Tabla de Contenidos: “…9.2 Related Work -- 9.3 K-Means Algorithm -- 9.4 Data Partitioning -- 9.5 Experimental Results -- 9.5.1 Datasets -- 9.5.2 Performance Analysis -- 9.5.3 Approximation on Real-World Datasets -- 9.6 Conclusion -- Acknowledgments -- References -- Chapter 10 An Analysis on Detection and Visualization of Code Smells -- 10.1 Introduction -- 10.2 Literature Survey -- 10.2.1 Machine Learning-Based Techniques -- 10.2.2 Code Smell Characteristics in Different Computer Languages -- 10.3 Code Smells -- 10.4 Comparative Analysis -- 10.5 Conclusion -- References -- Chapter 11 Leveraging Classification Through AutoML and Microservices -- 11.1 Introduction -- 11.2 Related Work -- 11.3 Observations -- 11.4 Conceptual Architecture -- 11.5 Analysis of Results -- 11.6 Results and Discussion -- References -- Part III: E-Learning Applications -- Chapter 12 Virtual Teaching Activity Monitor -- 12.1 Introduction -- 12.2 Related Works -- 12.3 Methodology -- 12.3.1 Head Movement -- 12.3.2 Drowsiness and Yawn Detection -- 12.3.3 Attendance System -- 12.3.4 Network Speed -- 12.3.5 Text Classification -- 12.4 Results and Discussion -- 12.5 Conclusions -- References -- Chapter 13 AI-Based Development of Student E-Learning Framework -- 13.1 Introduction -- 13.2 Objective -- 13.3 Literature Survey -- 13.4 Proposed Student E-Learning Framework -- 13.5 System Architecture -- 13.6 Working Module Description -- 13.6.1 Data Preprocessing -- 13.6.2 Driving Test Cases -- 13.6.3 System Analysis -- 13.7 Conclusion -- 13.8 Future Enhancements -- References -- Part IV: Networks Application -- Chapter 14 A Comparison of Selective Machine Learning Algorithms for Anomaly Detection in Wireless Sensor Networks -- 14.1 Introduction -- 14.1.1 Data Aggregation in WSNs -- 14.1.2 Anomalies -- 14.2 Anomaly Detection in WSN -- 14.2.1 Need for Anomaly Detection in WSNs…”

“…Providing themost current coverage of topics and applications, the book is paired withextensive traditional supplements as well as Jupyter Notebooks supplements.Real-world datasets and artificial-intelligence technologies allow students towork on projects making a difference in business, industry, government andacademia. …”

“…Following expert instruction from Swagger core contributor Josh Ponelat and API consultant Lukas Rosenstock, you'll spend each chapter progressively expanding the kind of APIs you'll want to build in the real world. You'll utilize OpenAPI and Swagger to help automate your workflow, and free up your time to work on more exciting features. …”

“…Common problems and pitfalls, based on real-world experiences, are discussed and solutions provided. …”

“…The focus is to portray and present recent developments in the areas where nature- inspired algorithms are specifically designed and applied to solve complex real-world problems in data analytics and pattern recognition, by means of domain-specific solutions. …”

Tabla de Contenidos: “…7.4.2 Smart Energy Trial Observations -- 7.4.3 General Observation -- 7.5 Conclusion -- Acknowledgments -- References -- Chapter 8 - BonFIRE: A Multi-Cloud Experimentation-as-a-Service Ecosystem -- 8.1 Introduction -- 8.2 A Cloud and Services Experimentation Service -- 8.3 Technical Approach -- 8.4 Federation of Heterogeneous Cloud and Networking Testbeds -- 8.5 Federation within the Broader FIRE Ecosystem -- 8.6 Pioneering Open Access Experimentation and Sustainability -- 8.7 Conclusions and Outlook -- Acknowledgements -- Chapter 9 - EXPERIMEDIA - A Multi-Venue Experimentation Service Supporting Technology Innovation through New Forms of Social Interaction and User Experience -- 9.1 Introduction -- 9.2 Networked Multimedia Systems -- 9.3 A Multi-Venue Media Experimentation Service -- 9.4 Smart Venues and Experiments -- 9.5 Users at the Heart of the System -- 9.6 Making a Difference in the Real-World -- 9.7 Real-Time Interactive and Immersive Media -- 9.8 Economic and Social Viability of Data Value Chains -- 9.9 Innovation whilst Respecting Privacy -- 9.10 Conclusions -- Acknowledgements -- References -- Chapter 10 - Cross-Domain Interoperability Using Federated Interoperable SemanticIoT/C loud Testbeds and Applications: The FIESTA-IoT Approach -- 10.1 Introduction -- 10.2 Federated IoT Testbeds and Deployment of Experimental Facilities -- 10.3 Cross-Domain Interoperability -- 10.4 Experimentation as a Service -- 10.5 IoT Data Marketplace -- 10.6 FIESTA Platform Services and Tools -- 10.6.1 FIESTA Approach on Global Market Confidence Programme on Interoperability Service -- 10.6.2 FIESTA Approach on Linking and Reasoning over IoT Data Streams Services -- 10.6.3 FIESTA Approach on Federating IoT Stream Data Management Services -- 10.6.4 FIESTA Approach on Semantic Interoperability for IoT/Cloud Data Streams Tools…”

“…Readers will learn about the evolution of network routing, the role of IP and E.164 addressing and traffic engineering in routing, the impact on router and switching architectures and their design, deployment of network routing protocols, and lessons learned from implementation and operational experience. Numerous real-world examples bring the material alive. Extensive coverage of routing in the Internet, from protocols (such as OSPF, BGP), to traffic engineering, to security issues A detailed coverage of various router and switch architectures, IP lookup and packet classification methods A comprehensive treatment of circuit-switched routing and optical network routing New topics such as software-defined networks, data center networks, multicast routing Bridges the gap between theory and practice in routing, including the fine points of implementation and operational experience Accessible to a wide audience due to its vendor-neutral approach…”

Tabla de Contenidos: “…References -- Chapter 4 New Age Teaching Pedagogy: Innovative Teaching Methods and their Impact on Educational Performance of the Students -- 4.1 Introduction -- 4.2 Teaching Pedagogy -- 4.3 Teacher Education in India -- 4.4 Modern Innovative Teaching Pedagogy -- 4.5 New Age Teaching Pedagogy: Need of the Hour -- 4.5.1 Transition -- 4.5.2 Technology -- 4.5.3 Innovative Tools -- 4.5.4 Training -- 4.5.5 Touch -- 4.6 Modern New Age Teaching Pedagogy -- 4.6.1 Learning by Design -- 4.6.2 Constructivism -- 4.6.3 Interactive Learning Environment -- 4.6.4 Collaborative Learning Environment -- 4.6.5 Spaced Learning Environment -- 4.6.6 Flipped Classroom Learning -- 4.6.7 Self-Learning -- 4.6.8 Gamification -- 4.6.9 Real-World Learning -- 4.6.10 Relationship Learning -- 4.6.11 Cross-Over Teaching and Learning -- 4.7 Modern Innovative Tools -- 4.7.1 Multimedia Learning -- 4.7.2 Mind Mapping -- 4.7.3 Chunking Strategy Learning -- 4.7.4 Virtual Reality Learning -- 4.7.5 Z to A Learning -- 4.7.6 Mnemonics Approach -- 4.7.7 Role Play -- 4.8 Conclusion -- References -- Chapter 5 Efficacy of V-Lab for Engineering Students during COVID-19 -- 5.1 Introduction -- 5.2 Materials and Methods: Sources and Importance of E-Learning and E-Teaching -- 5.2.1 Digital Platforms for Online Teaching -- 5.2.2 Virtual Platforms for Conducting Laboratory Online -- 5.2.2.1 Virtual Lab: An MHRD Initiative -- 5.2.2.2 Biotechnology and Biomedical Engineering Virtual Labs -- 5.2.2.3 Virtual Lab for Computer Science -- 5.2.3 Collaborative Learning Environs and Computer Models -- 5.2.3.1 OLabs -- 5.3 Undergraduate Responses to COVID-19 Pandemic Crisis in India -- 5.4 Methodology -- 5.4.1 Objectives -- 5.4.2 Hypotheses -- 5.4.3 Research Design -- 5.4.4 Data Collection -- 5.4.5 Data Description and Sampling Plan…”

“…"This book introduces novel algorithms and solutions to real-world problems under the umbrella of cyberphysical systems. …”

“…You'll explore interesting real-world datasets like Google's daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow. …”

“…The main goal of the book is to provide a comprehensive and accessible guide that empowers readers to understand, apply, and leverage machine learning algorithms and techniques effectively in real-world scenarios. Welcome to the exciting world of machine learning! …”

“…It comprehensively explores real-world applications, demonstrating how various operations' research techniques enhance edge computing's efficiency, reliability and resource allocation. …”

“…The authors have used their extensive real-world work experience in talent acquisition, and human resource development and retention to provide an examination of all major concepts of human resource management in a lucid and engaging manner. …”

“…Theory is accompanied by numerical modeling algorithms and illustrative computational examples that range from academic to full real-world scenarios. Covers both deterministic and stochastic modeling Presents implementations of integral equation approaches, overcoming the limitations of the FDTD approach Presents various biomedical applications…”

Tabla de Contenidos: “…3.1 The State Perspective -- 3.2 The Perspective of the Protection Seeker -- 3.2.1 Access to Territory -- 3.2.2 Access to FulI-fledged Procedures -- 3.2.3 Access to Protection -- 3.3 Two Loops -- 4 EUROPEAN INTEGRATION AND EXTRATERRITORIAL PROTECTION -- 4.1. The Real World: Flight Movements to and within Europe since 1985 -- 4.2 The Institutional World: From Schengen to Amsterdam -- 4.2.1 Freedom through Control: The 1985 White Paper and the Single European Act4.2.1 Freedom through Control: The 1985 White Paper and the Single European Act -- 4.2.2 L'Europe acceleree: Schengen4.2.2 L'Europe acceleree: Schengen -- 4.2.3 Trying to Catch Up: The European Political Cooperation -- 4.2.3.1 The Dublin Convention -- 4.2.3.2 The Draft External Border Convention -- 4.2.3.3 Enter Soft Law: The London Resolutions -- 4.2.3.4 Swapping Information: CIREA and CIREFI -- 4.2.4 Maastricht-Progress through Split Competencies? …”

Tabla de Contenidos: “…-- 3.6 Insights to Digital Twin Technology Concept -- 3.6.1 Parts Twins -- 3.6.2 Product Twins -- 3.6.3 System Twins -- 3.6.4 Process Twins -- 3.7 Types of Digital Twin -- 3.7.1 Digital Twin Prototype (DTP) -- 3.7.2 Digital Twin Instance (DTI) -- 3.7.3 Digital Twin Environment (DTE) -- 3.8 Traits of Digital Twin -- 3.8.1 Look Same as the Original Object -- 3.8.2 Consists Different Details of the Original Object -- 3.8.3 Behaves Same as the Original Object -- 3.8.4 Can Predict and Inform in Advance About Problems That Could Occur -- 3.9 Value of Digital Twin -- 3.10 Advantages of Digital Twin -- 3.11 Real-World Examples of Use of Digital Twin -- 3.12 Conclusion -- References -- Chapter 4 Digital Twin Solution Architecture -- 4.1 Introduction -- 4.2 Previous Work -- 4.2.1 How This Work Differs -- 4.3 Use Cases -- 4.4 Architecture Considerations -- 4.5 Understanding the Physical Object -- 4.5.1 Modeling Considerations -- 4.6 Digital Twin and IoT -- 4.7 Digital Twin Solution Architecture -- 4.7.1 Conceptual Digital Twin Solution Architecture -- 4.7.2 Infrastructure Platform and IoT Services -- 4.7.3 Digital Twin Data and Process Model -- 4.7.4 Digital Twin Services -- 4.7.5 Digital Twin Applications -- 4.7.6 Sample Basic Data Flow through Digital Twin…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgements -- Part 1: Fundamentals -- Chapter 1 Digital Twin Technology: Necessity of the Future in Education and Beyond -- 1.1 Introduction -- 1.2 Digital Twins in Education -- 1.2.1 Virtual Reality for Immersive Learning -- 1.2.2 Delivery of Remote Education -- 1.2.3 Replication of Real-World Scenarios -- 1.2.4 Promote Intelligences and Personalization -- 1.3 Examples and Case Studies -- 1.3.1 Examples of DTT in Education -- 1.3.2 Digital Twin-Based Educational Systems -- 1.4 Discussion -- 1.5 Challenges and Limitations -- 1.5.1 Technical Challenges -- 1.5.2 Pedagogical Challenges -- 1.5.3 Ethical and Privacy Concerns -- 1.5.4 Future Research Directions -- 1.6 Conclusion -- References -- Chapter 2 An Intersection Between Machine Learning, Security, and Privacy -- 2.1 Introduction -- 2.2 Machine Learning -- 2.2.1 Overview of Machine Learning -- 2.2.2 Machine Learning Stages: Training and Inference -- 2.3 Threat Model -- 2.3.1 Attack Model of Machine Learning -- 2.3.2 Trust Model -- 2.3.3 Machine Learning Capabilities in a Differential Environment -- 2.3.4 Opposite Views of Machine Learning in Security -- 2.4 Training in a Differential Environment -- 2.4.1 Achieving Integrity -- 2.5 Inferring in Adversarial Attack -- 2.5.1 Combatants in the White Box Model -- 2.5.2 Insurgencies in the Black Box Model -- 2.6 Machine Learning Methods That Are Sustainable, Private, and Accountable -- 2.6.1 Robustness of Models to Distribution Drifts -- 2.6.2 Learning and Inferring With Privacy -- 2.6.3 Fairness and Accountability in Machine Learning -- 2.7 Conclusion -- References -- Chapter 3 Decentralized, Distributed Computing for Internet of Things-Based Cloud Applications -- 3.1 Introduction to Volunteer Edge Cloud for Internet of Things Utilising Blockchain…”

“…In addition, the book presents AI solutions for hospital management during an epidemic or pandemic, along with real-world solutions and case studies of successful measures to support different types of communities…”

“…Apache Airflow provides a single customizable environment for building and managing data pipelines, eliminating the need for a hodgepodge collection of tools, snowflake code, and homegrown processes. Using real-world scenarios and examples, Data Pipelines with Apache Airflow teaches you how to simplify and automate data pipelines, reduce operational overhead, and smoothly integrate all the technologies in your stack. about the technology Data pipelines manage the flow of data from initial collection through consolidation, cleaning, analysis, visualization, and more. …”

“…It bridges the gap between the theoretical and practical by giving pragmatic solutions using components that are available in the real world from distributors. The book does not just give a design with a transfer function; instead, it provides design tools based on transfer function, getting you to a working circuit so you can make the right decision on which op amp is best for the job at hand. …”