Posts Tagged ‘ pdf ’

Applied Mathematics for Database Professionals by Lex de Haan

Relational databases hold data, right? They indeed do, but to think of a database as nothing more than a container for data is to miss out on the profound power that underlies relational technology. A far more powerful way of thinking lies in relational technologys foundation in the mathematical disciplines of logic and set theory.

Databases contain truths or propositions describing some area of interest such as a business. Those truths are organized into sets. Operations from logic and set theory can be applied to existing sets of truths to derive new sets of truths. Applied Mathematics for Database Professionals introduces you to this way of thinking, to the logic and set theory that underlies relational database technology. All this may sound abstract now, but there are profound benefits from the deeper understanding youll gain from this book. Youll learn to

  • Become a better database designer. Youll make fewer mistakes, and your designs will be more flexible in response to changing data needs.
  • Use the expressive power of mathematics to precisely specify designs and business rules.
  • Communicate effectively about design using the universal language of mathematics.
  • Develop and write complex SQL statements with confidence.
  • Avoid pitfalls and problems from common relational bugaboos such as null values and duplicate rows.

The math that you learn in this book will put you above the level of understanding of most database professionals today. Youll better understand the technology and be able to apply it more effectively. Youll avoid data anomalies like redundancy and inconsistency. Understanding whats in this book will take your mastery of relational technology to heights you may not have thought possible.

This book is reviewed and endorsed by C. J. Date and features a foreword by the same.

Apress | 376 pages | 2.81 MB | english | ISBN-10: 1590597451 | ISBN-13: 978-1590597453 | PDF | 2007

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Quantum Communications and Cryptography by Sergienko

All current methods of secure communication such as public-key cryptography can eventually be broken by faster computing. At the interface of physics and computer science lies a powerful solution for secure communications: quantum cryptography. Because eavesdropping changes the physical nature of the information, users in a quantum exchange can easily detect eavesdroppers. This allows for totally secure random key distribution, a central requirement for use of the one-time pad. Since the one-time pad is theoretically proven to be undecipherable, quantum cryptography is the key to perfect secrecy.

Quantum Communications and Cryptography is the first comprehensive review of the past, present, and potential developments in this dynamic field. Leading expert contributors from around the world discuss the scientific foundations, experimental and theoretical developments, and cutting-edge technical and engineering advances in quantum communications and cryptography.

The book describes the engineering principles and practical implementations in a real-world metropolitan network as well as physical principles and experimental results of such technologies as entanglement swapping and quantum teleportation. It also offers the first detailed treatment of quantum information processing with continuous variables. Technologies include both free-space and fiber-based communications systems along with the necessary protocols and information processing approaches.

Bridging the gap between physics and engineering, Quantum Communications and Cryptography supplies a springboard for further developments and breakthroughs in this rapidly growing area.

crc press | 248 pages | 3.68 MB | english | ISBN-10: 0849336848 | ISBN-13: 978-0849336843 | PDF | 2005

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Codes: The Guide to Secrecy From Ancient to Modern Times by Richard A. Mollin

From the Rosetta Stone to public-key cryptography, the art and science of cryptology has been used to unlock the vivid history of ancient cultures, to turn the tide of warfare, and to thwart potential hackers from attacking computer systems. Codes: The Guide to Secrecy from Ancient to Modern Times explores the depth and breadth of the field, remaining accessible to the uninitiated while retaining enough rigor for the seasoned cryptologist.

The book begins by tracing the development of cryptology from that of an arcane practice used, for example, to conceal alchemic recipes, to the modern scientific method that is studied and employed today. The remainder of the book explores the modern aspects and applications of cryptography, covering symmetric- and public-key cryptography, cryptographic protocols, key management, message authentication, e-mail and Internet security, and advanced applications such as wireless security, smart cards, biometrics, and quantum cryptography. The author also includes non-cryptographic security issues and a chapter devoted to information theory and coding. Nearly 200 diagrams, examples, figures, and tables along with abundant references and exercises complement the discussion.

Written by leading authority and best-selling author on the subject Richard A. Mollin, Codes: The Guide to Secrecy from Ancient to Modern Times is the essential reference for anyone interested in this exciting and fascinating field, from novice to veteran practitioner. ———————Features——————— · Presents self-contained, thorough, and vibrantly illustrated coverage accessible to both professionals and laypersons · Provides an intuitive approach with illustrations to provide an overview of the topics for the general reader that does not require a mathematical approach · Incorporates more than 200 footnotes and 300 references for access to more in-depth information and further reading · Contains all necessary mathematics, requisite probability theory, and exercises organized by chapter in the appendices

Chapman and Hall/CRC | 704 pages | 5.39 MB | english | ISBN-10: 1584884703 | ISBN-13: 978-1584884705 | PDF | 2005

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Introduction to Machine Learning by Ethem Alpaydin

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. In order to present a unified treatment of machine learning problems and solutions, it discusses many methods from different fields, including statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and data mining. All learning algorithms are explained so that the student can easily move from the equations in the book to a computer program.

The text covers such topics as supervised learning, Bayesian decision theory, parametric methods, multivariate methods, multilayer perceptrons, local models, hidden Markov models, assessing and comparing classification algorithms, and reinforcement learning. New to the second edition are chapters on kernel machines, graphical models, and Bayesian estimation; expanded coverage of statistical tests in a chapter on design and analysis of machine learning experiments; case studies available on the Web (with downloadable results for instructors); and many additional exercises. All chapters have been revised and updated.

Introduction to Machine Learning can be used by advanced undergraduates and graduate students who have completed courses in computer programming, probability, calculus, and linear algebra. It will also be of interest to engineers in the field who are concerned with the application of machine learning methods.

Publisher: The MIT Press | 584 pages | English | ISBN-10: 026201243X | ISBN-13: 978-0262012430 | PDF | 2004

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