The gold standard for attaining security is cryptography because it provides the most reliable tools for storing or transmitting digital information. Written by Niels Ferguson, lead cryptographer for Counterpane, Bruce Schneier's security company, and Bruce Schneier himself, this is the much anticipated follow-up book to Schneier's seminal encyclopedic reference, Applied Cryptography, Second Edition (0-471-11709-9), which has sold more than 150,000 copies. Niels Ferguson (Amsterdam, Netherlands) is a cryptographic engineer and consultant at Counterpane Internet Security. He has extensive experience in the creation and design of security algorithms, protocols, and multinational security infrastructures. Previously, Ferguson was a cryptographer for DigiCash and CWI. At CWI he developed the first generation of off-line payment protocols. He has published numerous scientific papers. Bruce Schneier (Minneapolis, MN) is Founder and Chief Technical Officer at Counterpane Internet Security, a managed-security monitoring company. He is also the author of Secrets and Lies: Digital Security in a Networked World (0-471-25311-1).

    Each year, the series editor and guest editor curate a truly exceptional collection. The only shared traits among all these diverse styles, voices, and stories are the extraordinarily high caliber of writing, and the pure passion they tap into that can only come from sports.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    

    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.

    It demonstrates how to encourage, develop, and foster the processes which seem to come naturally to mathematicians.

    The "Cooking Light 5-Ingredient 15-Minute Cookbook" meets those needs and delivers-with big flavor "and" nutritious dishes. And instead of just giving you recipes, we're giving you meals-94 in all! Each meal features a main-dish recipe and either a short recipe to go with it or suggestions for commercial side items. Plus there's a photograph of every meal! Grocery Shopping SolutionsWith each meal plan, you get a grocery list of everything you need to complete the meal. Stock up on the ingredients from the Stress-Free Grocery List, and you can make one-third of the recipes in this book. No WorriesThe nutrient analysis with every recipe gives you values for calories, fat, protein, carbohydrate, fiber, cholesterol, and sodium. You can use the exchange values to fit the recipes into your meal plan.All This with Only 5 Ingredients?You'll be surprised at all the recipes you can make using only 5 ingredients: Chicken Alfredo Pasta, Deep-Dish Pizza Casserole, Speedy Chicken Cacciatore, Teriyaki Roast Chicken, Barbecue Pork Chops ...just to name a few.Avoid the Rush HourWhen you have only 15 minutes to get dinner on the table, try these recipes: Cajun-Style Swordfish, Fresh Tomato Pizza, Ground Beef Stroganoff, Chili Bacon Burgers, Teriyaki-Ginger Pork Tenderloin, Zesty Fettuccine and Shrimp.Added ValueCreate 5 different desserts or salads from different combinations of the same 5 ingredients. Start with easy-to-make recipes in the Mix & Match chapter like Three-Bean Salad, Tex-Mex Salad, StrawberryShortcakes, and Brownie Sundaes.Slow Down to Speed UpLearn how to let a slow cooker do the work for you. All with 5 ingredients or less, these recipes are worth coming home to: Chili Grande, Chicken Pepper Pot, Italian Pot Roast, Glazed Turkey.

    Richard Bedard was a journalist in his mid-40s, living abroad, when he was diagnosed with patellofemoral pain syndrome, or chondromalacia patella. His burning joints made his life so miserable that he fantasized about hacking off his kneecaps. Four doctors failed to help; one said he would never get better. His physical therapist finally gave up too.Unable to sit normally, he quit his job. Unemployed and desperate, he launched a year-long, round-the-clock experiment to save his knees. He read from scores of clinical studies, medical textbooks, health newsletters. What he discovered left him stunned. There was a familiar story about what patellofemoral pain syndrome was and how to treat it: The advice to focus on strengthening the quads. To stretch. To take glucosamine. To forget about cartilage healing, because that never happened.And that story was completely wrong.Armed with this knowledge, he fashioned a plan to get better. Within two years, he fully recovered. This compelling story chronicles a long journey of healing and discovery. It shows that a patient’s true ally isn’t simply hope, but informed hope.

    Chapter topics include atomic structure, molecular orbitals, organometallic chemistry, simple bonding theory, symmetry and group theory, and more. For chemists and other professionals who want to update or improve their background in the field.

    

    With an accessible and lively writing style, it introduces modern techniques to what can often be a formal and intimidating subject. Readers are led from the physics of flat spacetime (special relativity), through the intricacies of differential geometry and Einstein's equations, and on to exciting applications such as black holes, gravitational radiation, and cosmology.

    Dozens of key charts, tables, and graphs, including updated steam tables and two new charts of LMTD heat exchanger correction factors, make it possible to work most exam problems using the Reference Manual alone. A complete, easy-to-use index saves you valuable time during the exam as it helps you quickly locate important information needed to solve problems._____________________________Since 1975 more than 2 million people preparing for their engineering, surveying, architecture, LEED®, interior design, and landscape architecture exams have entrusted their exam prep to PPI. For more information, visit us at www.ppi2pass.com.

    Unnikrishna Pillai of Polytechnic University. The book is intended for a senior/graduate level course in probability and is aimed at students in electrical engineering, math, and physics departments. The authors' approach is to develop the subject of probability theory and stochastic processes as a deductive discipline and to illustrate the theory with basic applications of engineering interest. Approximately 1/3 of the text is new material--this material maintains the style and spirit of previous editions. In order to bridge the gap between concepts and applications, a number of additional examples have been added for further clarity, as well as several new topics.

    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.

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.