This book comprehensively introduces data deduplication technologies for storage systems. It first presents the overview of data deduplication including its theoretical basis, basic workflow, application scenarios and its key technologies, and then the book focuses on each key technology of the deduplication to provide an insight into the evolution of the technology over the years including chunking algorithms, indexing schemes, fragmentation reduced schemes, rewriting algorithm and security solution. In particular, the state-of-the-art solutions and the newly proposed solutions are both elaborated. At the end of the book, the author discusses the fundamental trade-offs in each of deduplication design choices and propose an open-source deduplication prototype. The book with its fundamental theories and complete survey can guide the beginners, students and practitioners working on data deduplication in storage system. It also provides a compact reference in the perspective of key data deduplication technologies for those researchers in developing high performance storage solutions.

With this book, Christopher Kormanyos delivers a highly practical guide to programming real-time embedded microcontroller systems in C++. It is divided into three parts plus several appendices. Part I provides a foundation for real-time C++ by covering language technologies, including object-oriented methods, template programming and optimization. Next, part II presents detailed descriptions of a variety of C++ components that are widely used in microcontroller programming. It details some of C++'s most powerful language elements, such as class types, templates and the STL, to develop components for microcontroller register access, low-level drivers, custom memory management, embedded containers, multitasking, etc. Finally, part III describes mathematical methods and generic utilities that can be employed to solve recurring problems in real-time C++. The appendices include a brief C++ language tutorial, information on the real-time C++ development environment and instructions for building GNU GCC cross-compilers and a microcontroller circuit. For this fourth edition, the most recent specification of C++20 is used throughout the text. Several sections on new C++20 functionality have been added, and various others reworked to reflect changes in the standard. Also several new example projects ranging from introductory to advanced level are included and existing ones extended, and various reader suggestions have been incorporated. Efficiency is always in focus and numerous examples are backed up with runtime measurements and size analyses that quantify the true costs of the code down to the very last byte and microsecond. The target audience of this book mainly consists of students and professionals interested in real-time C++. Readers should be familiar with C or another programming language and will benefit most if they have had some previous experience with microcontroller electronics and the performance and size issues prevalent in embedded systems programming.

A collection of best practices and effective implementation recommendations that are proven to work, Secure, Resilient, and Agile Software Development leaves the boring details of software security theory out of the discussion as much as possible to concentrate on practical applied software security for practical people. Written to aid your career as well as your organization, the book shows how to gain skills in secure and resilient software development and related tasks. The book explains how to integrate these development skills into your daily duties, thereby increasing your professional value to your company, your management, your community, and your industry. Secure, Resilient, and Agile Software Development was written for the following professionals: AppSec architects and program managers in information security organizations Enterprise architecture teams with application development focus Scrum teams DevOps teams Product owners and their managers Project managers Application security auditors With a detailed look at Agile and Scrum software development methodologies, this book explains how security controls need to change in light of an entirely new paradigm on how software is developed. It focuses on ways to educate everyone who has a hand in any software development project with appropriate and practical skills to Build Security In. After covering foundational and fundamental principles for secure application design, this book dives into concepts, techniques, and design goals to meet well-understood acceptance criteria on features an application must implement. It also explains how the design sprint is adapted for proper consideration of security as well as defensive programming techniques. The book concludes with a look at white box application analysis and sprint-based activities to improve the security and quality of software under development.

Dokumentenmanagementprojekte sind ganzheitliche Projekte. Organisatorische, technische und menschliche Faktoren entscheiden uber Erfolg oder Mierfolg. Das DMS-Handbuch hilft fruhzeitig Fehler zu erkennen und zu vermeiden. Es ist eine Pflichtlekture fur jeden, der sich mit dem Gedanken tragt, ein Dokumentenmanagementsystem einzufuhren. Schritt fur Schritt wird der Leser durch die einzelnen Projektstufen gefuhrt. Mit Hilfe von Tabellen, Charts und Diagrammen wird eine komplexe Materie ubersichtlich dargestellt. Ein ausfuhrliches Glossar mit Begriffserklarungen der Fachtermini und eine Fulle von Checklisten machen das Buch zum unentbehrlichen Begleiter.

This book takes an in-depth look at the emerging technologies that are transforming the way clinicians manage patients, while at the same time emphasizing that the best practitioners use both artificial and human intelligence to make decisions. AI and machine learning are explored at length, with plain clinical English explanations of convolutional neural networks, back propagation, and digital image analysis. Real-world examples of how these tools are being employed are also discussed, including their value in diagnosing diabetic retinopathy, melanoma, breast cancer, cancer metastasis, and colorectal cancer, as well as in managing severe sepsis. With all the enthusiasm about AI and machine learning, it was also necessary to outline some of criticisms, obstacles, and limitations of these new tools. Among the criticisms discussed: the relative lack of hard scientific evidence supporting some of the latest algorithms and the so-called black box problem. A chapter on data analytics takes a deep dive into new ways to conduct subgroup analysis and how it's forcing healthcare executives to rethink the way they apply the results of large clinical trials to everyday medical practice. This re-evaluation is slowly affecting the way diabetes, heart disease, hypertension, and cancer are treated. The research discussed also suggests that data analytics will impact emergency medicine, medication management, and healthcare costs. An examination of the diagnostic reasoning process itself looks at how diagnostic errors are measured, what technological and cognitive errors are to blame, and what solutions are most likely to improve the process. It explores Type 1 and Type 2 reasoning methods; cognitive mistakes like availability bias, affective bias, and anchoring; and potential solutions such as the Human Diagnosis Project. Finally, the book explores the role of systems biology and precision medicine in clinical decision support and provides several case studies of how next generation AI is transforming patient care.

The overwhelming majority of a software system's lifespan is spent in use, not in design or implementation. So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems? In this collection of essays and articles, key members of Google's Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You'll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient-lessons directly applicable to your organization. This book is divided into four sections: Introduction-Learn what site reliability engineering is and why it differs from conventional IT industry practices Principles-Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE) Practices-Understand the theory and practice of an SRE's day-to-day work: building and operating large distributed computing systems Management-Explore Google's best practices for training, communication, and meetings that your organization can use

This book presents an overview of operations research and systems engineering and takes a look into both fields on content, histories, contributions, and future directions so a sound career choice can be made for those who might be deciding on a career path. The book also offers how these two fields can be integrated and used in current times and into the future. Operations Research and Systems Engineering: Growth and Transformation traces the history of both fields of research as well as offers comments on the importance of both areas of study. By taking a look back with a historical perspective and also looking forward with the presentation of applications currently being used, someone looking to make a sound career choice will be able to decide which area they want to move towards. The book also offers how to integrate both operations research methods with systems engineering concepts and tools and provides a comparison between the two, along with how they can work together in the future. The goal of this book is to provide the reader with enough information so they can move forward with their career goals. It is also an ideal book that provides engineers, scientists, and mathematicians with a way to broaden their knowledge and areas of study.

As the complexity of today's networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of networked computers rely on. It introduces the key issues, describes their interrelationships, and presents new research in support of these areas. The book presents the insights of a different group of international experts in each chapter. Reporting on recent developments in adaptive systems, it begins with a survey of application fields. It explains the requirements of such fields in terms of adaptation and resilience. It also provides some abstract relationship graphs that illustrate the key attributes of distributed systems to supply you with a better understanding of these factors and their dependencies. The text examines resilient adaptive systems from the perspectives of mobile, infrastructure, and enterprise systems and protecting critical infrastructure. It details various approaches for building adaptive, dynamic, and resilient systems-including agile, grid, and autonomic computing; multi-agent-based and biologically inspired approaches; and self-organizing systems. The book includes many stories of successful applications that illustrate a diversified range of cutting-edge approaches. It concludes by covering related topics and techniques that can help to boost adaptation and resilience in your systems.

The main objective is to provide quick and essential knowledge for the subject with the help of summary and solved questions /case studies without going into detailed discussion. This book will be much helpful for the students as a supplementary text/workbook; and to the non-computer professionals, who deal with the systems analysis and design as part of their business. Such problem solving approach will be able to provide practical knowledge of the subject and similar learning output, without going into lengthy discussions. Though the book is conceived as supplementary text/workbook; the topics are selected and arranged in such a way that it can provide complete and sufficient knowledge of the subject.

If you're like most R users, you have deep knowledge and love for statistics. But as your organization continues to collect huge amounts of data, adding tools such as Apache Spark makes a lot of sense. With this practical book, data scientists and professionals working with large-scale data applications will learn how to use Spark from R to tackle big data and big compute problems. Authors Javier Luraschi, Kevin Kuo, and Edgar Ruiz show you how to use R with Spark to solve different data analysis problems. This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users. Analyze, explore, transform, and visualize data in Apache Spark with R Create statistical models to extract information and predict outcomes; automate the process in production-ready workflows Perform analysis and modeling across many machines using distributed computing techniques Use large-scale data from multiple sources and different formats with ease from within Spark Learn about alternative modeling frameworks for graph processing, geospatial analysis, and genomics at scale Dive into advanced topics including custom transformations, real-time data processing, and creating custom Spark extensions

Present book covers new paradigms in Blockchain, Big Data and Machine Learning concepts including applications and case studies. It explains dead fusion in realizing the privacy and security of blockchain based data analytic environment. Recent research of security based on big data, blockchain and machine learning has been explained through actual work by practitioners and researchers, including their technical evaluation and comparison with existing technologies. The theoretical background and experimental case studies related to real-time environment are covered as well. Aimed at Senior undergraduate students, researchers and professionals in computer science and engineering and electrical engineering, this book: Converges Blockchain, Big Data and Machine learning in one volume. Connects Blockchain technologies with the data centric applications such Big data and E-Health. Easy to understand examples on how to create your own blockchain supported by case studies of blockchain in different industries. Covers big data analytics examples using R. Includes lllustrative examples in python for blockchain creation.

Build your expertise in the BPF virtual machine in the Linux kernel with this practical guide for systems engineers. You'll not only dive into the BPF program lifecycle but also learn to write applications that observe and modify the kernel's behavior; inject code to monitor, trace, and securely observe events in the kernel; and more. Authors David Calavera and Lorenzo Fontana help you harness the power of BPF to make any computing system more observable. Familiarize yourself with the essential concepts you'll use on a day-to-day basis and augment your knowledge about performance optimization, networking, and security. Then see how it all comes together with code examples in C, Go, and Python. Write applications that use BPF to observe and modify the Linux kernel's behavior on demand Inject code to monitor, trace, and observe events in the kernel in a secure way-no need to recompile the kernel or reboot the system Explore code examples in C, Go, and Python Gain a more thorough understanding of the BPF program lifecycle

Thoroughly classroom-tested and proven to be a valuable self-study companion, Linear Control System Analysis and Design: Sixth Edition provides an intensive overview of modern control theory and conventional control system design using in-depth explanations, diagrams, calculations, and tables. Keeping mathematics to a minimum, the book is designed with the undergraduate in mind, first building a foundation, then bridging the gap between control theory and its real-world application. Computer-aided design accuracy checks (CADAC) are used throughout the text to enhance computer literacy. Each CADAC uses fundamental concepts to ensure the viability of a computer solution. Completely updated and packed with student-friendly features, the sixth edition presents a range of updated examples using MATLAB (R), as well as an appendix listing MATLAB functions for optimizing control system analysis and design. Over 75 percent of the problems presented in the previous edition have been revised or replaced.

How society can shape individual actions in times of uncertainty

When we make decisions, our thinking is informed by societal norms, “guardrails” that guide our decisions, like the laws and rules that govern us. But what are good guardrails in today’s world of overwhelming information flows and increasingly powerful technologies, such as artificial intelligence? Based on the latest insights from the cognitive sciences, economics, and public policy, Guardrails offers a novel approach to shaping decisions by embracing human agency in its social context.

In this visionary book, Urs Gasser and Viktor Mayer-Schönberger show how the quick embrace of technological solutions can lead to results we don’t always want, and they explain how society itself can provide guardrails more suited to the digital age, ones that empower individual choice while accounting for the social good, encourage flexibility in the face of changing circumstances, and ultimately help us to make better decisions as we tackle the most daunting problems of our times, such as global injustice and climate change.

Whether we change jobs, buy a house, or quit smoking, thousands of decisions large and small shape our daily lives. Decisions drive our economies, seal the fate of democracies, create war or peace, and affect the well-being of our planet. Guardrails challenges the notion that technology should step in where our own decision making fails, laying out a surprisingly human-centered set of principles that can create new spaces for better decisions and a more innovative and prosperous society.

Written by Ganglia designers and maintainers, this book shows you how to collect and visualize metrics from clusters, grids, and cloud infrastructures at any scale. Want to track CPU utilization from 50,000 hosts every ten seconds? Ganglia is just the tool you need, once you know how its main components work together. This hands-on book helps experienced system administrators take advantage of Ganglia 3.x.

Learn how to extend the base set of metrics you collect, fetch current values, see aggregate views of metrics, and observe time-series trends in your data. You'll also examine real-world case studies of Ganglia installs that feature challenging monitoring requirements.Determine whether Ganglia is a good fit for your environmentLearn how Ganglia's gmond and gmetad daemons build a metric collection overlayPlan for scalability early in your Ganglia deployment, with valuable tips and adviceTake data visualization to a new level with gweb, Ganglia's web frontendWrite plugins to extend gmond's metric-collection capabilityTroubleshoot issues you may encounter with a Ganglia installationIntegrate Ganglia with the sFlow and Nagios monitoring systems

Contributors include: Robert Alexander, Jeff Buchbinder, Frederiko Costa, Alex Dean, Dave Josephsen, Peter Phaal, and Daniel Pocock. Case study writers include: John Allspaw, Ramon Bastiaans, Adam Compton, Andrew Dibble, and Jonah Horowitz.

Over the last 50 years, the theory and the methods of reliability analysis have developed significantly. Therefore, it is very important to the reliability specialist to be informed of each reliability measure. This book will provide historical developments, current advancements, applications, numerous examples, and many case studies to bring the reader up-to-date with the advancements in this area. It covers reliability engineering in different branches, includes applications to reliability engineering practice, provides numerous examples to illustrate the theoretical results, and offers case studies along with real-world examples. This book is useful to engineering students, research scientist, and practitioners working in the field of reliability.

This book describes methods to improve software performance and safety using advanced mathematical and computational analytics. The main focus is laid on the increase of software reliability by preventive and predictive maintenance with efficient usage of modern testing resources. The editors collect contributions from international researchers in the field.

Success is driven through collaboration. The field of Industrial and Systems Engineering has evolved as a major engineering field with interdisciplinary strength drawn from effective utilization, process improvement, optimization, design, and management of complex systems. It is a broad discipline that is important to nearly every attempt to solve problems facing the needs of society and the welfare of humanity. In order to carry this forward, successful collaborations are needed between industry, government, and academia. This book brings together an international group of distinguished practitioners and academics in manufacturing, healthcare, logistics, and energy sectors to examine what enables successful collaborations. The book is divided into two key parts: 1) partnerships, frameworks, and leadership; and 2) engineering applications and case studies. Part I highlights some of the ways partnerships emerge between those seeking to innovate and educate in industrial and systems engineering, some useful frameworks and methodologies, as well as some of the ideas and practices that undergird leadership in the profession. Part II provides case studies and applications to illustrate the power of the partnerships between academia and practice in industrial and systems engineering. Features Examines the success from multiple industries Provides frameworks for building teams and avoiding pitfalls Contains international perspectives of success Uses collaborative approaches from industry, government, and academia Includes real world case studies illustrating the enabling factors Offers engineering education and student-centric takeaways

This book constitutes the refereed proceedings of the 13th European Conference on Software Architecture, ECSA 2019, held in Paris, France, in September 2019. In the Research Track, 11 full papers presented together with 4 short papers were carefully reviewed and selected from 63 submissions. They are organized in topical sections as follows: Services and Micro-services, Software Architecture in Development Process, Adaptation and Design Space Exploration, and Quality Attributes. In the Industrial Track, 6 submissions were received and 3 were accepted to form part of these proceedings.

Final year projects are an important feature of most undergraduate and postgraduate degrees in the fields of Business Information Technology, Information Systems, Software Engineering and Business Computing. These projects usually involve students in the practical application of theory together with a critical analysis or evaluation of the excecution of their project or of the theory applied. This book is the first to provide detailed guidance and support for students in preparing for, conducting and evaluating a system development project, independent of the development methodology or technical tools to be used.

The 4-volume set LNCS 13534, 13535, 13536 and 13537 constitutes the refereed proceedings of the 5th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2022, held in Shenzhen, China, in November 2022. The 233 full papers presented were carefully reviewed and selected from 564 submissions. The papers have been organized in the following topical sections: Theories and Feature Extraction; Machine learning, Multimedia and Multimodal; Optimization and Neural Network and Deep Learning; Biomedical Image Processing and Analysis; Pattern Classification and Clustering; 3D Computer Vision and Reconstruction, Robots and Autonomous Driving; Recognition, Remote Sensing; Vision Analysis and Understanding; Image Processing and Low-level Vision; Object Detection, Segmentation and Tracking.

Introduction to Modeling and Simulation with MATLAB and Python is intended for students and professionals in science, social science, and engineering that wish to learn the principles of computer modeling, as well as basic programming skills. The book content focuses on meeting a set of basic modeling and simulation competencies that were developed as part of several National Science Foundation grants. Even though computer science students are much more expert programmers, they are not often given the opportunity to see how those skills are being applied to solve complex science and engineering problems and may also not be aware of the libraries used by scientists to create those models. The book interleaves chapters on modeling concepts and related exercises with programming concepts and exercises. The authors start with an introduction to modeling and its importance to current practices in the sciences and engineering. They introduce each of the programming environments and the syntax used to represent variables and compute mathematical equations and functions. As students gain more programming expertise, the authors return to modeling concepts, providing starting code for a variety of exercises where students add additional code to solve the problem and provide an analysis of the outcomes. In this way, the book builds both modeling and programming expertise with a "just-in-time" approach so that by the end of the book, students can take on relatively simple modeling example on their own. Each chapter is supplemented with references to additional reading, tutorials, and exercises that guide students to additional help and allows them to practice both their programming and analytical modeling skills. In addition, each of the programming related chapters is divided into two parts - one for MATLAB and one for Python. In these chapters, the authors also refer to additional online tutorials that students can use if they are having difficulty with any of the topics. The book culminates with a set of final project exercise suggestions that incorporate both the modeling and programming skills provided in the rest of the volume. Those projects could be undertaken by individuals or small groups of students. The companion website at http://www.intromodeling.com provides updates to instructions when there are substantial changes in software versions, as well as electronic copies of exercises and the related code. The website also offers a space where people can suggest additional projects they are willing to share as well as comments on the existing projects and exercises throughout the book. Solutions and lecture notes will also be available for qualifying instructors.

Balancing rigorous theory with practical applications, Linear Systems: Optimal and Robust Control explains the concepts behind linear systems, optimal control, and robust control and illustrates these concepts with concrete examples and problems.

Developed as a two-course book, this self-contained text first discusses linear systems, including controllability, observability, and matrix fraction description. Within this framework, the author develops the ideas of state feedback control and observers. He then examines optimal control, stochastic optimal control, and the lack of robustness of linear quadratic Gaussian (LQG) control. The book subsequently presents robust control techniques and derives "H"∞ control theory from the first principle, followed by a discussion of the sliding mode control of a linear system. In addition, it shows how a blend of sliding mode control and "H"∞ methods can enhance the robustness of a linear system.

By learning the theories and algorithms as well as exploring the examples in Linear Systems: Optimal and Robust Control, students will be able to better understand and ultimately better manage engineering processes and systems.