Tabla de Contenidos: “…Front Cover -- Half Title Page -- RIVER PUBLISHERS SERIES IN COMMUNICATIONS -- Title Page - Cognitive Hyperconnected Digital Transformation Internet of Things Intelligence Evolution -- Copyright Page -- Dedication -- Contents -- Preface -- Editors Biography -- List of Figures -- List of Tables -- Chapter 1 - IoT Driving Digital Transformation - Impact on Economy and Society -- 1.1 IoT as a Major Enabler for Digitizing Industry -- 1.2 Main Elements of the IoT Implementation Plan and Its First Pillar -- 1.3 The Second and the Third Pillar - Projects, Partnerships and Standardisation -- 1.4 Conclusion -- Reference -- Chapter 2 - Next Generation IoT Platforms -- 2.1 Introduction -- 2.2 DEI Implementation - Working Groups -- 2.3 IoT Platforms - State of Play -- 2.4 Needs and Priorities for the Next Generation IoT Platforms -- 2.5 Conclusion -- References -- Chapter 3 - Internet of Things Cognitive Transformation Technology Research Trends and Applications -- 3.1 Internet of Things Evolving Vision -- 3.1.1 IoT Common Definition -- 3.1.2 IoT Cognitive Transformation -- 3.2 IoT Strategic Research and Innovation Directions -- 3.2.1 IoT Research Directions and Challenges -- 3.3 IoT Smart Environments and Applications -- 3.3.1 IoT Use Cases and Applications -- 3.3.2 Wearables -- 3.3.3 Smart Health, Wellness and Ageing Well -- 3.3.4 Smart Buildings and Architecture -- 3.3.5 Smart Energy -- 3.3.6 Smart Mobility and Transport -- 3.4 IoT and Related Future Internet Technologies -- 3.4.1 Edge Computing -- 3.4.2 Networks and Communication -- 3.5 IoT Distributed Security - Blockchain Technology -- 3.5.1 Verification and Validation in Blockchain -- 3.5.2 IoT Blockchain Application in Healthcare -- 3.6 IoT Platforms -- References -- Chapter 4 - Internet of Robotic Things - Converging Sensing/Actuating, Hyperconnectivity, Artificial Intelligence and IoT Platforms…”

Tabla de Contenidos: “…2.3.5 Solar Carbothermal Reduction of Magnesia -- 2.3.6 Solar Carbothermal Reduction of Alumina -- 2.4 Conclusions -- Acknowledgments -- References -- Chapter 3 Design Optimization of a Solar Fuel Production Plant by Water Splitting With a Copper-Chlorine Cycle -- Nomenclature -- 3.1 Introduction -- 3.2 System Description -- 3.3 Mathematical Modeling and Optimization -- 3.3.1 Energy and Exergy Analyses -- 3.3.2 Economic Analysis -- 3.3.3 Multiobjective Optimization (MOO) Algorithm -- 3.4 Results and Discussion -- 3.5 Conclusions -- References -- Chapter 4 Diversifying Solar Fuels: A Comparative Study on Solar Thermochemical Hydrogen Production Versus Solar Thermochemical Energy Storage Using Co3O4 -- 4.1 Introduction -- 4.2 Materials and Methods -- 4.3 Thermodynamics of Direct Decomposition of Water -- 4.4 A Critical Analysis of Two-Step Thermochemical Water Splitting Cycles Through the Red/Ox Properties of Co3O4 -- 4.4.1 Red/Ox Characteristics of Co3O4 Measured by Temperature-Programmed Analysis -- 4.4.2 The Role of Pt as a Reduction Promoter of Co3O4 -- 4.4.3 A Critical Analysis of the Solar Thermochemical Cycles of Water Splitting -- 4.5 Cyclic Thermal Energy Storage Using Co3O4 -- 4.5.1 Mass and Heat Transfer Effects During Red/Ox Processes -- 4.5.2 Cyclic Thermal Energy Storage Performance of Co3O4 -- 4.6 Conclusions -- Acknowledgements -- References -- Part II: Artificial Photosynthesis and Solar Biofuel Production -- Chapter 5 Shedding Light on the Production of Biohydrogen from Algae -- 5.1 Introduction -- 5.2 Hydrogen or Biohydrogen as Source of Energy -- 5.3 Hydrogen Production From Various Resources -- 5.4 Mechanism of Biological Hydrogen Production from Algae -- 5.5 Production of Hydrogen from Different Algal Species -- 5.5.1 Generation of Hydrogen in Scenedesmus obliquus -- 5.5.2 Production of Hydrogen in Chlorella vulgaris…”

Tabla de Contenidos: “…3 The Impact of Distributed Computing on Data Analytics and Business Insights -- 3.1 Introduction -- 3.1.1 Role of Distributed Computing in Data Analytics -- 3.1.2 Importance of Business Insights in Decision-Making -- 3.1.3 Overview of Distributed Computing and Data Analytics -- 3.2 Distributed Computing and Data Analytics -- 3.2.1 Distributed Computing -- 3.2.2 Overview of Data Analytics -- 3.2.3 Distributed Computing in Data Analytics -- 3.3 Business Insights and Decision-Making -- 3.3.1 Definition of Business Insights -- 3.3.2 Importance of Business Insights in Decision-Making -- 3.3.3 Applications of Business Insights and their Impact -- 3.4 Challenges and Limitations -- 3.5 The Impact of Distributed Computing on Data Analytics -- 3.5.1 Distributed Computing in Improvising Data Analytics -- 3.6 Conclusion -- References -- 4 Machine Learning and Its Application in Educational Area -- 4.1 Introduction -- 4.2 Previous Work -- 4.3 Technique -- 4.3.1 Machine Learning -- 4.3.2 Supervised Learning -- 4.3.3 Unsupervised Learning -- 4.4 Analysis of Data -- 4.5 Educational Data Mining -- 4.6 Hadoop Approach -- 4.7 Artificial Neural Network (ANN) -- 4.8 Decision Tree -- 4.9 Results/Discussion -- 4.9.1 Personalized Learning Through Adaptive Learning -- 4.10 Increasing Efficiency Using Learning Analytics -- 4.11 Predictive Analysis for Better Assessment Evaluation -- 4.12 Future Scope -- 4.13 Conclusion -- References -- 5 Approaches and Methodologies for Distributed Systems: Threats, Challenges, and Future Directions -- 5.1 Introduction -- 5.2 Distributed Systems -- 5.3 Literature Review -- 5.4 Threats to Distributed Systems Security -- 5.4.1 Hacking -- 5.4.2 Malware -- 5.4.3 Denial of Service (DoS) Attacks -- 5.4.4 Man-in-the-Middle (MitM) Attacks -- 5.4.5 Advanced Persistent Threats (APTs) -- 5.4.6 Insider Threats -- 5.4.7 Phishing -- 5.4.8 Ransomware…”

Tabla de Contenidos: “…13.1.1 State-based regulation -- 13.1.2 Civil-based regulation -- 13.1.3 Co-regulation -- 13.2 Key lessons and recommendations of regulatory reviews to date -- 13.3 Multilateral and multiparty initiatives: the story so far -- 13.4 Moving forward amidst uncertainty -- References -- 4 SUSTAINABILITY -- 14 Exploring Boundaries Around the Safe Use of Advanced Materials: A Prospective Product-Based Case Studies Approach -- 14.1 Introduction -- 14.2 Defining advanced materials -- 14.3 Advanced material risks and safe use-a prospective product-based case study approach -- 14.4 Testing the prospective product case study methodology-an example using a hypothetical dynamic food product label -- 14.5 A prospective product case study-a graphene-based dynamic labels for food products -- 14.5.1 Product description -- 14.5.2 Material generation -- 14.5.3 Intermediary production -- 14.5.4 Final production -- 14.5.5 Product storage and transportation -- 14.5.6 Product use -- 14.5.7 Product disposal -- 14.5.8 Exposure potential -- 14.5.9 Risk red flags -- 14.5.10 Summary -- 14.6 Utility of the prospective product case study methodology -- Acknowledgments -- References -- 15 Nanomaterial Governance, Planetary Health, and the Sustainocene Transition -- 15.1 Introduction -- 15.2 Nanotechnology safety in global context -- 15.3 Regulatory uncertainty and nano-sunscreens -- 15.4 Regulatory uncertainty and nanosilver -- 15.5 Paths to greater nanoregulatory certainty -- 15.6 Reorienting global regulation so nanotechnology assists the Sustainocene -- 15.7 Reorienting the scientific quest toward nanotechnology's role with the Sustainocene -- 15.8 Rethinking the ethics of corporate globalization -- 15.9 Reorienting international law to nanotechnology's role with the Sustainocene -- 15.10 The moral culmination of nanoregulation in globalized artificial photosynthesis…”

Tabla de Contenidos: “…Laukkanen, COMPARISON OF COMPUTED AND MEASURED ACOUSTIC CHARACTERISTICS OF AN ARTIFICIALLY LENGTHENED VOCAL TRACT -- A. K. Fuchs, M. …”

Tabla de Contenidos: “…Big Data -- 5.4.2. Artificial Intelligence -- 5.4.3. FinTech -- 5.4.4. e-Governance -- 5.4.5. 5G/6G-Based Communication Backbone -- 5.4.6. …”

Tabla de Contenidos: “…. -- CAPÍTULO XI NUEVAS TECNOLOGÍAS, INTELIGENCIA ARTIFICIAL, DERECHO INTERNACIONAL MARÍTIMO Y DERECHOS FUNDAMENTALES(pp. 217-234) -- CAPÍTULO XI NUEVAS TECNOLOGÍAS, INTELIGENCIA ARTIFICIAL, DERECHO INTERNACIONAL MARÍTIMO Y DERECHOS FUNDAMENTALES(pp. 217-234) -- https://doi.org/10.2307/j.ctv2zp4rzq.16 -- https://www.jstor.org/stable/j.ctv2zp4rzq.16 -- Las tecnologías emergentes autónomas que están marcando toda una innovación en el ámbito marítimo, se encuentran en constante desarrollo y se están utilizando al servicio de empresas, puertos, la logística, el comercio y el transporte marítimo internacional, trayendo consigo innumerables beneficios pero al mismo tiempo nuevos problemas que atender. …”

Tabla de Contenidos: “…REVISIÓN -- CAPÍTULO 25 INNOVACIÓN Y MEJORA DE LA CALIDAD DEL TRABAJO FIN DE GRADO A TRAVÉS DE CONTENIDOS TRANSMEDIA EN EL GRADO DE BELLAS ARTES DE LA UNIVERSIDAD DE ZARAGOZA -- CAPÍTULO 26 LOS TEXTOS PERIODÍSTICOS EN CLASE DE L1 Y L2: TEMAS SOBRE "MUJER Y LENGUAJE" QUE PUEDEN ABORDARSE -- CAPÍTULO 27 VISUAL THINKING: ESTRATEGIAS DE PENSAMIENTO VISUAL PARA EL DESARROLLO DE COMPETENCIAS CRÍTICAS Y DISCURSIVAS EN EL MARCO DE LOS ESTUDIOS LITERARIOS -- CAPÍTULO 28 EL ARCHIVO SECRETO DE LA POLICÍA NACIONAL DE GUATEMALA: PROPUESTA DOCENTE PARA LA INTRODUCCIÓN A LA ARCHIVÍSTICA Y LA INVESTIGACIÓN --CAPÍTULO 29 ASPECTOS DIDÁCTICOS: IMPORTANCIA Y USO DE LAS PAREMIAS EN LA ENSEÑANZA DEL HASANIYA COMO LENGUA EXTRANJERA PARA HISPANOHABLANTES -- CAPÍTULO 30 TRADUCCIÓN ESPECIALIZADA EN EL BINOMIO ÁRABE ESPAÑOL: ENFOQUE DOCENTE BASADO SOBRE ENCARGOS DE TRADUCCIÓN -- CAPÍTULO 31 ESTRATEGIAS Y PRÁCTICAS DEL APRENDIZAJE CENTRADAS EN EL ESTUDIANTE APLICADAS A LA ENSEÑANZA DE LA LENGUA CHINA EN LA EDUCACIÓN SUPERIOR -- CAPÍTULO 32 LAS TAREAS DUALES COMO INTERVENCIÓN EN NIÑOS DE EDUCACIÓN PRIMARIA CON TDAH: APROXIMACIÓN BIBLIOGRÁFICA -- CAPÍTULO 33 ARTIFICIAL INTELLIGENCE ASSISTED ERROR ANALYSIS IN ESL AND SLA -- CAPÍTULO 34 FORMACIÓN DEL ALUMNADO DE HISTORIA DEL ARTE EN TECNOLOGÍAS COMPUTACIONALES 3D: ESTRATEGIAS PARA LA PRESERVACIÓN DEL PATRIMONIO CULTURAL -- CAPÍTULO 35 LA COMUNICACIÓN NO VERBAL EN EL PROCESO DE ENSEÑANZA-APRENDIZAJE EN EDUCACIÓN SECUNDARIA OBLIGATORIA: EL DEBATE COMO METODOLOGÍA DOCENTE -- CAPÍTULO 36 ENSEÑANZA DE LAS EXPRESIONES FRASEOLÓGICAS EN LA CLASE DE LENGUA CHINA: ESTUDIO DE LA VIABILIDAD DE USO DE LAS NUEVAS TECNOLOGÍAS PARA LA INCLUSIÓN DE LOS CHÉNGY (成语) EN LA DOCENCIA -- CAPÍTULO 37 ANÁLISIS PRAGMÁTICO A TRAVÉS DE PERUSALL -- CAPÍTULO 38 LAS CSL COMO PROPUESTA DIDÁCTICA EN EL AULA INVERTIDA DE ELE -- CAPÍTULO 39 PERUSALL COMO HERRAMIENTA PARA LA PARTICIPACIÓN Y LA CO-CREACIÓN EN -- CAPÍTULO 40 EL DOMINIO DEL ÁMBITO FRASEOLÓGICO Y SU PROYECCIÓN FRASEOGRÁFICA: UN RETO EN LEXICOGRAFÍA -- CAPÍTULO 41 LA NOVEDAD LÉXICA EN LA ENSEÑANZA DEL ESPAÑOL COMO SEGUNDA LENGUA -- CAPÍTULO 42 APRENDE IDIOMAS CANTANDO -- CAPÍTULO 43 EL PAISAJE URBANO DE MÁLAGA MODELADO POR EL RÍO GUADALMEDINA. …”

Tabla de Contenidos: “…Cabral & J.F.C.L. Costa Artificial intelligence using real-time data L.-P. Campeau & M. …”

Tabla de Contenidos: “…RY -- 3.1 Introduction 31 -- 3.2 Some elements of definition 32 -- 3.2.1 The term "virtual reality" 32 -- 3.2.2 The purpose of virtual reality 32 -- 3.2.3 A functional definition of virtual reality 33 -- 3.2.4 A technical definition of virtual reality 33 -- 3.3 The main interaction devices 34 -- 3.3.1 Display devices 35 -- 3.3.2 Motion and position capture devices 35 -- 3.3.3 Proprioceptive and cutaneous feedback devices 35 -- 3.3.4 Sound input and presentation devices 36 -- 3.4 The main areas of application of virtual reality 36 -- 3.4.1 Applications in everyday life 37 -- 3.4.2 Applications in various professional contexts 37 -- 3.5 Applications of virtual reality in industry 38 -- 3.6 Conclusion 40 -- 3.7 References 40 -- Chapter 4 Robotization in Industries: A Focus on SMEs 45 Sandrine BERGER-DOUCE -- 4.1 Introduction 45 -- 4.2 Focus on a robotization experiment in an industrial SME 46 -- 4.2.1 The case study in the service of exploratory research 46 -- 4.2.2 Presentation of the company 47 -- 4.2.3 A mixed technological adventure 47 -- 4.2.4 Lessons to be learned 48 -- 4.3 Receiving support in order to better implement a robot: illustration by the Robot Start PME program 49 -- 4.3.1 A program at the service of French industrial SMEs 50 -- 4.3.2 An inspiring framework to support technological change 53 -- 4.4 Conclusion 54 -- 4.5 References 55 -- Chapter 5 Serious Games for Vocational Training: From Emotional Labor to Knowledge Transfer 57 Lydia MARTIN, Julian ALVAREZ and Antoine TALY -- 5.1 Introduction 57 -- 5.2 Emotions, debriefing and learning 59 -- 5.2.1 Emotional labor 59 -- 5.2.2 Learning in a game 60 -- 5.3 The context and framework of the Serious Escape Game (SEG) 61 -- 5.3.1 Difficulty in gamification 61 -- 5.3.2 The training system 62 -- 5.3.3 A research-action approach 62 -- 5.4 Results 63 -- 5.4.1 Observations during gaming 63 -- 5.4.2 Post-game discussions 64 -- 5.4.3 Questionnaires 66 -- 5.5 Discussion and conclusion 67 -- 5.6 References 68 -- Chapter 6 The "Old" Issues of the "New" Artificial Intelligence Systems in Professional Activities 71 Tamari GAMKRELIDZE, Moustafa ZOUINAR and Flore BARCELLINI -- 6.1 Introduction 71 -- 6.2 AI: elements of definition and recent developments 72 -- 6.3 Functionalities and (potential) uses of new generation AI systems 74 -- 6.4 The "new" generation of AI and the old challenges of transforming work situations 77 -- 6.4.1 From the substitutive approach of automation to the complementary approaches of human-machine systems 77 -- 6.4.2 The challenges of "new" AI systems in work situations 79 -- 6.5 What are the approaches to designing and integrating AI systems in work situations? …”

Tabla de Contenidos: “…Machine generated contents note: Chapter 1: Introduction to High Performance Drives 1.1 Preliminary Remarks 1.2 General Overview of High Performance Drives 1.3 Challenges and Requirements for Electric Drives for Industrial Applications 1.4 Organization of the Book References Chapter 2: Mathematical and Simulation Models of AC Machines 2.1 Preliminary Remarks 2.2 DC Motors 2.2.1 Separately Excited DC Motor Control 2.2.2 Series DC Motor Control 2.3 Squirrel Cage Induction Motor 2.3.1 Space vector representation 2.3.2 Per unit model of Induction Motor 2.3.3 Double Fed Induction Generator (DFIG) 2.4 Mathematical Model of Permanent Magnet Synchronous Motor Problems References Chapter 3: Pulse Width Modulation of Power Electronic DC-AC Converter 3.1 Preliminary Remarks 3.2 Classification of Pulse Width Modulation Schemes for Voltage source inverter 3.3 Pulse Width Modulated Inverters 3.3.1 Single Phase Half Bridge Inverters 3.3.1.1 Matlab/Simulink Model of Half Bridge Inverter 3.3.2 Single Phase Full Bridge Inverters 3.3.2.1 Matlab/Simulink Model of Single-phase Full-Bridge Inverter 3.4 Three-phase PWM voltage source inverter 3.4.1 Carrier based Sinusoidal PWM 3.4.2 Third Harmonic Injection Carrier-based PWM 3.4.3 Carrier-based PWM With Offset Addition 3.4.4 Space Vector PWM 3.4.5 Discontinuous Space Vector PWM 3.4.6 Matlab/Simulink Model for space vector PWM 3.4.7 Space Vector PWM in Over-modulation Region 3.4.8 Artificial Neural Network Based PWM 3.5 Relationship Between Carrier-based PWM and Space Vector PWM 3.6 Multi-level Inverters 3.6.1 Diode Clamped Multi-level Inverters 3.6.2 Flying Capacitor Type Multi-level Inverter 3.6.3 Cascaded H-Bridge Multi-level Inverter 3.7 Impedance Source or Z-Source Inverter 3.7.1 Circuit Analysis 3.7.2 Carrier-based Simple Boost PWM control of a Z-source Inverter 3.7.3 Carrier-based Maximum Boost PWM control of a Z-source Inverter 3.7.4 Matlab/Simulink model of Z-source inverter 3.8 Quasi Impedance Source or qZSI Inverter 3.8.1 Matlab/Simulink model of qZ-source inverter 3.9 Dead Time Effect in a Multi-phase Inverter 3.10 Summary References Chapter 4: Field Oriented Control of AC Machines 4.1 Introduction 4.2 Induction Machines Control 4.2.1 Control of Induction Motor using V/f method 4.2.2 Vector Control of Induction Motor [4.1-4.16] 4.2.3 Direct and Indirect Field Oriented Control 4.2.4 Rotor and stator flux computation 4.2.5 Adaptive flux observer 4.2.6 Stator Flux Orientation 4.2.7 Field Weakening Control 4.3 Vector Control of Double Fed Induction Generator (DFIG) 4.3.1 Introduction 4.3.2 Vector Control of DFIG connected with the Grid (abModel) 4.3.3 Simulation Results 4.4 Control of Permanent Magnet Synchronous Machine 4.4.1 Introduction 4.4.2 Vector Control of PMSM in dq axis 4.4.3 Vector Control of PMSM in a-baxis using PI controller 4.4.4 Scalar Control of PMSM Exercises Additional tasks Possible tasks for DFIG References Chapter 5: XXXXXXXXXX Chapter 6: Nonlinear Control of Electrical Machines Using Nonlinear Feedback 6.1 Introduction 6.2 dynamic system linearization using non-linear feedback 6.3 Nonlinear Control of Separately Excited DC Motor 6.3.1 Matlab/Simulink Nonlinear Control Model 6.3.2 Nonlinear Control Systems 6.3.3 Speed Controller 6.3.4 Control for variable m 6.3.5 Field Current Controller 6.3.6 Simulation Results 6.4 Multiscalar model (MM) of induction motor 6.4.1 Multiscalar variables 6.4.2 Nonlinear linearization of induction motor fed by voltage controlled VSI 6.4.3 Design of system control 6.4.4 Nonlinear linearization of induction motor fed by current controlled VSI 6.4.5 Stator oriented nonlinear control system (based on Ys,is) 6.4.6 Rotor-Stator Fluxes based Model 6.4.7 Stator Oriented Multiscalar Model 6.4.8 Multiscalar Control of Induction Motor 6.4.9 Induction Motor Model 6.4.10 State Transformation 6.4.11 Decoupled IM Model 6.5 MM of double fed induction machine (DFIM) 6.6 Nonlinear Control of Permanent Magnet Synchronous Machine 6.6.1 Nonlinear Control of PMSM for a dq motor model 6.6.2 Nonlinear Vector Control of PMSM in a-baxis 6.6.3 PMSM in a-b(x-y) axis 6.6.4 Transformation 6.6.5 Control System 6.6.6 Simulation Results Problems References Chapter 7: Five-Phase Induction Motor Drive System 7.1 Preliminary remarks 7.2 Advantages and Applications of Multi-phase drives 7.3 Modelling and Simulation of a Five-phase Induction motor drive 7.3.1 Five-phase Induction motor model 7.3.1.1 Phase variable model 7.3.1.2 Model transformation 7.3.1.3 Machine model in an arbitrary common reference frame 7.3.1.4 Matlab/Simulink model of main fed five-phase induction motor drive 7.3.2 Five-phase Two-level Voltage source Inverter Model 7.3.2.A Ten-Step Mode of Operation 7.3.2.A.1 Fourier analysis of the five-phase inverter output voltages 7.3.2.A.2 Matlab/Simulink Modelling for Ten-step Mode 7.3.2.A.3 Prototype of a five-phase VSI for ten-step operation 7.3.2.A.4 Experimental Results for Ten-Step mode 7.3.2.A.5 PWM mode of operation of five-phase VSI 7.3.3 PWM Schemes of a Five-phase VSI 7.3.3.1 Carrier-based Sinusoidal PWM scheme 7.3.3.2 Matlab/Simulink simulation of Carrier-based sinusoidal PWM 7.3.3.3 5th Harmonic Injection Based pulse width modulation scheme 7.3.3.4 Matlab/Simulink simulation of 5th harmonic injection PWM 7.3.3.5 Offset addition based pulse width modulation scheme 7.3.3.6 Space Vector Pulse Width Modulation Scheme 7.3.3.7 Matlab/Simulink model of SVPWM 7.4 Indirect Rotor Field Oriented Control of Five-phase induction motor 7.4.1 Matlab/Simulink Model of Field oriented control of five-phase Induction machine 7.5 Field Oriented Control of Five-phase induction motor with current control in the Synchronous reference frame 7.6 Model Predictive Control (MPC) 7.6.1 MPC Applied to a Five-phase Two-Level VSI 7.6.2 Matlab/Simulink of MPC for Five-phase VSI 7.7 Summary 7.8 Bibliography Chapter 8: Sensorless Speed Control of AC Machines 8.1 Preliminary Remarks 8.2 Sensorless Control of Induction Motor 8.2.1 Observer 1 8.2.2 Observer 2 8.2.3 Observer 3 8.2.4 MRAS- (closed loop) speed estimator 8.2.5 The use of power measurements 8.3 Sensorless Control of PMSM 8.3.1 Control system of PMSM 8.3.2 Adaptive backstepping observer 8.3.3 Model Reference Adaptive System for PMSM 8.3.4 Simulation Results 8.4 MRAS-Based Sensorless Control of Five-Phase Induction Motor Drive 8.4.1 MRAS-BASED SPEED ESTIMATOR 8.4.2 Simulation Results References Chapter 9: Selected Problems of Induction Motor Drives with Voltage Inverter and Inverter Output Filters 9.1 Drives and filters - overview 9.2 Three phase to two phase transformations 9.3 Voltage and current common mode component 9.3.1 Matlab/Simulink model of induction motor drive with PWM inverter and common mode voltage 9.4 Induction motor common mode circuit 9.5 Bearing current types and reduction methods 9.5.1 Common mode choke 9.5.2 Common mode transformers 9.5.3 Common mode voltage reduction by PWM modifications 9.6 Inverter output filters 9.6.1 Selected structures of inverter output filters 9.6.2 Inverter output filters design 9.6.3 Motor choke 9.6.4 Matlab/Simulink model of induction motor drive with PWM inverter and differential mode (normal mode) LC filter 9.7 Estimation problems in the drive with filters 9.7.1 Introduction 9.7.2 Speed observer with disturbances model 9.7.3 Simple observer based on motor stator models 9.8 Motor control problems in the drive with filters 9.8.1 Introduction 9.8.2 Field oriented control 9.8.3 Nonlinear field oriented control 9.8.4 Nonlinear multiscalar control 9.9 Predictive current control in the drive system with output filter 9.9.1 Control system 9.9.2 Predictive current controller 9.9.3 EMF estimation technique 9.10 Problems 9.11 Questions 9.12 References Index…”

Tabla de Contenidos: “…. -- 1.1 Introduction -- 1.2 The Two Perceptive Elements -- 1.3 Immersive Tools and Technologies -- 1.4 The Methodology -- 1.5 Interaction Through Voice Assistant -- 1.6 Improved Distraction Tracking -- 1.7 Discussions -- 1.8 Market Analysis -- 1.9 Result -- 1.10 Conclusion -- 2 When Technology Meets Tradition: Rediscovering Tribes Through Virtual Reality 27 Debanjana Nag -- 2.1 Introduction -- 2.2 Concept of Communication and Virtual Reality as a Tool of Communication -- 2.3 The Tribes and the Concept of 'Modern' Society -- 2.4 Status of Women in Tribal Societies -- 2.5 Socio-Political Systems of Tribal Societies -- 2.6 Conditions of Education, Health and Hygiene -- 2.7 Application of Virtual Reality as a Learning Pedagogy to Understand Tribal Aspects -- 2.8 Problems in the Implementation of VR Among the Tribes -- 2.9 Utilization of Virtual Reality to Connect Tribes with the Mainstream -- 2.10 Epilogue -- 3 Post-Pandemic Approaches Through Various Advanced Toolkits for Online Teaching and Learning Confidence 47 Karthikeyan Kandasamy, Prakash Maran Jeganathan and Shalini Surajmani -- 3.1 Introduction -- 3.2 The Impact of Technology on Learning -- 3.3 MAXHUB UC BM35 Bluetooth Teleconference Speakerphone -- 3.4 4K Ultra HD -- 3.5 BenQ EdTech -- 3.6 Conclusion -- 4 Expanding Teaching Possibilities: Applications of Technological Products in Education 61 Jyoti Verma and Gagandeep -- 4.1 Introduction -- 4.2 Benefits of Technology in the Education Sector -- 4.3 Applications of Technological Products in Education -- 4.4 PESTLE Analysis of Technological Products in the Education Sector -- 4.5 Successive Growth of Technological Products in India -- 4.6 Conclusion -- 5 Evolutionary Advantages of Virtual Reality in Education 73 Richa Kapoor Mehra -- 5.1 Introduction -- 5.2 Differences Between Real and Virtual Space -- 5.3 Use of Virtual Reality: A Matter of Concern -- 5.4 Conclusion -- 6 Exploring Possibilities and Apprehensions About Application of Artificial Intelligence in Higher Education 87 Siddharth Shimpi -- 6.1 Introduction -- 6.2 The Current State of AI in Higher Education -- 6.3 Advantages of AI in Higher Education -- 6.4 Potential Risks of AI in Higher Education -- 6.5 Ethical Considerations in AI in Higher Education -- 6.6 Future of AI in Higher Education -- 6.7 Case Studies -- 6.8 Best Practices -- 6.9 Conclusion -- 7 Impact of Virtual Reality on Immersive Education 101 Manju Rani -- 7.1 Introduction -- 7.2 Techniques Used in Immersive Learning -- 7.3 Advantages of Immersive Learning -- 7.4 Disadvantages of Immersive Learning -- 7.5 Virtual Reality -- 7.6 Processing of VR -- 7.7 Types of Virtual Reality -- 7.8 Developing Content for VR -- 7.9 Creating a Virtual Reality Environment -- 7.10 VR in Education -- 7.11 E-Learning and VR -- 7.12 The Usefulness of VR Technology in the Field of Education -- 7.13 VR in Teacher Training and Pedagogy -- 7.14 Creating an Immersive VR Environment with MaxWhere -- 7.15 Applications or Software for Using VR Technology in the Field of Education -- 7.16 Growth of VR Technology in Education -- 7.17 Obstacles in Using VR Technology -- 7.18 Interpretation of Results -- Part 2: Reimaging Education with Metaverse -- 8 The Metaverse in Education: An Upcoming Future Trend 129 Priya Jindal and Ansh Jindal -- 8.1 Introduction -- 8.2 XR in Metaverse -- 8.3 Categories of Extended Reality (XR) -- 8.4 XR and Learning -- 8.5 Approaches of Learning in Metaverse -- 8.6 Comparison of Classes in Person, Virtual Classes, and in the Metaverse -- 8.7 Challenges of Metaverse in Education -- 8.8 Trends Supporting Metaverse in Education -- 8.9 Conclusion -- 9 Role of Virtual Reality in Education: Its Scope, Reach and Effect on Student Behavior 145 Shweta Kapoor and Gitanjali Kalia -- 9.1 Introduction -- 9.2 Types of Virtual Reality -- 9.3 Various Types of Augmented Reality -- 9.4 Virtual and Augmented Reality -- 9.5 Application of Virtual Reality -- 9.6 Implementation of VR in Education Sector -- 9.7 Effects of Virtual Reality on Student Behavior -- 9.8 Positive Effect of Virtual Reality on Students -- 9.9 Negative Effect of Virtual Reality on Students -- 9.10 Challenges Faced when Implementing VR in Education Sector -- 9.11 Conclusion -- 9.12 Forming New Perspectives -- 10 Virtual Reality in Education: Benefits, Applications and Challenges 165 Rajni Bala and Prachi Gupta -- 10.1 Introduction -- 10.2 Industry Key Players in VR in Education -- 10.3 VR Market Segmentation in the Education Sector -- 10.4 Application of VR in Education -- 10.5 Distance Learning -- 10.6 Advantages of VR in the Classroom -- 10.7 Disadvantages of VR in the Classroom -- 10.8 How VR Will Improve Education -- 10.9 Challenges of Implementing VR in Education -- 10.10 How to Maximize the Benefits of VR in Education -- 11 Exploring the Landscape of Virtual Reality in Education: A Bibliometric and Thematic Analysis 181 Natashaa Kaul and Chanakya Kumar -- 11.1 Introduction -- 11.2 Literature Review -- 11.3 Methodology -- 11.4 Findings and Results -- 11.5 Methodology and Research Perspectives -- 11.6 Temporal Analysis Using Word Clouds -- 11.7 Future Research -- 11.8 Conclusion -- 11.9 Implications for Research and Practice -- 11.10 Limitations of the Study -- 12 VR in Vocational Educational and Training: Conceptual Framework and Adoption Roadmap 201 Kumar Shalender, Babita Singla and Sandhir Sharma -- 12.1 Introduction -- 12.2 Benefits of VR in Training -- 12.3 VR Adoption Framework -- 12.4 Conclusion and Discussion -- 13 Virtual Reality in Education -- A Blessing or Curse? …”

Tabla de Contenidos: “…Cover -- Series Page -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- Part 1: A Guide to Simulated Techniques in Digital Twin -- Chapter 1 Introduction to Different Simulation Techniques of Digital Twin Development -- 1.1 Introduction -- 1.2 Literature Review -- 1.3 Digital Twin Simulation Techniques -- 1.3.1 Finite Element Analysis Simulation -- 1.3.2 Computational Fluid Dynamics Simulation -- 1.3.3 Discrete Event Simulation -- 1.3.4 Agent-Based Modeling Simulation -- 1.3.5 Multi-Body Dynamics Simulation -- 1.3.6 Monte Carlo Simulation -- 1.4 Conclusion -- References -- Chapter 2 Comprehensive Analysis of Error Rate and Channel Capacity of Fisher Snedecor Composite Fading Model -- 2.1 Introduction -- 2.2 Fisher Snedecor Composite Fading -- 2.3 Mathematical Analysis -- 2.3.1 Error Rate Analysis -- 2.3.1.1 NCBFSK and BDPSK -- 2.3.1.2 BPSK, BFSK, and QPSK -- 2.3.1.3 MQAM -- 2.3.1.4 MPSK -- 2.3.1.5 MDPSK -- 2.3.1.6 NCMFSK -- 2.3.1.7 DQPSK -- 2.3.2 Channel Capacity Analysis -- 2.3.2.1 ORA -- 2.3.2.2 OPRA -- 2.3.2.3 CIFR -- 2.3.2.4 TIFR -- 2.4 Numerical Results -- 2.5 Conclusion -- References -- Chapter 3 Implementation of Automatic Driving Car Test Approach Based on a Digital Twinning Technology and by Embedding Artificial Intelligence -- 3.1 Introduction -- 3.2 Literature Review -- 3.3 Comparative Analysis -- 3.4 Result -- 3.5 Concluding Remarks and Future Scope -- References -- Chapter 4 Intelligent Monitoring of Transformer Equipment in Terms of Earlier Fault Diagnosis Based on Digital Twins -- 4.1 Introduction -- 4.2 Methodology -- 4.2.1 Arduino Uno -- 4.2.2 ESP32 Microcontroller -- 4.2.3 Data Acquisition -- 4.2.4 Blynk App -- 4.3 Machine Learning-Based Predictive Maintenance -- 4.4 Results and Discussion -- 4.5 Conclusion and Future Work -- References…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright -- Contents -- Preface -- Acknowledgments -- Acronyms -- Chapter 1 IoT Technologies and Applications -- 1.1 Introduction -- 1.2 Traditional IoT Technologies -- 1.2.1 Traditional IoT System Architecture -- 1.2.1.1 Sensing Layer -- 1.2.1.2 Network Layer -- 1.2.1.3 Application Layer -- 1.2.2 IoT Connectivity Technologies and Protocols -- 1.2.2.1 Low‐power and Short‐range Connectivity Technologies -- 1.2.2.2 Low Data Rate and Wide‐area Connectivity Technologies -- 1.2.2.3 Emerging IoT Connectivity Technologies and Protocols -- 1.3 Intelligent IoT Technologies -- 1.3.1 Data Collection Technologies -- 1.3.1.1 mmWave -- 1.3.1.2 Massive MIMO -- 1.3.1.3 Software Defined Networks -- 1.3.1.4 Network Slicing -- 1.3.1.5 Time Sensitive Network -- 1.3.1.6 Multi‐user Access Control -- 1.3.1.7 Muti‐hop Routing Protocol -- 1.3.2 Computing Power Network -- 1.3.2.1 Intelligent IoT Computing Architecture -- 1.3.2.2 Edge and Fog Computing -- 1.3.3 Intelligent Algorithms -- 1.3.3.1 Big Data -- 1.3.3.2 Artificial Intelligence -- 1.4 Typical Applications -- 1.4.1 Environmental Monitoring -- 1.4.2 Public Safety Surveillance -- 1.4.3 Military Communication -- 1.4.4 Intelligent Manufacturing and Interactive Design -- 1.4.5 Autonomous Driving and Vehicular Networks -- 1.5 Requirements and Challenges for Intelligent IoT Services -- 1.5.1 A Generic and Flexible Multi‐tier Intelligence IoT Architecture -- 1.5.2 Lightweight Data Privacy Management in IoT Networks -- 1.5.3 Cross‐domain Resource Management for Intelligent IoT Services -- 1.5.4 Optimization of Service Function Placement, QoS, and Multi‐operator Network Sharing for Intelligent IoT Services -- 1.5.5 Data Time stamping and Clock Synchronization Services for Wide‐area IoT Systems -- 1.6 Conclusion -- References -- Chapter 2 Computing and Service Architecture for Intelligent IoT…”

Tabla de Contenidos: “…OTT Voice Service Quality 182 -- 6.2 QoS-enabled Video and IPTV Services 183 -- 6.2.1 IPTV and QoS 184 -- 6.3 QoE for VoIP and IPTV 188 -- 6.3.1 QoE for VoIP 188 -- 6.3.2 QoE for IPTV 190 -- 6.4 QoS for Popular Internet Services 192 -- 6.5 QoS for Business Users (VPN Services) 196 -- 6.6 QoS for Internet Access Service and Over-the-Top Data Services 198 -- 6.6.1 Traffic Management for OTT Services 200 -- 6.6.2 Traffic Management Approaches 200 -- 6.6.3 Traffic Management Influence on QoE for OTT Services 204 -- 6.7 Internet of Things (IoT) Services 205 -- 6.7.1 Mobile Cellular Internet of Things 206 -- 6.7.2 IoT Big Data and Artificial Intelligence 209 -- 6.8 Cloud Computing Services 210 -- 6.8.1 QoS Metrics for Cloud Services 212 -- 6.9 Business and Regulatory Challenges for Services Over Ultra-Broadband 214 -- 6.9.1 Business Aspects for Broadband Services 214 -- 6.9.2 Regulatory Challenges for Broadband Services 216 -- References 218 -- 7 Broadband QoS Parameters, KPIs, and Measurements 221 -- 7.1 QoS, QoE, and Application Needs 221 -- 7.2 Generic and Specific QoS Parameters 224.…”

Tabla de Contenidos: “…10.2.3 Variant Calling From RNA Sequencing Data -- 10.2.4 Variant Call Format (VCF) -- 10.2.5 Evaluating VCF Results -- 10.3 Structural Variant (SV) Calling -- 10.3.1 Short-Read-Based SV Calling -- 10.3.2 Long-Read-Based SV Calling -- 10.3.3 CNV Detection -- 10.3.4 Integrated SV Analysis -- 10.4 Annotation of Called Variants -- References -- 11 Clinical Sequencing and Detection of Actionable Variants -- 11.1 Clinical Sequencing Data Generation -- 11.1.1 Patient Sample Collection -- 11.1.2 Library Preparation and Sequencing Approaches -- 11.2 Read Mapping and Variant Calling -- 11.3 Variant Filtering -- 11.3.1 Frequency of Occurrence -- 11.3.2 Functional Consequence -- 11.3.3 Existing Evidence of Relationship to Human Disease -- 11.3.4 Clinical Phenotype Match -- 11.3.5 Mode of Inheritance -- 11.4 Variant Ranking and Prioritization -- 11.5 Classification of Variants Based On Pathogenicity -- 11.5.1 Classification of Germline Variants -- 11.5.2 Classification of Somatic Variants -- 11.6 Clinical Review and Reporting -- 11.6.1 Use of Artificial Intelligence in Variant Reporting -- 11.6.2 Expert Review -- 11.6.3 Generation of Testing Report -- 11.6.4 Variant Validation -- 11.6.5 Incorporation Into a Patient's Electronic Health Record -- 11.6.6 Reporting of Secondary Findings -- 11.6.7 Patient Counseling and Periodic Report Updates -- 11.7 Bioinformatics Pipeline Validation -- References -- 12 De Novo Genome Assembly With Long And/or Short Reads -- 12.1 Genomic Factors and Sequencing Strategies for De Novo Assembly -- 12.1.1 Genomic Factors That Affect De Novo Assembly -- 12.1.2 Sequencing Strategies for De Novo Assembly -- 12.2 Assembly of Contigs -- 12.2.1 Sequence Data Preprocessing, Error Correction, and Assessment of Genome Characteristics -- 12.2.2 Contig Assembly Algorithms -- 12.2.3 Polishing -- 12.3 Scaffolding and Gap Closure…”

Tabla de Contenidos: “…8.3.8 Concentration of particles -- 8.3.9 Membrane material -- 8.4 VARIABLES AND APPLICATIONS OF THE MFI-UF -- 8.4.1 Plant profiling and water quality monitoring -- 8.4.2 Flux rate -- 8.4.3 Predicting rate of fouling of seawater RO systems -- 8.4.4 Comparing fouling indices -- 8.5 REFERENCES -- Part 3: Inorganic fouling and scaling -- Chapter 9: Inorganic Fouling: Characterization Tools and Mitigation -- 9.1 INTRODUCTION -- 9.2 MAIN COMPONENTS OF INORGANIC FOULING -- 9.2.1 Colloidal matter/particulate -- 9.2.2 Metals -- 9.2.3 Scaling -- 9.2.4 OTHER COMPONENTS -- 9.3 METHODS FOR INORGANIC FOULING IDENTIFICATION -- 9.4 METHODS FOR INORGANIC FOULING REMOVAL -- 9.5 REFERENCES -- Chapter 10: Assessing Scaling Potential with Induction Time and a Once-through Laboratory Scale RO System -- 10.1 INTRODUCTION -- 10.2 INDUCTION TIME MEASUREMENTS -- 10.2.1 Experimental setup -- 10.2.1.1 Glass reactor -- 10.2.1.3 pH meter -- 10.2.1.4 Peristaltic pump -- 10.2.1.5 Thermostat -- 10.2.2 Experimental procedure -- 10.2.2.1 Preparation of artificial brackish water -- 10.2.2.2 Induction time measurement -- 10.2.3 Calculation of induction time -- 10.2.4 Cleaning of the reactor -- 10.2.5 Example of application of induction time -- 10.3 ONCE THROUGH LAB-SCALE RO SYSTEM -- 10.3.1 Experimental set-up -- 10.3.2 Experimental protocol -- 10.3.3 Example of application -- 10.4 OUTLOOK AND FINAL COMMENTS -- 10.5 REFERENCES -- Part 4: Organic fouling -- Chapter 11: Practical Considerations of Using LC-OCD for Organic Matter Analysis in Seawater -- 11.1 INTRODUCTION -- 11.2 LC-OCD ANALYSIS -- 11.2.1 Instrumentation and chromatogram integration -- 11.2.2 Effect of salinity on organic characterization and calibration -- 11.2.3 LEVEL OF DETECTION -- 11.2.4 REPRODUCIBILITY OF LC-OCD -- 11.2.5 CHARACTERISATION OF ORGANIC MIXTURES -- 11.2.6 Applications…”

Tabla de Contenidos: “…-- Notes -- Chapter 2: Cyber threats and the necessary clarifications -- 2.1 Risk -- 2.2 Different types of risk -- 2.2.1 Artificial Intelligence and risk -- 2.2.2 Human rights -- 2.3 Briefly about cyberattacks -- 2.4 Kill chain - a useful thought model -- 2.4.1 Reconnaissance -- 2.4.2 Weaponization -- 2.4.3 Delivery -- 2.4.4 Exploitation -- 2.4.5 Installation -- 2.4.6 Command and control -- 2.4.7 Achieving goals -- 2.4.8 Kill chain - summary -- 2.5 The MITRE model -- 2.6 Social engineering and phishing -- 2.6.1 Masquerade in France using the "minister" method -- 2.7 Threat groups -- 2.7.1 Hacktivists -- 2.7.2 Cybercriminals -- 2.7.3 State groups, APT -- 2.7.4 Groups - synthesis -- 2.8 Cyber tools or cyberweapons? …”

Tabla de Contenidos: “…6.13.3 The Critical Communications Association (TCCA) 121 -- 6.14 Public Safety Network from LTE to 5G 122 -- 6.15 Convergence Solution for LTE and TETRA for AngoláÖs National Communications Network 124 -- 6.15.1 The Objectives of the Project 124 -- 6.15.2 Advantages of the LTE-TETRA Solutions 124 -- 6.15.3 Illustration: Before Integration and After Integration 125 -- 6.15.4 Overview of LTE Technology 125 -- 6.16 5GWireless Network and Public Safety Perspective 126 -- 6.16.1 Waiting for 5G for Public Safety Implementation 127 -- 6.17 The Linkage Between 4G and 5G Evolution 128 -- 6.17.1 Connecting 4G and 5G Solutions for Public Safety 128 -- 6.17.2 Deploying LTE Public Safety Networks 129 -- 6.18 Conclusion 129 -- References 130 -- 7 Bringing Public Safety Communications into the 21st Century 133 -- 7.1 Emerging Technologies with Life-Saving Potential 133 -- 7.1.1 Artificial Intelligence 134 -- 7.1.2 The Internet of Things (IoT) 136 -- 7.1.3 Blockchain 138 -- References 139 -- 8 4G LTE: The Future of Mobile Wireless Telecommunication Systems for Public Safety Networks 141 -- 8.1 Introduction 141 -- 8.2 Network Architecture 145 -- 8.3 User Equipment 145 -- 8.4 eNodeB 145 -- 8.5 Radio Access Network 146 -- 8.5.1 Gateways and Mobility Management Entities 146 -- 8.6 Evolved Packet Core (EPC) 147 -- 8.7 The Innovative Technologies 148 -- 8.8 PS-LTE and Public Safety 151 -- 8.9 PS-LTE 152 -- 8.10 Nationwide Public Safety Communication Systems 152 -- 8.11 Advantages of LTE Technology 152 -- 8.12 Driving Trends in Public Safety Communications 153 -- 8.13 Benefits of PS-LTE 155 -- 8.14 Benefits of Converged Networking in Public Safety 157 -- 8.15 Mobilizing Law Enforcement 157 -- References 159 -- 9 4G and 5G for PS: Technology Options, Issues, and Challenges 161 -- 9.1 Introduction 161 -- 9.2 4G LTE and Public Safety Implementation 162 -- 9.2.1 Reliability 162 -- 9.2.2 Cost Effectiveness 163 -- 9.2.3 Real-Time Communication 164 -- 9.2.4 Remote Deployment and Configuration 164.…”