This is the most comprehensive and up-to-date guide to the technologies and applications of Augmented Reality (AR) and Virtual Reality (VR) systems and wearable computing devices. Ideal for practitioners and students concerned with any application, from gaming to medicine, it brings together comprehensive coverage of both theory and practice, emphasizing leading-edge displays, sensors, and DIY tools that are already available commercially or will be soon. Practical Augmented Reality begins by explaining the mechanics of human sight, hearing and touch, showing how these mechanisms (and their performance ranges) directly dictate the design and use of wearable displays, 3-D audio systems, and tactile/force feedback devices. It presents revealing case studies of real-world applications from gaming, entertainment, science, engineering, aerospace and air traffic control, defense, medicine, architecture, law enforcement, and geophysics. Readers will find clear, easy-to-understand explanations, photos, and illustrations of devices including Oculus (Facebook) Rift, Sony Morpheus, Google Glass, and many more. Functional diagrams clearly explain how each device operates, and link directly to relevant theoretical and practical content. Practical Augmented Reality thoroughly considers human factors, including sense and motor physiology constraints; resolution and realism; fields of view, angles, and distortion; latency and time display; flicker vertigo, phobia effects, and motion sickness. It concludes by assessing both the legal and societal implications of new and emerging AR, VR, and wearable technologies.
Learn how to use the Apache Hadoop projects, including MapReduce, HDFS, Apache Hive, Apache HBase, Apache Kafka, Apache Mahout, and Apache Solr. From setting up the environment to running sample applications each chapter in this book is a practical tutorial on using an Apache Hadoop ecosystem project. While several books on Apache Hadoop are available, most are based on the main projects, MapReduce and HDFS, and none discusses the other Apache Hadoop ecosystem projects and how they all work together as a cohesive big data development platform. What You Will Learn: Set up the environment in Linux for Hadoop projects using Cloudera Hadoop Distribution CDH 5 Run a MapReduce job Store data with Apache Hive, and Apache HBase Index data in HDFS with Apache Solr Develop a Kafka messaging system Stream Logs to HDFS with Apache Flume Transfer data from MySQL database to Hive, HDFS, and HBase with Sqoop Create a Hive table over Apache Solr Develop a Mahout User Recommender System Who This Book Is For: Apache Hadoop developers. Pre-requisite knowledge of Linux and some knowledge of Hadoop is required.
Stop manually analyzing binary! Practical Binary Analysis is the first book of its kind to present advanced binary analysis topics, such as binary instrumentation, dynamic taint analysis, and symbolic execution, in an accessible way. As malware increasingly obfuscates itself and applies anti-analysis techniques to thwart our analysis, we need more sophisticated methods that allow us to raise that dark curtain designed to keep us out--binary analysis can help. The goal of all binary analysis is to determine (and possibly modify) the true properties of binary programs to understand what they really do, rather than what we think they should do. While reverse engineering and disassembly are critical first steps in many forms of binary analysis, there is much more to be learned. This hands-on guide teaches you how to tackle the fascinating but challenging topics of binary analysis and instrumentation and helps you become proficient in an area typically only mastered by a small group of expert hackers. It will take you from basic concepts to state-of-the-art methods as you dig into topics like code injection, disassembly, dynamic taint analysis, and binary instrumentation. Written for security engineers, hackers, and those with a basic working knowledge of C/C++ and x86-64, Practical Binary Analysis will teach you in-depth how binary programs work and help you acquire the tools and techniques needed to gain more control and insight into binary programs. Once you´ve completed an introduction to basic binary formats, you´ll learn how to analyze binaries using techniques like the GNU/Linux binary analysis toolchain, disassembly, and code injection. You´ll then go on to implement profiling tools with Pin and learn how to build your own dynamic taint analysis tools with libdft and symbolic execution tools using Triton. You´ll learn how to: - Parse ELF and PE binaries and build a binary loader with libbfd - Use data-flow analysis techniques like program tracing, slicing, and reaching definitions analysis to reason about runtime flow of your programs - Modify ELF binaries with techniques like parasitic code injection and hex editing - Build custom disassembly tools with Capstone - Use binary instrumentation to circumvent anti-analysis tricks commonly used by malware - Apply taint analysis to detect control hijacking and data leak attacks - Use symbolic execution to build automatic exploitation tools With exercises at the end of each chapter to help solidify your skills, you´ll go from understanding basic assembly to performing some of the most sophisticated binary analysis and instrumentation. Practical Binary Analysis gives you what you need to work effectively with binary programs and transform your knowledge from basic understanding to expert-level proficiency.
In präziser, praxisorientierter Form vermitteln die Autoren das Wissen zur Therapie mit Herzschrittmachern und zur Betreuung von Herzschrittmacherpatienten: - anatomisch-physiologische und technische Grundlagen - Indikationen und Auswahl des Schrittmachers - Durchführung der Implantation - Schrittmacherprogrammierung - Kleine und große Schrittmacherkontrolle - Komplikationen und ihre Behandlung - Schrittmacher- oder Elektrodenwechsel Zahlreiche Fallbeschreibungen und EKG-Beispiele tragen zur Anschaulichkeit bei. Die häufigsten Fragen der Patienten an den Arzt sind mit Antwortvorschlägen in einem Anhang zusammengefaßt. Ein Schrittmacherlexikon ermöglicht auf einen Blick die Information über alle spezifischen Begriffe. Based on the needs of the educational community, and the software professional, this book takes a unique approach to teaching software testing. It introduces testing concepts that are managerial, technical, and process oriented, using the Testing Maturity Model (TMM) as a guiding framework. The TMM levels and goals support a structured presentation of fundamental and advanced test-related concepts to the reader. In this context, the interrelationships between theoretical, technical, and managerial concepts become more apparent. In addition, relationships between the testing process, maturity goals, and such key players as managers, testers and client groups are introduced. Topics and features: - Process/engineering-oriented text - Promotes the growth and value of software testing as a profession - Introduces both technical and managerial aspects of testing in a clear and precise style - Uses the TMM framework to introduce testing concepts in a systemmatic, evolutionary way to faciliate understanding - Describes the role of testing tools and measurements, and how to integrate them into the testing process Graduate students and industry professionals will benefit from the book, which is designed for a graduate course in software testing, software quality assurance, or software validation and verification Moreover, the number of universities with graduate courses that cover this material will grow, given the evoluation in software development as an engineering discipline and the creation of degree programs in software engineering.
´´The promise of cloud computing is here. These pages provide the ´eyes wide open´ insights you need to transform your business.´´ --Christopher Crowhurst, Vice President, Strategic Technology, Thomson Reuters A Down-to-Earth Guide to Cloud Computing Cloud Computing: A Practical Approach provides a comprehensive look at the emerging paradigm of Internet-based enterprise applications and services. This accessible book offers a broad introduction to cloud computing, reviews a wide variety of currently available solutions, and discusses the cost savings and organizational and operational benefits. You´ll find details on essential topics, such as hardware, platforms, standards, migration, security, and storage. You´ll also learn what other organizations are doing and where they´re headed with cloud computing. If your company is considering the move from a traditional network infrastructure to a cutting-edge cloud solution, you need this strategic guide. Cloud Computing: A Practical Approach covers: * Costs, benefits, security issues, regulatory concerns, and limitations * Service providers, including Google, Microsoft, Amazon, Yahoo, IBM, EMC/VMware, Salesforce.com, and others * Hardware, infrastructure, clients, platforms, applications, services, and storage * Standards, including HTTP, HTML, DHTML, XMPP, SSL, and OpenID * Web services, such as REST, SOAP, and JSON * Platform as a Service (PaaS), Software as a Service (SaaS), and Software plus Services (S+S) * Custom application development environments, frameworks, strategies, and solutions * Local clouds, thin clients, and virtualization * Migration, best practices, and emerging standards
Learn how to build your own computer vision (CV) applications quickly and easily with SimpleCV, an open source framework written in Python. Through examples of real-world applications, this hands-on guide introduces you to basic CV techniques for collecting, processing, and analyzing streaming digital images. You?ll then learn how to apply these methods with SimpleCV, using sample Python code. All you need to get started is a Windows, Mac, or Linux system, and a willingness to put CV to work in a variety of ways. Programming experience is optional. * Capture images from several sources, including webcams, smartphones, and Kinect * Filter image input so your application processes only necessary information * Manipulate images by performing basic arithmetic on pixel values * Use feature detection techniques to focus on interesting parts of an image * Work with several features in a single image, using the NumPy and SciPy Python libraries * Learn about optical flow to identify objects that change between two image frames * Use SimpleCV?s command line and code editor to run examples and test techniques
Designing Software Architectures is the first step-by-step guide to making the crucial design decisions that can make or break your software architecture. SEI expert Rick Kazman and Dr. Humberto Cervantes provide comprehensive guidance for ensuring that your architectural design decisions are consistently rational and evidence-based.
An introduction to the open-source machine learning package explains how to install H2O, import and export data, and distinguish H2O algorithms, and explores such machine learning techniques as deep learning, random forests, and ensemble learning.