transportation -- 11.2 System Modelling and Fabrication -- 11.3 Feedback Sensing, Experimental Results, and Discussions -- 11.4 Conclusions -- References -- Chapter 12 Design of SSA Tuned Cascaded TI-TID Controller for Load Frequency Control of Multi-Source Power System with Electric Vehicle -- 12.1 Introduction -- 12.2 Modelling of Studied MSIPS -- 12.3 Modelling of EV -- 12.4 Adopted Control Approach -- 12.4.1 PID Controller -- 12.4.2 Cascade Controller -- 12.4.3 CPI-TD Controller -- 12.4.4 Design of CTI-TID Controller -- 12.4.5 Formulated Fitness Function and Optimization Constraint -- 12.5 Description of SSA -- 12.6 Simulation Results and Analysis -- 12.6.1 Scenario 1: Performance Investigation of Studied Two-Area MSIPS Model -- 12.6.2 Scenario 2: Performance Investigation of Studied Two-Area MSIPS Model with EVs -- 12.6.3 Scenario 3: Sensitivity Analysis -- 12.7 Conclusion -- References -- Appendix -- Chapter 13 Cyber Security Control Systems for Operational Technology -- 13.1 Introduction -- 13.2 Operational Technology Security Risk -- 13.2.1 Today's Security of Industrial Networks -- 13.2.2 User Activity Monitoring -- 13.2.3 Hazard in Reputed Industries -- 13.2.4 Dynamic Security Battle Space.
13.3 Taxonomy of Security Vulnerabilities -- 13.3.1 Buffer Overflow -- 13.3.2 Non-Substantial Input -- 13.3.3 Race Conditions -- 13.3.4 Lack of Security Practices -- 13.3.5 Access Control Problems -- 13.3.6 Malicious Software -- 13.3.7 Spyware -- 13.3.8 Program in Adware -- 13.3.9 Bot -- 13.3.10 Ransomware -- 13.3.11 Scareware -- 13.3.12 Rootkit -- 13.3.13 Virus -- 13.3.14 Trojan Horse -- 13.3.15 Worms -- 13.3.16 Man-In-The-Middle [MitM] -- 13.3.17 Blended Attacks -- 13.4 Methodology -- 13.4.1 Stronger Operational Technology [OT] Security -- 13.4.2 Creating Inventory and Identifying OT Vulnerabilities -- 13.4.3 Acquiring Automated Threat Intelligence Feeds -- 13.4.4 Back/Restore -- 13.5 Style of Cyber Security -- 13.5.1 Security Automation -- 13.5.2 Breach Detection System (BDS) -- 13.5.3 Protection of Computing Devices From Intrusion -- 13.5.3.1 Keep the Firewall on Condition -- 13.5.3.2 Antivirus and Antispyware -- 13.5.3.3 Manage Your Operating System and Browser -- 13.5.3.4 Protection of Smart Devices -- 13.5.3.5 Unique Passwords for Each Online Account -- 13.5.3.6 Detecting Attacks in Real Time -- 13.5.3.7 Cyber Attacks in Operational Technology -- 13.6 Avoidance of Threads in Operational Technology -- 13.6.1 [DDoS] Distributed Denial of Services Attacks and Response -- 13.6.2 Protecting Against Malware in Operational Technology -- 13.7 Conclusion -- References -- About the Editors -- Index -- EULA.
Record Nr. UNINA-9910835069503321
Pal Vipin Chandra
Newark : , : John Wiley & Sons, Incorporated, , 2024
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