Allgemein
Pro ASP.NET Core Identity
Get the most from ASP.NET Core Identity. Best-selling author ADAM FREEMAN teaches developers common authentication and user management scenarios and explains how they are implemented in applications. He covers each topic clearly and concisely, and the book is packed with the essential details you need to be effective.The book takes a deep dive into the Identity framework and explains how the most important and useful features work in detail, creating custom implementations of key components to reveal the inner workings of ASP.NET Core Identity. ASP.NET Core Identity provides authentication and user management for ASP.NET Core applications. Identity is a complex framework in its own right, with support for a wide range of features, including authenticating users with services provided by Google, Facebook, and Twitter.WHAT YOU WILL LEARN* Gain a solid understanding of how Identity provides authentication and authorization for ASP.NET Core applications* Configure ASP.NET Core Identity for common application scenarios, including self-service registration, user management, and authentication with services provided by popular social media platforms* Create robust and reliable user management tools* Understand how Identity works in detailWHO THIS BOOK IS FORDevelopers with advanced knowledge of ASP.NET Core who are introducing Identity into their projects. Prior experience and knowledge of C#, ASP.NET Core is required, along with a basic understanding of authentication and authorization concepts.ADAM FREEMAN is an experienced IT professional who has held senior positions in a range of companies, most recently serving as chief technology officer and chief operating officer of a global bank. Now retired, he spends his time writing and long-distance running. Part 1 - Using ASP.NET Core Identity1. Getting Ready2. Your First Identity Application3. Creating the Example Project4. Using the Identity UI5. Configuring Identity6. Adapting Identity UI7. Using the Identity API8. Signing In and Out and Managing Passwords9. Creating and Deleting Accounts10. Using Roles and Claims11. Two-Factor and External Authentication12. Authenticating API ClientsPart 2 - Understanding ASP.NET Core Identity13. Creating the Example Project14. Working with ASP.NET Core15. Authorizing Requests16. Creating a User Store17. Claims, Roles, and Confirmations18. Signing In with Identity19. Creating a Role Store20. Lockouts and Two-Factor Sign Ins21. Authenticators and Recovery Codes22. External Authentication - Part 123. External Authentication - Part 2
Practical Machine Learning for Streaming Data with Python
Design, develop, and validate machine learning models with streaming data using the Scikit-Multiflow framework. This book is a quick start guide for data scientists and machine learning engineers looking to implement machine learning models for streaming data with Python to generate real-time insights.You'll start with an introduction to streaming data, the various challenges associated with it, some of its real-world business applications, and various windowing techniques. You'll then examine incremental and online learning algorithms, and the concept of model evaluation with streaming data and get introduced to the Scikit-Multiflow framework in Python. This is followed by a review of the various change detection/concept drift detection algorithms and the implementation of various datasets using Scikit-Multiflow.Introduction to the various supervised and unsupervised algorithms for streaming data, and their implementation on various datasets using Python are also covered. The book concludes by briefly covering other open-source tools available for streaming data such as Spark, MOA (Massive Online Analysis), Kafka, and more.WHAT YOU'LL LEARN* Understand machine learning with streaming data concepts* Review incremental and online learning* Develop models for detecting concept drift* Explore techniques for classification, regression, and ensemble learning in streaming data contexts* Apply best practices for debugging and validating machine learning models in streaming data context* Get introduced to other open-source frameworks for handling streaming data.WHO THIS BOOK IS FORMachine learning engineers and data science professionalsDr. Sayan Putatunda is an experienced data scientist and researcher. He holds a Ph.D. in Applied Statistics/ Machine Learning from the Indian Institute of Management, Ahmedabad (IIMA) where his research was on streaming data and its applications in the transportation industry. He has a rich experience of working in both senior individual contributor and managerial roles in the data science industry with multiple companies such as Amazon, VMware, Mu Sigma, and more. His research interests are in streaming data, deep learning, machine learning, spatial point processes, and directional statistics. As a researcher, he has multiple publications in top international peer-reviewed journals with reputed publishers. He has presented his work at various reputed international machine learning and statistics conferences. He is also a member of IEEE.Chapter 1: An Introduction to Streaming DataChapter Goal: Introduce the readers to the concept of streaming data, the various challenges associated with it, some of its real-world business applications, various windowing techniques along with the concepts of incremental and online learning algorithms. This chapter will also help in understanding the concept of model evaluation in case of streaming data and provide and introduction to the Scikit-Multiflow framework in Python.No of pages- 35Sub -Topics1. Streaming data2. Challenges of streaming data3. Concept drift4. Applications of streaming data5. Windowing techniques6. Incremental learning and online learning7. Illustration : Adopting batch learners into incremental learners8. Introduction to Scikit-Multiflow framework9. Evaluation of streaming algorithmsChapter 2: Change DetectionChapter Goal: Help the readers to understand the various change detection/concept drift detection algorithms and its implementation on various datasets using Scikit-Multiflow.No of pages : 35Sub - Topics:1. Change detection problem2. Concept drift detection algorithms3. ADWIN4. DDM5. EDDM6. Page HinkleyChapter 3: Supervised and Unsupervised Learning for Streaming DataChapter Goal: Help the readers to understand the various regression and classification (including Ensemble Learning) algorithms for streaming data and its implementation on various datasets using Scikit-Multiflow. Also, discuss some approaches for clustering with streaming data and its implementation using Python.No of pages: 35Sub - Topics:1. Regression with streaming data2. Classification with streaming data3. Ensemble Learning with streaming data4. Clustering with streaming dataChapter 4: Other Tools and the Path ForwardChapter Goal: Introduce the readers to the other open source tools for handling streaming data such as Spark streaming, MOA and more. Also, educate the reader about additional reading for advanced topics within streaming data analysis.No of pages: 35Sub - Topics:1. Other tools for handling streaming data1.1.1. Apache Spark1.1.2. Massive Online Analysis (MOA)1.1.3. Apache Kafka2. Active research areas and breakthroughs in streaming data analysis3. Conclusion
Protective Security
This book shows you how military counter-intelligence principles and objectives are applied. It provides you with valuable advice and guidance to help your business understand threat vectors and the measures needed to reduce the risks and impacts to your organization. You will know how business-critical assets are compromised: cyberattack, data breach, system outage, pandemic, natural disaster, and many more.Rather than being compliance-concentric, this book focuses on how your business can identify the assets that are most valuable to your organization and the threat vectors associated with these assets. You will learn how to apply appropriate mitigation controls to reduce the risks within suitable tolerances.You will gain a comprehensive understanding of the value that effective protective security provides and how to develop an effective strategy for your type of business.WHAT YOU WILL LEARN* Take a deep dive into legal and regulatory perspectives and how an effective protective security strategy can help fulfill these ever-changing requirements* Know where compliance fits into a company-wide protective security strategy* Secure your digital footprint* Build effective 5 D network architectures: Defend, detect, delay, disrupt, deter* Secure manufacturing environments to balance a minimal impact on productivity* Securing your supply chains and the measures needed to ensure that risks are minimizedWho This Book Is ForBusiness owners, C-suite, information security practitioners, CISOs, cybersecurity practitioners, risk managers, IT operations managers, IT auditors, and military enthusiastsJIM (JAMES) SEAMAN has been dedicated to the pursuit of security for his entire adult life. He served 22 years in the RAF Police, covering a number of specialist areas (physical security, aviation security, information security management, IT security management, cyber security management, security investigations, intelligence operations, incident response and disaster recovery), before successfully transitioning his skills to corporate environments (financial services, banking, retail, manufacturing, ecommerce, marketing, etc.) to help businesses enhance their cyber/InfoSec defensive measures working with various industry security standards.CHAPTER 1: WHAT IS PROTECTIVE SECURITY (PS)?An introduction to the term ‘Protective Security’ and a description of why this differs to other industry terms (e.g. Cyber Security, Information Security, IT Security, Network Security, etc.)?Why PS should be an integral for your business operations?CHAPTER 2: PROTECTIVE SECURITY (PS) IN TERMS OF THE LEGAL & REGULATORY PERSPECTIVE.A deep dive into the Legal and Regulatory perspectives and how an effective PS strategy can help fulfil these ever-changing requirements?PS and the European Union General Data Protection Act (EU-GDPR).CHAPTER 3: THE INTEGRATION OF COMPLIANCE WITH PROTECTIVE SECURITY (PS).A description of where compliance fits into a company-wide PS strategy.PS and the Payment Card Industry Data Security Standard (PCI DSS).CHAPTER 4: THE DEVELOPMENT OF AN EFFECTIVE PROTECTIVE SECURITY (PS) STRATEGY.A comprehensive guide to the development of an effective strategy, aligning business assets to their importance for the business objectives and goals, to incorporate the threats, risks, and core components of any strategy.Strategic alignment with the business context.CHAPTER 5: CYBER SECURITY.A deep dive into the concept of Cyber Security, with a focus on Point of Origins (PoO) that occur in the ‘Badlands’ (e.g. outside the corporate network) to compromise internet-facing technologies (e.g. Ecommerce, Digital, Mobile, etc.)Securing your Digital Footprint.CHAPTER 6: NETWORK/IT SECURITY.The importance of secure by design/default networks to help safeguard your most important business IT assets from compromise.Lateral Movement Attacks.CHAPTER 7: INFORMATION SYSTEMS SECURITY.Providing a guide to the securing of these systems, as a separate asset type, based upon the value of the data assets to the business and to aid the application of the 5 Ds of Security (Defend, Detect, Delay, Disrupt & Deter).Building Effective 5 Ds Network Architectures.CHAPTER 8: PHYSICAL SECURITY.A comprehensive guide to the development of appropriate physical security measures and its importance within the Protective Security strategy.Fortifying Your Business Operations.CHAPTER 9: INDUSTRIAL SYSTEMS SECURITYIncreasingly, Manufacturing systems are vulnerable to cyber-attacks. Gain an insight how securing these environments can be balanced with a minimal impact on productivity.Manufacturing Secure Operations.CHAPTER 10: SECURING YOUR SUPPLY CHAINGain an appreciation for securing your Supply Chains and the measures needed to ensure that the Supply Chain risks are minimized.The Weakest Link?CHAPTER 11: DEVELOPING YOUR INTERNAL FIREWALL.A focus on the development of a robust Security Culture, through the proactive engagement with a business’ personnel assets.Security Is Not A Dirty Word.CHAPTER 12: STRICT ACCESS RESTRICTIONSThe ‘Need To Know’/’Need To Access’ are the fundamental principles for any effective Protective Security strategy. Gain an insight into why this is the case and how to ensure that this is the case within your organization.The Keys To Your Empire.CHAPTER 13: BUILDING RESILIENT SYSTEMSGain an appreciation for the business value of building resilient systems and an understanding on what is required to develop resilience into your PS strategy.The Ability To ‘Bounce Back’.CHAPTER 14: DEMONSTRATING THE PROTECTIVE SECURITY (PS) RETURN ON INVESTMENTS (ROI)The value of an effective PS strategy is often underappreciated by business leaders. Gain an understanding on how to demonstrate to that their investments continue to deliver a robust security posture and continues to ensure that they remain a less viable target.The Value of PS.
Datenschutz nach DS-GVO und Informationssicherheit gewährleisten
In vielen Unternehmen und Behörden gibt es zahlreiche Verfahren, die sowohl die Anforderungen des Datenschutzes als auch die der Informationssicherheit erfüllen müssen. Was liegt da näher als die Auswahl der erforderlichen Sicherungsmaßnahmen in einem einheitlichen Vorgehen zu ermitteln. Mit diesem Werk gibt der Autor dem Praktiker einen Leitfaden an die Hand, den dieser gleichermaßen bei einfachen als auch komplexen Verfahren anwenden kann.Im ersten Teil wird auf Basis des Prozesses ZAWAS die Umsetzung der Anforderungen der DS-GVO (einschl. DSFA) aufgezeigt. Zusätzlich zeigt der Autor im zweiten Teil des Buches auf, wie durch eine kleine Prozesserweiterung dieses Vorgehen auch auf die Ermittlung der erforderlichen Sicherungsmaßnahmen für die Informationssicherheit genutzt werden kann.Dieses Vorgehen reduziert den Gesamtaufwand und führt zu einem höheren Schutzniveau.STEFAN MIEROWSKI, MSc., Dipl. Finanzwirt (FH), studierte Informatik und Rechtswissenschaft, Referent bei der Landesbeauftragten für den Datenschutz Niedersachsen, ehemaliger Referent beim BSI und zertifizierter ISO 27001 Auditor, Schöpfer des Prozesses ZAWAS. Ausgangslage: Anforderung der Digitalisierung.- Darstellung der Informationssicherheit und des Datenschutzes.- Der Prozess zur Auswahl angemessener Sicherungsmaßnahmen (ZAWAS).- Prüfung der Übertragbarkeit des Prozesses ZAWAS auf die Informationssicherheit.- Fazit.- Zusammenfassung
Introducing Blockchain with Lisp
Implement blockchain from scratch covering all the details with Racket, a general-purpose Lisp. You'll start by exploring what a blockchain is, so you have a solid foundation for the rest of the book. You'll then be ready to learn Racket before starting on your blockchain implementation. Once you have a working blockchain, you'll move onto extending it. The book's appendices provide supporting resources to help you in your blockchain projects.The recommended approach for the book is to follow along and write the code as it’s being explained instead of reading passively. This way you will get the most out of it. All of the source code is available for free download from GitHub.WHAT YOU WILL LEARN* Discover the Racket programming language and how to use it* Implement a blockchain from scratch using Lisp* Implement smart contracts and peer-to-peer support* Learn how to use macros to employ more general abstractionsWHO THIS BOOK IS FORNovices that have at least some experience with programming, as well as some basic working experience with computers. The book also assumes some experience with high school mathematics, such as functions.Boro Sitnikovski has over ten years of experience working professionally as a software engineer. He started programming with assembly on an Intel x86 at the age of ten. While in high school, he won several prizes in competitive programming, varying from 4th, 3rd, and 1st place. He is an informatics graduate - his bachelor’s thesis was titled “Programming in Haskell using algebraic data structures”, and his master’s thesis was titled “Formal verification of Instruction Sets in Virtual Machines”. He has also published a few papers on software verification. Other research interests of his include programming languages, mathematics, logic, algorithms, and writing correct software. He is a strong believer in the open-source philosophy and contributes to various open-source projects. In his spare time, he enjoys some time off with his family.1: Introduction to Blockchain2: Racket Programming Language3: Blockchain Implementation4: Extending the BlockchainConclusionFurther ReadingAppendix A: Macros
Scrum Master 2.0
Das nächste Level - Neuerscheinung in 04/2021!Dieses Buch ist für Scrum Master geschrieben, die festgestellt haben, dass ihnen die Theorie von Scrum alleine nicht weiterhilft. Denn wir arbeiten mit und für ein Team von Menschen, die ihre Schwächen, Stärken und Eigenheiten haben. Und da ist der offizielle Scrum Guide nur ein kleiner Teil der tatsächlichen Arbeitsinhalte. Hier setzt das Buch »Scrum Master 2.0« an: Nach den theoretischen Grundlagen zu diesem agilen Framework geht es um die Arbeit mit dem Team, um die tägliche Gestaltung des Scrum Master-Alltags, seine Vorgehensweisen, seine Tools, seine Interventionen. Scrum Master 2.0 startet da, wo der Scrum Guide endet.Jedes Kapitel konzentriert sich auf einen anderen Praxisbereich. Angesprochen werden Themen wie Teamentwicklung und -motivation, agile Konzepte, Visualisierung, Stressprävention, Kommunikation, Coaching, Kontaktmanagement, agile Moderation und vieles mehr. Dieses Buch ist somit ein unerlässliches Handwerkszeug für jeden Scrum Master.Kenntnisse des Scrum Frameworks werden für dieses Buch vorausgesetzt. Alle Themen lassen sich einfach und effektiv in den Arbeitsalltag integrieren.Leseprobe (PDF-Link)
Neuronale Netze mit C# programmieren
Mit praktischen Beispielen für Machine Learning im Unternehmenseinsatz.Sie wollen neuronale Netze und Machine-Learning-Algorithmen mit C# entwickeln? Dann finden Sie in diesem Buch eine gut verständliche Einführung in die Grundlagen und es wird Ihnen gezeigt, wie Sie neuronale Netze und Machine-Learning-Algorithmen in Ihren eigenen Projekten praktisch einsetzen.Mithilfe von Beispielen erstellen und trainieren Sie Ihr erstes neuronales Netz zur vorausschauenden Wartung einer Produktionsmaschine.Im Praxisteil lernen Sie dann, wie Sie TensorFlow-Modelle in ML.NET benutzen oder Infer.NET direkt verwenden können. Des Weiteren nutzen Sie die Predictive- und Sentiment-Analyse, um sich mit Machine-Learning-Algorithmen vertraut zu machen.Alle im Buch vorgestellten Projekte sind in C# programmiert und stehen als Download zur Verfügung. Grundkenntnisse in C# werden für die Arbeit mit dem Buch vorausgesetzt. Alle Projekte lassen sich ohne größere Rechnerressourcen umsetzen.Daniel Basler arbeitet als Lead Developer und Softwarearchitekt. Seine Schwerpunkte liegen auf Cross-Platform-Apps, Android, JavaScript und Microsoft-Technologien. Er entwickelt u.a. Software für Regal- und Flächenlagersysteme sowie Anlagenvisualisierung und setzt in diesem Umfeld verstärkt Machine-Learning-Methoden ein. Darüber hinaus schreibt er regelmäßig Artikel für die Fachzeitschriften dotnetpro und web&mobile Developer.Leseprobe (PDF-Link)
Stochastic Approaches to Electron Transport in Micro- and Nanostructures
The book serves as a synergistic link between the development of mathematical models and the emergence of stochastic (Monte Carlo) methods applied for the simulation of current transport in electronic devices. Regarding the models, the historical evolution path, beginning from the classical charge carrier transport models for microelectronics to current quantum-based nanoelectronics, is explicatively followed. Accordingly, the solution methods are elucidated from the early phenomenological single particle algorithms applicable for stationary homogeneous physical conditions up to the complex algorithms required for quantum transport, based on particle generation and annihilation. The book fills the gap between monographs focusing on the development of the theory and the physical aspects of models, their application, and their solution methods and monographs dealing with the purely theoretical approaches for finding stochastic solutions of Fredholm integral equations. Part I Aspets of Electron Transport Modeling: 1. Concepts of Device Modeling.- 2. The Semiconductor Model: Fundamentals.- 3. Transport Theories in Phase Space.- 4. Monte Carlo Computing.- Part II Stochastic Algorithms for Boltzmann Transport: 5. Homogeneous Transport: Empirical Approach.- 6. Homogeneous Transport: Stochastic Approach.- 7. Small Signal Analysis.- 8. Inhomogeneous Stationary Transport.- 9. General Transport: Self-Consistent Mixed Problem.- 10. Event Biasing.- Part III Stochastic Algorithms for Quantum Transport: 11.Wigner Function Modeling.- 12. Evolution in a Quantum Wire.- 13. Hierarchy of Kinetic Models.- 14. Stationary Quantum Particle Attributes.- 15. Transient Quantum Particle Attributes.
PHP 8 Objects, Patterns, and Practice
Learn how to develop elegant and rock-solid systems using PHP, aided by three key elements: object fundamentals, design principles, and best practices. The 6th edition of this popular book has been fully updated for PHP 8, including attributes, constructor property promotion, new argument and return pseudo-types, and more. It also covers many features new since the last edition including typed properties, the null coalescing operator, and void return types. This book provides a solid grounding in PHP's support for objects, it builds on this foundation to instill core principles of software design and then covers the tools and practices needed to develop, test, and deploy robust code.PHP 8 Objects, Patterns, and Practice begins by covering PHP's object-oriented features. It introduces key topics including class declarations, inheritance, and reflection. The next section is devoted to design patterns. It explains the principles that make patterns powerful. You’ll cover many of the classic design patterns including enterprise and database patterns. The last segment of the book covers the tools and practices that can help turn great code into a successful project. The section shows how to manage multiple developers and releases with git, and how to manage builds and dependencies with Composer. It also explores strategies for automated testing and continuous integration.After reading and using this book, you will have mastered object-oriented enhancements, design patterns, and the essential development tools available for PHP 8.WHAT YOU WILL LEARN* Work with object fundamentals: write classes and methods, instantiate objects, and create powerful class hierarchies using inheritanceMaster advanced object-oriented features, including static methods and properties, managing error conditions with exceptions, and creating abstract classes and interfaces * Understand and use design principles to deploy objects and classes effectively in your projects* Discover a set of powerful patterns that you can implement in your own projects* Guarantee a successful project including unit testing; version control and build, installation, and package management; and continuous integrationWHO THIS BOOK IS FORAnyone with at least a basic knowledge of PHP who wants to use its object-oriented features in their projects. It is also for PHP coders who want to learn about the practices and tools (version control, testing, continuous integration, etc) that can make projects safe, elegant and stable.MATT ZANDSTRA has worked as a web programmer, consultant, and writer for over two decades. He is the author of SAMS Teach Yourself PHP in 24 Hours (three editions) and is a contributor to DHTML Unleashed. He has written articles for Linux Magazine, Zend, IBM DeveloperWorks, and php|architect Magazine, among others. Matt was a senior developer/tech lead at Yahoo and API tech lead at LoveCrafts. Matt works as a consultant advising companies on their architectures and system management, and also develops systems primarily with PHP, and Java. Matt also writes fiction.Part I. Objects.-1. PHP: Design and Management.-2. PHP and Objects.-3. Object Basics.-4. Advanced Features.-5. Object Tools.-6. Objects and Design.-Part II. Patterns.-7. What Are Design Patterns? Why Use Them?.-8. Some Pattern Principles.-9. Generating Objects.-10. Patterns for Flexible Object Programming.-11. Performing and Representing Tasks.-12. Enterprise Patterns.-13. Database Patterns.-Part III. Practice.-14. Good (and Bad) Practice.-15. PHP Standards.-16. PHP Using and Creating Components with Composer.-17. Version Control with Git.-18. Testing.-19. Automated Build with Phing.-20. Vagrant.-21. Continuous Integration.-22. Objects, Patterns, and Practice.-23. App A: Bibliography.-24. App B: A Simple Parser.
Visualizing Data in R 4
Master the syntax for working with R’s plotting functions in graphics and stats in this easy reference to formatting plots. The approach in Visualizing Data in R 4 toward the application of formatting in ggplot() will follow the structure of the formatting used by the plotting functions in graphics and stats. This book will take advantage of the new features added to R 4 where appropriate including a refreshed color palette for charts, Cairo graphics with more fonts/symbols, and improved performance from grid graphics including ggplot 2 rendering speed.Visualizing Data in R 4 starts with an introduction and then is split into two parts and six appendices. Part I covers the function plot() and the ancillary functions you can use with plot(). You’ll also see the functions par() and layout(), providing for multiple plots on a page. Part II goes over the basics of using the functions qplot() and ggplot() in the package ggplot2. The default plots generated by the functions qplot() and ggplot() give more sophisticated-looking plots than the default plots done by plot() and are easier to use, but the function plot() is more flexible. Both plot() and ggplot() allow for many layers to a plot.The six appendices will cover plots for contingency tables, plots for continuous variables, plots for data with a limited number of values, functions that generate multiple plots, plots for time series analysis, and some miscellaneous plots. Some of the functions that will be in the appendices include functions that generate histograms, bar charts, pie charts, box plots, and heatmaps.WHAT YOU WILL LEARN* Use R to create informative graphics* Master plot(), qplot(), and ggplot()* Discover the canned graphics functions in stats and graphicsFormat plots generated by plot() and ggplot()WHO THIS BOOK IS FORThose in data science who use R. Some prior experience with R or data science is recommended.Margot Tollefson, PhD is a semi-retired freelance statistician, with her own consulting business, Vanward Statistics. She received her PhD in statistics from Iowa State University and has many years of experience applying R to statistical research problems. Dr. Tollefson has chosen to write this book because she often creates graphics using R and would like to share her knowledge and experience. Her professional blog is on WordPress at vanwardstat. Social media: @vanstat1) Introduction: plot(), qplot(), and ggplot(), Plus Somea) plot() – arguments, ancillary functions, and methods; par() and layout()b) qplot() and ggplot() – aesthetics, geometries, and other useful functionsc) other plotting functions in graphics and statsPart I. An Overview of plot()2) The plot() Functiona) what the function is and how the function worksb) will use method .xy for example3) The Arguments to plot()a) Type of plot, axis labels, plot titles, display formatb) Plotting characters, character size, fonts, colors, line styles and widths4) Ancillary Functions to use with plot()a) axis(), box(), clip(), grid(), legend(), mtext(), rug()b) abline(), contour(), curve(), lines(), polypath()c) arrows(), image(), points(), polygon(), rect(), segments(), symbols(), text()d) axTicks(), identify(), locator(), pch(), strwidth(),5) The Methods for plot()a) What are methods?b) Methods in the graphics packagec) Methods in the stats package6) How to Use the Functions par() and layout()a) What par() doesb) Arguments specific to par()c) Multiple plotsPart II. A look at the ggplot2 Package7) The Functions qplot(), ggplot(), and the Specialized Notation in ggplot2a) Working with qplot()b) The ggplot() functionc) Specialized notation8) Themesa) The theme() functionb) The element_*() functions9) Aesthetics and Geometriesa) The aes() functionb) The geom_*() functions10) Controlling the Appearancea) The annotate_*() functionsb) The coord_*() functionsc) The facet_*() functionsd) The guide_*() functionse) The position_*() functionsf) The scale_*() functionsg) The stat_*() functionsAppendix I. Plots for Contingency TablesAppendix II. Plots for Continuous VariablesAppendix III. Plots for Data with a Limited Number of ValuesAppendix IV. Functions that Generate Multiple PlotsAppendix V. Plots for Time SeriesAppendix VI. Miscellaneous Plots
Microsoft 365 Compliance
Use the information presented in this book to implement an end-to-end compliance program in your organization using Microsoft 365 tools. You will learn about the solutions available in the Microsoft 365 Compliance Center, including best practices and common pitfalls. IT professionals will benefit from the author’s approach of introducing each topic within a practical business context and scenarios behind the “whys” of compliance. Compliance managers will understand how to implement their requirements in Microsoft 365.Compliance and risk management is often a board- or CEO-level issue. The risks of hefty fines and bad PR from non-compliance are severe. IT is usually responsible for implementing compliance controls and for working with compliance and legal officers to manage the day-to-day risk in an organization.After reading Microsoft 365 Compliance, you will be prepared to have a well-informed conversation with your compliance and legal officers to determine how to work together to identify specific compliance requirements for your organization. You will be able to implement those requirements yourself using Microsoft 365 features. Compliance and legal officers will understand how to communicate their technical requirements to IT.Author Erica Toelle helps you build a solid compliance foundation by teaching you about topics such as information protection, retention, records management, eDiscovery, auditing, compliance with common regulations, managing insider risks, supervising communications, data loss prevention, protecting sensitive information, and using machine learning to reduce compliance costs.What You Will Learn* Understand typical business scenarios and requirements for a Microsoft 365 compliance program* Fulfill these compliance scenarios and requirements using out of the box Microsoft 365 solutions and functionality* Ensure that your Microsoft 365 implementation meets standard compliance regulations, such as GDPR and ISO/IEC 27001:2013* Enlist best practices and things to know when implementing Microsoft 365 solutions* Comprehend required Microsoft licensing and how to implement a least permissions model for each compliance solution* Explore what you can accomplish using the compliance center user interface, without custom scripting or codeThis book is for IT professionals, security managers, compliance officers, risk managers, internal audit, records managers, CIOs, and anyone who would like to learn more about Microsoft 365 compliance.·ERICA TOELLE is a Microsoft MVP in Office Apps and Services. She is an internationally recognized speaker on compliance, Office 365, and SharePoint. Erica has been working with customers to deploy these solutions since 2004 and has been hired as an expert by more than 75 Fortune 500 companies and several Microsoft product teams. Erica is a top 15 International SharePoint Influencer from 2016-present.CHAPTER 1: An Introduction to Compliance in Microsoft 365CHAPTER 2: Compliance ManagerCHAPTER 3: Data ClassificationCHAPTER 4: Data ConnectorsCHAPTER 5: Information ProtectionCHAPTER 6: Data Loss Prevention PoliciesCHAPTER 7: Information BarriersCHAPTER 8: Information GovernanceCHAPTER 9: Records ManagementCHAPTER 10: Insider Risk ManagementCHAPTER 11: Communication ComplianceCHAPTER 12: CONTENT SEARCHChapter 13: Core eDiscoveryChapter 14: Advanced eDiscoveryChapter 15: Data InvestigationsChapter 16: The Unified Audit Log
Big Data Analytics
Mit diesem Herausgeberwerk führen die Autoren den Begriff „Big Data Analytics“ ein und geben Fallstudien aus unterschiedlichen Anwendungsgebieten. Unter Big Data Analytics wird das Aufbereiten, Analysieren und Interpretieren von großen, oft heterogenen Datenbeständen verstanden, mit dem Ziel, Muster und Zusammenhänge in den Daten aufzudecken und Entscheidungsgrundlagen für wissenschaftliche, betriebliche oder gesellschaftliche Fragestellungen zu erhalten.Nebst den theoretischen Grundlagen widmet sich das Herausgeberwerk der Vielfalt verschiedener Anwendungsmöglichkeiten. Fallbeispiele geben Einblick in die Anwendung von Big Data Analytics und dessen Nutzenpotenziale.Das Werk richtet sich gleichermaßen an Studierende, Fachleute aller Fachrichtungen als auch an interessierte Anwender. Es hilft den Leserinnen und Leser, die Bedeutungsvielfalt des Begriffs Big Data Analytics zu verstehen und verschiedene Einsatzmöglichkeiten im eigenen Umfeld zu erkennen und zu bewerten.SARA D'ONOFRIO ist IT Business Partner Manager eines der größten Detailhandelsunternehmen der Schweiz, Autorin und Herausgeberin der Zeitschrift HMD - Praxis der Wirtschaftsinformatik bei Springer, Gastdozentin an Hochschulen und Mitglied der Stiftung FMsquare, welche die Anwendung von Fuzzy-Logik zur Lösung von wirtschaftlichen und sozialen Problemen fördert. Sie hat Betriebswirtschaft und Wirtschaftsinformatik studiert und in Informatik promoviert.ANDREAS MEIER hat Musik an der Musikakademie in Wien und Mathematik an der Eidgenössischen Technischen Hochschule (ETH) in Zürich studiert, wo er doktorierte und habilitierte. Er arbeitete bei IBM Schweiz, gehörte zum Direktionskader der internationalen Bank SBV und trug Mitverantwortung in der Geschäftsleitung des Versicherers CSS. In der Forschung war er am IBM Research Lab in Kalifornien tätig und gründete das Research Center Fuzzy Management Methods an der Universität Fribourg in der Schweiz.Grundlagen - Textanalyse - Machine Learning - Prädiktive Modelle - Trendforschung
Robotic Process Automation using UiPath StudioX
Learn about Robotic Processing Automation (RPA) and how to build bots using UiPath. This book uses hands-on examples to explain the basics of UiPath and then walks you through real-world prototypes for testing your knowledge.Organizations around the world are implementing RPA in some capacity, and there is a shortage of RPA developers in the market. Analysts predict that the RPA market size will be worth $4 Billion by 2025. With UiPath as one of the three major players in the RPA market, professionals and students can use this book to get ahead of the curve.This book helps you kick-start your automation journey with a special focus on one of the most popular RPA tools: UiPath. Robotic Process Automation using UiPath explains in detail the various features and functionalities of the RPA platform including development, debugging, and error handling.WHAT YOU'LL LEARN* Create robots from scratch, using one of the market leaders in RPA* Develop automation apps and deploy them to all the computers in your department* Build, test and perform enterprise automation tasks with UiPath* Understand the key building blocks and components of UiPath * Apply UiPath programming techniques to deploy robot configurations* Review email Automation* Automate Excel and PDF interactionsWHO THIS BOOK IS FORRPA developers and business users alike, bringing the power and skill set of automation to anyone interested in citizen-led development, specifically UiPath StudioX. The simple exercises and no-code platform require no prior programming or RPA knowledge to follow along with this beginner's guide.ADEEL JAVED is an intelligent automation architect, an author, and a speaker. He helps organizations automate work using low-code, business process management (BPM), robotic process automation (RPA), analytics, integrations and ML. He loves exploring new technologies and writing about them. He published his first book, "Building Arduino Projects for the Internet of Things", with Apress back in 2015. He shares his thoughts on various technology trends on his personal blog (adeeljaved.com).ANUM SUNDRANI is a business systems analyst and technology enthusiast who specializes in Business Process Management and Robotic Process Automation. Anum is a Certified Appian Analyst, Tableau Author, Six Sigma Green Belt and Scrum Master, alongside her several trainings in the areas of RPA development and the automation delivery lifecycle. She has an inquisitive eye for simplifying complex business processes and has focused on implementing automation solutions for business users since 2017.NADIA MALIK is a Presales Engineer with a background in software development. She has started her journey as a Software Engineer at IBM developing Cloud storage applications and then joining the UiPath rocket-ship in June of 2018 helping customers design, implement, and provide training in robotics process automation. Today she continues to evangelize RPA and mentor young women in STEM.SIDNEY MADISON PRESCOTT is a senior technology leader, keynote speaker, and robotics evangelist specializing in the creation of Robotic Process Automation Centers of Excellence for Fortune 500 companies. Sidney currently heads up the Global Intelligent Automation initiative at music streaming powerhouse Spotify. In addition to her enterprise technology expertise, Sidney is an executive board member for three global non-profit organizations, where she contributes valuable automation insights to enhance overall program objectives. To round out her career accolades, Sidney was also named a global recipient of the 2020 Top 50 Technology Visionaries award.Part I: IntroductionChapter 1. Robotic Process Automation Overview* Overview* Benefits* Market trends* Major vendors* Real-life use cases* Attended/unattendedChapter 2. UiPath StudioX Overview* Download* Install* Interface OverviewPart II: Activities – Your Building BlocksGoal of this section is to list down each activity under these tiles in UiPath StudioX, provide a brief description of what that activity does, screenshots of different configurations, quick examples. Essentially make this as the ultimate reference material.Chapter 3. Common ActivitiesChapter 4. UI AutomationChapter 5. Outlook AutomationChapter 6. Word AutomationChapter 7. Excel AutomationChapter 8. CSV AutomationChapter 9. File AutomationPart III: Building PrototypesGoal of this section is to build couple of real-life prototypes that uses knowledge acquired in prior sections. We have already developed two sample target applications, one browser-based, the other windows-based.Chapter 10. Real-life prototype 1 (Inventory Management)* Outlook Automation* CSV Automation* UI Automation (Browser)* File AutomationChapter 11. Real-life prototype 2 (Order Management)* UI Automation (App)* Excel Automation* Word Automation* File AutomationChapter 12. Real-life prototype 3 (Excel Management)* Excel AutomationPart IV: Scaling UpGoal of this section/chapter is to help people think about next steps. Most organizations have difficulty scaling up the concepts of citizen development.Chapter 13. Scaling RPA – high-level ideas
Deep Reinforcement Learning with Python
Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics, healthcare, finance, and many more. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding exercise.You'll begin by reviewing the Markov decision processes, Bellman equations, and dynamic programming that form the core concepts and foundation of deep reinforcement learning. Next, you'll study model-free learning followed by function approximation using neural networks and deep learning. This is followed by various deep reinforcement learning algorithms such as deep q-networks, various flavors of actor-critic methods, and other policy-based methods.You'll also look at exploration vs exploitation dilemma, a key consideration in reinforcement learning algorithms, along with Monte Carlo tree search (MCTS), which played a key role in the success of AlphaGo. The final chapters conclude with deep reinforcement learning implementation using popular deep learning frameworks such as TensorFlow and PyTorch. In the end, you'll understand deep reinforcement learning along with deep q networks and policy gradient models implementation with TensorFlow, PyTorch, and Open AI Gym.WHAT YOU'LL LEARN* Examine deep reinforcement learning * Implement deep learning algorithms using OpenAI’s Gym environment* Code your own game playing agents for Atari using actor-critic algorithms* Apply best practices for model building and algorithm training WHO THIS BOOK IS FORMachine learning developers and architects who want to stay ahead of the curve in the field of AI and deep learning.Nimish is a passionate technical leader who brings to table extreme focus on use of technology for solving customer problems. He has over 25 years of work experience in the Software and Consulting. Nimish has held leadership roles with P&L responsibilities at PwC, IBM and Oracle. In 2006 he set out on his entrepreneurial journey in Software consulting at SOAIS with offices in Boston, Chicago and Bangalore. Today the firm provides Automation and Digital Transformation services to Fortune 100 companies helping them make the transition from on-premise applications to the cloud.He is also an angel investor in the space of AI and Automation driven startups. He has co-founded Paybooks, a SaaS HR and Payroll platform for Indian market. He has also cofounded a Boston based startup which offers ZipperAgent and ZipperHQ, a suite of AI driven workflow and video marketing automation platforms. He currently hold the position as CTO and Chief Data Scientist for both these platforms.Nimish has an MBA from Indian Institute of Management in Ahmedabad, India and a BS in Electrical Engineering from Indian Institute of Technology in Kanpur, India. He also holds multiple certifications in AI and Deep Learning.Chapter 1: Introduction to Deep Reinforcement LearningChapter Goal: Introduce the reader to field of reinforcement learning and setting the context of what they will learn in rest of the bookSub -Topics1. Deep reinforcement learning2. Examples and case studies3. Types of algorithms with mind-map4. Libraries and environment setup5. SummaryChapter 2: Markov Decision ProcessesChapter Goal: Help the reader understand models, foundations on which all algorithms are built.Sub - Topics1. Agent and environment2. Rewards3. Markov reward and decision processes4. Policies and value functions5. Bellman equationsChapter 3: Model Based AlgorithmsChapter Goal: Introduce reader to dynamic programming and related algorithmsSub - Topics:1. Introduction to OpenAI Gym environment2. Policy evaluation/prediction3. Policy iteration and improvement4. Generalised policy iteration5. Value iterationChapter 4: Model Free ApproachesChapter Goal: Introduce Reader to model free methods which form the basis for majority of current solutionsSub - Topics:1. Prediction and control with Monte Carlo methods2. Exploration vs exploitation3. TD learning methods4. TD control5. On policy learning using SARSA6. Off policy learning using q-learningChapter 5: Function ApproximationChapter Goal: Help readers understand value function approximation and Deep Learning use in Reinforcement Learning.1. Limitations to tabular methods studied so far2. Value function approximation3. Linear methods and features used4. Non linear function approximation using deep LearningChapter 6: Deep Q-LearningChapter Goal: Help readers understand core use of deep learning in reinforcement learning. Deep q learning and many of its variants are introduced here with in depth code exercises.1. Deep q-networks (DQN)2. Issues in Naive DQN3. Introduce experience replay and target networks4. Double q-learning (DDQN)5. Duelling DQN6. Categorical 51-atom DQN (C51)7. Quantile regression DQN (QR-DQN)8. Hindsight experience replay (HER)Chapter 7: Policy Gradient AlgorithmsChapter Goal: Introduce reader to concept of policy gradients and related theory. Gain in depth knowledge of common policy gradient methods through hands-on exercises1. Policy gradient approach and its advantages2. The policy gradient theorem3. REINFORCE algorithm4. REINFORCE with baseline5. Actor-critic methods6. Advantage actor critic (A2C/A3C)7. Proximal policy optimization (PPO)8. Trust region policy optimization (TRPO)Chapter 8: Combining Policy Gradients and Q-LearningChapter Goal: Introduce reader to the trade offs between two approaches ways to connect together the two seemingly dissimilar approaches. Gain in depth knowledge of some land mark approaches.1. Tradeoff between policy gradients and q-learning2. The connection3. Deep deterministic policy gradient (DDPG)4. Twin delayed DDPG (TD3)5. Soft actor critic (SAC)Chapter 9: Integrated Learning and PlanningChapter Goal: Introduce reader to the scalable approaches which are sample efficient for scalable problems.1. Model based reinforcement learning2. Dyna and its variants3. Guided policy search4. Monte Carlo tree search (MCTS)5. AlphaGoChapter 10: Further Exploration and Next StepsChapter Goal: With the backdrop of having gone through most of the popular algorithms, readers are now introduced again to exploration vs exploitation dilemma, central to reinforcement learning.1. Multi arm bandits2. Upper confidence bound3. Thompson sampling
Practical C++20 Financial Programming
Apply C++ to programming problems in the financial industry using this hands-on book, updated for C++20. It explains those aspects of the language that are more frequently used in writing financial software, including the Standard Template Library (STL), templates, and various numerical libraries. Practical C++20 Financial Programming also describes many of the important problems in financial engineering that are part of the day-to-day work of financial programmers in large investment banks and hedge funds. The author has extensive experience in the New York City financial industry that is now distilled into this handy guide.Focus is on providing working solutions for common programming problems. Examples are plentiful and provide value in the form of ready-to-use solutions that you can immediately apply in your day-to-day work. You’ll see examples of matrix manipulations, curve fitting, histogram generation, numerical integration, and differential equation analysis, and you’ll learn how all these techniques can be applied to some of the most common areas of financial software development.These areas include performance price forecasting, optimizing investment portfolios, and more. The book style is quick and to-the-point, delivering a refreshing view of what one needs to master in order to thrive as a C++ programmer in the financial industry.WHAT YOU WILL LEARN* Cover aspects of C++ especially relevant to financial programmingWrite working solutions to commonly encountered problems in finance * Design efficient, numerical classes for use in finance, as well as to use those classes provided by Boost and other librariesWHO THIS BOOK IS FORThose who are new to programming for financial applications using C++, but should have some previous experience with C++.CARLOS OLIVEIRA works in the area of quantitative finance, with more than ten years of experience in creating scientific and financial models in C++. During his career, Carlos has developed several large-scale applications for financial companies such as Bloomberg L.P. and F-Squared Investments. Carlos Oliveira obtained a PhD in operations research and systems engineering from the University of Florida, an MSc in computer science from UFC (Brazil), and a BSc in computer science from UECE (Brazil). He has also performed academic research in the field of combinatorial optimization, with applications in diverse areas such as finance, telecommunications, computational biology, and logistics. Carlos has written more than 30 academic papers on optimization, and authored three books, including Options and Derivatives Programming in C++20 (Apress, 2020).1. The Fixed-Income Market2. The Equities Market3. C++ Programming Techniques in Finance4. Common Libraries for Financial Code5. Designing Numerical Classes6. Plotting Financial Data7. Linear Algebra8. Interpolation9. Calculating Roots of Equations10. Numerical Integration11. Solving Partial Differential Equations12. Algorithm Optimization13. Portfolio Optimization14. Monte Carlo Methods for Equity markets15. Extending Financial Libraries16. C++ with R and Octave17. MultithreadingA. Appendix A: C++20 Features
Beginning Machine Learning in the Browser
Apply Artificial Intelligence techniques in the browser or on resource constrained computing devices. Machine learning (ML) can be an intimidating subject until you know the essentials and for what applications it works. This book takes advantage of the intricacies of the ML processes by using a simple, flexible and portable programming language such as JavaScript to work with more approachable, fundamental coding ideas.Using JavaScript programming features along with standard libraries, you'll first learn to design and develop interactive graphics applications. Then move further into neural systems and human pose estimation strategies. For training and deploying your ML models in the browser, TensorFlow.js libraries will be emphasized.After conquering the fundamentals, you'll dig into the wilderness of ML. Employ the ML and Processing (P5) libraries for Human Gait analysis. Building up Gait recognition with themes, you'll come to understand a variety of ML implementation issues. For example, you’ll learn about the classification of normal and abnormal Gait patterns.With Beginning Machine Learning in the Browser, you’ll be on your way to becoming an experienced Machine Learning developer.WHAT YOU’LL LEARN* Work with ML models, calculations, and information gathering* Implement TensorFlow.js libraries for ML models* Perform Human Gait Analysis using ML techniques in the browserWHO THIS BOOK IS FORComputer science students and research scholars, and novice programmers/web developers in the domain of Internet TechnologiesNAGENDER KUMAR SURYADEVARA received his Ph.D. from the School of Engineering and Advanced Technology, Massey University, New Zealand, in 2014. He has authored two books and over 45 publications in different international journals, conferences, and book chapters. His research interests lie in the domains of wireless sensor networks, Internet of Things technologies, and time-series data mining.Chapter 1: What is Machine Learning (ML)?Basics of Java Script (JS)Programming in the browser using Java ScriptGraphics and Interactive processing in the browser using Java Script librariesGetting started with P5.JS and ML5.JSReferencesChapter 2: Human Pose Estimation in the BrowserBrowser based data processingPosenet vs Openpose modelsHuman pose estimation using ML5.PosenetInputs, Outputs and Data structures of Posenet modelReferencesChapter 3: Human Pose ClassificationClassification techniques using ML Neural Network in the browserHuman Pose classification based on the outputs of Posenet modelConsideration of poses using Confidence scores of Posenet modelStorage of data using JSON formats related to the outputs of Posenet modelReferencesChapter 4: Gait AnalysisNormal vs Abnormal Gait patternsDetermination of Gait patterns using threshold values of the modelsUser Interface design and development for monitoring of Gait patternsReal-Time data visualization of the Gait patterns on the browserReferencesChapter 5: Future Possible Applications of Key Concepts
MongoDB Performance Tuning
Use this fast and complete guide to optimize the performance of MongoDB databases and the applications that depend on them. You will be able to turbo-charge the performance of your MongoDB applications to provide a better experience for your users, reduce your running costs, and avoid application growing pains. MongoDB is the world’s most popular document database and the foundation for thousands of mission-critical applications. This book helps you get the best possible performance from MongoDB.MONGODB PERFORMANCE TUNING takes a methodical and comprehensive approach to performance tuning that begins with application and schema design and goes on to cover optimization of code at all levels of an application. The book also explains how to configure MongoDB hardware and cluster configuration for optimal performance. The systematic approach in the book helps you treat the true causes of performance issues and get the best return on your tuning investment. Even when you’re under pressure and don’t know where to begin, simply follow the method in this book to set things right and get your MongoDB performance back on track.WHAT YOU WILL LEARN* Apply a methodical approach to MongoDB performance tuning* Understand how to design an efficient MongoDB application* Optimize MongoDB document design and indexing strategies* Tune MongoDB queries, aggregation pipelines, and transactions* Optimize MongoDB server resources: CPU, memory, disk* Configure MongoDB Replica sets and Sharded clusters for optimal performanceWHO THIS BOOK IS FORDevelopers and administrators of high-performance MongoDB applications who want to be sure they are getting the best possible performance from their MongoDB system. For developers who wish to create applications that are fast, scalable, and cost-effective. For administrators who want to optimize their MongoDB server and hardware configuration.GUY HARRISON is CTO at ProvenDB, a partner at Toba Capital, and a software professional with more than 20 years of experience in database design, development, administration, and optimization. He is the author of Next Generation Databases (Apress) and other books and articles on database technology. He is a MongoDB certified DBA and developer, and an Oracle ACE.MICHAEL HARRISON is the lead developer at ProvenDB, working intimately with MongoDB from both an application and database perspective. He is a co-author of The MongoDB Workshop as well as senior developer of DBKoda, an open-source development environment for MongoDB.PART I. METHODS AND TOOLS1. Methodical Performance Tuning2. MongoDB Architecture and Concepts3. Tools of the TradePART II. APPLICATION AND DATABASE DESIGN4. Schema Modelling5. IndexingPART III. TUNING MONGODB CODE6. Query Tuning7. Tuning Aggregation Pipelines8. Inserts, Updates and Deletes9. Transactions10. Server MonitoringPART IV. SERVER TUNING11. Memory Tuning12. Disk IO13. Replica Sets and Atlas14. Sharding
Automated Unit Testing with ABAP
Write automated unit tests for the ABAP language. This book teaches programmers using simple examples and metaphors and explains the underlying concepts of writing effective automated unit tests. Many, if not most, ABAP programmers learned their programming and testing skills before the ABAP development environment provided an automated unit testing facility.AUTOMATED UNIT TESTING WITH ABAP: A PRACTICAL APPROACH offers hope and salvation to ABAP programmers who continue to toil with antiquated manual unit testing processes, taking them by the hand and lifting them out of that dungeon of despair with a modern and proven alternative. It begins by explaining how the xUnit family of automated testing frameworks provides a quick and effective means of insuring high-quality software. It then focuses on the ABAP Unit Testing Facility, the xUnit framework applicable specifically to the ABAP language, showing how it can be used to bring ABAP applications underautomated testing control, from old legacy applications to those newly written.Whereas xUnit testing has been widely accepted with developers writing in many other programming languages, it is an unfortunate fact in the ABAP community that many programmers still are unfamiliar with xUnit concepts and do not know how to begin implementing automated unit testing into their development process. This book demonstrates how to refactor programs so they become designed for testability, showing how to use process encapsulation and test isolation to facilitate automated testing, including a thorough explanation of test-driven development and the use of test doubles. The book:* Shows how to write automated unit tests for ABAP* Instills ABAP programmers with the confidence to refactor poorly written code* Explains how an automated testing harness facilitates rapid software development* Teaches how to utilize test-driven development (TDD) withABAP* Offers advice and tips on the best ways to write automated unit testsWHAT YOU WILL LEARN* Become familiar with the xUnit approach to testing* Know the ABAP statements that interfere with running automated unit tests and how to accommodate them* Understand what it means to isolate code for testing and how this is achieved* Gain the confidence to refactor poorly written code* Make ABAP programs designed for testability* Reap the benefits of spending less time manually unit testing ABAP programs* Use test-driven development (TDD) with ABAP programming* Use configurable test doubles in ABAPWHO THIS BOOK IS FORABAP programmers who remain unfamiliar with the automated unit testing facility and those who already use it butwant to improve their skill writing and using automated tests. The book addresses the reluctance and trepidation felt by procedural ABAP programmers who need to know some object-oriented concepts to use this facility, expands their horizons, and helps them step through the doorway leading to a different approach to program design. JAMES E. MCDONOUGH received a degree in music education from Trenton State College. After teaching music for only two years in the New Jersey public school system, he spent the past 38 years as a computer programmer while also maintaining an active presence as a freelance jazz bassist between New York and Philadelphia. Having switched from mainframe programming to ABAP in 1997, he now works as a contract ABAP programmer designing and writing ABAP programs on a daily basis. An advocate of using the object-oriented programming features available with ABAP, he has been teaching private ABAP education courses over the past few years, where his background in education enables him to present and explain complicated concepts in a way that makes sense to beginners.Chapter 1: Introduction.- Chapter 2: Preparing to Take the First Step.- Chapter 3: Software Quality.- Chapter 4: The Origins of Automated Unit Testing.- Chapter 5: Automated Unit Testing with ABAP.- Chapter 6: Rudiments.- Chapter 7: Design for Testability.- Chapter 8: Test Doubles.- Chapter 9: Service Locator.- Chapter 10: Leveraging the Service Locator.- Chapter 11: Test-Driven Development.- Chapter 12: Configurable Test Doubles.- Chapter 13: Obtaining Code Coverage Information Through ABAP Unit Testing.- Chapter 14: Cultivating Good Test Writing Skills.- Chapter 15: Welcome to Autropolis.- Appendix A: Requirements Documentation and ABAP Exercise Programs.- Appendix B: Answers to Chapter Quizzes.- Appendix C: Concepts Associated with Defining Local Test Classes.-
Set Up and Manage Your Virtual Private Server
The need for every professional to have a solid presence on the Internet is more important than ever before. Having a presence beyond an email account, such as a custom web page or web application, usually requires a clumsy assortment of outside services or hiring a dedicated administrator. Thus it is more sensible for the average professional to become adept at managing their own private server.In Set Up and Manage Your Virtual Private Server, author Jon Westfall expertly designs interesting, understandable lessons for professionals such as teachers, doctors, lawyers, and more to deploy their own virtual private server. He walks you through choosing the right service and customizing it for your specific business or personal needs, and does this with great ease while instilling invaluable knowledge. Basics such as setting up users, managing security and firewalls, installing and updating software, and troubleshooting by reviewing log files, backing up data, and so much more.Set Up and Manage Your Virtual Private Server equips you with the power of knowledge to set your web presence apart from the rest. You now have complete control over your virtual brand that is your own—separate from any employer or affiliate. Your career mobility is in your hands with the ability to run your own private server at your fingertips. The digital era centers this technical literacy and independence as a critical skillset.WHAT YOU WILL LEARN* Understand basic server terminology and the way servers operate and are networked together* See how software is used on a server and its role (for example, Linux, Apache, MySQL, PHP, and so on)* Get comfortable with the basic command-line operation of a virtual private server to set up users, manage security and firewalls, install software, update software, and troubleshoot by reviewing log files* Store and back up important information* Identify, analyze, and deploy open-source software products that can enhance productivityWHO THIS BOOK IS FORNon-tech professionals, individuals who have an established professional career, looking to understand more about how to set up and manage a private server. Jon Westfall is an award-winning professor, published author, and practicing cognitive scientist. He teaches a variety of courses in psychology, from introduction to psychology to upper-level seminars. His current research focuses on the variables that influence economic and consumer finance decisions, and the retention of college students. With applications to both psychology and marketing, his work finds an intersection between basic and applied science. His current appointment is as an assistant professor of psychology, coordinator of the first year seminar program, and coordinator of the Okra Scholars program at Delta State University. Previously he was a visiting assistant professor at Centenary College of Louisiana, and the associate director for research and technology at the Center for Decision Sciences, a center within Columbia Business School at Columbia University in New York City. He now maintains a role with Columbia as a research affiliate and technology consultant.In addition to his research, Dr. Westfall has career ties in information technology, where he has worked as a consultant since 1997, founding his own firm, Bug Jr. Systems. As a consultant he has developed custom software solutions (including native Windows 32 applications, Windows .NET applications, Windows Phone 7 and Android mobile applications, as well as ASP, ASP.NET, and PHP web applications). He has also served as a senior network and systems architect and administrator (on both Windows and Unix networks, and hybrids) and has also been recognized as a Microsoft Most Valuable Professional (MVP) 2008 – 2012. He has authored several books, and presented at academic as well as technology conferences and gatherings.Chapter 1: What is a Virtual Private Server?Chapter Goal: Go over basic terminology of how the internet operates, how servers run, and how virtualization allows individuals to have their own server for a very small cost per month.• How does the magic happen?o How does a webpage appear on my screen? How does email route through the internet to someone else? How do domain names work?• What options does someone have if they want to get into this?o Who provides services (data centers, co-locations, virtual servers, cloud computing)o How much does it cost?o How much do I have to do?o How much time does it take?• Am I ready for this?o Do I have the necessary skills and time to learn skills I need?o Am I OK with being my own system administrator?o Who do I call if I need help? Or can I call someone?Chapter 2: Selecting a VPS ProviderChapter Goal: Walk the reader through identifying and selecting a VPS provider.• How do I find a provider?o Low-end, High-end, Cloudo Trust and Reliability, what is an SLA?o Warning signs• Resources & Budgetingo What do I really need?o How much does it cost?o Extras that can cost money.• Setting up a New Accounto Security of your account.o Extras you may or may not need.o Terms of Serviceo Choosing your Linux distribution: CentOS or Debian (Throughout the book, commands for both CentOS 8 and Debian 10 will be provided).Chapter 3: Basic Linux Administration via Command-LineChapter Goal: Providing the basic commands to administer your server, finding files, and adding and configuring software.• Logging into your servero Shell accesso SSHo SFTPo Setting up your user account• Basic commandso Linux Directory Structureo Ls, cp, mv, and the most dangerous: rmo Finding fileso Su / sudo and file permissions.o Disk usage, memory usage, and overall server health commands.o How do I edit files: Vim and Nano• How your System Starts up and Shuts Downo Services, what they are and how to enable/disableo The right and wrong way to shutdown, and why it’s important.o Graphical user modes versus command-line.o Files that you might want to keep copies of.• How do I install software?o Package managers (apt / yum)o Compiling from Sourceo Updating / upgrading / removing softwareo Configuring software through configuration files.Chapter 4: Basic Linux Administration via GUI (Webmin)Chapter Goal: To provide a basic overview of the Open Source project “Webmin” for configuration of your server though a graphical interface.• Deciding if a GUI is needed or not. Pros and Cons• Downloading and installing Webmin• Setting up Webmin security, including SSL and 2 Factor authentication.• Delegating tasks to others using Webmin Users.• Basic walkthrough of the modules that you’ll need to access, with an eye on settings you don’t want to change.• Webmin’s Usermin module: GUI for users to access files, mail, databases, and more.Chapter 5: Basics of Linux SecurityChapter Goal: The basics of setting up security on your server, with a discussion of auditing and verifying files haven’t changed.• What is a firewall and how do I set it up?• How do I give some users access to administrative functions, but not all?• Advanced File Permissions, and more on users and groups.• SELinux• Auditing and log file management.Chapter 6: Basics of Backups and Version ControlChapter Goal: How to keep your files backed up and safe.• Backup Basics: What to back up, where to back it up, and how often to back up.• Backup Method 1: Gzipped Tar files and shell scripts.• Backup Method 2: Duplicati GUI• Simulated disaster recovery, and migration to a new server.Chapter 7: Basics of Server Software AdministrationChapter Goal: How to get the most common software up and running on your VPS, customizing it to be secure and reliable.• Web Server Basics (Apache 2)o Extending the Server with PHPo SSL certificates.• Database Server Basics (MySQL)• Mail Server Basics (Postfix)• DNS Server Basics (Bind)• Monitoring your Server (Nagios)Chapter 8: Installing an Open Source Software Product – WordpressChapter Goal: How to get a basic website up and running quickly using an open source content management system, Wordpress.• Do you need a full CMS or are your needs more basic?• Downloading and installing Wordpress• Configuring Wordpress to be secure.• Backing up Wordpress• Extending Wordpress with Plugins.Chapter 9: Administrators Weekly ChecklistChapter Goal: Describe concept of preventive maintenance – what one needs to do regularly to keep the server running smoothly.• Software update basics• Following mailing lists and security discussions.• Monitoring for potential security breaches.• Verifying backups.Chapter 10: Open Source Application PossibilitiesChapter Goal: Introduce the reader to software packages that will allow them to up their productivity by hosting their own content on their server. Basic installations will be covered, but not in-depth customization as was done in Chapter 8.• Moodle: Open Source Learning Management System• osTicket: Open Source Helpdesk / Issue Tracking.• YoURLS: Open Source URL Shortener• OpenVPN: Open Source VPN software• Odoo: Open Source CRM Software• LimeSurvey: Open Source Survey Software (Covered in my previous book, Practical R 4 – but less in-depth here)• Other possibilities, including writing
Der Mensch als Rohstoff
Gentechnik, Nanotechnik, Robotik, Künstliche Intelligenz. Welche Revolutionen stehen uns bevor und wie denken die großen Konzerne darüber? Mit welchen Gefahren ist zu rechnen, wie hat sich unser Leben bereits verändert und wohin führt diese Reise? Zur Beantwortung dieser Fragen wagt Christian Blasge einen Ausflug in die menschliche Psyche und untersucht dabei, inwieweit sich unsere Gesellschaft mittlerweile in einem Modus der vollständigen Konkurrenz befindet.Getrieben ist die Entwicklung durch die Stigmatisierung des Menschen als "Mängelwesen", das überwunden werden soll. Dazu dienen die Digitalisierung und Automatisierung menschlicher Arbeitskraft, deren Auswirkung auf den Arbeitsmarkt und den Menschen selbst untersucht werden. Viele der technologischen Neuerungen des beginnenden 21. Jahrhunderts haben einerseits neue Freiheiten mit sich gebracht, die andererseits zu Überforderung, Entwurzelung und Entfremdung führen können. Verbunden ist das Zeitalter der Digitalisierung aber auch mit dem Mythos, Probleme ließen sich durch Konsum lösen, gekoppelt mit dem Trend, sich (freiwillig oder unfreiwillig) zu dem Vermarkter einer Ware und gleichzeitig selbst zu einer Ware zu machen.Im Kontext von Künstlicher Intelligenz und fortschreitenden persönlicher Optimierung drängt sich die Frage auf: "Was ist der Mensch und darf er so bleiben, wie er ist?" Technik-Utopisten (alb)träumen von Maschinen mit Bewusstsein und von Superintelligenzen, die unsere Lebenswelt neu gestalten. Sie schwärmen von der Überwindung der menschlichen Biologie, der Abschaffung aller Krankheiten bis hin zur Unsterblichkeit; und sie bestehen auf der bestmöglichen genetischen Ausstattung für unsere Nachkommen.Das Buch endet mit der brisanten Debatte über den Trans- bzw. Posthumanismus. Eine (schöne?) neue Gesellschaft mit optimierten Menschen, autonomen Robotern und virtuellen Entitäten wird unsere Lebenswelt von Grund auf verändern. Daher bedarf es, so der Autor, dringend eines neuen Gesellschaftsvertrags, wie mit den Früchten des Fortschritts umgegangen werden soll.Christian Blasge, geboren 1988 in Klagenfurt, ist als Schullehrer sowie als Fachlehrer im Bereich Ethik, Bewegung und Sport an der Pädagogischen Hochschule Steiermark sowie an der Karl-Franzens-Universität Graz tätig.
Big Data Analytics for Internet of Things
BIG DATA ANALYTICS FOR INTERNET OF THINGSDISCOVER THE LATEST DEVELOPMENTS IN IOT BIG DATA WITH A NEW RESOURCE FROM ESTABLISHED AND EMERGING LEADERS IN THE FIELDBig Data Analytics for Internet of Things delivers a comprehensive overview of all aspects of big data analytics in Internet of Things (IoT) systems. The book includes discussions of the enabling technologies of IoT data analytics, types of IoT data analytics, challenges in IoT data analytics, demand for IoT data analytics, computing platforms, analytical tools, privacy, and security.The distinguished editors have included resources that address key techniques in the analysis of IoT data. The book demonstrates how to select the appropriate techniques to unearth valuable insights from IoT data and offers novel designs for IoT systems.With an abiding focus on practical strategies with concrete applications for data analysts and IoT professionals, Big Data Analytics for Internet of Things also offers readers:* A thorough introduction to the Internet of Things, including IoT architectures, enabling technologies, and applications* An exploration of the intersection between the Internet of Things and Big Data, including IoT as a source of Big Data, the unique characteristics of IoT data, etc.* A discussion of the IoT data analytics, including the data analytical requirements of IoT data and the types of IoT analytics, including predictive, descriptive, and prescriptive analytics* A treatment of machine learning techniques for IoT data analyticsPerfect for professionals, industry practitioners, and researchers engaged in big data analytics related to IoT systems, Big Data Analytics for Internet of Things will also earn a place in the libraries of IoT designers and manufacturers interested in facilitating the efficient implementation of data analytics strategies. TAUSIFA JAN SALEEM is currently pursuing her Doctor of Philosophy (Ph.D) from National Institute of Technology Srinagar, India. She has received the Bachelor of Technology (B. Tech.) degree in Information Technology (IT) from National Institute of Technology Srinagar, India and the M.Tech. degree in Computer Science from University of Jammu, India. She has published more than 10 research articles in reputed journals (indexed by Scopus and SCI) and conferences (indexed by Scopus). Her research areas of interest include Internet of Things, Data Analytics, Machine Learning, and Deep Learning.MOHAMMAD AHSAN CHISHTI, PH.D, is Dean at the School of Engineering & Technology and Associate Professor in the Department of Information Technology at the Central University of Kashmir. He has published over 100 scholarly papers and holds 12 patents. He is the recipient of “Young Engineers Award 2015-2016” from IEI and “Young Scientist Award 2009-2010” from the government of Jammu and Kashmir. He is a Senior Member of the IEEE, MIEI, MCSI & MIETE.List of Contributors xvList of Abbreviations xix1 BIG DATA ANALYTICS FOR THE INTERNET OF THINGS: AN OVERVIEW 1Tausifa Jan Saleem and Mohammad Ahsan Chishti2 DATA, ANALYTICS AND INTEROPERABILITY BETWEEN SYSTEMS (IOT) IS INCONGRUOUS WITH THE ECONOMICS OF TECHNOLOGY: EVOLUTION OF POROUS PARETO PARTITION (P3) 7Shoumen Palit Austin Datta, Tausifa Jan Saleem, Molood Barati, María Victoria López López, Marie-Laure Furgala, Diana C. Vanegas, Gérald Santucci, Pramod P. Khargonekar, and Eric S. McLamore2.1 Context 82.2 Models in the Background 122.3 Problem Space: Are We Asking the Correct Questions? 142.4 Solutions Approach: The Elusive Quest to Build Bridges Between Data and Decisions 152.5 Avoid This Space: The Deception Space 172.6 Explore the Solution Space: Necessary to Ask Questions That May Not Have Answers, Yet 172.7 Solution Economy: Will We Ever Get There? 192.8 Is This Faux Naïveté in Its Purest Distillate? 212.9 Reality Check: Data Fusion 222.10 “Double A” Perspective of Data and Tools vs. The Hypothetical Porous Pareto (80/20) Partition 282.11 Conundrums 292.12 Stigma of Partition vs. Astigmatism of Vision 382.13 The Illusion of Data, Delusion of Big Data, and the Absence of Intelligence in AI 402.14 In Service of Society 502.15 Data Science in Service of Society: Knowledge and Performance from PEAS 522.16 Temporary Conclusion 60Acknowledgements 63References 633 MACHINE LEARNING TECHNIQUES FOR IOT DATA ANALYTICS 89Nailah Afshan and Ranjeet Kumar Rout3.1 Introduction 893.2 Taxonomy of Machine Learning Techniques 943.2.1 Supervised ML Algorithm 953.2.1.1 Classification 963.2.1.2 Regression Analysis 983.2.1.3 Classification and Regression Tasks 993.2.2 Unsupervised Machine Learning Algorithms 1033.2.2.1 Clustering 1033.2.2.2 Feature Extraction 1063.2.3 Conclusion 107References 1074 IOT DATA ANALYTICS USING CLOUD COMPUTING 115Anjum Sheikh, Sunil Kumar, and Asha Ambhaikar4.1 Introduction 1154.2 IoT Data Analytics 1174.2.1 Process of IoT Analytics 1174.2.2 Types of Analytics 1184.3 Cloud Computing for IoT 1184.3.1 Deployment Models for Cloud 1204.3.1.1 Private Cloud 1204.3.1.2 Public Cloud 1204.3.1.3 Hybrid Cloud 1214.3.1.4 Community Cloud 1214.3.2 Service Models for Cloud Computing 1224.3.2.1 Software as a Service (SaaS) 1224.3.2.2 Platform as a Service (PaaS) 1224.3.2.3 Infrastructure as a Service (IaaS) 1224.3.3 Data Analytics on Cloud 1234.4 Cloud-Based IoT Data Analytics Platform 1234.4.1 Atos Codex 1254.4.2 AWS IoT 1254.4.3 IBM Watson IoT 1264.4.4 Hitachi Vantara Pentaho, Lumada 1274.4.5 Microsoft Azure IoT 1284.4.6 Oracle IoT Cloud Services 1294.5 Machine Learning for IoT Analytics in Cloud 1324.5.1 ML Algorithms for Data Analytics 1324.5.2 Types of Predictions Supported by ML and Cloud 1364.6 Challenges for Analytics Using Cloud 1374.7 Conclusion 139References 1395 DEEP LEARNING ARCHITECTURES FOR IOT DATA ANALYTICS 143Snowber Mushtaq and Omkar Singh5.1 Introduction 1435.1.1 Types of Learning Algorithms 1465.1.1.1 Supervised Learning 1465.1.1.2 Unsupervised Learning 1465.1.1.3 Semi-Supervised Learning 1465.1.1.4 Reinforcement Learning 1465.1.2 Steps Involved in Solving a Problem 1465.1.2.1 Basic Terminology 1475.1.2.2 Training Process 1475.1.3 Modeling in Data Science 1475.1.3.1 Generative 1485.1.3.2 Discriminative 1485.1.4 Why DL and IoT? 1485.2 DL Architectures 1495.2.1 Restricted Boltzmann Machine 1495.2.1.1 Training Boltzmann Machine 1505.2.1.2 Applications of RBM 1515.2.2 Deep Belief Networks (DBN) 1515.2.2.1 Training DBN 1525.2.2.2 Applications of DBN 1535.2.3 Autoencoders 1535.2.3.1 Training of AE 1535.2.3.2 Applications of AE 1545.2.4 Convolutional Neural Networks (CNN) 1545.2.4.1 Layers of CNN 1555.2.4.2 Activation Functions Used in CNN 1565.2.4.3 Applications of CNN 1585.2.5 Generative Adversarial Network (GANs) 1585.2.5.1 Training of GANs 1585.2.5.2 Variants of GANs 1595.2.5.3 Applications of GANs 1595.2.6 Recurrent Neural Networks (RNN) 1595.2.6.1 Training of RNN 1605.2.6.2 Applications of RNN 1615.2.7 Long Short-Term Memory (LSTM) 1615.2.7.1 Training of LSTM 1615.2.7.2 Applications of LSTM 1625.3 Conclusion 162References 1636 ADDING PERSONAL TOUCHES TO IOT: A USER-CENTRIC IOT ARCHITECTURE 167Sarabjeet Kaur Kochhar6.1 Introduction 1676.2 Enabling Technologies for BDA of IoT Systems 1696.3 Personalizing the IoT 1716.3.1 Personalization for Business 1726.3.2 Personalization for Marketing 1726.3.3 Personalization for Product Improvement and Service Optimization 1736.3.4 Personalization for Automated Recommendations 1746.3.5 Personalization for Improved User Experience 1746.4 Related Work 1756.5 User Sensitized IoT Architecture 1766.6 The Tweaked Data Layer 1786.7 The Personalization Layer 1806.7.1 The Characterization Engine 1806.7.2 The Sentiment Analyzer 1826.8 Concerns and Future Directions 1836.9 Conclusions 184References 1857 SMART CITIES AND THE INTERNET OF THINGS 187Hemant Garg, Sushil Gupta, and Basant Garg7.1 Introduction 1877.2 Development of Smart Cities and the IoT 1887.3 The Combination of the IoT with Development of City Architecture to Form Smart Cities 1897.3.1 Unification of the IoT 1907.3.2 Security of Smart Cities 1907.3.3 Management of Water and Related Amenities 1907.3.4 Power Distribution and Management 1917.3.5 Revenue Collection and Administration 1917.3.6 Management of City Assets and Human Resources 1927.3.7 Environmental Pollution Management 1927.4 How Future Smart Cities Can Improve Their Utilization of the Internet of All Things, with Examples 1937.5 Conclusion 194References 1958 A ROADMAP FOR APPLICATION OF IOT-GENERATED BIG DATA IN ENVIRONMENTAL SUSTAINABILITY 197Ankur Kashyap8.1 Background and Motivation 1978.2 Execution of the Study 1988.2.1 Role of Big Data in Sustainability 1988.2.2 Present Status and Future Possibilities of IoT in Environmental Sustainability 1998.3 Proposed Roadmap 2028.4 Identification and Prioritizing the Barriers in the Process 2048.4.1 Internet Infrastructure 2048.4.2 High Hardware and Software Cost 2048.4.3 Less Qualified Workforce 2048.5 Conclusion and Discussion 205References 2059 APPLICATION OF HIGH-PERFORMANCE COMPUTING IN SYNCHROPHASOR DATA MANAGEMENT AND ANALYSIS FOR POWER GRIDS 209C.M. Thasnimol and R. Rajathy9.1 Introduction 2099.2 Applications of Synchrophasor Data 2109.2.1 Voltage Stability Analysis 2119.2.2 Transient Stability 2129.2.3 Out of Step Splitting Protection 2139.2.4 Multiple Event Detection 2139.2.5 State Estimation 2139.2.6 Fault Detection 2149.2.7 Loss of Main (LOM) Detection 2149.2.8 Topology Update Detection 2149.2.9 Oscillation Detection 2159.3 Utility Big Data Issues Related to PMU-Driven Applications 2159.3.1 Heterogeneous Measurement Integration 2159.3.2 Variety and Interoperability 2169.3.3 Volume and Velocity 2169.3.4 Data Quality and Security 2169.3.5 Utilization and Analytics 2179.3.6 Visualization of Data 2189.4 Big Data Analytics Platforms for PMU Data Processing 2199.4.1 Hadoop 2209.4.2 Apache Spark 2219.4.3 Apache HBase 2229.4.4 Apache Storm 2229.4.5 Cloud-Based Platforms 2239.5 Conclusions 224References 22410 INTELLIGENT ENTERPRISE-LEVEL BIG DATA ANALYTICS FOR MODELING AND MANAGEMENT IN SMART INTERNET OF ROADS 231Amin Fadaeddini, Babak Majidi, and Mohammad Eshghi10.1 Introduction 23110.2 Fully Convolutional Deep Neural Network for Autonomous Vehicle Identification 23310.2.1 Detection of the Bounding Box of the License Plate 23310.2.2 Segmentation Objective 23410.2.3 Spatial Invariances 23410.2.4 Model Framework 23410.2.4.1 Increasing the Layer of Transformation 23410.2.4.2 Data Format of Sample Images 23510.2.4.3 Applying Batch Normalization 23610.2.4.4 Network Architecture 23610.2.5 Role of Data 23610.2.6 Synthesizing Samples 23610.2.7 Invariances 23710.2.8 Reducing Number of Features 23710.2.9 Choosing Number of Classes 23810.3 Experimental Setup and Results 23910.3.1 Sparse Softmax Loss 23910.3.2 Mean Intersection Over Union 24010.4 Practical Implementation of Enterprise-Level Big Data Analytics for Smart City 24010.5 Conclusion 244References 24411 PREDICTIVE ANALYSIS OF INTELLIGENT SENSING AND CLOUD-BASED INTEGRATED WATER MANAGEMENT SYSTEM 247Tanuja Patgar and Ripal Patel11.1 Introduction 24711.2 Literature Survey 24811.3 Proposed Six-Tier Data Framework 25011.3.1 Primary Components 25111.3.2 Contact Unit (FC-37) 25311.3.3 Internet of Things Communicator (ESP8266) 25311.3.4 GSM-Based ARM and Control System 25311.3.5 Methodology 25311.3.6 Proposed Algorithm 25611.4 Implementation and Result Analysis 25711.4.1 Water Report for Home 1 and Home 2 Modules 26311.5 Conclusion 263References 26312 DATA SECURITY IN THE INTERNET OF THINGS: CHALLENGES AND OPPORTUNITIES 265Shashwati Banerjea, Shashank Srivastava, and Sachin Kumar12.1 Introduction 26512.2 IoT: Brief Introduction 26612.2.1 Challenges in a Secure IoT 26712.2.2 Security Requirements in IoT Architecture 26812.2.2.1 Sensing Layer 26812.2.2.2 Network Layer 26912.2.2.3 Interface Layer 27112.2.3 Common Attacks in IoT 27112.3 IoT Security Classification 27212.3.1 Application Domain 27212.3.1.1 Authentication 27212.3.1.2 Authorization 27412.3.1.3 Depletion of Resources 27412.3.1.4 Establishment of Trust 27512.3.2 Architectural Domain 27512.3.2.1 Authentication in IoT Architecture 27512.3.2.2 Authorization in IoT Architecture 27612.3.3 Communication Channel 27612.4 Security in IoT Data 27712.4.1 IoT Data Security: Requirements 27712.4.1.1 Data: Confidentiality, Integrity, and Authentication 27812.4.1.2 Data Privacy 27912.4.2 IoT Data Security: Research Directions 28012.5 Conclusion 280References 28113 DDOS ATTACKS: TOOLS, MITIGATION APPROACHES, AND PROBABLE IMPACT ON PRIVATE CLOUD ENVIRONMENT 285R. K. Deka, D. K. Bhattacharyya, and J. K. Kalita13.1 Introduction 28513.1.1 State of the Art 28713.1.2 Contribution 28813.1.3 Organization 29013.2 Cloud and DDoS Attack 29013.2.1 Cloud Deployment Models 29013.2.1.1 Differences Between Private Cloud and Public Cloud 29313.2.2 DDoS Attacks 29413.2.2.1 Attacks on Infrastructure Level 29413.2.2.2 Attacks on Application Level 29613.2.3 DoS/DDoS Attack on Cloud: Probable Impact 29713.3 Mitigation Approaches 29813.3.1 Discussion 30913.4 Challenges and Issues with Recommendations 30913.5 A Generic Framework 31013.6 Conclusion and Future Work 312References 31214 SECURING THE DEFENSE DATA FOR MAKING BETTER DECISIONS USING DATA FUSION 321Syed Rameem Zahra14.1 Introduction 32114.2 Analysis of Big Data 32214.2.1 Existing IoT Big Data Analytics Systems 32214.2.2 Big Data Analytical Methods 32414.2.3 Challenges in IoT Big Data Analytics 32414.3 Data Fusion 32514.3.1 Opportunities Provided by Data Fusion 32614.3.2 Data Fusion Challenges 32614.3.3 Stages at Which Data Fusion Can Happen 32614.3.4 Mathematical Methods for Data Fusion 32614.4 Data Fusion for IoT Security 32714.4.1 Defense Use Case 32914.5 Conclusion 329References 33015 NEW AGE JOURNALISM AND BIG DATA (UNDERSTANDING BIG DATA AND ITS INFLUENCE ON JOURNALISM) 333Asif Khan and Heeba Din15.1 Introduction 33315.1.1 Big Data Journalism: The Next Big Thing 33415.1.2 All About Data 33615.1.3 Accessing Data for Journalism 33715.1.4 Data Analytics: Tools for Journalists 33815.1.5 Case Studies – Big Data 34015.1.5.1 BBC Big Data 34015.1.5.2 The Guardian Data Blog 34215.1.5.3 Wikileaks 34415.1.5.4 World Economic Forum 34415.1.6 Big Data – Indian Scenario 34515.1.7 Internet of Things and Journalism 34615.1.8 Impact on Media/Journalism 347References 34816 TWO DECADES OF BIG DATA IN FINANCE: SYSTEMATIC LITERATURE REVIEW AND FUTURE RESEARCH AGENDA 351Nufazil Altaf16.1 Introduction 35116.2 Methodology 35316.3 Article Identification and Selection 35316.4 Description and Classification of Literature 35416.4.1 Research Method Employed 35416.4.2 Articles Published Year Wise 35516.4.3 Journal of Publication 35616.5 Content and Citation Analysis of Articles 35616.5.1 Citation Analysis 35616.5.2 Content Analysis 35716.5.2.1 Big Data in Financial Markets 35816.5.2.2 Big Data in Internet Finance 35916.5.2.3 Big Data in Financial Services 35916.5.2.4 Big Data and Other Financial Issues 36016.6 Reporting of Findings and Research Gaps 36016.6.1 Findings from the Literature Review 36116.6.1.1 Lack of Symmetry 36116.6.1.2 Dominance of Research on Financial Markets, Internet Finance, and Financial Services 36116.6.1.3 Dominance of Empirical Research 36116.6.2 Directions for Future Research 362References 362Index 367
Basiswissen Requirements Engineering
KOMPAKTES GRUNDLAGENWERK FÜR DEN REQUIREMENTS ENGINEER * Standardwerk in 5. Auflage * konform zum IREB-Lehrplan Version 3.0 * mit interaktiven Elementen: animierte Grafiken, Videos Dieses Lehrbuch umfasst den erforderlichen Stoff zum Ablegen der Prüfung "Certified Professional for Requirements Engineering (Foundation Level)" nach IREB-Standard. Es vermittelt das Grundlagenwissen und behandelt die wesentlichen Prinzipien und Praktiken sowie wichtige Begriffe und Konzepte. Die Themen im Einzelnen: - Grundlegende Prinzipien des Requirements Engineering - Arbeitsprodukte und Dokumentationspraktiken - Praktiken für die Erarbeitung von Anforderungen - Prozess und Arbeitsstruktur - Praktiken für das Requirements Management - Werkzeugunterstützung Das Buch eignet sich gleichermaßen für das Selbststudium, zur Vorbereitung auf die Zertifizierung sowie als kompaktes Basiswerk zum Thema in der Praxis und an Hochschulen. Die 5. Auflage wurde komplett überarbeitet, ist konform zum IREB-Lehrplan Foundation Level Version 3.0 und wurde angereichert mit interaktiven Elementen wie animierte Grafiken und Videos.
Data Science
KNOW-HOW FÜR DATA SCIENTISTS * übersichtliche und anwendungsbezogene Einführung * zahlreiche Anwendungsfälle und Praxisbeispiele aus unterschiedlichen Branchen * Potenziale, aber auch mögliche Fallstricke werden aufgezeigt Data Science steht derzeit wie kein anderer Begriff für die Auswertung großer Datenmengen mit analytischen Konzepten des Machine Learning oder der künstlichen Intelligenz. Nach der bewussten Wahrnehmung der Big Data und dabei insbesondere der Verfügbarmachung in Unternehmen sind Technologien und Methoden zur Auswertung dort gefordert, wo klassische Business Intelligence an ihre Grenzen stößt. Dieses Buch bietet eine umfassende Einführung in Data Science und deren praktische Relevanz für Unternehmen. Dabei wird auch die Integration von Data Science in ein bereits bestehendes Business-Intelligence-Ökosystem thematisiert. In verschiedenen Beiträgen werden sowohl Aufgabenfelder und Methoden als auch Rollen- und Organisationsmodelle erläutert, die im Zusammenspiel mit Konzepten und Architekturen auf Data Science wirken. Diese 2., überarbeitete Auflage wurde um neue Themen wie Feature Selection und Deep Reinforcement Learning sowie eine neue Fallstudie erweitert.
Design and Development of Efficient Energy Systems
There is not a single industry which will not be transformed by machine learning and Internet of Things (IoT). IoT and machine learning have altogether changed the technological scenario by letting the user monitor and control things based on the prediction made by machine learning algorithms. There has been substantial progress in the usage of platforms, technologies and applications that are based on these technologies. These breakthrough technologies affect not just the software perspective of the industry, but they cut across areas like smart cities, smart healthcare, smart retail, smart monitoring, control, and others. Because of these “game changers,” governments, along with top companies around the world, are investing heavily in its research and development. Keeping pace with the latest trends, endless research, and new developments is paramount to innovate systems that are not only user-friendly but also speak to the growing needs and demands of society.This volume is focused on saving energy at different levels of design and automation including the concept of machine learning automation and prediction modeling. It also deals with the design and analysis for IoT-enabled systems including energy saving aspects at different level of operation.The editors and contributors also cover the fundamental concepts of IoT and machine learning, including the latest research, technological developments, and practical applications. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in the area of IoT and machine technology, this is a must-have for any library.SUMAN LATA TRIPATHI, PHD, is a professor at Lovely Professional with more than seventeen years of experience in academics. She has published more than 45 research papers in refereed journals and conferences. She has organized several workshops, summer internships, and expert lectures for students, and she has worked as a session chair, conference steering committee member, editorial board member, and reviewer for IEEE journals and conferences. She has published one edited book and currently has multiple volumes scheduled for publication, including volumes available from Wiley-Scrivener.DUSHYANT KUMAR SINGH, is an assistant professor and Head of Embedded Systems Domain at Lovely Professional University. With a masters degree from Punjab Engineering College, University of Technology, Chandigarh, he has several years of industrial experience and more than ten years of teaching experience.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.P. RAJA is currently working as an assistant professor at Lovely Professional University. His expertise is in VLSI and embedded systems. He has more than 14 years of experience with 5 years in embedded industry. He has 14 publications in UGC-approved and other reputable journals. He also has 10 patents to his credit.Preface xv1 DESIGN OF LOW POWER JUNCTION-LESS DOUBLE-GATE MOSFET 1Namrata Mendiratta and Suman Lata Tripathi1.1 Introduction 11.2 MOSFET Performance Parameters 21.3 Comparison of Existing MOSFET Architectures 31.4 Proposed Heavily Doped Junction-Less Double Gate MOSFET (AJ-DGMOSFET) 31.5 Heavily Doped JL-DG MOSFET for Biomedical Application 81.6 Conclusion 9References 102 VLSI IMPLEMENTATION OF VEDIC MULTIPLIER 13Abhishek Kumar2.1 Introduction 132.2 8x8 Vedic Multiplier 142.3 The Architecture of 8x8 Vedic Multiplier (VM) 162.3.1 Compressor Architecture 172.3.1.1 3:2 Compressor 182.3.1.2 4:3 Compressor 182.3.1.3 5:3 Compressor 182.3.1.4 8:4 Compressor 192.3.1.5 10:4 Compressor 192.3.1.6 12:5 Compressor 202.3.1.7 15:5 Compressor 212.3.1.8 20:5 Compressor 212.4 Results and Discussion 232.4.1 Instance Power 232.4.2 Net Power 242.4.3 8-Bit Multiplier 252.4.4 16-Bit Multiplier 262.4.5 Applications of Multiplier 272.5 Conclusion 28References 283 GAS LEAKAGE DETECTION FROM DRAINAGE TO OFFER SAFETY FOR SANITARY WORKERS 31Dr. D. Jeyabharathi, Dr. D. Kesavaraja and D. Sasireka3.1 Introduction 313.1.1 IOT-Based Sewer Gas Detection 313.1.1.1 IoT Sensors 323.1.2 Objective 323.1.3 Contribution of this Chapter 333.1.4 Outline of the Chapter 333.2 Related Works 333.2.1 Sewer Gas Leakage Detection 333.2.2 Crack Detection 343.3 Methodology 343.3.1 Sewer Gas Detection 343.3.1.1 Proposed Tristate Pattern 353.3.2 Crack Detection 363.3.3 Experimental Setup 373.4 Experimental Results 393.5 Conclusion 40References 404 MACHINE LEARNING FOR SMART HEALTHCARE ENERGY-EFFICIENT SYSTEM 43S. Porkodi, Dr. D. Kesavaraja and Dr. Sivanthi Aditanar4.1 Introduction 434.1.1 IoT in the Digital Age 434.1.2 Using IoT to Enhance Healthcare Services 444.1.3 Edge Computing 444.1.4 Machine Learning 444.1.5 Application in Healthcare 454.2 Related Works 454.3 Edge Computing 474.3.1 Architecture 474.3.2 Advantages of Edge Computing over Cloud Computing 474.3.3 Applications of Edge Computing in Healthcare 484.3.4 Edge Computing Advantages 494.3.5 Challenges 504.4 Smart Healthcare System 504.4.1 Methodology 504.4.2 Data Acquisition and IoT End Device 514.4.3 IoT End Device and Backend Server 514.5 Conclusion and Future Directions 52References 525 REVIEW OF MACHINE LEARNING TECHNIQUES USED FOR INTRUSION AND MALWARE DETECTION IN WSNS AND IOT DEVICES 57Dr. Jeyabharathi, Dr. A. Sherly Alphonse, Ms. E.L. Dhivya Priya and Dr. M. Kowsigan5.1 Introduction 575.2 Types of Attacks 585.3 Some Countermeasures for the Attacks 595.4 Machine Learning Solutions 595.5 Machine Learning Algorithms 595.6 Authentication Process Based on Machine Learning 605.7 Internet of Things (IoT) 625.8 IoT-Based Attacks 625.8.1 Botnets 625.8.2 Man-in-the-Middle 625.9 Information and Identity Theft 625.10 Social Engineering 635.11 Denial of Service 635.12 Concerns 635.13 Conclusion 64References 646 SMART ENERGY-EFFICIENT TECHNIQUES FOR LARGE-SCALE PROCESS INDUSTRIES 67B Koti Reddy and N V Raghavaiah6.1 Pumps Operation 676.1.1 Parts in a Centrifugal Pump 686.1.2 Pump Efficiency 686.1.3 VFD 706.1.4 VFD and Pump Motor 726.1.5 Large HT Motors 736.1.6 Smart Pumps 736.2 Vapour Absorption Refrigeration System 746.2.1 Vapour Compression Refrigeration 746.2.2 Vapour Absorption Refrigeration 756.3 Heat Recovery Equipment 776.3.1 Case Study 776.3.2 Advantages of Heat Recovery 786.4 Lighting System 786.4.1 Technical Terms 786.4.2 Introduction 786.4.3 LED Lighting 796.4.4 Energy-Efficiency Techniques 796.4.5 Light Control with IoT 806.4.5.1 Wipro Scheme 806.4.5.2 Tata Scheme 806.4.6 EU Practices 816.5 Air Conditioners 826.5.1 Technical Terms 826.5.2 Types of Air Conditioners 826.5.3 Star Rating of BEE 836.5.4 EU Practices 836.5.5 Energy-Efficiency Tips 836.5.6 Inverter Air Conditioners 856.5.7 IoT-Based Air Conditioners 856.6 Fans and Other Smart Appliances 866.6.1 BLDC Fan Motors 876.6.2 Star Ratings 876.6.3 Group Drive of Fans 886.6.4 Other Smart Appliances 886.7 Motors 926.7.1 Motor Efficiency 926.7.2 Underrated Operation 936.7.3 Energy-Efficient Motors 946.7.3.1 Energy-Efficiency Ratings of BEE 946.7.3.2 Energy-Efficiency Ratings of IEC 946.7.4 Retrofit of Standard Motors with Energy-Efficient Motors 966.7.5 Other Salient Points 976.7.6 Use of Star-Delta Starter Motor 976.8 Energy-Efficient Transformers 986.8.1 IEC Recommendation 986.8.2 Super Conducting Transformers 99References 997 LINK RESTORATION AND RELAY NODE PLACEMENT IN PARTITIONED WIRELESS SENSOR NETWORK 101Manwinder Singh and Anudeep Gandam7.1 Introduction 1017.2 Related Work 1037.2.1 Existing Techniques 1057.3 Proposed K-Means Clustering Algorithm 1057.3.1 Homogenous and Heterogeneous Network Clustering Algorithms 1057.3.2 Dynamic and Static Clustering 1057.3.2.1 Routing 1067.3.3 Flow Diagram 1067.3.4 Objective Function 1067.4 System Model and Assumption 1087.4.1 Simulation Parameters 1087.4.1.1 Residual Energy 1087.4.1.2 End-to-End Delay 1097.4.1.3 Number of Hops or Hop Count in the Network 1097.5 Results and Discussion 1097.6 Conclusions 114References 1158 FREQUENCY MODULATED PV POWERED MLI FED INDUCTION MOTOR DRIVE FOR WATER PUMPING APPLICATIONS 119Arunkumar S, Mohana Sundaram N and K. Malarvizhi8.1 Introduction 1198.2 PV Panel as Energy Source 1208.2.1 Solar Cell 1208.3 Multi-Level Inverter Topologies 1218.3.1 Types of Inverters Used for Drives 1218.3.2 Multi-Level Inverters 1218.4 Experimental Results and Discussion 1228.4.1 PV Powered H Bridge Inverter-Fed Drive 1238.4.2 PV Powered DCMLI Fed Drive 1268.5 Conclusion and Future Scope 128References 1299 ANALYSIS AND DESIGN OF BIDIRECTIONAL CIRCUITS FOR ENERGY STORAGE APPLICATION 131Suresh K, Sanjeevikumar Padmanaban and S Vivek9.1 Introduction 1319.2 Modes of Operation Based on Main Converters 1339.2.1 Single-Stage Rectification 1349.2.2 Single-Stage Inversion 1359.2.3 Double-Stage Rectification 1379.2.3.1 Duty Mode - Interval -I 1379.2.3.2 Freewheeling Mode - Interval -II 1389.2.4 Double-Stage Inversion 1399.2.4.1 Charging Mode - Interval -I 1409.2.4.2 Duty Mode - Interval -II 1419.3 Proposed Methodology for Three-Phase System 1419.3.1 Control Block of Overall System 1439.3.2 Proposed Carrier-Based PWM Strategy 1449.3.3 Experiment Results 1459.4 Conclusion 148References 14810 LOW-POWER IOT-ENABLED ENERGY SYSTEMS 151Yogini Dilip Borole and Dr. C. G. Dethe10.1 Overview 15110.1.1 Conceptions 15110.1.2 Motivation 15210.1.3 Methodology 15410.2 Empowering Tools 15610.2.1 Sensing Components 15610.2.2 Movers 15910.2.3 Telecommunication Technology 16010.2.4 Internet of Things Information and Evaluation 16610.2.4.1 Distributed Evaluation 16610.2.4.2 Fog Computing (Edge Computing) 16710.3 Internet of Things within Power Region 16710.3.1 Internet of Things along with Vitality Production 16810.3.2 Smart Metropolises 16810.3.3 Intelligent Lattice Network 17110.3.4 Smart Buildings Structures 17210.3.5 Powerful Usage of Vitality in Production 17310.3.6 Insightful Transport 17410.4 Difficulties - Relating Internet of Things 17410.4.1 Vitality Ingestion 17810.4.2 Synchronization via Internet of Things through Sub-Units 17810.4.3 Client Confidentiality 18010.4.4 Safety Challenges 18010.4.5 IoT Standardization and Architectural Concept 18110.5 Upcoming Developments 18210.5.1 IoT and Block Chain 18210.5.2 Artificial Intelligence and IoT 18410.5.3 Green IoT 18510.6 Conclusion 187References 18811 EFFICIENT RENEWABLE ENERGY SYSTEMS 199Prabhansu and Nayan KumarIntroduction 19911.1 Renewable-Based Available Technologies 20011.1.1 Wind Power 20111.1.1.1 Modeling of the Wind Turbine Generator (WTG) 20111.1.1.2 Categorization of Wind Turbine 20211.1.2 Solar Power 20211.1.2.1 PV System 20211.1.2.2 Network-Linked Photovoltaic Grid-Connected PV Set-Up 20311.1.3 Tidal Energy 20311.1.4 Battery Storage System 20411.1.5 Solid Oxide Energy Units for Enhancing Power Life 20411.1.5.1 Common Utility of SOFC 20411.1.5.2 Integrated Solid Oxide Energy Components and Sustainable Power Life 20511.2 Adaptability Frameworks 20611.2.1 Distributed Energy Resources (DER) 20611.2.2 New Age Grid Connection 20911.3 Conclusion 210References 21112 EFFICIENT RENEWABLE ENERGY SYSTEMS 215Dr. Arvind Dhingra12.1 Introduction 21512.1.1 World Energy Scenario 21512.2 Sources of Energy: Classification 21712.3 Renewable Energy Systems 21712.3.1 Solar Energy 21812.3.2 Wind 21812.3.3 Geothermal 21812.3.4 Biomass 21812.3.5 Ocean 21812.3.6 Hydrogen 21812.4 Solar Energy 21812.5 Wind Energy 22312.6 Geothermal Energy 22512.7 Biomass 22612.7.1 Forms of Biomass 22612.8 Ocean Power 22712.9 Hydrogen 22712.10 Hydro Power 22712.11 Conclusion 227References 22713 AGRICULTURE-IOT-BASED SPRINKLER SYSTEM FOR WATER AND FERTILIZER CONSERVATION AND MANAGEMENT 229Dilip Kumar and Ujala Choudhury13.1 Introduction 22913.1.1 Novelty of the Work 23213.1.2 Benefit to Society 23213.2 Development of the Proposed System 23313.3 System Description 23313.3.1 Study of the Crop Under Experiment 23313.3.2 Hardware of the System 23513.3.3 Software of the System 23513.4 Layers of the System Architecture 23613.4.1 Application Layer 23613.4.2 Cloud Layer 23713.4.3 Network Layer 23713.4.4 Physical Layer 23713.5 Calibration 23713.6 Layout of the Sprinkler System 23913.7 Testing 23913.8 Results and Discussion 24113.9 Conclusion 242References 24214 A BEHAVIOUR-BASED AUTHENTICATION TO INTERNET OF THINGS USING MACHINE LEARNING 245Mohit Goyal and Durgesh Srivastava14.1 Introduction 24614.2 Basics of Internet of Things (IoT) 24614.2.1 The IoT Reference Model 24814.2.2 Working of IoT 24914.2.2.1 Device 24914.2.2.2 Connectivity to Cloud 25014.2.2.3 Data Analysis 25014.2.2.4 User Interface 25014.2.3 Utilization of Internet of Things (IoT) 25014.3 Authentication in IoT 25114.3.1 Methods of Authentication 25114.3.1.1 Authentication Based on Knowledge 25214.3.1.2 Authentication Based on Possession 25214.3.1.3 Authentication Based on Biometric 25314.4 User Authentication Based on Behavioral-Biometric 25514.4.1 Machine Learning 25614.4.1.1 Supervised Machine Learning 25614.4.1.2 Unsupervised Machine Learning 25614.4.2 Machine Learning Algorithms 25714.4.2.1 RIPPER 25714.4.2.2 Multilayer Perceptron 25714.4.2.3 Decision Tree 25714.4.2.4 Random Forest 25814.4.2.5 Instance-Based Learning 25814.4.2.6 Bootstrap Aggregating 25814.4.2.7 Naïve Bayes 25814.5 Threats and Challenges in the Current Security Solution for IoT 25814.6 Proposed Methodology 25914.6.1 Collection of Gait Dataset 25914.6.2 Gait Data Preprocessing 25914.6.3 Reduction in Data Size 26014.6.4 Gaits Feature 26014.6.5 Classification 26014.7 Conclusion and Future Work 261References 26115 A FUZZY GOAL PROGRAMMING MODEL FOR QUALITY MONITORING OF FRUITS DURING SHIPMENT OVERSEAS 265Pushan Kr. Dutta, Somsubhra Gupta, Simran Kumari and Akshay Vinayak15.1 Introduction 26515.2 Proposed System 26615.2.1 Problem Statement 26615.2.2 Overview 26615.2.3 System Components 26815.3 Work Process 27115.3.1 System Hardware 27115.3.2 Connections and Circuitry 27115.4 Optimization Framework 27115.4.1 Fuzzy Goal Description 27115.4.2 Characterizing Fuzzy Membership Function 27215.4.3 Construction of FGP Model 27215.4.4 Definition of Variables and Parameters 27315.4.5 Fuzzy Goal Description 27415.5 Creation of Database and Website 27515.5.1 Hosting PHP Application and Creation of MySQL Database 27515.5.2 Creation of API (Application Programming Interfaces) Key 27515.5.2.1 $api_key_value = “3mM44UaC2DjFcV_63GZ14aWJcRDNmYBMsxceu”; 27515.5.2.2 Preparing Mysql Database 27515.5.2.3 Structured Query Language (SQL) 27515.5.2.4 Use of HTTP (Hypertext Transfer Protocol) in Posting Request 27615.5.2.5 Adding a Dynamic Map to the Website 27715.5.2.6 Adding Dynamic Graph to the Website 27715.5.2.7 Adding the Download Option of the Data Set 27815.6 Libraries Used and Code Snipped 27815.7 Mode of Communication 28015.8 Conclusion 280Abbreviations 282References 28216 INTERNET OF THINGS – DEFINITION, ARCHITECTURE, APPLICATIONS, REQUIREMENTS AND KEY RESEARCH CHALLENGES 285Dushyant Kumar Singh, Himani Jerath and P. Raja16.1 Introduction 28516.2 Defining the Term Internet of Things (IoT) 28616.3 IoT Architecture 28716.4 Applications of Internet of Things (IoT) 28916.5 Requirement for Internet of Things (IoT) Implementation 29016.6 Key Research Challenges in Internet of Things (IoT) 29116.6.1 Computing, Communication and Identification 29116.6.2 Network Technology 29216.6.3 Greening of Internet of Things (IoT) 29216.6.4 Security 29316.6.5 Diversity 29316.6.6 Object Safety and Security 29316.6.7 Data Confidentiality and Unauthorized Access 29316.6.8 Architecture 29316.6.9 Network and Routing Information Security 293References 29417 FINFET TECHNOLOGY FOR LOW-POWER APPLICATIONS 297Bindu Madhavi, Suman Lata Tripathi and Bhagwan Shree Ram17.1 Introduction 29717.2 Exiting Multiple-Gate MOSFET Architectures 29917.3 FinFET Design and Analysis 30117.4 Low-Power Applications 30417.4.1 FinFET-Based Digital Circuit Design 30417.4.2 FinFET-Based Memory Design 30417.4.3 FinFET-Based Biosensors 30417.5 Conclusion 305References 30518 AN ENHANCED POWER QUALITY SINGLE-SOURCE LARGE STEP-UP SWITCHED-CAPACITOR BASED MULTI-LEVEL INVERTER CONFIGURATION WITH NATURAL VOLTAGE BALANCING OF CAPACITORS 307Mahdi Karimi, Paria Kargar, Kazem Varesi and Sanjeevikumar Padmanaban18.1 Introduction 30718.2 Suggested Topology 30918.2.1 Circuit Configuration 30918.2.2 Generation of Output Voltage Steps 31018.2.3 Voltage Stress of Switches 32018.3 Cascaded Configuration of Suggested Topology 32018.4 Modulation Technique 32118.5 Power Loss Analysis 32418.5.1 Conduction Losses 32418.5.2 Switching Losses 32618.5.3 Capacitor Losses 32718.6 Design of Capacitors 32818.7 Comparative Analysis 33018.8 Simulation Results 33318.9 Conclusions 336References 336Index 339