Allgemein
Green Internet of Things and Machine Learning
HEALTH ECONOMICS AND FINANCINGENCAPSULATES DIFFERENT CASE STUDIES WHERE GREEN-IOT AND MACHINE LEARNING CAN BE USED FOR MAKING SIGNIFICANT PROGRESS TOWARDS IMPROVISING THE QUALITY OF LIFE AND SUSTAINABLE ENVIRONMENT.The Internet of Things (IoT) is an evolving idea which is responsible for connecting billions of devices that acquire, perceive, and communicate data from their surroundings. Because this transmission of data uses significant energy, improving energy efficiency in IOT devices is a significant topic for research. The green internet of things (G-IoT) makes it possible for IoT devices to use less energy since intelligent processing and analysis are fundamental to constructing smart IOT applications with large data sets. Machine learning (ML) algorithms that can predict sustainable energy consumption can be used to prepare guidelines to make IoT device implementation easier. Green Internet of Things and Machine Learning lays the foundation of in-depth analysis of principles of Green-Internet of Things (G-IoT) using machine learning. It outlines various green ICT technologies, explores the potential towards diverse real-time areas, as well as highlighting various challenges and obstacles towards the implementation of G-IoT in the real world. Also, this book provides insights on how the machine learning and green IOT will impact various applications: It covers the Green-IOT and ML-based smart computing, ML techniques for reducing energy consumption in IOT devices, case studies of G-IOT and ML in the agricultural field, smart farming, smart transportation, banking industry and healthcare. AUDIENCEThe book will be helpful for research scholars and researchers in the fields of computer science and engineering, information technology, electronics and electrical engineering. Industry experts, particularly in R&D divisions, can use this book as their problem-solving guide. ROSHANI RAUT, PHD is an associate professor in the Department of Information Technology at Pimpri Chinchwad College of Engineering, Pune University, India. She has presented and published more than 70 research communications in national/international conferences and journals and has published 13 patents.SANDEEP KAUTISH, PHD is a professor & Dean of Academics with LBEF Campus, Kathmandu Nepal. He has published more than 40 papers in international journals. ZDZISLAW POLKOWSKI, PHD is a professor in the Faculty of Technical Sciences, Jan Wyzykowski University, Polkowice, Poland. He has published more than 75 research articles in peer-reviewed journals. ANIL KUMAR, PHD is a professor of CSE and Head of Department of Information Technology, DIT University, India. He has published more than 200 research papers. CHUAN-MING LIU, PHD is a professor in the Department of Computer Science and Information Engineering (CSIE), National Taipei University of Technology (Taipei Tech), Taiwan. He has published more than 100 research article is international journals.
Smart Systems for Industrial Applications
SMART SYSTEMS FOR INDUSTRIAL APPLICATIONSTHE PRIME OBJECTIVE OF THIS BOOK IS TO PROVIDE AN INSIGHT INTO THE ROLE AND ADVANCEMENTS OF ARTIFICIAL INTELLIGENCE IN ELECTRICAL SYSTEMS AND FUTURE CHALLENGES.The book covers a broad range of topics about AI from a multidisciplinary point of view, starting with its history and continuing on to theories about artificial vs. human intelligence, concepts, and regulations concerning AI, human-machine distribution of power and control, delegation of decisions, the social and economic impact of AI, etc. The prominent role that AI plays in society by connecting people through technologies is highlighted in this book. It also covers key aspects of various AI applications in electrical systems in order to enable growth in electrical engineering. The impact that AI has on social and economic factors is also examined from various perspectives. Moreover, many intriguing aspects of AI techniques in different domains are covered such as e-learning, healthcare, smart grid, virtual assistance, etc. AUDIENCEThe book will be of interest to researchers and postgraduate students in artificial intelligence, electrical and electronic engineering, as well as those engineers working in the application areas such as healthcare, energy systems, education, and others. C. VENKATESH, PHD is Professor and Principal, Sengunthar Engineering College, India, and has 28 years of teaching experience. He has published 5 patents, about 80 research papers in international journals, and about 70 papers in international and national conferences.N. RENGARAJAN, PHD is Professor and Principal, Nandha Engineering College, India and has more than three decades of experience. He has published 8 patents, 70 papers in international journals, and 20 papers in national and international conferences. P. PONMURUGAN, PHD is an associate professor, Sri Krishna College of Technology, India has almost a decade of experience in academics. He has published 11 patents and about 40 papers in international journals and conferences. He was awarded the “Best Young Engineer” by IEI – Erode Local Centre and “Young Scientist” by the International Association of Research and Developed Organization (IARDO). S. BALAMURUGAN, PHD, SMIEEE and ACM Distinguished Speaker, received his PhD from Anna University, India. He has published 57 books, 300+ international journals/conferences, and 100 patents. He is the Director of the Albert Einstein Engineering and Research Labs. He is also the Vice-Chairman of the Renewable Energy Society of India (RESI). He is serving as a research consultant to many companies, startups, SMEs, and MSMEs. He has received numerous awards for research at national and international levels.
Kompatibilitätsverfahren für Profinet-Hardware mit Ethernet Time Sensitive Networks
Die Vernetzung von industriellen Produktionssystemen soll in Zukunft auf Basis von Ethernet Time Sensitive Networks (TSN) umgesetzt werden. Die Einführung einer neuen Netzwerktechnik in die Feldebene der industriellen Produktion stellt jedoch eine besondere Herausforderung dar, da neben Netzwerkfunktionen eine echtzeitfähige Implementierung von Protokollen und spezifischen Anwendungen in die Feldgeräte erforderlich ist. Bei häufig geringen Stückzahlen der anwendungsspezifischen Geräte sind derartige Neuentwicklungen häufig wirtschaftlich nicht tragbar. Migrationsstrategien kommt daher eine entsprechend große Bedeutung zu.Die Forschungsfrage dieser Arbeit lautet: Wie können bestehende Geräte des Echtzeit-Ethernet-Systems PROFINET mit den geforderten Funktions- und Leistungsmerkmalen wie Zeitsynchronisation und synchronisierte Kommunikation kompatibel mit Ethernet TSN-Netzwerken genutzt werden? Der Autor entwickelte Kompatibilitätsverfahren, mit denen dies möglich wird. Das zentrale Kompatibilitätsverfahren ist der Ethernet TSN-kompa¬tible Bridging-Modus Time Aware Forwarding (TAF), der zeitgesteuerte Kommunikation auf der Basis der Empfangszeit zeitrichtig weiterleitet und per Softwareupdate auf bestehender PROFINET-Hardware implementiert werden kann. Diese Geräte können damit in TSN-Netzwerke integriert werden und synchronisierte Kommunikation mit einem Jitter kleiner als 1 µs nutzen.SEBASTIAN SCHRIEGEL absolvierte eine Berufsausbildung als Kommunikationselektroniker und studierte anschließend an der Technischen Hochschule Ostwestfalen-Lippe Elektrotechnik (Dipl.-Ing. FH) und Mechatronische Systeme (M.Sc.). Er arbeitet bei Fraunhofer IOSB-INA in Lemgo und schloss 2021 eine Promotion an der Universität Bielefeld (Dr.-Ing.) ab.Einleitung.- Entwicklung der industriellen Kommunikation und der Anforderungen.- Stand der Wissenschaft und Technik.- Analyse der Kompatibilität von Ethernet TSN und PROFINET-Hardware.- Kompatibilitätsverfahren.- Validierung der Verfahren.- Zusammenfassung und Bewertung.
Intelligent Systems for Rehabilitation Engineering
INTELLIGENT SYSTEMS FOR REHABILITATION ENGINEERINGENCAPSULATES DIFFERENT CASE STUDIES WHERE TECHNOLOGY CAN BE USED AS ASSISTIVE TECHNOLOGY FOR THE PHYSICALLY CHALLENGED, VISUALLY AND HEARING IMPAIRED. Rehabilitation engineering includes the development of technological solutions and devices to assist individuals with disabilities, while also supporting the recovery of the disabled who have lost their physical and cognitive functions. These systems can be designed and built to meet a wide range of needs that can help individuals with mobility, communication, vision, hearing, and cognition. The growing technological developments in machine learning, deep learning, robotics, virtual intelligence, etc., play an important role in rehabilitation engineering. Intelligent Systems for Rehabilitation Engineering focuses on trending research of intelligent systems in rehabilitation engineering which involves the design and development of innovative technologies and techniques including rehabilitation robotics, visual rehabilitation, physical prosthetics, brain computer interfaces, sensory rehabilitation, motion rehabilitation, etc. This groundbreaking book* Provides a comprehensive reference covering different computer assistive techniques for the physically disabled, visually and hearing impaired.* Focuses on trending research of intelligent systems in rehabilitation engineering which involves the design and development of innovative technologies and techniques.* Provides insights into the role of intelligent systems in rehabilitation engineering.AUDIENCEEngineers and device manufacturers working in rehabilitation engineering as well as researchers in computer science, artificial intelligence, electronic engineering, who are working on intelligent systems. ROSHANI RAUT, PHD is an associate professor in the Department of Information Technology at Pimpri Chinchwad College of Engineering, Pune University, India. She has presented and published more than 70 research communications in national/ international conferences and journals and has published 13 patents.PRANAV D. PATHAK, PHD from Visveswaraya National Institute of Technology, Nagpur, India. He is currently an assistant professor at MIT School of Bioengineering Sciences & Research, Pune. SANDEEP KAUTISH, PHD in Computer Science on Intelligent Systems in Social Networks is Professor & Dean of Academics with LBEF Campus, Kathmandu Nepal. He has published more than 40 papers in international journals. PRADEEP N., PHD is an associate professor in Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Karnataka, India. He has a number of edited books and journal research articles to his credit.
SAP Enterprise Portfolio and Project Management
Learn the fundamentals of SAP Enterprise Project and Portfolio management Project Systems (PS), Portfolio and Project Management (PPM) and Commercial Project Management (CPM) and their integration with other SAP modules. This book covers various business scenarios from different industries including the public sector, engineering and construction, professional services, telecom, mining, chemical, and pharmaceutical. Author Joseph Alexander Soosaimuthu will help you understand common business challenges and pain areas faced in portfolio, program and project management, and will provide suitable recommendations to overcome these challenges. This book not only suggests solutions within SAP, but also provides workarounds or integrations with third-party tools based on various Industry-specific business requirements. SAP Portfolio and Project Management addresses commonly asked questions regarding SAP EPPM implementation and deployment, and conveys a framework to facilitate engagement and discussion with key stakeholders. This provides coverage of SAP on-premise solutions with ECC 6.08 and SAP PPM 6.1 deployed on the same client, as well as S/4 HANA On-Premise 2020 with integration to BPC and BI/W systems. Interface with other third-party schedule management, estimation, costing and forecasting applications are also covered in this book. After completing SAP Portfolio and Project Management, you will be able to implement SAP Enterprise Portfolio and Project Management based on industry best practices. For your reference, you’ll also gain a list of development objects and a functionality list by Industry, and a Fiori apps list for Enterprise Portfolio and Project Management (EPPM). What You Will Learn * Understand the fundamentals of project, program and portfolio management within SAP EPPM * Master the art of project forecasting and scheduling integrations with other SAP modules * Gainknowledge of the different interface options for scheduling, estimation, costing and forecasting third party applications * Learn EPPM industry best practices, and how to address industry-specific business challenges * Leverage operational and strategic reporting within EPPM Who This Book For Functional consultants and business analysts who are involved in SAP EPPM (PS, PPM and CPM) deployment and clients who are interested and are in the process of having SAP EPPM deployed for their Enterprise. Chapter 1: Enterprise Project, Program and Portfolio Management – Fundamentals.- Chapter 2: SAP Enterprise Portfolio and Project Management using SAP PS, PPM and CPM.- Chapter 3: Interface with Scheduling, Estimation, Costing and Forecasting Applications.- Chapter 4: Industry Best Practices and Recommendations.- Chapter 5: Reporting and Analytics - Operational and Strategic.
Numerical Methods Using Java
Implement numerical algorithms in Java using NM Dev, an object-oriented and high-performance programming library for mathematics.You’ll see how it can help you easily create a solution for your complex engineering problem by quickly putting together classes.Numerical Methods Using Java covers a wide range of topics, including chapters on linear algebra, root finding, curve fitting, differentiation and integration, solving differential equations, random numbers and simulation, a whole suite of unconstrained and constrained optimization algorithms, statistics, regression and time series analysis. The mathematical concepts behind the algorithms are clearly explained, with plenty of code examples and illustrations to help even beginners get started.WHAT YOU WILL LEARN* Program in Java using a high-performance numerical library* Learn the mathematics for a wide range of numerical computing algorithms* Convert ideas and equations into code* Put together algorithms and classes to build your own engineering solution* Build solvers for industrial optimization problems* Do data analysis using basic and advanced statisticsWHO THIS BOOK IS FORProgrammers, data scientists, and analysts with prior experience with programming in any language, especially Java.HAKSUN LI, PHD, is founder of NM Group, a scientific and mathematical research company. He has the vision of “Making the World Better Using Mathematics”. Under his leadership, the firm serves worldwide brokerage houses and funds, multinational corporations and very high net worth individuals. Haksun is an expert in options trading, asset allocation, portfolio optimization and fixed-income product pricing. He has coded up a variety of numerical software, including SuanShu (a library of numerical methods), NM Dev (a library of numerical methods), AlgoQuant (a library for financial analytics), NMRMS (a portfolio management system for equities), and supercurve (a fixed-income options pricing system). Prior to this, Haksun was a quantitative trader/quantitative analyst with multiple investment banks. He has worked in New York, London, Tokyo, and Singapore.Additionally, Haksun is the vice dean of the Big Data Finance and Investment Institute of Fudan University, China. He was an adjunct professor with multiple universities. He has taught at the National University of Singapore (mathematics), Nanyang Technological University (business school), Fudan University (economics), as well as Hong Kong University of Science and Technology (mathematics). Dr. Haksun Li has a B.S. and M.S. in pure and financial mathematics from the University of Chicago, and an M.S. and a PhD in computer science and engineering from the University of Michigan, Ann Arbor.Table of ContentsAbout the Authors...........................................................................................................iPreface............................................................................................................................ii1. Why Java?..............................................................................................................61.1. Java in 2020.....................................................................................................61.2. Java vs. C++....................................................................................................61.3. Java vs. Python................................................................................................61.4. Java in the future .............................................................................................62. Data Structures.......................................................................................................72.1. Function...........................................................................................................72.2. Polynomial ......................................................................................................73. Linear Algebra .......................................................................................................83.1. Vector and Matrix ...........................................................................................83.1.1. Vector Properties .....................................................................................83.1.2. Element-wise Operations.........................................................................83.1.3. Norm ........................................................................................................93.1.4. Inner product and angle ...........................................................................93.2. Matrix............................................................................................................103.3. Determinant, Transpose and Inverse.............................................................103.4. Diagonal Matrices and Diagonal of a Matrix................................................103.5. Eigenvalues and Eigenvectors.......................................................................103.5.1. Householder Tridiagonalization and QR Factorization Methods..........103.5.2. Transformation to Hessenberg Form (Nonsymmetric Matrices)...........104. Finding Roots of Single Variable Equations .......................................................114.1. Bracketing Methods ......................................................................................114.1.1. Bisection Method ...................................................................................114.2. Open Methods...............................................................................................114.2.1. Fixed-Point Method ...............................................................................114.2.2. Newton’s Method (Newton-Raphson Method) .....................................114.2.3. Secant Method .......................................................................................114.2.4. Brent’s Method ......................................................................................115. Finding Roots of Systems of Equations...............................................................125.1. Linear Systems of Equations.........................................................................125.2. Gauss Elimination Method............................................................................125.3. LU Factorization Methods ............................................................................125.3.1. Cholesky Factorization ..........................................................................125.4. Iterative Solution of Linear Systems.............................................................125.5. System of Nonlinear Equations.....................................................................126. Curve Fitting and Interpolation............................................................................146.1. Least-Squares Regression .............................................................................146.2. Linear Regression..........................................................................................146.3. Polynomial Regression..................................................................................146.4. Polynomial Interpolation...............................................................................146.5. Spline Interpolation .......................................................................................147. Numerical Differentiation and Integration...........................................................157.1. Numerical Differentiation .............................................................................157.2. Finite-Difference Formulas...........................................................................157.3. Newton-Cotes Formulas................................................................................157.3.1. Rectangular Rule....................................................................................157.3.2. Trapezoidal Rule....................................................................................157.3.3. Simpson’s Rules.....................................................................................157.3.4. Higher-Order Newton-Coles Formulas..................................................157.4. Romberg Integration .....................................................................................157.4.1. Gaussian Quadrature..............................................................................157.4.2. Improper Integrals..................................................................................158. Numerical Solution of Initial-Value Problems....................................................168.1. One-Step Methods.........................................................................................168.2. Euler’s Method..............................................................................................168.3. Runge-Kutta Methods...................................................................................168.4. Systems of Ordinary Differential Equations.................................................169. Numerical Solution of Partial Differential Equations..........................................179.1. Elliptic Partial Differential Equations...........................................................179.1.1. Dirichlet Problem...................................................................................179.2. Parabolic Partial Differential Equations........................................................179.2.1. Finite-Difference Method ......................................................................179.2.2. Crank-Nicolson Method.........................................................................179.3. Hyperbolic Partial Differential Equations.....................................................1710..................................................................................................................................1811..................................................................................................................................1912. Random Numbers and Simulation ....................................................................2012.1. Uniform Distribution .................................................................................2012.2. Normal Distribution...................................................................................2012.3. Exponential Distribution............................................................................2012.4. Poisson Distribution ..................................................................................2012.5. Beta Distribution........................................................................................2012.6. Gamma Distribution ..................................................................................2012.7. Multi-dimension Distribution ....................................................................2013. Unconstrainted Optimization ............................................................................2113.1. Single Variable Optimization ....................................................................2113.2. Multi Variable Optimization .....................................................................2114. Constrained Optimization .................................................................................2214.1. Linear Programming..................................................................................2214.2. Quadratic Programming ............................................................................2214.3. Second Order Conic Programming............................................................2214.4. Sequential Quadratic Programming...........................................................2214.5. Integer Programming.................................................................................2215. Heuristic Optimization......................................................................................2315.1. Genetic Algorithm .....................................................................................2315.2. Simulated Annealing .................................................................................2316. Basic Statistics..................................................................................................2416.1. Mean, Variance and Covariance................................................................2416.2. Moment......................................................................................................2416.3. Rank...........................................................................................................2417. Linear Regression .............................................................................................2517.1. Least-Squares Regression..........................................................................2517.2. General Linear Least Squares....................................................................2518. Time Series Analysis ........................................................................................2618.1. Univariate Time Series..............................................................................2618.2. Multivariate Time Series ...........................................................................2618.3. ARMA .......................................................................................................2618.4. GARCH .....................................................................................................2618.5. Cointegration .............................................................................................2619. Bibliography .....................................................................................................2720. Index .....................................................................................................
Pro Microservices in .NET 6
Know the fundamentals of creating and deploying microservices using .NET 6 and gain insight from prescriptive guidance in this book on the when and why to incorporate them.The microservices architecture is a way of distributing process workloads to independent applications. This distribution allows for the independent applications to scale and evolve separately. It also enables developers to dismantle large applications into smaller, easier-to-maintain, scalable parts. While the return is valuable and the concept straightforward, applying it to an application is far more complicated. Where do you start? How do you find the optimal dividing point for your app, and strategically, how should your app be parceled out into separate services?PRO MICROSERVICES IN .NET 6will introduce you to all that and more. The authors get you started with an overview of microservices, .NET 6, event storming, and domain-driven design. You will use that foundational information to build a reference application throughout the book. From there, you will create your first microservice using .NET 6 that you can deploy into Docker and Azure Kubernetes Service. You will also learn about communication styles, decentralizing data, and testing microservices. Finally, you will learn about logging, metrics, tracing, and use that information for debugging.WHAT YOU WILL LEARN* Build a foundation of basic microservices architecture design* Follow an example of using event storming and domain-driven design to understand the monolithic application modified for microservices* Understand, via detailed commands, how Docker is used to containerize applications* Get an overview of creating microservices from a monolithic application* Call microservices using RPC and messaging communication styles with MassTransit* Comprehend decentralizing data and handling distributed transactions* Use Azure Kubernetes Service to host and scale your microservices* Know the methods to make your microservices more robust* Discover testing techniques for RPC and messaging communication styles* Apply the applications you build for actual use* Practice cross-cutting concerns such as logging, metrics, and tracingWHO THIS BOOK IS FORDevelopers and software architects. Readers should have basic familiarity with Visual Studio and experience with .NET, ASP.NET Core, and C#.SEAN WHITESELL is a Microsoft MVP and cloud architect at TokenEx, where he designs cloud-based architectural solutions for hosting internal services for TokenEx. He serves as President of the Tulsa Developers Association. He regularly presents in the community at developer events, conferences, and local MeetUps.ROB RICHARDSON is a software craftsman, building web properties in ASP.NET and Node, React, and Vue. He is a Microsoft MVP, published author, frequent speaker at conferences, user groups, and community events, and a diligent teacher and student of high-quality software development. You can find his recent work at robrich.org/presentations.MATTHEW D. GROVES is a Microsoft MVP who loves to code. From C# to jQuery, or PHP, he will submit pull requests for anything. He got his start writing a QuickBASIC point-of-sale app for his parent's pizza shop back in the 1990s. Currently a Product Marketing Manager for Couchbase, he is the author of the book AOP in .NET, and the video Creating and Managing Your First Couchbase Cluster.1. Introducing Microservices - Sean2. ASP.NET Core Overview- Sean3. Searching for Microservices- Sean4. First Microservice- Sean5. Microservice Messaging- Sean6. Decentralizing Data - Josh7. Testing Microservices - Sean8. Containerization - Matthew9. Healthy Microservices – Rob
Decision Intelligence For Dummies
LEARN TO USE, AND NOT BE USED BY, DATA TO MAKE MORE INSIGHTFUL DECISIONSThe availability of data and various forms of AI unlock countless possibilities for business decision makers. But what do you do when you feel pressured to cede your position in the decision-making process altogether?Decision Intelligence For Dummies pumps the brakes on the growing trend to take human beings out of the decision loop and walks you through the best way to make data-informed but human-driven decisions. The book shows you how to achieve maximum flexibility by using every available resource, and not just raw data, to make the most insightful decisions possible.In this timely book, you’ll learn to:* Make data a means to an end, rather than an end in itself, by expanding your decision-making inquiries * Find a new path to solid decisions that includes, but isn’t dominated, by quantitative data * Measure the results of your new framework to prove its effectiveness and efficiency and expand it to a whole team or company Perfect for business leaders in technology and finance, Decision Intelligence For Dummies is ideal for anyone who recognizes that data is not the only powerful tool in your decision-making toolbox. This book shows you how to be guided, and not ruled, by the data.PAM BAKERis a veteran business analyst and journalist whose work is focused on big data, artificial intelligence, machine learning, business intelligence, and data analysis. She is the author of Data Divination – Big Data Strategies.INTRODUCTION 1About This Book 2Conventions Used in This Book 3Foolish Assumptions 3What You Don’t Have to Read 4How This Book Is Organized 5Part 1: Getting Started with Decision Intelligence 5Part 2: Reaching the Best Possible Decision 5Part 3: Establishing Reality Checks 5Part 4: Proposing a New Directive 6Part 5: The Part of Tens 6Icons Used in This Book 6Beyond the Book 7Where to Go from Here 7PART 1: GETTING STARTED WITH DECISION INTELLIGENCE 9CHAPTER 1: SHORT TAKES ON DECISION INTELLIGENCE 11The Tale of Two Decision Trails 12Pointing out the way 13Making a decision 16Deputizing AI as Your Faithful Sidekick 18Seeing How Decision Intelligence Looks on Paper 20Tracking the Inverted V 21Estimating How Much Decision Intelligence Will Cost You 22CHAPTER 2: MINING DATA VERSUS MINDING THE ANSWER 25Knowledge Is Power — Data Is Just Information 26Experiencing the epiphany 26Embracing the new, not-so-new idea 28Avoiding thought boxes and data query borders 29Reinventing Actionable Outcomes 32Living with the fact that we have answers and still don’t know what to do 32Going where humans fear to tread on data 34Ushering in The Great Revival: Institutional knowledge and human expertise 36CHAPTER 3: CRYPTIC PATTERNS AND WILD GUESSES 39Machines Make Human Mistakes, Too 40Seeing the Trouble Math Makes 42The limits of math-only approaches 42The right math for the wrong question 43Why data scientists and statisticians often make bad question-makers 46Identifying Patterns and Missing the Big Picture 48All the helicopters are broken 48MIA: Chunks of crucial but hard-to-get real-world data 49Evaluating man-versus-machine in decision-making 51CHAPTER 4: THE INVERTED V APPROACH 53Putting Data First Is the Wrong Move 54What’s a decision, anyway? 55Any road will take you there 56The great rethink when it comes to making decisions at scale 57Applying the Upside-Down V: The Path to the Output and Back Again 59Evaluating Your Inverted V Revelations 60Having Your Inverted V Lightbulb Moment 61Recognizing Why Things Go Wrong 63Aiming for too broad an outcome 63Mimicking data outcomes 64Failing to consider other decision sciences 64Mistaking gut instincts for decision science 64Failing to change the culture 65PART 2: REACHING THE BEST POSSIBLE DECISION 67CHAPTER 5: SHAPING A DECISION INTO A QUERY 69Defining Smart versus Intelligent 70Discovering That Business Intelligence Is Not Decision Intelligence 71Discovering the Value of Context and Nuance 72Defining the Action You Seek 73Setting Up the Decision 74Decision science versus data science 75Framing your decision 77Heuristics and other leaps of faith 78CHAPTER 6: MAPPING A PATH FORWARD 81Putting Data Last 82Recognizing when you can (and should) skip the data entirely 83Leaning on CRISP-DM 84Using the result you seek to identify the data you need 85Digital decisioning and decision intelligence 85Don’t store all your data — know when to throw it out 87Adding More Humans to the Equation 88The shift in thinking at the business line level 90How decision intelligence puts executives and ordinary humans back in charge 92Limiting Actions to What Your Company Will Actually Do 94Looking at budgets versus the company will 95Setting company culture against company resources 98Using long-term decisioning to craft short-term returns 99CHAPTER 7: YOUR DI TOOLBOX 101Decision Intelligence Is a Rethink, Not a Data Science Redo 102Taking Stock of What You Already Have 103The tool overview 104Working with BI apps 105Accessing cloud tools 106Taking inventory and finding the gaps 107Adding Other Tools to the Mix 108Decision modeling software 109Business rule management systems 110Machine learning and model stores 110Data platforms 112Data visualization tools 112Option round-up 113Taking a Look at What Your Computing Stack Should Look Like Now 113PART 3: ESTABLISHING REALITY CHECKS 115CHAPTER 8: TAKING A BOW: GOODBYE, DATA SCIENTISTS — HELLO, DATA STRATEGISTS 117Making Changes in Organizational Roles 118Leveraging your current data scientist roles 120Realigning your existing data teams 121Looking at Emerging DI Jobs 122Hiring data strategists versus hiring decision strategists 125Onboarding mechanics and pot washers 127The Chief Data Officer’s Fate 127Freeing Executives to Lead Again 129CHAPTER 9: TRUSTING AI AND TACKLING SCARY THINGS 131Discovering the Truth about AI 132Thinking in AI 133Thinking in human 136Letting go of your ego 137Seeing Whether You Can Trust AI 138Finding out why AI is hard to test and harder to understand 140Hearing AI’s confession 142Two AIs Walk into a Bar 144Doing the right math but asking the wrong question 146Dealing with conflicting outputs 147Battling AIs 148CHAPTER 10: MEDDLING DATA AND MINDFUL HUMANS 151Engaging with Decision Theory 152Working with your gut instincts 153Looking at the role of the social sciences 155Examining the role of the managerial sciences 156The Role of Data Science in Decision Intelligence 157Fitting data science to decision intelligence 157Reimagining the rules 159Expanding the notion of a data source 161Where There’s a Will, There’s a Way 163CHAPTER 11: DECISIONS AT SCALE 165Plugging and Unplugging AI into Automation 167Dealing with Model Drifts and Bad Calls 168Reining in AutoML 170Seeing the Value of ModelOps 173Bracing for Impact 174Decide and dedicate 174Make decisions with a specific impact in mind 175CHAPTER 12: METRICS AND MEASURES 179Living with Uncertainty 180Making the Decision 182Seeing How Much a Decision Is Worth 185Matching the Metrics to the Measure 187Leaning into KPIs 188Tapping into change data 191Testing AI 193Deciding When to Weigh the Decision and When to Weigh the Impact 195PART 4: PROPOSING A NEW DIRECTIVE 197CHAPTER 13: THE ROLE OF DI IN THE IDEA ECONOMY 199Turning Decisions into Ideas 200Repeating previous successes 201Predicting new successes 202Weighing the value of repeating successes versus creating new successes 202Leveraging AI to find more idea patterns 203Disruption Is the Point 205Creative problem-solving is the new competitive edge 205Bending the company culture 207Competing in the Moment 207Changing Winds and Changing Business Models 209Counting Wins in Terms of Impacts 210CHAPTER 14: SEEING HOW DECISION INTELLIGENCE CHANGES INDUSTRIES AND MARKETS 213Facing the What-If Challenge 214What-if analysis in scenarios in Excel 216What-if analysis using a Data Tables feature 217What-if analysis using a Goal Seek feature 218Learning Lessons from the Pandemic 220Refusing to make decisions in a vacuum 221Living with toilet paper shortages and supply chain woes 222Revamping businesses overnight 224Seeing how decisions impact more than the Land of Now 226Rebuilding at the Speed of Disruption 228Redefining Industries 230CHAPTER 15: TRICKLE-DOWN AND STREAMING-UP DECISIONING 231Understanding the Who, What, Where, and Why of Decision-Making 232Trickling Down Your Upstream Decisions 234Looking at Streaming Decision-Making Models 236Making Downstream Decisions 238Thinking in Systems 240Taking Advantage of Systems Tools 241Conforming and Creating at the Same Time 244Directing Your Business Impacts to a Common Goal 245Dealing with Decision Singularities 246Revisiting the Inverted V 248CHAPTER 16: CAREER MAKERS AND DEAL-BREAKERS 251Taking the Machine’s Advice 252Adding Your Own Take 255Mastering your decision intelligence superpowers 257Ensuring that you have great data sidekicks 257The New Influencers: Decision Masters 259Preventing Wrong Influences from Affecting Decisions 262Bad influences in AI and analytics 262The blame game 265Ugly politics and happy influencers 266Risk Factors in Decision Intelligence 268DI and Hyperautomation 270PART 5: THE PART OF TENS 273CHAPTER 17: TEN STEPS TO SETTING UP A SMART DECISION 275Check Your Data Source 275Track Your Data Lineage 276Know Your Tools 277Use Automated Visualizations 278Impact = Decision 279Do Reality Checks 280Limit Your Assumptions 280Think Like a Science Teacher 281Solve for Missing Data 282Partial versus incomplete data 282Clues and missing answers 282Take Two Perspectives and Call Me in the Morning 283CHAPTER 18: BIAS IN, BIAS OUT (AND OTHER PITFALLS) 285A Pitfalls Overview 285Relying on Racist Algorithms 286Following a Flawed Model for Repeat Offenders 287Using A Sexist Hiring Algorithm 287Redlining Loans 287Leaning on Irrelevant Information 288Falling Victim to Framing Foibles 288Being Overconfident 288Lulled by Percentages 289Dismissing with Prejudice 289Index 291
Army of Metalloids
ABOUT THE BOOK:Who will win the race? Humans or Artificial Intelligence? Memory, problem-solving, learning, planning, language, reasoning, and perception are all cognitive functions that artificial intelligence (AI) and human intelligence investigate. Both of these have played significant roles in advancing cultures. In terms of their distinctions, AI is a human-created innovation that is designed to perform specific activities considerably faster and with less effort. Human intelligence, on the other hand, is better at multitasking and may include emotional aspects, human contact, and self-awareness in the cognitive process. Machine intelligence is another name for AI, which was established as an academic discipline in 1956, the same year that John McCarthy invented the term "artificial intelligence."
Intelligent Renewable Energy Systems
INTELLIGENT RENEWABLE ENERGY SYSTEMSTHIS COLLECTION OF PAPERS ON ARTIFICIAL INTELLIGENCE AND OTHER METHODS FOR IMPROVING RENEWABLE ENERGY SYSTEMS, WRITTEN BY INDUSTRY EXPERTS, IS A REFLECTION OF THE STATE OF THE ART, A MUST-HAVE FOR ENGINEERS, MAINTENANCE PERSONNEL, STUDENTS, AND ANYONE ELSE WANTING TO STAY ABREAST WITH CURRENT ENERGY SYSTEMS CONCEPTS AND TECHNOLOGY.Renewable energy is one of the most important subjects being studied, researched, and advanced in today’s world. From a macro level, like the stabilization of the entire world’s economy, to the micro level, like how you are going to heat or cool your home tonight, energy, specifically renewable energy, is on the forefront of the discussion. This book illustrates modelling, simulation, design and control of renewable energy systems employed with recent artificial intelligence (AI) and optimization techniques for performance enhancement. Current renewable energy sources have less power conversion efficiency because of its intermittent and fluctuating behavior. Therefore, in this regard, the recent AI and optimization techniques are able to deal with data ambiguity, noise, imprecision, and nonlinear behavior of renewable energy sources more efficiently compared to classical soft computing techniques. This book provides an extensive analysis of recent state of the art AI and optimization techniques applied to green energy systems. Subsequently, researchers, industry persons, undergraduate and graduate students involved in green energy will greatly benefit from this comprehensive volume, a must-have for any library. AUDIENCEEngineers, scientists, managers, researchers, students, and other professionals working in the field of renewable energy. NEERAJ PRIYADARSHI, PHD, works in the Department of Energy Technology, Aalborg University, Denmark, from which he also received a post doctorate. He received his M. Tech. degree in power electronics and drives in 2010 from the Vellore Institute of Technology (VIT), Vellore, India, and his PhD from the Government College of Technology and Engineering, Udaipur, Rajasthan, India. He has published over 60 papers in scientific and technical journals and conferences and has organized several international workshops. He is a reviewer for a number of technical journals, and he is the lead editor for four edited books, including Scrivener Publishing. AKASH KUMAR BHOI, PHD, is an assistant professor in the Department of Electrical and Electronics Engineering at Sikkim Manipal Institute of Technology (SMIT), India. He is also a research associate at Wireless Networks (WN) Research Laboratory, Institute of Information Science and Technologies, National Research Council (ISTI-CRN) Pisa, Italy. He is a member of several technical associations and is an editorial board member for a number of journals. He has published several papers in scientific journals and conferences and is currently working on several edited volumes for various publishers, including Scrivener Publishing. SANJEEVIKUMAR PADMANABAN, PHD, is a faculty member with the Department of Energy Technology, Aalborg University, Esbjerg, Denmark and works with CTIF Global Capsule (CGC), Department of Business Development and Technology, Aarhus University, Denmark. He received his PhD in electrical engineering from the University of Bologna, Italy. He has almost ten years of teaching, research and industrial experience and is an associate editor on a number of international scientific refereed journals. He has published more than 300 research papers and has won numerous awards for his research and teaching. S. BALAMURUGAN is the Head of Research and Development, QUANTS IS & Consultancy Services, India. He has authored or edited 40 books, more than 200 papers in scientific and technical journals and conferences and has 15 patents to his credit. He is either the editor-in-chief, associate editor, guest editor, or editor for many scientific and technical journals, from many well-respected publishers around the world. He has won numerous awards, and he is a member of several technical societies. JENS BO HOLM-NIELSEN currently works at the Department of Energy Technology, Aalborg University and is head of the Esbjerg Energy Section. He helped establish the Center for Bioenergy and Green Engineering in 2009 and served as the head of the research group. He has served as technical advisor for many companies in this industry, and he has executed many large-scale European Union and United Nation projects. He has authored more than 300 scientific papers and has participated in over 500 various international conferences. Preface xv1 OPTIMIZATION ALGORITHM FOR RENEWABLE ENERGY INTEGRATION 1Bikash Das, SoumyabrataBarik, Debapriya Das and V Mukherjee1.1 Introduction 21.2 Mixed Discrete SPBO 51.2.1 SPBO Algorithm 51.2.2 Performance of SPBO for Solving Benchmark Functions 81.2.3 Mixed Discrete SPBO 111.3 Problem Formulation 121.3.1 Objective Functions 121.3.2 Technical Constraints Considered 141.4 Comparison of the SPBO Algorithm in Terms of CEC-2005 Benchmark Functions 171.5 Optimum Placement of RDG and Shunt Capacitor to the Distribution Network 181.5.1 Optimum Placement of RDGs and ShuntCapacitors to 33-Bus Distribution Network 251.5.2 Optimum Placement of RDGs and Shunt Capacitors to 69-Bus Distribution Network 291.6 Conclusions 33References 342 CHAOTIC PSO FOR PV SYSTEM MODELLING 41Souvik Ganguli, Jyoti Gupta and Parag Nijhawan2.1 Introduction 422.2 Proposed Method 432.3 Results and Discussions 432.4 Conclusions 72References 723 APPLICATION OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TECHNIQUES IN ISLAND DETECTION IN A SMART GRID 79Soham Dutta, Pradip Kumar Sadhu, Murthy Cherikuri and Dusmanta Kumar Mohanta3.1 Introduction 803.1.1 Distributed Generation Technology in Smart Grid 813.1.2 Microgrids 813.3.1.1 Problems with Microgrids 813.2 Islanding in Power System 823.3 Island Detection Methods 833.3.1 Passive Methods 833.3.2 Active Methods 853.3.3 Hybrid Methods 863.3.4 Local Methods 873.3.5 Signal Processing Methods 873.3.6 Classifer Methods 883.4 Application of Machine Learning and Artificial Intelligence Algorithms in Island Detection Methods 893.4.1 Decision Tree 893.4.1.1 Advantages of Decision Tree 913.4.1.2 Disadvantages of Decision Tree 913.4.2 Artificial Neural Network 913.4.2.1 Advantages of Artificial Neural Network 933.4.2.2 Disadvantages of Artificial Neural Network 933.4.3 Fuzzy Logic 933.4.3.1 Advantages of Fuzzy Logic 943.4.3.2 Disadvantages of Fuzzy Logic 943.4.4 Artificial Neuro-Fuzzy Inference System 953.4.4.1 Advantages of Artificial Neuro-Fuzzy Inference System 953.4.4.2 Disadvantages of Artificial Neuro-Fuzzy Inference System 963.4.5 Static Vector Machine 963.4.5.1 Advantages of Support Vector Machine 973.4.5.2 Disadvantages of Support Vector Machine 973.4.6 Random Forest 973.4.6.1 Advantages of Random Forest 983.4.6.2 Disadvantages of Random Forest 983.4.7 Comparison of Machine Learning and Artificial Intelligence Based Island Detection Methods with Other Methods 993.5 Conclusion 99References 1014 INTELLIGENT CONTROL TECHNIQUE FOR REDUCTION OF CONVERTER GENERATED EMI IN DG ENVIRONMENT 111Ritesh Tirole, R R Joshi, Vinod Kumar Yadav, Jai Kumar Maherchandani and Shripati Vyas4.1 Introduction 1124.2 Grid Connected Solar PV System 1134.2.1 Grid Connected Solar PV System 1134.2.2 PhotoVoltaic Cell 1144.2.3 PhotoVoltaic Array 1144.2.4 PhotoVoltaic System Configurations 1144.2.4.1 Centralized Configurations 1154.2.4.2 Master Slave Configurations 1154.2.4.3 String Configurations 1154.2.4.4 Modular Configurations 1154.2.5 Inverter Integration in Grid Solar PV System 1154.2.5.1 Voltage Source Inverter 1164.2.5.2 Current Source Inverter 1174.3 Control Strategies for Grid Connected Solar PV System 1174.3.1 Grid Solar PV System Controller 1174.3.1.1 Linear Controllers 1174.3.1.2 Non-Linear Controllers 1174.3.1.3 Robust Controllers 1184.3.1.4 Adaptive Controllers 1184.3.1.5 Predictive Controllers 1184.3.1.6 Intelligent Controllers 1184.4 Electromagnetic Interference 1184.4.1 Mechanisms of Electromagnetic Interference 1194.4.2 Effect of Electromagnetic Interference 1204.5 Intelligent Controller for Grid Connected Solar PV System 1204.5.1 Fuzzy Logic Controller 1204.6 Results and Discussion 1214.6.1 Generated EMI at the Input Side of Grid SPV System 1224.7 Conclusion 125References 1255 A REVIEW OF ALGORITHMS FOR CONTROL AND OPTIMIZATION FOR ENERGY MANAGEMENT OF HYBRID RENEWABLE ENERGY SYSTEMS 131Megha Vyas, Vinod Kumar Yadav, Shripati Vyas, R.R Joshi and Ritesh Tirole5.1 Introduction 1325.2 Optimization and Control of HRES 1345.3 Optimization Techniques/Algorithms 1355.3.1 Genetic Algorithms (GA) 1365.4 Use of Ga In Solar Power Forecasting 1405.5 PV Power Forecasting 1425.5.1 Short-Term Forecasting 1435.5.2 Medium Term Forecasting 1445.5.3 Long Term Forecasting 1445.6 Advantages 1455.7 Disadvantages 1465.8 Conclusion 146Appendix A: List of Abbreviations 146References 1476 INTEGRATION OF RES WITH MPPT BY SVPWM SCHEME 157Busireddy Hemanth Kumar and Vivekanandan Subburaj6.1 Introduction 1586.2 Multilevel Inverter Topologies 1586.2.1 Cascaded H-Bridge (CHB) Topology 1596.2.1.1 Neutral Point Clamped (NPC) Topology 1606.2.1.2 Flying Capacitor (FC) Topology 1606.3 Multilevel Inverter Modulation Techniques 1616.3.1 Fundamental Switching Frequency (FSF) 1626.3.1.1 Selective Harmonic Elimination Technique for MLIs 1626.3.1.2 Nearest Level Control Technique 1636.3.1.3 Nearest Vector Control Technique 1646.3.2 Mixed Switching Frequency PWM 1646.3.3 High Level Frequency PWM 1646.3.3.1 CBPWM Techniques for MLI 1646.3.3.2 Pulse Width Modulation Algorithms Using Space Vector Techniques for Multilevel Inverters 1676.4 Grid Integration of Renewable Energy Sources (RES) 1676.4.1 Solar PV Array 1676.4.2 Maximum Power Point Tracking (MPPT) 1696.4.3 Power Control Scheme 1706.5 Simulation Results 1716.6 Conclusion 176References 1767 ENERGY MANAGEMENT OF STANDALONE HYBRID WIND-PV SYSTEM 179Raunak Jangid, Jai Kumar Maherchandani, Vinod Kumar and Raju Kumar Swami7.1 Introduction 1807.2 Hybrid Renewable Energy System Configuration & Modeling 1807.3 PV System Modeling 1817.4 Wind System Modeling 1837.5 Modeling of Batteries 1857.6 Energy Management Controller 1867.7 Simulation Results and Discussion 1867.7.1 Simulation Response at Impulse Change in Wind Speed, Successive Increase in Irradiance Level and Impulse Change in Load 1877.8 Conclusion 193References 1948 OPTIMIZATION TECHNIQUE BASED DISTRIBUTION NETWORK PLANNING INCORPORATING INTERMITTENT RENEWABLE ENERGY SOURCES 199Surajit Sannigrahi and Parimal Acharjee8.1 Introduction 2008.2 Load and WTDG Modeling 2048.2.1 Modeling of Load Demand 2048.2.2 Modeling of WTDG 2058.3 Objective Functions 2078.3.1 System Voltage Enhancement Index (SVEI) 2088.3.2 Economic Feasibility Index (EFI) 2088.3.3 Emission Cost Reduction Index (ECRI) 2118.4 Mathematical Formulation Based on Fuzzy Logic 2128.4.1 Fuzzy MF for SVEI 2128.4.2 Fuzzy MF for EFI 2138.4.3 Fuzzy MF for ECRI 2148.5 Solution Algorithm 2158.5.1 Standard RTO Technique 2158.5.2 Discrete RTO (DRTO) Algorithm 2178.5.3 Computational Flow 2198.6 Simulation Results and Analysis 2218.6.1 Obtained Results for Different Planning Cases 2238.6.2 Analysis of Voltage Profile and Power Flow Under the Worst Case Scenarios: 2308.6.3 Comparison Between Different Algorithms 2318.6.3.1 Solution Quality 2348.6.3.2 Computational Time 2348.6.3.3 Failure Rate 2348.6.3.4 Convergence Characteristics 2348.6.3.5 Wilcoxon Signed Rank Test (WSRT) 2368.7 Conclusion 237References 2399 USER INTERACTIVE GUI FOR INTEGRATED DESIGN OF PV SYSTEMS 243SushmitaSarkar, K UmaRao, Prema V, Anirudh Sharma C A, Jayanth Bhargav and ShrikeshSheshaprasad9.1 Introduction 2449.2 PV System Design 2459.2.1 Design of a Stand-Alone PV System 2459.2.1.1 Panel Size Calculations 2469.2.1.2 Battery Sizing 2479.2.1.3 Inverter Design 2489.2.1.4 Loss of Load 2499.2.1.5 Average Daily Units Generated 2499.2.2 Design of a Grid-Tied PV System 2509.2.3 Design of a Large-Scale Power Plant 2519.3 Economic Considerations 2529.4 PV System Standards 2529.5 Design of GUI 2529.6 Results 2559.6.1 Design of a Stand-Alone System Using GUI 2559.6.2 GUI for a Grid-Tied System 2579.6.3 GUI for a Large PV Plant 2599.7 Discussions 2609.8 Conclusion and Future Scope 2609.9 Acknowledgment 261References 26110 SITUATIONAL AWARENESS OF MICRO-GRID USING MICRO-PMU AND LEARNING VECTOR QUANTIZATION ALGORITHM 267Kunjabihari Swain and Murthy Cherukuri10.1 Introduction 26810.2 Micro Grid 26910.3 Phasor Measurement Unit and Micro PMU 27010.4 Situational Awareness: Perception, Comprehension and Prediction 27210.4.1 Perception 27310.4.2 Comprehension 27410.4.3 Projection 28010.5 Conclusion 280References 28011 AI AND ML FOR THE SMART GRID 287Dr M K Khedkar and B RameshAbbreviations 28811.1 Introduction 28811.2 AI Techniques 29111.2.1 Expert Systems (ES) 29111.2.2 Artificial Neural Networks (ANN) 29111.2.3 Fuzzy Logic (FL) 29211.2.4 Genetic Algorithm (GA) 29211.3 Machine Learning (ML) 29311.4 Home Energy Management System (HEMS) 29411.5 Load Forecasting (LF) in Smart Grid 29511.6 Adaptive Protection (AP) 29711.7 Energy Trading in Smart Grid 29811.8 AI Based Smart Energy Meter (AI-SEM) 300References 30212 ENERGY LOSS ALLOCATION IN DISTRIBUTION SYSTEMS WITH DISTRIBUTED GENERATIONS 307Dr Kushal Manohar Jagtap12.1 Introduction 30812.2 Load Modelling 31112.3 Mathematicl Model 31212.4 Solution Algorithm 31712.5 Results and Discussion 31712.6 Conclusion 341References 34113 ENHANCEMENT OF TRANSIENT RESPONSE OF STATCOM AND VSC BASED HVDC WITH GA AND PSO BASED CONTROLLERS 345Nagesh Prabhu, R Thirumalaivasan and M.Janaki13.1 Introduction 34613.2 Design of Genetic Algorithm Based Controller for STATCOM 34713.2.1 Two Level STACOM with Type-2 Controller 34813.2.1.1 Simulation Results with Suboptimal Controller Parameters 34913.2.1.2 PI Controller Without Nonlinear State Variable Feedback 34913.2.1.3 PI Controller with Nonlinear State Variable Feedback 35113.2.2 Structure of Type-1 Controller for 3-Level STACOM 35413.2.2.1 Transient Simulation with Suboptimal Controller Parameters 35713.2.3 Application of Genetic Algorithm for Optimization of Controller Parameters 35713.2.3.1 Boundaries of Type-2 Controller Parameters in GA Optimization 35913.2.3.2 Boundaries of Type-1 Controller Parameters in GA Optimization 36013.2.4 Optimization Results of Two Level STATCOM with GA Optimized Controller Parameters 36013.2.4.1 Transient Simulation with GA Optimized Controller Parameters 36113.2.5 Optimization Results of Three Level STATCOM with Optimal Controller Parameters 36213.2.5.1 Transient Simulation with GA Optimized Controller Parameters 36313.3 Design of Particle Swarm Optimization Based Controller for STATCOM 36413.3.1 Optimization Results of Two Level STATCOM with GA and PSO Optimized Parameters 36513.4 Design of Genetic Algorithm Based Type-1 Controller for VSCHVDC 37113.4.1 Modeling of VSC HVDC 37113.4.1.1 Converter Controller 37413.4.2 A Case Study 37513.4.2.1 Transient Simulation with Suboptimal Controller Parameters 37613.4.3 Design of Controller Using GA and Simulation Results 37813.4.3.1 Description of Optimization Problem and Application of GA 37813.4.3.2 Transient Simulation 37913.4.3.3 Eigenvalue Analysis 37913.5 Conclusion 379References 38614 SHORT TERM LOAD FORECASTING FOR CPP USING ANN 391Kirti Pal and Vidhi Tiwari14.1 Introduction 39214.1.1 Captive Power Plant 39414.1.2 Gas Turbine 39414.2 Working of Combined Cycle Power Plant 39514.3 Implementation of ANN for Captive Power Plant 39614.4 Training and Testing Results 39714.4.1 Regression Plot 39714.4.2 The Performance Plot 39814.4.3 Error Histogram 39914.4.4 Training State Plot 39914.4.5 Comparison between the Predicted Load and Actual Load 40114.5 Conclusion 40314.6 Acknowlegdement 403References 40415 REAL-TIME EVCS SCHEDULING SCHEME BY USING GA 409Tripti Kunj and Kirti Pal15.1 Introduction 41015.2 EV Charging Station Modeling 41315.2.1 Parts of the System 41315.2.2 Proposed EV Charging Station 41415.2.3 Proposed Charging Scheme Cycle 41415.3 Real Time System Modeling for EVCS 41515.3.1 Scenario 1 41515.3.2 Design of Scenario 1 41815.3.3 Scenario 2 41915.3.4 Design of Scenario 2 42115.3.5 Simulation Settings 42215.4 Results and Discussion 42415.4.1 Influence on Average Waiting Time 42415.4.1.1 Early Morning 42515.4.1.2 Forenoon 42515.4.1.3 Afternoon 42615.4.2 Influence on Number of Charged EV 42615.5 Conclusion 428References 428About the Editors 435Index 437
Machine Learning with Dynamics 365 and Power Platform
APPLY CUTTING-EDGE AI TECHNIQUES TO YOUR DYNAMICS 365 ENVIRONMENT TO CREATE NEW SOLUTIONS TO OLD BUSINESS PROBLEMSIn Machine Learning with Dynamics 365 and Power Platform: The Ultimate Guide to Apply Predictive Analytics, an accomplished team of digital and data analytics experts delivers a practical and comprehensive discussion of how to integrate AI Builder with Dataverse and Dynamics 365 to create real-world business solutions. It also walks you through how to build powerful machine learning models using Azure Data Lake, Databricks, Azure Synapse Analytics.The book is filled with clear explanations, visualizations, and working examples that get you up and running in your development of supervised, unsupervised, and reinforcement learning techniques using Microsoft machine learning tools and technologies. These strategies will transform your business verticals, reducing costs and manual processes in finance and operations, retail, telecommunications, and manufacturing industries.The authors demonstrate:* What machine learning is all about and how it can be applied to your organization's Dynamics 365 and Power Platform Projects* The creation and management of environments for development, testing, and production of a machine learning project* How adopting machine learning techniques will redefine the future of your ERP/CRM systemPerfect for Technical Consultants, software developers, and solution architects, Machine Learning with Dynamics 365 and Power Platform is also an indispensable guide for Chief Technology Officers seeking an intuitive resource for how to implement machine learning in modern business applications to solve real-world problems.AURELIEN CLERE is a Microsoft MVP, Global Solution Architect with 10 years of experience in the Dynamics world (ERP, CRM). He is a speaker and organizes weekly webinars.VINNIE BANSAL is an independent Dynamics 365 Business Advisor. He liaises between business and IT teams and serves as technical advisor to clients in assigned subject areas. Foreword viiPreface ixAcknowledgments xiAbout the Authors xiiiCHAPTER 1: DYNAMICS 365, POWER PLATFORM, AND MACHINE LEARNING 1Introduction to Dynamics 365 1Introduction to Power Platform 6What Is Machine Learning: How Has It Evolved? 11Definition of Machine Learning 12CHAPTER 2: ARTIFICIAL INTELLIGENCE AND PRE-BUILT MACHINE LEARNING IN DYNAMICS 365 33Azure AI Platform 33Azure Machine Learning Service 41Knowledge Mining 67CHAPTER 3: ML/AI FEATURES AND THEIR APPLICATIONS IN DYNAMICS 365 71Customer Insights 71Customer Service Insights 77Sales Insights 83Product Insights 95Virtual Agent for Customer Service in Dynamics 365 96Artificial Intelligence in Power Apps with AI Builder 99What Is Mixed Reality? 102CHAPTER 4: DYNAMICS 365 AND CUSTOM ML MODELS USING AZURE ML 107Azure Machine Learning 108Azure Machine Learning Studio 115Azure Machine Learning Service 146CHAPTER 5: DEEP DIVE IN MACHINE LEARNING CUSTOM MODELS 149Azure CLI Extension 149Visual Studio Code 153CHAPTER 6: MACHINE LEARNING WITH DYNAMICS 365 USE CASES 161ML for Finance 162Demand Forecasting 190Connected Store 192ML for Human Resources Management 195Machine Learning at the Workplace 200Afterword 205Index 207
Information Organization of the Universe and Living Things
The universe is considered an expansive informational field subjected to a general organizational law. The organization of the deployment results in the emergence of an autonomous organization of spatial and material elements endowed with permanence, which are generated on an informational substratum where an organizational law is exercised at all scales. The initial action of a generating informational element produces a quantity of basic informational elements that multiply to form other informational elements that will either be neutral, constituting the basic spatial elements, or active, forming quantum elements.The neutral basic elements will form the space by a continuous aggregation and will represent the substrate of the informational links, allowing the active informational elements to communicate, in order to aggregate and organize themselves.Every active element is immersed in an informational envelope, allowing it to continue its organization through constructive communications. The organizational law engages the active quantum elements to aggregate and produce new and more complex quantum elements, then molecular elements, massive elements, suns and planets. Gravity will then be the force of attraction exerted by the informational envelopes of the aggregates depending on their mass, to develop them by acquisition of new aggregates.The organizational communication of the informational envelopes of all of the physical material elements on Earth will enable the organization of living things, with reproduction managed by communications between the informational envelopes of the elements, realizing a continuous and powerful evolution. ALAIN CARDON is Professor in Computer Science, specializing in artificial intelligence and artificial consciousness. He has retired from the LIP6 at Pierre and Marie Curie University, France, and is currently developing his research at the INSA of Rouen, in the LITIS laboratoryIntroduction ixPART 1 INFORMATIONAL GENERATION OF THE UNIVERSE 1CHAPTER 1 THE COMPUTABLE MODEL, COMPUTER SCIENCE AND PHYSICAL CONCEPTS 31.1 The Turning model 31.2 Computer science 61.3 Formation of the Universe in physical sciences 10CHAPTER 2 THE INFORMATIONAL COMPONENTS AND THE ORGANIZATIONAL LAW OF THE FORMATION OF SPACE AND THE ELEMENTS OF THE UNIVERSE 152.1 Informational model of universe generation and organizational law 152.2 The notion of generating information in the Universe 232.3 The generative informational component and the informational energy of the substrate of the Universe 342.4 The formation process of the Universe from the informational components 46CHAPTER 3 AN AGENT MODEL TO REPRESENT INFORMATIONAL COMPONENTS 533.1 Informational and control agents representing the components 533.2 The generation of atoms and molecules in the informational agent model 603.3 The formation of a hydrogen atom agent with informational agents 613.4 Formation of a helium-type atomic agent 68CHAPTER 4 THE GENERATION OF THE FIRST MOLECULES IN THE AGENT APPROACH 734.1 The informational characteristics of the system forming the molecules 734.2 Formation of simple molecules of helium hydride and dihydrogen 75CHAPTER 5 THE FORMATION OF PHYSICAL ELEMENTS IN THE AGENT APPROACH 815.1 The notion of aggregate mass 825.2 The formation of stars and galaxies by the general action of the organizational law 855.3 The informational program for the design of the universal system 94PART 2 LIFE PRODUCED BY THE ORGANIZATIONAL LAW 101INTRODUCTION TO PART 2 103CHAPTER 6 THE CHARACTERISTICS OF SCIENTIFIC THEORIES OF LIFE 1056.1 Evolution and selection: Charles Darwin’s theory of gradual evolution and the biochemical approach 1056.2 The constitution of life, from DNA to developmental biology 1106.3 Genes and their expression: an open problem 113CHAPTER 7 THE INFORMATIONAL INTERPRETATION OF THE LIVING 1197.1 Origin of the living and bifurcation of the organizational law 1207.2 Evolutionary reproduction 1337.3 Informational action of reproduction of life with morphological patterns 1407.4 The application of the organizational law in the reproduction process 1487.5 The continuous evolution of life 1557.6 The human species in the organizational evolution of life 1617.7 The informational envelope of the planet Earth today 171Conclusion 175References 177Index 179
Perceptions and Analysis of Digital Risks
The concept of digital risk, which has become ubiquitous in the media, sustains a number of myths and beliefs about the digital world. This book explores the opposite view of these ideologies by focusing on digital risks as perceived by actors in their respective contexts.Perceptions and Analysis of Digital Risks identifies the different types of risks that concern actors and actually impact their daily lives, within education or various socio-professional environments. It provides an analysis of the strategies used by the latter to deal with these risks as they conduct their activities; thus making it possible to characterize the digital cultures and, more broadly, the informational cultures at work.This book offers many avenues for action in terms of educating the younger generations, training teachers and leaders, and mediating risks. CAMILLE CAPELLE is a Lecturer in Information and Communication Sciences at the University of Bordeaux, France. She has coordinated research on perceptions held by teachers and young adolescents on digital risks and their impact on education.VINCENT LIQUETE is a Professor in Information and Communication Sciences at the University of Bordeaux, France. He has worked on information cultures and info-communication practices in various fields, including education.Foreword xiFranc MORANDIIntroduction xviiCamille CAPELLEPART 1. RISK PERCEPTIONS, EDUCATION AND LEARNING 1CHAPTER 1. DIGITAL RISKS: AN OBSTACLE OR A LEVER FOR EDUCATION? 3Camille CAPELLE1.1. Introduction 31.2. Digital risks and education: what are we talking about? 41.2.1. Digital risks 41.2.2. What are the risks in education? 81.3. Questioning perceptions of digital risks among new teachers 91.3.1. Why was this target audience chosen? 91.3.2. Methodology and data collection 101.4. Teachers’ perceptions of digital risks 111.4.1. When perceptions of risk inhibit any practice 111.4.2. When perceptions of risk freeze practices 141.4.3. When risk perceptions lead us to consider them in order to overcome them 181.5. Reflection on the role of digital risk representations in education 211.6. Conclusion 241.7. References 25CHAPTER 2. TEENAGERS FACED WITH “FAKE NEWS”: PERCEPTIONS AND THE EVALUATION OF AN EPISTEMIC RISK 27Gilles SAHUT and Sylvie FRANCISCO2.1. Introduction 272.2. Fake news: From production to reception 282.2.1. Characterizing the fake news phenomenon 292.2.2. The potential risks associated with fake news 312.2.3. The credibility of fake news 322.3. Methodological framework of the study 342.4. Results of the study 362.4.1. A heterogeneous understanding of the concept 372.4.2. A blurred perception of the goals of fake news 392.4.3. The diversity of fake news sources 402.4.4. Identifying fake news: heuristic processing and analytical strategies 422.4.5. A remote and controlled phenomenon? 452.5. Discussion of the results and reflections on media and information literacy 462.6. Conclusion 492.7. References 50CHAPTER 3. “A BIG NEBULA THAT IS A BIT SCARY” (LOUISE, TRAINEE SCHOOLTEACHER): TRAINING THROUGH/IN DIGITAL TECHNOLOGY, IN SCHOOL AND IN PROFESSIONAL TRAINING 55Anne CORDIER3.1. Social beings, above all else 573.1.1. A “fluid identity” to be grasped 573.1.2. Digital technology in the actors’ personal ecosystem 613.2. Understanding of digital technology in the classroom 623.2.1. Crystallization and awareness of issues 623.2.2. When the socio-technical framework hinders the entry of digital technology into the classroom 643.2.3. Rather modest and low-risk experiments 663.3. Teaching with and through digital technology: Constant risks 683.3.1. Tensions in the classroom 683.3.2. Tensions in training 713.3.3. Desires on both sides 733.4. Potential courses of action 763.5. References 78PART 2. RISKS IN THE LIGHT OF SOCIO-ECONOMIC ISSUES 81CHAPTER 4. TOP MANAGERS CONFRONTED WITH INFORMATION RISKS: AN EXPLORATORY STUDY WITHIN THE TELECOMMUNICATIONS SECTOR 83Dijana LEKIC, Anna LEZON-RIVIÈRE and Madjid IHADJADENE4.1. Introduction 834.2. Information risk: The conceptual field 844.3. Controlling information risks: Security policy 894.4. Information risk and management 914.5. Study methodology and the stakeholder group 934.6. Information risk: The perspective of top telecoms managers 944.6.1. Top managers as responsible for information risk management 944.6.2. Information risk management 974.6.3. Operational challenges related to the information risk management approach 1004.7. Conclusion 1044.8 Acknowledgments 1064.9. References 106CHAPTER 5. CELL PHONES AND SCAMMING RISKS IN CAMEROON: USERS’ EXPERIENCES AND SOCIO-INSTITUTIONAL RESPONSES 111Freddy TSOPFACK FOFACK and Abdel Bernazi RENGOU5.1. Introduction 1115.2. Mechanisms behind cell phone scamming in Cameroon: Exhibiting credulity 1155.2.1. Setting the scene 1165.2.2. Enticing but misleading proposals 1175.2.3. Disguised telephone number confusion 1195.3. The dynamics of cell phone use in Cameroon 1215.3.1. The Ministry of Posts and Telecommunications 1215.3.2. Agence Nationale des Technologies de l’Information et de la Communication 1225.3.3. Agence de Régulation des Télécommunications 1225.3.4. Cell phone operators 1235.3.5. The judicial system and cell phone scams 1245.3.6. Cell phone users and consumer associations 1255.4. Socio-institutional governance of cell phone use in Cameroon: Optimal or approximate mediations? 1265.4.1. Information deficit of the users 1265.4.2. Insufficient means of action 1275.4.3. Mis-selling of SIM cards by mobile operators: An “ingredient” of mobile scammers 1285.4.4. The ease of monetary transactions 1295.4.5. Technological constraints and border porosity 1295.5. Conclusion 1305.6. References 131PART 3. DIGITAL RISKS: PRACTICES AND MEDIATION 135CHAPTER 6. TOWARDS A NORMATIVE PRESCRIPTION OF INFORMATION PRACTICES ON DIGITAL SOCIAL NETWORKS: A STUDY OF DOCUMENTARY PEDAGOGICAL PROJECTS IN MIDDLE SCHOOL 137Adeline ENTRAYGUES6.1. Introduction 1376.2. Contextualization of risk 1386.3. Issues to consider 1386.4. Research objects 1396.5. Research protocol 1426.6. Risk regarding DSNs in the pedagogical approach 1446.6.1. Raising awareness of risks: An obvious approach for teacher librarians 1446.6.2. Considering the views of learners and teachers 1456.6.3. Considering the risks: Learners aware of digital dangers 1486.7. Discovering DSNs in a school context: Dealing with risks 1516.7.1. Pedagogical projects on DSNs to prevent risks: Teachers’ perspectives 1516.7.2. Overcoming risks: Learners’ perspectives 1526.8. Perspectives for an information culture 1536.8.1. Risks, standards and education 1536.8.2. A culture of information in training 1546.9. Conclusion 1556.10. References 155CHAPTER 7. MIL AS A TOOL FOR TEACHERS TO PREVENT RISK AND TRANSMIT DIGITAL CULTURE 159Julie PASCAU7.1. Studying digital technology in schools from the perspective of teachers’ representations 1597.1.1. Why be interested in representations? 1617.1.2. The social representation of digital risks through the analysis of institutional discourses 1637.2. What do digital and media literacy evoke in teachers? 1647.2.1. The weak presence of digital technology and MIL in elementary school 1657.2.2. Risks in the representations of MIL among primary school teachers 1667.2.3. A positive perception of the role of digital technology in the classroom 1697.3. The contours of media and information literacy according to teachers 1717.3.1. The objects of MIL from the discourse of primary school teachers 1727.3.2. What does digital technology mean for teachers? 1737.4. What does the requirement to transmit digital culture mean for teachers? 1787.4.1. Digital culture: A very vague concept 1787.4.2. What primary school teachers think digital literacy means 1807.5. Conclusion 1877.6. References 189Conclusion 193Camille CAPELLEPostface 197Vincent LIQUÈTEList of Authors 201Index 203
Beginning VFX with Autodesk Maya
Dive into the nuances of visual effects (VFX) design, from planning to execution, using Autodesk Maya. This book introduces the methods and techniques required for your first foray into 3D FX generation from scratch.You will start with the fundamentals of visual effects, including a history of VFX, tools and techniques for creating believable visual effects, and popular tools used in the industry. Next, you are introduced to Autodesk Maya and its various components that make it a favorite among professionals. You will learn how to create rigid body collisions and simulate realistic particles such as dust, fire, water, and more.This book also presents strategies for creating a vortex, rain, hair, fluids, and other soft body simulations and also demonstrates nature element simulations for computer-generated production.At the end of the book, there is a capstone project to make your own visual effects scene in a practical way. After going through this book, you will be able to start building computer-generated visual effects from your imagination through to production.WHAT YOU WILL LEARN* Understand the basic physics behind effect creation* Create 3D visual effects scenes from scratch* Know the details of dynamic simulation in the computer generation space using various functionalities available in Autodesk MayaWHO THIS BOOK IS FORBeginning-level users; students from the field of visual effects design, 3D modeling, and simulation; game designers; those creating computer graphics; FX artists and aspirants looking for a career in the field of 3DDR ABHISHEK KUMAR is an Apple Certified Associate, Adobe Education Trainer, and certified by Autodesk. He received a PhD in computer applications and a master’s degree in animation and computer science. He also received a post-doctoral fellowship at Imam Mohammad Ibn Saud Islamic University, Saudi Arabia.Dr Kumar is actively involved in course development in animation and design engineering for various institutions and universities. He has published a number of research papers and covered a wide range of topics in various digital scientific areas (image analysis, visual identity, graphics, digital photography, motion graphics, 3D animation, visual effects, editing, composition). He holds 10 patents in the field of AI, design, and IoT.Dr Kumar has completed professional studies related to animation, computer graphics, virtual reality, stereoscopy, filmmaking, visual effects, and photography from Norwich University of Arts, University of Edinburg, and Wizcraft MIME & FXPHD, Australia. He is passionate about the media and entertainment industry and has directed two animation short films. Dr Kumar has trained more than 100,000 students across the globe from 153 countries (top five: India, Germany, USA, Spain, Australia). His alumni have worked for national and international movies.Dr Kumar has delivered sessions for more than 100 workshops and seminars as a subject matter expert and resource person at universities, institutes, and colleges such as Delhi University, GGU Central University, Savitribai Phule University, Anna University, Rajiv Gandhi Central University, Allahabad University, Banaras Hindu University, MANNU Hyderabad, Gujrat Technological University ,TMU, GIET University, NIT’s, IIT’s, and several international institutes and universities to make career opportunities and immersive technology opportunities for educators in awareness about the future of elearning, MOOCs, virtual reality, animation design, and the VFX industry.Chapter 1: Introduction to Visual Effects• Scope of this book• Topics to be covered• The importance of Visual Effects• The need for the creation of the visual magicChapter 2: History of VFX• The Evolution of Science in visual design• The State of Art technology in the Digital EraChapter 3: Industrial application for VFX• How to approach the planning of a VFX shot• Industry practices• Software, tools, and techniques used in the rendition of the visual splendor on ScreenChapter 4: Introduction to FX in Maya• Maya Nucleus• nParticle System• Fluids• ncloth • nHairChapter 5: Working with nParticle FX• Fun with Emitter• nParticle tool• Identical object creation with InstancerChapter 6: Creating effects with Particle Emission, Fields/Solvers• Real-life simulation with Gravity• Creation of galaxy• Tinker bell magical dust particle generationChapter 7: Maya Rigid and Soft Body Systems• Introduction to Rigid Body and Constraints• Rigid & Soft Body exampleChapter 8: Working with Maya Fluids• Introduction to fluid -working with container• Working with 2D container• Working with 3D containerChapter 9: Maya Effects• Get Effect Asset Library• Collision with effects• Creating fire, fireworks, lightening, shatter, and smoke effectsChapter 10: Playing with MAYA nucleus Cloth & nConstraint• Creating nCloth• Working with passive collider• Play with nCloth Attributes• Power of nConstraints for effective and efficient simulation.Chapter 11: Working with Hair and Fur Styling• Foundation concept of hair and fur creation• Long hair creation and simulation• Maya Hair libraryChapter 12: Technical Fluid Simulation with Bifrost• Importance of Bifrost Fluids• Working with Bifrost library• Learn to compute and execute water simulation shot EfficientlyChapter 13: FX Capstone Project• Creating a 3D Scene• Integrating the 2D and the 3D worlds• Render FX scene• Conclusion
Java 17 for Absolute Beginners
Write your first code in Java 17 using simple, step-by-step examples that model real-word objects and events, making learning easy. With Java 17 for Absolute Beginners you’ll be able to pick up the concepts without fuss. It teaches Java development in language anyone can understand, giving you the best possible start.You’ll see clear code descriptions and layout so that you can get your code running as soon as possible. Author Iuliana Cosmina focuses on practical knowledge and getting you up to speed quickly—all the bits and pieces a novice needs to get started programming in Java.First, you’ll discover what type of language Java is, what it is good for, and how it is executed. With the theory out of the way, you’ll install Java, choose an editor such as IntelliJ IDEA, and write your first simple Java program. Along the way you’ll compile and execute this program so it can run on any platform that supports Java. As part of this tutorial you’ll see how to write high-quality code by following conventions and respecting well-known programming principles, making your projects more professional and efficient.Java 17 for Absolute Beginners gives you all you need to start your Java programming journey. No experience necessary. After reading this book, you'll come away with the basics to get started writing programs in Java.WHAT YOU WILL LEARN* Get started with Java 17 from scratchUse data types, operators, and the stream API * Install and use the IntelliJ IDEA and the Gradle build tool* Exchange data using the new JSON APIs * Play with images using multi-resolution APIs* Implement the publish-subscribe architectureWHO THIS BOOK IS FORThose who are new to programming and who want to start with Java.IULIANA COSMINA is currently a software engineer for NCR Edinburgh. She has been writing Java code since 2002 and contributed to various types of applications such as experimental search engines, ERPs, track and trace, and banking. During her career, she has been a teacher, a team leader, software architect, DevOps professional, and software manager. She is a Spring-certified Professional, as defined by Pivotal, the makers of Spring Framework, Boot, and other tools, and considers Spring the best Java framework to work with. When she is not programming, she spends her time reading, blogging, learning to play piano, travelling, hiking, or biking.Chapter 1: An Introduction to Java- When every version was released, how were they called and what were the particularities- What is Java, how it is executed, what type of language it is and what is it good for-Chapter 2: Preparing your development environment- Installing Java, choosing an editor, choosing a build tool-Chapter 3: Getting your feet wet- Writing a simple program, compile and execute- Adding a dependency of somebody else’s code through dependencies of existing libraries- Mention best tools for java and most used frameworks like SpringChapter 4: Java syntax- what is a package, module- class- enums- interface ( private methods & default methods)- class, constructor, methods… etc- removal of _Chapter 5: Data Types- primitive, object types (emphasis on String, Collections, Calendar API)- String – compact Strings- Collections: Immutable collections, factory methods for Collections(JEP 269)- mention Generics- optional – enhancements- threads, futures – CompletableFuture (JEP 266)Chapter 6: Operators- unary, binary, ternary, logic, and the diamond operator (used in conjunction with anonymous inner classes)Chapter 7: Controlling the flow- if, loops- try catch (try with resources with managed variables)- recursionChapter 8: The Stream API- streams , optional to Stream, enhancementsChapter 9: Debugging , testing and documenting- what is a break point- loggers : unified JVM logging (JEP 264)- mocks and stubs- jmc, jps, jcmd – JDK utilities- The new Doclet API- the JShell Command Line Tool- accessing the process API- @Deprecated enhancements (JEP 277)Chapter 10: Making your application interactive- request data with System.in- Swing- Web applications (use the new HTTP client)- JavaFX UI (JEP 253)- Internationalization (JEP 267)Chapter 11: Writing files- storing data to files, reading it from them- serialization to Binary, XML, JSON, YML (JEP290)- playing with images – multi-resolution APIChapter 12: Publish-Subscribe Framework- reactive streamsChapter 13: Garbage Collection- JEP 214,248,271,291
Azure Arc-Enabled Kubernetes and Servers
Welcome to this introductory guide to using Microsoft’s Azure Arc service, a new multi-cloud management platform that belongs in every cloud or DevOps estate. As many IT pros know, servers and Azure Kubernetes Service drive a huge amount of consumption in Azure—so why not extend familiar management tools proven in Azure to on-premises and other cloud networks? This practical guide will get you up to speed quickly, with instruction that treads light on the theory and heavy on the hands-on experience to make setting up Azure Arc servers and Kubernetes across multiple clouds a lot less complex.Azure experts and MVPs Buchanan and Joyner provide just the right amount of context so you can grasp important concepts, and get right to the business of using and gaining value from Azure Arc. If your organization has resources across hybrid cloud, multi-cloud, and edge environments, then this book is for you. You will learn how to configure and use Azure Arc to uniformly manage workloads across all of these environments.WHAT YOU WILL LEARN* Introduces the basics of hybrid, multi-cloud, and edge computing and how Azure Arc fits into that IT strategy* Teaches the fundamentals of Azure Resource Manager, setting the reader up with the knowledge needed on the technology that underpins Azure Arc* Offers insights into Azure native management tooling for managing on-premises servers and extending to other clouds* Details an end-to-end hybrid server monitoring scenario leveraging Azure Monitor and/or Azure Sentinel that is seamlessly delivered by Azure Arc* Defines a blueprint to achieve regulatory compliance with industry standards using Azure Arc, delivering Azure Policy from Azure Defender for Servers* Explores how Git and GitHub integrate with Azure Arc; delves into how GitOps is used with Azure Arc* Empowers your DevOps teams to perform tasks that typically fall under IT operations* Dives into how to best use Azure CLI with Azure ArcWHO THIS BOOK IS FORDevOps, system administrators, security professionals, and IT workers responsible for servers both on-premises and in the cloud. Some experience in system administration, DevOps, containers, and use of Git/GitHub is helpful.STEVE BUCHANAN is a Director, Azure Platform Lead & Containers Services Lead on a Cloud Transformation team with a large consulting firm. He is a 10-time Microsoft MVP, Pluralsight author, and the author of six technical books. He has presented at tech events, including DevOpsDays, Midwest Management Summit (MMS), Microsoft Ignite, BITCon, Experts Live Europe, OSCON, Inside Azure management, and user groups. He stays active in the technical community and enjoys blogging about his adventures in the world of IT at www.buchatech.com.JOHN JOYNER is Senior Director, Technology at AccountabilIT, a managed services provider of 24x7 Network Operations and Security Operations Center (NOC & SOC) services. As an Azure Solutions Architect Expert, he designs and builds modern management and security solutions based on Azure Lighthouse, Azure Arc, Azure Monitor Logs, Azure Sentinel, Azure Defender, and Microsoft Defender. John is also an authority on System Center products in private cloud and hybrid cloud environments and has been awarded Microsoft MVP 14 times. John is a retired U.S. Navy Lt. Cmdr., where he was a computer scientist, worked for NATO in Europe and was aboard an aircraft carrier in the Pacific. He is a veteran of the Persian Gulf War.1. AZURE ARC AS EXTENSION OF THE AZURE CONTROL PLANE2. AZURE RESOURCE MANAGER INSIGHTS3. AZURE MANAGEMENT INSIGHTS4. AZURE ARC SERVERS: GETTING STARTED5. AZURE ARC SERVERS: USING AT SCALE6. HYBRID SERVER MONITORING SOLUTION7. REGULATORY AND SECURITY COMPLIANCE FOR AZURE ARC SERVERS8. GITOPS INSIGHTS9. AZURE ARC ENABLED KUBERNETES: GETTING STARTED
Practical AI for Healthcare Professionals
PRACTICAL AI FOR HEALTHCARE PROFESSIONALSArtificial Intelligence (AI) is a buzzword in the healthcare sphere today. However, notions of what AI actually is and how it works are often not discussed. Furthermore, information on AI implementation is often tailored towards seasoned programmers rather than the healthcare professional/beginner coder. This book gives an introduction to practical AI in the medical sphere, focusing on real-life clinical problems, how to solve them with actual code, and how to evaluate the efficacy of those solutions. You’ll start by learning how to diagnose problems as ones that can and cannot be solved with AI. You’ll then learn the basics of computer science algorithms, neural networks, and when each should be applied. Then you’ll tackle the essential parts of basic Python programming relevant to data processing and making AI programs. The Tensorflow/Keras library along with Numpy and Scikit-Learn are covered as well.Once you’ve mastered those basic computer science and programming concepts, you can dive into projects with code, implementation details, and explanations. These projects give you the chance to explore using machine learning algorithms for issues such as predicting the probability of hospital admission from emergency room triage and patient demographic data. We will then use deep learning to determine whether patients have pneumonia using chest X-Ray images.The topics covered in this book not only encompass areas of the medical field where AI is already playing a major role, but also are engineered to cover as much as possible of AI that is relevant to medical diagnostics. Along the way, readers can expect to learn data processing, how to conceptualize problems that can be solved by AI, and how to program solutions to those problems. Physicians and other healthcare professionals who can master these skills will be able to lead AI-based research and diagnostic tool development, ultimately benefiting countless patients.Abhinav “Abhi” Suri is a current medical student at the UCLA David Geffen School of Medicine. He completed his undergraduate degree at the University of Pennsylvania with majors in Computer Science and Biology. He also completed a Masters in Public Health (in Epidemiology) at Columbia University Mailman School of Public Health. Abhihas been dedicated to exploring the intersection between computer science and medicine. As an undergraduate, he carried out and directed research on deep learning algorithms for the detection of vertebral deformities and the detection of genetic factors that increase risk of COPD. His public health research focused on opioid usage trends in NY State and the development/utilization of geospatial dashboards for monitoring demographic disease trends in the COVID-19 pandemic.Outside of classes and research, Abhi is an avid programmer and has made applications that address healthcare worker access in Tanzania, aid the discovery process for anti-wage theft cases, and facilitate access to arts classes in underfunded school districts. He also developed (and currently maintains) a popular open-source repository, Flask-Base, which has over 2,000 stars on Github. He also enjoys teaching (lectured a course on JavaScript) and writing. So far, his authored articles and videos have reached over 200,000 people across a variety of platforms.CHAPTER 1: INTRODUCTION TO AI AND FEASIBILITY· AI, ML, Big Data: What do the buzzwords mean?· Defining a problem· What can and cannot be solved· Common algorithmic alternatives· You think you need AI, now what?· Data considerations for Healthcare & Patient Privacy· Cautionary tales of AI Snake Oil in HealthcareCHAPTER 2: AI IN THEORY· Classification problems in the field of healthcare· Decision trees· Logistic regression· Support vector ,achines· Neural Networks and Deep Learning· Convolutional Neural Networks· Evaluation metrics for AI-driven diagnostic toolsCHAPTER 3: OVERVIEW OF PROGRAMMING· Introduction to Python and environment set up· Control Structures & Loops· Data structures· Functions· File I/O· Classes· Packages/Libraries· Numpy & MatplotlibCHAPTER 4: PROJECT #1 ML & DIABETES· Problem overview and why ML might be the best· Introduction to scikit-learn· Data Pre-processing· Try 1: Decision Trees· Try 2: k Nearest Neighbors· k-fold Cross Validation· TakeawaysCHAPTER 5: PROJECT #2 NEURAL NETWORKS & HEART DISEASE· Problem overview and why neural networks might work· Introduction to keras· Data Pre-processing· Model design and implementation· Measure Efficacy· TakeawaysCHAPTER 6: PROJECT #3 CNNS & BRAIN TUMOR DETECTION· Problem overview· Overview of segmentation problems and Mask-RCNN· Data Pre-processing & Working with MRI images· Data Augmentation· Model design and implementation· Measure Efficacy with Dice Score and AP metrics· TakeawaysCHAPTER 7: THE FUTURE OF HEALTHCARE AND AI· Review of book· Problems in Medical AI: Data Issues· Medical Problems waiting to be solved· Misconception of the "death" of traditional Radiology· Ethical AI in medicine· Next steps
Azure Kubernetes Services with Microservices
Design and implement scalable microservices using Azure Kubernetes Services (AKS) and other Azure Services. This book will help you understand why and when to choose microservices as a solution for modernization and how to use Azure DevOps to implement CI/CD for deploying microservices.The book starts with an introduction to the evolution to microservices and AKS along with its components. You will learn design patterns to implement microservices on AKS and understand Kubernetes as a container orchestration platform. You will go through the common errors faced in AKS-based applications and ways to handle them. You will learn error handling tips and tricks and how to design for business continuity and disaster recovery. The book discusses things you should know related to security and monitoring when working with AKS-based applications. The book presents a practical approach to set up processes for CI/CD, such as building Build and release pipelines for AKS deployment using Azure DevOps.After reading this book, you will understand design considerations for designing scalable microservices and know how to implement the design through AKS.WHAT YOU WILL LEARN* Know design patterns for microservices and how to handle failure scenarios* Be aware of architecture and design considerations* Understand container and Kubernetes architecture components* Understand security and monitoring aspects* Take a practical approach to continuous integration and continuous deliveryWHO THIS BOOK IS FORIT professionals associated with cloud computing, especially with Microsoft AzureKASAM SHAIKH is an Azure AI enthusiast, published author, global speaker, community MVP, and Microsoft Docs Contributor. He has more than 14 years of experience in the IT industry and is a regular speaker at various meetups, online communities, and international conferences on Azure and AI. He is currently working as Senior Cloud Architect for a multi-national firm where he leads multiple programs in the Practice for Microsoft Cloud Platform and Low Code. He is also a founder of the community named DearAzure-Azure INDIA (az-India) and leads the community for learning Microsoft Azure. He owns a YouTube channel and website and shares his experience over his website https://www.kasamshaikh.comSHAILESH AGASKAR has 20+ years of experience in information technology. For the last 20 years, he has been working on Microsoft technologies such as Win32 SDK using C, C++, Office 365, Azure Data Engineering & Analytics powered by Azure Cloud Platform. He has been advising customers across the globe and helping them leverage best fit technologies to drive their enterprise digital transformation journey. Microsoft Platforms & Technologies is one of the options which has been heavily leveraged by his customers. He is currently working as Chief Architect for a multi-national firm where he heads the Practice for Microsoft Cloud Platform, M365, and other technologies.CHAPTER 1: A QUICK HANDSHAKE WITH MICROSERVICES & AKSCHAPTER GOAL: This Chapter will present an overview of Microservices and AKS. This will detail down the What, Why, When for using this Architecture and Service. How they are related to each other and merits on coupling these two entities.NO OF PAGES 30 -40SUB -TOPICS1. Introduction to Microservices2. Monolith vs Microservices3. Introduction to Cloud Native4. How does Business benefit from Cloud Native Applications.5. Introduction to AKS and its componentsCHAPTER 2: ARCHITECTURE & DESIGNING CONSIDERATIONCHAPTER GOAL: This chapter will involve points to be considered while Architectural & designing Microservices with AKS based applications. Must consideration checklist, and points to be remembered while brainstorming on making designing decisions.NO OF PAGES: 30 - 40SUB - TOPICS1. Introduction to Microservices design patterns2. Design patterns to implement Microservices on AKS3. What are Containers4. Kubernetes as a container orchestration platform5. Sample application to drive the design best practices of Microservices and AKSCHAPTER 3: DEALING WITH COMMON FAILURESCHAPTER GOAL: This Chapter will help in detailing common errors faced in AKS based applications and ways to handle the same. This will cover the error handling tips & tricks.NO OF PAGES : 30 - 40SUB - TOPICS:1. Failure scenarios and how to handle them e.g. Handling node failures2. Common failures and building resiliency in Microservices using AKS and other Azure Services.3. high availability and deployment scenarios to ensure always available microservices using Azure services.4. How to design for business continuity and disaster recoveryCHAPTER 4: SECURING YOUR AKS WORKLOADSCHAPTER GOAL: This Chapter deals with setting up and configuring AKS workloads with Security aspects. Steps to keep the AKS application secure.NO OF PAGES: 30 - 40SUB - TOPICS:1. Security best practices for microservices and how to leverage AKS2. Role based access control in AKS and how to design .3. Azure Active Directory pod- managed identities3. Leverage of Azure Key Vaults and Network Security in AKS4. Azure Security Center leverage for AKSCHAPTER 5: MONITORING AKS BASED APPLICATIONChapter Goal: This Chapter will detail all required commands used for debugging and Monitoring ASK based applications. Configuring Metrics and Diagnostics for AKS.NO OF PAGES: 30 - 40SUB - TOPICS:1. Monitoring AKS cluster and microservices2. Ready and Alive probes and how to implement them3. Health and Diagnostics Metric for the Microservices and AKS4. Pod Consumption metrics and thresholds managementCHAPTER 6: CI/CD FOR AKSCHAPTER GOAL: This chapter will present with Setup process for CI/CD, like building Build, release pipelines for AKS deployment using Azure and GitHub.NO OF PAGES: 30 - 40SUB - TOPICS:1. Azure DevOps setup Microservices deployment2.CI/CD process for containers and kubernetes3. Setup of CI/CD pipelines and promotion to various environments4. Overview of testing integration.
Practical C++ Design
Go from competent C++ developer to skilled designer or architect using this book as your personal C++ design master class. Updated for the C++20 standard, this title will guide you through the design and implementation of an engaging case study that forms the backdrop for learning the art of applying design patterns and modern C++ techniques to create a high quality, robust application.Starting with a quick exploration of the requirements for building the application, you'll delve into selecting an appropriate architecture, eventually designing and implementing all of the necessary modules to meet the project’s requirements. By the conclusion of Practical C++ Design, you'll have constructed a fully functioning calculator capable of building and executing on any platform that supports both Qt and C++20. Access to the complete source code will help speed your learning.Utilize the Model-View-Controller pattern as the basis for the architecture of the calculator; the observer pattern to design an event system; the singleton pattern as you design the calculator’s central data repository, a reusable stack; the command pattern to design a command system supporting unlimited undo/redo; the abstract factory pattern to build a cross-platform plugin infrastructure for extensibility; coroutines to implement a command line interface with a lazy tokenizer; and more.After reading and using this book, you’ll have begun the transition from C++ programmer to architect.WHAT YOU WILL LEARN* Read a specification document and translate it into a practical C++ design using some of the latest language features from C++20* Understand trade-offs in selecting between alternative design scenarios* Gain practical experience in applying design patterns to realistic development scenarios* Learn how to effectively use language elements of modern C++ to create a lasting design* Develop a complete C++ program from a blank canvas through to a fully functioning, cross platform application* Read, modify, and extend existing, high quality code* Learn the fundamentals of API design, including class, module, and plugin interfacesWHO THIS BOOK IS FORThe experienced C++ developer ready to take the next step to becoming a skilled C++ designer.ADAM B. SINGER graduated first in his class at the Georgia Institute of Technology in 1999 with a bachelors degree in chemical engineering. He subsequently attended the Massachusetts Institute of Technology on a National Defense, Science, and Engineering Graduate Fellowship. He graduated from MIT with a Ph.D. in chemical engineering in 2004 after defending his thesis titled Global Dynamic Optimization. Since graduation, Adam has been a member of the research and engineering staff at an oil and gas major, where he has worked in software development, design, and project management in areas such as optimization, reservoir simulation, decision support under uncertainty, basin modeling, well log modeling, and stratigraphy. He has also served on and chaired committees designing in-house training in the areas of technical software development and computational and applied mathematics. He currently holds a research supervisory position. Adam additionally held the title of adjunct assistant professor in the Department of Computational and Applied Mathematics at Rice University from 2007-2012. In both 2006 and 2007, he taught a graduate level course, CAAM 520, on computational science. The course focused on the design and implementation of high performance parallel programs.Preface (5 pages)The preface details my motivation for writing the book, the target audience for the book, thegeneral structure of the book, and how to contact the author. Of particular importance is therationale behind choosing the case study, the target language (C++), and the GUI toolkit (Qt).Chapter 1: Defining the Case Study (6 pages)The first chapter describes, in detail, the case study to be examine in the book. The chapterdiscusses requirements in the abstract and then transitions to the calculator’s specific requirements.This sets the stage for the remainder of the book, which describes, in detail, the design andimplementation of the calculator, pdCalc, proposed in Chapter 1.1. A Brief Introduction2. A Few Words About Requirements3. Reverse Polish Notation (RPN)4. The Calculator’s Requirements5. The Source Code1The advice, information, and conclusions discussed in this book are those of the author and have not beenendorsed by, or reflect the opinions or practices of, ExxonMobil Corporation or its affiliates.5Chapter 2: Decomposition (18 pages)In this chapter, I explain the elements of a good decomposition and strategies for decomposing aproblem into manageable pieces. Subsequently, an architecture for pdCalc is selected, the calculatoris modularized, and use cases are used to develop interfaces for the high level calculator modules.The four high level modules are the stack, the command dispatcher, the user interface (subdividedinto a command line interface and a graphic user interface), and a plugin manager.1. The Elements of a Good Decomposition2. Selecting An Architecture3. Interfaces4. Assessment of Our Current Design5. Next StepsChapter 3: The Stack (20 pages)The stack is the first module discussed in detail. The stack is the fundamental data repositoryof the calculator. As part of the calculator’s design and implementation, the singleton pattern isexplored. The stack also affords the first opportunity to discuss an event system for the calculator,which provides a backdrop for exploration of the observer pattern, including the design andimplementation of reusable publisher and observer abstract classes.1. Decomposition of the Stack Module2. The Stack Class3. Adding Events4. A Quick Note on TestingChapter 4: The Command Dispatcher (32 pages)This chapter describes the design and implementation of the command dispatcher, the module ofthe calculator responsible for the creation, storage, and execution of commands. Of particular notein this chapter is the exposition on the command pattern and how it can be used to implement apractical undo/redo framework. In addition to exploring a traditional deep hierarchy method forimplementing commands, a C++11 alternative using lambda expressions and the standard functiontemplate are presented as a modern alternative design.1. The Decomposition of the Command Dispatcher2. The Command Class3. The Command Repository4. The Command Manager5. The Command Dispatcher6. Revisiting Earlier Decisions6Chapter 5: The Command Line Interface (14 pages)This chapter marks an important milestone, the creation of the first user executable program.In addition to building a simple command line interface, we’ll explore how to create an abstractsoftware interface suitable for both a command line interface and a graphical user interface. Withinthe context of the command line interface, we’ll learn techniques for simple parsing and tokenizingof input text streams.1. The User Interface Abstraction2. The Concrete CLI Class3. Tying It Together: A Working ProgramChapter 6: The Graphical User Interface (24 pages)In this chapter, we build the Qt-based graphical user interface for the calculator. Here, we’llexamine different strategies for building GUIs, abstraction of GUI elements, and modularization ofthe overall GUI design. Included in the discussion is design for the separation of on-screen widgetsfrom look-and-feel.1. Requirements2. Building GUIs3. Modularization4. A Working Program5. A Microsoft Windows Build NoteChapter 7: Plugins (38 pages)In this chapter, I describe how to build a cross-platform plugin system. This system includes theabstract interface for C++ plugins as well as the operating system specific mechanics involved withloading plugins and executing plugin functions. In the concrete case of the plugin loader, I explainthe many build tricks that can be used to handle cross-platform code and demonstrate how theabstract factory pattern provides an elegant design solution to this problem.1. What Is a Plugin?2. Problem 1: The Plugin Interface3. Problem 2: Loading Plugins4. Problem 3: Retrofitting pdCalc5. Incorporating Plugins6. A Concrete Plugin7. Next Steps7Chapter 8: New Requirements (24 pages)Any developer who has ever worked on a production software project quickly learns that newrequirements are always added late in the development cycle. In this chapter, we explore theaddition of new user requests after the original requirements have already been satisfied. Thediscussion progresses from fully implemented solutions to design only solutions to vague ideas forthe reader to explore on her own.1. Fully Designed New Features2. Designs Toward a More Useful Calculator3. Some Interesting Extensions for Self-ExplorationAppendix A: Acquiring, Building, and Executing pdCalc (4 pages)This appendix explains how to download the source code from GitHub and how to build the casestudy on Linux and Windows. Once the program is built, readers will want to execute the codeand its included test suite; execution instructions are therefore provided.1. Getting The Source Code2. Dependencies3. Building pdCalc4. Executing pdCalcAppendix B: Organization of the Source Code (6 pages)This appendix simply explains the organization of the source tree for pdCalc. This appendix isuseful for finding the locations for the source files referenced in the text.1. The src Directory2. The test DirectoryReferences (2 pages)This section lists twenty-nine references cited in the book.Index (3 pages)This section is a complete index for the book.
Hands-On Guide to AgileOps
Discover the best practices for transforming cloud and infrastructure operations by using Agile, Scrum, Kanban, Scrumban and Spotify models. This book will help you gain an in-depth understanding of these processes so that you can apply them to your own work.The book begins by offering an overview of current processes and methods used in IT Operations using ITIL and IT4IT. The Authors provide a background of the Agile, Scrum, Kanban, SaFe, Scrumban, and Spotify models used in software development. You’ll then gain in-depth guidance and best practices to implement Agile in the Operations world. You’ll see how Agile, Site Reliability Engineering and DevOps work in tandem to provide the foundation for modern day infrastructure and cloud operations. The book also offers a comparison of various agile processes and their suitability to the infrastructure and cloud operations world.After completing this is hands-on guide, you’ll know how to adopt Agile, DevOps and SRE and select the most suitable processes for your organization to achieve higher reliability, agility and lower costs while running cloud and infrastructure operations.WHAT YOU WILL LEARN* Understand how cloud computing and microservices architecture are changing operations dynamics* Understand ITIL, IT4IT, and Lean* Learn how Site Reliability Engineering, Agile and DevOps work in tandem* Leverage Agile, Scrum, Kanban, Scrumban, and Spotify models to run cloud operations* Use Site Reliability techniques along with Agile and DevOps* Study the different agile frameworks (Spotify, SAFe, LeSS, DAD, Nexus), their purpose, benefits and implementation approaches.* Learn a step-by-step process to identify and implement these frameworks in your organizationWHO THIS BOOK IS FORInfrastructure architects, DevOps architects, Agile practitioners, DevSecOps Experts, Product Managers/Scrum Masters, DevOps Engineers.NAVIN SABHAWAL, currently is the Chief Architect and Head of Strategy for Autonomics, named ‘DRYiCE’ at HCL Technologies. He is responsible for innovation, presales, and delivery of award-winning autonomics platforms for HCL Technologies.He is an innovator, thought leader, author and a consultant in areas of AI and Machine Learning, Cloud Computing, Big Data Analytics, Software Product Development, Engineering and R&D. He is responsible for IP Development & Service Delivery in the Areas of AI and Machine Learning, Automation products, Cloud Computing, Public Cloud AWS, Microsoft Azure, VMWare Private Cloud, Microsoft Private Cloud, Data Center Automation, Analytics for IT Operations, IT Service Management.RAMINDER RATHORE , an enthusiastic IT Practitioner with close to about two decades of work experience ranging from research and development to product management, to enabling organizations towards digitalization through agile ways of working. She currently leads the DevOps Centre of Excellence (CoE) at HCL Technologies, Canada.She holds a Master’s degree in Computer Science and is certified in a couple of areas on IBM Rational tools, Microsoft Azure, Scrum and ITIL methodologies. She started her career as a developer and progressed into product lifecycle management and consulting. She has been driving enterprise transformative programs on Automation (CI/CD), Cloud and DevOps for multiple customers. She has strong expertise in analyzing ecosystems, designing transformation roadmaps with milestones, building, and implementing accelerators / tools that drive end to end product traceability with agility and resiliency.UDITA AGRAWAL , an agile and automation transformation expert with over seventeen years of work experience, working with HCL Technologies. She holds a Master's degree in Business Administration in Information Technology and is also a PMP certified professional. She has wide experience in managing and leading engagements across different domains that includes Java, Data science and Automation. She is a passionate consultant running digital transformation programs for various customers. She also delivers enablement sessions on Agile and DevOps and works closely with product teams to practice agile methods. She also runs workshops on planning and implementing automated pipelines using various tools that includes COTS and open-source tools.Chapter 1: IntroductionCHAPTER GOAL: UNDERSTANDING THE AGILE JOURNEY AND THE NEED TO BRIDGE DEVELOPMENT AND OPERATIONS AREANO OF PAGES 17SUB -TOPICS1. Agile History2. Evolving software teams3. Bridging the gap4. Complementing Agile5. Agile in InfraOps6. Agile ManifestoChapter 2: Traditional Infrastructure OperationsCHAPTER GOAL: QUICK BRIEF ON TRADITIONAL ITSM APPROACH AND THE NEED TO TRANSITION TO AGILE OPERATIONS.No of pages: 20SUB - TOPICS1. ITSM and its phase2. Drawbacks3. Need to changeChapter 3: Agile and DevOpsCHAPTER GOAL: INTRODUCE CORE CONCEPTS TO AGILE AND DEVOPS AND UNDERSTAND ITS RELEVANCE IN THE PRODUCT LIFECYCLE.NO OF PAGES : 13SUB - TOPICS:1. When to adopt Agile2. Agile principles and values3. Scaling Agile with DevOps4. When to adopt DevOps5. DevOps in product lifecycleChapter 4: Factors leading to Agile OperationsCHAPTER GOAL: GET TO LEARN THE FACTORS THAT ARE MOTIVATING ORGANIZATIONS TO TRANSITION THEIR INFRASTRUCTURE OPERATIONS TO AGILE OPERATIONSNO OF PAGES: 29SUB - TOPICS:1.Shift towards Agile2.Benefits with Agility3.Cloud Computing4. Microservices5. Deployment patterns6. Shift left testing7. Changes in architectureChapter 5: Introduction to Agile MethodsCHAPTER GOAL: Introduce agile methods, roles, ceremonies and best practicesNO OF PAGES: 40SUB - TOPICS:1. Scrum2. Kanban3. ScrumbanChapter 6: Introduction to Agile FrameworksChapter Goal: INTRODUCE AGILE FRAMEWORKS, ROLES, AND STUDY THEIR COMPARISON.NO. OF PAGES : 47SUB - TOPICS:1. Agile ITSM2. IT4IT3. Lean IT4. SAFe5. Spotify6. LeSS7. Nexus8. DAD9. Site Reliability EngineeringChapter 7: Using Agile for Infrastructure OperationsCHAPTER GOAL:WITH THE BASIC UNDERSTANDING ON AGILE, THIS CHAPTER FOCUSES ON THE STRATEGY FOR ADOPTING AGILE IN INFRASTRUCTURE OPERATIONS SPACE.NO. OF PAGES : 22SUB - TOPICS:1. Adopting the right agile method2. Identify the right tools3. Upskill teams4. Redefine roles and responsibilities5. Continuously monitoring team performance6. Pilot-Expand-SustainChapter 8: Infrastructure as CodeCHAPTER GOAL:LEARN HOW TO LEVERAGE AGILE METHODS WHILE IMPLEMENTING INFRASTRUCTURE AS CODE PIPELINES AND EXTEND ITS INTEGRATION WITH DEVELOPMENT PIPELINES.NO. OF PAGES : 21SUB - TOPICS:1. Getting started with Scrum2. Estimating stories3. Defining acceptance criteria4. Integrating IaC with development pipelines5. IaC ExampleChapter 9: Success PathCHAPTER GOAL:THIS CHAPTER SHARES THE JOURNEY OF AN IMAGINARY COMPANY ON HOW THEY TRANSITION INTO AGILE OPS WITH A WELL-DEFINED TRANSFORMATION MAP AND MILESTONES.NO. OF PAGES : 7SUB - TOPICS:1. Enterprise Alpha2. New operating model3. OutcomesChapter 10: Learnings and Way forwardCHAPTER GOAL:AS ORGANIZATIONS ADOPT AGILE, THEY ALSO NEED TO PLAN FOR THE TRENDING TECHNOLOGIES THAT WILL BENEFIT THEM. THIS LAST CHAPTER SUMMARIZES THE LEARNINGS FROM THE EARLIER CHAPTERS AND SHARES UPCOMING TRENDS AND NEXT STEPS TO CONSIDER.NO. OF PAGES : 6SUB - TOPICS:1. Our Learnings2. Emerging Trends3. Next Steps
Navigating Hyperspace
Like a hurricane that exposes the underlying bedrock--and an occasional hidden treasure--by washing away the accumulated grains of sand, the pandemic blew away the accumulated certainties and securities of the globally connected, digitized society. Suddenly, nothing can be taken for granted: visiting ailing relatives, shopping--or going to church. The internet and, particularly, social networking sites have become the indispensable infrastructure holding our sociability together. The global companies of the digital economy profited handsomely. How about the users of their services? This volume explores how priests inhabit the digital environment of social networking sites, specifically Facebook. The authors looked at how they present themselves, what they publish, and how people engage with this content. The context of the pandemic suggested that we should also examine how digital technology and social media are being used for purposes of priestly ministry. Our hope is that these analyses and considerations will help not just priests but every person at becoming proficient not only in things virtual but also in practicing virtue. Peter Lah is a Jesuit priest and associate professor at the Faculty of Social Sciences, Pontifical Gregorian University, in Rome. He teaches courses in communication and media studies, focusing on media literacy, ICT regulation, and media ethics. Since 2016, he has been summer director at the Monte Santo di Lussari–Svete Višarje pilgrimage site in Italy.
#Myprivacy #Myright
If you ever thought you could run away into the wilderness without being noticed, think again. Right from the time you get up in the morning, picking up your mobile devices, wearing your fitness tracker, and every aspect of your life is connected to an unknown world—a world that decides whether you are noteworthy or play worthy of being tracked. A common man is caught up in a world that is intertwined between your private life, gains of the government through surveillance capitalism and the law of the internet and dark web. This book takes you through a journey that looks at various privacy aspects of your private life and unusual case laws. Laws that have challenged the courts to think beyond the traditional line of thinking. They have also influenced the media who are looking for juicy scoops to make stories more enticing for their viewership/ readership. It further dwells into the idea of Artificial Intelligence, and it will make things even more invasive with the unknown sources and data of an individual that is out there. Finally, the book attempts to answer the question of what should individuals do if they are caught up in a storm of data breaches.Remember, once the information is out on the internet, it is virtually impossible to redact it back.
Building an Effective Data Science Practice
Gain a deep understanding of data science and the thought process needed to solve problems in that field using the required techniques, technologies and skills that go into forming an interdisciplinary team. This book will enable you to set up an effective team of engineers, data scientists, analysts, and other stakeholders that can collaborate effectively on crucial aspects such as problem formulation, execution of experiments, and model performance evaluation.You’ll start by delving into the fundamentals of data science – classes of data science problems, data science techniques and their applications – and gradually build up to building a professional reference operating model for a data science function in an organization. This operating model covers the roles and skills required in a team, the techniques and technologies they use, and the best practices typically followed in executing data science projects.Building an Effective Data Science Practice provides a common base of reference knowledge and solutions, and addresses the kinds of challenges that arise to ensure your data science team is both productive and aligned with the business goals from the very start. Reinforced with real examples, this book allows you to confidently determine the strategic answers to effectively align your business goals with the operations of the data science practice.WHAT YOU’LL LEARN* Transform business objectives into concrete problems that can be solved using data science* Evaluate how problems and the specifics of a business drive the techniques and model evaluation guidelines used in a project* Build and operate an effective interdisciplinary data science team within an organization* Evaluating the progress of the team towards the business RoI* Understand the important regulatory aspects that are applicable to a data science practice WHO THIS BOOK IS FORTechnology leaders, data scientists, and project managersVineet is a Chief Data Scientist at GS Lab, India, and has led the effort of setting up a Data Science group at GS Lab which has now successfully executed Data Science projects in diverse fields like healthcare, IoT, communication, etc. He has also led research projects - in Computer Vision and Demand Forecasting, and developed new Data Science algorithms/techniques in areas like model performance tuning.Vineet is a computer science engineer from Pune university with a master’s degree from BITS Pilani. For most of his 17-year professional career, he has been associated with Data Science projects and has 2 US patents in his name. Prior to joining GS Lab, he worked at SAS for 7 years building data science products. He has presented papers in global conferences and has given talks in colleges on topics related to Data Science. He has also been associated with universities for research projects in the field of Data Science.Srinath is a Principal Architect at GS Lab, India. His key responsibility has been to bootstrap, and now to lead, the Data Science capability in GS Lab. A TOGAF9-certified architect, Srinath specializes in aligning business goals to the technical roadmap and data strategy for his clients. His typical clients are software technology companies that depend on data science, or enterprises looking to leverage data science as part of their digitalization programs.Srinath is a computer-science graduate from Pune University. During his 17 years of professional experience, he has primarily worked on data mining, predictive modeling, and analytics in varied areas such as CRM (retail/finance), life-sciences, healthcare, video conferencing, industrial-IoT and smart cities.Part One: Fundamentals1. Introduction: The Data Science Process2. Data Science and your business3. Monks vs. Cowboys: Data Science CulturesPart Two: Classes of Problems4. Classification5. Regression6. Natural Language Processing7. Clustering8. Anomaly Detection9. Recommendations10. Computer Vision11. Sequential Decision MakingPart Three: Techniques & Technologies12. Overview13. Data Capture14. Data Preparation15. Data Visualization16. Machine Learning17. Inference18. Other tools and services19. Reference Architecture20. Monks vs. Cowboys: PraxisPart Four: Building Teams and Executing Projects21. The Skills Framework22. Building and structuring the team23. Data Science ProjectsAppendix FAQs
Windows 10 Troubleshooting
Troubleshoot Windows 10 the way the experts do, whatever device or form factor you are using. Focus on the problems that most commonly plague PC users and fix each one with a step-by-step approach that helps you understand the cause, solution, and tools required.Windows 10 is constantly evolving and changing and a great many aspects of the operating system, including many associated with troubleshooting and repair, have been changed, removed, replaced, or expanded since the first edition of this book was published. This new edition is updated with a dedicated chapter on using scripting tools for troubleshooting along with numerous updates on Windows device and update installation, Microsoft Sysinternals Suite, and Troubleshooting malware attacks. Additionally, there is extensive coverage of the technical diagnosis and troubleshooting tools you need from Event Viewer to Recovery Console.This book will help you discover the connections between different hardware and software in your devices, and how their bonds with external hardware, networks, and the Internet are more inter-dependent than you think. You will also learn how to support the increasing volume of home workers, and make sure they can stay online and active on PCs from your own organization or their own devices.If you are fed up with those nagging, day-to-day issues, want to avoid costly repairs, or just want to learn more about how PCs work, _Windows 10 Troubleshooting_ is your ideal one-stop guide to the Windows 10 operating system.What You Will Learn* Understand your PC’s ecosystem and how to connect the dots, so you can successfully track problems to their source* Support home workers using PCs from your organization and family devices, and keep workers productive and online* Make your PC safe and secure for family and everyone in your workplace, and ensure that data is kept secure from loss or attack* Understand the threat from malware and viruses and a range of approaches to dealing with them, depending on the situation* Know tips and tricks for researching difficult problems, including third-party tools and useful web resourcesWHO THIS BOOK IS FORAnyone using Windows 10 on a desktop, laptop, or hybrid deviceMIKE HALSEY has been a Microsoft MVP (Most Valuable Professional) awardee since 2011 and is a recognized technical expert. As the author of Windows 7, 8, and 10 troubleshooting books and associated video courses, he is well versed in the problems and issues that PC users, IT pros, and system administrators face when administering and maintaining all aspects of a PC ecosystem.Mike understands that some subjects can be intimidating for some people and that everybody is different, so he approaches each subject area in straightforward and easy-to-understand ways.Mike is originally from the UK, but now lives in the south of France with his rescue border collies, Evan and Robbie. You can contact Mike on Twitter @MikeHalsey.Part 1: Getting Started with Windows TroubleshootingChapter 1: Introducing Troubleshooting in Windows 10The Three Seashells…The Problems We EncounterHardware ProblemsSoftware and App ProblemsNetworking ProblemsStartup ProblemsOS Installation and Update Problems“Prevention Is Better Than Cure”The Security and Maintenance CenterAutomatically Check for Solutions to ProblemsWindows Reliability HistoryWindows Automatic MaintenanceManaging Diagnostic Feedback and PrivacyRecovery OptionsWindows’ Security SystemsWindows Defender Anti-malwareWindows FirewallWindows SmartScreenUACUser Account ManagementAdministrators vs. Standard UsersLocal Accounts vs. Microsoft AccountsAzure ADUser Identity and Sign-In ManagementAn Introduction to Family SafetyManaging and Deleting User AccountsChapter 2: Building a Safe and Secure OSCreating a Recovery DriveBacking Up and Restoring Windows 10.ResetSystem Image BackupCreating a System Image Backup.Restoring a System Image BackupUsing Windows System RestoreConfiguring System RestoreUsing the Windows 10 Media Creation ToolSetting Up and Managing OneDriveBacking Up Your Files with OneDriveUsing OneDrive Personal and OneDrive ProfessionalRestoring Deleted and Previous Versions of FilesChapter 3: Configuring Windows 10The Settings AppSystem > StorageSystem > Default AppsSystem > AboutDevices > Printers & Scanners / Connected DevicesDevices > AutoPlayNetwork & InternetAccountsTime & LanguageUpd^ Windows UpdateUpdate & Security > Windows Defender / BackupUpdate & Security > ActivationUpdate & Security > For DevelopersIntroducing the Control PanelManaging the Virtual Memory, Paging FileManaging Remote Connections to the PCMoving the Shell User Folders.Creating, Managing, and Deleting PartitionsManaging Startup AppsChapter 4: Fixing Windows 10 QuicklyThe Disk Cleanup WizardManaging EdgeCleaning Temporary and Other Files from EdgeResetting - EdgeResetting the Windows Store and Store AppsDefragmenting Your Hard DisksManaging Running Apps and Services with Task ManagerManaging win32 App CompatibilityUsing the System File CheckerMicrosoft Answers, Service Status Site, and Being a TwitChapter 5: Understanding Tasks and EventsThe Windows Event ViewerIntroducing the Microsoft Management ConsoleThe Main Events ViewMaking Sense of Error LogsCreating Custom Event ViewsCreating Event SubscriptionsAttaching a Task to an EventSaving, Exporting, and Importing Event InformationChapter 6: Understanding PC HardwareBIOS and UEFIBIOS Virus/Malware AttackResetting BIOS and UEFI FirmwarePower SuppliesJump-Starting a PCThe MotherboardThe Rear Panel Connectors and CablesMemoryHard Disks, SSDs, M.2, and PCIe DrivesExpansion CardsMonitors and CablingKeyboards and MiceChapter 7: Diagnosing and Repairing Problem Hardware and PeripheralsGetting USB Devices to Work ReliablyInstalling and Managing Bluetooth DevicesInstalling and Configuring PrintersInstalling Different Types of PrinterFinding the Name or IP Address of a PrinterManaging Printing PoliciesHave You Tried [Not] Turning It Off and On Again?Chapter 8: Troubleshooting StartupHave You Tried Turning It Off and On Again?Using Startup RepairThe Windows Recovery Options MenuUsing the Command Prompt to Repair Windows StartupChapter 9: Troubleshooting NetworksThe Network and Sharing CenterConfiguring Network ConnectionsManaging Network AdaptersManaging Network Connections in the Settings AppSetting Up and Managing Your RouterTroubleshooting Wi-Fi Connection ProblemsRecovering Lost Wi-Fi PasswordsChapter 10: Troubleshoot and Manage EdgeManaging EdgeManaging Permissions, Security and Privacy in EdgeManaging Temporary and Other Files in EdgeUsing the Edge Task Manager to Manage Running Web AppsResetting EdgeOther Useful Settings in EdgePart 2: Becoming a Proficient TroubleshooterChapter 11: Dealing with Common Windows AnnoyancesIncorrect File AssociationsSetting Disk and File PermissionsManaging Audio DevicesTroubleshooting Windows ActivationTroubleshooting and Resetting Windows UpdateTroubleshooting Power Loss During an Update InstallationManaging and Resetting Windows SearchTroubleshooting Slow StartupWindows 10 Hangs on StartupWindows 10 Shuts Down SlowlyWindows Fails to Sleep/Resume from Sleep.Gaining Access After Bitlocker LockoutTroubleshooting Touch Screen ProblemsUSB Type-C and Thunderbolt ProblemsNo Picture on Desktop PC Monitor or TVDisappearing and Conflicting DrivesUnderstanding the BSODChapter 12: Remote HelpThe Problem Steps RecorderRecording an App with Game DVRQuick AssistWindows Remote AssistanceSending and Responding to a Remote Assistance RequestSending Unsolicited Remote Assistance OffersRemote DesktopChapter 13: Repairing Windows Startup ProblemsManually Repairing Windows StartupRepairing BIOS Startup FilesRepairing UEFI Startup FilesAdditional Repair Commands for BIOS and UEFIRecreating or Moving the Boot PartitionStep 1a: Create a New Boot Partition (Command Prompt)Step 1b: Create a New Boot Partition (Disk Management Console)Step 2: Create the New Boot FilesSetting Up and Managing Dual/Multiboot SystemsSecure BootBitlocker and Dual-Boot SystemsManaging Boot Systems with BCDEditBCDEdit IdentifiersBCDEdit Data FormatsExamples of BCDEdit UseEffecting Repairs on the Boot Partition StructuresChapter 14: Networks and Internet ConnectionsChecking the Status of a Network ConnectionDisplaying Information About Wi-Fi NetworksCreating Wi-Fi HotspotsPrioritizing Network ConnectionsDiagnosing Network Connection ProblemsGetting Network Diagnostic Reports from the Event ViewerSee the Status of Your Connection with the Performance Monitor.See What’s Using Your Bandwidth with the Resource MonitorTroubleshooting in the Network and Sharing CenterChanging a Network Type Between Private and PublicSetting Advanced Network Configuration OptionsUsing and Managing Ad-Hoc NetworksHOSTS, LMHOSTS and WINSUsing Authentication TechnologiesUnderstanding TCP/IPOSI Network LayersIPv4 vs IPv6 AddressingDCHPDNSUsing TCP/IP Management ToolsPingTraceRTIPConfigNetshManaging User ProfilesRoaming ProfilesAzure and AD Domain Profiles and SettingsChapter 15: Managing Device Drivers and PC ResourcesDeciphering the Device ManagerIdentifying and Installing Unknown DevicesInstalling Legacy HardwareForcibly installing a Device DriverUninstalling and Deleting Device DriversBlocking Device Driver and Device App InstallationFinding Device Driver Details and InformationTroubleshooting Device DriversBacking Up and Restoring the Driver StoreManaging Driver PropertiesChapter 16: Windows Update and System UpgradesDeferring Updates in Windows 10Long-Term Servicing ChannelChoosing How Updates Are DeliveredUninstalling and Blocking UpdatesTroubleshooting and Repairing Windows UpdateWindows Upgrades and the Reset ImageThe Windows Insider Programme (for Business)Chapter 17: Maintaining App and Web Site CompatibilityMaintaining Compatibility with Win32 AppsManaging Web Site and Intranet CompatibilityUsing Edge in IE Compatibility ModeManaging Security in EdgeInstalling and Managing Browser Plug-ins in EdgeSynchronizing Settings in EdgeSetting Your Default Web BrowserInstalling, Removing, Managing and Using Progressive Web AppsUsing the Software Compatibility TroubleshooterDPI ScalingProgram Compatibility AssistantMicrosoft Application Compatibility ToolkitShimsStandard User AnalyzerChapter 18: Managing Security and PrivacyCreating a Strong Password?Using Two-Factor AuthenticationTFA for Microsoft ServicesTFA for Third-Party ServicesMicrosoft TFA AppGoogle TFA AppManaging Safety and Privacy for ChildrenUsing the Credential ManagerManaging Passwords in EdgeManaging Encryption in Windows 10Using the EFSManaging EFS Encryption with Cipher.exeManaging Device EncryptionEncrypting Your PC with BitlockerManaging a TPM on Your PC and in Windows 10Managing Bitlocker Encryption on Your PCUsing Bitlocker To GoChapter 19: Malware and VirusesHow to Defend Against MalwareSo What Is This Malware Stuff Anyway?Viruses and WormsSpywareAdwareTrojansBotsRootkits / BootkitsBackdoorsRansomwareSpam and Phishing EmailDefending PCs Against MalwareDefending Your Files Against RansomwareSecure BootTrusted BootUsing EncryptionApp ContainersIdentifying a Malware AttackHow Malware Infects PCsHow Malware Infects NetworksIdentifying External AttacksIdentifying Internal AttacksTraining Staff for VigilanceManually Removing Malware from a PCFirst Steps – IsolationIdentifying the Running ProcessesDeactivating the MalwareTest and RetestFinishing UpRemoving RootkitsUsing BCDEdit to Repair Malware DamageUsing Third-Party Tools to Remove MalwareMalware Protection CenterBaseline Security AmalyzerMicrosoft DaRTWindows Defender OfflineESET Online (and Offline) ScannerNorton Bootable Recovery ToolSophos Bootable AntivirusKaspersky Rescue DiskKaspersky Ransomware DecryptorAVG Bootkit RemoverF-Secure Rescue CDTrend Micro Rescue DiskMcAfee Free ToolsD7IIRKillJunkware/Adware Removal ToolsMicrosoft SysInternals SuiteResearching Virus Removal OnlineChapter 20: Using Virtualization to Protect PCsCreating and Managing VMs in Hyper-VManaging Networks in Hyper-VCreating Backups of VMs in Hyper-VBooting and Repurposing Your PC from a VMCreating a VHDAdding a VHD to the Boot MenuVirtual Switches in Hyper-VCreating a Virtual SwitchManaging a Virtual SwitchManaging Hyper-V with PowerShellTroubleshooting Hyper-V ConnectionsPart 3: Mastering Windows 10 TroubleshootingChapter 21: Bomb-Proofing Your PCCreating a Robust Backup StrategyLock Down Your PCs with Group PolicyUsing the Group Policy EditorConfiguring a GPOUsing Server-Side Group PoliciesAdvanced Usage of Group PolicyUsing the Group Policy Management ConsoleActivating and Configuring the GPMCUsing the GPMCTroubleshooting Group Policy IssuesManaging Windows ServicesManage Your Local Security PolicyManaging Advanced Firewall PolicyChapter 22: Microsoft SysinternalsFile and Disk UtilitiesAccessChksAccessEnumContigDisk2VhdDiskExtDiskmonDiskViewEFSDumpMoveFile and PendMovesNTFSInfoPsFileSDeleteShareEnumSigcheckNetworking UtilitiesPSPingPsToolsTCPViewWhoIsProcess UtilitiesAutoRunsHandleListDLLsPortmonProcDumpProcess ExplorerProcess MonitorPSExecPsKillPsListPsServicePsSuspendShellRunasVMMapSecurity UtilitiesLogonSessionsPsLoggedOnPsLogListSysmon/Sysmon64System Information UtilitiesHandleLiveKdLoadOrderRAMMapMiscellaneous UtilitiesRegDelNullRegistry UsageRegJumpChapter 23: Best Practice in the WorkplaceManaging Power and BatteriesManaging Users and BYOD PCsMDMGroup PolicyBackups Best PracticeDeployment and Recovery Best PracticeManaging External and Network HardwareChapter 24: Managing BYOD HardwareManaging VPNs and Secure ConnectionsWorkplace JoinConnecting to an Exchange or ActiveSync AccountConnecting to Office 365 or Microsoft AzureWork FoldersChapter 25: Getting Advanced InformationThe Task ManagerThe Performance MonitorData Collector SetsThe Resource MonitorThe Computer Management ConsoleSystem InformationDXDiagChapter 26: The Registry in DepthRegistry FilesRegistry Keys and ValuesHKEY_CLASSES_ROOT (HKCR)HKEY_CURRENT_USER (HKCU)HKEY_LOCAL_MACHINE (HKLM)HKEY_USERS (HKU)HKEY_CURRENT_CONFIG (HKCC)HKEY_PERFORMANCE_DATARegistry Value TypesThe Registry EditorBacking Up and Restoring the RegistryCreating and Modifying Registry KeysEditing Other Users’ Registry DatabasesConnecting to a Remote RegistryUsing PowerShellUsing Group PolicyComparing RegistriesREGINI.EXEEditing the Registry with PowerShellScanRegEdit the Registry from the Recovery PanelThird-Party Registry UtilitiesChapter 27: Using Scripting Tools for TroubleshootingUsing the Windows Command LineUseful Command Line Tools for TroubleshootingUsing the Command Line from the Recovery ConsoleTroubleshooting Using PowerShellGetting Started with PowerShellUsing the Event Log in PowerShellGathering Detailed Reports and InformationManaging AppsManaging Running ProcessesManaging the RegistryManaging Windows UpdateManaging ServicesAdditional Troubleshooting with PowerShellThe Windows TerminalInstalling and Using the Windows TerminalChapter 28: Windows 10 File Structure in DepthThe Windows 10 File and Folder StructureRoot Windows FoldersWin32 and Store App FoldersWindows Operating System FoldersUser Account FoldersWindows Log FoldersWindows Temporary File FoldersWindows File TypesManaging the Shell User FoldersFile System Tools and UtilitiesFile Management from the Command LineHow File Systems Handle Files DifferentlyTroubleshooting File and Folder PermissionsACLs, DACLs, and PermissionsNTFS InheritanceUsign GroupsEffective AccessTaking OwnershipAuditingTroubleshooting File and Folder SharingChapter 29: Researching Difficult ProblemsReading the Windows Log FilesLog Text FilesReading .xml and .etl FilesReading .dmp filesSearching the Internet for SolutionsAnswers.Microsoft.comSupport.Microsoft.comTechnet.Microsoft.com and MSDN.Microsoft.comOther Microsoft and Third-Party Support SitesHardware Driver and Support SitesThird-Party Support ToolsChapter 30: Troubleshooting Difficult Problems“Mike Halsey’s Holistic Troubleshooting Agency”Gauging Both Internal and External FactorsUsing Troubleshooting Tools TogetherTroubleshooting and Repairing HardwareMinimal Boot Configuration and Jumpstarting PCsChapter 31: Installation and RestoreTroubleshooting the Windows 10 UpgradeInstalling Windows 10Obtaining Up-to-Date Installation MediaCreating Customized Installation MediaNondestructively Reinstalling Windows 10Windows 10 SysPrep