Allgemein
Beginning Java 17 Fundamentals
Learn the fundamentals of the Java 17 LTS or Java Standard Edition version 17 Long Term Support release, including basic programming concepts and the object-oriented fundamentals necessary at all levels of Java development. Authors Kishori Sharan and Adam L. Davis walk you through writing your first Java program step-by-step. Armed with that practical experience, you'll be ready to learn the core of the Java language. Beginning Java 17 Fundamentals provides over 90 diagrams and 240 complete programs to help you learn the topics faster.While this book teaches you the basics, it also has been revised to include the latest from Java 17 including the following: value types (records), immutable objects with an efficient memory layout; local variable type inference (var); pattern matching, a mechanism for testing and deconstructing values; sealed types, a mechanism for declaring all possible subclasses of a class; multiline text values; and switch expressions.The book continues with a series of foundation topics, including using data types, working with operators, and writing statements in Java. These basics lead onto the heart of the Java language: object-oriented programming. By learning topics such as classes, objects, interfaces, and inheritance you'll have a good understanding of Java's object-oriented model. The final collection of topics takes what you've learned and turns you into a real Java programmer.You'll see how to take the power of object-oriented programming and write programs that can handle errors and exceptions, process strings and dates, format data, and work with arrays to manipulate data.WHAT YOU WILL LEARN* Write your first Java programs with emphasis on learning object-oriented programming* How to work with switch expressions, value types (records), local variable type inference, pattern matching switch and more from Java 17* Handle exceptions, assertions, strings and dates, and object formatting* Learn about how to define and use modules* Dive in depth into classes, interfaces, and inheritance in Java* Use regular expressions* Take advantage of the JShell REPL toolWHO THIS BOOK IS FORThose who are new to Java programming, who may have some or even no prior programming experience.KISHORI SHARAN has earned a Master of Science in Computer Information Systems degree from Troy State University, Alabama. He is a Sun Certified Java 2 programmer. He has vast experience in providing training to professional developers in Java, JSP, EJB, and Web technology. He possesses over ten years of experience in implementing enterprise level Java application.ADAM L. DAVIS makes software. He’s spent many years developing in Java (since Java 1.2) and has enjoyed using Spring and Hibernate for more than a decade. Since 2006 he’s been using Groovy, Grails, HTML, CSS, and JavaScript, in addition to Java, to create SaaS web applications that help track finances for large institutions (among other things). Adam has a master’s and a bachelor’s degree in Computer Science from Georgia Tech. He is also the author of Reactive Streams in Java (Apress, 2019), Learning Groovy 3, Second Edition (Apress, 2019) and Modern Programming Made Easy, Second Edition (Apress, 2020).1. Programming Concepts2. Setting Up the Environment3. Writing Java Programs4. Data Types5. Operators6. Statements7. Classes and Objects8. Methods9. Constructors10. Modules11. Object and Objects Classes12. Wrapper Classes13. Execution Handling14. Assertions15. Strings16. Dates and Times17. Formatting Data18. Regular Expressions19. Arrays20. Inheritance21. Interfaces22. Enum Types23. Java ShellAppendix A: Character EncodingsAppendix B: Documentation Comments
Spring REST
Design and develop Java-based RESTful APIs using the latest versions of the Spring MVC and Spring Boot frameworks. This book walks you through the process of designing and building a REST application while delving into design principles and best practices for versioning, security, documentation, error handling, paging, and sorting.Spring REST provides a brief introduction to REST, HTTP, and web infrastructure. You will learn about several Spring projects such as Spring Boot, Spring MVC, Spring Data JPA, and Spring Security, and the role they play in simplifying REST application development. You will learn how to build clients that consume REST services. Finally, you will learn how to use the Spring MVC test framework to unit test and integration test your REST API.After reading this book, you will come away with all the skills to build sophisticated REST applications using Spring technologies.WHAT YOU WILL LEARN* Build Java-based microservices, native cloud, or any applications using Spring REST* Employ Spring MVC and RESTful Spring* Build a QuickPoll application example* Document REST services, as well as versioning, paging, and sorting* Test, handle errors and secure your applicationWHO THIS BOOK IS FORIntermediate Java programmers with at least some prior experience with Spring and web/cloud application development.BALAJI VARANASI is a software development manager and technology entrepreneur. He has over 13 years of experience architecting and developing Java/.Net applications and, more recently, iPhone apps. During this period he has worked in the areas of security, web accessibility, search, and enterprise portals. He has a Master s Degree in Computer Science and serves as adjunct faculty, teaching programming and information system courses. When not programming, he enjoys spending time with his lovely wife in Salt Lake City, Utah.MAXIM BARTKOV is a staff engineer with more than seven years of commercial experience in Java. Maxim specializes in building architecture for high-load systems. He is skilled in the development of Distributed High-Load Systems, Microservice architecture, Spring Framework, System Architecture, and In-Memory Data Grid (IMDG). In his spare time, he writes articles for the Java community.1. Introduction to REST2. Spring MVC & Spring Boot Primer3. RESTful Spring4. Beginning the QuickPoll Application5. Error Handling6. Documenting REST Services7. Versioning, Paging, and Sorting8. Security9. Clients and Testing10. HATEOASA. Installing cURL on Windows
Mastering Excel Through Projects
Master Excel in less than two weeks with this unique project-based book! Let’s face it, we all master skills in our own way, but building a soup-to-nuts project is one of the best ways to make learning stick and get up to speed quickly. Whether you are just getting started with Excel or are an experienced user, this book will elevate your knowledge and skills. For a beginner, the micro examples in each chapter will warm you up before you dive into the projects. For experienced users, the projects, especially those with table setup considerations, will help you become more creative in your interactions with Excel.Readers will benefit from building eight unique projects, each covering a different topic, including a word game, a food nutrition ranking, a payroll (tax withholding) calculation, an encryption, a two-way table, a Kaplan-Meier analysis, a data analysis via a pivot table and the K-means Clustering data mining method. Through these projects, you will experience firsthand how Excel skills are organized together to accomplish tasks that sound complex and daunting when first described.Get started with a word game which asks users to find English words that amount to exactly 100 points, with each letter of the alphabet assigned a point 1, 2, 3, … 26, respectively. You will disassemble a word into letters and then sum up their points, and then take it one step further, contemplating how to make the completed Excel worksheet more user friendly and completely automated. Increasingly challenging tasks like this example build on what you have learned and increase your confidence along the way, ensuring your mastery of Excel.WHAT YOU WILL LEARN* Gain confidence to tackle a challenging Excel-related mission, even those that seem impossible* Become skilled in the creative uses of Excel formulas and functions and other built-in features* Appreciate the art of refining worksheets to maximize automation* Understand the value of treating each worksheet as a unique productWHO THIS BOOK IS FORPeople who are interested in learning Excel as quickly and efficiently as possible. While Excel beginners and intermediate users are the primary audience, experienced Excel users might also discover new skills and ways of working with Excel.HONG ZHOU is a professor of computer science and mathematics at the University of Saint Joseph in Connecticut. Before returning to school for his doctoral degree, Dr. Zhou worked as a Java developer in Silicon Valley. Since 2004, Dr. Zhou has been teaching various courses in computer science, data science, mathematics, statistics, and informatics. His major research interests include data mining, bioinformatics, software agents, and blockchain. Dr. Zhou became interested in Excel through teaching computer skills and using them for research purposes; for example, applying Excel in teaching data mining, encryption, and health informatics. He also enjoys applying his Excel skills to help colleagues in their research projects.Chapter 1: Master Excel through ProjectsChapter 2: Food Nutrition RankingChapter 3: Payroll CalculationChapter 4: Public and Private Key CryptographyChapter 5: Two-Way Table and Chi-Square TestChapter 6: Kaplan-Meier AnalysisChapter 7: PivotTable Data AnalysisChapter 8: K-means Clustering and Iterative Calculation
Tableau for Business Users
Learn Tableau by working through concrete examples and issues that you are likely to face in your day-to-day work.Author Shankar Arul starts by teaching you the fundamentals of data analytics before moving on to the core concepts of Tableau. You will learn how to create calculated fields, and about the currently available calculation functionalities in Tableau, including Basic Expressions, Level of Detail (LOD) Expressions, and Table Calculations. As the book progresses, you’ll be walked through comparisons and trend calculations using tables. A concluding chapter on dashboarding will show you how to build actionable dashboards to communicate analysis and visualizations. You’ll also see how Tableau can complement and communicate with Excel.After completing this book, you will be ready to tackle the challenges of data analytics using Tableau without getting bogged down by the technicalities of the tool.WHAT WILL YOU LEARNMaster the core concepts of Tableau * Automate and simplify dashboards to help business users* Understand the basics of data visualization techniques* Leverage powerful features such as parameters, table calculations, level of detail expressions, and more WHO IS THIS BOOK FORBusiness analysts, data analysts, as well as financial analysts.Shankar Arul holds a Masters in industrial engineering from Virginia Tech, USA and an MBA in Finance from ESSEC, France. He has more than 15 years of hands-on experience in the field of Data Visualization and data science. Having faced the frustrations of Business users in data-driven decision making, in companies such as BNP, Apple, Groupon and Kering, he decided to enable the Business users with the power of data visualization and Tableau through this book. Chapter 1: IntroductionCHAPTER GOAL: THE NEED FOR DATA VISUALIZATION TOOLS SUCH AS TABLEAU FOR BUSINESS USERSNO OF PAGES 4SUB -TOPICS1. Why visualize data2. Who is this book for3. How is this book differentChapter 2: Installation and SetupChapter Goal: Onboard readers with the setup of tableau.NO OF PAGES: 3SUB - TOPICS1. Installation of tableau2. Data sources required for the exercisesChapter 3: Fundamentals of DataCHAPTER GOAL: GENTLE INTRODUCTION TO THE FUNDAMENTALS OF DATANo of pages : 6SUB - TOPICS:1. Data types2. Data sources3. Data preparation4. Converting business questions to the language of dataChapter 4: The Crux of TableauCHAPTER GOAL: DISTILLATION OF THE CORE CONCEPTS OF TABLEAUNO OF PAGES: 17SUB - TOPICS:1. 4 Building pillars2. Putting it all together3. Show me3. Sheets & DashboardsChapter 5: CalculationsCHAPTER GOAL: ENRICH THE DATA BY CREATING CALCULATED FIELDSNo of pages: 16SUB - TOPICS:1. Grouping Values2. Calculated Fields3. Row level, Aggreation & Dis-Aggregation4. Bringin more data5. Importance of Cardinality6. Data ModelingChapter 6: Tables & Table CalculationsChapter Goal: Comparisons and trend calculations through tablesNO OF PAGES: 15SUB - TOPICS:1. Show me or start from scratch ?2. Table totals3. Table calculations4. SortingChapter 7: Advanced TipsCHAPTER GOAL: ADVANCED FUNCTIONALITIES OF TABLEAUNo of pages: 15SUB - TOPICS:1. Dynamic Inputs - Parameters2. Top 10/20/50 filters3. Dual Axis4. Shapes & Icons5. Level of detail calculations6. Reference lines & forecast7. Order of operationsChapter 8: DashboardsCHAPTER GOAL: BRING IT ALL TOGETHER BY ENABLING USERS TO BUILD INTERACTIVE DASHBOARDSNO OF PAGES: 9SUB - TOPICS:1. Less I more2. Dashboards: A view from 10000ft3. Fit & Layout4. Filters & Interaction
Beginning React and Firebase
Use React with Firebase to build four beginner-friendly apps. A lot of React tutorials out there today only cover basic web apps, but with additional features the web apps included in this book can be converted into fully scaled startups.You will start with the basics: learn to deploy a React app with Firebase hosting. Next, you will learn to create a fully functional "ToDo" app that will use Firebase database to store a list action items. You will also learn to create a "Stories" app, in which you can show short vertical videos, and a document storage app. Here, we will be able to log in using Google Authentication, and will learn to store files in the app using Firebase storage. Lastly, you will create a career social media app. Your users will be able to log in using email and password authentication. You will learn to use Redux in this project.While creating these web apps, you will employ multiple concepts, including React hooks, React components, and how to use Material UI. You will learn to use Firebase to host your database, as well as hosting your app. With these projects in your portfolio you'll be ready to take your developer skills to the next level.WHAT YOU'LL LEARN* Use Firebase’s powerful services, and how to connect Firebase with React* Explore the React ecosystem, including Redux and React hooks* Work with MaterialUI, the popular React UI framework* Understand how to use Google Authentication techniques in your sites* Deploy all sites using simple Firebase hostingWHO THIS BOOK IS FORDevelopers at the beginning of their career, or anyone who wants to take their React skills to the next level.Nabendu Biswas is a full stack JavaScript developer who has been working in the IT industry for the past 16 years and has worked for some of the world’s top development firms and investment banks. He is a passionate tech blogger who publishes on dev.to and medium.com and on thewebdev.tech. He is an all-round nerd, passionate about everything JavaScript, React and Gatsby. You can find him on Twitter @nabendu82.Chapter One: Getting Started with React and Firebase· Introduction to firebase· Creating an account in firebase· Setting up hosting from firebase console· Deploying a simple ReactJS project from terminalChapter Two: TODO App· Firebase initial setup· React basic setup· Code to show local Todo list· Using Material UI in project· Setting up firebase database· Integrating firebase database with React· Implementing Edit and Delete feature· Deploying and hosting through firebaseChapter Three: Stories App· Firebase initial setup· React basic setup· Adding Short videos to site· Adding snap feature to video· Setting up firebase database· Integrating firebase database with React· Deploying and hosting through firebaseChapter Four: Storage App· Firebase initial setup· React basic setup· Creating Header and Sidebar component· Setting up firebase database· Integrating firebase database with React· Using firebase storage to upload files· Adding Google Authentication· Deploying and hosting through firebaseChapter Five: Social Media App· Firebase initial setup· React basic setup· Create the Header· Create the Sidebar· Create the Feed component· Setting up firebase database· Integrating firebase database with React· Adding Redux to project· Adding email/password authentication· Deploying and hosting through firebase
Implementing Always On VPN
Implement and support Windows 10 Always On VPN, the successor to Microsoft's popular DirectAccess. This book teaches you everything you need to know to test and adopt the technology at your organization that is widely deployed around the world.The book starts with an introduction to Always On VPN and discusses fundamental concepts and use cases to compare and contrast it with DirectAccess. You will learn the prerequisites required for implementation and deployment scenarios. The book presents the details of recommended VPN protocols, client IP address assignment, and firewall requirements. Also covered is how to configure Routing and Remote Access Service (RRAS) along with security and performance optimizations. The Configuration Service Provider (CSP) is discussed, and you will go through provisioning Always On VPN to Windows 10 clients using PowerShell and XML as well as Microsoft Intune. Details about advanced client configuration and integration with Azure security services are included. You will know how to implement Always On VPN infrastructure in a redundant and highly available (HA) configuration, and guidance for ongoing system maintenance and operational support for the VPN and NPS infrastructure is provided. And you will know how to diagnose and troubleshoot common issues with Always On VPN.After reading this book, you will be able to plan, design, and implement a Windows 10 Always On VPN solution to meet your specific requirements.WHAT WILL YOU LEARN* Prepare your infrastructure to support Windows 10 Always On VPN on premises or in the cloud* Provision and manage Always On VPN clients using modern management methods such as Intune* Understand advanced integration concepts for extending functionality with Microsoft Azure* Troubleshoot and resolve common configuration and operational errors for your VPNWHO THIS BOOK IS FORIT professionals and technology administrators for organizations of all sizesRICHARD HICKS is the founder and principal consultant at Richard M. Hicks Consulting, Inc. He is a widely recognized enterprise mobility and security infrastructure expert with more than 25 years of experience implementing secure remote access and Public Key Infrastructure (PKI) solutions for organizations around the world. Richard is a former Microsoft Most Valuable Professional (MVP 2009-2019) and is active in the online community, sharing his knowledge and experience with IT professionals on his blog and through various social media channels. Visit his web site https://www.richardhicks.com/ or connect with him on Twitter @richardhicks. CHAPTER 1 – ALWAYS ON VPN OVERVIEWo This chapter will introduce Always On VPN as a technology and cover the concepts and underlying technologies used by the solution. We will discuss the high-level use cases and compare with its predecessor, DirectAccess.CHAPTER 2 – PLAN AN ALWAYS ON VPN DEPLOYMENTo In this chapter we will dive more deeply into the implementation prerequisites. We will identify infrastructure requirements, discuss networking and authentication requirements, and learn about various deployment scenarios. Guidance will be provided for certificate services configuration and networking models will be covered. Details about VPN protocols, client IP address assignment, and firewall requirements will also be covered.CHAPTER 3 – CONFIGURE WINDOWS SERVER FOR ALWAYS ON VPNIn this chapter, configuring Windows Server Routing and Remote Access Service (RRAS) will be covered in detail. In addition, we will cover Remote Access Service (RRAS) configuration and perform server security and performance optimizations.CHAPTER 4 – PROVISION ALWAYS ON VPN CLIENTSThis chapter will provide guidance for provisioning Always On VPN to Windows 10 clients. The Configuration Service Provider (CSP) mode will be discussed, and readers will learn to create a configuration XML file and provision it locally using PowerShell. In addition, Intune deployment using custom XML and native VPN profiles will be covered.CHAPTER 5 – CLOUD DEPLOYMENTSo For those organizations deploying infrastructure in a public cloud, this chapter will outline how to deploy an Always On VPN infrastructure in Microsoft Azure. Deploying RRAS in Azure and leveraging native cloud VPN infrastructure such as Azure Virtual Network Gateway and Azure Virtual WAN will be discussed.CHAPTER 6 – AZURE INTEGRATIONo This chapter will provide guidance for advanced client configuration and integration with Azure security services. Azure MFA integration with on-premises NPS will be covered in detail. Also, Azure Conditional Access will be covered.CHAPTER 7 – HIGH AVAILABILITYo This chapter will describe in detail how to implement an Always On VPN infrastructure in a redundant and highly available configuration. Locally redundancy NPS and VPN servers will be covered. Guidance for multisite deployment with geographic redundancy for VPN servers will be included.CHAPTER 8 – MONITOR AND REPORTo This chapter will cover ongoing system maintenance and operational support for the VPN and NPS infrastructure. It will include guidance for ensuring automatic certificate management, how to renew certificates that cannot be managed automatically, how to find logging details, and which monitoring tools can be effective for daily operation.CHAPTER 9 – TROUBLESHOOTINGo This chapter will provide detailed guidance for troubleshooting and resolving common configuration and operational errors for the VPN and authentication infrastructure, from both the client and server perspective. Common failure scenarios will be covered, and detailed resolution steps will be provided.CHAPTER 10 – MIGRATE FROM DIRECTACCESS TO ALWAYS ON VPNo Always On VPN is most commonly deployed to replace existing DirectAccess infrastructure. In this chapter I’ll provide guidance and share experience for migrating from DirectAccess to Always On VPN seamlessly and without disruption.
PowerShell Fast Track
Create complex scripts in PowerShell and learn how to connect them to cloud services like Azure and Azure AD. This book will help you learn PowerShell by providing small “cheat” snippets that you can combine to write efficient and effective scripts.PowerShell Fast Track starts with the basics of PowerShell before moving on to discuss functions like date and logs, along with concepts such as inputs for your scripts. Author Vikas Sukhija then walks you through interactive input and Snapins modules, where you will learn GUI button prompts and how to import sessions. He’ll then show you how to report errors through email and log errors to a text file. Reporting CSV (Comma Separate Value) is discussed next, followed by a demonstration of miscellaneous functions, including how to connect your PowerShell scripts with Azure, SharePoint, Teams and other services. As you progress further, you’ll see how PowerShell provides powerful features for automation that can be leveraged for managing your Teams workload. Finally, using practical examples, you will learn how to implement and create scripts for day-to-day usage.After reading this book, you will be able to hit the ground running and use PowerShell’s powerful features in your own work.WHAT WILL YOU LEARN:* Utilize code Snippets to perform practical tasks* Combine the code to create more complex scripts.* Logging and reporting* Connect to various products such as Exchange, SharePoint, Teams, and AzureADWHO IS THIS BOOK FOR:System administratorsVikas Sukhija has over a decade of IT infrastructure experience with expertise in Messaging, Collaboration & IT automations utilizing PowerShell, PowerApps , Power Automate and other tools. He is currently working as a Global Director at Golden Five Consulting in Canada. He is also a Blogger, Architect, Microsoft MVP and is known by the name TechWizard. As an experienced professional he is assisting small to large enterprises in architecting, implementing, and automating Microsoft 365 and Azure. CHAPTER 1. POWERSHELL BASICSVariables & Printing If Else/ switch Conditional / Logical Operators Loops For –Loop While –Loop FunctionsCHAPTER 2. DATE & LOGSDefine LogsFirst day & Last day of MonthMidnight Create Folders based on Date Recycle Logs Progress barCHAPTER 3. INPUT TO YOUR SCRIPTSImport CSV Import from text file Input from ArrayCHAPTER 4. INTERACTIVE INPUTRead-host Parameters GUI Button PromptCHAPTER 5. ADDING SNAP INS/ MODULESPowerShell Snapins Modules Import Session Example:CHAPTER 6. SENDING EMAILCHAPTER 7. ERROR REPORTINGReporting Error thru EmailLogging Everything including Error Logging error to Text fileCHAPTER 8. REPORTING CSVReport HTML ReportingCHAPTER 9. MISCELLANEOUS KEYWORDSSplit ReplaceSelect-StringCompare-ObjectCHAPTER 10. PRODUCT EXAMPLES (DAILY USE)Microsoft Exchange Clean Database so that mailboxes appear in disconnected stateFind Disconnected Mailboxes Clustered Mailbox Status (2007)Extract Message accept from Active Sync Stats Message Tracking Search mailbox / Delete Messages Exchange Quota Report Set Quota Active Directory Export Group members Set values for Ad attributes Export Active Directory attributes Add members to the group from text file Remove members to the group from text file Office 365 Exchange Online Mailbox Report Exchange Online Message Tracking Searching Unified Log11. Appendix
Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithms
COGNITIVE BEHAVIOR AND HUMAN COMPUTER INTERACTION BASED ON MACHINE LEARNING ALGORITHMSTHE OBJECTIVE OF THIS BOOK IS TO PROVIDE THE MOST RELEVANT INFORMATION ON HUMAN-COMPUTER INTERACTION TO ACADEMICS, RESEARCHERS, AND STUDENTS AND FOR THOSE FROM INDUSTRY WHO WISH TO KNOW MORE ABOUT THE REAL-TIME APPLICATION OF USER INTERFACE DESIGN.Human-computer interaction (HCI) is the academic discipline, which most of us think of as UI design, that focuses on how human beings and computers interact at ever-increasing levels of both complexity and simplicity. Because of the importance of the subject, this book aims to provide more relevant information that will be useful to students, academics, and researchers in the industry who wish to know more about its real-time application. In addition to providing content on theory, cognition, design, evaluation, and user diversity, this book also explains the underlying causes of the cognitive, social and organizational problems typically devoted to descriptions of rehabilitation methods for specific cognitive processes. Also described are the new modeling algorithms accessible to cognitive scientists from a variety of different areas. This book is inherently interdisciplinary and contains original research in computing, engineering, artificial intelligence, psychology, linguistics, and social and system organization as applied to the design, implementation, application, analysis, and evaluation of interactive systems. Since machine learning research has already been carried out for a decade in various applications, the new learning approach is mainly used in machine learning-based cognitive applications. Since this will direct the future research of scientists and researchers working in neuroscience, neuroimaging, machine learning-based brain mapping, and modeling, etc., this book highlights the framework of a novel robust method for advanced cross-industry HCI technologies. These implementation strategies and future research directions will meet the design and application requirements of several modern and real-time applications for a long time to come. AUDIENCE: A wide range of researchers, industry practitioners, and students will be interested in this book including those in artificial intelligence, machine learning, cognition, computer programming and engineering, as well as social sciences such as psychology and linguistics. SANDEEP KUMAR, PHD is a Professor in the Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India. He has published more than 100 research papers in various international/national journals and 6 patents. He has been awarded the “Best Excellence Award” in New Delhi, 2019.ROHIT RAJA, PHD is an associate professor in the IT Department at the Guru Ghasidas, Vishwavidyalaya, Bilaspur (Central University-CG). He gained his PhD in Computer Science and Engineering in 2016 from C. V. Raman University India. He has filed successfully 10 (9 national + 1 international) patents and published more than 80 research papers in various international/national journals. SHRIKANT TIWARI, PHD is an assistant professor in the Department of Computer Science & Engineering (CSE) at Shri Shankaracharya Technical Campus, Junwani, Bhilai, Distt. Chattisgarh, India. He received his PhD from the Department of Computer Science & Engineering (CSE) from the Indian Institute of Technology (Banaras Hindu University), Varanasi (India) in 2012. SHILPA RANI, PHD is an assistant professor in the Department of Computer Science & Engineering, Neil Gogte Institute of Technology, Hyderabad, India. Preface xv1 COGNITIVE BEHAVIOR: DIFFERENT HUMAN-COMPUTER INTERACTION TYPES 1S. Venkata Achyuth Rao, Sandeep Kumar and GVRK Acharyulu1.1 Introduction: Cognitive Models and Human-Computer User Interface Management Systems 21.1.1 Interactive User Behavior Predicting Systems 21.1.2 Adaptive Interaction Observatory Changing Systems 31.1.3 Group Interaction Model Building Systems 41.1.4 Human-Computer User Interface Management Systems 51.1.5 Different Types of Human-Computer User Interfaces 51.1.6 The Role of User Interface Management Systems 61.1.7 Basic Cognitive Behavioral Elements of Human- Computer User Interface Management Systems 71.2 Cognitive Modeling: Decision Processing User Interacting Device System (DPUIDS) 91.2.1 Cognitive Modeling Automation of Decision Process Interactive Device Example 91.2.2 Cognitive Modeling Process in the Visualization Decision Processing User Interactive Device System 111.3 Cognitive Modeling: Decision Support User Interactive Device Systems (DSUIDS) 121.3.1 The Core Artifacts of the Cognitive Modeling of User Interaction 131.3.2 Supporting Cognitive Model for Interaction Decision Supportive Mechanism 131.3.3 Representational Uses of Cognitive Modeling for Decision Support User Interactive Device Systems 141.4 Cognitive Modeling: Management Information User Interactive Device System (MIUIDS) 171.5 Cognitive Modeling: Environment Role With User Interactive Device Systems 191.6 Conclusion and Scope 20References 202 CLASSIFICATION OF HCI AND ISSUES AND CHALLENGES IN SMART HOME HCI IMPLEMENTATION 23Pramod Vishwakarma, Vijay Kumar Soni, Gaurav Srivastav and Abhishek Jain2.1 Introduction 232.2 Literature Review of Human-Computer Interfaces 262.2.1 Overview of Communication Styles and Interfaces 332.2.2 Input/Output 372.2.3 Older Grown-Ups 372.2.4 Cognitive Incapacities 382.3 Programming: Convenience and Gadget Explicit Substance 402.4 Equipment: BCI and Proxemic Associations 412.4.1 Brain-Computer Interfaces 412.4.2 Ubiquitous Figuring—Proxemic Cooperations 432.4.3 Other Gadget-Related Angles 442.5 CHI for Current Smart Homes 452.5.1 Smart Home for Healthcare 452.5.2 Savvy Home for Energy Efficiency 462.5.3 Interface Design and Human-Computer Interaction 462.5.4 A Summary of Status 482.6 Four Approaches to Improve HCI and UX 482.6.1 Productive General Control Panel 492.6.2 Compelling User Interface 502.6.3 Variable Accessibility 522.6.4 Secure Privacy 542.7 Conclusion and Discussion 55References 563 TEACHING-LEARNING PROCESS AND BRAIN-COMPUTER INTERACTION USING ICT TOOLS 63Rohit Raja, Neelam Sahu and Sumati Pathak3.1 The Concept of Teaching 643.2 The Concept of Learning 653.2.1 Deficient Visual Perception in a Student 673.2.2 Proper Eye Care (Vision Management) 683.2.3 Proper Ear Care (Hearing Management) 683.2.4 Proper Mind Care (Psychological Management) 693.3 The Concept of Teaching-Learning Process 703.4 Use of ICT Tools in Teaching-Learning Process 763.4.1 Digital Resources as ICT Tools 773.4.2 Special ICT Tools for Capacity Building of Students and Teachers 773.4.2.1 CogniFit 773.4.2.2 Brain-Computer Interface 783.5 Conclusion 80References 814 DENOISING OF DIGITAL IMAGES USING WAVELET-BASED THRESHOLDING TECHNIQUES: A COMPARISON 85Devanand Bhonsle4.1 Introduction 854.2 Literature Survey 874.3 Theoretical Analysis 894.3.1 Wavelet Transform 904.3.1.1 Continuous Wavelet Transform 904.3.1.2 Discrete Wavelet Transform 914.3.1.3 Dual-Tree Complex Wavelet Transform 944.3.2 Types of Thresholding 954.3.2.1 Hard Thresholding 964.3.2.2 Soft Thresholding 964.3.2.3 Thresholding Techniques 974.3.3 Performance Evaluation Parameters 1024.3.3.1 Mean Squared Error 1024.3.3.2 Peak Signal–to-Noise Ratio 1034.3.3.3 Structural Similarity Index Matrix 1034.4 Methodology 1034.5 Results and Discussion 1054.6 Conclusions 112References 1125 SMART VIRTUAL REALITY–BASED GAZE-PERCEPTIVE COMMON COMMUNICATION SYSTEM FOR CHILDREN WITH AUTISM SPECTRUM DISORDER 117Karunanithi Praveen Kumar and Perumal Sivanesan5.1 Need for Focus on Advancement of ASD Intervention Systems 1185.2 Computer and Virtual Reality–Based Intervention Systems 1185.3 Why Eye Physiology and Viewing Pattern Pose Advantage for Affect Recognition of Children With ASD 1205.4 Potential Advantages of Applying the Proposed Adaptive Response Technology to Autism Intervention 1215.5 Issue 1225.6 Global Status 1235.7 VR and Adaptive Skills 1245.8 VR for Empowering Play Skills 1255.9 VR for Encouraging Social Skills 1255.10 Public Status 1265.11 Importance 1275.12 Achievability of VR-Based Social Interaction to Cause Variation in Viewing Pattern of Youngsters With ASD 1285.13 Achievability of VR-Based Social Interaction to Cause Variety in Eye Physiological Indices for Kids With ASD 1295.14 Possibility of VR-Based Social Interaction to Cause Variations in the Anxiety Level for Youngsters With ASD 132References 1336 CONSTRUCTION AND RECONSTRUCTION OF 3D FACIAL AND WIREFRAME MODEL USING SYNTACTIC PATTERN RECOGNITION 137Shilpa Rani, Deepika Ghai and Sandeep Kumar6.1 Introduction 1386.1.1 Contribution 1396.2 Literature Survey 1406.3 Proposed Methodology 1436.3.1 Face Detection 1436.3.2 Feature Extraction 1436.3.2.1 Facial Feature Extraction 1436.3.2.2 Syntactic Pattern Recognition 1436.3.2.3 Dense Feature Extraction 1476.3.3 Enhanced Features 1486.3.4 Creation of 3D Model 1486.4 Datasets and Experiment Setup 1486.5 Results 1496.6 Conclusion 152References 1547 ATTACK DETECTION USING DEEP LEARNING–BASED MULTIMODAL BIOMETRIC AUTHENTICATION SYSTEM 157Nishant Kaushal, Sukhwinder Singh and Jagdish Kumar7.1 Introduction 1587.2 Proposed Methodology 1607.2.1 Expert One 1607.2.2 Expert Two 1607.2.3 Decision Level Fusion 1617.3 Experimental Analysis 1627.3.1 Datasets 1627.3.2 Setup 1627.3.3 Results 1637.4 Conclusion and Future Scope 163References 1648 FEATURE OPTIMIZED MACHINE LEARNING FRAMEWORK FOR UNBALANCED BIOASSAYS 167Dinesh Kumar, Anuj Kumar Sharma, Rohit Bajaj and Lokesh Pawar8.1 Introduction 1688.2 Related Work 1698.3 Proposed Work 1708.3.1 Class Balancing Using Class Balancer 1718.3.2 Feature Selection 1718.3.3 Ensemble Classification 1718.4 Experimental 1728.4.1 Dataset Description 1728.4.2 Experimental Setting 1738.5 Result and Discussion 1738.5.1 Performance Evaluation 1738.6 Conclusion 176References 1769 PREDICTIVE MODEL AND THEORY OF INTERACTION 179Raj Kumar Patra, Srinivas Konda, M. Varaprasad Rao, Kavitarani Balmuri and G. Madhukar9.1 Introduction 1809.2 Related Work 1819.3 Predictive Analytics Process 1829.3.1 Requirement Collection 1829.3.2 Data Collection 1849.3.3 Data Analysis and Massaging 1849.3.4 Statistics and Machine Learning 1849.3.5 Predictive Modeling 1859.3.6 Prediction and Monitoring 1859.4 Predictive Analytics Opportunities 1859.5 Classes of Predictive Analytics Models 1879.6 Predictive Analytics Techniques 1889.6.1 Decision Tree 1889.6.2 Regression Model 1899.6.3 Artificial Neural Network 1909.6.4 Bayesian Statistics 1919.6.5 Ensemble Learning 1929.6.6 Gradient Boost Model 1929.6.7 Support Vector Machine 1939.6.8 Time Series Analysis 1949.6.9 k-Nearest Neighbors (k-NN) 1949.6.10 Principle Component Analysis 1959.7 Dataset Used in Our Research 1969.8 Methodology 1989.8.1 Comparing Link-Level Features 1999.8.2 Comparing Feature Models 2009.9 Results 2019.10 Discussion 2029.11 Use of Predictive Analytics 2049.11.1 Banking and Financial Services 2059.11.2 Retail 2059.11.3 Well-Being and Insurance 2059.11.4 Oil Gas and Utilities 2069.11.5 Government and Public Sector 2069.12 Conclusion and Future Work 206References 20810 ADVANCEMENT IN AUGMENTED AND VIRTUAL REALITY 211Omprakash Dewangan, Latika Pinjarkar, Padma Bonde and Jaspal Bagga10.1 Introduction 21210.2 Proposed Methodology 21410.2.1 Classification of Data/Information Extracted 21510.2.2 The Phase of Searching of Data/Information 21610.3 Results 21810.3.1 Original Copy Publication Evolution 21810.3.2 General Information/Data Analysis 22410.3.2.1 Nations 22410.3.2.2 Themes 22710.3.2.3 R&D Innovative Work 22710.3.2.4 Medical Services 22910.3.2.5 Training and Education 23010.3.2.6 Industries 23210.4 Conclusion 233References 23511 COMPUTER VISION AND IMAGE PROCESSING FOR PRECISION AGRICULTURE 241Narendra Khatri and Gopal U Shinde11.1 Introduction 24211.2 Computer Vision 24311.3 Machine Learning 24411.3.1 Support Vector Machine 24511.3.2 Neural Networks 24511.3.3 Deep Learning 24511.4 Computer Vision and Image Processing in Agriculture 24611.4.1 Plant/Fruit Detection 24911.4.2 Harvesting Support 25211.4.3 Plant Health Monitoring Along With Disease Detection 25211.4.4 Vision-Based Vehicle Navigation System for Precision Agriculture 25211.4.5 Vision-Based Mobile Robots for Agriculture Applications 25711.5 Conclusion 259References 25912 A NOVEL APPROACH FOR LOW-QUALITY FINGERPRINT IMAGE ENHANCEMENT USING SPATIAL AND FREQUENCY DOMAIN FILTERING TECHNIQUES 265Mehak Sood and Akshay Girdhar12.1 Introduction 26612.2 Existing Works for the Fingerprint Ehancement 26912.2.1 Spatial Domain 26912.2.2 Frequency Domain 27012.2.3 Hybrid Approach 27112.3 Design and Implementation of the Proposed Algorithm 27212.3.1 Enhancement in the Spatial Domain 27312.3.2 Enhancement in the Frequency Domain 27912.4 Results and Discussion 28212.4.1 Visual Analysis 28312.4.2 Texture Descriptor Analysis 28512.4.3 Minutiae Ratio Analysis 28512.4.4 Analysis Based on Various Input Modalities 29312.5 Conclusion and Future Scope 293References 29613 ELEVATE PRIMARY TUMOR DETECTION USING MACHINE LEARNING 301Lokesh Pawar, Pranshul Agrawal, Gurjot Kaur and Rohit Bajaj13.1 Introduction 30113.2 Related Works 30213.3 Proposed Work 30313.3.1 Class Balancing 30413.3.2 Classification 30413.3.3 Eliminating Using Ranker Algorithm 30513.4 Experimental Investigation 30513.4.1 Dataset Description 30513.4.2 Experimental Settings 30613.5 Result and Discussion 30613.5.1 Performance Evaluation 30613.5.2 Analytical Estimation of Selected Attributes 31113.6 Conclusion 31113.7 Future Work 312References 31214 COMPARATIVE SENTIMENT ANALYSIS THROUGH TRADITIONAL AND MACHINE LEARNING-BASED APPROACH 315Sandeep Singh and Harjot Kaur14.1 Introduction to Sentiment Analysis 31614.1.1 Sentiment Definition 31614.1.2 Challenges of Sentiment Analysis Tasks 31814.2 Four Types of Sentiment Analyses 31914.3 Working of SA System 32114.4 Challenges Associated With SA System 32314.5 Real-Life Applications of SA 32414.6 Machine Learning Methods Used for SA 32414.7 A Proposed Method 32614.8 Results and Discussions 32814.9 Conclusion 333References 33415 APPLICATION OF ARTIFICIAL INTELLIGENCE AND COMPUTER VISION TO IDENTIFY EDIBLE BIRD’S NEST 339Weng Kin Lai, Mei Yuan Koay, Selina Xin Ci Loh, Xiu Kai Lim and Kam Meng Goh15.1 Introduction 34015.2 Prior Work 34215.2.1 Low-Dimensional Color Features 34215.2.2 Image Pocessing for Automated Grading 34315.2.3 Automated Classification 34315.3 Auto Grading of Edible Birds Nest 34315.3.1 Feature Extraction 34415.3.2 Curvature as a Feature 34415.3.3 Amount of Impurities 34415.3.4 Color of EBNs 34515.3.5 Size—Total Area 34615.4 Experimental Results 34715.4.1 Data Pre-Processing 34715.4.2 Auto Grading 34915.4.3 Auto Grading of EBNs 35315.5 Conclusion 355Acknowledgments 356References 35616 ENHANCEMENT OF SATELLITE AND UNDERWATER IMAGE UTILIZING LUMINANCE MODEL BY COLOR CORRECTION METHOD 361Sandeep Kumar, E. G. Rajan and Shilpa Rani16.1 Introduction 36216.2 Related Work 36216.3 Proposed Methodology 36416.3.1 Color Correction 36416.3.2 Contrast Enhancement 36516.3.3 Multi-Fusion Method 36616.4 Investigational Findings and Evaluation 36716.4.1 Mean Square Error 36716.4.2 Peak Signal–to-Noise Ratio 36816.4.3 Entropy 36816.5 Conclusion 375References 376Index 381
Modern Deep Learning Design and Application Development
Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and deep-learning case studies, this book reveals how to acquire the tools you need to design and implement like a deep-learning architect. It covers tools deep learning engineers can use in a wide range of fields, from biology to computer vision to business. With nine in-depth case studies, this book will ground you in creative, real-world deep learning thinking.You’ll begin with a structured guide to using Keras, with helpful tips and best practices for making the most of the framework. Next, you’ll learn how to train models effectively with transfer learning and self-supervised pre-training. You will then learn how to use a variety of model compressions for practical usage. Lastly, you will learn how to design successful neural network architectures and creatively reframe difficult problems into solvable ones. You’ll learn not only to understand and apply methods successfully but to think critically about it.Modern Deep Learning Design and Methods is ideal for readers looking to utilize modern, flexible, and creative deep-learning design and methods. Get ready to design and implement innovative deep-learning solutions to today’s difficult problems.WHAT YOU’LL LEARN* Improve the performance of deep learning models by using pre-trained models, extracting rich features, and automating optimization.* Compress deep learning models while maintaining performance.* Reframe a wide variety of difficult problems and design effective deep learning solutions to solve them. * Use the Keras framework, with some help from libraries like HyperOpt, TensorFlow, and PyTorch, to implement a wide variety of deep learning approaches.WHO THIS BOOK IS FORData scientists with some familiarity with deep learning to deep learning engineers seeking structured inspiration and direction on their next project. Developers interested in harnessing modern deep learning methods to solve a variety of difficult problems.Andre Ye is a data science writer and editor; he has written over 300 data science articles for various top data science publications with over ten million views. He is also a cofounder at Critiq, a peer revision platform that uses machine learning to match users’ essays. In his spare time, Andre enjoys keeping up with current deep learning research, playing the piano, and swimming.Chapter 1: “A Deep Dive Into Keras”Chapter Goal: To give a structured yet deep overview of Keras and to lay the groundwork for implementations in future chapters.Number of Pages: ~30Subtopics1. Why Keras? Versatility and simplicity.2. Steps needed to create a Keras model: define architecture, compile, fit.a. Compile: discuss TensorFlow optimizers, losses, and metrics.b. Fit: discuss callbacks.3. Sequential model + example.4. Functional model + example.5. Visualizing Keras models.6. Data: using NumPy arrays, Keras Image Data Generator, and TensorFlow datasets.7. Hardware: using and accessing CPU, GPU, and TPU.Chapter 2: Pre-training Strategies and Transfer LearningChapter Goal: To understand the importance of transfer learning and to use a variety of transfer learning methods to solve deep learning problems efficiently.Number of Pages: ~30Subtopics1. Transfer learning theory, practical tips and tricks.2. Accessing and using Keras and TensorFlow pretrained models.a. Bonus: converting PyTorch models (PyTorch has a wider variety) into Keras models for greater access to pretrained networks.3. Manipulating pretrained models with other network elements.4. Layer freezing.5. Self-supervised learning methods.Chapter 3: “The Versatility of Autoencoders”Chapter Goal: To understand the versatility of autoencoders and to be able to use them in a wide variety of problem scenarios.Number of Pages: ~30Subtopics1. Autoencoder theory.2. One-dimensional data autoencoder implementation, tips and tricks.3. Convolutional autoencoder implementation, tips and tricks, special concerns.4. Using autoencoders for pretraining.a. Example case study: TabNet.5. Using autoencoders for feature reduction.6. Variational autoencoders for data generation.Chapter 4: “Model Compression for Practical Deployment”Chapter Goal: To understand pruning theory, implement pruning for effective model compression, and to recognize the important role of pruning in modern deep learning research.Number of Pages: ~20Subtopics1. Pruning theory.2. Pruning Keras models with TensorFlow.3. Exciting implications of pruning – the Lottery Ticket Hypothesis.a. Example case-study: no-training neural networks.b. Example case-study: extreme learning machines.Chapter 5: “Automating Model Design with Meta-Optimization”Chapter Goal: To understand what meta-optimization is and to be able to use it to effectively automate the design of neural networks.Number of Pages: ~20Subtopics1. Meta-optimization theory.2. Demonstration of meta-optimization using HyperOpt on Keras.3. Demonstration of Auto-ML and Neural Architecture Search.Chapter 6: “Successful Neural Network Architecture Design”Chapter Goal: To gain an understanding of principles in successful neural network architecture design through three case studies.Number of Pages: ~25Subtopics1. Diversity of neural network designs and the need to design specific architectures for particular problems.2. Theory and implementation of block/cell/module design and considerations.a. Example case study: Inception model.3. Theory and implementation of “Normal” and “extreme” usages of skip connections.a. Parallel towers and cardinalityb. Example case study: UMAP model.4. Neural network scaling.a. Example case study: EfficientNet.Chapter 7: “Reframing Difficult Deep Learning Problems”Chapter Goal: To explore how hard problems can be reframed to be solved by deep learning with three case studies.Number of Pages: ~30Subtopics1. The diversity of problems deep learning is being used to solve.2. Example case study: Siamese networks – experimenting with architecture.3. Example case study: DeepInsight – experimenting with data representation.4. Example case study: Semi-supervised generative adversarial networks – experimenting with data availability.
Introducing Robotic Process Automation to Your Organization
For your robotic process automation (RPA) program to be successful, you need to follow a general framework and governance model. This book covers, in detail, what they should look like and how to adapt them to your organization.INTRODUCING ROBOTIC PROCESS AUTOMATION TO YOUR ORGANIZATION is structured to enable you, a novice to RPA, to successfully implement an RPA program at your company. RPA is rapidly growing in use, but is only starting to be taught at a university level. Many mid-level managers will be tasked with introducing an RPA program at their organizations as senior management learns of its efficacy, but will be unfamiliar with how to do so. This book provides you with the skills and information you need to make an informed decision.For decades, there has been much discussion about the fast pace of technology, the rapidly changing technology environment, and the need for companies to be on the cutting edge to remain competitive or even relevant. In this ever-changing environment, there is a need to know what can be done in terms of current processes, here and now, that will increase efficiency, benefit customers, and improve profitability. One option is RPA.This book includes information to assist you in getting the required buy-in and identifying the first few processes for automation. A structure for identifying opportunities on an ongoing basis is detailed, along with concepts that must be considered for solution design and deployment. Throughout the book there are several "pause and consider" statements to help you think about how principles pertain to your organization. Additionally, there are tips included that offer short, concrete suggestions on how to help implement the particular step being discussed.WHAT YOU WILL LEARN* Know the benefits of robotic process automation (RPA)* Understand the limitations of RPA* Ask the right questions to determine whether a process is a good candidate for automation* Obtain buy-in from skeptics at the senior and middle manager levels, and from line workers* Be familiar with the structure required for successWHO THIS BOOK IS FORMiddle managers who have either identified the need for robotic process automation (RPA) in their organization or have been directed by senior management to explore the possibility of introducing RPA to their organization; managers at all levels who hear about RPA, either through conferences, professional associations, or industry publications, and want to know more; students of business and technology who wish to broaden their understanding of important current trends.ANDRIY STOROZHUK has extensive expertise in all aspects of Lean Six Sigma, and he has utilized those skills in a variety of environments and methodologies. He has incorporated that knowledge, along with knowledge received in his university studies and constant ongoing training, in all of his work. Most recently, he brought that knowledge and experience to bear in creating an RPA program at his current place of employment.KAMAL GOYAL has been working exclusively in the field of RPA for the last six years. He has been instrumental in establishing the required infrastructure at several companies, including where he currently works. He, too, is constantly learning to keep abreast of current trends within IT.ROBERT FANTINA is an acknowledged process improvement expert, and has worked closely with Andriy and Kamal in establishing an effective and successful RPA program at his most recent place of employment. He is the author of eight books, including Practical Software Process Improvement and Your Customers’ Perception of Quality: What It Means to Your Bottom Line and How to Control It (co-author Baboo Kureemun). His paper, "Successful Software Process Implementation", was published in the journal, Software Quality Professional. He has given presentations on process improvement and quality at conferences in Atlanta, Georgia and Los Angeles, California and Orlando, Florida, among other places.Andriy, Kamal, and Robert have, combined, over 70 years of experience in various aspects of information technology.INTRODUCTIONCHAPTER 1. Initial PreparationChapter Goal: To inform the reader of different ways RPA is brought into an organization, and how to get buy-in depending on the method of introduction.- Need for RPA- Senior Management Decision- Mid-Level Management Idea- A Technology Leader Recognizes the Importance of RPACHAPTER 2. Operating Model - Governance, Sponsorship and FrameworkChapter Goal: To educate the reader on the overall structure required for an effective RPA program.- Governance: this section will assist the reader in knowing how best to structure governance within the context of his/her organization.- Sponsorship: the roles that generally provide sponsorship, and their attendant duties, are described.- Framework: a basic overview of the structure is discussed, with information on how to apply it within different types of organizations.CHAPTER 3. Opportunity IdentificationChapter Goal: To ensure that the reader has a clear idea of the kinds of processes that might be suitable for automation.- Discussion with department managers.CHAPTER 4. Opportunity AssessmentChapter Goal: To enable the reader to fully and efficiently make an assessment on whether or not a process proposed for automation is a suitable candidate.- Basic request form- Mapping the process.- Determining suitability (it is pointless to automate an inefficient process)- Meeting with governance groupCHAPTER 5. Solution DesignChapter Goal: To ensure that the reader knows how best to build a solution that will effectively automate the process.- Understanding risks- Understanding upstream and downstream changes required, and their potential impacts.CHAPTER 6. Solution Deployment, Maintenance and RetirementChapter Goal: To explain how to actually deploy the solution.- Piloting- Warranty period- Maintenance- Reuse- Phase out when the process is no longer required (if this is an eventuality)CHAPTER 7. Organizational StructureChapter Goal: RPA in your organization- Maximizing usage- Hub and Spoke- Etc.CHAPTER 8. Product Development MethodologiesChapter Goal: To explain how RPA is compatible with various development methodologies- Agile- Waterfall- Lean- DevOps- Etc.CHAPTER 9. Designing for FutureChapter Goal: Looking ahead within your organization- Designing processes digitally- Full stack automation- Simulation testing- ComplianceCHAPTER 10. SummaryChapter Goal: To concisely state the vital points of RPA- Conclusion- Wrapping it all together- High points (must haves) for successful RPA- FrameworkAPPENDIXChapter Goal: To provide tools for the RPA manager.- Templateso Request formo Business caseo Risk assessmento Map/flowchart (Visio)o Map/flowchart documentation (Word)- FAQs
Data-Driven Alexa Skills
Design and build innovative, custom, data-driven Alexa skills for home or business. Working through several projects, this book teaches you how to build Alexa skills and integrate them with online APIs. If you have basic Python skills, this book will show you how to build data-driven Alexa skills. You will learn to use data to give your Alexa skills dynamic intelligence, in-depth knowledge, and the ability to remember.DATA-DRIVEN ALEXA SKILLS takes a step-by-step approach to skill development. You will begin by configuring simple skills in the Alexa Skill Builder Console. Then you will develop advanced custom skills that use several Alexa Skill Development Kit features to integrate with lambda functions, Amazon Web Services (AWS), and Internet data feeds. These advanced skills enable you to link user accounts, query and store data using a NoSQL database, and access real estate listings and stock prices via web APIs.WHAT YOU WILL LEARN* Set up and configure your development environment properly the first time* Build Alexa skills quickly and efficiently using Agile tools and techniques* Create a variety of data-driven Alexa skills for home and business* Access data from web applications and Internet data sources via their APIs* Test with unit-testing frameworks throughout the development life cycle* Manage and query your data using the DynamoDb NoSQL database enginesWHO THIS BOOK IS FORDevelopers who wish to go beyond Hello World and build complex, data-driven applications on Amazon's Alexa platform; developers who want to learn how to use Lambda functions, the Alexa Skills SDK, Alexa Presentation Language, and Alexa Conversations; developers interested in integrating with public APIs such as real estate listings and stock market prices. Readers will need to have basic Python skills.SIMON KINGABY is a software developer, programming professor, and public speaker residing in middle Tennessee. He believes that voice user interfaces will change the world and that tools like Alexa are just the tip of the iceberg. He spends his days moving data for Deloitte Global and teaching DataViz and FinTech at Vanderbilt University. In 2016, he published his first Alexa skill and has been enthralled by voice development ever since. In 2017, his uncle suddenly went blind and Simon began exploring ways Alexa could be used to help the blind by developing skills from “What’s the time?” and home navigation skills to smart home skills like “Turn on the coffee pot." In 2019 that same uncle committed suicide, and Simon turned his attention to mental health issues and using Alexa to help identify and prevent suicidal behavior. Now he is focused on enabling developers to use their programming abilities to build data-driven Alexa skills that will make a real difference in the world.PART I: GETTING STARTEDChapter 1: Voice User InterfacesChapter 2: Routines and BlueprintsChapter 3: The Developer AccountsChapter 4: Creating the VUI for a Custom Data-driven SkillChapter 5: Writing the Back-end CodeChapter 6: Publishing an Alexa SkillPART II: CUSTOM SKILL DEVELOPMENTChapter 7: Custom Alexa SkillsChapter 8: Beyond Hello WorldChapter 9: Configuring the VUIChapter 10: Using APL to Present on ScreensChapter 11: Coding the Lambda FunctionChapter 12: Unit Testing an Alexa SkillChapter 13: Storing the DataPART III: USING APIS IN ADVANCED SKILLSChapter 14: A Personal Net Worth SkillChapter 15: The Real Estate APIChapter 16: The Stock Market APIChapter 17: What’s Next?
Digineering
Als Folge der zunehmenden Verfügbarkeit neuer Informationstechnologien entstehen völlig neue Kundenerwartungen, Geschäftsmodelle und Prozesse. Die umfassende Neugestaltung digitaler Prozesse ist mit Konzepten der Vergangenheit nicht zu bewältigen. Business Process Management benötigt angepasste Methoden, Fähigkeiten, Technologien und Strukturen.„Digineering“ steht für die Kombination der Aspekte einer zunehmenden Digitalisierung mit den Methoden und Vorgehensweisen des Re-Engineering und überträgt damit Ansätze aus dem Business Process Management, dem Management der digitalen Transformation und dem Software-Engineering auf die aktuellen Herausforderungen der Prozessdigitalisierung.„Digineering“ liefert einen agilen Lösungsansatz, der alle Phasen der Prozessdigitalisierung von der Analyse der Kundenanforderungen über die Prozessgestaltung bis zur Implementierung neuer IT-Anwendungen umfasst. In allen Phasen werden die Potenziale innovativer IT einbezogen, um so ganzheitliche Prozesse mit einzigartigem Kundenerlebnis und hoher Effizienz zu schaffen.PROF. DR. ARNO MÜLLER lehrt an der NORDAKADEMIE Hochschule der Wirtschaft Prozessmanagement, strategisches IT-Management und Logistik und ist Geschäftsführer der bps business process solutions GmbH.PROF. DR. HINRICH SCHRÖDER ist Professor und Studiengangsleiter für Wirtschaftsinformatik an der NORDAKADEMIE Hochschule der Wirtschaft.LARS VON THIENEN ist Geschäftsführer der bps business process solutions GmbH und berät Unternehmen bei der Transformation der IT-Organisation und dem Aufbau von innovativen IT-Management-Methoden.Bausteine des Digineering.- Fitness-Check zur Entwicklung der Technology- und Capability-Roadmap.- Methoden und Rollenmodell für die Prozessdigitalisierung: (Ro)-Bots: Orchestrierung von digitalen Services und Mensch-Maschine-Kommunikation.- Roadmap zur Aufdeckung und Realisierung der KI-Potenziale in der Prozessdigitalisierung.- Dataism: Wertschöpfung mit datengetriebenen Geschäftsmodellen.- Steuerung der unternehmensweiten Prozessdigitalisierung.- Operating-Model für digitalisierte Prozesse.
Beginning IntelliJ IDEA
Get started quickly with IntelliJ, from installation to configuration to working with the source code and more. This tutorial will show you how to leverage IntelliJ’s tools to develop clean, efficient Java applications.Author TED HAGOS will first walk you through buidling your first Java applications using IntelliJ. Then, he’ll show you how to analyze your application, top to bottom; using version control and tools that allow you expand your application for big data or data science applications and more. You'll also learn some of the IDE’s advanced features to fully maximize your application's capabilities.The last portion of the book focuses on application testing and deployment, and language- and framework- specific guidelines. After reading this book and working through its freely available source code, you'll be up to speed with this powerful IDE for today's Java development.WHAT YOU WILL LEARN* Use IntelliJ IDEA to build Java applications* Set up your IDE and project* Work with source code* Extend your Java application to data science and other kinds of applications* Test and deploy your application and much moreWHO THIS BOOK IS FORProgrammers new to IntelliJ IDEA who may have some prior exposure to Java programming.Ted Hagos is a software developer by trade; at the moment, he’s Chief Technology Officer and Data Protection Officer of RenditionDigital International, a software development company based out of Dublin. He wore many hats in his 20+ years in software development e.g. team lead, project manager, architect and director for development. He also spent time as a trainer for IBM Advanced Career Education, Ateneo ITI and Asia Pacific College. He wrote a couple of books for Apress.1. Install IntelliJ2. Getting Started3. Configuring the IDE4. Configuring Projects5. Working with Source Code6. Building Applications7. Analyzing Applications8. Version Control9. Big Data / Data Science Tools10. Other Tools11. Advanced IDE Features12. Migration Guides13. Language and Framework Specific Guidelines14. Testing15. Deployment
Four Laws for the Artificially Intelligent
ASK NOT WHAT AI CAN DO FOR A COMPANY, RATHER WHAT ARTIFICIAL INTELLIGENCE MAY DO TO A COMPANY.* How does a company successfully integrate artificial intelligence into its operations?* What are the problems in doing so?* And how does the introduction of AI into society change the answer to the first question?As companies delay or even cancel initiatives in artificial intelligence, Four Laws for the Artificially Intelligent redefines possibilities and offers leverage to turn AI visions into reality. It is a story of transformation: of people, of companies, and of artificial intelligence itself.The Four Laws is unique in its combination of stories and science illustrating how a technology competing with human consciousness is introduced and assimilated within a company. A work of creative nonfiction stretched on a frame of research, it is an essential trail guide for navigating the Industry Version 4.0 jungle in a search of the fruits of innovation.
Unity Networking Fundamentals
Learn the fundamentals of networking with Unity and C#. This book covers a variety of topics, including accessing data using RESTful APIs, local networked games, and creating multiplayer online games using client-server architecture.The book provides the basics of networking, sockets, TCP vs. UDP, client-server architecture, serialization, RESTful APIs, network latency, and client-side prediction. Projects are presented to illustrate the concepts, including a chat client/server overlay for your game, and a 3D maze game that allows up to four players to connect over the network.By the end of the book, you will be familiar with low-level networking concepts such as protocols and architecture as well as high-level knowledge on how to create applications that use a client/server architecture for multiplayer games.WHAT YOU WILL LEARN* Know the difference between TCP and UDP, and the pros and cons of these protocols* Create client-server multiplayer games in Unity using C#* Receive and process data from a remote server using RESTful APIs* Understand latency and how to mitigate its impact WHO THIS BOOK IS FORReaders familiar with Unity and C# development who want to create multiplayer games SLOAN KELLY has worked in the games industry for more than 13 years. He has worked on a number of AAA and indie titles and currently works for an educational game company. He lives in Ontario, Canada with his wife and children. Sloan is on Twitter @codehoose and makes YouTube videos in his spare time.KHAGENDRA KUMAR has worked with a number of educational institutions and game studios for training and solutions. He lives in Bihar, India and spends most of his time working with game AI. He can be reached via Linkedin at /itskhagendra and Instagram @Khagendra_Developer.Chapter 1: Networking ConceptsChapter 2: SerializationChapter 3: Restful APIsChapter 4: TCP connectionsChapter 5: Networking IssuesChapter 6: Develop Maze ShooterChapter 7: LAN NetworkingChapter 8: Servers
WebAssembly for Cloud
Journey into the amazing world of WebAssembly (Wasm) and learn about how it can be applied on the cloud. This book is an introduction to Wasm aimed at professionals accustomed to working with cloud-related technologies such as Kubernetes and Istio service mesh.Author SHASHANK JAIN begins with an introduction to Wasm and its related tooling such as wasm-bindgen and wapc. He then walks you through code examples using Rust, Golang, and JavaScript to demonstrate how they can be compiled to Wasm and consumed from Wasm runtimes deployed standalone, as well as on the cloud. You will see how a wasm module can be run through an http interface, and how Wasm fits into CNCF projects such as Kubernetes and Istio service mesh. After that, you’ll learn how the polyglot nature of WebAssembly can be leveraged through examples written in languages like Rust and consumed via Golang and JavaScript, with a focus on how WebAssembly allows interoperability between them. You’ll gain an understanding of how Wasm-based modules can be deployed inside Linux containers and orchestrated via Kubernetes, and how Wasm can be used within the Istio proxy to apply rules and filters.After reading this book, you’ll have the knowledge necessary to apply WebAssembly to create multi tenanted workloads which can be polyglot in nature and can be deployed on cloud environments like Kubernetes.WHAT YOU WILL LEARN* Understand how Wasm can be used for server-side applications* Learn about Wasm memory model and Wasm module layout* How communication between host and Wasm module is facilitated* The basics of Wasm sandboxing and security* The fundamentals of tooling around Wasm, such as WAT and Wasm-pack* Create a Wasm module in Rust and consume it from JavaScript, Rust and Golang.* Grasp how Kubernetes can be used to orchestrate Wasm-based workloads* How Wasm fits into service meshWHO IS THIS BOOK FORSoftware developers/architects who are looking to hone their skills in virtualization and explore alternatives to Docker and container-based technologies for their workload deployments. Readers should have a basic programming background in languages such as Rust and Golang to get the most out of this book.Shashank Mohan Jain has been working in the IT industry for around 20 years mainly in the areas of cloud computing and distributed systems. He has keen interests in virtualization techniques, security, and complex systems. Shashank has 32 software patents (many yet to be published) to his name in the area of cloud computing, IoT, and machine learning. He is a speaker at multiple reputed cloud conferences. Shashank holds Sun, Microsoft, and Linux kernel certifications.CHAPTER 1: INTRODUCTION TO WEBASSEMBLY (WASM)Chapter Goal :History and Introduction to Wasm• What is WebAssembly and why is it important for Cloud native• Wasm architecture and how we realize virtualization via Wasm• Kind of workloads supported by Wasm (Cloud, Browser, and Edge)CHAPTER 2: WEBASSEMBLY MEMORY MODEL AND RUNTIMESChapter Goal: Memory model internals and layout of Wasm modules in memory• Introduction to Wasm file format• Deep dive into the sections of the Wasm file (function table, types, etc.) and their relevance• Memory layout for tenant isolation within a linux process using WasmCHAPTER 3: WEBASSEMBLY TEXT TOOLKITChapter Goal: Covers the WebAssembly text format by showing examples of how to write Wasm. Usage of tools like wasm2wat will also be covered with examples• Introduction to WebAssembly text format (wat)• Creating simple wat programs and compiling to Wasm using wat2wasm toolCHAPTER 4: RUST AND WEBASSEMBLY Chapter Goal: Covers examples of how to create a Wasm module in Rust and invoke it via JS and other runtimes• Creating a Rust program and compiling it as a Wasm module• Explain wasm-bindgen tool for compiling Rust to Wasm• Consuming the Rust program from a JavaScript-based runtime like Node.jsCHAPTER 5: GOLANG AND WEBASSEMBLY Chapter Goal: Covers examples of how to create a Wasm module in Golang and invoke it via JS and other runtimes• Create a Golang program and expose it as a Wasm module• Use WaPC (web assembly procedure call) to consume this program fromo Rusto Node.js• Show how complex types can be created in Wasm using WaPC and how these types can be passed between guest and host boundariesCHAPTER 6: WRITING A SIMPLE WEB APPLICATION IN WEBASSEMBLYChapter Goal: How to create a simple web app in WebAssembly• Expose the Wasm module using a web application• Web application will be written ino Rusto Node.jso Golang• All three runtimes will embed a Wasm engine and load a Wasm module on an http request. Invoke the exposed function within Wasm module and return back the http responseCHAPTER 7: DEPLOYING WASM WORKLOADS TO KUBERNETES AND SERVICE MESHChapter Goal: Showcase how Wasm modules can be deployed using the kubernetes control plane and can be represented as pods instead of Docker containers. Also covers some of the serverless aspects around and detail out a service mesh scenario where we can use Wasm-based filters for massaging the data on the Istio data plane• Intro to Kubernetes• Dockerize the embedded Wasm engine in the runtimes created in Chapter 6• Host these docker images into dockerhub• Create a Kubernetes pod using these docker images• Deploy the pod into kubernetes• Expose the web servers (hosting the Wasm runtime) as a service in k8s• Show invocation of the Wasm modules via the service• Intro to Istio and Service Mesh in context of API gateways• Create a simple Wasm filter for Istio/Envoy• Show invocation of the Wasm filter as part of the data pathCHAPTER 8: SUMMARYChapter Goal : Summary of the topics around Wasm and its usage• Summary of Wasm and various runtimes for Wasm• Summarize enablement of Wasm-based workloads on k8s
Language Server Protocol and Implementation
Understand the important aspects of implementing a production-grade language server in support of language-smart tools such as code editors and other programming utilities. This book shows you how to create a single implementation of a language server that can be used by multiple tools, enabling you to do the job once in a way that can be shared and reused.This book covers the language server protocol used for communication between programming tools and your language server. The book also provides an in-depth understanding of the design, implementation, and user experience aspects which should be considered when implementing a language server. The book walks you through an example language server implementation to illustrate the basic concepts, then goes on to cover advanced aspects of language server use such as progress reporting, launchers, and extension points.User experience is an important aspect of language server implementation and different tooling vendors strive to provide their own unique user experiences. This book explains how the protocol features can be leveraged to address the unique developer experience provided by different tooling vendors. The book also shows how to enhance the smoothness of the editing experience by orchestrating multiple features together.WHAT YOU WILL LEARN* Implement a language server from scratch* Understand language server protocol and its data models* Leverage the protocol while preserving the unique user experience of different editors* Extend the protocol to support more than its standard capabilities* Run a language server on top of launchers such as standard I/O and TCP socket* Seamlessly incorporate language semantics into your protocol featuresWHO THIS BOOK IS FORDevelopers focused on and passionate about implementing language development tools such as plug-ins and extensions for interactive development environments (IDEs) or other tools that rely upon parsing of language statements and commands, and developers who need an in-depth understanding of the language server protocol as well as how to use the language server protocol to develop extensible language servicesNADEESHAAN GUNASINGHE is Technical Lead at WSO2 and has more than five years of experience in enterprise integration, programming languages, and developer tooling. He leads the Ballerina Language Server team and is a key contributor to Ballerina, which is an open-source programming language and platform for the cloud, and he is an active contributor to the WSO2 Enterprise Service Bus.NIPUNA MARCUS is Technical Lead at WSO2 and has more than five years of experience in front end development, programming languages, and developer tooling. He was a member of the Ballerina Language Server team and a key contributor to the Ballerina programming language. 1. Developer Tools and Language Services2. Understanding the Language Server Protocol3. Implementing a Language Server4. General Messages5. Text Synchronization6. Diagnostics, Smart Editing, and Documentation7. Refactoring and Code Fixes8. Code Navigation and Navigation Helpers9. Presentation and Folding10. Workspace Operations11. Advanced ConceptsA. Data Models and Resources
Expert Oracle Database Architecture
Now in its fourth edition and covering Oracle Database 21c, this best-selling book continues to bring you some of the best thinking on how to apply Oracle Database to produce scalable applications that perform well and deliver correct results. Tom Kyte and Darl Kuhn share a simple philosophy: "you can treat Oracle as a black box and just stick data into it, or you can understand how it works and exploit it as a powerful computing environment." If you choose the latter, then you’ll find that there are few information management problems that you cannot solve quickly and elegantly.This fully revised fourth edition covers the developments and new features up to Oracle Database 21c. Up-to-date features are covered for tables, indexes, data types, sequences, partitioning, data loading, temporary tables, and more. All the examples are demonstrated using modern techniques and are executed in container and pluggable databases. The book’s proof-by-example approach encourages you to let evidence be your guide. Try something. See the result. Understand why the result is what it is. Apply your newfound knowledge with confidence. The book covers features by explaining how each one works, how to implement software using it, and the common pitfalls associated with it.Don’t treat Oracle Database as a black box. Get this book. Dive deeply into Oracle Database’s most powerful features that many do not invest the time to learn about. Set yourself apart from your competition and turbo-charge your career.WHAT YOU WILL LEARN* Identify and effectively resolve application performance issues and bottlenecks* Architect systems to leverage the full power and feature set of Oracle’s database engine* Configure a database to maximize the use of memory structures and background processes* Understand internal locking and latching technology and how it impacts your system* Proactively recommend best practices around performance for table and index structures* Take advantage of advanced features such as table partitioning and parallel executionWHO THIS BOOK IS FOROracle developers and Oracle DBAs. If you’re a developer and want a stronger understanding of Oracle features and architecture that will enable your applications to scale regardless of the workload, this book is for you. If you’re a DBA and want to intelligently work with developers to design applications that effectively leverage Oracle technology, then look no further.DARL KUHN is a DBA/developer working for Oracle. He also teaches Oracle classes at Regis University in Denver, Colorado, and is an active member of the Rocky Mountain Oracle Users Group. Darl enjoys sharing knowledge and has authored several books.THOMAS KYTE is a former vice president of the Core Technologies Group at Oracle Corporation. He is the same Tom who created the "Ask Tom" website and the Oracle Magazine column of the same name. He has a long history of answering questions about the Oracle database and tools that developers and database administrators struggle with every day.1. Developing Successful Oracle Applications2. Architecture Overview3. Files4. Memory Structures5. Oracle Processes6. Locking and Latching7. Concurrency and Multi-versioning8. Transactions9. Redo and Undo10. Database Tables11. Indexes12. Datatypes13. Partitioning14. Parallel Execution15. Data Loading and Unloading
Automated Essay Scoring
THIS BOOK DISCUSSES THE STATE OF THE ART OF AUTOMATED ESSAY SCORING, ITS CHALLENGES AND ITS POTENTIAL. One of the earliest applications of artificial intelligence to language data (along with machine translation and speech recognition), automated essay scoring has evolved to become both a revenue-generating industry and a vast field of research, with many subfields and connections to other NLP tasks. In this book, we review the developments in this field against the backdrop of Elias Page's seminal 1966 paper titled "The Imminence of Grading Essays by Computer."Part 1 establishes what automated essay scoring is about, why it exists, where the technology stands, and what are some of the main issues.In Part 2, the book presents guided exercises to illustrate how one would go about building and evaluating a simple automated scoring system, while Part 3 offers readers a survey of the literature on different types of scoring models, the aspects of essay quality studied in prior research, and the implementation and evaluation of a scoring engine. Part 4 offers a broader view of the field inclusive of some neighboring areas, and Part \ref{part5} closes with summary and discussion.This book grew out of a week-long course on automated evaluation of language production at the North American Summer School for Logic, Language, and Information (NASSLLI), attended by advanced undergraduates and early-stage graduate students from a variety of disciplines. Teachers of natural language processing, in particular, will find that the book offers a useful foundation for a supplemental module on automated scoring. Professionals and students in linguistics, applied linguistics, educational technology, and other related disciplines will also find the material here useful.* Preface* Building an Automated Essay Scoring System* From Lessons to Guidelines* Models* Generic Features* Genre- and Task-Specific Features* Automated Scoring Systems: From Prototype to Production* Evaluating for Real-World Use* Automated Feedback* Automated Scoring of Content* Automated Scoring of Speech* Fooling the System: Gaming Strategies* Looking Back, Looking Ahead* Definitions-in-Context* Index* References* Authors' Biographies
AI and Ed
The United States has undergone several major transformations economically, politically, and socially. Today, the impact of artificial intelligence will bring another transformation affecting citizens’ private lives as well as employment, communication, politics, and almost every other aspect of life.The question artificial intelligence raises is: what kind of education will students need in confronting the obvious and projected impact of technology? Transformations affect obvious aspects of life, but also raise significant issues that challenge values, ethics and standards.The purpose of this book is to define the role of education and its goals, content, and approaches that will assist citizens in addressing the challenges the artificial intelligence movement brings to the life of citizens. Positive aspects of the transformation include communication, productivity, and other issues. However, there are hazards and downsides to artificial intelligence that must be addressed through an educated society.Education’s role encompasses assisting individuals to address the positive and negative aspects of any creative intervention. Thinking coupled with insight into principles, ethics, and the meaning of life are critical. Education prepares individuals for changing times in order to protect their freedoms and democracy and find a life of purpose and meaning.George A. Goens, PhD, has written seven books and co-authored four on leadership, school reform, education, and social issues. He served an executive in teaching positions, as well as leadership consultant to public boards and individuals.Chapter 1: TransformationChapter 2: Personal TransformationChapter 3: Innovation: The Big and Small PictureChapter 4: TechnologyChapter 5: Artificial IntelligenceChapter 6: From Butterflies to Black SwansChapter 7: Artificial Intelligence and Real World IssuesChapter 8: Gains and LossesChapter 9: Implications: EducationChapter 10: Humans BeingsEpilogue: Intelligence, Mind, and HeartBibliographyIndexAbout the Author
Semantic Web for Effective Healthcare Systems
SEMANTIC WEB FOR EFFECTIVE HEALTHCARE SYSTEMSTHE BOOK SUMMARIZES THE TRENDS AND CURRENT RESEARCH ADVANCES IN WEB SEMANTICS, DELINEATING THE EXISTING TOOLS, TECHNIQUES, METHODOLOGIES, AND RESEARCH SOLUTIONSSemantic Web technologies have the opportunity to transform the way healthcare providers utilize technology to gain insights and knowledge from their data and make treatment decisions. Both Big Data and Semantic Web technologies can complement each other to address the challenges and add intelligence to healthcare management systems. The aim of this book is to analyze the current status on how the semantic web is used to solve health data integration and interoperability problems, and how it provides advanced data linking capabilities that can improve search and retrieval of medical data. Chapters analyze the tools and approaches to semantic health data analysis and knowledge discovery. The book discusses the role of semantic technologies in extracting and transforming healthcare data before storing it in repositories. It also discusses different approaches for integrating heterogeneous healthcare data. This innovative book offers:* The first of its kind and highlights only the ontology driven information retrieval mechanisms and techniques being applied to healthcare as well as clinical information systems;* Presents a comprehensive examination of the emerging research in areas of the semantic web; * Discusses studies on new research areas including ontological engineering, semantic annotation and semantic sentiment analysis;* Helps readers understand key concepts in semantic web applications for the biomedical engineering and healthcare fields;* Includes coverage of key application areas of the semantic web.AUDIENCE: Researchers and graduate students in computer science, biomedical engineering, electronic and software engineering, as well as industry scientific researchers, clinicians, and systems managers in biomedical fields. VISHAL JAIN is an associate professor in the Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida, U. P. India. He obtained Ph.D (CSE), M.Tech (CSE), MBA (HR), MCA, MCP and CCNA. He has authored more than 80 research papers in reputed conferences and journals, including Web of Science and Scopus. He has authored and edited more than 10 books with various international publishers. JYOTIR MOY CHATTERJEE is an assistant professor in the Department of Information Technology at Lord Buddha Education Foundation (Asia Pacific University of Technology & Innovation), Kathmandu, Nepal. ANKITA BANSAL is an assistant professor in the Division of Information Technology at Netaji Subhas University of Technology. She received her master’s and doctoral degree in computer science from Delhi Technological University (DTU). ABHA JAIN is an assistant professor in the Department of Computer Science Engineering, Shaheed Rajguru College of Applied Sciences for Women, Delhi University, India. She received her master’s and doctorate degree in software engineering from Delhi Technological University. Preface xvAcknowledgment xix1 AN ONTOLOGY-BASED CONTEXTUAL DATA MODELING FOR PROCESS IMPROVEMENT IN HEALTHCARE 1A. M. Abirami and A. Askarunisa1.1 Introduction 11.1.1 Ontology-Based Information Extraction 31.1.2 Ontology-Based Knowledge Representation 41.2 Related Work 51.3 Motivation 81.4 Feature Extraction 91.4.1 Vector Space Model 101.4.2 Latent Semantic Indexing (LSI) 111.4.3 Clustering Techniques 121.4.4 Topic Modeling 121.5 Ontology Development 171.5.1 Ontology-Based Semantic Indexing (OnSI) Model 171.5.2 Ontology Development 181.5.3 OnSI Model Evaluation 191.5.4 Metrics Analysis 231.6 Dataset Description 241.7 Results and Discussions 251.7.1 Discussion 1 291.7.2 Discussion 2 291.7.3 Discussion 3 301.8 Applications 311.9 Conclusion 321.10 Future Work 33References 332 SEMANTIC WEB FOR EFFECTIVE HEALTHCARE SYSTEMS: IMPACT AND CHALLENGES 39Hemendra Shankar Sharma and Ashish Sharma2.1 Introduction 402.2 Overview of the Website in Healthcare 452.2.1 What is Website? 452.2.2 Types of Website 452.2.2.1 Static Website 452.2.2.2 Dynamic Website 462.2.3 What is Semantic Web? 462.2.4 Role of Semantic Web 472.2.4.1 Pros and Cons of Semantic Web 492.2.4.2 Impact on Patient 512.2.4.3 Impact on Practitioner 522.2.4.4 Impact on Researchers 522.3 Data and Database 532.3.1 What is Data? 542.3.2 What is Database? 542.3.3 Source of Data in the Healthcare System 542.3.3.1 Electronic Health Record (EHR) 552.3.3.2 Biomedical Image Analysis 562.3.3.3 Sensor Data Analysis 572.3.3.4 Genomic Data Analysis 572.3.3.5 Clinical Text Mining 582.3.3.6 Social Media 592.3.4 Why Are Databases Important? 602.3.5 Challenges With the Database in the Healthcare System 612.4 Big Data and Database Security and Protection 612.4.1 What is Big Data 612.4.2 Five V’s of Big Data 622.4.2.1 Volume 622.4.2.2 Variety 632.4.2.3 Velocity 632.4.2.4 Veracity 642.4.2.5 Value 652.4.3 Architectural Framework of Big Data 652.4.4 Data Protection Versus Data Security in Healthcare 672.4.4.1 Phishing Attacks 672.4.4.2 Malware and Ransomware 672.4.4.3 Cloud Threats 672.4.5 Technology in Use to Secure the Healthcare Data 682.4.5.1 Access Control Policy 692.4.6 Monitoring and Auditing 692.4.7 Standard for Data Protection 702.4.7.1 Healthcare Standard in India 702.4.7.2 Security Technical Standards 712.4.7.3 Administrative Safeguards Standards 712.4.7.4 Physical Safeguard Standards 71References 713 ONTOLOGY-BASED SYSTEM FOR PATIENT MONITORING 75R. Mervin, Tintu Thomas and A. Jaya3.1 Introduction 763.1.1 Basics of Ontology 773.1.2 Need of Ontology in Patient Monitoring 783.2 Literature Review 783.2.1 Uses of Ontology in Various Domains 783.2.2 Ontology in Patient Monitoring System 803.3 Architectural Design 803.3.1 Phases of Patient Monitoring System 823.3.2 Reasoner in Patient Monitoring 873.4 Experimental Results 883.4.1 SPARQL Results 893.4.2 Comparison Between Other Systems 893.5 Conclusion and Future Enhancements 90References 914 SEMANTIC WEB SOLUTIONS FOR IMPROVISED SEARCH IN HEALTHCARE SYSTEMS 95Nidhi Malik, Aditi Sharan and Sadika Verma4.1 Introduction 954.1.1 Key Benefits and Usage of Technology in Healthcare System 964.2 Background 974.2.1 Significance of Semantics in Healthcare Systems 974.2.2 Scope and Benefits of Semantics in Healthcare Systems 984.2.3 Issues in Incorporating Semantics 984.2.4 Existing Semantic Web Technologies 994.3 Searching Techniques in Healthcare Systems 1004.3.1 Keyword-Based Search 1004.3.2 Controlled Vocabularies Based Search 1014.3.3 Improvising Searches With Semantic Web Solutions 1014.3.4 Health Domain-Specific Resources for Semantic Search 1024.3.4.1 Ontologies 1034.3.4.2 Libraries 1034.3.4.3 Search Engines 1034.4 Emerging Technologies/Resources in Health Sector 1084.4.1 Elasticsearch 1094.4.2 BioBERT 1094.4.3 Knowledge Graphs 1104.5 Conclusion 110References 1115 ACTIONABLE CONTENT DISCOVERY FOR HEALTHCARE 115Ujwala Bharambe and Anuradha Srinivasaraghavan5.1 Introduction 1165.2 Actionable Content 1175.2.1 Actionable Content in Theory 1175.2.2 Actionable Content in Practice 1225.3 Health Analytics 1245.3.1 Artificial Intelligence/Machine Learning-Based Predictive Analytics 1255.3.2 Semantic Technology for Prescriptive Health Analytics 1265.4 Ontologies and Actionable Content 1275.4.1 Ontologies in Healthcare Domain 1295.5 General Architecture for the Discovery of Actionable Content for Healthcare Domain 1305.5.1 Ontology-Driven Actionable Content Discovery in Healthcare Domain 1315.5.2 Case Study for Actionable Content Discovery in Cancer Domain 1345.6 Conclusion 136References 1366 INTELLIGENT AGENT SYSTEM USING MEDICINE ONTOLOGY 139Tintu Thomas and R. Mervin6.1 Introduction to Semantic Search 1406.1.1 What is an Ontology in Terms of Medicine? 1406.1.2 Needs and Benefits of Ontology in Medical Search 1416.2 Sematic Search 1426.2.1 How NLP Works in Sematic Search? 1426.2.2 Part of Speech Tagging and Chunking 1426.2.3 Sentence Parsing 1436.2.4 Discussion About the Various Semantic Search in Medical Databases 1446.2.5 Discussion About the Retrieval Tools Used in Sematic Search in Medline 1456.3 Structural Pattern of Semantic Search 1466.3.1 Architectural Diagram 1476.3.2 Agent Ontology 1486.3.3 Rule-Based Approach 1496.3.4 Reasoners-Based Approach 1516.4 Implementation of Reasoners 1526.5 Implementation and Results 1536.6 Conclusion and Future Prospective 153References 1547 ONTOLOGY-BASED SYSTEM FOR ROBOTIC SURGERY—A HISTORICAL ANALYSIS 159Ajay Agarwal and Amit Kumar Mishra7.1 Historical Discourse of Surgical Robots 1607.2 The Necessity for Surgical Robots 1627.3 Ontological Evolution of Robotic Surgical Procedures in Various Domains 1637.4 Inferences Drawn From the Table 1647.5 Transoral Robotic Surgery 1667.6 Pancreatoduodenectomy 1677.7 Robotic Mitral Valve Surgery 1687.8 Rectal Tumor Surgery 1707.9 Robotic Lung Cancer Surgery 1707.10 Robotic Surgery in Gynecology 1717.11 Robotic Radical Prostatectomy 1717.12 Conclusion 1727.13 Future Work 172References 1728 IOT-ENABLED EFFECTIVE HEALTHCARE MONITORING SYSTEM USING SEMANTIC WEB 175Sapna Juneja, Abhinav Juneja, Annu Dhankhar and Vishal Jain8.1 Introduction 1768.2 Literature Review 1778.3 Phases of IoT-Based Healthcare 1788.4 IoT-Based Healthcare Architecture 1798.5 IoT-Based Sensors for Health Monitoring 1808.6 IoT Applications in Healthcare 1828.7 Semantic Web, Ontology, and Its Usage in Healthcare Sector 1838.8 Semantic Web-Based IoT Healthcare 1838.9 Challenges of IoT in Healthcare Industry 1858.10 Conclusion 186References 1869 PRECISION MEDICINE IN THE CONTEXT OF ONTOLOGY 191Rehab A. Rayan and Imran Zafar9.1 Introduction 1929.2 The Rationale Behind Data 1959.3 Data Standards for Interoperability 1979.4 The Evolution of Ontology 1989.5 Ontologies and Classifying Disorders 1999.6 Phenotypic Ontology of Humans in Rare Disorders 2019.7 Annotations and Ontology Integration 2029.8 Precision Annotation and Integration 2039.9 Ontology in the Contexts of Gene Identification Research 2049.10 Personalizing Care for Chronic Illness 2079.11 Roadblocks Toward Precision Medicine 2089.12 Future Perspectives 2099.13 Conclusion 209References 21010 A KNOWLEDGEBASE MODEL USING RDF KNOWLEDGE GRAPH FOR CLINICAL DECISION SUPPORT SYSTEMS 215Ravi Lourdusamy and Xavierlal J. Mattam10.1 Introduction 21610.2 Relational Database to Graph Database 21710.2.1 Relational Database for Knowledge Representation 21810.2.2 NoSQL Databases 22010.2.3 Graph Database 22310.3 RDF 22510.3.1 RDF Model and Technology 22610.3.2 Metadata and URI 22610.3.3 RDF Stores 22810.4 Knowledgebase Systems and Knowledge Graphs 23010.4.1 Knowledgebase Systems 23010.4.2 Knowledge Graphs 23210.4.3 RDF Knowledge Graphs 23310.4.4 Information Retrieval Using SPARQL 23410.5 Knowledge Base for CDSS 23510.5.1 Curation of Knowledge Base for CDSS 23610.5.2 Proposed Model for Curation 23610.5.3 Evaluation Methodology 23810.6 Discussion for Further Research and Development 23910.7 Conclusion 239References 24011 MEDICAL DATA SUPERVISED LEARNING ONTOLOGIES FOR ACCURATE DATA ANALYSIS 249B. Tarakeswara Rao, R. S. M. Lakshmi Patibandla, V. Lakshman Narayana and Arepalli Peda Gopi11.1 Introduction 25011.2 Ontology of Biomedicine 25111.2.1 Ontology Resource Open Sharing 25411.3 Supervised Learning 25511.4 AQ21 Rule in Machine Learning 25611.5 Unified Medical Systems 25911.5.1 Note of Relevance to Bioinformatic Experts 25911.5.2 Terminological Incorporation Principles 26011.5.3 Cross-References External 26111.5.4 UMLS Data Access 26211.6 Performance Analysis 26211.7 Conclusion 265References 26512 RARE DISEASE DIAGNOSIS AS INFORMATION RETRIEVAL TASK 269Jaya Lakkakula, Rutuja Phate, Alfiya Korbu and Sagar Barage12.1 Introduction 27012.2 Definition 27112.3 Characteristics of Rare Diseases (RDs) 27212.4 Types of Rare Diseases 27312.4.1 Genetic Causes 27412.4.2 Non-Genetic Causes 27512.4.3 Pathogenic Causes (Infectious Agents) 27512.4.4 Toxic Agents 27512.4.5 Other Causes 27612.5 A Brief Classification 27612.6 Rare Disease Databases and Online Resources 27712.6.1 European Reference Network: ERN 27712.6.2 Genetic and Rare Diseases Information Center: GARD 27812.6.3 International Classification of Diseases, 10th Revision: ICD-10 27912.6.4 Orphanet-INSERM (Institut National de la Santé et de la Recherche Médicale) 28012.6.5 Medical Dictionary for Regulatory Activities: MedDRA 28012.6.6 Medical Subject Headings: MeSH 28112.6.7 Online Mendelian Inheritance in Man: OMIM 28212.6.8 Orphanet Rare Disease Ontology: ORDO 28212.6.9 UMLS: Unified Medical Language System 28212.6.10 SNOMED-CT: Systematized Nomenclature of Human and Veterinary Medicine—Clinical Terms 28312.7 Information Retrieval of Rare Diseases Through a Web Search and Other Methods 28412.7.1 What is Information Retrieval (IR)? 28412.7.2 Listed Below Are Some of the Methods for Information Retrieval 28412.7.2.1 Web Search for a Diagnosis 28412.7.2.2 Cause of Diagnostic Errors in Web-Based Tools 28512.7.2.3 Nonprofessional Use of Web Tool for Diagnosis 28512.7.2.4 Performance of Web Search Tools 28512.7.2.5 Design of Watson 28612.8 Tips and Tricks for Information Retrieval 28712.9 Research on Rare Disease Throughout the World 28812.10 Conclusion 290References 29013 ATYPICAL POINT OF VIEW OF SEMANTIC COMPUTING IN HEALTHCARE 293L. Mayuri and K. M. Mehata13.1 Introduction 29413.2 Mind the Language 29513.2.1 Why Words Matter 29613.2.2 What Words Matter 29613.2.3 How Words Matter 29713.3 Semantic Analytics and Cognitive Computing: Recent Trends 29713.3.1 Semantic Data Analysis 29813.3.2 Semantic Data Integration 29913.3.3 Semantic Applications 30013.4 Semantics-Powered Healthcare SOS Engineering 30213.5 Conclusion 303References 30414 USING ARTIFICIAL INTELLIGENCE TO HELP COVID-19 PATIENTS 309Ayush Hans14.1 Introduction 31014.2 Method 31314.3 Results 31414.4 Discussion 31514.4.1 What is the Use of AI in Healthcare? 31514.4.2 How to Use AI for Critical Care Units 31514.4.2.1 Input Stage 31514.4.2.2 Process Stage 31614.4.2.3 Output Stage 31714.5 Conclusion 320Acknowledgment 321References 321Index 325
Data Science
Data Science ist in vielen Organisationen angekommen und oft alltägliche Praxis. Dennoch stehen viele Verantwortliche vor der Herausforderung, sich erstmalig mit konkreten Fragestellungen zu beschäftigen oder laufende Projekte weiterzuentwickeln. Die Spannbreite der Methoden, Werkzeuge und Anwendungsmöglichkeiten ist sehr groß und entwickelt sich kontinuierlich weiter. Die Vielzahl an Publikationen zu Data Science ist spezialisiert und behandelt fokussiert Einzelaspekte.Das vorliegende Werk gibt den Leserinnen und Lesern eine umfassende Orientierung zum Status Quo aus der wissenschaftlichen Perspektive und zahlreiche vertiefende Darstellungen praxisrelevanter Aspekte. Die Inhalte bauen auf den wissenschaftlichen CAS-Zertifikatskursen zu Big Data und Data Science der Hochschule Niederrhein in Kooperation mit der Hochschule Bonn-Rhein-Sieg und der FH Dortmund auf. Sie berücksichtigen wissenschaftliche Grundlagen und Vertiefungen, aber auch konkrete Erfahrungen aus Data Science Projekten. Das Buch greift praxisrelevante Fragen auf wissenschaftlichem Niveau aus Sicht der Rollen eines „Data Strategist“, „Data Architect“ und „Data Analyst“ auf und bindet erprobte Praxiserfahrungen u. a. von Seminarteilnehmern mit ein. Das Buch gibt für Interessierte einen Einblick in die aktuell relevante Vielfalt der Aspekte zu Data Science bzw. Big Data und liefert Hinweise für die praxisnahe Umsetzung.PROF. DR. DETLEV FRICK ist Professor für BWL, insb. Wirtschaftsinformatik an der Hochschule Niederrhein,PROF. DR. ANDREAS GADATSCH ist Professor für BWL, insb. für Wirtschaftsinformatik an der Hochschule Bonn-Rhein-Sieg,PROFESSOR DR. JENS KAUFMANN ist Professor für Wirtschaftsinformatik, insb. Data Science an der Hochschule Niederrhein,DIPL.-KFF. (FH) BIRGIT LANKES ist Lehrkraft für besondere Aufgaben an der Hochschule Niederrhein,PROF. DR. CHRISTOPH QUIX ist Professor für Wirtschaftsinformatik und Data Science an der Hochschule Niederrhein,ANDREAS SCHMIDT, M.A. ist Wissenschaftlicher Mitarbeiter im Data Innovation Lab der Hochschule Bonn-Rhein-Sieg undPROF. DR. UWE SCHMITZ ist Professor für Wirtschaftsinformatik an der FH Dortmund.Data Strategist: Digitalisierung von Geschäftsmodellen – Big Data Technologien erfolgreich implementieren - Data Architect: Informationsarchitekturen gestalten – Daten effizient verwalten - Data Analyst: Auswerten, Präsentieren, Entscheiden – Systematische Datenanalyse im Unternehmen - Anwendungsorientierte Data Science
Practical Event-Driven Microservices Architecture
In the simplest terms, event-driven architectures are like onions; they are manageable as a single layer (like a monolith) but when you get into them, they begin to cascade apart and you quickly realize that there are many complex layers (distributed microservices architecture). And that’s when the tears begin.This prescriptive guide takes you through the steps of moving a platform with millions of users from a monolith to a microservices event-driven architecture. You will learn about the challenges and complexities that arise in high-throughput environments that often contain upwards of hundreds of microservices. This book is designed to be your single best resource for learning how to apply event-driven architectures in real-world scenarios and offers hundreds of patterns to overcome the common and not so common challenges.While event-driven architectures have been the standard for decoupled, pluggable, evolutionary architectures for years, they have only recently been adopted by enterprises for the purpose of distributed microservices and there is little information about adopting them. Using them at scale can save valuable resources, but requires different considerations, including the added complexity of supporting several moving parts and getting the event schema right from the start in order to avoid large restructuring later on.Author Hugo Rocha understands that these kinds of challenges, as well as many others, need to be considered from the beginning, and helps teach you the mindset needed to create a deliberate strategy upfront. This book offers learning approaches and patterns to get you up to speed in order to sustainably build and manage event-driven architectures.WHAT YOU WILL LEARN* Understand the real-world challenges of event-driven architectures and the patterns to deal with those challenges and the trade-offs of each solution* Leverage the advantages of event-driven architectures to build scalable solutions and address legacy applications* Plan successful future implementations to avoid common pitfalls and apply proven patterns to deal with challenges in a real-world platform with millions of users* Decide whether event-driven solutions are the right choice for the requirements at hand* Discuss and understand advanced concepts about event-driven architecturesWHO IS THIS BOOK FORSoftware engineers and software architects. Anyone currently working with microservice architectures, primarily event-driven microservices, will greatly benefit from this book. Readers working with monoliths will benefit, as the book explores migration from a monolithic application to an event-driven microservice architecture.HUGO ROCHA has nearly a decade of experience working with highly distributed event-driven microservices architectures. He currently is an engineering lead for the leading global ecommerce platform for luxury products (Farfetch), providing services to millions of active users, backed by an event-driven architecture with hundreds of microservices processing hundreds of changes per second. Before that, he worked for several reference telecommunications companies that transitioned from monolithic applications to microservice-oriented architectures. Hugo has managed several teams that directly face the caveats of event-driven architectures every day. He designed solutions for critical pieces of the platform’s highly distributed backoffice platform, handling hundreds of changes per second, concurrently, scalably, and with high performance.CHAPTER 1. EMBRACING EVENT-DRIVEN ARCHITECTURES1.1. The truth about monoliths1.1.1. Anatomy of a typical monolith1.1.2. It's not all bad1.1.3. When monoliths become the business constrictor knot1.1.4. Using event-driven architectures to move away from a monolith1.2. What are microservices and how do they relate to event-driven1.3. SOA, microservice, and event-driven architectures1.4. The promise of event-driven microservices1.5. When should you use event-driven microservices?1.6. Overview of the challenges in event-driven architectures1.7. SummaryCHAPTER 2. MOVING FROM A MONOLITH TO AN EVENT-DRIVEN ARCHITECTURE2.1. Is migrating to an event-driven architecture your best option?2.2. How to decide where to start2.3. Using an event-driven approach to migrate data2.4. Using change data capture (CDC)2.4.1. Event-driven and change data capture (CDC), a real-world example2.5. Event-driven as a source of truth for both systems2.6. Managing dependencies between the two systems2.6.1. Dependency from new event-driven services to the monolith2.6.2. Dependency from the monolith to new event-driven services2.7. Gradually moving traffic2.8. Two-way synchronization and living with two sources of truth2.9. SummaryCHAPTER 3. DEFINING AN EVENT-DRIVEN MICROSERVICE AND ITS BOUNDARIES3.1. Building event-driven microservices3.1.1. Durable vs. ephemeral message brokers and GDPR3.1.2. Message types3.1.3. When to use documents over events3.1.4. Common event-driven messaging patterns3.1.5. Event-driven service topologies3.1.6. Common event-driven pitfalls and anti-patterns3.2. Organizing event-driven microservice boundaries3.3. Brief and practical introduction to domain-driven design and bounded contexts3.4. The impact of aggregate size and common pitfalls3.5. Request-driven vs. event-driven services3.6. Adding functionality to an existing microservice vs. creating a new one3.7. SummaryCHAPTER 4. EVENT-DRIVEN STRUCTURAL PATTERNS AND HIGH-LEVEL PROCESSES4.1. The challenges of transactional consistency in distributed systems4.1.1. Why abandon a monolithic database in the first place?4.1.2. The limitations of distributed transactions4.1.3. Managing multi-step processes with Sagas4.2. Event-driven orchestration pattern4.3. Event-driven choreography pattern4.4. Orchestration, choreography, or both?4.5. Data retrieval in event-driven architectures and associated patterns4.5.1. CQS, CQRS and when to use them4.5.2. The different flavors of CQRS4.5.3. When and how to use event sourcing4.5.4. Using command sourcing and its applicability4.6. Building multiple read models4.7. The pitfall of microservice spaghetti architectures and how to avoid it4.8. SummaryCHAPTER 5. HOW TO MANAGE EVENTUAL CONSISTENCY5.1. The impacts of eventual consistency and the need for alignment with the business5.2. Using event schema to leverage eventual consistency5.3. Applying domain boundaries to leverage eventual consistency5.4. Event versioning to manage delays5.5. Saving state to avoid eventual consistency5.6. End-to-end argument: a real-world use case5.7. For most use cases, it's not eventual if nobody notices5.7.1. Autoscaling use case with Prometheus and Kafka5.8. Tradeoffs of each solution5.9. SummaryCHAPTER 6. DEALING WITH EVENT-DRIVEN CONCURRENCY AND OUT OF ORDER MESSAGES6.1. Why is concurrency different in a monolith from an event-driven architecture?6.2. Pessimistic vs. optimistic concurrency, when and when not to use6.2.1. Pessimistic vs. optimistic approaches6.2.2. Solving concurrency by implementation and by architecture6.3. Using optimistic concurrency6.4. Using pessimistic concurrency6.4.1. Distributed locks6.4.2. Database transactions6.5. Dealing with out-of-order events6.5.1. How can events lose their order?6.5.2. Solving out of order events with versioning6.6. Using end-to-end message partitioning to handle concurrency and guarantee message ordering6.6.1. The relevance of message routing and partitioning6.6.2. Real-world example of message routing using Kafka6.6.3. Using end-to-end partitioning6.6.4. Limitations of end-to-end partitioning6.7. SummaryCHAPTER 7. ACHIEVING RESILIENCE AND EVENT PROCESSING RELIABILITY IN EVENT-DRIVEN MICROSERVICES7.1. Common failures in microservice architectures and how they relate to event-driven architectures7.1.1. Cascading failures and event-driven services7.1.2. Load balancing and rate limiters in event-driven services7.2. Understanding message delivery semantics7.3. Avoiding inconsistencies when saving state and publishing events7.3.1. Event stream as the only source of truth7.3.2. Outbox pattern7.3.3. Transactions and compensating actions7.4. Applying ACID 2.0 as a resilience strategy7.5. Avoiding message leak7.6. Applying common resilience patterns7.6.1. Retries7.6.2. Circuit breakers7.7. Recovering data and repairing state7.8. Bulkhead pattern7.9. SummaryCHAPTER 8. CHOOSING THE CORRECT EVENT SCHEMA DESIGN8.1. Event storming8.2. Event headers and envelopes8.2.1. Headers vs envelopes8.2.2. Relevant event contextual information8.3. Town crier events8.4. Bee events8.5. The event schema goldilocks principle8.6. Denormalized event schema8.7. Schema evolution8.7.1. Event stream versioning8.7.2. Using a downscaler/upscaler8.8. SummaryCHAPTER 9. HOW TO LEVERAGE THE USER INTERFACE9.1. Using an aggregating layer9.2. Backends for frontends9.3. UI Decomposition9.3.1. Application decomposition9.3.2. Page decomposition9.3.3. Section decomposition9.4. The limitations of API composition9.5. Task-based UIs9.6. Event-driven APIs9.7. SummaryCHAPTER 10. OVERCOMING THE CHALLENGES IN QUALITY ASSURANCE10.1. The only happens in production syndrome10.2. Component tests vs integration tests10.3. The correct mix of component validation and production validations10.4. Monitoring and alarmistic from the ground up10.5. SummaryCHAPTER 11. ORGANIZATIONAL COST OF EVENT-DRIVEN MICROSERVICES11.1. The epic journey to be onboarded11.2. When implementation overhead impacts time to market11.3. Dependencies management11.4. Summary
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