Recent Advances in RSA Cryptography is of interest to graduate level students and researchers who will gain an insight into current research topics in the field and an overview of recent results in a unified way.
Recent Advances in RSA Cryptography is suitable as a secondary text for a graduate level course, and as a reference for researchers and practitioners in industry.
This book explores Steganography, as a means by which two or more parties may communicate using invisible or subliminal communication. "Steganalysis" is described as methods which can be used to break steganographic communication. This comprehensive resource also includes an introduction to watermarking and its methods, a means of hiding copyright data in images and discusses components of commercial multimedia applications that are subject to illegal use. This book demonstrates a working knowledge of watermarking’s pros and cons, and the legal implications of watermarking and copyright issues on the Internet.
In addition to being tightly organized by themes and a carefully selected group of contributors, the Editors will write introductory material to the sections along with introductory and concluding chapters. The result is a book that provides the field with the conceptual framework of mass customization, its tools, its solutions, and real-world examples of successful implementations of the business strategy. An important book for academics working in production operations, production manufacturing, industrial engineering, logistics, supply chain management, and industry practitioners.
Understanding the needs and desires of the customer are central to the strategy of mass customization. However, introducing customer needs into the realm of product development dramatically increases the level of complexity of creating and delivering the product both internally and externally. This book introduces an innovative model that assesses and distinguishes subjective and objective customer needs. This model along with other software tools and AI agents address the complexity issues that are both external and internal in a mass customization strategy. Fundamentally, the book— with its technical analysis, models, conceptual frameworks, and managerial tools—closes the gap between the complexity and the difficulty of mass customization with its potential payoffs and implementation.
The 27 revised full papers presented together with an invited paper were carefully reviewed and selected from 130 submissions. The papers are organized in topical sections on constraint databases, deductive databases, heterogenous and Web information systems, cross enterprise information systems, knowledge discovery, database modeling, XML and semistructured databases, physical database design and query evaluation, transaction management and workflow systems, query processing and data streams, spatial databases, and agents and mobile systems.
The 8 revised full technical papers presented together with 12 technical communications, and 16 extended abstracts were carefully reviewed and selected from 44 submissions.
The conference provides the opportunity to present a wider range of results and ideas that are of interest to the KI audience, including reports about recent own publications, position papers, and previews of ongoing work.
Based on the above reasoning, the editors identified key researchers and practitioners in each of the aforementioned categories and invited them to contribute a corresponding work to this book. However, as the authors’ contributions started to arrive, the editors also started to realize that although these categories participate in each chapter to different degrees, none of them can ever be totally obsolete from them. Moreover, it seems that theory and methods are inherent in the development of tools and applications and inversely the application is also inherent in the motivation and presentation of tools and methods.
The book begins with a summary of the nontechnical aspects of interviewing, such as common mistakes, strategies for a great interview, perspectives from the other side of the table, tips on negotiating the best offer, and a guide to the best ways to use EPI.
The technical core of EPI is a sequence of chapters on basic and advanced data structures, searching, sorting, broad algorithmic principles, concurrency, and system design. Each chapter consists of a brief review, followed by a broad and thought-provoking series of problems. We include a summary of data structure, algorithm, and problem solving patterns.
The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts.
The companion web site, algs4.cs.princeton.edu, containsAn online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material
The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants.
Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.
This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Inside, you'll learn about:
Interaction design and physical computingThe Arduino hardware and software development environmentBasics of electricity and electronicsPrototyping on a solderless breadboardDrawing a schematic diagram
And more. With inexpensive hardware and open-source software components that you can download free, getting started with Arduino is a snap. To use the introductory examples in this book, all you need is a USB Arduino, USB A-B cable, and an LED.
Join the tens of thousands of hobbyists who have discovered this incredible (and educational) platform. Written by the co-founder of the Arduino project, with illustrations by Elisa Canducci, Getting Started with Arduino gets you in on the fun! This 128-page book is a greatly expanded follow-up to the author's original short PDF that's available on the Arduino website.
Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it’s specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples
If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.What You Will LearnExplore how to use different machine learning models to ask different questions of your dataLearn how to build neural networks using Keras and TheanoFind out how to write clean and elegant Python code that will optimize the strength of your algorithmsDiscover how to embed your machine learning model in a web application for increased accessibilityPredict continuous target outcomes using regression analysisUncover hidden patterns and structures in data with clusteringOrganize data using effective pre-processing techniquesGet to grips with sentiment analysis to delve deeper into textual and social media dataIn Detail
Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.
Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization.Style and approach
Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
The Art of Computer Programming, Volumes 1-4A Boxed Set, 3/e
Art of Computer Programming, Volume 4, Fascicle 4,The: Generating All Trees--History of Combinatorial Generation: Generating All Trees--History of Combinatorial Generation
This multivolume work on the analysis of algorithms has long been recognized as the definitive description of classical computer science.The three complete volumes published to date already comprise a unique and invaluable resource in programming theory and practice. Countless readers have spoken about the profound personal influence of Knuth's writings. Scientists have marveled at the beauty and elegance of his analysis, while practicing programmers have successfully applied his “cookbook” solutions to their day-to-day problems. All have admired Knuth for the breadth, clarity, accuracy, and good humor found in his books.
To begin the fourth and later volumes of the set, and to update parts of the existing three, Knuth has created a series of small books called fascicles, which will be published at regular intervals. Each fascicle will encompass a section or more of wholly new or revised material. Ultimately, the content of these fascicles will be rolled up into the comprehensive, final versions of each volume, and the enormous undertaking that began in 1962 will be complete.
Volume 4, Fascicle 4
This latest fascicle covers the generation of all trees, a basic topic that has surprisingly rich ties to the first three volumes of The Art of Computer Programming. In thoroughly discussing this well-known subject, while providing 124 new exercises, Knuth continues to build a firm foundation for programming. To that same end, this fascicle also covers the history of combinatorial generation. Spanning many centuries, across many parts of the world, Knuth tells a fascinating story of interest and relevance to every artful programmer, much of it never before told. The story even includes a touch of suspense: two problems that no one has yet been able to solve.
Sams Teach Yourself SQL in 10 Minutes, Fourth Edition
New full-color code examples help you see how SQL statements are structured
Whether you're an application developer, database administrator, web application designer, mobile app developer, or Microsoft Office users, a good working knowledge of SQL is an important part of interacting with databases. And Sams Teach Yourself SQL in 10 Minutes offers the straightforward, practical answers you need to help you do your job.
Expert trainer and popular author Ben Forta teaches you just the parts of SQL you need to know–starting with simple data retrieval and quickly going on to more complex topics including the use of joins, subqueries, stored procedures, cursors, triggers, and table constraints.
You'll learn methodically, systematically, and simply–in 22 short, quick lessons that will each take only 10 minutes or less to complete.
With the Fourth Edition of this worldwide bestseller, the book has been thoroughly updated, expanded, and improved. Lessons now cover the latest versions of IBM DB2, Microsoft Access, Microsoft SQL Server, MySQL, Oracle, PostgreSQL, SQLite, MariaDB, and Apache Open Office Base. And new full-color SQL code listings help the beginner clearly see the elements and structure of the language.
10 minutes is all you need to learn how to...
Use the major SQL statements Construct complex SQL statements using multiple clauses and operators Retrieve, sort, and format database contents Pinpoint the data you need using a variety of filtering techniques Use aggregate functions to summarize data Join two or more related tables Insert, update, and delete data Create and alter database tables Work with views, stored procedures, and more Table of Contents
1 Understanding SQL
2 Retrieving Data
4 Filtering Data
5 Advanced Data Filtering
6 Using Wildcard Filtering
7 Creating Calculated Fields
8 Using Data Manipulation Functions
9 Summarizing Data
10 Grouping Data
11 Working with Subqueries
12 Joining Tables
13 Creating Advanced Joins
14 Combining Queries
15 Inserting Data
16 Updating and Deleting Data
17 Creating and Manipulating Tables
18 Using Views
19 Working with Stored Procedures
20 Managing Transaction Processing
21 Using Cursors
22 Understanding Advanced SQL Features
Appendix A: Sample Table Scripts
Appendix B: Working in Popular Applications
Appendix C : SQL Statement Syntax
Appendix E: SQL Reserved Words
Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you’ll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research.Develop a naïve Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a “whom to follow” recommendation system from Twitter data
Updated to reflect recent advances in MySQL and InnoDB performance, features, and tools, this third edition not only offers specific examples of how MySQL works, it also teaches you why this system works as it does, with illustrative stories and case studies that demonstrate MySQL’s principles in action. With this book, you’ll learn how to think in MySQL.Learn the effects of new features in MySQL 5.5, including stored procedures, partitioned databases, triggers, and viewsImplement improvements in replication, high availability, and clusteringAchieve high performance when running MySQL in the cloudOptimize advanced querying features, such as full-text searchesTake advantage of modern multi-core CPUs and solid-state disksExplore backup and recovery strategies—including new tools for hot online backups
Let's face it, SQL is a deceptively simple language to learn, and many database developers never go far beyond the simple statement: SELECT columns FROM table WHERE conditions. But there is so much more you can do with the language. In the SQL Cookbook, experienced SQL developer Anthony Molinaro shares his favorite SQL techniques and features. You'll learn about:
Window functions, arguably the most significant enhancement to SQL in the past decade. If you're not using these, you're missing out
Powerful, database-specific features such as SQL Server's PIVOT and UNPIVOT operators, Oracle's MODEL clause, and PostgreSQL's very useful GENERATE_SERIES function
Pivoting rows into columns, reverse-pivoting columns into rows, using pivoting to facilitate inter-row calculations, and double-pivoting a result set
Bucketization, and why you should never use that term in Brooklyn.
How to create histograms, summarize data into buckets, perform aggregations over a moving range of values, generate running-totals and subtotals, and other advanced, data warehousing techniques
The technique of walking a string, which allows you to use SQL to parse through the characters, words, or delimited elements of a string
Written in O'Reilly's popular Problem/Solution/Discussion style, the SQL Cookbook is sure to please. Anthony's credo is: "When it comes down to it, we all go to work, we all have bills to pay, and we all want to go home at a reasonable time and enjoy what's still available of our days." The SQL Cookbook moves quickly from problem to solution, saving you time each step of the way.
This highly versatile text provides mathematical background used in a wide variety of disciplines, including mathematics and mathematics education, computer science, biology, chemistry, engineering, communications, and business.
Some of the major features and strengths of this textbook
More than 1,600 exercises, ranging from elementary to challenging, are included with hints/answers to all odd-numbered exercises.
Descriptions of proof techniques are accessible and lively.
Students benefit from the historical discussions throughout the textbook.
Updated for the latest versions of this popular database, this edition covers many complex features that have been added to MySQL 5.0 and 5.1, including a section dedicated to stored procedures and triggers. After a brief introduction on installation and initial setup, the book explains: How to configure MySQL, such as setting the root passwordMySQL data types, including numerics, strings, dates, and complex typesSQL syntax, commands, data types, operators, and functionsArithmetic, comparison and logical operatorsAggregate and general functionsStored procedures and triggers, including procedure definition, procedure calls, procedure management, cursors, and triggersYou don't have time to stop and thumb through an exhaustive reference when you're hard at work. This portable and affordable guide is small enough to fit into your pocket, and gives you a convenient reference that you can consult anywhere. When you reach a sticking point and need to get to a solution quickly, the MySQL Pocket Reference is the book you want to have.
Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates
Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop.Get started quickly with an R tutorial and hundreds of examplesExplore R syntax, objects, and other language detailsFind thousands of user-contributed R packages online, including BioconductorLearn how to use R to prepare data for analysisVisualize your data with R’s graphics, lattice, and ggplot2 packagesUse R to calculate statistical fests, fit models, and compute probability distributionsSpeed up intensive computations by writing parallel R programs for HadoopGet a complete desktop reference to R
Inside, you’ll learn about:Interaction design and physical computing The Arduino hardware and software development environment Basics of electricity and electronics Prototyping on a solderless breadboard Drawing a schematic diagram
Getting started with Arduino is a snap. To use the introductory examples in this guide, all you need an Arduino Uno or earlier model, along with USB A-B cable and an LED. The easy-to-use Arduino development environment is free to download.
Join hundreds of thousands of hobbyists who have discovered this incredible (and educational) platform. Written by the co-founder of the Arduino project, Getting Started with Arduino gets you in on all the fun!
You’ll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques—classification, collaborative filtering, and anomaly detection among others—to fields such as genomics, security, and finance. If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you’ll find these patterns useful for working on your own data applications.
Patterns include:Recommending music and the Audioscrobbler data setPredicting forest cover with decision treesAnomaly detection in network traffic with K-means clusteringUnderstanding Wikipedia with Latent Semantic AnalysisAnalyzing co-occurrence networks with GraphXGeospatial and temporal data analysis on the New York City Taxi Trips dataEstimating financial risk through Monte Carlo simulationAnalyzing genomics data and the BDG projectAnalyzing neuroimaging data with PySpark and Thunder