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Books in Computer science

The Computing collection presents a range of foundational and applied content across computer and data science, including fields such as Artificial Intelligence; Computational Modelling; Computer Networks, Computer Organization & Architecture, Computer Vision & Pattern Recognition, Data Management; Embedded Systems & Computer Engineering; HCI/User Interface Design; Information Security; Machine Learning; Network Security; Software Engineering.

BooksJournals

    • Online Arab Spring

      • 1st Edition
      • December 3, 2014
      • Reza Jamali
      • English
      • Paperback
        9 7 8 1 8 4 3 3 4 7 5 7 6
      • eBook
        9 7 8 1 7 8 0 6 3 4 3 8 8
      What is the role of social media on fundamental change in Arab countries in the Middle East and North Africa? <I>Online Arab Spring</I> responds to this question, considering five countries: Egypt, Libya, Jordan, Yemen, and Tunisia, along with additional examples. The book asks why the penetration rate for social media differs in different countries: are psychological and social factors at play? Each chapter considers national identity, the legitimacy crisis, social capital, information and media literacy, and socialization. Religious attitudes are introduced as a key factor in social media, with Arabic countries in the Middle East and North Africa being characterized by Islamic trends. The insight gained will be helpful for analysing online social media effects internationally, and predicting future movements in a social context.

    • Advances in Software Science and Technology

      • 1st Edition
      • Volume 5
      • December 3, 2014
      • Tsutomu Kamimura
      • English
      • Paperback
        9 7 8 1 4 9 3 3 0 5 8 8 9
      • eBook
        9 7 8 1 4 8 3 2 9 4 3 2 2
      This serial is a translation of the original works within the Japan Society of Software Science and Technology. A key source of information for computer scientists in the U.S., the serial explores the major areas of research in software and technology in Japan. These volumes are intended to promote worldwide exchange of ideas among professionals.This volume includes original research contributions in such areas as Augmented Language Logic (ALL), distributed C language, Smalltalk 80, and TAMPOPO-an evolutionary learning machine based on the principles of Realtime Minimum Skyline Detection.

    • Joe Celko's SQL for Smarties

      • 5th Edition
      • December 2, 2014
      • Joe Celko
      • English
      • Paperback
        9 7 8 0 1 2 8 0 0 7 6 1 7
      • eBook
        9 7 8 0 1 2 8 0 0 8 3 0 0
      SQL for Smarties was hailed as the first book devoted explicitly to the advanced techniques needed to transform an experienced SQL programmer into an expert. Now, 20 years later and in its fifth edition, this classic reference still reigns supreme as the only book written by a SQL master that teaches programmers and practitioners to become SQL masters themselves! These are not just tips and techniques; also offered are the best solutions to old and new challenges. Joe Celko conveys the way you need to think in order to get the most out of SQL programming efforts for both correctness and performance.New to the fifth edition, Joe features new examples to reflect the ANSI/ISO Standards so anyone can use it. He also updates data element names to meet new ISO-11179 rules with the same experience-based teaching style that made the previous editions the classics they are today. You will learn new ways to write common queries, such as finding coverings, partitions, runs in data, auctions and inventory, relational divisions and so forth.SQL for Smarties explains some of the principles of SQL programming as well as the code. A new chapter discusses design flaws in DDL, such as attribute splitting, non-normal forum redundancies and tibbling. There is a look at the traditional acid versus base transaction models, now popular in NoSQL products. You’ll learn about computed columns and the DEFERRABLE options in constraints. An overview of the bi-temporal model is new to this edition and there is a longer discussion about descriptive statistic aggregate functions. The book finishes with an overview of SQL/PSM that is applicable to proprietary 4GL vendor extensions.

    • Advances in Software Science and Technology

      • 1st Edition
      • December 1, 2014
      • Teruo Hikita + 2 more
      • English
      • Paperback
        9 7 8 1 4 8 3 2 0 2 2 9 7
      • eBook
        9 7 8 1 4 8 3 2 1 5 7 2 3
      Advances in Software Science and Technology, Volume 4 provides information pertinent to the advancement of the science and technology of computer software. This book discusses the various applications for computer systems. Organized into two parts encompassing 10 chapters, this volume begins with an overview of the historical survey of programming languages for vector/parallel computers in Japan and describes compiling methods for supercomputers in Japan. This text then explains the model of a Japanese software factory, which is presented by the logical configuration that has been satisfied by the semantics of software engineering. Other chapters consider fluent joint as an algorithm that operates on relations organized as multidimensional linear hash files. The final chapter deals with the rules for submission of English papers that will be published, which includes papers that are reports of academic research by members of the Society. This book is a valuable resource for scientists, software engineers, and research workers.

    • Predictive Analytics and Data Mining

      • 1st Edition
      • November 27, 2014
      • Vijay Kotu + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 0 1 4 6 0 8
      • eBook
        9 7 8 0 1 2 8 0 1 6 5 0 3
      Put Predictive Analytics into ActionLearn the basics of Predictive Analysis and Data Mining through an easy to understand conceptual framework and immediately practice the concepts learned using the open source RapidMiner tool. Whether you are brand new to Data Mining or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, business intelligence and data warehousing professionals and for anyone who wants to learn Data Mining.You’ll be able to:1. Gain the necessary knowledge of different data mining techniques, so that you can select the right technique for a given data problem and create a general purpose analytics process.2. Get up and running fast with more than two dozen commonly used powerful algorithms for predictive analytics using practical use cases.3. Implement a simple step-by-step process for predicting an outcome or discovering hidden relationships from the data using RapidMiner, an open source GUI based data mining tool Predictive analytics and Data Mining techniques covered: Exploratory Data Analysis, Visualization, Decision trees, Rule induction, k-Nearest Neighbors, Naïve Bayesian, Artificial Neural Networks, Support Vector machines, Ensemble models, Bagging, Boosting, Random Forests, Linear regression, Logistic regression, Association analysis using Apriori and FP Growth, K-Means clustering, Density based clustering, Self Organizing Maps, Text Mining, Time series forecasting, Anomaly detection and Feature selection. Implementation files can be downloaded from the book companion site at www.LearnPredictiveA...

    • Foundations of Genetic Algorithms 1995 (FOGA 3)

      • 1st Edition
      • Volume 3
      • November 27, 2014
      • FOGA
      • English
      • Paperback
        9 7 8 1 4 9 3 3 0 6 1 7 6
      • eBook
        9 7 8 1 4 8 3 2 9 5 0 2 2
      Foundations of Genetic Algorithms, 3 focuses on the principles, methodologies, and approaches involved in the integration of genetic algorithm into mainstream mathematics, as well as genetic operators, genetic programming, and evolutionary algorithms. The selection first offers information on an experimental design perspective on genetic algorithms; schema theorem and price's theorem; and fitness variance of formae and performance prediction. Discussions focus on representation-indep... recombination, representation-indep... mutation and hill-climbing, recombination and the re-emergence of schemata, and Walsh transforms and deception. The publication then examines the troubling aspects of a building block hypothesis for genetic programming and order statistics for convergence velocity analysis of simplified evolutionary algorithms. The manuscript ponders on stability of vertex fixed points and applications; predictive models using fitness distributions of genetic operators; and modeling simple genetic algorithms for permutation problems. Topics include exact models for permutations, fitness distributions of genetic operators, predictive model based on linear fitness distributions, and stability in the simplex. The book also takes a look at the role of development in genetic algorithms and productive recombination and propagating and preserving schemata. The selection is a dependable source of data for mathematicians and researchers interested in genetic algorithms.

    • Data Architecture: A Primer for the Data Scientist

      • 1st Edition
      • November 26, 2014
      • W.H. Inmon + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 0 2 0 4 4 9
      • eBook
        9 7 8 0 1 2 8 0 2 0 9 1 3
      Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the existing systems (data warehousing systems). Taking a look at the larger picture into which Big Data fits gives the data scientist the necessary context for how pieces of the puzzle should fit together. Most references on Big Data look at only one tiny part of a much larger whole. Until data gathered can be put into an existing framework or architecture it can’t be used to its full potential. Data Architecture a Primer for the Data Scientist addresses the larger architectural picture of how Big Data fits with the existing information infrastructure, an essential topic for the data scientist. Drawing upon years of practical experience and using numerous examples and an easy to understand framework. W.H. Inmon, and Daniel Linstedt define the importance of data architecture and how it can be used effectively to harness big data within existing systems. You’ll be able to: Turn textual information into a form that can be analyzed by standard tools. Make the connection between analytics and Big Data Understand how Big Data fits within an existing systems environment Conduct analytics on repetitive and non-repetitive data

    • Face Detection and Recognition on Mobile Devices

      • 1st Edition
      • November 25, 2014
      • Haowei Liu
      • English
      • Paperback
        9 7 8 0 1 2 4 1 7 0 4 5 2
      • eBook
        9 7 8 0 1 2 4 1 7 1 2 8 2
      This hands-on guide gives an overview of computer vision and enables engineers to understand the implications and challenges behind mobile platform design choices. Using face-related algorithms as examples, the author surveys and illustrates how design choices and algorithms can be geared towards developing power-saving and efficient applications on resource constrained mobile platforms.

    • RDF Database Systems

      • 1st Edition
      • November 24, 2014
      • Olivier Curé + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 7 9 9 9 5 7 9
      • eBook
        9 7 8 0 1 2 8 0 0 4 7 0 8
      RDF Database Systems is a cutting-edge guide that distills everything you need to know to effectively use or design an RDF database. This book starts with the basics of linked open data and covers the most recent research, practice, and technologies to help you leverage semantic technology. With an approach that combines technical detail with theoretical background, this book shows how to design and develop semantic web applications, data models, indexing and query processing solutions.

    • Enterprise Business Intelligence and Data Warehousing

      • 1st Edition
      • November 24, 2014
      • Alan Simon
      • English
      • Paperback
        9 7 8 0 1 2 8 0 1 5 4 0 7
      • eBook
        9 7 8 0 1 2 8 0 1 7 4 6 3
      Corporations and governmental agencies of all sizes are embracing a new generation of enterprise-scale business intelligence (BI) and data warehousing (DW), and very often appoint a single senior-level individual to serve as the Enterprise BI/DW Program Manager. This book is the essential guide to the incremental and iterative build-out of a successful enterprise-scale BI/DW program comprised of multiple underlying projects, and what the Enterprise Program Manager must successfully accomplish to orchestrate the many moving parts in the quest for true enterprise-scale business intelligence and data warehousing. Author Alan Simon has served as an enterprise business intelligence and data warehousing program management advisor to many of his clients, and spent an entire year with a single client as the adjunct consulting director for a $10 million enterprise data warehousing (EDW) initiative. He brings a wealth of knowledge about best practices, risk management, organizational culture alignment, and other Critical Success Factors (CSFs) to the discipline of enterprise-scale business intelligence and data warehousing.

Related subjects

Applications

Artificial intelligence

Business intelligence

Computer systems organization

Computer vision and pattern recognition

Computing milieux

Data

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Hardware and architecture

Information systems

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Software

Theory and mathematics