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Acclaimed one of the "seminal books... comparable in ultimate importance to... Galileo or Malthus or Rousseau or Mill," Cybernetics was judged by twenty-seven historians, economists, educators, and philosophers to be one of those books published during the "past four decades," which may have a substantial impact on public thought and action in the years ahead.—Saturday Review

For advanced undergraduate and beginning graduate students in atmospheric, oceanic, and climate science, Atmosphere, Ocean and Climate Dynamics is an introductory textbook on the circulations of the atmosphere and ocean and their interaction, with an emphasis on global scales. It will give students a good grasp of what the atmosphere and oceans look like on the large-scale and why they look that way. The role of the oceans in climate and paleoclimate is also discussed. The combination of observations, theory and accompanying illustrative laboratory experiments sets this text apart by making it accessible to students with no prior training in meteorology or oceanography.* Written at a mathematical level that is appealing for undergraduates andbeginning graduate students* Provides a useful educational tool through a combination of observations andlaboratory demonstrations which can be viewed over the web* Contains instructions on how to reproduce the simple but informativelaboratory experiments* Includes copious problems (with sample answers) to help students learn thematerial.

Learn How Coupling Impacts Every Software Design Decision You Make--and How to Control It If you want to build modular, evolvable, and resilient software systems, you have to get coupling right. Every design decision you make influences coupling, which in turn shapes the design options available to you. Despite its importance, coupling often doesn't receive the attention it deserves--until now. Since the dawn of software engineering, it's been clear that proper management of coupling is essential for architecting modular software systems. This topic has been extensively researched over the years, but some of that knowledge has been forgotten, and some of it is challenging to apply in this day and age. In Balancing Coupling in Software Design, author Vlad Khononov has built a model that not only draws on this accumulated knowledge, but also adapts it to modern software engineering practices, offering a fresh perspective on modular software design. With principles grounded in practice, Vlad teaches you not only to navigate the multi-dimensional nature of coupling but also to use coupling as a tool for managing complexity and increasing modularity. And who knows, maybe this book will change the way you think about software design as whole. Defines the concept of coupling and the role it plays in system design and architecture Explains how coupling can both increase complexity and foster modularity of a system Introduces a holistic model that turns coupling into a tool for designing modular software Shows how to evolve design decisions to support continuous growth of software systems Illustrates the discussed principles with detailed examples based on real-life case studies "Coupling is one of those words that is used a lot, but little understood. Vlad propels us from simplistic slogans like 'always decouple components' to a nuanced discussion of coupling in the context of complexity and software evolution. If you build modern software, read this book!" --Gregor Hohpe, author of The Software Architect Elevator Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Discover how planes get--and stay--airborne Now you can truly master an understanding of the phenomenon of flight. This practical guide is the most intuitive introduction to basic flight mechanics available. Understanding Flight, Second Edition, explains the principles of aeronautics in terms, descriptions, and illustrations that make sense--without complicated mathematics. Updated to include helicopter flight fundamentals and aircraft structures, this aviation classic is required reading for new pilots, students, engineers, and anyone fascinated with flight. Understanding Flight, Second Edition, covers: Physics of flight Wing design and configuration Stability and control Propulsion High-speed flight Performance and safety Aerodynamic testing Helicopters and autogyros Aircraft structures and materials  

In the field of machine learning, semi-supervised learning (SSL) occupies the middle ground, between supervised learning (in which all training examples are labeled) and unsupervised learning (in which no label data are given). Interest in SSL has increased in recent years, particularly because of application domains in which unlabeled data are plentiful, such as images, text, and bioinformatics. This first comprehensive overview of SSL presents state-of-the-art algorithms, a taxonomy of the field, selected applications, benchmark experiments, and perspectives on ongoing and future research.Semi-Supervised Learning first presents the key assumptions and ideas underlying the field: smoothness, cluster or low-density separation, manifold structure, and transduction. The core of the book is the presentation of SSL methods, organized according to algorithmic strategies. After an examination of generative models, the book describes algorithms that implement the low-density separation assumption, graph-based methods, and algorithms that perform two-step learning. The book then discusses SSL applications and offers guidelines for SSL practitioners by analyzing the results of extensive benchmark experiments. Finally, the book looks at interesting directions for SSL research. The book closes with a discussion of the relationship between semi-supervised learning and transduction.Olivier Chapelle and Alexander Zien are Research Scientists and Bernhard Schölkopf is Professor and Director at the Max Planck Institute for Biological Cybernetics in Tübingen. Schölkopf is coauthor of Learning with Kernels (MIT Press, 2002) and is a coeditor of Advances in Kernel Methods: Support Vector Learning (1998), Advances in Large-Margin Classifiers (2000), and Kernel Methods in Computational Biology (2004), all published by The MIT Press.

Graphical models, a marriage between probability theory and graph theory, provide a natural tool for dealing with two problems that occur throughout applied mathematics and engineering--uncertainty and complexity. In particular, they play an increasingly important role in the design and analysis of machine learning algorithms. Fundamental to the idea of a graphical model is the notion of modularity: a complex system is built by combining simpler parts. Probability theory serves as the glue whereby the parts are combined, ensuring that the system as a whole is consistent and providing ways to interface models to data. Graph theory provides both an intuitively appealing interface by which humans can model highly interacting sets of variables and a data structure that lends itself naturally to the design of efficient general-purpose algorithms. This book presents an in-depth exploration of issues related to learning within the graphical model formalism. Four chapters are tutorial chapters--Robert Cowell on Inference for Bayesian Networks, David MacKay on Monte Carlo Methods, Michael I. Jordan et al. on Variational Methods, and David Heckerman on Learning with Bayesian Networks. The remaining chapters cover a wide range of topics of current research interest.

Noted for its highly readable style, the new edition of this bestseller provides an updated overview of aeronautical and aerospace engineering. Introduction to Flight blends history and biography with discussion of engineering concepts, and shows the development of flight through this perspective. Anderson covers new developments in flight, including unmanned aerial vehicles, uninhabited combat aerial vehicles, and applications of CFD in aircraft design. Many new and revised problems have been added in this edition. Chapter learning features help readers follow the text discussion while highlighting key engineering and industry applications.

According to Webster's Dictionary, a fascicle is "one of the division of a bookpublished in parts."This material represents significant updates to Volume 1, Third Edition ofDonald Knuth's The Art of Computer Programming.Knuth's fascicle philosophy is as follows: "The material will first appear in betatestform as fascicles of approximately 128 pages each, issued approximatelytwice per year. These fascicles will represent my best attempt to write acomprehensive account, but computer science has grown to the point where Icannot hope to be an authority on all the material covered in these books.Therefore I'll need feedback from readers in order to prepare the officialvolumes later."

Soft matter science is concerned with soft materials such as polymers, colloids, liquid crystals, and foams, and has emerged as a rich interdisciplinary field over the last 30 years. Drawing on physics, chemistry, mathematics and engineering, soft matter links fundamental scientific ideas to everyday phenomena. One such example is 'polymers', encountered in plastic materials and melted cheese, which illustrate how 'sliminess' emerges from the flow and form of giant molecules. This Very Short Introduction delves into the field of soft matter, looking beneath the appearances of matter into its inner structure. Tom McLeish shows how Brownian Motion - the random local motion of molecules that gives rise to 'heat' - is an underlying principle of soft matter. From hair conditioner to honey, he discusses how the shared physical properties and characteristics of these materials influence the way they behave, and their industrial applications. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.The definitive guide to dimensional design for your data warehouseLearn the best practices of dimensional design. Star Schema: The Complete Reference offers in-depth coverage of design principles and their underlying rationales. Organized around design concepts and illustrated with detailed examples, this is a step-by-step guidebook for beginners and a comprehensive resource for experts.This all-inclusive volume begins with dimensional design fundamentals and shows how they fit into diverse data warehouse architectures, including those of W.H. Inmon and Ralph Kimball. The book progresses through a series of advanced techniques that help you address real-world complexity, maximize performance, and adapt to the requirements of BI and ETL software products. You are furnished with design tasks and deliverables that can be incorporated into any project, regardless of architecture or methodology.Master the fundamentals of star schema design and slow change processingIdentify situations that call for multiple stars or cubesEnsure compatibility across subject areas as your data warehouse growsAccommodate repeating attributes, recursive hierarchies, and poor data qualitySupport conflicting requirements for historic dataHandle variation within a business process and correlation of disparate activitiesBoost performance using derived schemas and aggregatesLearn when it's appropriate to adjust designs for BI and ETL tools