This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.

    Now, security expert Brian Carrier has written the definitive reference for everyone who wants to understand and be able to testify about how file system analysis is performed. Carrier begins with an overview of investigation and computer foundations and then gives an authoritative, comprehensive, and illustrated overview of contemporary volume and file systems: Crucial information for discovering hidden evidence, recovering deleted data, and validating your tools. Along the way, he describes data structures, analyzes example disk images, provides advanced investigation scenarios, and uses today's most valuable open source file system analysis tools--including tools he personally developed. Coverage includes Preserving the digital crime scene and duplicating hard disks for dead analysis Identifying hidden data on a disk's Host Protected Area (HPA) Reading source data: Direct versus BIOS access, dead versus live acquisition, error handling, and more Analyzing DOS, Apple, and GPT partitions; BSD disk labels; and Sun Volume Table of Contents using key concepts, data structures, and specific techniques Analyzing the contents of multiple disk volumes, such as RAID and disk spanning Analyzing FAT, NTFS, Ext2, Ext3, UFS1, and UFS2 file systems using key concepts, data structures, and specific techniques Finding evidence: File metadata, recovery of deleted files, data hiding locations, and more Using The Sleuth Kit (TSK), Autopsy Forensic Browser, and related open source tools When it comes to file system analysis, no other book offers this much detail or expertise. Whether you're a digital forensics specialist, incident response team member, law enforcement officer, corporate security specialist, or auditor, this book will become an indispensable resource for forensic investigations, no matter what analysis tools you use.

    This edition explores the major concepts and theories of the psychology of bargaining and negotiation, and the dynamics of interpersonal and intergroup conflict and its resolution.

    The addition of lambda expressions (closures) and streams represents the biggest change to Java programming since the introduction of generics and annotations. Now, with Java SE 8 for the Really Impatient , internationally renowned Java author Cay S. Horstmann concisely introduces Java 8's most valuable new features (plus a few Java 7 innovations that haven't gotten the attention they deserve). If you're an experienced Java programmer, Horstmann's practical insights and sample code will help you quickly take advantage of these and other Java language and platform improvements. This indispensable guide includes Coverage of using lambda expressions (closures) to write computation "snippets" that can be passed to utility functions The brand-new streams API that makes Java collections far more flexible and efficient Major updates to concurrent programming that make use of lambda expressions (filter/map/reduce) and that provide dramatic performance improvements for shared counters and hash tables A full chapter with advice on how you can put lambda expressions to work in your own programs Coverage of the long-awaited introduction of a well-designed date/time/calendar library (JSR 310) A concise introduction to JavaFX, which is positioned to replace Swing GUIs, and to the Nashorn Javascript engine A thorough discussion of many small library changes that make Java programming more productive and enjoyable This is the first title to cover all of these highly anticipated improvements and is invaluable for anyone who wants to write tomorrow's most robust, efficient, and secure Java code.

    In cultivating a deep understanding and appreciation of Objective-C, its frameworks and ecosystem, one is able to create apps that delight and inspire users. Combining articles from NSHipster.com with new essays, this book is the essential guide for modern iOS and Mac OS X developers.

    She has since become one of our most respected authors of verse.Schnackenberg's first three books, collected in Supernatural Love, show the thrilling evolution of a unique voice in today's letters. From an early mastery in which precision and heartbreak are inseparable, her poetry accelerates book by book through the searching, dense, and metaphysical imagery--as well as the cascading syntax--which have become her signature. Whether we are witnessing her classic portrait of Darwin in his last year or discovering the vertiginous brillance of her elegy for the Byzantine monuments of Ravenna, we find in Schnackenberg gemlike poems offered as visionary documents, unmistakable in their glittering range and passion--and never the same twice.

    Another AI discovered a new antibiotic by analyzing molecular properties human scientists did not understand. Now, AI-powered jets are defeating experienced human pilots in simulated dogfights. AI is coming online in searching, streaming, medicine, education, and many other fields and, in so doing, transforming how humans are experiencing reality.In The Age of AI, three leading thinkers have come together to consider how AI will change our relationships with knowledge, politics, and the societies in which we live. The Age of AI is an essential roadmap to our present and our future, an era unlike any that has come before.

    “Big data” refers to our burgeoning ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena—from the price of airline tickets to the text of millions of books—into searchable form, and uses our increasing computing power to unearth epiphanies that we never could have seen before. A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, from the inevitable end of privacy as we know it to the prospect of being penalized for things we haven’t even done yet, based on big data’s ability to predict our future behavior.In this brilliantly clear, often surprising work, two leading experts explain what big data is, how it will change our lives, and what we can do to protect ourselves from its hazards. Big Data is the first big book about the next big thing.www.big-data-book.com

    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.

    Students will find concepts easy-to-understand through the clear writing style and full-color figures that illustrate current technology and trends. Examples and cases are drawn from actual systems projects that enable students to learn in the context of solving problems, much like the ones they will encounter on the job. This approach, combined with motivating tools such as the SCR Associates interactive Web-Based Case Study, Systems Analyst's Toolkit, the Student Study Tool on CD-ROM, and more, makes Systems Analysis and Design, Seventh Edition a wise and exciting choice for your introductory systems analysis and design class.

    Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of their organization’s massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you’ll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization. Provides a background in data science fundamentals before moving on to working with relational databases and unstructured data and preparing your data for analysis Details different data visualization techniques that can be used to showcase and summarize your data Explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques Includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark It’s a big, big data world out there – let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.

    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.

    By presenting actual experiences and analyzing them as they are described, the author conveys the developmental thought processes employed and shows a style of thinking that leads to successful results is something that can be learned. Along with spectacular successes, the author also conveys how failures contributed to shaping the thought processes. Provides the reader with a style of thinking that will enhance a person's ability to function as a problem-solver of complex technical issues. Consists of a collection of stories about the author's participation in significant discoveries, relating how those discoveries came about and, most importantly, provides analysis about the thought processes and reasoning that took place as the author and his associates progressed through engineering problems.

    With this long-awaited revision, the authors continue to present the theory in a concise and straightforward manner, now with an eye out for the practical applications. They have revised this book to make it more accessible to today's students, including the addition of more material on writing proofs, more figures and pictures to convey ideas, side-boxes to highlight other interesting material, and a less formal writing style. Exercises at the end of each chapter, including some new, easier exercises, help readers confirm and enhance their understanding of the material. *NEW! Completely rewritten to be less formal, providing more accessibility to todays students. *NEW! Increased usage of figures and pictures to help convey ideas. *NEW! More detail and intuition provided for definitions and proofs. *NEW! Provides special side-boxes to present supplemental material that may be of interest to readers. *NEW! Includes more exercises, including many at a lower level. *NEW! Presents program-like notation for PDAs and Turing machines. *NEW! Increas