You think you can solve your human error problem by telling people to be more careful, by reprimanding the miscreants, by issuing a new rule or procedure. These are all expressions of 'The Bad Apple Theory', where you believe your system is basically safe if it were not for those few unreliable people in it. This old view of human error is increasingly outdated and will lead you nowhere. The new view, in contrast, understands that a human error problem is actually an organizational problem. Finding a 'human error' by any other name, or by any other human, is only the beginning of your journey, not a convenient conclusion. The new view recognizes that systems are inherent trade-offs between safety and other pressures (for example: production). People need to create safety through practice, at all levels of an organization. Breaking new ground beyond its successful predecessor, The Field Guide to Understanding Human Error guides you through the traps and misconceptions of the old view. It explains how to avoid the hindsight bias, to zoom out from the people closest in time and place to the mishap, and resist the temptation of counterfactual reasoning and judgmental language. But it also helps you look forward. It suggests how to apply the new view in building your safety department, handling questions about accountability, and constructing meaningful countermeasures. It even helps you in getting your organization to adopt the new view and improve its learning from failure. So if you are faced by a human error problem, abandon the fallacy of a quick fix. Read this book.

    Comprehensive explanations of their secret rituals and symbolism. Including alchemy, astrology, Kabbalism, ceremonial magic, animal magnetism and more.

    The study of type systems--and of programming languages from a type-theoretic perspective--has important applications in software engineering, language design, high-performance compilers, and security.This text provides a comprehensive introduction both to type systems in computer science and to the basic theory of programming languages. The approach is pragmatic and operational; each new concept is motivated by programming examples and the more theoretical sections are driven by the needs of implementations. Each chapter is accompanied by numerous exercises and solutions, as well as a running implementation, available via the Web. Dependencies between chapters are explicitly identified, allowing readers to choose a variety of paths through the material.The core topics include the untyped lambda-calculus, simple type systems, type reconstruction, universal and existential polymorphism, subtyping, bounded quantification, recursive types, kinds, and type operators. Extended case studies develop a variety of approaches to modeling the features of object-oriented languages.

    The novel approach taken here banishes determinants to the end of the book and focuses on the central goal of linear algebra: understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space (or an odd-dimensional real vector space) has an eigenvalue. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition includes a new section on orthogonal projections and minimization problems. The sections on self-adjoint operators, normal operators, and the spectral theorem have been rewritten. New examples and new exercises have been added, several proofs have been simplified, and hundreds of minor improvements have been made throughout the text.

    It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.

    This text is user-focused and has been highly updated including topics, pictures and examples. The Williams text contains less theory and more application to engage students who might be more familiar with technology. Continually published and updated for over 15 years, Using Information Technology was the first text to foresee and define the impact of digital convergence--the fusion of computers and communications. It was also the first text to acknowledge the new priorities imposed by the Internet and World Wide Web and bring discussion of them from late in the course to the beginning. Today, it is directed toward the "Always On" generation that is at ease with digital technology--comfortable with iPhones, MySpace, Facebook, Twitter, Wikipedia, and the blogosphere--but not always savvy about its processes, possibilities, and liabilities. This 8th edition continues to address the two most significant challenges that instructors face in teaching this course: -Trying to make the course interesting and challenging, and -Trying to teach to students with a variety of computer backgrounds. In addition, this text correlates with Simnet Online for full integration of resources within the Computing Concepts course.

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    In Rules of Play Katie Salen and Eric Zimmerman present a much-needed primer for this emerging field. They offer a unified model for looking at all kinds of games, from board games and sports to computer and video games. As active participants in game culture, the authors have written Rules of Play as a catalyst for innovation, filled with new concepts, strategies, and methodologies for creating and understanding games. Building an aesthetics of interactive systems, Salen and Zimmerman define core concepts like play, design, and interactivity. They look at games through a series of eighteen game design schemas, or conceptual frameworks, including games as systems of emergence and information, as contexts for social play, as a storytelling medium, and as sites of cultural resistance.Written for game scholars, game developers, and interactive designers, Rules of Play is a textbook, reference book, and theoretical guide. It is the first comprehensive attempt to establish a solid theoretical framework for the emerging discipline of game design.

    It has become known for its engaging writing style, instructional art program and focus on active learning. We are so excited to offer a robust learning program with student-focused learning activities, allowing the student to manage their learning while you easily manage their assessment. Detailed reports show how your assignments measure various learning objectives from the book (or input your own!), levels of Bloom's Taxonomy or other categories, and how your students are doing. The Cowan Learning program will save you time and improve your student's success in this course.

    Not any more. Wordpress makes it possible for anyone to create and run a professional looking website.While Wordpress is an amazing tool, the truth is it does have a steep learning curve, even if you have built websites before. Therefore, the goal of this book is to take anyone, even a complete beginner and get them building a professional looking website. I'll hold your hand, step-by-step, all the way. As I was planning this book, I made one decision early on. I wanted to use screenshots of everything, so the reader wasn't left looking for something on their screen that I was describing in text. This book has screenshots. I haven't counted them all, but it must be close to 300. These screenshots will help you find the things I am talking about. They'll help you check your settings and options against the screenshot of mine. No more doubt, no more wondering if you have it correct. Look, compare and move on to the next section.With so many screenshots, you may be worried that the text might be a little on the skimpy side. No need to worry there. I have described in the minutest detail, every step on your journey to a great looking website. In all, this book has over 35,000 words. This book will cut your learning curve associated with WordpressEvery chapter of the book ends with a "Tasks to Complete" section. By completing these tasks, you'll not only become proficient at using Wordpress, you'll become confident & enjoy using Wordpress.

    You'll learn how to install, configure, operate, manage, and secure the latest release.Covers all the new features and capabilities of the much-anticipated new release of VMware vSphere Discusses the planning, installation, operation, and management for the latest release Reviews migration to the latest vSphere software Offers hands-on instruction and clear explanations with real-world examples Mastering VMware vSphere is the strategic guide you need to maximize the opportunities of virtualization.

    Not in an editor, IDE, or design tool. You're well educated on how to work with software and hardware, but what about wetware--our own brains? Learning new skills and new technology is critical to your career, and it's all in your head. In this book by Andy Hunt, you'll learn how our brains are wired, and how to take advantage of your brain's architecture. You'll learn new tricks and tips to learn more, faster, and retain more of what you learn. You need a pragmatic approach to thinking and learning. You need to Refactor Your Wetware. Programmers have to learn constantly; not just the stereotypical new technologies, but also the problem domain of the application, the whims of the user community, the quirks of your teammates, the shifting sands of the industry, and the evolving characteristics of the project itself as it is built. We'll journey together through bits of cognitive and neuroscience, learning and behavioral theory. You'll see some surprising aspects of how our brains work, and how you can take advantage of the system to improve your own learning and thinking skills.In this book you'll learn how to:Use the Dreyfus Model of Skill Acquisition to become more expertLeverage the architecture of the brain to strengthen different thinking modesAvoid common "known bugs" in your mindLearn more deliberately and more effectivelyManage knowledge more efficientlyPrinted in full color.

    The book emphasizes a general introduction to probability theory and provides a detailed discussion of specific designs and analyses that are typically encountered in ecology and environmental science. Appropriate for use as either a stand-alone or supplementary text for upper-division undergraduate or graduate courses in ecological and environmental statistics, ecology, environmental science, environmental studies, or experimental design, the Primer also serves as a resource for environmental professionals who need to use and interpret statistics daily but have little or no formal training in the subject.

    Particularly noteworthy are the numerous historical examples of past efforts to make sense of complex systems of information. In this new companion volume, The Book of Trees, data viz expert Manuel Lima examines the more than eight hundred year history of the tree diagram, from its roots in the illuminated manuscripts of medieval monasteries to its current resurgence as an elegant means of visualization. Lima presents two hundred intricately detailed tree diagram illustrations on a remarkable variety of subjects—from some of the earliest known examples from ancient Mesopotamia to the manuscripts of medieval monasteries to contributions by leading contemporary designers. A timeline of capsule biographies on key figures in the development of the tree diagram rounds out this one-of-a-kind visual compendium.

    Each mini-chapter adds one feature to the ray tracer, and by the end the reader can produce the image on the book cover. Details of basic ray tracing code architecture and C++ classes are given.