Books by Subject
- 2007 Microsoft Office system plain & ...
- — Human-computer interaction handbook. ...
- Image and signal processing for netwo...
- — Pervasive computing in healthcare ......
- Photoshop CS A to Z ....................
- — XSLT cookbook. 2nd ed. .................
- Photoshop CS A to Z 2004, books24x7, SUNet ID login required.
- Photoshop CS for dummies 2004, books24x7, SUNet ID login required.
- Photoshop CS3 bible 2007, books24x7, SUNet ID login required.Fulltext ProQuest Safari
- Practical biomedical signal analysis using MATLAB 2012, CRCnetBASE
- Practical data mining 2012, CRCnetBASEWhat is data mining and what can it do? -- The data mining process -- Problem definition (Step 1) -- Data evaluation (Step 2) -- Feature extraction and enhancement (Step 3) -- Prototyping plan and model development (Step 4) -- Model evaluation (Step 5) -- Implementation (Step 6) -- Supervised learning Genre section 1 - Detecting and characterizing known patterns -- Forensic analysis Genre Section 2 -Detecting, characterizing, and exploiting hidden patterns -- Genre Section 3 - Knowledge : Its acquisition, representation, and use.
- Practical guide to clinical data management. 2nd ed. 2007, CRCnetBASE
- Practical SQL handbook. 4th ed. 2001, ProQuest SafariSQL and relational database management -- Designing databases -- Creating and filling a database -- Selecting data from the database -- Sorting data and other selection techniques -- Grouping data and reporting from it -- Joining tables for comprehensive data analysis -- Structuring queries with subqueries -- Creating and using views -- Security, transactions, performance, and integrity -- Solving business problems.
- Part 1.Principles of Health Interoperability --The Health Information Revolution --Why Interoperability is Hard --Models --UML and XML --Privacy --Standards Development Organizations --Part 2.HL7 and Interchange Formats --HL7 Version 2 --The HL7 V3 RIM --Constrained Information Models --Clinical Document Architecture --HL7 Dynamic Model --IHE XDS --Part 3.SNOMED and Terminology --Clinical Terminology --Coding and Classification Schemes --SNOMED CT --SNOMED CT Concept Model --Using SNOMED and HL7 Together.
- Pro SharePoint solution development 2007, Springer
- Probing experience 2008, Springer
- Progamming ArcObjects with VBA 2005, CRCnetBASE
- Programming collective intelligence 2007, ProQuest Safari
- Programming graphical user interfaces in R 2012, CRCnetBASE"Preface About this book Two common types of user interfaces in statistical computing are the command line interface (CLI) and the graphical user interface (GUI). The usual CLI consists of a textual console in which the user types a sequence of commands at a prompt, and the output of the commands is printed to the console as text. The R console is an example of a CLI. A GUI is the primary means of interacting with desktop environments, such as Windows and Mac OS X, and statistical software, such as JMP. GUIs are contained within windows, and resources, such as documents, are represented by graphical icons. User controls are packed into hierarchical drop-down menus, buttons, sliders, etc. The user manipulates the windows, icons, and menus with a pointer device, such as a mouse. The R language, like its predecessor S, is designed for interactive use through a command line interface (CLI), and the CLI remains the primary interface to R. However, the graphical user interface (GUI) has emerged as an effective alternative, depending on the specific task and the target audience. With respect to GUIs, we see R users falling into three main target audiences: those who are familiar with programming R, those who are still learning how to program, and those who have no interest in programming. On some platforms, such as Windows and Mac OS X, R has graphical front-ends that provide a CLI through a text console control. Similar examples include the multi-platform RStudioTM IDE, the Java-based JGR and the RKWard GUI for the Linux KDE desktop. Although these interfaces are GUIs, they are still very much in essence CLIs, in that the primary mode of interacting with R is the same. Thus, these GUIs appeal mostly to those who are comfortable with R programming"--Provided by publisher.
- Python cookbook. 2nd ed. 2005, ProQuest Safari
- Python for bioinformatics 2010, CRCnetBASEI. PROGRAMMING. 1. Introduction -- 2. First Steps with Python -- 3. Basic Programming: Data Types -- 4. Programming: Flow Control -- 5. Dealing with Files -- 6. Code Modularizing -- 7. Error Handling -- 8. Introduction to Object Orienting Programming (OOP) -- 9. Regular Expressions --- II. BIOPYTHON. 10. Introduction to Biopython --- III. ADVANCED TOPICS. 11. Web Applications -- 12. XML -- 13. Python and Databases -- 14. Collaborative Development: Version Control --- IV. PYTHON RECIPES WITH COMMENTED SOURCE CODE. 15. Sequence Manipulation in Batch -- 16. Web Application for Filtering Vector Contamination -- 17. Searching for PCR Primers Using Primer3 -- 18. Calculating Melting Temperature from a Set of Primers -- 19. Filtering out Specific Fields from a Genbank File -- 20. Converting XML Blast File into HTML -- 21. Inferring Splicing Sites -- 22. DNA Mutations with Restrictions -- 23. Web Server for Multiple Alignment -- 24. Drawing Marker Positions Using Data Stored in a Database --- Appendixes. A. Python and Biopython Installation -- B. Selected Papers -- C. Included DVD: Virtual Machine Installation and Use -- D. Python Language Reference -- E. Answers to Odd-Numbered Questions -- F. Python Style Guide.
- Querying XML 2006, ScienceDirectXML -- Querying -- Querying XML -- Metadata, an overview -- Structural metadata -- The XML information set (Infoset) and beyond -- Managing XML : transforming and connecting -- Storing : XML and databases -- XPath 1.0 and XPath 2.0 -- Introduction to XQuery 1.0 -- XQuery 1.0 definition -- What's missing? -- XQuery APIs -- SQL/XML -- XML-derived markup languages -- Internationalization : putting the "W" in "WWW" -- Finding stuff.
- R book 2007, WileyPreface --1.Getting started --2.Essentials of the R language --3.Data input --4.Dataframes --5.Graphics --6.Tables --7.Mathematics --8.Classical tests --9.Statistical modelling --10.Regression --11.Analysis of variance --12.Analysis of covariance --13.Generalized linear models --14.Count data --15.Count data in tables --16.Proportion data --17.Binary response variables --18.Generalized additive models --19.Mixed-effects models --20.Non-linear regression --21.Tree models --22.Time series analysis --23.Multivariate statistics --24.Spatial statistics --25.Survival analysis --26.Simulation models --27.Changing the look of graphics --References and further reading --Index.
- R companion to linear statistical models 2012, CRCnetBASE"Focusing on user-developed programming, An R Companion to Linear Statistical Models serves two audiences: Those who are familiar with the theory and applications of linear statistical models and wish to learn or enhance their skills in R; and those who are enrolled in an R-based course on regression and analysis of variance. For those who have never used R, the book begins with a self-contained introduction to R that lays the foundation for later chapters.This book includes extensive and carefully explained examples of how to write programs using the R programming language. These examples cover methods used for linear regression and designed experiments with up to two fixed-effects factors, including blocking variables and covariates. It also demonstrates applications of several pre-packaged functions for complex computational procedures"-- Provided by publisher."Preface This work (referred to as Companion from here on) targets two primary audiences: Those who are familiar with the theory and applications of linear statistical models and wish to learn how to use R or supplement their abilities with R through unfamiliar ideas that might appear in this Companion; and those who are enrolled in a course on linear statistical models for which R is the computational platform to be used. About the Content and Scope While applications of several pre-packaged functions for complex computational procedures are demonstrated in this Companion, the focus is on programming with applications to methods used for linear regression and designed experiments with up to two fixed-effects factors, including blocking variables and covariates. The intent in compiling this Companion has been to provide as comprehensive a coverage of these topics as possible, subject to the constraint on the Companion's length. The reader should be aware that much of the programming code presented in this Companion is at a fairly basic level and, hence, is not necessarily very elegant in style. The purpose for this is mainly pedagogical; to match instructions provided in the code as closely as possible to computational steps that might appear in a variety of texts on the subject. Discussion on statistical theory is limited to only that which is necessary for computations; common "rules of thumb" used in interpreting graphs and computational output are provided. An effort has been made to direct the reader to resources in the literature where the scope of the Companion is exceeded, where a theoretical refresher might be useful, or where a deeper discussion may be desired. The bibliography lists a reasonable starting point for further references at a variety of levels"-- Provided by publisher.
- R cookbook. 1st ed. 2011, ProQuest Safari
- R graphics 2006, CRCnetBASE
- R graphics. 2nd ed. 2011, CRCnetBASEAn introduction to R graphics -- Traditional graphics. Simple usage of traditional graphics -- Customizing traditional graphics -- Grid graphics. Trellis graphics : the lattice package -- The grammar of graphics : the ggplot2 package -- The grid graphics model -- The grid graphics object model -- Developing new graphics functions and objects -- The graphics engine. Graphics formats -- Graphical parameters -- Graphics packages. Graphics extensions -- Plot extensions -- Graphics for categorical data -- Maps -- Node-and-edge graphs -- 3D graphics -- Dynamic and interactive graphics -- Importing graphics -- Combining graphics systems.
- R graphs cookbook 2011, ProQuest Safari
- R in a nutshell 2010, ProQuest Safari
- R primer 2012, CRCnetBASE
- Rapid contextual design 2005, ScienceDirect
- Real-time systems 2002, Wileych. 1. Introduction, p. 1-9 -- ch. 2. Analysis and Verification of Non-Real-Time Systems, p. 10-40 -- ch. 3. Real-Time Scheduling and Schedulability Analysis, p. 41-85 -- ch. 4. Model Checking of Finite-State Systems, p. 86-133 -- ch. 5. Visual Formalism, Statecharts, and Statemate, p. 134-147 -- ch. 6. Real-Time Logic, Graph-Theoretic Analysis, and Modechart, p. 148-186 -- ch. 7. Verification Using Timed Automata, p. 187-211 -- ch. 8. Timed Petri Nets, p. 212-236 -- ch. 9. Process Algebra, p. 237-258 -- ch. 10. Design and Analysis of Propositional-Logic Rule-Based Systems, p. 259-366 -- ch. 11. Timing Analysis of Predicate-Logic Rule-Based Systems, p. 367-435 -- ch. 12. Optimization of Rule-Based Systems, p. 436-465.
- Regression modeling 2009, CRCnetBASEReview of fundamental of statistics -- Bivariate linear regression and correlation -- Misspecified disturbance terms -- Nonparametric regression -- Logistic regression -- Bayesian regression -- Robust regression -- Fuzzy regression -- Random coefficients regression -- L1 and q-Quantile regression -- Regression in a spatial domain -- Multiple regression -- Normal correlation models -- Ridge regression -- Indicator variables -- Polynomial model estimation -- Semiparametric regression -- Nonlinear regression -- Issues in time series modeling and estimation.
- Relevance of the time domain to neural network models 2012, SpringerIntroduction -- Adaptation and contraction theory for the synchronization of complex neural networks -- Temporal coding is not only about cooperation, it is also about competition -- Using non-oscillatory dynamics to disambiguate pattern mixtures -- Functional constraints on network topology via generalized sparse -- Evolution of time in neural networks, from the present to the past, and forward to the future -- Synchronization of coupled pulse-type hardware neuron models for CPG model -- A univesal abstract-time platform for real-time neural networks -- Solving complex control tasks via simple rule(s), using chaotic dynamics in a recurrent neural network model -- Time scale analysis of neuronal ensemble data used to feed neural network models -- Simultaneous EEG-fMRI, integrating spatial and temporal resolution -- Erratum to: Time scale analysis of neuronal ensemble data used to feed neural network models.
- Ruby in a nutshell 2002, ProQuest Safari
- Running Linux. 5th ed. rev. & expanded / 2006, ProQuest Safari
- SAS and R 2010, CRCnetBASE
- SAS for dummies 2007, books24x7, SUNet ID login required.Fulltext ProQuest Safari
- SAS functions by example. 2nd ed. 2010, ProQuest SafariFulltext SUNet ID login required. books24x7Character functions -- Perl regular expressions -- Sort functions -- Date and time functions -- Array functions -- Truncation functions -- Descriptive statistics functions -- Mathematical and numeric functions -- Random number functions -- Special functions -- State and ZIP code functions -- Trigonometric functions -- Macro functions -- SAS file I/O functions -- Variable information functions -- Bitwise logical functions.
- SAS programming 2004, CRCnetBASE
- Scientific and statistical database management 2008, Springer
- Scientific imaging with Photoshop 2008, ProQuest Safari
- SharePoint 2003 user's guide Springer
- SharePoint 2007 user's guide Springer
- Signal analysis 2004, Wileych. 1. Signals: Analog, Discrete, and Digital, p. 1-108 -- ch. 2. Discrete Systems and Signal Spaces, p. 109-172 -- ch. 3. Analog Systems and Signal Spaces, p. 173-272 -- ch. 4. Time-Domain Signal Analysis, p. 273-382 -- ch. 5. Fourier Transforms of Analog Signals, p. 383-439 -- ch. 6. Generalized Fourier Transforms of Analog Signals, p. 440-481 -- ch. 7. Discrete Fourier Transforms, p. 482-553 -- ch. 8. The z-Transform, p. 554-584 -- ch. 9. Frequency-Domain Signal Analysis, p. 585-711 -- ch. 10. Time-Frequency Signal Transforms, p. 712-801 -- ch. 11. Time-Scale Signal Transforms, p. 802-872 -- ch. 12. Mixed-Domain Signal Analysis, p. 873-927.
- Simulation training in laparoscopy and robotic surgery 2012, SpringerLessons Learned from the Aviation Industry: Surgical Checklists /Stig Müller and Hitendra R. H. Patel --Human Factors, Nontechnical Skills, and Surgical Training /Stig Müller, Waleed Al-Singary and Hitendra R. H. Patel --Current State of Laparoscopic and Robotic Surgery /Jens J. Rassweiler, Marcel Hruza, Thomas Frede and Salvatore Micali --Simulation and Training in Minimally Invasive Surgery /Sonal Arora, Shabnam Undre and Roger Kneebone --Value of Virtual Reality in Medical Education /Amina A. Bouhelal, Hitendra R. H. Patel and Bijendra Patel --The MIMIC Virtual Reality Trainer: Stepping into Three-Dimensional, Binocular, Robotic Simulation /Steven M. Lucas and Chandru P. Sundaram --Laparoscopic Cholecystectomy Skills Acquisition and Procedural Proficiency in Novices Using Virtual Reality /Amina A. Bouhelal, Hitendra R. H. Patel and Bijendra Patel --Lesson Learnt from the Military Surgeons Using Simulation in Trauma Surgery /Simon S. Fleming and John-Joe Reilly --Clinical and Educational Benefits of Surgical Telementoring /Knut Mague Augestad, Taridzo Chomutare, Johan G. Bellika, Andrius Budrionis and Rolv-Ole Lindsetmo, et al. --Portable Learning and Multimedia in Surgical Training /Narinderjit Singh Kullar, Stig Müller and Hitendra R. H. Patel.
- Software solutions for engineers and scientists 2008, CRCnetBASE
- This book details a model of consciousness supported by scientific experimental data from the human brain. It presents how the Corollary Discharge of Attention Movement (CODAM) neural network model allows for a scientific understanding of consciousness as well as provides a solution to the Mind-Body problem. The book provides readers with a general approach to consciousness that is powerful enough to lead to the inner self and its ramifications for the vast range of human experiences. It also offers an approach to the evolution of human consciousness and features chapters on mental disease (especially schizophrenia) and on meditative states (including drug-induced states of mind). Solving the Mind-Body Problem bridges the gap that exists between philosophers of mind and the neuroscience community, allowing the enormous weight of theorizing on the nature of mind to be brought to earth and put under the probing gaze of the scientific facts of life and mind.
- SQL cookbook 2006, ProQuest SafariRetrieving records --Sorting query results --Working with multiple tables --Inserting, updating, deleting --Metadata queries --Working with strings --Working with numbers --Date arithmetic --Date manipulation --Working with ranges --Advanced searching --Reporting and warehousing --Hierarchical queries --Odds 'n' ends.
- SQL for dummies. 6th ed. 2006, SUNet ID login required to search for this title
- SQL functions programmer's reference 2005, books24x7, SUNet ID login required.
- Statistical analysis with Excel for dummies 2005, books24x7, SUNet ID login required.
- Statistical data mining using SAS applications. 2nd ed. 2010, CRCnetBASE
- Statistical learning and data science 2012, CRCnetBASE"Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become mainstream. Unsupervised data analysis, including cluster analysis, factor analysis, and low dimensionality mapping methods continually being updated, have reached new heights of achievement in the incredibly rich data world that we inhabit.Statistical Learning and Data Science is a work of reference in the rapidly evolving context of converging methodologies. It gathers contributions from some of the foundational thinkers in the different fields of data analysis to the major theoretical results in the domain. On the methodological front, the volume includes conformal prediction and frameworks for assessing confidence in outputs, together with attendant risk. It illustrates a wide range of applications, including semantics, credit risk, energy production, genomics, and ecology. The book also addresses issues of origin and evolutions in the unsupervised data analysis arena, and presents some approaches for time series, symbolic data, and functional data. Over the history of multidimensional data analysis, more and more complex data have become available for processing. Supervised machine learning, semi-supervised analysis approaches, and unsupervised data analysis, provide great capability for addressing the digital data deluge. Exploring the foundations and recent breakthroughs in the field, Statistical Learning and Data Science demonstrates how data analysis can improve personal and collective health and the well-being of our social, business, and physical environments. "--Provided by publisher.
- Stochastic relations 2007, CRCnetBASE
- Succinct guide to Windows users migrating to the Mac.
- Taking your iPhone to the max 2008, SpringerA guide to the iPhone discusses the features of the device, including the iPhone media and the QWERTY keyboard, as well as its e-mail, voicemail, and calendar functions; Internet connectivity and applications; third-party software to enhance the iPhone; iTunes, iBooks, and iPhone games; power user applications; and accessories
- Teach yourself visually iPad 2010, ProQuest SafariExploring the iPad -- Understanding what you can do with your iPad -- Configuring the iPad -- Getting the most from the internet -- Maximizing email on the iPad -- Syncing the iPad -- Getting the most from iTunes and photos -- Getting the most from YouTube and iBooks -- Managing contacts and appointments -- Simplifying your life with the iPad -- Enhance your iPad with the app store -- Maintaining and troubleshooting the iPad.
- Tech mining 2005, WileyPart I. Understanding Tech Mining -- Chapter 1. Technological Innovation and the Need for Tech Mining , p. 2-15 -- Chapter 2. How Tech Mining Works, p. 17-32 -- Chapter 3. What Tech Mining Can Do for You, p. 33-40 -- Chapter 4. Example Results. Fuel Cells Tech Mining, p. 41-50 -- Chapter 5. What to Watch for in Tech Mining, p. 51-66 -- Part II. Doing Tech Mining -- Chapter 7. Forming the Right Query, p. 95-111 -- Chapter 8. Getting the Data, p. 113-127 -- Chapter 9. Basic Analyses, p. 129-154 -- Chapter 10. Advanced Analyses, p. 155-186 -- Chapter 11. Trend Analyses, p. 187-214 -- Chapter 12. Patent Analyses, p. 215-248 -- Chapter 13. Generating and Presenting Innovation Indicators, p. 249-288 -- Chapter 14. Managing the Tech Mining Process, p. 289-306 -- Chapter 15. Measuring Tech Mining Results, p. 307-320 -- Chapter 16. Example Process. Tech Mining on Fuel Cells, p. 321-354 -- Appendix A. Selected Publication and Patent Databases, p. 355-359 -- Appendix B. Text Mining Software, p. 361-362 -- Appendix C. What You Can Do without Tech Mining Software, p. 363-364 -- Appendix D. Statistics and Distributions for Analyzing Text Entities, p. 365-368.
- Telehealthcare computing and engineering 2013, CRCnetBASEPt. 1. System : tele-healthcare monitoring networks -- pt. 2. Hardware : medical sensors and devices -- pt. 3. Software : medical signal processing -- pt. 4. Others : medical security and privacy.
- Teleneurology by Internet and telephone 2011, Springer
- Testing computer systems for FDA/MHRA compliance 2004, CRCnetBASE
- ch. 1. Parallel and distributed computing / S. Hariri and M. Parashar -- ch. 2. Message-passing tools / S. Hariri and I. Ra -- ch. 3. Distributed shared memory tools / M. Parashar and S. Chandra -- ch. 4. Distributed-object computing tools / R. Raje, A. Kalyanaraman, and N. Nayani -- ch. 5. Gestalt of the grid / G. von Laszewski and P. Wagstrom -- ch. 6. Software development for parallel and distributed computing / M. Parashar and S. Hariri.
- UML for developing knowledge management systems 2006, CRCnetBASE
- Understanding MySQL internals 2007, ProQuest Safari
- Understanding your users 2004, ScienceDirectIntroduction to user requirements -- Before you choose an activity : learning about your product and users -- Ethical and legal considerations -- Setting up facilities for your user requirements activity -- Preparing for your user requirements activity -- During your user requirements activity -- Interviews -- Surveys -- Wants and needs analysis -- Card sorting -- Group task analysis -- Focus groups -- Studies -- Concluding your activity.
- Undocumented secrets of MATLAB-Java programming 2012, CRCnetBASE"Preface The Matlab programming environment uses Java for numerous tasks, including networking, data-processing algorithms, and graphical user-interface (GUI). Matlab's internal Java classes can often be easily accessed and used by Matlab users. Matlab also enables easy access to external Java functionality, either third-party or user-created. Using Java, we can extensively customize the Matlab environment and application GUI, enabling the creation of very esthetically pleasing applications. Unlike Matlab's interface with other programming languages, the internal Java classes and the Matlab-Java interface were never fully documented by The MathWorks (TMW), the company that manufactures the Matlab product. This is really quite unfortunate: Java is one of the most widely used programming languages, having many times as many programmers as Matlab. Using this huge pool of knowledge and components can significantly improve Matlab applications. As a consultant, I often hear clients claim that Matlab is a fine programming platform for prototyping, but is not suitable for real-world modern-looking applications. This book aimed at correcting this misconception. It shows how using Java can significantly improve Matlab program appearance and functionality and that this can be done easily and even without any prior Java knowledge. In fact, many basic programming requirements cannot be achieved (or are difficult) in pure Matlab, but are very easy in Java. As a simple example, maximizing and minimizing windows is not possible in pure Matlab, but is a trivial one-liner using the underlying Java codeʹ:"--Provided by publisher.
- Unified modeling language reference manual. 2nd ed. 2005, ProQuest Safari
- Unix in a nutshell. 4th ed. 2006, ProQuest SafariIntroduction -- Unix commands -- The Unix shell: an overview -- The Bash and Korn shells -- tcsh: an extended C shell -- Package management -- Pattern matching -- The Emacs editor -- The vi, ex, and vim editors -- The sed editor -- The awk programming language -- Source code management: an overview -- The revision control system -- The concurrent versions system -- The subversion version control system -- The GNU make utility -- The GDB debugger -- Writing manual pages.
- Unofficial guide to Microsoft Office Excel 2007 2007, books24x7, SUNet ID login required.
- Unofficial guide to Microsoft Office Word 2007 2007, books24x7, SUNet ID login required.
- Using artificial intelligence in chemistry and biology 2008, CRCnetBASE
- VBA for dummies. 5th ed. 2006, books24x7, SUNet ID login required.
- Visual Basic 2005 in a nutshell. 3rd ed. 2006, ProQuest Safari
- Visual Basic 2005 jumpstart. 1st ed. 2005, ProQuest Safari
- Web site cookbook 2006, ProQuest Safari
- Wicked cool Perl scripts 2006, SUNet ID login required to search for this title
- Windows XP cookbook ProQuest Safari
- Windows XP hacks. 2nd ed. 2005, ProQuest Safari
- Windows XP in a nutshell. 2nd ed. 2005, ProQuest Safari
- Wireless security 2012, CRCnetBASE1. Introduction -- 2. WLAN -- 3. PDAs -- 4. Mobile phones -- 5. Bluetooth -- 6. Infrared -- 7. Security policy.
- XML in a nutshell. 3rd ed. 2004, Proquest Safari
- XML in data management 2004, ScienceDirect
- XML in scientific computing 2013, CRCnetBASE"Preface XML stands for extensible markup language. In fact, XML is not a language, but a systematic way of encoding and formatting data and statements contained in an electronic file according to a chosen tagging system. A tag may represent a general entity, a physical, mathematical, or abstract object, an instruction, or a computer language construct. The data can describe cars and trucks in a dealer's lot, the chapters of a book, the input or output of a scientific experiment or calculation, the eigenvalues of a matrix, and anything else that can be described by numbers and words. Data presentation and description In the XML framework, information is described and presented in the same doc- ument, thus circumventing the need for legends and explanations. For example, we may order: <breakfast> toast and eggs <breakfast> Further cooking instructions can be included between the breakfast tag enclosed by the pointy brackets (<>) and its closure denoted by the slash (/). Data reuse XML data (input) can be read by a person or parsed and processed by a program (application) that produces a new set of data (output.) Although the input is the same, the output depends on the interpretation of the tags formatting the data. The inherent polymorphism allows us to materialize the same original data in different ways. For example: 1. An author may write a book inserting formatting tags between words, equations, and figures according to xml conventions and grammar. The text (data) file can be processed to produce books with different appear- ances. 2. A scientist may write a finite-element code that produces output tagged according to xml conventions"--Provided by publisher.
- XSLT 2.0 web development 2004, ProQuest Safari
- XSLT cookbook. 2nd ed. 2006, ProQuest Safari
- 2007 Microsoft Office system plain & ...
- — Human-computer interaction handbook. ...
- Image and signal processing for netwo...
- — Pervasive computing in healthcare ......
- Photoshop CS A to Z ....................
- — XSLT cookbook. 2nd ed. .................
- Harrison's Principles of Internal Medicine
- AAP Red Book Online
- Robbins & Cotran Pathologic Basis of Disease
- Sabiston Textbook of Surgery
- Nelson's Textbook of Pediatrics
- Surgical Exposures in Orthopaedics
- Mandell, Douglas, & Bennett's Principles & Practice of Infectious Diseases
- Red Book Online
- ICU Book
- Primary Care Medicine
- Campbell-Walsh Urology
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