krainaksiazek a dictionary of computer science 20052072
- znaleziono 6 produktów w 2 sklepach
Dictionary of Computer Science Oxford University Press
Książki / Literatura obcojęzyczna
Previously named A Dictionary of Computing, this bestselling dictionary has been renamed A Dictionary of Computer Science, and fully revised by a team of computer specialists, making it the most up-to-date and authoritative guide to computing available. Containing over 6,500 entries and with expanded coverage of multimedia, computer applications, networking, and personal computer science, it is a comprehensive reference work encompassing all aspects of the subject and is as valuable for home and office users as it is indispensable for students of computer science. Terms are defined in a jargon-free and concise manner with helpful examples where relevant. The dictionary contains approximately 150 new entries including cloud computing, cross-site scripting, iPad, semantic attack, smartphone, and virtual learning environment. Recommended web links for many entries, accessible via the Dictionary of Computer Science companion website, provide valuable further information and the appendices include useful resources such as generic domain names, file extensions, and the Greek alphabet. This dictionary is suitable for anyone who uses computers, and is ideal for students of computer science and the related fields of IT, maths, physics, media communications, electronic engineering, and natural sciences.
Elsevier's Dictionary of Automation Technics Elsevier Science Publishers
This dictionary contains 13,000 terms with more than 4,000 cross-references used in the following fields: automation, technology of management and regulation, computing machine and data processing, computer control, automation of industry, laser technology, theory of information and theory of signals, theory of algorithms and programming, philosophical bases of cybernetics, cybernetics and mathematical methods. Automation pertains to the theory, art, or technique of making a machine, a process or a device more fully automatic. Computers and information processing equipment play a large role in the automation of a process because of the inherent ability of a computer to develop decision that will, in effect, control or govern the process from the information received by the computer concerning the status of the process. Thus automation pertains to both the theory, and techniques of using automatic systems in industrial applications and the processes of investigation, design and conversion to automatic methods. Automatic control, automatic materials handling, automatic testing, automatic packaging, for continuous as well as batch processing, are all considered parts of the overall or completely automatic process. The Dictionary consists of two parts, Basic Table and Indexes. In the first part the English terms are listed alphabetically, numbered consecutively and followed by its German, French and Russian equivalents. English synonyms appear as cross-references to the main entries in their proper alphabetical order. The second part of the Dictionary, the Indexes, contains separate alphabetical indexes of the German, French and Russian terms. The reference number(s) with each term stands for the number of the English term(s) in the basic table. Elsevier's Dictionary of Automatic Technics will be a valuable tool for specialists, scientists, students and everyone who takes interest in the problems of investigation devoted to the design, development, and applications of methods and techniques for rendering a process of group of machines self-actuating, self-moving, or self-controlling.
Dictionary of Media and Communications M.E. Sharpe
Książki / Literatura obcojęzyczna
Presents a listing of media concepts, figures, and techniques with illustrations and historical commentaries. This dictionary includes terms related to psychology, linguistics, aesthetics, computer science, semiotics, culture theory, anthropology, and those that have relevance in media studies.
Beautiful Code O´REILLY
Książki / Literatura obcojęzyczna
How do the experts solve difficult problems in software development? In this unique and insightful book, leading computer scientists offer case studies that reveal how they found unusual, carefully designed solutions to high-profile projects. You will be able to look over the shoulder of major coding and design experts to see problems through their eyes. This is not simply another design patterns book, or another software engineering treatise on the right and wrong way to do things. The authors think aloud as they work through their project's architecture, the tradeoffs made in its construction, and when it was important to break rules. "Beautiful Code" is an opportunity for master coders to tell their story. All author royalties will be donated to Amnesty International. The book includes the following contributions: "Beautiful Brevity: Rob Pike's Regular Expression Matcher" by Brian Kernighan, Department of Computer Science, Princeton University; "Subversion's Delta Editor: Interface as Ontology" by Karl Fogel, editor of "QuestionCopyright.org", Co-founder of Cyclic Software, the first company offering commercial CVS support; "The Most Beautiful Code I Never Wrote" by Jon Bentley, Avaya Labs Research; "Finding Things" by Tim Bray, Director of Web Technologies at Sun Microsystems, co-inventor of XML 1. 0; "Correct, Beautiful, Fast (In That Order): Lessons From Designing XML Validators" by Elliotte Rusty Harold, Computer Science Department at Polytechnic University, author of "Java I/O, Java Network Programming", and "XML in a Nutshell" (O'Reilly); and, "The Framework for Integrated Test: Beauty through Fragility" by Michael Feathers, consultant at Object Mentor, author of "Working Effectively with Legacy Code" (Prentice Hall). It also includes: "Beautiful Tests" by Alberto Savoia, Chief Technology Officer, Agitar Software Inc; "On-the-Fly Code Generation for Image Processing" by Charles Petzold, author "Programming Windows and Code: The Hidden Language of Computer Hardware and Software" (both Microsoft Press); "Top Down Operator Precedence" by Douglas Crockford, architect at Yahoo! Inc, Founder and CTO of State Software, where he discovered JSON; "Accelerating Population Count" by Henry Warren, currently works on the Blue Gene petaflop computer project Worked for IBM for 41 years; "Secure Communication: The Technology of Freedom" by Ashish Gulhati, Chief Developer of Neomailbox, an Internet privacy service Developer of Cryptonite, an OpenPGP-compatible secure webmail system; and, "Growing Beautiful Code in BioPerl" by Lincoln Stein, investigator at Cold Spring Harbor Laboratory - develops databases and user interfaces for the Human Genome Project using the Apache server and its module API. It also includes: "The Design of the Gene Sorter" by Jim Kent, Genome Bioinformatics Group, University of California Santa Cruz; "How Elegant Code Evolves With Hardware: The Case Of Gaussian Elimination" by Jack Dongarra, University Distinguished Professor of Computer Science in the Computer Science Department at the University of Tennessee, also distinguished Research Staff member in the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) and Piotr Luszczek, Research Professor at the University of Tennessee; "Beautiful Numerics" by Adam Kolawa, co-founder and CEO of Parasoft; and, "The Linux Kernel Driver Model" by Greg Kroah-Hartman, SuSE Labs/Novell, Linux kernel maintainer for driver subsystems, author of "Linux Kernel in a Nutshell", co-author of "Linux Device Drivers, 3rd Edition" (O'Reilly). It also includes: "Another Level of Indirection" by Diomidis Spinellis, Associate Professor at the Department of Management Science and Technology at the Athens University of Economics and Business, Greece; "An Examination of Python's Dictionary Implementation" by Andrew Kuchling, longtime member of the Python development community, and a director of the Python Software Foundation; "Multi-Dimensional Iterators in NumPy" by Travis Oliphant, Assistant Professor in the Electrical and Computer Engineering Department at Brigham Young University; and, "A Highly Reliable Enterprise System for NASAs Mars Rover Mission" by Ronald Mak, co-founder and CTO of Willard & Lowe Systems, Inc, formerly a senior scientist at the Research Institute for Advanced Computer Science on contract to NASA Ames. It also includes: "ERP5: Designing for Maximum Adaptability" by Rogerio de Carvalho, researcher at the Federal Center for Technological Education of Campos (CEFET Campos), Brazil and Rafael Monnerat, IT Analyst at CEFET Campos, and an offshore consultant for Nexedi SARL; "A Spoonful of Sewage" by Bryan Cantrill, Distinguished Engineer at Sun Microsystems, where he has spent most of his career working on the Solaris kernel; "Distributed Programming with MapReduce" by Jeff Dean and Sanjay Ghemawat, Google Fellows in Google's Systems Infrastructure Group; "Beautiful Concurrency" by Simon Peyton Jones, Microsoft Research, key contributor to the design of the functional language Haskell, and lead designer of the Glasgow Haskell Compiler (GHC); and, "Syntactic Abstraction: The syntax-case expander" by Kent Dybvig, Developer of Chez Scheme and author of the Scheme Programming Language. It also includes: "Object-Oriented Patterns and a Framework for Networked Software" by William Otte, a Ph.D. student in the Department of Electrical Engineering and Computer Science (EECS) at Vanderbilt University and Doug Schmidt, Full Professor in the Electrical Engineering and Computer Science (EECS) Department, Associate Chair of the Computer Science and Engineering program, and a Senior Research Scientist at the Institute for Software Integrated Systems (ISIS) at Vanderbilt University; "Integrating Business Partners the RESTful Way" by Andrew Patzer, Director of the Bioinformatics Program at the Medical College of Wisconsin; and, "Beautiful Debugging" by Andreas Zeller, computer science professor at Saarland University, author of "Why Programs Fail: A Guide to Systematic Debugging" (Morgan Kaufman). It also includes: "Code That's Like an Essay" by Yukihiro Matsumoto, inventor of the Ruby language; "Designing Interfaces Under Extreme Constraints: the Stephen Hawking editor" by Arun Mehta, professor and chairman of the Computer Engineering department of JMIT, Radaur, Haryana, India; "Emacspeak: The Complete Audio Desktop" by TV Raman, Research Scientist at Google where he focuses on web applications; "Code in Motion" by Christopher Seiwald, founder and CTO of Perforce Software and Laura Wingerd, vice president of product technology at Perforce Software, author of "Practical Perforce" (O'Reilly); and, "Writing Programs for 'The Book'" by Brian Hayes who writes the Computing Science column in American Scientist magazine, author of "Infrastructure: A Field Guide to the Industrial Landscape"(W.W. Norton).
A Course in In-Memory Data Management Springer, Berlin
Książki / Literatura obcojęzyczna
Recent achievements in hardware and software development, such as multi-core CPUs and DRAM capacities of multiple terabytes per server, enabled the introduction of a revolutionary technology: in-memory data management. This technology supports the flexible and extremely fast analysis of massive amounts of enterprise data. Professor Hasso Plattner and his research group at the Hasso Plattner Institute in Potsdam, Germany, have been investigating and teaching the corresponding concepts and their adoption in the software industry for years. This book is based on an online course that was first launched in autumn 2012 with more than 13,000 enrolled students and marked the successful starting point of the openHPI e-learning platform. The course is mainly designed for students of computer science, software engineering, and IT related subjects, but addresses business experts, software developers, technology experts, and IT analysts alike. Plattner and his group focus on exploring the inner mechanics of a column-oriented dictionary-encoded in-memory database. Covered topics include - amongst others - physical data storage and access, basic database operators, compression mechanisms, and parallel join algorithms. Beyond that, implications for future enterprise applications and their development are discussed. Step by step, readers will understand the radical differences and advantages of the new technology over traditional row-oriented, disk-based databases. In this completely revised 2 nd edition, we incorporate the feedback of thousands of course participants on openHPI and take into account latest advancements in hard- and software. Improved figures, explanations, and examples further ease the understanding of the concepts presented. We introduce advanced data management techniques such as transparent aggregate caches and provide new showcases that demonstrate the potential of in-memory databases for two diverse industries: retail and life sciences.
Machine Learning Academic Press Inc
Książki / Literatura obcojęzyczna
This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches, which rely on optimization techniques, as well as Bayesian inference, which is based on a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as short courses on sparse modeling, deep learning, and probabilistic graphical models. * All major classical techniques: Mean/Least-Squares regression and filtering, Kalman filtering, stochastic approximation and online learning, Bayesian classification, decision trees, logistic regression and boosting methods.* The latest trends: Sparsity, convex analysis and optimization, online distributed algorithms, learning in RKH spaces, Bayesian inference, graphical and hidden Markov models, particle filtering, deep learning, dictionary learning and latent modeling.* Case studies - protein folding prediction, optical character recognition, text authorship identification, fMRI data analysis, change point detection, hyperspectral image unmixing, target localization, channel equalization and echo cancellation, show how the theory can be applied.* MATLAB code for all the main algorithms are available on an accompanying website, enabling the reader to experiment with the code.
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