Computer und IT
Data Science and Analytics for SMEs
Master the tricks and techniques of business analytics consulting, specifically applicable to small-to-medium businesses (SMEs). Written to help you hone your business analytics skills, this book applies data science techniques to help solve problems and improve upon many aspects of a business' operations.SMEs are looking for ways to use data science and analytics, and this need is becoming increasingly pressing with the ongoing digital revolution. The topics covered in the books will help to provide the knowledge leverage needed for implementing data science in small business. The demand of small business for data analytics are in conjunction with the growing number of freelance data science consulting opportunities; hence this book will provide insight on how to navigate this new terrain.This book uses a do-it-yourself approach to analytics and introduces tools that are easily available online and are non-programming based. Data science will allow SMEs to understand their customer loyalty, market segmentation, sales and revenue increase etc. more clearly. Data Science and Analytics for SMEs is particularly focused on small businesses and explores the analytics and data that can help them succeed further in their business.WHAT YOU'LL LEARN* Create and measure the success of their analytics project* Start your business analytics consulting career* Use solutions taught in the book in practical uses cases and problems WHO THIS BOOK IS FORBusiness analytics enthusiasts who are not particularly programming inclined, small business owners and data science consultants, data science and business students, and SME (small-to-medium enterprise) analystsAfolabi Ibukun is a Data Scientist and is currently a Senior Lecturer in the Department of Computer and Information Sciences, Covenant University. She holds a B.Sc in Engineering Physics, an M.Sc and Ph.D in Computer Science. Afolabi Ibukun has over 15 years working experience in Computer Science research, teaching and mentoring. Her specific areas of interest are Data & Text Mining, Programming and Business Analytics. She has supervised several undergraduate and postgraduate students and published several articles in international journals and conferences. Afolabi Ibukun is also a Data Science Nigeria Mentor and currently runs a Business Analytics Consulting and Training firm named I&F Networks SolutionsINTRODUCTIONWe introduce data science generally and narrow it down to data science for business which is also referred to as business analytics. We then give a detailed explanation of the process involved in business analytics in form of the business analytics journey. In this journey, we explain what it takes from start to finish to carry out an analytics project in the business world, focusing on small business consulting, even though the process is generic to all types of business, small or large. We also give a description of what small business refers to in this book and the peculiarities of navigating an analytics project in such a terrain. To conclude the chapter, we talk about the types of analytics problems that is common to small business and the tools available to solve these problems given the budget situation of small businesses when it comes to analytics project.· DATA SCIENCE· DATA SCIENCE FOR BUSINESS· BUSINESS ANALYTICS JOURNEY· SMALL AND MEDIUM BUSINESS (SME)· BUSINESS ANALYTICS IN SMALL BUSINESS· TYPES OF ANALYTICS PROBLEMS IN SME· ANALYTICS TOOLS FOR SMES· ROAD MAPS TO THIS BOOK· PROBLEMS· REFERENCESCHAPTER 1: DATA FOR ANALYSIS IN SMALL BUSINESSIn this chapter, we would look at the various sources of data generally and in small business. This chapter is important because the major challenge of consulting for small business is the lack of data or quality data for analysis. This chapter will therefore detail the sources of data for analysis explaining first the type or form that data exists and some general ideas of how to collect such data. It gives an overview on data quality and integrity issues and touches on data literacy. The chapter also includes the typical data preparation procedures for the common types of techniques used in small business analytics and by extension used in this book. To conclude the chapter, we look at data visualization, particularly towards preparing data for various analytics task as explained in section 1.3.· SOURCE OF DATA· DATA QUALITY & INTEGRITY· DATA GOVERNANCE· DATA PREPARATION· DATA VISUALIZATION· PROBLEMS· REFERENCESCHAPTER 2: BUSINESS ANALYTICS CONSULTINGIn this chapter, we will look at business analytics consulting, particularly what the concept implies and how to build such a career path. We will explain the types of business analytics consulting that exist and then narrow it down to how to navigate the world of business analytics consulting for small business. In this chapter, we will look at how to manage a typical analytics project and measure the success of analytics projects. In conclusion, we will discuss issues revolving around how to bill analytics project particularly as a consultant.· BUSINESS ANALYTICS CONSULTING· MANAGING ANALYTICS PROJECT· SUCCESS METRICS IN ANALYTICS PROJECT· BILLING ANALYTICS PROJECT· PROBLEMS· REFERENCESCHAPTER 3: BUSINESS ANALYTICS CONSULTING PHASESIn this chapter we will look at the stages involved business analytics consulting, particularly when the analytics service is offered as a product from either within or outside the business. We will look at the proposal and initial analysis stage which gives direction to the analytics project. Then we look at the details involved in the pre-engagement, engagement and post engagement phase. It is important to know that the stages are presented in a typical or generic way but when implemented, there might be reason to modify or customize them for the application scenario.· PROPOSAL & INITIAL ANALYSIS· PRE- ENGAGEMENT PHASE· ENGAGEMENT PHASE· POST ENGAGEMENT PHASE· PROBLEMS· REFERENCESCHAPTER 4: DESCRIPTIVE ANALYTICS TOOLSThis chapter is focused on the mostly common descriptive analytics tools used in business generally and specifically in small businesses. The chapter will help to use descriptive analytics tools to understand your business and make recommendations that can improve your business profits. For small business, descriptive analytics helps SMEs to make sense of available data in order to monitor business indicators at a glance, helps SME owners to observe sales trends and patterns on an overall basis, as well as deep-dive into product categories and customer groups. It also helps SME’s to plan product strategy, pricing policies that will maximize their projected revenues and derive a lot of valuable insights for getting more customers.· INTRODUCTION· BAR CHART· HISTOGRAM· LINE GRAPHS· SCATTER PLOTS· PACKED BUBBLES CHARTS· HEAT MAPS· GEOGRAPHICAL MAPS· A PRACTICAL BUSINESS PROBLEM I· PROBLEMS· REFERENCESCHAPTER 5: PREDICTION TECHNIQUESIn this chapter, we will explore the popular techniques used for prediction, particularly in retails business. The approach used in explaining these techniques us to use them in solving a business problem. The second business problem to be addressed is the sales prediction problem which is common in retail business. The chapter first explain the fundamental concept of prediction techniques, next we look at how such techniques are evaluated. After this, we describe the business problem we intend solving. We then pick each of the selected techniques one by one and explain the algorithms involved and how they can be used to solve the problem described. The prediction techniques used and compared are the Multiple linear regression, the Regression Trees and the Neural Network. To conclude the chapter, we compare the results of the three algorithms and conclude on the problem in question. In this chapter therefore, the analytics products being offered is to solve sales prediction problem for small retail business.· INTRODUCTION· PRACTICAL BUSINESS PROBLEM II (SALES PREDICTION)· MULTIPLE LINEAR REGRESSION· REGRESSIN TREES· NEURAL NETWORK (PREDICTION)· CONCLUSION ON SALES PREDICTION· PROBLEMS· REFERENCESCHAPTER 6: CLASSIFICATION TECHNIQUESIn this chapter, even though there are several classification techniques, we will explore the popular ones used for classification in the business domain. In doing this, we will use the third business problem centered on customer loyalty comparing neural network, classification tree and random forest algorithms. In solving this problem, we are particular about how to get and retain more customers for our small business. We will also introduce some other classification based techniques such as K-nearest neighbour logistic regression and persuasion modelling. We will use persuasion modelling for the fourth practical business problem. In using these techniques to solve the problem we explain the fundamental concepts in the chosen algorithms and use them to demonstrate how this problems solving process can be adopted in real business scenarios.· CLASSIFICATION MODELS & EVALUATION· PRACTICAL BUSINESS PROBLEM III (CUSTOMER LOYALTY)· NEURAL NETWORK· CLASSIFICATION TREE· RANDOM FOREST & BOOSTED TREES· K NEAREST NEIGHBOUR· LOGISTIC REGRESSION· PROBLEMS· REFERENCESCHAPTER 7: ADVANCED DESCRIPTIVE ANALYTICSThis chapter is focused mainly on advanced descriptive analytics techniques. In this chapter, we will first explain the concept of clustering which is a type of unsupervised learning approach. We will then pick one clustering technique which is the K means clustering. Using the fourth practical business problem, we will explain how we can use the K means clustering technique to solve a real business problem. Next will explain the association rule example and finally Network analysis. We conclude with the fifth business problem which is focused on using network analytics for employee efficiency.· CLUSTERING· K MEANS· PRACTICAL BUSINESS PROBLEM IV (Customer Segmentation)· ASSOCIATION ANALYSIS· NETWORK ANALYSIS· PRACTICAL BUSINESS PROBLEM V (Staff Efficiency)· PROBLEMS· REFERENCESCHAPTER 8: CASE STUDY PART IThis chapter is the beginning part of major consulting case study for this book. We will explain what transpired during a typical business analytics consulting and help to create a road map or an example of how to navigate a business analytics consulting project. We start with a description of the SME Ecommerce environment generally, since this is the business environment of our selected case study, we then talk about the sources of data for analytics peculiar this environment. Next we describe the business to be used as case study briefly, followed by the analytics road map peculiar to consulting for this business. This chapter ends with the results of the initial analysis and pre engagement phase which forms the bases for the detailed analytics and implementation phase in chapter 10.· SME ECORMERCE· INTRODUCTION TO SME CASE STUDY· INITIAL ANALYSIS· ANALYTICS APPROACH· PRE –ENGAGEMENT· PROBLEMS· REFERENCESCHAPTER 9: CASE STUDY PART IIIn this chapter, we will conclude the case study used for illustration of a typical business analytics consulting for an SME by presenting the details of the engagement phase for the case study in question. The post engagement phase is left out as the implementation of the recommendations is determined by the systems and procedures of the business. It is important to note that the consulting steps can be customized for any small business based on the intended problem. The whole steps described in chapter 9 and 10 have been made simple for understanding, though in real life business application there might be need to iterate the process until satisfactory results have been gotten. This is because you constantly need to incorporate feedback from the stakeholders and domain experts.· GOAL 1: INCREASE WEBSITE TRAFFIC· GOAL 2: INCREASE WEBSITE SALES REVENUE· PROBLEMS· REFERENCES
3D-Konstruktionen mit Autodesk Inventor 2023
* 3D-MODELLIEREN VON DER SKIZZE ÜBER BAUTEILE UND BAUGRUPPEN BIS ZUR WERKZEICHNUNG UND ANIMATION* PRAXISNAHE ERLÄUTERUNG GRUNDLEGENDER BEFEHLE MIT VIELEN VERSCHIEDENEN KONSTRUKTIONSBEISPIELEN ZUM NACHBAUEN* ZWEI BONUS-KAPITEL MIT ZUSÄTZLICHEN THEMEN SOWIE ALLE BEISPIELPROJEKTE ALS DOWNLOADDieses Grundlagen- und Lehrbuch zeigt Ihnen anhand vieler einzelner Konstruktionsbeispiele die Möglichkeiten von Inventor 2023 und richtet sich insbesondere an Inventor-Neulinge, die Wert auf einen gründlichen praxisnahen Einstieg legen.Mit der Inventor-Testversion von der Autodesk-Webseite können Sie zügig eigene dreidimensionale Konstruktionen erstellen. Die wichtigsten Vorgehensweisen werden mit vielen einzelnen Beispielen erklärt. Für jedes Kapitel finden Sie Testfragen mit Lösungen im Anhang.Alle Befehle werden umfangreich vorgestellt und können daher leicht für eigene Projekte eingesetzt werden.ZAHLREICHE BEFEHLE WERDEN DETAILLIERT ERLÄUTERT, Z.B.:* 2D-Skizzen mit Linie, Bogen, Kreis, Rechteck, Langloch, Polygon* Abhängigkeiten und Bemaßungen in der Skizze* Volumenkörper aus Skizzen mit Extrusion, Rotation, Sweeping und Lofting* Spezielle Modellierung mit Spirale, Prägen, Ableiten, Rippe und Aufkleben* Befehle mit neuen Eigenschaften-Dialogen* Import für AutoCAD-2D-Zeichnungen mit assoziativer Zuordnung* 3D-Modellierung mit Grundkörpern wie Quader, Zylinder, Kugel und Torus* Volumenkörper durch Features ergänzen: Bohrung, Fase, Rundung, Gewinde, Wandstärke, Flächenverjüngung etc.* Baugruppen durch Platzieren der Bauteile mit geometrischen Abhängigkeiten* Zeichnungsableitung mit Ansichten, Bemaßungen und Beschriftungen* Erstellen von Stücklisten und Positionsnummern* Gestaltung verschiedener Modellzustände innerhalb eines Bauteils oder einer Baugruppe* Animierte Präsentationen, fotorealistische Bilder mit verschiedenen StilenAUS DEM INHALT:* Installation und Benutzeroberfläche* Skizzenerstellung in 2D und 3D* 3D-Modellierung* Abhängigkeiten und Bemaßungen* AutoCAD-2D-Import* 3D-Modellierung* iFeatures, iMates, iParts, iAssemblies* Baugruppenerstellung und Gestaltung von Modellzuständen* Zeichnungs-Ableitung* Bemaßungen und Stile* PräsentationenDetlef Ridder hat bereits zahlreiche Bücher zu AutoCAD, Inventor, Revit und ArchiCAD veröffentlicht und gibt Schulungen zu diesen Programmen und im Bereich CNC.
Einführung in Domain-Driven Design
Hands-On DDD: von der Strategie bis zum technischen DesignSoftwareentwicklung ist heutzutage anspruchsvoller denn je: Als Entwicklerin oder Entwickler müssen Sie technologische Trends im Blick behalten, aber genauso die Fachdomänen hinter der Software verstehen. Dieses Praxisbuch beschreibt zentrale Patterns, Prinzipien und Praktiken, mit denen Sie Geschäftsbereiche analysieren, die Business-Strategie verstehen und, was am wichtigsten ist, Ihr Softwaredesign besser an den Geschäftsanforderungen ausrichten.DDD-Experte Vlad Khononov zeigt, wie diese Praktiken helfen, von der Geschäftslogik ausgehend zu einem robusten Softwaredesign und einer zukunftsfähigen Softwarearchitektur zu kommen. Er beschreibt, wie DDD mit anderen Methoden kombiniert werden kann, um geeignete Architekturentscheidungen zu treffen. Das reale Beispiel eines Start-ups, das DDD einführt, bietet dabei viele praxisnahe Einblicke.In diesem Buch erfahren Sie, wie Sie:die Fachdomäne analysieren, um herauszufinden, welche Anforderungen an Ihr Systemdie strategischen und taktischen Werkzeuge von DDD nutzen, um effektive Softwarelösungen zu entwickeln, die diesen Geschäftsanforderungen entsprechenein gemeinsames Verständnis der Fachdomänen entwickelnein System in Bounded Contexts aufgliederndie Arbeit mehrerer Teams koordinierenDDD schrittweise in Brownfield-Projekten einführenAutor:Vlad (Vladik) Khononov ist Softwareentwickler mit über 20 Jahren Branchenerfahrung, in denen er für große und kleine Firmen gearbeitet hat – in unterschiedlichsten Rollen vom Webmaster bis zum Chefarchitekten. Vlad ist zudem als Sprecher, Blogger und Autor unterwegs. Er ist überall auf der Welt aktiv, um zu beraten und über Domain-Driven Design, Microservices und Softwarearchitektur ganz allgemein zu sprechen. Vlad hilft Firmen dabei, aus ihren Fachdomänen Sinn zu ziehen, Legacy-Systeme zu entwirren und komplexe Architekturaufgaben anzugehen. Er lebt im Norden Israels zusammen mit seiner Frau und einer fast vernünftigen Anzahl an Katzen.Zielgruppe:Softwareentwickler*innenSoftwarearchitekt*innenProjektleitung(IT-)Manager*innenLeseprobe (PDF-Link)
Troubleshooting Microsoft Teams
Learn and understand Microsoft Teams functionality, potential issues, and the tools available to troubleshoot Teams. This book provides a complete overview of Teams Phone system (PSTN) connectivity, call routing and quality troubleshooting, and best practices to support a Teams environment.The book begins with an introduction to Microsoft Teams and it provides a troubleshooting terminology. You will understand how to identify and develop a systematic approach for troubleshooting Teams. You will learn Teams Phone (voice) management and how to handle issues related to: Direct Routing connectivity, call routing, emergency calling, and much more. The book covers issues related to Teams client-side and external access along with Teams call quality troubleshooting. You will gain knowledge of real-world issues and use Teams troubleshooting tools such as the: Connectivity Analyzer, call diagnostic tool, SBC Syslog, Call Quality Dashboard, and quality analytics tool. You will go through the: Call Quality Dashboard with custom queries, PowerBI connector tool for the Teams Call Quality Dashboard, Teams Phone system Direct Routing Health Dashboard for call quality troubleshooting, and learn how to design PowerBI-based Teams reports.After reading this book, you will be able to quickly diagnose Teams connectivity and quality problems, and discover the root cause of any Teams issue. This book also is a practical guide you can use to prepare for the certification exam on troubleshooting Microsoft Teams (Exam MS-740).WHAT YOU WILL LEARN* Understand Microsoft Teams service components and their functionality* Understand unique approaches and techniques to identify an issue, capture the diagnostic log, and analyze the log* Detect poor audio/video calls and troubleshoot underlying problems* Troubleshoot and administer Teams Phone system connectivity and call routing issues* Use the Call Quality Dashboard, and Analytics, for call quality troubleshooting* Understand and design a custom call report based on PowerBI report templates* Prepare for the certification exam on troubleshooting Microsoft Teams (Exam MS-740)WHO THIS BOOK IS FORMicrosoft Teams administrators, support engineers, helpdesk engineers, telecom admins, and network engineersBALU N. ILAG is currently working as Unified Communication and Collaboration Engineer. His role combines product support and customization, implementation, and strategic guidance for enterprise customers. He is fascinated with artificial intelligence (AI) and machine learning (ML) technology. Balu is a Microsoft Certified Trainer (MCT), former Microsoft MVP (2013-2019), and Microsoft Certified Solution Expert (MCSE) for communication. He regularly writes blog posts and articles on Microsoft products.ARUN M. SABALE is a Microsoft Certified Azure architect and Microsoft Certified Modern Desktop Expert. He has written several blog posts on Azure services and automation, PowerShell, ARM, and Terraform. Arun has more than 12 years of experience in PowerShell automation and other Microsoft services such as AD, DNS, DHCP, and VMM, and more than six years of experience in Azure infra design/deployment/automation, PowerShell, ARM, Terraform, and Azure DevOps. His current role is a combination of Azure design and development and automation.CHAPTER 1: INTRODUCTION (TROUBLESHOOTING)CHAPTER GOAL: TROUBLESHOOTING INTRODUCTIONNO OF PAGES 20-30SUB -TOPICS1. Introduction2. What is Microsoft Teams?3. Why are Teams so popular?4. Understand troubleshoot approaches5. Discuss a systematic approach to troubleshooting6. SummaryCHAPTER 2: MICROSOFT TEAMS OVERVIEWCHAPTER GOAL: WHATS NEW IN MICROSOFT TEAMS AND MANAGEMENTNO OF PAGES: 30-40Sub - Topics1. Introduction2. Microsoft Teams Service architecture3. Teams, Team, Channel, file, and Tab4. Microsoft Teams different client5. Teams Phone system6. Teams live Event7. Introduction of Microsoft Teams admin center8. SummaryCHAPTER 3: IDENTIFY AND DEVELOP SYSTEMIC APPROACH FOR TEAMS TROUBLESHOOTINGChapter Goal:NO OF PAGES : 30 -35SUB - TOPICS:1. Introduction2. Understand Microsoft Teams administration3. Teams diagnostic logs and collecting process4. Diagnose common Teams problem5. Use a troubleshooting methodology using6. Create and implement a plan of action7. SummaryCHAPTER 4: TROUBLESHOOT TEAMS IDENTITY AND SIGN-IN ISSUESChapter Goal:NO OF PAGES: 30-40SUB - TOPICS:1. Introduction2. Understand and review Teams network configuration3. Evaluate and design conditional access policies4. Understand Teams Identity and troubleshoot Teams account issues5. Capture and Analyze Teams sign-in logs6. Troubleshoot issues with Teams apps (first and 3rd party)7. Troubleshoot problems with public and private channels8. Troubleshoot file issues for private and public channels9. SummaryCHAPTER 5: TROUBLESHOOT MICROSOFT TEAMS CALL QUALITY ISSUE.CHAPTER GOAL:1. Introduction2. Understand and troubleshoot Teams signaling and media flow.3. Learn and troubleshoot Teams One-to-One and multi-party call flow problem4. Troubleshoot Teams meeting creation and recording issues5. Examine Teams content sharing and attendee access problems6. Effectively manage and troubleshoot Teams live events issues7. Troubleshoot Teams messaging and reporting problems8. Troubleshoot file sharing in person-to-person private chat9. SummaryCHAPTER 6: TROUBLESHOOT MICROSOFT TEAMS PHONE SYSTEM (CALLING PLAN & DIRECT ROUTING) ISSUECHAPTER GOAL:NO OF PAGES: 30-40SUB - TOPICS:1. Introduction2. Understand Microsoft Teams phone systema. Teams calling planb. Teams Direct Routing3. Troubleshoot Teams Direct routing (connectivity) issue4. Troubleshoot emergency calling issues.5. Troubleshoot Teams Call (PSTN) routing issues.6. Configure and troubleshoot audio conferencing7. Troubleshoot dial-plan, voice routing, and emergency call routing policies8. Troubleshoot phone system issues9. SummaryCHAPTER 7: TROUBLESHOOTING TEAMS CLIENT-SIDE AND EXTERNAL ACCESS ISSUESCHAPTER GOAL:NO OF PAGES: 20-30SUB - TOPICS:1. Introduction2. Deploy and update Teams client software3. Troubleshoot Teams client startup and configuration4. Troubleshoot audio and video devices5. Troubleshoot Teams desktop client performance issues6. Understand Teams external and Troubleshoot external (federation) access issues7. Enable and Troubleshoot Teams Guest access issues8. Troubleshoot issues interoperating with Skype for Business9. SummaryCHAPTER 8: APPLY BEST PRACTICES AND TEAMS OPTIMAL MANAGEMENT USING POWERSHELLCHAPTER GOAL:NO OF PAGES: 30-40SUB - TOPICS:· Introduction· Best practices for Implementation QoS· Best practices for Implementing VPN split tunnel· Lesson learning for applying Location-Based Routing (LBR)· Implementations inbound and outbound normalization rules· Frequently used PowerShell command and script· SummaryCHAPTER 9: TEAMS REAL-WORLD ISSUE USING TROUBLESHOOTING TOOLSCHAPTER GOAL:No of pages: 20-30SUB - TOPICS:1. Introduction2. Identify and Review Teams troubleshooting toolsa. Connectivity analyzerb. Call diagnostic tool3. Understand and use Teams call quality analytics toola. Troubleshoot single user call quality issues4. Use the Call Quality Dashboard to investigate audio and video issues.a. Investigate organization call quality issues5. Log parsing tool6. Diagnose and resolve Teams real-world issues7. SummaryCHAPTER 10: POWERBI BASED TEAMS CALL QUALITY DASHBOARD FOR CALL QUALITY TROUBLESHOOTING CHAPTER GOAL:NO OF PAGES: 30-40SUB - TOPICS:1. Introduction2. PowerBI and Microsoft Teams3. Design PowerBI based Teams Reports4. Design Teams Call Quality dashboard to identify poor audio and video call5. Use Call quality dashboard for call quality troubleshooting6. Summary7. Knowledge check
The IoT Product Manager
Enhance your product management skills and set yourself apart from other product managers working in the IoT industry. This book shows you how to navigate through the world of small and Edge devices to successfully launch and monitor products connected together to make smart environments.Working in Agile environments, you'll learn to guide UI builds that serve customer needs and function the way top tech companies expect. Then measure the right product metrics and create reporting dashboards for your IoT products. That way you can effectively engage partners, engineers, and stakeholders. And you’ll learn the entire end-to-end development process of IoT products so that you can make sure you make the right moves at the right stages.After mastering the IoT product lifecycle and measuring your success against KPIs, you’ll see how to work with marketing to effectively launch your product in the marketplace. Finally, a self-interview section has been provided so that you can evaluate your skills and responses to common IoT Product Manager questions. Then take what you've learned and go out into the world to develop integrated IoT products that your customers love!WHAT YOU'LL LEARN* Create UI/UX experiences that engage and wow your customers* Work in Agile environments with best business practices* Negotiate effectively at each step of the product lifecycleWHO THIS BOOK IS FORAny wanting to build a IoT products. Aspiring Internet of Things product managers, product owners, analysts, business consultants, engineers, and business owners. DR. PADMARAJ NIDAGUNDI obtained his Bachelor’s degree in Information Science and Engineering from Visvesvaraya Technological University in 2010 and a Master’s degree in Computer Engineering in 2014. With more than a decade of experience in the field, he currently works as a researcher with Riga Technical University. He’s found success in software development and testing, where he gained significant international accolades. His research interests include software development, quantum computing, cybersecurity, and artificial intelligence, as well as, Internet of Things. Chapter 1. History of IoT Product ManagementGrowth of IoT technologyScope of product managementHow to become a PMChapter 2. UI / UX for IoT Product DesignUser experience and user interface creationSteps for productBusiness modelsHardware and recent IoT landscapeChapter 3. IoT Manager in the Agile EraProduct Manager journeyAdvance skillsCreating product metricsCreating reporting dashboards,Communication with partners, engineersm and stakeholdersEnd-to-end development.Chapter 4. IoT Product Development and Life CycleProduct evaluationJourney of the productChapter 5. IoT Product Manager and Life Cycle ManagementCollaborateNegotiateLaunchChapter 6. IoT Product MarketingMarketing strategy creationMonitor industry trendsReview generation methodsChapter 7. Government Regulation in IoTExisting laws (US, EU, Canada)How to follow regulationsAudience: Intermediate
Hands- On Liferay DXP
Explore the development and customization of OSGi modules in Liferay DXP and choosing the right underlying technology for it.The book starts with the basic Liferay Architecture to understand how things work in Liferay DXP, as well as in OSGi. Next, you’ll understand Blade CLI, Liferay workspace and how you can develop portlet modules in different module templates. Once you are familiar with portlet modules, you’ll explore some advance concepts such as Inter Portlet Communications (IPC), message bus etc.Moving on, you’ll understand about building service layer using service builder and exposing web services. Later chapters will cover how to customize the default behavior of Liferay, Liferay services, and user interface using Hooks. Additionally, this book will cover topics like Gogo shell, xxpando attributes, basic integration with the Liferay search framework etc.By the end of this book, you should be able to develop portlet modules in Liferay DXP and customize the default Liferay behavior.WHAT YOU'LL LEARN* Review OSGI Concepts* Use Liferay workspace and Blade CLI* Develop Liferay Portlet modules* Build services and web services using service builder* Study customizations of Liferay default behavior and user interfaceWHO THIS BOOK IS FORDevelopers who wish to learn Liferay DXP development approach to improve their productivity. It is best suited for those who possess basic Java knowledge and are familiar with Liferay User Interface.APOORVA PRAKASH is a Liferay certified professional who is working on Liferay for over a decade. Currently, he is working with Schneider Electric Pvt Ltd., India; as Liferay Expert. Apoorva has defined architecture of different kind of portals, such as large Employee Portals, e-commerce sites, etc. in Liferay for over 12 years and counting. His other work area includes AWS and Kubernetes. Development and deployment are his passions and he is inherently very keen on attention to detail. He is an avid blogger and his blog has been mentioned in the Liferay community round-up several times. Apoorva has completed his master’s degree in computer application from Apeejay Institute of Technology, Greater Noida, Uttar Pradesh, and his other hobbies are tech blogging and wildlife photography.SHAIK INTHIYAZ BASHA is a Liferay Architect and Technical Specialist at Schneider Electric Pvt Ltd., India. He is an expert in Content Management Systems (CMS) and Amazon Web Service (AWS). Inthiyaz currently holds the position of Platform Architect in a group involved in developing Liferay and Elastic Search Applications. His accomplishments in enhancing and creating various Liferay components are evident from his various successful implementations. His experience and knowledge are supported by certificate such as Liferay Backend Developer (DXP), Inthiyaz is also founder of the etuslearnliferay, which contains a lot of information on Liferay and the CMS world. Since 2011, he has created various kinds of CMS applications, supporting large banking and financial systems. His main area of interest is web applications. Inthiyaz uses Java, AWS and Elastic Search on a daily basis, but he is open to learning other technologies and solutions. He holds a master's degree in Computer Networks from Quba College of Eng & Tech , Affiliated by JNTUA University, Andhra Pradesh, India.Chapter 1: OSGi BasicsChapter Goal: This chapter will focus on explaining the core concept of OSGi, benefits and how it is being used in Liferay.Subtopics:1. Understanding OSGi2. Introduction Bundles, Component and Services, Lifecycle3. Liferay's OSGi Architecture4. OSGi BenefitsChapter 2: Liferay Development BasicsChapter Goal: This chapter will focus on initial development setup and underlying concept of Blade CLI, build tools, database connectivity and Liferay Modules creation.Subtopics:1. Liferay Workspace2. Blade CLI3. Build Tools4. Database connectivity5. Introduction to Liferay Modules6. Introduction to Gogo shellChapter 3: Portlet Module DevelopmentChapter Goal: This chapter will focus on basics and creation of portlet modules.Subtopics:1. Introduction to Portlet modules, Portlet specifications2. Java Standard Portlets3. Liferay Portlet Modules – LiferayMVC Portlets4. Introduction to Other Portlet Modules5. Gogo shell in actionChapter 4: Advance Liferay ConceptsChapter Goal: This chapter will focus on advance concepts, such as message bus and Inter Portlet Communication (IPC).Subtopics:1. Inter Portlet Communication2. Liferay Message Bus3. Using service in Freemarker TemplatesChapter 5: Service Builder ConceptsChapter Goal: This chapter will focus on database connectivity and service builder and web services.Subtopics:1. Introduction to Service builder2. Creation of services3. Local services4. Exposing and consuming web servicesChapter 6: CustomizationChapter Goal This chapter will focus on customization of default Liferay behaviorSubtopics:1. Customizing User Interface with widget templates2. Customizing MVC Action Commands3. Customizing Services using wrappers4. Customizing Models using ModelListners5. Expando Attributes6. Post and Pre-Actions7. Customization of Search
Outlook 2021
Nein, Kaffee kochen wird Ihnen Outlook vorläufig nicht. Aber Post sortieren, kennzeichnen, wiederfinden, vielleicht gleich wegwerfen oder zur Wiedervorlage dann präsentieren, wenn Sie das möchten. Außerdem kann es Termine organisieren, Anfahrtsbeschreibungen und Personenfotos zu Kontaktadressen liefern und vieles mehr. Mit Outlook 2021 haben Sie einen Exchange-Server im Hintergrund, der sich auch in Ihrer Abwesenheit um Ihre Angelegenheiten kümmert. Hier bekommen Sie verschiedene Vorschläge, wie Outlook Ihre Wünsche genau so ausführen wird, wie Sie sich das wünschen.Ina Koys ist langjährige Trainerin für MS-Office-Produkte. Viele Fragen werden in den Kursen immer wieder gestellt, aber selten in Fachbüchern behandelt. Einige davon beantwortet sie jetzt in der Reihe "kurz & knackig".
Practical Haskell
Get a practical, hands-on introduction to the Haskell language, its libraries and environment, and to the functional programming paradigm that is fast growing in importance in the software industry. This updated edition includes more modern treatment of Haskell's web framework and APIs.This book contains excellent coverage of the Haskell ecosystem and supporting tools, including Cabal and Stack for managing projects, HUnit and QuickCheck for software testing, WAI and Elm to develop the back end and front end of web applications, Persistent and Esqueleto for database access, and parallel and distributed programming libraries.You’ll see how functional programming is gathering momentum, allowing you to express yourself in a more concise way, reducing boilerplate, and increasing the safety of your code. Haskell is an elegant and noise-free pure functional language with a long history, having a huge number of library contributors and an active community.This makes Haskell the best tool for both learning and applying functional programming, and Practical Haskell, Third Edition takes advantage of this to show off the language and what it can do. Free source code available on the Apress GitHub page for this book.WHAT YOU WILL LEARN* Get started programming with Haskell* Examine the different parts of the language* Gain an overview of the most important libraries and tools in the Haskell ecosystem* Apply functional patterns in real-world scenarios* Understand monads and monad transformers* Proficiently use laziness and resource managementWHO THIS BOOK IS FORExperienced programmers who may be new to the Haskell programming language. However, some prior exposure to Haskell is recommended.ALEJANDRO SERRANO MENA has more than a decade of experience as a developer, trainer, and researcher in functional programming, with an emphasis on Haskell and related languages. He holds a Ph.D. from Utrecht University on the topic of error message customization in compilers. He's an active member of the community, maintaining a few open-source projects, writing books about Haskell, and collaborating on podcasts and conferences.PART I: FIRST STEPS1. Going Functional2. Declaring the Data Model3. Increasing Code Reuse4. Using Containers and Type Classes5. Laziness and Infinite StructuresPART II: DATA MINING6. Knowing Your Clients Using Monads7. More Monads: Now for Recommendations8. Working in Several CoresPART III: RESOURCE HANDLING9. Dealing with Files: IO and Conduit10. Building and Parsing Text11. Safe Database Access12. Web ApplicationsPART IV: DOMAIN SPECIFIC LANGUAGES13. Strong Types14. Interpreting Offers with AttributesPART V: ENGINEERING THE STORE15. Documenting, Testing, and Verifying16. Architecting Your Application17. Looking Further
Practical Ansible
Get ready to go from the basics of using Ansible to becoming proficient at implementing configuration management in your projects. This book begins with the basics of Ansible, providing you with details on how to install and configure your environment while working with different Ansible modules from the command line. Next, it introduces you to working with Ansible tasks and organizing configuration code into playbooks.You’ll then learn how to extend playbooks further, using roles and templates within the configuration code. Author Vincent Sesto then extends your knowledge further by covering custom Ansible modules using Python and Linux shell scripts and demonstrating how you can start to keep your secret values encrypted and secure using Ansible Vault. You’ll also develop Ansible roles with the use of Ansible Galaxy to reuse existing roles that others have created.This updated edition reflects changes added in the latest version of Ansible (2.9). It also includes an expanded chapter on testing Ansible using Molecule and managing large server environments using applications like Ansible Tower.WHAT WILL YOU LEARN* Understand what Ansible is and how to install and run your first basic command line commands* Expand your configuration management using Ansible playbooks, roles and templates* Customize your code further using Ansible Vault and third-party roles in Ansible Galaxy.* Work with Ansible in managing cloud infrastructure, specifically in Amazon Web Services* Troubleshoot your Ansible code and use frameworks like Molecule and Testinfra to help test your code changes* Manage large server environments using real-world examples and extend your configurations using an application like Ansible TowerWHO THIS BOOK IS FORSystems Engineers, Developers, DevOps Engineers and Software Administrators.VINCENT SESTO is a DevOps engineer, endurance athlete and author.As a DevOps engineer Vince specializes in Linux, Amazon Web Services, and open source applications. He is particularly interested in developing his skills in DevOps, continuous integration, security, log aggregation (management, UI, and reporting), and Python development. In his spare time, you’ll find him running or cycling for long periods of time, making the most of his time outdoors.Chapter 1: Configuration Management With AnsibleCHAPTER GOAL: INTRODUCE CONFIGURATION MANAGEMENT AND AUTOMATION, INTRODUCE ANSIBLENO OF PAGES: 20 - 25SUB -TOPICS* Introduce Ansible to readers and installation onto your system.* Start with the basic configurations of Ansible and basic command line options.* Introduce working with Ansible on the command line, and demonstrate the basics of Ansible Playbooks.* Introduce common Ansible Modules used in day to day configuration management.* Introduce the projects we are going to work with during this book. A LAMP Stack for the first part of the book and a Splunk Server towards the end of the book when deploying to AWS.Chapter 2: Ansible PlaybooksCHAPTER GOAL: EXPAND KNOWLEDGE OF ANSIBLE WITH AN IN DEPTH LOOK AT ANSIBLE PLAYBOOKSNO OF PAGES: 20 - 25SUB - TOPICS* Start with a brief discussion on YAML Syntax and how it relates to Ansible Playbooks.Demonstrate how we can join numerous modules together to create a larger project Ansible Playbooks. * Expand Playbook functionality with import, include, loops and variables.Start creating the Ansible Playbook for our first project of the book, the LAMP Stack.Chapter 3: Expanding Playbooks With Roles and TemplatesCHAPTER GOAL: EXPAND THE LAMP STACK PROJECT FURTHER EXPANDING THE READERS KNOWLEDGE ON THE USE OF ANSIBLE PLAYBOOKSNO OF PAGES: 20 - 25SUB - TOPICS:* Introduce Ansible Roles and create roles for the LAMP Stack including Web Server, Database and Django Server.* Provide a discussion on how to use command line options and variables with Ansible Playbooks.3. Configuring Playbooks using conditional tasks and tags to limit what changes are made by the Ansible Playbook.Chapter 4: Custom Ansible Modules, Vaults And Galaxay’sCHAPTER GOAL: PROVIDE AN INTRODUCTION TO USING ANSIBLE VAULT TO MANAGE THEIR SYSTEM SECRETS, AS WELL AS EXPLORING ANSIBLE GALAXY TO HELP THEM FAST TRACK THEIR PROJECT DEPLOYMENTS.NO OF PAGES: 20 - 25SUB - TOPICS:* Provide the reader with a demonstration on how to use Ansible Vault to help manage secrets within your Ansible Projects. * Provide an introduction to Ansible Galaxy getting the reader familiar with searching and using third party roles in Ansible Galaxy.* Demonstrate to the reader how they can start to create their own roles in Ansible Galaxy.Demonstrate to the user how with some basic Python skills, they can create their own Ansible Modules if they need to.Chapter 5: Working with Ansible In The CloudCHAPTER GOAL: THE GOAL OF THIS CHAPTER IS TO PROVIDE A BRIEF INTRODUCTION TO AMAZON WEB SERVICES AND GET THE READER TO IMPLEMENT ANSIBLE PLAYBOOKS THAT DEPLOY TO AWS.NO OF PAGES: 20 - 25SUB - TOPICS:* Introduce Amazon Web Services to the reader and provide a brief discussion on what it is and how you can create your own AWS account.* Discuss how to allow Ansible and your playbooks to interact with AWS and deploy services to the cloud.Introduce the reader to the modules you will be using to create your new services on AWS. * Create our new project playbook for our second project to deploy a Splunk Server to AWS.Chapter 6: AWS Templates and CloudFormation ScriptsCHAPTER GOAL: EXPAND THE READERS KNOWLEDGE FURTHER ON DEPLOYING TO THEIR PROJECTS TO AWS USING TEMPLATES, WORKING WITH ANSIBLE PULL AND USING GITHUB REPOSITORY DEPLOYMENTS.NO OF PAGES: 20 - 25SUB - TOPICS:* Working with Ansible templates in AWS Instances.Using Ansible Pull and GitHub repository deployments. * Provide a demonstration on how to build AWS Images in your projects to improve the speed of your deployments.* Combining CloudFormation and Ansible in our projects.Chapter 7: Ansible Troubleshooting And VariablesCHAPTER GOAL: FURTHER OUR WORK WITH SOME FINER POINTS ON HOW WE CAN REDUCE POTENTIAL ISSUES FROM ARISING IN OUR PLAYBOOKS AND ENSURE THINGS RUN AS SMOOTHLY AS POSSIBLE.NO OF PAGES: 20 - 25SUB - TOPICS:Start with a brief discussion on why modules in AWS work differently than modules in dedicated hardware. * Provide details on how to use the Debug Module in your Playbooks to provide clarity on your running playbooks.* Working with Ansible Facts.Using functions like Ansible Lint to help troubleshoot and ensure you are limiting the chance of your playbooks failing. * Provide a discussion on migrating from one configuration management system like Chef or Puppet to Ansible and how you might want to approach this.Provide details on how you can interact and connect to servers when SSH is not available.Chapter 8: Testing Ansible Playbooks With MoleculeCHAPTER GOAL: THIS CHAPTER WILL INTRODUCE SETTING UP A TEST FRAMEWORK FOR ANSIBLE PLAYBOOKS AND ROLES, AS WELL AS TESTING THE END STATE INFRASTRUCTURE OF WHAT OUR ANSIBLE ROLES ARE TRYING TO ACHIEVE.NO OF PAGES: 20 - 25SUB - TOPICS:1. Introduce Molecule as a way of testing your Ansible code.2. Provide the basic commands on how to set up your roles and playbooks using Molecule and how to begin testing.3. Discuss how you can set up a workflow to automatically test your code and infrastructure when changes are made.Chapter 9: Managing Larger Server EnvironmentsCHAPTER GOAL: INTRODUCE ANSIBLE TOWER TO THE READER AND DISCUSS HOW YOU CAN USE THE APPLICATION AS PART OF MANAGING LAGER SERVER ENVIRONMENTS. DUE TO LICENSING OF ANSIBLE THE CHAPTER WILL DEMONSTRATE HOW TO USE THE OPEN SOURCE VERSION CALLED AWX.NO OF PAGES: 20 - 25SUB - TOPICS:* Discuss how to set up your hosts files for larger server environments.* Introduce Ansible Tower to the reader and show some of the basic usage.* Show how to install Ansible Tower on your system.* Introduce basic usage of Tower and how to start implementing your configuration management using the application.
(ISC)2 CCSP Certified Cloud Security Professional Official Practice Tests
Efficient, effective review for the CCSP® exam (ISC)2®CCSP® Certified Cloud Security Professional Official Practice Tests, Third Edition is the ideal companion to (ISC)2 CCSP Certified Cloud Security Professional Official Study Guide, 3rd Edition. It is your hands-on guide that boosts your confidence and gives you the opportunity to test your level of preparedness for the Certified Cloud Security Professional (CCSP) exam. As the only Practice Questions book reviewed and endorsed by (ISC)2 it provides you with more than 800 practice questions (complete with answers and explanations) covering all the CCSP exam domains with all questions new or updated for the 2022 exam objectives. Organized in a logical sequence by domain, the tests help you review only the areas you need to reconsider without spending time on the topics you clearly understand! Coverage of 100% of all exam objectives in these practice tests means you'll be ready for: Cloud Concepts, Architecture and DesignCloud Data SecurityCloud Platform and Infrastructure SecurityCloud Application SecurityCloud Security OperationsLegal, Risk and Compliance Interactive learning environment Take your exam prep to the next level with Sybex’s superior interactive online study tools. To access our learning environment, simply visit www.wiley.com/ go/sybextestprep, register your book to receive your unique PIN, and instantly gain one year of FREE access after activation to: Interactive test bank Use the interactive online version of the book’s domain by domain questions and 2 practice exams to help you identify areas where further review is needed. Get more than 90% of the answers correct, and you’re ready to take the certification exam. Over 800 questions total! ABOUT THE CCSP CERTIFICATION The CCSP is the premier cloud security certification from (ISC)2. This vendor-neutral certification validates IT and information security professionals’ knowledge and competency to apply best practices to cloud security architecture, design, operations and service orchestration. It shows you’re on the forefront of cloud security. (ISC)2 is a global nonprofit organization that maintains the Common Body of Knowledge for information security professionals. Candidates must have experience, adhere to the (ISC)2 Code of Ethics and maintain continuing education requirements or recertify every three years. Visit www.isc2.org to learn more. ABOUT THE AUTHORS The only official CCSP practice test product endorsed by (ISC)2 With over 850 practice questions all new for the 2022-2025 exam objectives, (ISC)2 CCSP Certified Cloud Security Professional Official Practice Tests, 3rd Edition gives you the opportunity to test your level of understanding and gauge your readiness for the Certified Cloud Security Professional (CCSP) exam long before the big day. These questions cover 100% of the CCSP exam domains and include answers with full explanations to help you understand the reasoning and approach for each. Logical organization by domain allows you to practice only the areas you need to bring you up to par, without wasting precious time on topics you’ve already mastered. As the only official practice test product for the CCSP exam endorsed by (ISC)2, this essential resource is your best bet for gaining a thorough understanding of the topic. It also illustrates the relative importance of each domain, helping you plan your remaining study time so you can go into the exam fully confident in your knowledge. When you’re ready, two practice exams allow you to simulate the exam day experience and apply your own test-taking strategies with domains given in proportion to the real thing. The online learning environment and practice exams are the perfect way to prepare and make your progress easy to track. For this new Third Edition, cloud security experts Mike Chapple and David Seidl have delivered an all-new question set for the new CCSP 2022-2025 objectives. These authors are well known for their best-selling (ISC)2 CISSP Certified Information Systems Security Professional Official Practice Tests and now they’ve joined forces again to deliver the same high caliber practice questions for the CCSP exam. Mike Chapple, PhD, CISSP, CCSP, is a bestselling author and Teaching Professor of Information Technology, Analytics, and Operations at Notre Dame's Mendoza College of Business. He is also the Academic Director of the University’s Master of Science in Business Analytics program and holds multiple technical certifications, including the SSCP, CIPP/US, CySA+, CISM, PenTest+, and Security+. David Seidl, CISSP, is Vice President for Information Technology and Chief Information Officer at Miami University. He holds multiple technical certifications including GPEN, GCIH, Pentest+ and CySA+ and has written books on security certification and cyberwarfare. Introduction xv Chapter 1 Domain 1: Cloud Concepts, Architecture, and Design 1 Chapter 2 Domain 2: Architecture and Design 23 Chapter 3 Domain 3: Cloud Platform and Infrastructure Security 45 Chapter 4 Domain 4: Cloud Application Security 65 Chapter 5 Domain 5: Cloud Security Operations 85 Chapter 6 Domain 6: Legal, Risk, and Compliance 105 Chapter 7 Practice Test 1 125 Chapter 8 Practice Test 2 151 Appendix Answers to Review Questions 175 Chapter 1: Domain 1: Cloud Concepts, Architecture, and Design 176 Chapter 2: Domain 2: Architecture and Design 188 Chapter 3: Domain 3: Cloud Platform and Infrastructure Security 198 Chapter 4: Domain 4: Cloud Application Security 213 Chapter 5: Domain 5: Cloud Security Operations 223 Chapter 6: Domain 6: Legal, Risk, and Compliance 232 Chapter 7: Practice Test 1 245 Chapter 8: Practice Test 2 259 Index 273
Deep Learning for Targeted Treatments
DEEP LEARNING FOR TREATMENTSTHE BOOK PROVIDES THE DIRECTION FOR FUTURE RESEARCH IN DEEP LEARNING IN TERMS OF ITS ROLE IN TARGETED TREATMENT, BIOLOGICAL SYSTEMS, SITE-SPECIFIC DRUG DELIVERY, RISK ASSESSMENT IN THERAPY, ETC.Deep Learning for Targeted Treatments describes the importance of the deep learning framework for patient care, disease imaging/detection, and health management. Since deep learning can and does play a major role in a patient’s healthcare management by controlling drug delivery to targeted tissues or organs, the main focus of the book is to leverage the various prospects of the DL framework for targeted therapy of various diseases. In terms of its industrial significance, this general-purpose automatic learning procedure is being widely implemented in pharmaceutical healthcare. AUDIENCEThe book will be immensely interesting and useful to researchers and those working in the areas of clinical research, disease management, pharmaceuticals, R&D formulation, deep learning analytics, remote healthcare management, healthcare analytics, and deep learning in the healthcare industry. RISHABHA MALVIYA, PHD, is an associate professor in the Department of Pharmacy, School of Medical and Allied Sciences, Galgotias University. His areas of interest include formulation optimization, nanoformulation, targeted drug delivery, localized drug delivery, and characterization of natural polymers as pharmaceutical excipients. He has authored more than 150 research/review papers for national/international journals of repute. He has been granted more than 10 patents from different countries while a further 40 patents are published/under evaluation. GHEORGHITA GHINEA, PHD, is a professor in Computing, Department of Computer Science Brunel University London. His research activities lie at the confluence of computer science, media, and psychology, and particularly interested in building semantically underpinned human-centered e-systems, particularly integrating human perceptual requirements. Has published more than 30+ articles and received 10+ research grants. RAJESH KUMAR DHANARAJ, PHD, is an associate professor in the School of Computing Science and Engineering at Galgotias University, Greater Noida, India. He has contributed 20+ books on various technologies and 35+ articles and papers in various refereed journals and international conferences and contributed chapters to the books. His research interests include machine learning, cyber-physical systems, and wireless sensor networks. He is an Expert Advisory Panel Member of Texas Instruments Inc USA. BALAMURUGAN BALUSAMY, PHD, is a professor at Galgotias University. He has published 30+ books on various technologies as well as more than 150 journal articles, conferences, and book chapters. SONALI SUNDRAM completed B. Pharm & M. Pharm (pharmacology) from AKTU, Lucknow, and is working at Galgotias University, Greater Noida. Her areas of interest are neurodegeneration, clinical research, and artificial intelligence. She has more than 8 patents to her credit. Preface xviiAcknowledgement xix1 DEEP LEARNING AND SITE-SPECIFIC DRUG DELIVERY: THE FUTURE AND INTELLIGENT DECISION SUPPORT FOR PHARMACEUTICAL MANUFACTURING SCIENCE 1Dhanalekshmi Unnikrishnan Meenakshi, Selvasudha Nandakumar, Arul Prakash Francis, Pushpa Sweety, Shivkanya Fuloria, Neeraj Kumar Fuloria, Vetriselvan Subramaniyan and Shah Alam Khan1.1 Introduction 21.2 Drug Discovery, Screening and Repurposing 51.3 DL and Pharmaceutical Formulation Strategy 111.3.1 DL in Dose and Formulation Prediction 111.3.2 DL in Dissolution and Release Studies 151.3.3 DL in the Manufacturing Process 161.4 Deep Learning Models for Nanoparticle-Based Drug Delivery 191.4.1 Nanoparticles With High Drug Delivery Capacities Using Perturbation Theory 201.4.2 Artificial Intelligence and Drug Delivery Algorithms 211.4.3 Nanoinformatics 221.5 Model Prediction for Site-Specific Drug Delivery 231.5.1 Prediction of Mode and a Site-Specific Action 231.5.2 Precision Medicine 261.6 Future Scope and Challenges 271.7 Conclusion 29References 302 ROLE OF DEEP LEARNING, BLOCKCHAIN AND INTERNET OF THINGS IN PATIENT CARE 39Akanksha Sharma, Rishabha Malviya and Sonali Sundram2.1 Introduction 402.2 IoT and WBAN in Healthcare Systems 422.2.1 IoT in Healthcare 422.2.2 WBAN 442.2.2.1 Key Features of Medical Networks in the Wireless Body Area 442.2.2.2 Data Transmission & Storage Health 452.2.2.3 Privacy and Security Concerns in Big Data 452.3 Blockchain Technology in Healthcare 462.3.1 Importance of Blockchain 462.3.2 Role of Blockchain in Healthcare 472.3.3 Benefits of Blockchain in Healthcare Applications 482.3.4 Elements of Blockchain 492.3.5 Situation Awareness and Healthcare Decision Support with Combined Machine Learning and Semantic Modeling 512.3.6 Mobile Health and Remote Monitoring 532.3.7 Different Mobile Health Application with Description of Usage in Area of Application 542.3.8 Patient-Centered Blockchain Mode 552.3.9 Electronic Medical Record 572.3.9.1 The Most Significant Barriers to Adoption Are 602.3.9.2 Concern Regarding Negative Unintended Consequences of Technology 602.4 Deep Learning in Healthcare 622.4.1 Deep Learning Models 632.4.1.1 Recurrent Neural Networks (RNN) 632.4.1.2 Convolutional Neural Networks (CNN) 642.4.1.3 Deep Belief Network (DBN) 652.4.1.4 Contrasts Between Models 662.4.1.5 Use of Deep Learning in Healthcare 662.5 Conclusion 702.6 Acknowledgments 70References 703 DEEP LEARNING ON SITE-SPECIFIC DRUG DELIVERY SYSTEM 77Prem Shankar Mishra, Rakhi Mishra and Rupa Mazumder3.1 Introduction 783.2 Deep Learning 813.2.1 Types of Algorithms Used in Deep Learning 813.2.1.1 Convolutional Neural Networks (CNNs) 823.2.1.2 Long Short-Term Memory Networks (LSTMs) 833.2.1.3 Recurrent Neural Networks 833.2.1.4 Generative Adversarial Networks (GANs) 843.2.1.5 Radial Basis Function Networks 843.2.1.6 Multilayer Perceptron 853.2.1.7 Self-Organizing Maps 853.2.1.8 Deep Belief Networks 853.3 Machine Learning and Deep Learning Comparison 863.4 Applications of Deep Learning in Drug Delivery System 873.5 Conclusion 90References 904 DEEP LEARNING ADVANCEMENTS IN TARGET DELIVERY 101Sudhanshu Mishra, Palak Gupta, Smriti Ojha, Vijay Sharma, Vicky Anthony and Disha Sharma4.1 Introduction: Deep Learning and Targeted Drug Delivery 1024.2 Different Models/Approaches of Deep Learning and Targeting Drug 1044.3 QSAR Model 1054.3.1 Model of Deep Long-Term Short-Term Memory 1054.3.2 RNN Model 1074.3.3 CNN Model 1084.4 Deep Learning Process Applications in Pharmaceutical 1094.5 Techniques for Predicting Pharmacotherapy 1094.6 Approach to Diagnosis 1104.7 Application 1134.7.1 Deep Learning in Drug Discovery 1144.7.2 Medical Imaging and Deep Learning Process 1154.7.3 Deep Learning in Diagnostic and Screening 1164.7.4 Clinical Trials Using Deep Learning Models 1164.7.5 Learning for Personalized Medicine 1174.8 Conclusion 121Acknowledgment 122References 1225 DEEP LEARNING AND PRECISION MEDICINE: LESSONS TO LEARN FOR THE PREEMINENT TREATMENT FOR MALIGNANT TUMORS 127Selvasudha Nandakumar, Shah Alam Khan, Poovi Ganesan, Pushpa Sweety, Arul Prakash Francis, Mahendran Sekar, Rukkumani Rajagopalan and Dhanalekshmi Unnikrishnan Meenakshi5.1 Introduction 1285.2 Role of DL in Gene Identification, Unique Genomic Analysis, and Precise Cancer Diagnosis 1325.2.1 Gene Identification and Genome Data 1335.2.2 Image Diagnosis 1355.2.3 Radiomics, Radiogenomics, and Digital Biopsy 1375.2.4 Medical Image Analysis in Mammography 1385.2.5 Magnetic Resonance Imaging 1395.2.6 CT Imaging 1405.3 dl in Next-Generation Sequencing, Biomarkers, and Clinical Validation 1415.3.1 Next-Generation Sequencing 1415.3.2 Biomarkers and Clinical Validation 1425.4 dl and Translational Oncology 1445.4.1 Prediction 1445.4.2 Segmentation 1465.4.3 Knowledge Graphs and Cancer Drug Repurposing 1475.4.4 Automated Treatment Planning 1495.4.5 Clinical Benefits 1505.5 DL in Clinical Trials—A Necessary Paradigm Shift 1525.6 Challenges and Limitations 1555.7 Conclusion 157References 1576 PERSONALIZED THERAPY USING DEEP LEARNING ADVANCES 171Nishant Gaur, Rashmi Dharwadkar and Jinsu Thomas6.1 Introduction 1726.2 Deep Learning 1746.2.1 Convolutional Neural Networks 1756.2.2 Autoencoders 1806.2.3 Deep Belief Network (DBN) 1826.2.4 Deep Reinforcement Learning 1846.2.5 Generative Adversarial Network 1866.2.6 Long Short-Term Memory Networks 188References 1917 TELE-HEALTH MONITORING USING ARTIFICIAL INTELLIGENCE DEEP LEARNING FRAMEWORK 199Swati Verma, Rishabha Malviya, Md Aftab Alam and Bhuneshwar Dutta Tripathi7.1 Introduction 2007.2 Artificial Intelligence 2007.2.1 Types of Artificial Intelligence 2017.2.1.1 Machine Intelligence 2017.2.1.2 Types of Machine Intelligence 2037.2.2 Applications of Artificial Intelligence 2047.2.2.1 Role in Healthcare Diagnostics 2057.2.2.2 AI in Telehealth 2057.2.2.3 Role in Structural Health Monitoring 2057.2.2.4 Role in Remote Medicare Management 2067.2.2.5 Predictive Analysis Using Big Data 2077.2.2.6 AI’s Role in Virtual Monitoring of Patients 2087.2.2.7 Functions of Devices 2087.2.2.8 Clinical Outcomes Through Remote Patient Monitoring 2107.2.2.9 Clinical Decision Support 2117.2.3 Utilization of Artificial Intelligence in Telemedicine 2117.2.3.1 Artificial Intelligence–Assisted Telemedicine 2127.2.3.2 Telehealth and New Care Models 2137.2.3.3 Strategy of Telecare Domain 2147.2.3.4 Role of AI-Assisted Telemedicine in Various Domains 2167.3 AI-Enabled Telehealth: Social and Ethical Considerations 2187.4 Conclusion 219References 2208 DEEP LEARNING FRAMEWORK FOR CANCER DIAGNOSIS AND TREATMENT 229Shiv Bahadur and Prashant Kumar8.1 Deep Learning: An Emerging Field for Cancer Management 2308.2 Deep Learning Framework in Diagnosis and Treatment of Cancer 2328.3 Applications of Deep Learning in Cancer Diagnosis 2338.3.1 Medical Imaging Through Artificial Intelligence 2348.3.2 Biomarkers Identification in the Diagnosis of Cancer Through Deep Learning 2348.3.3 Digital Pathology Through Deep Learning 2358.3.4 Application of Artificial Intelligence in Surgery 2368.3.5 Histopathological Images Using Deep Learning 2378.3.6 MRI and Ultrasound Images Through Deep Learning 2378.4 Clinical Applications of Deep Learning in the Management of Cancer 2388.5 Ethical Considerations in Deep Learning–Based Robotic Therapy 2398.6 Conclusion 240Acknowledgments 240References 2419 APPLICATIONS OF DEEP LEARNING IN RADIATION THERAPY 247Akanksha Sharma, Ashish Verma, Rishabha Malviya and Shalini Yadav9.1 Introduction 2489.2 History of Radiotherapy 2509.3 Principal of Radiotherapy 2519.4 Deep Learning 2519.5 Radiation Therapy Techniques 2549.5.1 External Beam Radiation Therapy 2579.5.2 Three-Dimensional Conformal Radiation Therapy (3D-CRT) 2599.5.3 Intensity Modulated Radiation Therapy (IMRT) 2609.5.4 Image-Guided Radiation Therapy (IGRT) 2619.5.5 Intraoperative Radiation Therapy (IORT) 2639.5.6 Brachytherapy 2659.5.7 Stereotactic Radiosurgery (SRS) 2689.6 Different Role of Deep Learning with Corresponding Role of Medical Physicist 2699.6.1 Deep Learning in Patient Assessment 2699.6.1.1 Radiotherapy Results Prediction 2699.6.1.2 Respiratory Signal Prediction 2719.6.2 Simulation Computed Tomography 2719.6.3 Targets and Organs-at-Risk Segmentation 2739.6.4 Treatment Planning 2749.6.4.1 Beam Angle Optimization 2749.6.4.2 Dose Prediction 2769.6.5 Other Role of Deep Learning in Corresponds with Medical Physicists 2779.7 Conclusion 280References 28110 APPLICATION OF DEEP LEARNING IN RADIATION THERAPY 289Shilpa Rawat, Shilpa Singh, Md. Aftab Alam and Rishabha Malviya10.1 Introduction 29010.2 Radiotherapy 29110.3 Principle of Deep Learning and Machine Learning 29310.3.1 Deep Neural Networks (DNN) 29410.3.2 Convolutional Neural Network 29510.4 Role of AI and Deep Learning in Radiation Therapy 29510.5 Platforms for Deep Learning and Tools for Radiotherapy 29710.6 Radiation Therapy Implementation in Deep Learning 30010.6.1 Deep Learning and Imaging Techniques 30110.6.2 Image Segmentation 30110.6.3 Lesion Segmentation 30210.6.4 Computer-Aided Diagnosis 30210.6.5 Computer-Aided Detection 30310.6.6 Quality Assurance 30410.6.7 Treatment Planning 30510.6.8 Treatment Delivery 30510.6.9 Response to Treatment 30610.7 Prediction of Outcomes 30710.7.1 Toxicity 30910.7.2 Survival and the Ability to Respond 31010.8 Deep Learning in Conjunction With Radiomoic 31210.9 Planning for Treatment 31410.9.1 Optimization of Beam Angle 31510.9.2 Prediction of Dose 31510.10 Deep Learning’s Challenges and Future Potential 31610.11 Conclusion 317References 31811 DEEP LEARNING FRAMEWORK FOR CANCER 333Pratishtha11.1 Introduction 33411.2 Brief History of Deep Learning 33511.3 Types of Deep Learning Methods 33611.4 Applications of Deep Learning 33911.4.1 Toxicity Detection for Different Chemical Structures 33911.4.2 Mitosis Detection 34011.4.3 Radiology or Medical Imaging 34111.4.4 Hallucination 34211.4.5 Next-Generation Sequencing (NGS) 34211.4.6 Drug Discovery 34311.4.7 Sequence or Video Generation 34311.4.8 Other Applications 34311.5 Cancer 34311.5.1 Factors 34411.5.1.1 Heredity 34511.5.1.2 Ionizing Radiation 34511.5.1.3 Chemical Substances 34511.5.1.4 Dietary Factors 34511.5.1.5 Estrogen 34611.5.1.6 Viruses 34611.5.1.7 Stress 34711.5.1.8 Age 34711.5.2 Signs and Symptoms of Cancer 34711.5.3 Types of Cancer Treatment Available 34811.5.3.1 Surgery 34811.5.3.2 Radiation Therapy 34811.5.3.3 Chemotherapy 34811.5.3.4 Immunotherapy 34811.5.3.5 Targeted Therapy 34911.5.3.6 Hormone Therapy 34911.5.3.7 Stem Cell Transplant 34911.5.3.8 Precision Medicine 34911.5.4 Types of Cancer 34911.5.4.1 Carcinoma 34911.5.4.2 Sarcoma 34911.5.4.3 Leukemia 35011.5.4.4 Lymphoma and Myeloma 35011.5.4.5 Central Nervous System (CNS) Cancers 35011.5.5 The Development of Cancer (Pathogenesis) Cancer 35011.6 Role of Deep Learning in Various Types of Cancer 35011.6.1 Skin Cancer 35111.6.1.1 Common Symptoms of Melanoma 35111.6.1.2 Types of Skin Cancer 35211.6.1.3 Prevention 35311.6.1.4 Treatment 35311.6.2 Deep Learning in Skin Cancer 35411.6.3 Pancreatic Cancer 35411.6.3.1 Symptoms of Pancreatic Cancer 35511.6.3.2 Causes or Risk Factors of Pancreatic Cancer 35511.6.3.3 Treatments of Pancreatic Cancer 35511.6.4 Deep Learning in Pancreatic Cancer 35511.6.5 Tobacco-Driven Lung Cancer 35711.6.5.1 Symptoms of Lung Cancer 35711.6.5.2 Causes or Risk Factors of Lung Cancer 35811.6.5.3 Treatments Available for Lung Cancer 35811.6.5.4 Deep Learning in Lung Cancer 35811.6.6 Breast Cancer 35911.6.6.1 Symptoms of Breast Cancer 36011.6.6.2 Causes or Risk Factors of Breast Cancer 36011.6.6.3 Treatments Available for Breast Cancer 36111.6.7 Deep Learning in Breast Cancer 36111.6.8 Prostate Cancer 36211.6.9 Deep Learning in Prostate Cancer 36211.7 Future Aspects of Deep Learning in Cancer 36311.8 Conclusion 363References 36312 CARDIOVASCULAR DISEASE PREDICTION USING DEEP NEURAL NETWORK FOR OLDER PEOPLE 369Nagarjuna Telagam, B.Venkata Kranti and Nikhil Chandra Devarasetti12.1 Introduction 37012.2 Proposed System Model 37512.2.1 Decision Tree Algorithm 37512.2.1.1 Confusion Matrix 37612.3 Random Forest Algorithm 38112.4 Variable Importance for Random Forests 38312.5 The Proposed Method Using a Deep Learning Model 38412.5.1 Prevention of Overfitting 38612.5.2 Batch Normalization 38612.5.3 Dropout Technique 38612.6 Results and Discussions 38612.6.1 Linear Regression 38612.6.2 Decision Tree Classifier 38812.6.3 Voting Classifier 38912.6.4 Bagging Classifier 38912.6.5 Naïve Bayes 39012.6.6 Logistic Regression 39012.6.7 Extra Trees Classifier 39112.6.8 K-Nearest Neighbor [KNN] Algorithm 39112.6.9 Adaboost Classifier 39212.6.10 Light Gradient Boost Classifier 39312.6.11 Gradient Boosting Classifier 39312.6.12 Stochastic Gradient Descent Algorithm 39312.6.13 Linear Support Vector Classifier 39412.6.14 Support Vector Machines 39412.6.15 Gaussian Process Classification 39512.6.16 Random Forest Classifier 39512.7 Evaluation Metrics 39612.8 Conclusion 401References 40213 MACHINE LEARNING: THE CAPABILITIES AND EFFICIENCY OF COMPUTERS IN LIFE SCIENCES 407Shalini Yadav, Saurav Yadav, Shobhit Prakash Srivastava, Saurabh Kumar Gupta and Sudhanshu Mishra13.1 Introduction 40813.2 Supervised Learning 41013.2.1 Workflow of Supervised Learning 41013.2.2 Decision Tree 41013.2.3 Support Vector Machine (SVM) 41113.2.4 Naive Bayes 41313.3 Deep Learning: A New Era of Machine Learning 41413.4 Deep Learning in Artificial Intelligence (AI) 41613.5 Using ML to Enhance Preventive and Treatment Insights 41713.6 Different Additional Emergent Machine Learning Uses 41813.6.1 Education 41813.6.2 Pharmaceuticals 41913.6.3 Manufacturing 41913.7 Machine Learning 41913.7.1 Neuroscience Research Advancements 42013.7.2 Finding Patterns in Astronomical Data 42013.8 Ethical and Social Issues Raised ! ! ! 42113.8.1 Reliability and Safety 42113.8.2 Transparency and Accountability 42113.8.3 Data Privacy and Security 42113.8.4 Malicious Use of AI 42213.8.5 Effects on Healthcare Professionals 42213.9 Future of Machine Learning in Healthcare 42213.9.1 A Better Patient Journey 42213.9.2 New Ways to Deliver Care 42413.10 Challenges and Hesitations 42413.10.1 Not Overlord Assistant Intelligent 42413.10.2 Issues with Unlabeled Data 42513.11 Concluding Thoughts 425Acknowledgments 426References 426Index 431
Rechnerarchitektur für Dummies
Dieses Buch bietet eine kompakte, verständliche Einführung in das Thema "Rechnerarchitektur". Alle heute essenziellen Themengebiete werden behandelt. Der Schwerpunkt des Buches liegt auf der systemtechnischen funktionalen Beschreibung von Rechnern, ihren Komponenten und Prozessen, ohne auf die unzähligen Details dedizierter Systeme einzugehen. Die funktionale Darstellung mittels geeigneter Modellierungstechniken erlaubt das grundsätzliche Verständnis dieser Systeme, unabhängig von der jeweiligen Art der Realisierung und dem aktuellen Stand der Technologie. So müssen Sie keine Sorge haben, dass Sie sich bei der Prüfungsvorbereitung in den Details verlieren. Jürgen Neuschwander ist Professor für Informatik mit dem Schwerpunkt "Technik der Informations- und Kommunikationssysteme". Er lehrt an der Hochschule für Technik, Wirtschaft und Gestaltung in Konstanz.Über den Autor 7EINLEITUNG19Über dieses Buch 20Törichte Annahmen über den Leser 21Was Sie nicht lesen müssen 22Wie dieses Buch aufgebaut ist 22Teil I: Grundlegendes zu Rechnerarchitekturen 22Teil II: Das Kernelement: Der Prozessor 22Teil III: Das Konzept der Speicherhierarchie 23Teil IV: Vom Nutzen der Parallelverarbeitung 23Teil V: Der Top-Ten-Teil 23Symbole, die in diesem Buch verwendet werden 23Wie es weitergeht 24TEIL I: GRUNDLEGENDES ZU RECHNERARCHITEKTUREN25KAPITEL 1 BLICK AUS DER VOGELPERSPEKTIVE27Das Zeitalter der Computer 27Embedded Systems und Ubiquitous Computing 28Klassen von Rechnern 30Der Begriff »Rechnerarchitektur« 33Die Instruction Set Architecture (ISA) 34Die Mikro-Architekturebene 38Die Definition der Rechnerarchitektur aus meiner Sicht 38Höchstintegration und die Grenzen des Wachstums 39Steigerung der Anzahl der Transistoren auf einem Chip 39Der Performance-Gap 42Alternativen zur Steigerung der Taktrate 44Fortschritte beim automatisierten Entwurf solcher Chips 45Modellierungstechnik 47Aufbaupläne (Instanzennetze) 48Ablaufpläne (Petri-Netze) 51KAPITEL 2 LEISTUNGSBEWERTUNG VON RECHNERN55Überblick über Leistungsmaße 56MIPS und MFLOPS 57Die Prozessorausführungszeit 58Vereinfachung durch den CPI-Wert 61Benchmarkprogramme 63Das Gesetz von Amdahl 67TEIL II: DAS KERNELEMENT: DER PROZESSOR71KAPITEL 3 DIE VON NEUMANN-MASCHINE73Die Komponenten eines von Neumann-Rechners 76Der Prozessor 76Die Ein-/Ausgabeeinheit 77Der Hauptspeicher 78Der Systembus 79Charakteristika der von Neumann-Maschine 80Interpretation der Informationskomponenten 80Befehlszählerprinzip und die Abwicklung eines Programms 84Prozesse und Strukturelemente in einem Rechner 87Komponenten des Operationswerks 94Speicherorganisation 104Klassen von Prozessorarchitekturen 118Das Steuerwerk 124KAPITEL 4 PROGRAMMIERMODELL UND ASSEMBLERPROGRAMMIERUNG139Charakteristische Merkmale der Hochsprachen-Programmierung 140Charakteristische Merkmale der maschinennahen Programmierung 140Das Programmiermodell 141Assemblerprogrammierung 143Der Befehlssatz des Prozessors 144Adressierungsarten 150Assemblerprogrammierung am Beispiel 158Ablauf der Assemblierung 166Unterprogrammtechnik 179KAPITEL 5 KOMMUNIKATION UND AUSNAHMEVERARBEITUNG193Datenaustausch über den Systembus 193Zeitverhalten am Systembus 194Synchroner Bus 194Semi-synchroner Systembus 197Asynchroner Systembus 198Bussysteme in der heutigen Praxis 202Bus-Arbitration 203Lokale Bus-Arbitration 203Globale Bus-Arbitration 206Priorisierung mehrerer Master 207Zentrales Verfahren zur Busvergabe 207Dezentrales Verfahren zur Busvergabe 208Erweiterung des Prozessormodells 209Ausnahmeverarbeitung 210Einführung des Abwicklerverwalters 211Klassifizierung von Unterbrechungen und Ausnahmeverarbeitungen 213Priorisierung in einer Interruptebene 222Modellierung des Hardware-Dispatchers 228Ein-/Ausgabe-Interfaces und Synchronisation 234Ein-/ Ausgabe-Interfaces 234Informationelle Struktur eines Interface-Bausteins 235Synchronisation mit peripheren Instanzen 236Synchronisation durch Busy-Waiting 238Synchronisation durch Programmunterbrechung 241Synchronisation durch Handshake-Betrieb 241Direkter Speicherzugriff DMA (Direct Memory Access) 243Der DMA-Controller 246Aufbau eines DMA-Controllers 247Das Kommunikations-Interface PCI-Express 251TEIL III: DAS KONZEPT DER SPEICHERHIERARCHIE253KAPITEL 6 SPEICHERSYSTEME IM RECHNER255Der optimale Rechner 255Die Speicherhierarchie 257Inhomogenität und Organisation der Speicherhierarchie 259Lokalitätseigenschaften von Programmen 262Prinzipieller Aufbau von Halbleiter-Speicherbausteinen 263Festwertspeicher 264Schreib-/Lesespeicher 265Speicherzugriffe mittels Blockbuszyklen 271Verschränkung von Speicherbänken (Interleaving) 272Modularer Speicheraufbau 275Organisation des Hauptspeichers 276Praktische Ausprägung des Hauptspeicherzugriffs 278Eine Lösung durch spezielle Chipsätze 280Weitere Bausteintypen für Schreib-/Lesespeicher 283Sekundärspeicher 285Festplatten 286Redundant Array of Inexpensive Disks (RAID) 288Solid State Disks (SSD) 290Unternehmensweite Speichersysteme (NAS und SAN) 290Archivspeicher 292Optische Plattenspeicher 292Magnetbandspeicher 293KAPITEL 7 CACHESPEICHER295Das Problem der Zykluszeit 296Die Idee des Cachings 296Systemstrukturen für Caches 299Look-aside-Cache 299Look-through-Cache 300Zugriff auf den Cachespeicher 301Lesezugriffe 301Schreibzugriffe 303Die Idee des Assoziativspeichers 306Verdrängungsstrategie und Alterungsinformation 308Arbeitsweise des Cachespeichers 309Trefferrate und Zugriffszeiten 309Cache-Kohärenzproblem 310Kohärenzproblem bei einem Cache-Hit 312Kohärenzproblem bei Copy-back-Verfahren 312Lösung des Kohärenzproblems 313Strukturen von Cachespeichern 315Der voll-assoziative Cachespeicher 316Direkt zuordnender Cache (Direct-mapped Cache) 319Mehrwege-Satz-assoziativer Cache (n-way Set-associative Cache) 322Das MESI-Protokoll 325Cachespeicher-Hierarchie 331KAPITEL 8 VIRTUELLE SPEICHERVERWALTUNG337Die Idee des virtuellen Speichers 337Das Problem der Speicherzuweisung 339Die Memory Management Unit (MMU) 343Zusammenfassung: Das Prinzip der virtuellen Speicherverwaltung 344Segmentverwaltung 346Das Seitenverfahren 356Die zweistufige Adressumsetzung 365Virtuelle und reale Cache-Adressierung 368Virtuelle Cache-Adressierung 368Reale Cache-Adressierung 370TEIL IV: VOM NUTZEN DER PARALLELVERARBEITUNG373KAPITEL 9 DIE IDEE DER PARALLELISIERUNG375Der Einfluss der Parallelisierung auf die Rechnerarchitektur 376Charakteristika für eine Parallelisierung auf Hardwareebene 377Mikroskopische oder makroskopische Parallelität 378Symmetrische oder asymmetrische Strukturen 379Feinkörnige oder grobkörnige Parallelität 380Implizite oder explizite Parallelität 381Typen paralleler Architekturen – die Taxonomie von Flynn 381Single Instruction Single Data (SISD) 383Single Instruction Multiple Data (SIMD) 383Multiple Instruction Single Data (MISD) 384Multiple Instruction Multiple Data (MIMD) 384Performance von Multiprozessorsystemen und von Multicore-Prozessoren 386Die Harvard-Architektur 389CISC-Rechner und deren Probleme 389Die Idee der RISC-Maschinen 390Die Architektur eines RISC-Prozessors 391Erweiterung der ALU um einen Bypass 395Zusammenfassung 397Synchronisation von Prozessen 398Sequenzielle und parallele Prozesse 398Gegenseitiger Ausschluss von Prozessen 400Binäre Semaphore zur Synchronisation 402Der Test-and-Set- Befehl für Semaphorvariablen 404KAPITEL 10 FLIEẞBANDVERARBEITUNG409Die DLX-Pipeline 412Leistungssteigerung durch Pipelining 415Hardwarestruktur einer k-stufigen Pipeline 419Pipeline-Hemmnisse 422Datenabhängigkeiten 423Lösung der Datenkonflikte 429Strukturkonflikte 433Lösungen von Strukturkonflikten 434Steuerflusskonflikte 435KAPITEL 11 PARALLELE PIPELINES UND SUPERSKALARITÄT 441Parallelisierung der Programmabwicklung 441Pipelines mit mehreren Ausführungseinheiten 442VLIW-Prozessoren 446Superskalare Prozessoren 449Prinzipielle Architektur einer superskalaren Pipeline 450Sprungzielvorhersage 457Statische Sprungzielvorhersage 459Dynamische Sprungzielvorhersage 459Superskalare Pipeline – eine Verbesserung 464Core-Architektur 466Leistungssteigerung durch Multithreading 468Prozesse 468Threads 469Vorteile des Multithreading 470Simultaneous Multithreading bei superskalaren Pipelines 474Nachteile der auf Performance optimierten Prozessor-Hardware 475KAPITEL 12 VOM PROZESSOR ZU RECHNERSYSTEMEN479Cluster 480Supercomputer 481Grid Computing 482Virtuelle Maschinen 484Cloud Computing 486Liefermodelle 487Dienstleistungsmodelle 488KAPITEL 13 DIE ZUKÜNFTIGE ENTWICKLUNG491Taktfrequenzen und Miniaturisierung 491Ein neuer Hoffnungsträger – Graphen 493Nanotubes als Speichertechnologie 493Optische Prozessoren 494Architektur und Mikroarchitektur 495Processing-in-Memory 496Neuromorphe Hardware 497Memristor 499Quantencomputer 500Qubits und Quantengatter 500Superposition und Quantenparallelismus 501Quantenverschränkung 503Einsatzgebiete für Quantencomputer 505Ein kurzes Resümee 506TEIL V: DER TOP-TEN-TEIL 507KAPITEL 14 ZEHN KERNTHEMEN ZUR RECHNERARCHITEKTUR509Höchstintegration für Rechnerchips 509Die von Neumann-Architektur 510Die Harvard-Architektur und die RISC-Maschinen 511Die Instruction Set Architecture (ISA) 511Die Speicherhierarchie 512Cachespeicher 513Virtueller Speicher 514Fließbandverarbeitung 514Superskalare Prozessoren 516Quantencomputer 516KAPITEL 15 MÖGLICHE TRUGSCHLÜSSE519Assemblerprogrammierung ist immer schneller 519Die übertragenen Daten pro Zeiteinheit 520Lange Pipelines ergeben eine bessere Performance 520Höhere Cache-Kapazität ergibt bessere Performance 521Von Neumann-Architektur als Auslaufmodell 522Multi-Prozessorsysteme sind stets performanter als Mono-Prozessorsysteme 522Amdahls Gesetz bei parallelen Rechnern 523Flash-Speicher statt Hauptspeicher 523Multicore-Prozessoren in der Taxonomie von Flynn 524Hoher Parallelitätsgrad bei Anwendungssoftware 524KAPITEL 16 ZEHN SELBSTTESTS ZUM FACHGEBIET527Selbsttest zu Kapitel 1 527Selbsttest zu Kapitel 2 und 3 528Selbsttest zu Kapitel 4 529Selbsttest zu Kapitel 4 und 5 529Selbsttest zu Kapitel 3 und 6 530Selbsttest zu Kapitel 9 und 10 531Selbsttest zu Kapitel 10 und 11 531Selbsttest zu Kapitel 7 und 11 532Selbsttest zu Kapitel 8 533Selbsttest zu Kapitel 13 533Lösungen zu den Selbsttests 534Wichtige Literatur 535Abbildungsverzeichnis 537Stichwortverzeichnis 545
Hybrid Intelligent Approaches for Smart Energy
HYBRID INTELLIGENT APPROACHES FOR SMART ENERGYGREEN TECHNOLOGIES AND CLEANER ENERGY ARE TWO OF THE MOST IMPORTANT TOPICS FACING OUR WORLD TODAY, AND THE MARCH TOWARD EFFICIENT ENERGY SYSTEMS, SMART CITIES, AND OTHER GREEN TECHNOLOGIES, HAS BEEN, AND CONTINUES TO BE, A LONG AND INTRICATE ONE. BOOKS LIKE THIS ONE KEEP THE VETERAN ENGINEER AND STUDENT, ALIKE, UP TO DATE ON CURRENT TRENDS IN THE TECHNOLOGY AND OFFER A REFERENCE FOR THE INDUSTRY FOR ITS PRACTICAL APPLICATIONS.Energy optimization and consumption prediction are necessary to prevent energy waste, schedule energy usage, and reduce the cost. Today, smart computing technologies are slowly replacing the traditional computational methods in energy optimization, consumption, scheduling, and usage. Smart computing is an important core technology in today’s scientific and engineering environment. Smart computation techniques such as artificial intelligence, machine learning, deep learning and Internet of Things (IoT) are the key role players in emerging technologies across different applications, industries, and other areas. These newer, smart computation techniques are incorporated with traditional computation and scheduling methods to reduce power usage in areas such as distributed environment, healthcare, smart cities, agriculture and various functional areas. The scope of this book is to bridge the gap between traditional power consumption methods and modern consumptions methods using smart computation methods. This book addresses the various limitations, issues and challenges of traditional energy consumption methods and provides solutions for various issues using modern smart computation technologies. These smart technologies play a significant role in power consumption, and they are cheaper compared to traditional technologies. The significant limitations of energy usage and optimizations are rectified using smart computations techniques, and the computation techniques are applied across a wide variety of industries and engineering areas. Valuable as reference for engineers, scientists, students, and other professionals across many areas, this is a must-have for any library. JOHN A, PHD, is an assistant professor at Galgotias University, Greater Noida, India, and he received his PhD in computer science and engineering from Manonmaniam Sundaranar University, Tirunelveli, India. He has presented papers in various national and international conferences and has published papers in scientific journals. SENTHIL KUMAR MOHAN, PHD, is an associate professor in the Department of Software and System Engineering at the School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India. He received his PhD in engineering and technology from Vellore Institute of Technology, and he has contributed to many research articles in various technical journals and conferences. SANJEEVIKUMAR PADMANABAN, PHD, is a faculty member with the Department of Energy Technology, Aalborg University, Esbjerg, Denmark. He has almost ten years of teaching, research and industrial experience and is an associate editor on a number of international scientific refereed journals. He has published more than 300 research papers and has won numerous awards for his research and teaching. YASIR HAMID, PHD, is an assistant professor in the Department of Information Security Engineering Technology at Abu Dhabi Polytechnic. He earned his PhD in 2019 from Pondicherry University in Computer Science and Engineering. Before joining ADPOLY, he was an assistant professor in the Department of Computer Science, Islamic University of Science and Technology, India. He is an editorial board member on many scientific and technical journals. List of Contributors xiiiPreface xvAcknowledgements xix1 REVIEW AND ANALYSIS OF MACHINE LEARNING BASED TECHNIQUES FOR LOAD FORECASTING IN SMART GRID SYSTEM 1Shihabudheen KV and Sheik Mohammed S1.1 Introduction 21.2 Forecasting Methodology 41.3 AI-Based Prediction Methods 51.3.1 Single Prediction Methods 51.3.1.1 Linear Regression 51.3.1.2 Artificial Neural Networks (ANN) 71.3.1.3 Support Vector Regression (SVR) 81.3.1.4 Extreme Learning Machine 91.3.1.5 Neuro-Fuzzy Techniques 101.3.1.6 Deep Learning Techniques 111.3.2 Hybrid Prediction Methods 121.3.2.1 Combined AI-Based Prediction Techniques 121.3.2.2 Signal Decomposition Based Prediction Techniques 131.3.2.3 EMD Based Decomposition 141.3.2.4 Wavelet Based Decomposition 141.4 Results and Discussions 151.4.1 Description of Dataset 151.4.2 Performance Analysis of Single Prediction Methods for Load Forecasting 161.4.2.1 Feature Selection 161.4.2.2 Optimal Parameter Selection 171.4.2.3 Prediction Results of Single Prediction Methods 171.4.3 Performance Analysis of Hybrid Prediction Methods for Load Forecasting 171.4.4 Comparative Analysis 211.5 Conclusion 22References 232 ENERGY OPTIMIZED TECHNIQUES IN CLOUD AND FOG COMPUTING 27N.M. Balamurugan, TKS Rathish babu, K Maithili and M. Adimoolam2.1 Introduction 282.2 Fog Computing and Its Applications 332.3 Energy Optimization Techniques in Cloud Computing 382.4 Energy Optimization Techniques in Fog Computing 422.5 Summary and Conclusions 44References 453 ENERGY-EFFICIENT CLOUD COMPUTING TECHNIQUES FOR NEXT GENERATION: WAYS OF ESTABLISHING AND STRATEGIES FOR FUTURE DEVELOPMENTS 49Praveen Mishra, M. Sivaram, M. Arvindhan, A. Daniel and Raju Ranjan3.1 Introduction 503.2 A Layered Model of Cloud Computing 523.2.1 System of Architecture 533.3 Energy and Cloud Computing 543.3.1 Performance of Network 553.3.2 Reliability of Servers 553.3.3 Forward Challenges 553.3.4 Quality of Machinery 563.4 Saving Electricity Prices 563.4.1 Renewable Energy 573.4.2 Cloud Freedom 573.5 Energy-Efficient Cloud Usage 583.6 Energy-Aware Edge OS 583.7 Energy Efficient Edge Computing Based on Machine Learning 593.8 Energy Aware Computing Offloading 613.8.1 Energy Usage Calculation and Simulation 633.9 Comments and Directions for the Future 63References 644 ENERGY OPTIMIZATION USING SILICON DIOXIDE COMPOSITE AND ANALYSIS OF WIRE ELECTRICAL DISCHARGE MACHINING CHARACTERISTICS 67M.S. Kumaravel, N. Alagumurthi and P. Mathiyalagan4.1 Introduction 674.2 Materials and Methods 694.3 Results and Discussion 724.3.1 XRD Analysis 724.3.2 SEM Analysis 734.3.3 Grey Relational Analysis (GRA) 734.3.4 Main Effects Graph 764.3.5 Analysis of Variance (ANOVA) 774.3.6 Confirmatory Test 784.4 Conclusion 80Acknowledgement 80References 805 OPTIMAL PLANNING OF RENEWABLE DG AND RECONFIGURATION OF DISTRIBUTION NETWORK CONSIDERING MULTIPLE OBJECTIVES USING PSO TECHNIQUE FOR DIFFERENT SCENARIOS 83Balmukund Kumar and Aashish Kumar Bohre5.1 Introduction 845.2 Literature Review for Recent Development in DG Planning and Network Reconfiguration 845.3 System Performance Parameters and Index 875.4 Proposed Method 885.4.1 Formulation of Multi-Objective Fitness Function 885.4.2 Backward-Forward-Sweep Load Flow Based on BIBC-BCBV Method 895.5 PSO Based Optimization 905.6 Test Systems 925.7 Results and Discussions 925.8 Conclusions 101References 1026 INVESTIGATION OF ENERGY OPTIMIZATION FOR SPECTRUM SENSING IN DISTRIBUTED COOPERATIVE IOT NETWORK USING DEEP LEARNING TECHNIQUES 107M. Pavithra, R. Rajmohan, T. Ananth Kumar, S. Usharani and P. Manju Bala6.1 Introduction 1086.2 IoT Architecture 1116.3 Cognitive Spectrum Sensing for Distributed Shared Network 1136.4 Intelligent Distributed Sensing 1156.5 Heuristic Search Based Solutions 1176.6 Selecting IoT Nodes Using Framework 1186.7 Training With Reinforcement Learning 1196.8 Model Validation 1206.9 Performance Evaluations 1236.10 Conclusion and Future Work 125References 1267 ROAD NETWORK ENERGY OPTIMIZATION USING IOT AND DEEP LEARNING 129N. M. Balamurugan, N. Revathi and R. Gayathri7.1 Introduction 1297.2 Road Network 1327.2.1 Types of Road 1327.2.2 Road Structure Representation 1347.2.3 Intelligent Road Lighting System 1357.3 Road Anomaly Detection 1397.4 Role of IoT in Road Network Energy Optimization 1417.5 Deep Learning of Road Network Traffic 1427.6 Road Safety and Security 1427.7 Conclusion 144References 1448 ENERGY OPTIMIZATION IN SMART HOMES AND BUILDINGS 147S. Sathya, G. Karthi, A. Suresh Kumar and S. Prakash8.1 Introduction 1488.2 Study of Energy Management 1508.3 Energy Optimization in Smart Home 1508.3.1 Power Spent in Smart-Building 1538.3.2 Hurdles of Execution in Energy Optimization 1568.3.3 Barriers to Assure SH Technologies 1568.4 Scope and Study Methodology 1578.4.1 Power Cost of SH 1588.5 Conclusion 159References 1599 MACHINE LEARNING BASED APPROACH FOR ENERGY MANAGEMENT IN THE SMART CITY REVOLUTION 161Deepica S., S. Kalavathi, Angelin Blessy J. and D. Maria Manuel Vianny9.1 Introduction 1629.1.1 Smart City: What is the Need? 1629.1.2 Development of Smart City 1639.2 Need for Energy Optimization 1669.3 Methods for Energy Effectiveness in Smart City 1669.3.1 Smart Electricity Grids 1669.3.2 Smart Transportation and Smart Traffic Management 1699.3.3 Natural Ventilation Effect 1729.4 Role of Machine Learning in Smart City Energy Optimization 1739.4.1 Machine Learning: An Overview 1739.5 Machine Learning Applications in Smart City 1759.6 Conclusion 177References 17810 DESIGN OF AN ENERGY EFFICIENT IOT SYSTEM FOR POULTRY FARM MANAGEMENT 181G. Rajakumar, G. Gnana Jenifer, T. Ananth Kumar and T. S. Arun Samuel10.1 Introduction 18210.2 Literature Survey 18310.3 Proposed Methodology 18710.3.1 Monitoring and Control Module 18810.3.2 Monitoring Temperature 18810.3.3 Monitoring Humidity 18910.3.4 Monitoring Air Pollutants 18910.3.5 Artificial Lightning 19010.3.6 Monitoring Water Level 19010.4 Hardware Components 19010.4.1 Arduino UNO 19010.4.2 Temperature Sensor 19010.4.3 Humidity Sensor 19110.4.4 Gas Sensor 19210.4.5 Water Level Sensor 19210.4.6 LDR Sensor 19310.4.7 GSM (Global System for Mobile Communication) Modem 19410.5 Results and Discussion 19510.5.1 Hardware Module 19510.5.2 Monitoring Temperature 19610.5.3 Monitoring Gas Content 19810.5.4 Monitoring Humidity 19810.5.5 Artificial Lighting 19810.5.6 Monitoring Water Level 19810.5.7 Poultry Energy-Efficiency Tips 19910.6 Conclusion 201References 20311 IOT BASED ENERGY OPTIMIZATION IN SMART FARMING USING AI 205N. Padmapriya, T. Ananth Kumar, R. Aswini, R. Rajmohan, P. Kanimozhi and M. Pavithra11.1 Introduction 20611.2 IoT in Smart Farming 20811.2.1 Benefits of Using IoT in Agriculture 20811.2.2 The IoT-Based Smart Farming Cycle 20911.3 AI in Smart Farming 21011.3.1 Artificial Intelligence Revolutionises Agriculture 21011.4 Energy Optimization in Smart Farming 21111.4.1 Energy Optimization in Smart Farming Using IoT and AI 21211.5 Experimental Results 21511.5.1 Analysis of Network Throughput 21611.5.2 Analysis of Network Latency 21711.5.3 Analysis of Energy Consumption 21811.5.4 Applications of IoT and AI in Smart Farming 21911.6 Conclusion 220References 22112 SMART ENERGY MANAGEMENT TECHNIQUES IN INDUSTRIES 5.0 225S. Usharani, P. Manju Bala, T. Ananth Kumar, R. Rajmohan and M. Pavithra12.1 Introduction 22612.2 Related Work 22712.3 General Smart Grid Architecture 22912.3.1 Energy Sub-Sectors 23012.3.1.1 Smart Grid: State-of-the-Art Inside Energy Sector 23012.3.2 EV and Power-to-Gas: State-of-the-Art within Biomass and Transport 23112.3.3 Constructing Zero Net Energy (CZNE): State-of-the-Art Inside Field of Buildings 23312.3.4 Manufacturing Industry: State-of-the-Art 23412.3.5 Smart Energy Systems 23512.4 Smart Control of Power 23612.4.1 Smart Control Thermal System 23612.4.2 Smart Control Cross-Sector 23712.5 Subsector Solutions 23812.6 Smart Energy Management Challenges in Smart Factories 23912.7 Smart Energy Management Importance 24012.8 System Design 24112.9 Smart Energy Management for Smart Grids 24112.10 Experimental Results 24712.11 Conclusions 250References 25113 ENERGY OPTIMIZATION TECHNIQUES IN TELEMEDICINE USING SOFT COMPUTING 253R. Indrakumari13.1 Introduction 25313.2 Essential Features of Telemedicine 25513.3 Issues Related to Telemedicine Networks 25613.4 Telemedicine Contracts 25713.5 Energy Efficiency: Policy and Technology Issue 25813.5.1 Soft Computing 25813.5.2 Fuzzy Logic 26013.5.3 Artificial Intelligence 26013.5.4 Genetic Algorithms 26313.5.5 Expert System 26313.5.6 Expert System Based on Fuzzy Logic Rules 26413.6 Patient Condition Monitoring 26613.7 Analysis of Physiological Signals and Data Processing 27113.8 M-Health Monitoring System Architecture 27213.9 Conclusions 275References 27614 HEALTHCARE: ENERGY OPTIMIZATION TECHNIQUES USING IOT AND MACHINE LEARNING 279G. Vallathan, Senthilkumar Meyyappan and T. Rajani14.1 Introduction 28014.2 Energy Optimization Process 28114.3 Energy Optimization Techniques in Healthcare 28314.3.1 Energy Optimization in Building 28314.3.2 Machine Learning for Energy Optimization 28414.3.3 Reinforcement Learning for Energy Optimization 28614.3.4 Energy Optimization of Sustainable Internet of Things (IoT) 28714.4 Future Direction of Energy Optimizations 28814.5 Conclusion 289References 28915 CASE STUDY OF ENERGY OPTIMIZATION: ELECTRIC VEHICLE ENERGY CONSUMPTION MINIMIZATION USING GENETIC ALGORITHM 291Pedram Asef15.1 Introduction 29215.2 Vehicle Modelling to Optimisation 29515.2.1 Vehicle Mathematical Modelling 29515.2.2 Vehicle Model Optimisation Process: Applied Genetic Algorithm 29815.2.3 GA Optimisation Results and Discussion 30115.3 Conclusion 305References 305About the Editors 307Index 309
Practical Database Auditing for Microsoft SQL Server and Azure SQL
Know how to track changes and key events in your SQL Server databases in support of application troubleshooting, regulatory compliance, and governance. This book shows how to use key features in SQL Server ,such as SQL Server Audit and Extended Events, to track schema changes, permission changes, and changes to your data. You’ll even learn how to track queries run against specific tables in a database.Not all changes and events can be captured and tracked using SQL Server Audit and Extended Events, and the book goes beyond those features to also show what can be captured using common criteria compliance, change data capture, temporal tables, or querying the SQL Server log. You will learn how to audit just what you need to audit, and how to audit pretty much anything that happens on a SQL Server instance. This book will also help you set up cloud auditing with an emphasis on Azure SQL Database, Azure SQL Managed Instance, and AWS RDS SQL Server.You don’t need expensive, third-party auditing tools to make auditing work for you, and to demonstrate and provide value back to your business. This book will help you set up an auditing solution that works for you and your needs. It shows how to collect the audit data that you need, centralize that data for easy reporting, and generate audit reports using built-in SQL Server functionality for use by your own team, developers, and organization’s auditors.WHAT YOU WILL LEARN* Understand why auditing is important for troubleshooting, compliance, and governance* Track changes and key events using SQL Server Audit and Extended Events* Track SQL Server configuration changes for governance and troubleshooting* Utilize change data capture and temporal tables to track data changes in SQL Server tables* Centralize auditing data from all your databases for easy querying and reporting* Configure auditing on Azure SQL, Azure SQL Managed Instance, and AWS RDS SQL Server WHO THIS BOOK IS FORDatabase administrators who need to know what’s changing on their database servers, and those who are making the changes; database-savvy DevOps engineers and developers who are charged with troubleshooting processes and applications; developers and administrators who are responsible for generating reports in support of regulatory compliance reporting and auditingJOSEPHINE BUSH has more than 10 years of experience as a database administrator. Her experience is extensive and broad-based, including experience in financial, business, and energy data systems using SQL Server, MySQL, Oracle, and PostgreSQL. She is a Microsoft Certified Solutions Expert: Data Management and Analytics. She holds a BS in Information Technology, an MBA in IT Management, and an MS in Data Analytics. She is the author of Learn SQL Database Programming. You can reach her on Twitter @hellosqlkitty.IntroductionPART I. GETTING STARTED WITH AUDITINGChapter 1. Why Auditing is ImportantChapter 2. Types of AuditingPART II. IMPLEMENTING AUDITINGChapter 3. What is SQL Server Audit?Chapter 4. Implementing SQL Server Audit via the GUIChapter 5. Implementing SQL Server Audit via SQL ScriptsChapter 6: What is Extended Events?Chapter 7: Implementing Extended Events via the GUIChapter 8: Implementing Extended Events via SQL ScriptsChapter 9. Tracking SQL Server Configuration ChangesChapter 10. Additional SQL Server Auditing and Tracking MethodsPART III. CENTRALIZING AND REPORTING ON AUDITING DATAChapter 11. Centralizing Audit DataChapter 12. Create Reports from Audit DataPART IV. CLOUD AUDITING OPTIONSChapter 13. Auditing Azure SQL DatabasesChapter 14. Auditing Azure SQL Managed InstanceChapter 15. Other Cloud Provider Auditing OptionsPART V. APPENDIXESAppendix A. Database Auditing Options Comparison
The Art of Site Reliability Engineering (SRE) with Azure
Gain a foundational understanding of SRE and learn its basic concepts and architectural best practices for deploying Azure IaaS, PaaS, and microservices-based resilient architectures.The book starts with the base concepts of SRE operations and developer needs, followed by definitions and acronyms of Service Level Agreements in real-world scenarios. Moving forward, you will learn how to build resilient IaaS solutions, PaaS solutions, and microservices architecture in Azure. Here you will go through Azure reference architecture for high-available storage, networking and virtual machine computing, describing Availability Sets and Zones and Scale Sets as main scenarios. You will explore similar reference architectures for Platform Services such as App Services with Web Apps, and work with data solutions like Azure SQL and Azure Cosmos DB.Next, you will learn automation to enable SRE with Azure DevOps Pipelines and GitHub Actions. You’ll also gain an understanding of how an open culture around post-mortems dramatically helps in optimizing SRE and the overall company culture around managing and running IT systems and application workloads. You’ll be exposed to incent management and monitoring practices, by making use of Azure Monitor/Log Analytics/Grafana, which forms the foundation of monitoring Azure and Hybrid-running workloads.As an extra, the book covers two new testing solutions: Azure Chaos Studio and Azure Load Testing. These solutions will make it easier to test the resilience of your services.After reading this book, you will understand the underlying concepts of SRE and its implementation using Azure public cloud.WHAT WILL YOU LEARN:* Learn SRE definitions and metrics like SLI/SLO/SLA, Error Budget, toil, MTTR, MTTF, and MTBF* Understand Azure Well-Architected Framework (WAF) and Disaster Recovery scenarios on Azure* Understand resiliency and how to design resilient solutions in Azure for different architecture types and services* Master core DevOps concepts and the difference between SRE and tools like Azure DevOps and GitHub* Utilize Azure observability tools like Azure Monitor, Application Insights, KQL or Grafana* Understand Incident Response and Blameless Post-Mortems and how to improve collaboration using ChatOps practices with Microsoft toolsWHO IS THIS BOOK FOR:IT operations administrators, engineers, security team members, as well as developers or DevOps engineers.UNAI HUETE BELOKI is a Microsoft Technical Trainer (MTT) working at Microsoft, based in San Sebastian (Spain).From February 2017 to July 2020 he worked as a PFE (Premier Field Engineer), offering support and education as a DevOps Expert to Microsoft customers all around EMEA , mainly focused in the following technologies: GitHub, Azure DevOps, Azure Cloud Architecture and Monitoring, Azure AI/Cognitive Services.Since July 2020, he has worked as a Microsoft Technical Trainer (MTT) on the technologies mentioned above, and served as the MTT lead for the AZ-400 DevOps Solutions exam, helping shape content of the exam/course.In his free time, he loves traveling, water sports like surfing and spearfishing, and mountain-related activities such as MTB and snowboarding.CHAPTER 1: THE FOUNDATION OF SREThis chapter lays out the foundation of Site Resiliency Engineering, founded by Google. From the base concepts of how IT Operations and Developers need to collaborate, to how SRE helps organizations in running business-critical workloads without major downtimeCHAPTER 2: SERVICE LEVEL MANAGEMENT DEFINITIONS AND ACRONYMS AND THEIR MEANING IN A REAL-LIFE CONTEXTThis Chapter describes all common Service Level Agreements (SLA) definitions and acronyms, looked at from a real-world scenario to provide a clear understandingo Some examples, SLA, SLO, MTTF, MTBF, MTTR,…CHAPTER 3: ARCHITECTING RESILIENT INFRASTRUCTURE AS A SERVICE (IAAS) SOLUTIONS IN AZURESRE is all about providing ultimate uptime of your organization’s workloads, and this chapter will cover that in relation to Azure IaaS Compute solutions. Explaining the Azure reference architecture for high-available storage, networking and Virtual Machine computing, describing Availability Sets and Zones and ScaleSets as main scenarios. It will also touch on preparing for Disaster Recovery with Azure Backup and Azure Site Recovery, helping you to quickly mitigate outages in case of a failureCHAPTER 4: ARCHITECTING RESILIENT PLATFORM AS A SERVICE (PAAS) SOLUTIONS IN AZUREFollowing on the scenario of Virtual Machines, this chapter details similar reference architectures for Platform Services such as App Services with Web Apps, but also touching on data solutions like Azure SQL and Azure Cosmos DBCHAPTER 5: ARCHITECTING RESILIENT SERVERLESS AND MICROSERVICES ARCHITECTURES IN AZUREThis third chapter in the reference architecture topic describes how to build high-available, business-critical scenarios using Serverless Functions and Azure LogicApps, as well as Microservices scenarios using Azure Container Instance and Azure Kubernetes Service (AKS).CHAPTER 6: AUTOMATION TO ENABLE SRE WITH AZURE DEVOPS PIPELINES / GITHUB ACTIONSAutomation is the cornerstone to SRE, allowing businesses to not only deploy new workloads in a easy way, but also relying on SRE to avoid critical outages or, when an outage occurs, relying on automation to mitigate the problem as fast as possible. Sharing several examples from both Azure DevOps Pipelines and GitHub Actions, this chapter provides the reader a lot of real-life examples to reuse in their own environmentCHAPTER 7: EFFICIENTLY HANDLING BLAMELESS POST-MORTEMSPost-Mortems are the way to look back at what caused the outage, and describe any lessons learned for the future, helping in avoiding a similar outage in the future, or assist in quickly fixing an identical incident. Blameless is where the focus is on finding the root-cause of the problem, without pinpointing any individual or team as being the victim. This chapter describes how an open culture around post-mortems dramatically helps in optimizing SRE and the overall company culture around managing and running IT systems and application workloads.CHAPTER 8: MONITORING AS THE KEY TO KNOWLEDGEBesides the automated deployments, monitoring is the 2nd big technical topic in any SRE scenario. You can’t manage what you don’t know. This chapter provides an overview of Azure Monitor and Log Analytics, which forms the foundation of monitoring Azure and Hybrid-running workloads. Starting from metrics for the different Azure services touched on in earlier chapters, this chapter also covers how to export logs to 3rd party solutions such as Splunk or integrating dashboarding tools like Grafana
Enterprise-Grade IT Security for Small and Medium Businesses
Understand the IT security features that are needed to secure the IT infrastructure of a small to medium-size business. This book will give IT managers and executives a solid understanding of the different technology solutions that their business relies upon–or should be employing–in order to make reasoned decisions regarding the implementation of those features. Coverage includes multi-factor authentication, firewalls, zero-trust environments, network segmentation, remote access solutions, and the people aspects of security that are often overlooked and represent an organization’s biggest vulnerability.Chapters on the various technologies such as multi-factor authentication and zero-trust environments explain in plain English the values and benefits that each technology provides. Clear technical explanations are accompanied by business case explanations that explain the “why” of each technology and when each technology should be implemented. You will come away equipped to have business-driven discussions with your IT staff that allow for a productive balancing of the need for security with the need to do business and drive profits.YOU WILL LEARN* The importance of multi-factor authentication* The limits of what multi-factor authentication can protect* How firewalls are used to protect your company from attackers* What zero-trust environments are and what they mean* Whether zero-trust networks are what is needed to secure your own environment* The security benefits from implementing a network segmentation policy* The best ways to access files and resources from remote locations outside the officeWHO THIS BOOK IS FORManagers and executives at small to medium-size businesses who want to understand the core aspects of IT security on which their business relies, business leaders who want to be able to follow along with and engage in discussions with IT professionals about security features, and leaders who are tasked with making decisions on which IT security features to implementDENNY CHERRY has been working in the information technology field for ore than 20 years and has written almost a dozen IT books and hundreds of articles for various publications, including Inc., MSDN Magazine, and SQL Server Magazine, as well as having spoken at dozens of conferences around the world. He holds the Microsoft Certified Master certification, has been awarded the Microsoft Most Valuable Professional (MVP) award annually for more than 15 years, and has been awarded the VMware vExpert award six times. His public speaking started at local events in Southern California where he lives with his wife and their pet bunny rabbits and has expanded out to events worldwide. Speaking at conferences has taken Denny to six continents and over a dozen countries where he speaks at both small local events as well as large industry and corporate events. IntroductionPART I. THE INFRASTRUCTURE1. Why IT Security Matters2. Network Design3. Firewalls4. Distributed Denial of Service5. Remote ConnectivityPART II. THE COMPUTERS6. Operating System Security7. Multi-Factor Authentication8. Zero Trust EnvironmentsPART III. THE PEOPLE9. Protection Against the Weakest Security Link10. Employee Training
IoT System Testing
To succeed, teams must assure the quality of IoT systems. The world of technology continually moves from one hot area to another; this book considers the next explosion—of IoT—from a quality testing viewpoint. You'll first gain an introduction to the Internet of Things (IoT), V&V, and testing. Next, you'll be walked through IoT test planning and strategy over the full life cycle, including the impact of data analytics and AI. You will then delve deeper into IoT security testing and various test techniques, patterns, and more. This is followed by a detailed study of IoT software test labs, architecture, environments and AI. There are many options for testing IoT qualities based on the criticality of the software and risks involved; each option has positives, negatives, as well as cost and schedule impacts. The book will guide start-up and experienced teams into these paths and help you to improve the testing and quality assessment ofIoT systems. What You Will Learn Understand IoT software test architecture and planningMaster IoT security testing and test techniquesStudy IoT test lab automation and architecturesReview the need for IoT security, data analytics, AI, Neural Networks and dependability using testing and V&V Who This Book Is For Readers with basic knowledge of software development who want to learn more about IoT testing and its intricacies, as well as companies moving into the domain of IoT, and even those already deep into the IoT domain will benefit from this book.
CASP+ CompTIA Advanced Security Practitioner Study Guide
PREPARE TO SUCCEED IN YOUR NEW CYBERSECURITY CAREER WITH THE CHALLENGING AND SOUGHT-AFTER CASP+ CREDENTIALIn the newly updated Fourth Edition of CASP+ CompTIA Advanced Security Practitioner Study Guide Exam CAS-004, risk management and compliance expert Jeff Parker walks you through critical security topics and hands-on labs designed to prepare you for the new CompTIA Advanced Security Professional exam and a career in cybersecurity implementation. Content and chapter structure of this Fourth edition was developed and restructured to represent the CAS-004 Exam Objectives.From operations and architecture concepts, techniques and requirements to risk analysis, mobile and small-form factor device security, secure cloud integration, and cryptography, you’ll learn the cybersecurity technical skills you’ll need to succeed on the new CAS-004 exam, impress interviewers during your job search, and excel in your new career in cybersecurity implementation.This comprehensive book offers:* Efficient preparation for a challenging and rewarding career in implementing specific solutions within cybersecurity policies and frameworks * A robust grounding in the technical skills you’ll need to impress during cybersecurity interviews * Content delivered through scenarios, a strong focus of the CAS-004 Exam * Access to an interactive online test bank and study tools, including bonus practice exam questions, electronic flashcards, and a searchable glossary of key terms Perfect for anyone preparing for the CASP+ (CAS-004) exam and a new career in cybersecurity, CASP+ CompTIA Advanced Security Practitioner Study Guide Exam CAS-004 is also an ideal resource for current IT professionals wanting to promote their cybersecurity skills or prepare for a career transition into enterprise cybersecurity.ABOUT THE AUTHORSNADEAN H. TANNER has been in the technology industry for over 20 years in a variety of positions from marketing to training to web development to hardware. She has worked in academia as an IT director and a postgraduate technology instructor. She has also been a trainer and consultant in advanced cybersecurity for Fortune 500 companies as well as the U.S. Department of Defense. Nadean is the author of CASP+ Practices Tests: Exam CAS-004 and Cybersecurity Blue Team Toolkit.JEFF T. PARKER, CISSP, COMPTIA PROJECT+, CYSA+, is a certified technical trainer and consultant specializing in governance, risk management and compliance. Jeff’s infosec roots began as a security engineer, a member of a HP consulting group in Boston, USA. Prior to becoming an author, Jeff was a Global IT Risk Manager residing for several years in Prague, Czech Republic, where he rolled out a new risk management strategy for a multinational logistics firm. Introduction xxvAssessment Test xxxvCHAPTER 1 RISK MANAGEMENT 1Risk Terminology 4The Risk Assessment Process 6Asset Identification 6Information Classification 8Risk Assessment 9Risk Assessment Options 14Implementing Controls 16Policies Used to Manage Employees 17Pre-Employment Policies 18Employment Policies 18End of Employment and Termination Procedures 20Cost-Benefit Analysis 21Continuous Monitoring 22Enterprise Security Architecture Frameworks and Governance 23Training and Awareness for Users 24Best Practices for Risk Assessments 25Business Continuity Planning and Disaster Recovery 27Reviewing the Effectiveness of Existing Security Controls 28Conducting Lessons Learned and After-Action Reviews 30Creation, Collection, and Analysis of Metrics 31Metrics 31Trend Data 32Analyzing Security Solutions to Ensure They Meet Business Needs 32Testing Plans 33Internal and External Audits 34Using Judgment to Solve Difficult Problems 35Summary 35Exam Essentials 36Review Questions 38CHAPTER 2 CONFIGURE AND IMPLEMENT ENDPOINT SECURITY CONTROLS 43Hardening Techniques 45Address Space Layout Randomization Use 47Hardware Security Module and Trusted Platform Module 48Trusted Operating Systems 52Compensating Controls 55Summary 57Exam Essentials 58Review Questions 59CHAPTER 3 SECURITY OPERATIONS SCENARIOS 63Threat Management 66Types of Intelligence 66Threat Hunting 67Threat Emulation 67Actor Types 67Intelligence Collection Methods 71Open-SourceIntelligence 71Human Intelligence and Social Engineering 73Frameworks 74MITRE Adversarial Tactics, Techniques and Common Knowledge 74ATT&CK for Industrial Control Systems 75Cyber Kill Chain 76Diamond Model of Intrusion Analysis 76Indicators of Compromise 77Reading the Logs 77Intrusion Detection and Prevention 78Notifications and Responses to IoCs 79Response 80Summary 85Exam Essentials 85Review Questions 86CHAPTER 4 SECURITY OPS: VULNERABILITY ASSESSMENTS AND OPERATIONAL RISK 91Terminology 97Vulnerability Management 98Security Content Automation Protocol 103Self-Assessment vs. Third-Party Vendor Assessment 105Patch Management 108Information Sources 110Tools 112Assessments 124Penetration Testing 129Assessment Types 131Vulnerabilities 134Buffer Overflow 134Integer Overflow 135Memory Leaks 136Race Conditions (TOC/TOU) 136Resource Exhaustion 137Data Remnants 138Use of Third-Party Libraries 138Code Reuse 138Cryptographic Vulnerabilities 138Broken Authentication 139Security Misconfiguration 140Inherently Vulnerable System/Application 140Client-Side Processing vs. Server-Side Processing 141Attacks 145Proactive Detection 153Incident Response 153Countermeasures 153Deceptive Technology 154USB Key Drops 155Simulation 155Security Data Analytics 155Application Control 156Allow and Block Lists 157Security Automation 157Physical Security 158Summary 159Exam Essentials 160Review Questions 161CHAPTER 5 COMPLIANCE AND VENDOR RISK 165Shared Responsibility in Cloud Computing 168Cloud Service/Infrastructure Models 169Cloud Computing Providers and Hosting Options 169Benefits of Cloud Computing 171Security of On-Demand/Elastic Cloud Computing 174Geographic Location 175Infrastructure 175Compute 175Storage 175Networking 176Managing and Mitigating Risk 182Security Concerns of Integrating Diverse Industries 185Regulations, Accreditations, and Standards 187PCI DSS 187GDPR 190ISO 192CMMI 193NIST 194COPPA 195CSA-STAR 196HIPAA, SOX, and GLBA 197Contract and Agreement Types 198Third-Party Attestation of Compliance 202Legal Considerations 203Summary 204Exam Essentials 205Review Questions 206CHAPTER 6 CRYPTOGRAPHY AND PKI 211The History of Cryptography 216Cryptographic Goals and Requirements 217Supporting Security Requirements 218Compliance and Policy Requirements 219Privacy and Confidentiality Requirements 219Integrity Requirements 220Nonrepudiation 220Risks with Data 221Data at Rest 221Data in Transit 222Data in Process/Data in Use 222Hashing 223Message Digest 225Secure Hash Algorithm 225Message Authentication Code 226Hashed Message Authentication Code 226RACE Integrity Primitives Evaluation Message Digest 226Poly1305 226Symmetric Algorithms 227Data Encryption Standard 230Triple DES 231Rijndael and the Advanced Encryption Standard 231ChaCha 232Salsa20 232International Data Encryption Algorithm 232Rivest Cipher Algorithms 233Counter Mode 233Asymmetric Encryption 233Diffie–Hellman 235RSA 236Elliptic Curve Cryptography 237ElGamal 238Hybrid Encryption and Electronic Data Exchange (EDI) 238Public Key Infrastructure Hierarchy 239Certificate Authority 240Registration Authority 241Digital Certificates 241Certificate Revocation List 243Certificate Types 243Certificate Distribution 244The Client’s Role in PKI 245Implementation of Cryptographic Solutions 247Application Layer Encryption 248Transport Layer Encryption 249Internet Layer Controls 250Additional Authentication Protocols 251Cryptocurrency 252Digital Signatures 252Recognizing Cryptographic Attacks 254Troubleshooting Cryptographic Implementations 256Summary 259Exam Essentials 259Review Questions 261CHAPTER 7 INCIDENT RESPONSE AND FORENSICS 265The Incident Response Framework 268Event Classifications 268Triage Events 269Pre-Escalation Tasks 270The Incident Response Process 270Response Playbooks and Processes 273Communication Plan and Stakeholder Management 274Forensic Concepts 277Principles, Standards, and Practices 278The Forensic Process 279Forensic Analysis Tools 283File Carving Tools 284Binary Analysis Tools 284Analysis Tools 286Imaging Tools 288Hashing Utilities 289Live Collection vs. Postmortem Tools 290Summary 294Exam Essentials 294Review Questions 295CHAPTER 8 SECURITY ARCHITECTURE 301Security Requirements and Objectives for a Secure Network Architecture 310Services 310Segmentation 334Deperimeterization/Zero Trust 344Merging Networks from Various Organizations 352Software-Defined Networking 357Organizational Requirements for Infrastructure Security Design 358Scalability 358Resiliency 359Automation 359Containerization 360Virtualization 361Content Delivery Network 361Integrating Applications Securely into an Enterprise Architecture 362Baseline and Templates 362Software Assurance 367Considerations of Integrating Enterprise Applications 370Integrating Security into the Development Life Cycle 373Data Security Techniques for Securing Enterprise Architecture 384Data Loss Prevention 384Data Loss Detection 387Data Classification, Labeling, and Tagging 388Obfuscation 390Anonymization 390Encrypted vs. Unencrypted 390Data Life Cycle 391Data Inventory and Mapping 391Data Integrity Management 391Data Storage, Backup, and Recovery 392Security Requirements and Objectives for Authentication and Authorization Controls 394Credential Management 394Password Policies 396Federation 398Access Control 399Protocols 401Multifactor Authentication 403One-Time Passwords 404Hardware Root of Trust 404Single Sign-On 405JavaScript Object Notation Web Token 405Attestation and Identity Proofing 406Summary 406Exam Essentials 407Review Questions 410CHAPTER 9 SECURE CLOUD AND VIRTUALIZATION 415Implement Secure Cloud and Virtualization Solutions 418Virtualization Strategies 419Deployment Models and Considerations 425Service Models 429Cloud Provider Limitations 433Extending Appropriate On-Premises Controls 433Storage Models 439How Cloud Technology Adoption Impacts Organization Security 445Automation and Orchestration 445Encryption Configuration 445Logs 446Monitoring Configurations 447Key Ownership and Location 448Key Life-Cycle Management 448Backup and Recovery Methods 449Infrastructure vs. Serverless Computing 450Software-Defined Networking 450Misconfigurations 451Collaboration Tools 451Bit Splitting 461Data Dispersion 461Summary 461Exam Essentials 462Review Questions 463CHAPTER 10 MOBILITY AND EMERGING TECHNOLOGIES 467Emerging Technologies and Their Impact on Enterprise Security and Privacy 471Artificial Intelligence 472Machine Learning 472Deep Learning 472Quantum Computing 473Blockchain 473Homomorphic Encryption 474Distributed Consensus 475Big Data 475Virtual/Augmented Reality 4753D Printing 476Passwordless Authentication 476Nano Technology 477Biometric Impersonation 477Secure Enterprise Mobility Configurations 478Managed Configurations 479Deployment Scenarios 486Mobile Device Security Considerations 487Security Considerations for Technologies, Protocols, and Sectors 495Embedded Technologies 495ICS/Supervisory Control and Data Acquisition 496Protocols 498Sectors 499Summary 500Exam Essentials 500Review Questions 501Appendix Answers to Review Questions 505Chapter 1: Risk Management 506Chapter 2: Configure and Implement Endpoint Security Controls 507Chapter 3: Security Operations Scenarios 509Chapter 4: Security Ops: Vulnerability Assessments and Operational Risk 511Chapter 5: Compliance and Vendor Risk 513Chapter 6: Cryptography and PKI 514Chapter 7: Incident Response and Forensics 516Chapter 8: Security Architecture 519Chapter 9: Secure Cloud and Virtualization 522Chapter 10: Mobility and Emerging Technologies 524Index 529
MCA Microsoft Certified Associate Azure Network Engineer Study Guide
PREPARE TO TAKE THE NEW EXAM AZ-700 WITH CONFIDENCE AND LAUNCH YOUR CAREER AS AN AZURE NETWORK ENGINEERNot only does MCA Microsoft Certified Associate Azure Network Engineer Study Guide: Exam AZ-700 help you prepare for your certification exam, it takes a deep dive into the role and responsibilities of an Azure Network Engineer, so you can learn what to expect in your new career. You’ll also have access to additional online study tools, including hundreds of bonus practice exam questions, electronic flashcards, and a searchable glossary of important terms. Prepare smarter with Sybex's superior interactive online learning environment and test bank.Exam AZ-700, Designing and Implementing Microsoft Azure Networking Solutions, measures your ability to design, implement, manage, secure, and monitor technical tasks such as hybrid networking; core networking infrastructure; routing; networks; and private access to Azure services. With this in-demand certification, you can qualify for jobs as an Azure Network Engineer, where you will work with solution architects, cloud administrators, security engineers, application developers, and DevOps engineers to deliver Azure solutions. This study guide covers 100% of the objectives and all key concepts, including:* Design, Implement, and Manage Hybrid Networking* Design and Implement Core Networking Infrastructure* Design and Implement Routing* Secure and Monitor Networks* Design and Implement Private Access to Azure ServicesIf you’re ready to become the go-to person for recommending, planning, and implementing Azure networking solutions, you’ll need certification with Exam AZ-700. This is your one-stop study guide to feel confident and prepared on test day. Trust the proven Sybex self-study approach to validate your skills and to help you achieve your career goals!ABOUT THE AUTHORSPUTHIYAVAN UDAYAKUMAR is an infrastructure architect with over 14 years of experience in modernizing and securing IT infrastructure, including the Cloud. He has been writing technical books for more than ten years on various infrastructure and security domains. He has designed, deployed, and secured IT infrastructure out of on-premises and Cloud, including virtual servers, networks, storage, and desktops for various industries, including pharmaceutical, banking, healthcare, aviation, federal entities, etc. He is an open group certified Master certified architect. KATHIRAVAN UDAYAKUMAR is Head of Delivery and Chief Architect for Oracle Digital Technologies (Europe Practice) at Cognizant, covering various elements of technology stack in on-prem and cloud. He has over 18 years of experience in architecture, design, implementation, administration and integration with Green-field IT Systems, ERP, Cloud Platforms and Solutions across various business domains and Industries. He has had a passion for networking since he was an undergraduate and becoming a Cisco Certified Network Associate (CCNA). Introduction xxvAssessment Test xxxviiCHAPTER 1 GETTING STARTED WITH AZ-700 CERTIFICATION FOR AZURE NETWORKING 1Basics of Cloud Computing and Networking 2The Need for Networking Infrastructure 3The Need for the Cloud 3Basics of Networking 6Enterprise Cloud Networking 10Microsoft Azure Overview 11Azure Cloud Foundation 12Azure Global Infrastructure 14Azure Networking Terminology 20Azure Networking Overview 21Azure Networking Services 23Azure Virtual Network 26VNet Concepts and Best Practices 28Deploying a Virtual Network with Azure PowerShell 35Configure Public IP Services 37Basic SKUs 38Standard SKUs 39Configure a Basic SKU Public IP 40Configure a Standard SKU Public IP with Zones 40Configuring Domain Name Services 40Configure an Azure DNS Zone and Record Using Azure PowerShell 42Configuring Cross-Virtual Network Connectivity with Peering 43Configuring Peering between Two Virtual Networks in the Same Region 45Configuring Virtual Network Traffic Routing 46Using Forced Tunneling to Secure the VNet Route 52Configuring Internet Access with Azure Virtual NAT 53Deploy the NAT Gateway Using Azure PowerShell 54Summary 56Exam Essentials 56Hands-On Lab: Design and Deploy a Virtual Network via the Azure Portal 57Activity 1: Prepare the Network Schema 58Activity 2: Build the Aviation Resource Group 60Activity 3a: Build the CoreInfraVnet Virtual Network and Subnets 60Activity 3b: Build the EngineeringVnet Virtual Network and Subnets 64Activity 3c: Build the BranchofficeVnet Virtual Network and Subnets 66Activity 4: Validate the Build of VNets and Subnets 68Review Questions 70CHAPTER 2 DESIGN, DEPLOY, AND MANAGE A SITE-TO-SITE VPN CONNECTION AND POINT-TO-SITE VPN CONNECTION 75Overview of Azure VPN Gateway 76Designing an Azure VPN Connection 79Design Pattern 1 86Design Pattern 2 87Design Pattern 3 88Choosing a Virtual Network Gateway SKU for Site-to-Site VPN 89Using Policy-Based VPNs vs. Route-Based VPNs 92Building and Configuring a Virtual Network Gateway 94Building and Configuring a Local Network Gateway 97Building and Configuring an IPsec/IKE Policy 101Configuration Workflow 104Diagnosing and Resolving VPN Gateway Connectivity Issues 109Choosing a VNet Gateway SKU for Point-to-Site VPNs 112Configuring RADIUS, Certificate-Based, and Azure AD Authentication 116Configuration Workflow for Native Azure Certification Authentication 117Configuration Workflow for Native Azure Active Directory 124Configuration Workflow for Windows Active Directory 127Diagnosing and Resolving Client-Side and Authentication Issues 133Summary 136Exam Essentials 136Review Questions 140CHAPTER 3 DESIGN, DEPLOY, AND MANAGE AZURE EXPRESSROUTE 145Getting Started with Azure ExpressRoute 146Key Use Case for ExpressRoute 151ExpressRoute Deployment Model 151Choosing Between the Network Service Provider and ExpressRoute Direct 153Designing and Deploying Azure Cross-Region Connectivity between Multiple ExpressRoute Locations 156Selecting ExpressRoute Circuit SKUs 156Estimating Price Based on ExpressRoute SKU 156Select a Peering Location 157Select the Proper ExpressRoute Circuit 157Select a Billing Model 159Select a High Availability Design 159Pick a Business Continuity and Disaster Recovery Design Pattern 162Choosing an Appropriate ExpressRoute SKU and Tier 169Designing and Deploying ExpressRoute Global Reach 171Deploying ExpressRoute Global Reach 173Use Case 1: Enabling Circuits in the Same Region 173Use Case 2: Enabling Circuits in Different Regions 174Designing and Deploying ExpressRoute FastPath 175Evaluate Private Peering Only, Microsoft Peering Only, or Both 176Setting Up Private Peering 178Setting Up Microsoft Peering 181Building and Configuring an ExpressRoute Gateway 182Connect a Virtual Network to an ExpressRoute Circuit 186Recommend a Route Advertisement Configuration 190Configure Encryption over ExpressRoute 191Deploy Bidirectional Forwarding Detection 192Diagnose and Resolve ExpressRoute Connection Issues 193Summary 196Exam Essentials 196Review Questions 199CHAPTER 4 DESIGN AND DEPLOY CORE NETWORKING INFRASTRUCTURE: PRIVATE IP AND DNS 203Designing Private IP Addressing for VNets 204Deploying a VNet 210Preparing Subnetting for Services 213Subnetting Design Considerations 214Example Case Study: Preparing Subnetting for Services 218Configuring Subnetting for Services 220Preparing and Configuring a Subnet Delegation 223Configure Subnet Delegation 225Planning and Configuring Subnetting for Azure Route Server 226Designing and Configuring Public DNS Zones 231Creating an Azure DNS Zone and Record Using PowerShell 233Designing and Configuring Private DNS Zones 235Creating a Private DNS Zone and Record Using PowerShell 238Designing Name Resolution Inside a VNet 240VMs and Role Instances 243Web Apps 243Linking a Private DNS Zone to a VNet 245Summary 248Exam Essentials 249Review Questions 251CHAPTER 5 DESIGN AND DEPLOY CORE NETWORKING INFRASTRUCTURE AND VIRTUAL WANS 255Overview of Virtual Network Peering, Service Chaining, and Gateway Transit 256Configure VPN Gateway Transit for Virtual Network Peering 258Design VPN Connectivity between VNets 263Deploy VNet Peering 266Deployment Model 1: Running in the Same Azure Subscription and Deployed Using Azure Resource Manager 267Deployment Model 2: Running in Different Subscriptions and Deploying Using Resource Manager 270Deployment Model 3: Running in the Same Subscription and Deploying One VNet Using Resource Manager and Another Using the Classic Model 273Deployment Model 4: Running in Different Subscriptions and Deploying One VNet Using Resource Manager and Another Using the Classic Model 275Design an Azure Virtual WAN Architecture 277Choosing SKUs and Services for Virtual WANs 289Connect a VNet Gateway to an Azure Virtual WAN and Build a Hub in a Virtual WAN 291Build a Virtual Network Appliance (NVA) in a Virtual Hub 299Set Up Virtual Hub Routing 304Build a Connection Unit 306Summary 309Exam Essentials 310Review Questions 312CHAPTER 6 DESIGN AND DEPLOY VNET ROUTING AND AZURE LOAD BALANCER 317Design and Deploy User-Defined Routes 318Basic Routing Concepts 318Azure Routes 321Associate a Route Table with a Subnet 328Set Up Forced Tunneling 329Diagnose and Resolve Routing Issues 334Design and Deploy Azure Route Server 336Route Server Design Pattern 1 338Route Server Design Pattern 2 339Choosing an Azure Load Balancer SKU 344Choosing Between Public and Internal Load Balancers 349Build and Configure an Azure Load Balancer (Including Cross-Region) 353Build and Configure Cross-Region Load Balancer Resources 361Deploy a Load Balancing Rule 366Build and Configure Inbound NAT Rules 370Build Explicit Outbound Rules for a Load Balancer 371Summary 374Exam Essentials 375Review Questions 377CHAPTER 7 DESIGN AND DEPLOY AZURE APPLICATION GATEWAY, AZURE FRONT DOOR, AND VIRTUAL NAT 381Azure Application Gateway Overview 383How Application Gateway Works 385Scaling Options for Application Gateway and WAF 389Overview of Application Gateway Deployment 390Front-End Setup 390Back-End Setup 390Health Probes Setup 391Configuring Listeners 393Redirection Overview 394Application Gateway Request Routing Rules 395Redirection Setting 397Application Gateway Rewrite Policies 397Features and Capabilities of Azure Front Door SKUs 409Health Probe Characteristics and Operation 411Secure Front Door with SSL 412Front Door for Web Applications with a High-Availability Design Pattern 413SSL Termination and End-to-End SSL Encryption 421Multisite Listeners 423Back-Ends, Back-End Pools, Back-End Host Headers, and Back-End Health Probes 424Routing and Routing Rules 426URL Redirection and URL Rewriting in Front Door Standard and Premium 427Design and Deploy Traffic Manager Profiles 429How Traffic Manager Works 430Traffic Manager Routing Methods 432Priority-Based Traffic Routing 433Weighted-Based Traffic Routing 433Performance-Based Traffic Routing 435Geographic-Based Traffic Routing 436Multivalue-Based Traffic Routing 437Subnet-Based Traffic Routing 437Building a Traffic Manager Profile 438Virtual Network NAT 442Using a Virtual Network NAT 443Allocate Public IP or Public IP Prefixes for a NAT Gateway 445Associate a Virtual Network NAT with a Subnet 447Summary 451Exam Essentials 451Review Questions 455CHAPTER 8 DESIGN, DEPLOY, AND MANAGE AZURE FIREWALL AND NETWORK SECURITY GROUPS 459Azure Firewall and Firewall Manager Features 460How Azure Firewall Manager Works 467How Azure Firewall and Firewall Manager Protect VNets 468Build and Configure an Azure Firewall Deployment 476Azure Firewall Policy 495Build and Configure a Secure Hub within an Azure Virtual WAN Hub 501Build and Configure a Secure Hub within an Azure Virtual WAN Hub Using Azure PowerShell 503Integrate an Azure Virtual WAN Hub with a Third-Party Network Virtual Appliance 507High-Level Use Case for Network Virtual Appliances 508Create and Attach a Network Security Group to a Resource 509Create an Application Security Group and Attach It to a NIC 519Create and Configure NSG Rules and Read Network Security Group Flow Logs 524Validate NSG Flow Rules 531Verify IP Flow 534Summary 536Exam Essentials 536Review Questions 539CHAPTER 9 DESIGN AND DEPLOY AZURE WEB APPLICATION FIREWALL AND MONITOR NETWORKS 543Azure Web Application Firewall Functions and Features 544WAF on Application Gateway 547WAF on Front Door 549WAF on Azure CDN from Microsoft 550Set Up Detection or Prevention Mode 551Azure Front Door WAF Policy Rule Sets 553Managed Rule Sets 555Custom Rule Sets 558WAF Policies 560Application Gateway WAF Policy Rule Sets 566Per-Site WAF Policy 568Per-URI Policy 568Managed Rules 568WAF Policies 572Custom Rules 573Deploy and Attach WAF Policies 580Set Up Network Health Alerts and Logging Using Azure Monitor 582Build and Configure Azure Network Watcher 591Build and Configure a Connection Monitor Instance 595Build, Configure, and Use Traffic Analytics 600Build and Configure NSG Flow Logs 604Enable and Set Up Diagnostic Logging 607Enabling Diagnostic Logging 608Summary 609Exam Essentials 609Review Questions 611CHAPTER 10 DESIGN AND DEPLOY PRIVATE ACCESS TO AZURE SERVICES 615Overview of Private Link Services and Private Endpoints 616Key Benefits of Private Link 618How Private Link Integrates into an Azure Virtual Network 619How Azure Private Endpoint Works 619Plan Private Endpoints 628Configure Access to Private Endpoints 632Azure Private Link RBAC Permissions 634Integrate Private Link with DNS and Private Link Services with On-Premises Clients 634Use Case 1: Workloads on Virtual Networks without a Custom DNS Server 635Use Case 2: Workloads That Use a DNS Forwarder On-Premises 637Use Case 3: Using a DNS Forwarder for Virtual Network Workloads and On-Premises Workloads 640Set Up Service Endpoints and Configure Service Endpoint Policies 642Overview of Service Tags and Access to Service Endpoints 646Configure Access to Service Endpoints 651Integrating App Services into Regional VNets 657Azure Regional VNet Integration 658How Azure Regional VNet Integration Works 659Subnet Requirements 660Access Management 661Route Management 661Application Route Management 662Configure Azure Kubernetes Service (AKS) for Regional VNet Integration 665Configure Clients to Access the App Service Environment 670Summary 673Exam Essentials 673Review Questions 675Appendix Answers to Review Questions 679Chapter 1: Getting Started with AZ-700 Certification for Azure Networking 680Chapter 2: Design, Deploy, and Manage a Site-to-Site VPN Connection and Point-to-Site VPN Connection 681Chapter 3: Design, Deploy, and Manage Azure ExpressRoute 683Chapter 4: Design and Deploy Core Networking Infrastructure: Private IP and DNS 685Chapter 5: Design and Deploy Core Networking Infrastructure and Virtual WANs 686Chapter 6: Design and Deploy VNet Routing and Azure Load Balancer 688Chapter 7: Design and Deploy Azure application gateway, Azure front door, and Virtual NAT 690Chapter 8: Design, Deploy, and Manage Azure Firewall and Network Security Groups 691Chapter 9: Design and Deploy Azure Web Application Firewall and Monitor Networks 693Chapter 10: Design and Deploy Private Access to Azure Services 694Index 697
A Practical Guide to Verilog-A
Discover how Verilog-A is particularly designed to describe behavior and connectivity of circuits and system components for analog SPICE-class simulators, or for continuous time (SPICE-based) kernels in Verilog-AMS simulators. With continuous updates since it’s release 30 years ago, this practical guide provides a comprehensive foundation and understanding to the modeling language in its most recent standard formulation.With the introduction of language extensions to support compact device modeling, the Verilog-A has become today de facto standard language in the electronics industry for coding compact models of active and passive semiconductor devices. You'll gain an in depth look at how analog circuit simulators work, solving system equations, modeling of components from other physical domains, and modeling the same physical circuits and systems at various levels of detail and at different levels of abstraction.All industry standard compact models released by Si2 Compact Model Coalition (CMC) as well as compact models of emerging nano-electronics devices released by New Era Electronic Devices and Systems (NEEDS) initiative are coded in Verilog-A. This book prepares you for the current trends in the neuromorphic computing, hardware customization for artificial intelligence applications as well as circuit design for internet of things (IOT) will only increase the need for analog simulation modeling and make Verilog-A even more important as a multi-domain component-oriented modeling language.Let A Practical Guide to Verilog-A be the initial step in learning the extended mixed-signal Verilog-AMS hardware description language.WHAT YOU'LL LEARN* Review the hardware description and modeling language Verilog-A in its most recent standard formulation.* Code new compact models of active and passive semiconductor devices as well as new models for emerging circuit components from different physical disciplines.* Extend the application of SPICE-like circuit simulators to non-electronics field (neuromorphic, thermal, mechanical, etc systems).* Apply the initial steps towards the extended mixed-signal Verilog-AMS hardware description language.WHO THIS BOOK IS FORElectronic circuit designers and SPICE simulation model developers in academia and industry. Developers of electronic design automation (EDA) tools. Engineers, scientists and students of various disciplines using SPICE-like simulators for research and development.Dr. Slobodan Mijalkovic is a Senior R&D Engineer at Silvaco, Inc., specialized in semiconductor device and integrated circuit modeling for electronic design automation (EDA) software tools. Before joining Silvaco Europe, he was a Principal Researcher in HiTeC Laboratory at Delft University of Technology in the Netherlands, where he led a team for standardization of the Mextram bipolar transistor model with Compact Model Coalition (CMC). Formerly, he was an Assistant and an Associate Professor with the Department of Microelectronics at Faculty of Electronics Engineering, University of Nis in Serbia (Yugoslavia).Dr. Mijalkovic has authored 50 cited publications including the monograph “Multigrid Methods for Process Simulation” published by Springer. In the period 2002-2006 he has set and chaired four editions of “Compact Modeling for RF Application (CMRF)” workshops that strongly contributed to the acceptance of Verilog-A as a standard compact modeling language. He is a senior Member of IEEE and currently a member of the IEEE EDS Compact Modeling Committee.Chapter 1: IntroductionChapter Goal: Verilog-A delineation. Comparison to other HDLs and modeling languages. Book organization.Chapter 2: The Lexical Basis of Verilog-AChapter Goal: Introducing Verilog-A lexical tokens, token separators as well as basic token groups and token containers.Chapter 3: Basic Types and ExpressionsChapter Goal: Introducing integer, real and string data types and how expressions are assembled for different types using operators.Chapter 4: Nets and SignalsChapter Goal: Introducing the concept of nets and signals defined by nature and net_discipline types.Chapter 5: Modules and NetlistsChapter Goal: Introducing modules, as basic units of hierarchy in Verilog-A language, and their instantiation in SPICE and Verilog-A netlists.Chapter 6: Parameters and ParamsetsChapter Goal: Introducing the concept of parameters, customization of modules by passing parameters into a module at instantiation and the concept of instance and model parameters defined via paramsets.Chapter 7: Branch Contribution StatementsChapter Goal: Introducing the concept of analog branch assignments and signal access mechanisms.Chapter 8: Procedural StatementsChapter Goal: Introducing analog procedural block and procedural control statements.Chapter 9: Derivative and Integral OperatorsChapter Goal: Detailed description of analog functions used to perform differentiation and integration in time.Chapter 10: Built-in Mathematical FunctionsChapter Goal: Define all Verilog-A standard mathematical function.Chapter 11: User Defined FunctionsChapter Goal: Describe how to write modular, maintainable and reusable models in Verilog-A using user defined functions.Chapter 12: Analog Filter FunctionsChapter Goal: Introducing Verilog-A time and frequency domain filter functions and their usage with constant and dynamic arguments.Chapter 13: Look-Up Table ModelsChapter Goal: Describing how to create a multidimensional interpolation lookup-up table models in Verilog-AChapter 14: Small Signal and Noise SourcesChapter Goal: Introducing Verilog-A functions supporting small signal and noise analysis in SPICE simulators.Chapter 15: EventsChapter Goal: Introducing methods to control analog behaviour of the component models in Verilog-A.Chapter 16: Input and OutputChapter Goal: Describe methods and functions to read and write formatted data.Chapter 17: Simulator Query and Control MethodsChapter Goal: Describing the methods to access the simulator kernel parameters in the Verilog-A model.Chapter 18: AttributesChapter Goal: Introducing attributes as a mechanism for specifying properties about objects, statements and groups of statements in the Verilog-A source that can be used by the simulator.Chapter 19: Compiler DirectivesChapter Goal: Introducing compiler directives that dictate Verilog-A compiler behaviour in a pre-processingcompilation phase.Chapter 20: SPICE CompatibilityChapter Goal: Describes the degree of compatibility with SPICE-like simulators which Verilog-A provides and the approach taken to provide that compatibility.
Make: Elektronik (3. Auflage)
Eine unterhaltsame Einführung für Maker, Kids, Tüftlerinnen und Bastler in 3. Auflage.Dinge verheizen, Sachen vermasseln – so lernt man. Beginnend mit den grundlegenden Konzepten können Sie anhand eigener praktischer Experimente und unter Verwendung erschwinglicher Teile und Werkzeuge lernen.Auf dem Weg dorthin können Sie eine Sicherung durchbrennen lassen, ein Relais zum Summen bringen und eine Leuchtdiode durchbrennen lassen. In Make: Elektronik gibt es kein misslungenes Experiment, denn alle Experimente sind ein wertvoller Lernprozess. Mit dieser dritten Auflage wird das bewährte Buch jetzt noch besser.Innerhalb weniger Stunden bauen Sie einen Reflexionstester, einen Einbruchsalarm, ein Quizspiel oder ein Zahlenschloss – und modifizieren sie, um noch viel mehr zu tun. Nachdem Sie die Grundlagen von Spannung, Strom, Widerstand, Kapazität und Induktivität kennengelernt haben, werden Sie die Grundlagen von Logikchips, Funk, Mikrocontrollern und Elektromagnetismus entdecken. Jedes Projekt passt auf ein einziges Breadboard, und die meisten erfordern keine Lötarbeiten.Alle Experimente arbeiten mit sicheren, niedrigen Spannungen, die meist von einer einzigen 9-Volt-Batterie geliefert werden. Make:-Elektronik zieht Leserinnen und Leser aller Altersgruppen angezogen, von 10-Jährigen bis hin zu Rentnerinnen und Rentnern, die endlich freie Zeit haben, um ihre Neugierde an Elektronik zu befriedigen.Zum Autor:Charles Platts erstes Elektronik-Projekt war ein Telefonanrufbeantworter, den er mit 15 selbst baute. Er wurde Science-Fiction-Autor (The Silicon Man), brachte Leuten das Erstellen von Computergrafiken bei und war Redakteur bei der Zeitschrift Wired, ehe er wieder zu seiner ersten Liebe, der Elektronik, zurückkehrte. Er ist Editor beim amerikanischen Make:-Magazin.
AWS Certified Solutions Architect Study Guide with 900 Practice Test Questions
MASTER AMAZON WEB SERVICES SOLUTION DELIVERY AND EFFICIENTLY PREPARE FOR THE AWS CERTIFIED SAA-C03 EXAM WITH THIS ALL-IN-ONE STUDY GUIDEThe AWS Certified Solutions Architect Study Guide: Associate (SAA-C03) Exam, 4th Edition comprehensively and effectively prepares you for the challenging SAA-C03 Exam. This Study Guide contains efficient and accurate study tools that will help you succeed on the exam. It offers access to the Sybex online learning environment and test bank, containing hundreds of test questions, bonus practice exams, a glossary of key terms, and electronic flashcards.In this complete and authoritative exam prep blueprint, Ben Piper and David Clinton show you how to:* Design resilient AWS architectures* Create high-performing solutions* Craft secure applications and architectures* Design inexpensive and cost-optimized architecturesAn essential resource for anyone trying to start a new career as an Amazon Web Services cloud solutions architect, the AWS Certified Solutions Architect Study Guide: Associate (SAA-C03) Exam, 4th Edition will also prove invaluable to currently practicing AWS professionals looking to brush up on the fundamentals of their work.ABOUT THE AUTHORBEN PIPER is an IT consultant who has created more than 30 educational courses covering Amazon Web Services, networking, and automation. Learn more about Ben from his website at www.benpiper.com. DAVID CLINTON is a system administrator, teacher, and writer. He has created training material for subjects including Linux systems, cloud computing (AWS in particular), and container technologies like Docker. David has written books on AWS, Linux administration, and server virtualization. Many of his video training courses can be found on Pluralsight.com. Introduction xxvAssessment Test xxxiAnswers to Assessment Test xxxviiPART I THE CORE AWS SERVICES 1CHAPTER 1 INTRODUCTION TO CLOUD COMPUTING AND AWS 3Cloud Computing and Virtualization 4Cloud Computing Architecture 4Cloud Computing Optimization 5The AWS Cloud 6AWS Platform Architecture 10AWS Reliability and Compliance 13The AWS Shared Responsibility Model 13The AWS Service Level Agreement 14Working with AWS 14AWS Organizations 14AWS Control Tower 15AWS Service Catalog 15AWS License Manager 16AWS Artifact 16The AWS CLI 16AWS SDKs 17Technical Support and Online Resources 17Support Plans 17Other Support Resources 18Migrating Existing Resources to AWS 18AWS Migration Hub 19AWS Application Migration Service 19AWS Database Migration Service 19AWS Application Discovery Service 20Summary 20Exam Essentials 21Review Questions 22CHAPTER 2 COMPUTE SERVICES 25Introduction 26EC2 Instances 27Provisioning Your Instance 27Configuring Instance Behavior 32Placement Groups 33Instance Pricing 33Instance Life Cycle 34Resource Tags 35Service Limits 36EC2 Storage Volumes 36Elastic Block Store Volumes 36Instance Store Volumes 38Accessing Your EC2 Instance 39Securing Your EC2 Instance 41Security Groups 41IAM Roles 41NAT Devices 42Key Pairs 42EC2 Auto Scaling 43Launch Configurations 43Launch Templates 43Auto Scaling Groups 45Auto Scaling Options 46AWS Systems Manager 49Actions 50Insights 52AWS Systems Manager Inventory 53Running Containers 54Amazon Elastic Container Service 54Amazon Elastic Kubernetes Service 55Other Container-Oriented Services 55AWS CLI Example 56Summary 57Exam Essentials 58Review Questions 60CHAPTER 3 AWS STORAGE 67Introduction 68S3 Service Architecture 69Prefixes and Delimiters 69Working with Large Objects 69Encryption 71Logging 71S3 Durability and Availability 72Durability 72Availability 73Eventually Consistent Data 73S3 Object Life Cycle 74Versioning 74Life Cycle Management 74Accessing S3 Objects 75Access Control 75Presigned URLs 77Static Website Hosting 77Amazon S3 Glacier 79Storage Pricing 80Other Storage-Related Services 81Amazon Elastic File System 81Amazon FSx 81AWS Storage Gateway 81AWS Snow Family 82AWS DataSync 82AWS CLI Example 83Summary 84Exam Essentials 85Review Questions 86CHAPTER 4 AMAZON VIRTUAL PRIVATE CLOUD (VPC) 91Introduction 92VPC CIDR Blocks 92Secondary CIDR Blocks 93IPv6 CIDR Blocks 93Subnets 95Subnet CIDR Blocks 96Availability Zones 97IPv6 CIDR Blocks 99Elastic Network Interfaces 99Primary and Secondary Private IP Addresses 100Attaching Elastic Network Interfaces 100Enhanced Networking 101Internet Gateways 102Route Tables 102Routes 103The Default Route 104Security Groups 106Inbound Rules 106Outbound Rules 107Sources and Destinations 108Stateful Firewall 108Default Security Group 109Network Access Control Lists 110Inbound Rules 110Outbound Rules 113Using Network Access Control Lists and Security Groups Together 114AWS Network Firewall 115Public IP Addresses 115Elastic IP Addresses 116AWS Global Accelerator 118Network Address Translation 119Network Address Translation Devices 120Configuring Route Tables to Use NAT Devices 121NAT Gateway 121NAT Instance 122AWS PrivateLink 123VPC Peering 123Hybrid Cloud Networking 124AWS Site-to-Site VPN 125AWS Transit Gateway 125AWS Direct Connect 133High-Performance Computing 134Elastic Fabric Adapter 135AWS ParallelCluster 136Summary 136Exam Essentials 137Review Questions 138CHAPTER 5 DATABASE SERVICES 143Introduction 144Relational Databases 144Columns and Attributes 144Using Multiple Tables 145Structured Query Language 146Online Transaction Processing vs. Online Analytic Processing 147Amazon Relational Database Service 148Database Engines 148Licensing Considerations 149Database Option Groups 150Database Instance Classes 150Storage 151Read Replicas 154High Availability (Multi-AZ) 155Single-Master 156Multi-Master 157Backup and Recovery 157Automated Snapshots 157Maintenance Items 158Amazon RDS Proxy 158Amazon Redshift 159Compute Nodes 159Data Distribution Styles 159Redshift Spectrum 160AWS Database Migration Service 160Nonrelational (NoSQL) Databases 161Storing Data 161Querying Data 161Types of Nonrelational Databases 162DynamoDB 162Partition and Hash Keys 163Attributes and Items 164Throughput Capacity 165Reading Data 167Global Tables 168Backups 168Summary 168Exam Essentials 169Review Questions 170CHAPTER 6 AUTHENTICATION AND AUTHORIZATION—AWS IDENTITY AND ACCESS MANAGEMENT 175Introduction 176IAM Identities 176IAM Policies 177User and Root Accounts 178Access Keys 180Groups 181Roles 182Authentication Tools 183Amazon Cognito 183AWS Managed Microsoft AD 183AWS Single Sign-On 184AWS Key Management Service 184AWS Secrets Manager 184AWS CloudHSM 185AWS Resource Access Manager (AWS RAM) 185AWS CLI Example 185Summary 187Exam Essentials 187Review Questions 189CHAPTER 7 CLOUDTRAIL, CLOUDWATCH, AND AWS CONFIG 193Introduction 194CloudTrail 195Management Events 195Data Events 196Event History 196Trails 196Log File Integrity Validation 198CloudWatch 199CloudWatch Metrics 200Graphing Metrics 201Metric Math 203CloudWatch Logs 205CloudWatch Alarms 208Amazon EventBridge 211AWS Config 212The Configuration Recorder 213Configuration Items 213Configuration History 213Configuration Snapshots 213Monitoring Changes 214Summary 216Exam Essentials 216Review Questions 218CHAPTER 8 THE DOMAIN NAME SYSTEM AND NETWORK ROUTING: AMAZON ROUTE 53 AND AMAZON CLOUDFRONT 223Introduction 224The Domain Name System 224Namespaces 225Name Servers 225Domains and Domain Names 226Domain Registration 226Domain Layers 226Fully Qualified Domain Names 227Zones and Zone Files 227Record Types 227Alias Records 228Amazon Route 53 228Domain Registration 229DNS Management 229Availability Monitoring 231Routing Policies 232Traffic Flow 234Route 53 Resolver 234Amazon CloudFront 235AWS CLI Example 237Summary 238Exam Essentials 238Review Questions 239CHAPTER 9 DATA INGESTION, TRANSFORMATION, AND ANALYTICS 243Introduction 244AWS Lake Formation 244Ingestion 245Transformation 245Analytics 245AWS Transfer Family 246Kinesis 246Kinesis Video Streams 246Kinesis Data Streams 247Kinesis Data Firehose 248Kinesis Data Firehose vs. Kinesis Data Streams 248Summary 249Exam Essentials 249Review Questions 250PART II ARCHITECTING FOR REQUIREMENTS 255CHAPTER 10 RESILIENT ARCHITECTURES 257Introduction 258Calculating Availability 258Availability Differences in Traditional vs. Cloud-Native Applications 259Know Your Limits 262Increasing Availability 262EC2 Auto Scaling 263Launch Configurations 263Launch Templates 263Auto Scaling Groups 265Auto Scaling Options 266Data Backup and Recovery 270S3 270Elastic File System 271Elastic Block Storage 271Database Resiliency 271Creating a Resilient Network 272VPC Design Considerations 272External Connectivity 273Simple Queue Service 273Queues 274Queue Types 275Polling 276Dead-Letter Queues 276Designing for Availability 276Designing for 99 Percent Availability 277Designing for 99.9 Percent Availability 278Designing for 99.99 Percent Availability 279Summary 280Exam Essentials 281Review Questions 282CHAPTER 11 HIGH-PERFORMING ARCHITECTURES 289Introduction 290Optimizing Performance for the Core AWS Services 290Compute 291Storage 295Database 298Network Optimization and Load Balancing 299Infrastructure Automation 302CloudFormation 302Third-Party Automation Solutions 309Reviewing and Optimizing Infrastructure Configurations 310AWS Well-Architected Tool 311Load Testing 311Visualization 312Optimizing Data Operations 313Caching 313Partitioning/Sharding 315Compression 315Summary 316Exam Essentials 316Review Questions 318CHAPTER 12 SECURE ARCHITECTURES 323Introduction 324Identity and Access Management 324Protecting AWS Credentials 325Fine-GrainedAuthorization 325Permissions Boundaries 327Roles 328Enforcing Service-Level Protection 334Detective Controls 335CloudTrail 335CloudWatch Logs 335Searching Logs with Athena 336Auditing Resource Configurations with AWS Config 338Amazon GuardDuty 339Amazon Inspector 342Amazon Detective 343Security Hub 344Amazon Fraud Detector 344AWS Audit Manager 344Protecting Network Boundaries 344Network Access Control Lists and Security Groups 345AWS Web Application Firewall 345AWS Shield 345AWS Firewall Manager 346Data Encryption 346Data at Rest 346Data in Transit 348Macie 349Summary 349Exam Essentials 350Review Questions 351CHAPTER 13 COST-OPTIMIZED ARCHITECTURES 357Introduction 358Planning, Tracking, and Controlling Costs 358AWS Budgets 359Monitoring Tools 360AWS Trusted Advisor 361Online Calculator Tools 362Cost-OptimizingCompute 363Maximizing Server Density 364EC2 Reserved Instances 364EC2 Spot Instances 365Auto Scaling 368Elastic Block Store Lifecycle Manager 368Summary 368Exam Essentials 369Review Questions 370APPENDIX A ANSWERS TO REVIEW QUESTIONS 375Chapter 1: Introduction to Cloud Computing and AWS 376Chapter 2: Compute Services 377Chapter 3: AWS Storage 380Chapter 4: Amazon Virtual Private Cloud (VPC) 381Chapter 5: Database Services 383Chapter 6: Authentication and Authorization—AWS Identity and Access Management 386Chapter 7: CloudTrail, CloudWatch, and AWS Config 388Chapter 8: The Domain Name System and Network Routing: Amazon Route 53 and Amazon CloudFront 390Chapter 9: Data Ingestion, Transformation, and Analytics 392Chapter 10: Resilient Architectures 393Chapter 11: High-Performing Architectures 397Chapter 12: Secure Architectures 399Chapter 13: Cost-Optimized Architectures 401APPENDIX B ADDITIONAL SERVICES 405Deployment Tools 406AWS Amplify 406AWS Serverless Application Repository 406AWS Proton 407Developer Tools 407Amazon API Gateway 407AWS Device Farm 407AWS Step Functions 407Infrastructure Tools 408AWS Outposts 408AWS Wavelength 408VMware Cloud on AWS 408Connectivity Tools 409Amazon Pinpoint 409AWS Transfer Family 409AWS AppSync 409Database Tools 410Amazon DocumentDB (with MongoDB Compatibility) 410Amazon Keyspaces (for Apache Cassandra) 410Amazon Quantum Ledger Database (QLDB) 410Data Streaming Tools 410Amazon Managed Streaming for Apache Kafka (MSK) 410Amazon MQ 411AWS Data Exchange 411Amazon Timestream 411AWS Data Pipeline 411Amazon AppFlow 411Machine Learning and Artificial Intelligence 412Amazon Comprehend 412Amazon Forecast 412Amazon Lex 412Amazon Polly 412Amazon Rekognition 413Amazon Textract 413Amazon Transcribe 413Amazon Translate 413Other Tools 413AWS Batch 413AWS X-Ray 414Amazon Kendra 414Amazon OpenSearch Service (Amazon Elasticsearch Service) 414Amazon Managed Grafana 414Amazon Managed Service for Prometheus 415Index 417
Tools, Languages, Methodologies for Representing Semantics on the Web of Things
This book is a guide to the combination of the Internet of Things (IoT) and the Semantic Web, covering a variety of tools, technologies and applications that serve the myriad needs of the researchers in this field. It provides a multi dimensional view of the concepts, tools, techniques and issues that are involved in the development of semantics for the Web of Things.The various aspects studied in this book include Multi-Model Multi-Platform (SHM3P) databases for the IoT, clustering techniques for discovery services for the semantic IoT, dynamic security testing methods for the Semantic Web of Things, Semantic Web-enabled IoT integration for a smart city, IoT security issues, the role of the Semantic Web of Things in Industry 4.0, the integration of the Semantic Web and the IoT for e-health, smart healthcare systems to monitor patients, Semantic Web-based ontologies for the water domain, science fiction and searching for a job. SHIKHA MEHTA is Associate Professor in the Department of CSE & IT, Jaypee Institute of Information Technology, India. Her research interests include machine/deep learning algorithms, nature-inspired computing and social networks analytics.SANJU TIWARI is Senior Researcher at Universidad Autonoma de Tamaulipas, Mexico, DAAD Post-Doc-Net AI Fellow and PhD co-supervisor at Rai University, India, and has worked as a post-doctoral researcher in OEG, Universidad Politecnica de Madrid, Spain. Her research interests include artificial intelligence, knowledge graphs and ontology engineering.PATRICK SIARRY is Professor in automatics and informatics at University Paris Est Créteil, France. His research interests include the design of stochastic global optimization heuristics and their applications to various engineering fields. M.A. Jabbar is Professor and Head of the Department of CSE (AI & ML), Vardhaman College of Engineering, India. His research interests include artificial intelligence, Big Data analytics, bio-informatics and machine learning.Preface xiShikha MEHTA, Sanju TIWARI, Patrick SIARRY and M.A JABBARCHAPTER 1 THE ROLE OF SEMANTIC HYBRID MULTI-MODEL MULTI-PLATFORM (SHM3P) DATABASES FOR IOT 1Sven GROPPE, Jinghua GROPPE and Tobias GROTH1.1 Introduction 11.2 Databases for multi-model data 51.3 Platforms 71.4 Variations of SHM3P DBMS 131.5 What are the benefits of SHM3P databases for IoT? 141.5.1 Data storage and placement 141.5.2 Data processing 151.5.3 IoT applications 151.6 Summary and conclusions 161.7 References 16CHAPTER 2 A SYSTEMATIC REVIEW OF ONTOLOGIES FOR THE WATER DOMAIN 21Sanju TIWARI and Raúl GARCÍA-CASTRO2.1 Introduction 212.2 Literature review 232.2.1 Features in the water domain 232.2.2 Semantic models in the water domain 242.2.3 A comprehensive review of ontologies in the water domain 242.3 Applications of ontologies in the water domain 322.4 Discussion and conclusion 352.5 References 36CHAPTER 3 SEMANTIC WEB APPROACH FOR SMART HEALTH TO ENHANCE PATIENT MONITORING IN RESUSCITATION 41Fatima Zahra AMARA, Mounir HEMAM, Meriem DJEZZAR and Moufida MAIMOUR3.1 Introduction 423.2 Background 433.2.1 Semantic Web 433.2.2 SSN (Semantic Sensor Network) ontology 443.3 IoT Smart Health applications and semantics 453.4 Proposed approach and implementation 463.4.1 Knowledge representation 473.4.2 Ontology evaluation 513.4.3 Reasoning and querying 513.4.4 Linked Data 553.5 Conclusion 563.6 References 57CHAPTER 4 ROLE OF CLUSTERING IN DISCOVERY SERVICES FOR THE SEMANTIC INTERNET OF THINGS 61Shachi SHARMA4.1 Introduction 614.2 Discovery services in IoT 644.2.1 Directory-based architectures 644.2.2 Directory-less architectures 664.3 Semantic-based architectures 674.3.1 Search engine-based 674.3.2 ONS DNS-based 684.4 Discovery services and clustering 684.5 Clustering methods in IoT 694.6 Conclusion 714.7 References 71CHAPTER 5 DYNAMIC SECURITY TESTING TECHNIQUES FOR THE SEMANTIC WEB OF THINGS: MARKET AND INDUSTRY PERSPECTIVE 75Dhananjay SINGH CHAUHAN, Gaurav CHOUDHARY, Shishir Kumar SHANDILYA and Vikas SIHAG5.1 Introduction 755.2 Related studies 775.3 Background of dynamic security testing techniques 795.3.1 Black Box testing techniques 805.4 DAST using static analysis 825.4.1 Current implementation 825.5 DAST using user session 845.5.1 Current implementation 845.6 DAST using Extended Tainted Mode Model 865.6.1 Current implementation 875.7 Current issues and research directions 885.8 Conclusion 895.9 References 89CHAPTER 6 SCIFIONTO: MODELING, VISUALIZATION AND EVALUATION OF SCIENCE FICTION ONTOLOGIES BASED ON INDIAN CONTEXTUALIZATION WITH AUTOMATIC KNOWLEDGE ACQUISITION 93Gerard DEEPAK, Ayush A KUMAR and Sheeba J PRIYADARSHINI6.1 Introduction 946.2 Literature survey 976.2.1 Formulation and modeling of ontologies for varied domains of importance 976.2.2 Auxiliary automatic and semi-automatic models in ontology synthesis 976.2.3 Ontology-driven systems and applications 986.2.4 Automatic Knowledge Acquisition systems 996.2.5 Science fiction as an independent domain of existence 996.3 Modeling and evaluation of the ontology 1006.3.1 Ontology modeling 1006.3.2 Ontology visualization 1046.3.3 Ontology evaluation 1076.4 Automatic Knowledge Acquisition model 1116.4.1 System architecture 1116.4.2 Acquisition algorithm 1136.5 Conclusion 1196.6 References 119CHAPTER 7 SEMANTIC WEB-ENABLED IOT INTEGRATION FOR A SMART CITY 123Ronak PANCHAL and Fernando ORTIZ-RODRIGUEZ7.1 Introduction: Semantic Web and sensors 1237.2 Motivation and challenge 1247.3 Literature review 1247.4 Implementation of forest planting using SPARQL queries 1257.4.1 Architecture sketch with conceptual diagram 1257.4.2 Implementation ontology from the dataset 1267.4.3 Technologies and tools 1297.5 Conclusion 1367.6 References 136CHAPTER 8 HEART RATE MONITORING USING IOT AND AI 139Kalpana MURUGAN, Cherukuri NIKHIL KUMAR, Donthu Sai SUBASH and Sangam DEVA KISHORE REDDY8.1 Introduction 1408.2 Literature survey 1428.3 Heart rate monitoring system 1458.4 Results and discussion 1498.5 Conclusion and future works 1528.6 References 152CHAPTER 9 IOT SECURITY ISSUES AND ITS DEFENSIVE METHODS 155Keshavi NALLA and Seshu VARDHAN POTHABATHULA9.1 Introduction 1559.2 IoT security architecture 1589.2.1 Typical IoT architecture 1589.2.2 Centralized and distributed approaches over the IoT security architecture 1619.2.3 IoT security architecture based on blockchain 1639.2.4 Internet of Things security architecture: trust zones and boundaries 1649.2.5 Threat modeling in IoT security architecture 1689.3 Specific security challenges and approaches 1709.3.1 Identity and authentication 1709.3.2 Access control 1719.3.3 Protocol and network security 1729.3.4 Privacy 1729.3.5 Trust and governance 1739.3.6 Fault tolerance 1739.4 Methodologies used for securing the systems 1749.4.1 PKI and digital certificates 1749.4.2 Network security 1749.4.3 API security 1749.4.4 Network access control 1759.4.5 Segmentation 1759.4.6 Security gateways 1759.4.7 Patch management and software updates 1759.5 Conclusion 1769.6 References 176CHAPTER 10 ELUCIDATING THE SEMANTIC WEB OF THINGS FOR MAKING THE INDUSTRY 4.0 REVOLUTION A SUCCESS 179Deepika CHAUDHARY and Jaiteg SINGH10.1 Introduction 17910.2 Correlation of the Semantic Web of Things with IR4.0 18010.2.1 Smart machines 18110.2.2 Smart products 18210.2.3 Augmented operators 18210.2.4 The Web of Things 18310.2.5 Semantic Web of Things 18410.3 Smart manufacturing system and ontologies 18510.3.1 Vertical level integration 18510.3.2 Horizontal level of integration 18510.3.3 End-to-end integration 18510.4 Literature survey 18810.5 Conclusion and future work 19010.6 References 190CHAPTER 11 SEMANTIC WEB AND INTERNET OF THINGS IN E-HEALTH FOR COVID-19 195ANURAG and Naren JEEVA11.1 Introduction 19611.2 Dataset 19711.3 Application of IoT for Covid-19 19811.3.1 Continuous real-time remote monitoring 19811.3.2 Remote monitoring using W-kit 19811.3.3 Early identification and monitoring 19811.3.4 Continuous and reliable health monitoring 19811.3.5 ANN-assisted patient monitoring 19911.3.6 City lockdown monitoring 19911.3.7 Technologies for tracking and tracing 19911.3.8 Tracking and tracing suspected cases 19911.3.9 Anonymity preserving contact tracing model 20011.3.10 Cognitive radio-based IoT architecture 20011.3.11 Analyzing reasons for the outbreak 20011.3.12 Analyzing Covid-19 cases using disruptive technology 20011.3.13 Post-Covid applications 20111.4 Semantic Web applications for Covid-19 20111.4.1 Ontological approach for drug development 20211.4.2 Early detection and diagnosis 20211.4.3 Knowledge-based pre-diagnosis system 20211.4.4 Semantic-based searching for online learning resources 20311.4.5 Ontology-based physiological monitoring of students 20311.4.6 Analysis of clinical trials 20311.4.7 Data annotation of EHRs 20411.4.8 Disease pattern study 20411.4.9 Surveillance in primary care 20411.4.10 Performance assessment of healthcare services 20511.4.11 Vaccination drives and rollout strategies 20511.5 Limitations and challenges of IoT and SW models 20511.6 Discussion 20611.7 Conclusion 20611.8 References 207CHAPTER 12 DEVELOPMENT OF A SEMANTIC WEB ENABLED JOB_SEARCH ONTOLOGY SYSTEM 211Hina J CHOKSHI, Dhaval VYAS and Ronak PANCHAL12.1 Introduction 21112.1.1 Ontology 21212.1.2 Importance of ontology 21312.1.3 Semantic Web and its solutions 21412.1.4 Online recruitment scenarios 21412.2 Review of the related work done for online recruitment 21512.3 Design of “SearchAJob” ontology for the IT domain 21712.3.1 Ontology structure 21812.4 Implementing the proposed ontology 22212.4.1 Architecture of semantics-based job ontology 22312.5 Benefits of Semantic Web enabled SearchAJob system 23112.6 Conclusion and future scope 23212.7 References 233List of Authors 237Index 241
Practical MATLAB Deep Learning
Harness the power of MATLAB for deep-learning challenges. Practical MATLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. In this book, you’ll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. This edition includes new and expanded projects, and covers generative deep learning and reinforcement learning.Over the course of the book, you'll learn to model complex systems and apply deep learning to problems in those areas. Applications include:* Aircraft navigation* An aircraft that lands on Titan, the moon of Saturn, using reinforcement learning* Stock market prediction* Natural language processing* Music creation usng generative deep learning* Plasma control* Earth sensor processing for spacecraft* MATLAB Bluetooth data acquisition applied to dance physics WHAT YOU WILL LEARN* Explore deep learning using MATLAB and compare it to algorithms* Write a deep learning function in MATLAB and train it with examples* Use MATLAB toolboxes related to deep learning* Implement tokamak disruption prediction* Now includes reinforcement learningWHO THIS BOOK IS FOREngineers, data scientists, and students wanting a book rich in examples on deep learning using MATLAB.MICHAEL PALUSZEK is the co-author of MATLAB Recipes published by Apress. He is President of Princeton Satellite Systems, Inc. (PSS) in Plainsboro, New Jersey. Mr. Paluszek founded PSS in 1992 to provide aerospace consulting services. He used MATLAB to develop the control system and simulation for the Indostar-1 geosynschronous communications satellite, resulting in the launch of PSS' first commercial MATLAB toolbox, the Spacecraft Control Toolbox, in 1995. Since then he has developed toolboxes and software packages for aircraft, submarines, robotics, and fusion propulsion, resulting in PSS' current extensive product line. He is currently leading an Army research contract for precision attitude control of small satellites and working with the Princeton Plasma Physics Laboratory on a compact nuclear fusion reactor for energy generation and propulsion. Prior to founding PSS, Mr. Paluszek was an engineer at GE Astro Space in East Windsor, NJ. At GE he designed the Global Geospace Science Polar despun platform control system and led the design of the GPS IIR attitude control system, the Inmarsat-3 attitude control systems and the Mars Observer delta-V control system, leveraging MATLAB for control design. Mr. Paluszek also worked on the attitude determination system for the DMSP meteorological satellites. Mr. Paluszek flew communication satellites on over twelve satellite launches, including the GSTAR III recovery, the first transfer of a satellite to an operational orbit using electric thrusters. At Draper Laboratory Mr. Paluszek worked on the Space Shuttle, Space Station and submarine navigation. His Space Station work included designing of Control Moment Gyro based control systems for attitude control. Mr. Paluszek received his bachelors in Electrical Engineering, and master's and engineer’s degrees in Aeronautics and Astronautics from the Massachusetts Institute of Technology. He is author of numerous papers and has over a dozen U.S. Patents.STEPHANIE THOMAS is the co-author of MATLAB Recipes, published by Apress. She received her bachelor's and master's degrees in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 1999 and 2001. Ms. Thomas was introduced to PSS' Spacecraft Control Toolbox for MATLAB during a summer internship in 1996 and has been using MATLAB for aerospace analysis ever since. She built a simulation of a lunar transfer vehicle in C++, LunarPilot, during the same internship. In her nearly 20 years of MATLAB experience, she has developed many software tools including the Solar Sail Module for the Spacecraft Control Toolbox; a proximity satellite operations toolbox for the Air Force; collision monitoring Simulink blocks for the Prisma satellite mission; and launch vehicle analysis tools in MATLAB and Java, to name a few. She has developed novel methods for space situation assessment such as a numeric approach to assessing the general rendezvous problem between any two satellites implemented in both MATLAB and C++. Ms. Thomas has contributed to PSS' Attitude and Orbit Control textbook, featuring examples using the Spacecraft Control Toolbox, and written many software User's Guides. She has conducted SCT training for engineers from diverse locales such as Australia, Canada, Brazil, and Thailand and has performed MATLAB consulting for NASA, the Air Force, and the European Space Agency.ERIC HAM is a a Technical Specialist, Princeton Satellite Systems. His expertise lies with deep learning, programming using MATLAB, C++ and related.1. What is deep learning? – no changes except editoriala. Machine learning vs. deep learningb. Approaches to deep learningc. Recurrent deep learningd. Convolutional deep learning2. MATLAB machine and deep learning toolboxesa. Describe the functionality and applications of each toolboxb. Demonstrate MATLAB toolboxes related to Deep Learningc. Include the text toolbox generative toolbox and reinforcement learning toolboxd. Add more detail on each3. Finding Circles – no changes except editorial.4. Classifying movies – no changes except editorial.5. Tokamak disruption detection – this would be updated.6. Classifying a pirouette – no changes except editorial.7. Completing sentences - This would be revamped using the MATLAB Text Processing Toolbox.8. Terrain based navigation-The example in the original book would be changed to a regression approach that can interpolate position. We would switch to a terrestrial example applicable to drones.9. Stock prediction – this is a very popular chapter. We would improve the algorithm.10. Image classification – no changes except editorial.11. Orbit Determination – add inclination to the algorithm.12. Earth Sensors – a new example on how to use neural networks to measure roll and yaw from any Earth sensor.13. Generative deep learning example. This would be a neural network that generates pictures after learning an artist’s style.14. Reinforcement learning. This would be a simple quadcopter hovering control system. It would be simulation based although readers would be able to apply this to any programmable quadcopter.