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Introduction to Scientific Visualization
Scientific visualization is recognised as important for understanding data, whether measured, sensed remotely or calculated. Introduction to Scientific Visualization is aimed at readers who are new to the subject, either students taking an advanced option at undergraduate level or postgraduates wishing to visualize some specific data.
Introduction to robotics : Mechanics and control ; 3rd ed.
Includes material from traditional mechanical engineering, control theoretical material and computer science. It includes coverage of rigid-body transformations and forward and inverse positional kinematics
Introduction to robotics : Mechanics and control ; 2nd ed.
Written for senior level or first year graduate level robotics courses, this text includes material from traditional mechanical engineering, control theoretical material and computer science. It includes coverage of rigid-body transformations and forward and inverse positional kinematics
Introduction to Reliable Distributed Programming
Guerraoui and Rodrigues present an introductory description of fundamental reliable distributed programming abstractions as well as algorithms to implement these abstractions. The authors follow an incremental approach by first introducing basic abstractions in simple distributed environments, before moving to more sophisticated abstractions and more challenging environments. Each core chapter is devoted to one specific class of abstractions, covering reliable delivery, shared memory, consensus and various forms of agreement. This textbook comes with a companion set of running examples implemented in Java. These can be used by students to get a better understanding of how reliable distributed programming abstractions can be implemented and used in practice. Combined, the chapters deliver a full course on reliable distributed programming. The book can also be used as a complete reference on the basic elements required to build reliable distributed applications.
Introduction to Programming with Fortran : with coverage of Fortran 90, 95, 2003 and 77
Introduction to Programming with Fortran contains: lots of clear and simple examples highlighting the key language features of the most recent versions of Fortran – Fortran 2003, 95 and 90. practical examples based on ISO TR 15580 and ISO TR 15581 which are widely supported and cover the ISO TR on Enhanced Modules – particularly important to large code suites common problems that occur when programming which are highlighted via clear examples and solutions Introduction to Programming with Fortran is an essential introduction for beginners as well as a concise reference for professionals. Overall the book gives a very effective hands-on coverage of Fortran, valuable to students and practitioners alike.
Introduction to Probability with Statistical Applications
This textbook is an introduction to probability and statistics for non-mathematics majors who do not need the exhaustive detail and mathematical depth provided in more comprehensive treatments of the subject. The presentation covers the mathematical laws of random phenomena, including discrete and continuous random variables, expectation and variance, and common probability distributions such as the binomial, Poisson, and normal distributions. Main statistical concepts considered are point and interval estimates, hypothesis testing, power function, various statistical tests: z, t, chi-square and Kolmogorov-Smirnov.
Introduction to PHP for Scientists and Engineers : Beyond JavaScript
This text presents key information needed to write your own online science and engineering applications, including reading, creating and manipulating data files stored as text on a server, thereby overcoming the limitations of a client-side language.
Introduction to Operating System Design and Implementation : The OSP 2 Approach
This book exposes students to many essential features of operating systems while at the same time isolating them from low-level, machine-dependent concerns. With its accompanying software, the book contains enough projects for up to three semesters.
Introduction to Mathematical Systems Theory : Linear Systems, Identification and Control
This book provides an introduction to the theory of linear systems and control for students in business mathematics, econometrics, computer science, and engineering. The focus is on discrete time systems, which are the most relevant in business applications, as opposed to continuous time systems, requiring less mathematical preliminaries. The subjects treated are among the central topics of deterministic linear system theory: controllability, observability, realization theory, stability and stabilization by feedback, LQ-optimal control theory. Kalman filtering and LQC-control of stochastic systems are also discussed, as are modeling, time series analysis and model specification, along with model validation.
Introduction to information retrieval
Teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science.
Introduction to Geometric Computing
The geometric ideas in computer science, mathematics, engineering, and physics have considerable overlap and students in each of these disciplines will eventually encounter geometric computing problems. The topic is traditionally taught in mathematics departments via geometry courses, and in computer science through computer graphics modules. This text isolates the fundamental topics affecting these disciplines and lies at the intersection of classical geometry and modern computing.
Introduction to Discrete Event Systems
Introduction to Discrete Event Systems is a comprehensive introduction to the field of discrete event systems, offering a breadth of coverage that makes the material accessible to readers of varied backgrounds. The book emphasizes a unified modeling framework that transcends specific application areas, linking the following topics in a coherent manner: language and automata theory, supervisory control, Petri net theory, Markov chains and queueing theory, discrete-event simulation, and concurrent estimation techniques
Introduction to data systems : Building from Python
Encompassing a broad range of forms and sources of data, this textbook introduces data systems through a progressive presentation. Introduction to Data Systems covers data acquisition starting with local files, then progresses to data acquired from relational databases, from REST APIs and through web scraping. It teaches data forms/formats from tidy data to relationally defined sets of tables to hierarchical structure like XML and JSON using data models to convey the structure, operations, and constraints of each data form.
Introduction to Cryptography : Principles and Applications
In the first part, this book covers the key concepts of cryptography on an undergraduate level, from encryption and digital signatures to cryptographic protocols. In the second part, more advanced topics are addressed, such as the bit security of one-way functions and computationally perfect pseudorandom bit generators.
Introduction to Computer Graphics : Using Java 2D and 3D
This book introduces the most important basic concepts of computer graphics, coupling the technical background and theory with practical examples and applications throughout. Its user-friendly approach enables the reader to gain understanding through the theory at work, via the many example programs provided. With only elementary knowledge of the programming language Java, the reader will be able to create their own images and animations immediately, using Java 2D and/or Java 3D.
Introduction to C++ Programming and Graphics
Introduction to C++ Programming and Graphics offers a venue for rapidly learning the language by concisely revealing its grammar, syntax and main features, and by explaining the key ideas behind object oriented programming (OOP), with emphasis on scientific computing.
Introduction to C++ : 500+ Difficulty-Scaled Solved Programming Exercises
Includes more than 500 exercises and examples of progressive difficulty to aid the reader in understanding the C++ principles and to see how concepts can materialize in code. The examples are designed to be short, concrete, and substantial, quickly giving the reader the ability to understand how to apply correctly and efficiently the features of the C++ language and to get a solid programming know-how. Rest assured that if you are able to understand this book's examples and solve the exercises, you can safely go on to edit larger programs, you will be able to develop your own applications, and you will have certainly established a solid fundamental conceptual and practical background to expand your knowledge and skills
Introduction to Assembly Language Programming : For Pentium and RISC Processors
Assembly language continues to hold a core position in the programming world because of its similar structure to machine language and its very close links to underlying computer-processor architecture and design. These features allow for high processing speed, low memory demands, and the capacity to act directly on the system’s hardware. This completely revised second edition of the highly successful Introduction to Assembly Language Programming introduces readers to assembly language programming and its role in computer programming and design. It focuses on providing a firm grasp of the main features of assembly programming, and how it can be used to improve a computer's performance. The revised edition covers a broad scope of subjects and adds valuable material on protected-mode Pentium programming, MIPS assembly language programming, and use of the NASM and SPIM assemblers for a Linux orientation. All of the language's main features are covered in depth. The book requires only some basic experience with a structured, high-level language.
Introduction pratique aux bases de données relationnelles = A practical introduction to relational databases
Cet ouvrage introduit le lecteur dans le domaine des bases de données relationnelles en présentant une vaste sélection de sujets portant sur la modélisation des données, les langages de base de données, l'architecture des systèmes et l'évolution post-relationnelle. - Notions fondamentales: le modèle relationnel, les composants d’un système de gestion de bases de données, l’organisation de la mise en œuvre d’une base de données, les tâches de gestion des données. - De l'analyse à la base de données : le modèle entité association, la généralisation et l’agrégation, les dépendances et les formes normales,les contraintes d’intégrité. - Aperçu des langages de requête et de manipulation des données: l’algèbre relationnelle, le calcul des prédicats, SQL, QUEL, QBE, le traitement des valeurs nulles, la protection des données. - Les composants de l'architecture d'un système de bases de données : la compilation, l’interprétation et l’optimisation des requêtes, l’environnement multiutilisateur, le concept de transaction et la sérialisation, les méthodes optimiste et pessimiste, les structures de stockage et les méthodes d’accès. L’intégration et la migration des bases de données: l’exploitation des bases de données hétérogènes, les bases de données sur le Web, les règles de conversion pour effectuer l’intégration et la migration, les variantes de migration des bases de données hétérogènes, la planification de l’intégration et de la migration.
Introduction à SCILAB
Ce livre est organisé en deux parties. La première partie est consacrée au langage Scilab et à son environnement. Dans la seconde partie, les fonctionnalités des grands domaines d'utilisation du calcul numérique sont décrites et illustrées par des exemples: calcul matriciel, simulation, optimisation, résolution d'équations, statistiques.
