It gives a clear and authoritative guide to the general framework of network analysis, explaining the basic concepts, technical measures and reviewing the available computer programs.The book outlines both the theoretical basis of network analysis and the key techniques for using it as a research tool. Building upon definitions of points, lines and paths, John Scott demonstrates their use in clarifying such measures as density, fragmentation and centralization. He identifies the various cliques, components and circles into which networks are formed, and outlines

    Yet greenhouse gas emissions increased, atmospheric concentrations grew, and global warming became an observable fact of life.In this book, philosopher Dale Jamieson explains what climate change is, why we have failed to stop it, and why it still matters what we do. Centered in philosophy, the volume also treats the scientific, historical, economic, and political dimensions of climate change. Our failure to prevent or even to respond significantly to climate change, Jamieson argues, reflects the impoverishment of our systems of practical reason, the paralysis of our politics, and the limits of our cognitive and affective capacities. The climate change that is underway is remaking the world in such a way that familiar comforts, places, and ways of life will disappear in years or decades rather than centuries.Climate change also threatens our sense of meaning, since it is difficult to believe that our individual actions matter. The challenges that climate change presents go beyond the resources of common sense morality -- it can be hard to view such everyday acts as driving and flying as presenting moral problems. Yet there is much that we can do to slow climate change, to adapt to it and restore a sense of agency while living meaningful lives in a changing world.

    Spammers, virus writers, phishermen, money launderers, and spies now trade busily with each other in a lively online criminal economy and as they specialize, they get better. In this indispensable, fully updated guide, Ross Anderson reveals how to build systems that stay dependable whether faced with error or malice. Here's straight talk on critical topics such as technical engineering basics, types of attack, specialized protection mechanisms, security psychology, policy, and more.

    Missile trajectories. Cornering dynamics in speeding cars. By applying the laws of physics, you can realistically model nearly everything in games that bounces around, flies, rolls, slides, or isn't sitting still, to create compelling, believable content for computer games, simulations, and animation. "Physics for Game Developers" serves as the starting point for those who want to enrich games with physics-based realism.Part one is a mechanics primer that reviews basic concepts and addresses aspects of rigid body dynamics, including kinematics, force, and kinetics. Part two applies these concepts to specific real-world problems, such as projectiles, boats, airplanes, and cars. Part three introduces real-time simulations and shows how they apply to computer games. Many specific game elements stand to benefit from the use of real physics, including: The trajectory of rockets and missiles, including the effects of fuel burn offThe collision of objects such as billiard ballsThe stability of cars racing around tight curvesThe dynamics of boats and other waterborne vehiclesThe flight path of a baseball after being struck by a batThe flight characteristics of airplanesYou don't need to be a physics expert to learn from "Physics for Game Developers, " but the author does assume you know basic college-level classical physics. You should also be proficient in trigonometry, vector and matrix math (reference formulas and identities are included in the appendixes), and college-level calculus, including integration and differentiation of explicit functions. Although the thrust of the book involves physics principles and algorithms, it should be noted that the examples are written in standard C and use Windows API functions.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    It is the definitive reference guide, now in a second edition. Although the first edition was written in 1978, it continues to be a worldwide best-seller. This second edition brings the classic original up to date to include the ANSI standard. From the Preface: We have tried to retain the brevity of the first edition. C is not a big language, and it is not well served by a big book. We have improved the exposition of critical features, such as pointers, that are central to C programming. We have refined the original examples, and have added new examples in several chapters. For instance, the treatment of complicated declarations is augmented by programs that convert declarations into words and vice versa. As before, all examples have been tested directly from the text, which is in machine-readable form. As we said in the first preface to the first edition, C "wears well as one's experience with it grows." With a decade more experience, we still feel that way. We hope that this book will help you to learn C and use it well.

    Taking the view that understanding the meaning behind the complex formulas of science is more important than ever, this work attempts to explain the systems view of the world as the paradigm of the latest scientific developments.

    Among the ironies and entanglements resulting from this goal are the sale of nature in our malls through the Nature Company, and the disputes between working people and environmentalists over spotted owls and other objects of species preservation.The problem is that we haven't learned to live responsibly in nature. The environmentalist aim of legislating humans out of the wilderness is no solution. People, Cronon argues, are inextricably tied to nature, whether they live in cities or countryside. Rather than attempt to exclude humans, environmental advocates should help us learn to live in some sustainable relationship with nature. It is our home.

      Today, innovation is seen by business leaders and the media alike as the key to growth, a burning issue in every company, from startups to the Fortune 500. And in that space, Fahrenheit 212 is viewed as a high-performance innovation SWAT team, able to solve the most complex, mission-critical challenges. Under Mark Payne, the firm's president and head of Idea Development, Fahrenheit 212, since its inception a decade ago, has worked with such giants of industry as Coca-Cola, Samsung, Hershey's, Campbell's Soup, LG, Starbucks, Mattel, Office Depot, Citibank, P&G, American Express, Nutrisystem, GE, and Goldman Sachs, to name but a few. It has been praised as a hotspot for innovation in publications like Fortune, Esquire, Businessweek, and FastCompany.  What Drives Fahrenheit 212's success is its unique methodology, combining what it calls Magic--the creative side of innovation--with Money, the business side. They explore every potential idea with the end goal in mind--bringing an innovative product to market in a way that will transform a company's business and growth. In How to Kill a Unicorn, Mark Payne pulls back the curtain on how the company is able to bring more innovative products and ideas successfully to market than any other firm and offers blow by blow inside accounts of how they grapple with and solved their biggest challenges.

    The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on a large scale, and the development of a variety of new theoretical tools has allowed us to extract new knowledge from many different kinds of networks.The study of networks is broadly interdisciplinary and important developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas.Subjects covered include the measurement and structure of networks in many branches of science, methods for analyzing network data, including methods developed in physics, statistics, and sociology, the fundamentals of graph theory, computer algorithms, and spectral methods, mathematical models of networks, including random graph models and generative models, and theories of dynamical processes taking place on networks.

    While modern social life can make even the best of us feel gawky, for roughly one in five of us, navigating its challenges is consistently overwhelming—an ongoing maze without an exit. Often unable to grasp social cues or master the skills and grace necessary for smooth interaction, we feel out of sync with those around us. Though individuals may recognize their awkward disposition, they rarely understand why they are like this—which makes it hard for them to know how to adjust their behavior.Psychologist and interpersonal relationship expert Ty Tashiro knows what it’s like to be awkward. Growing up, he could do math in his head and memorize the earned run averages of every National League starting pitcher. But he couldn’t pour liquids without spilling and habitually forgot to bring his glove to Little League games. In Awkward, he unpacks decades of research into human intelligence, neuroscience, personality, and sociology to help us better understand this widely shared trait. He explores its nature vs. nurture origins, considers how the awkward view the world, and delivers a welcome counterintuitive message: the same characteristics that make people socially clumsy can be harnessed to produce remarkable achievements.Interweaving the latest research with personal tales and real world examples, Awkward offers reassurance and provides valuable insights into how we can embrace our personal quirks and unique talents to harness our awesome potential—and more comfortably navigate our complex world.

    The text examines the basics of analog image analysis while placing greater emphasis on digitally based systems and analysis techniques. The presentation is discipline neutral, so students in any field of study can gain a clear understanding of these systems and their virtually unlimited applications.

    Using it, scientists can find order emerging from seemingly random interactions of all kinds, from something as simple as flipping coins through to more challenging problems such as the patterns in modern jazz, the growth of cancer tumours, and predicting shopping habits.

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

    The phenomenon he describes as social production is reshaping markets, while at the same time offering new opportunities to enhance individual freedom, cultural diversity, political discourse, and justice. But these results are by no means inevitable: a systematic campaign to protect the entrenched industrial information economy of the last century threatens the promise of today’s emerging networked information environment.In this comprehensive social theory of the Internet and the networked information economy, Benkler describes how patterns of information, knowledge, and cultural production are changing—and shows that the way information and knowledge are made available can either limit or enlarge the ways people can create and express themselves. He describes the range of legal and policy choices that confront us and maintains that there is much to be gained—or lost—by the decisions we make today.