Although Cocoa is indeed huge, once you understand the object-oriented patterns it uses, you'll find it remarkably elegant, consistent, and simple. Cocoa Design Patterns begins with the mother of all patterns: the Model-View-Controller (MVC) pattern, which is central to all Mac and iPhone development. Encouraged, and in some cases enforced by Apple's tools, it's important to have a firm grasp of MVC right from the start. The book's midsection is a catalog of the essential design patterns you'll encounter in Cocoa, including Fundamental patterns, such as enumerators, accessors, and two-stage creation Patterns that empower, such as singleton, delegates, and the responder chain Patterns that hide complexity, including bundles, class clusters, proxies and forwarding, and controllers And that's not all of them! Cocoa Design Patterns painstakingly isolates 28 design patterns, accompanied with real-world examples and sample code you can apply to your applications today. The book wraps up with coverage of Core Data models, AppKit views, and a chapter on Bindings and Controllers. Cocoa Design Patterns clearly defines the problems each pattern solves with a foundation in Objective-C and the Cocoa frameworks and can be used by any Mac or iPhone developer.

    In this book, a wealth of exercises are provided throughout each section, designed to reinforce learning and the logical comprehension of topics. The use of real data is incorporated much more extensively than in any other book on the market. Consist of strong coverage of computer-based methods, especially in the coverage of analysis of variance and regression. This text stresses mastery of methods most often used in medical research, with specific reference to actual medical literature and actual medical research. The approach minimizes mathematical formulation, yet gives complete explanations of all important concepts. Every new concept is systematically developed through completely worked-out examples from current medical research problems. Computer output is used to illustrate concepts when appropriate.

    From the physics of energy to climate change, and from spy technology to quantum computers, this is the only textbook to focus on the modern physics affecting the decisions of political leaders and CEOs and, consequently, the lives of every citizen. How practical are alternative energy sources? Can satellites really read license plates from space? What is the quantum physics behind iPods and supermarket scanners? And how much should we fear a terrorist nuke? This lively book empowers students possessing any level of scientific background with the tools they need to make informed decisions and to argue their views persuasively with anyone--expert or otherwise.Based on Richard Muller's renowned course at Berkeley, the book explores critical physics topics: energy and power, atoms and heat, gravity and space, nuclei and radioactivity, chain reactions and atomic bombs, electricity and magnetism, waves, light, invisible light, climate change, quantum physics, and relativity. Muller engages readers through many intriguing examples, helpful facts to remember, a fun-to-read text, and an emphasis on real-world problems rather than mathematical computation. He includes chapter summaries, essay and discussion questions, Internet research topics, and handy tips for instructors to make the classroom experience more rewarding.Accessible and entertaining, "Physics and Technology for Future Presidents" gives students the scientific fluency they need to become well-rounded leaders in a world driven by science and technology.Professors: A supplementary Instructor's Manual is available for this book. It is restricted to teachers using the text in courses. For information on how to obtain a copy, refer to: http: //press.princeton.edu/class_use/solutio...

    Each chapter in this revised Eighth Edition includes two case studies—one clinical and one pharmaceutical. Content coincides with the CAPE, APhA, and NAPLEX competencies.This edition includes updated drug information and expanded sections on parenterals, excipients, liposomes, and biopharmaceutics. Coverage incorporates all new dosage forms in the current USP Pharmacopoeia-National Formulary. Capsules and tablets are now covered in separate chapters. The thoroughly revamped illustration program includes new product and manufacturing equipment photographs.

    Reflecting the demands for entry-level accountants, the focus of this book is on fostering critical thinking skills, reducing emphasis on memorisation and encouraging more analysis and interpretation by requiring use of technology tools, spreadsheets and databases.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    Chapters cover cancer, infection, immune disorders, genetics, and disorders of each body system, highlighting pathophysiologic processes, resulting signs and symptoms, diagnostic test findings, and current treatments. Reader-friendly features include illustrations, checklists, and full-color miniguides illustrating the pathophysiology of specific disorders.This edition has new full-color miniguides on cancer pathophysiology and neuropathology. A new Focus on Genetics feature identifies gene-related discoveries and their implications for treatment or diagnosis. Review questions and answers follow current NCLEX-RN® requirements and alternate-format questions are included.

    Highlights of the book include realistic problems and examples from a wide range of application areas. New to this edition are: much sharper pedagogy; an increase in the number of examples; more thorough development of the concepts; a greater range of homework problems; a greater number and variety of worked out examples; expanded coverage of dynamics modelling and Laplace transform topics; and integration of MATLAB, including many examples that are formatted in MATLAB.

    College Writing Skills With Reading features John Langan's clear writing style and his wide range of writing assignments and activities that effectively reinforce the four essentials of good writing: unity, support, coherence, and sentence skills. This alternate version provides 25 entertaining and informative essays by professional writers.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    With this book, you'll learn how to load data, assemble and disassemble data objects, navigate R's environment system, write your own functions, and use all of R's programming tools.RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You'll gain valuable programming skills and support your work as a data scientist at the same time.Work hands-on with three practical data analysis projects based on casino gamesStore, retrieve, and change data values in your computer's memoryWrite programs and simulations that outperform those written by typical R usersUse R programming tools such as if else statements, for loops, and S3 classesLearn how to write lightning-fast vectorized R codeTake advantage of R's package system and debugging toolsPractice and apply R programming concepts as you learn them

    Verification that algorithms work is emphasized more than their complexity. An effective use of examples, and huge number of interesting exercises, demonstrate the topics of trees and distance, matchings and factors, connectivity and paths, graph coloring, edges and cycles, and planar graphs. For those who need to learn to make coherent arguments in the fields of mathematics and computer science.

    Intuition and computational abilities are stressed. Original material on DE and multiple integrals has been expanded.

    These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.

    Design patterns are time-tested solutions to recurring problems, letting the designer build programs on solutions that have already proved effective Provides developers with more than a dozen ASP.NET examples showing standard design patterns and how using them helpsbuild a richer understanding of ASP.NET architecture, as well as better ASP.NET applications Builds a solid understanding of ASP.NET architecture that can be used over and over again in many projects Covers ASP.NET code to implement many standard patterns including Model-View-Controller (MVC), ETL, Master-Master Snapshot, Master-Slave-Snapshot, Facade, Singleton, Factory, Single Access Point, Roles, Limited View, observer, page controller, common communication patterns, and more