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Using Microcomputers in Research
This volume takes the reader step-by-step through writing the research proposal, gathering data, analyzing and manipulating data, and writing the research report. Provides a comprehensive introduction to micro-computing in the social sciences.
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Structures
Using aspects of structural behaviour, good design practice and effective computational techniques to illustrate the importance of the fundamental theoretical concepts presented, this book provides a comprehensive introduction to the analysis and design of structures.The over-riding importance of equilibrium is emphasized and, together with related topics, is the subject of the first five chapters. After deflections have been introduced in chapter six, elastic theory, buckling, plastic theory and energy methods are all introduced and their range of applicability discussed. Numerous case studies are included to help readers gain an appreciation of how theory relates in practice to real life structures.With a broad range of worked examples, questions and references to further reading, Structures is the ideal course text for entry-level students on degree, HNC and HND courses.
R 16,723.95
Gaussian Process Regression Analysis for Functional Data
Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables.Covering the basics of Gaussian process regression, the first several chapters discuss functional data analysis, theoretical aspects based on the asymptotic properties of Gaussian process regression models, and new methodological developments for high dimensional data and variable selection. The remainder of the text explores advanced topics of functional regression analysis, including novel nonparametric statistical methods for curve prediction, curve clustering, functional ANOVA, and functional regression analysis of batch data, repeated curves, and non-Gaussian data.Many flexible models based on Gaussian processes provide efficient ways of model learning, interpreting model structure, and carrying out inference, particularly when dealing with large dimensional functional data. This book shows how to use these Gaussian process regression models in the analysis of functional data. Some MATLAB® and C codes are available on the first author’s website.
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Exploratory Data Analysis Using R
Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA), and this revised edition is accompanied by the R package ExploreTheData that implements many of the approaches described. As before, the primary focus of the book is on identifying "interesting" features - good, bad, and ugly - in a dataset, why it is important to find them, how to treat them, and more generally, the use of R to explore and explain datasets and the analysis results derived from them.The book begins with a brief overview of exploratory data analysis using R, followed by a detailed discussion of creating various graphical data summaries in R. Then comes a thorough introduction to exploratory data analysis, and a detailed treatment of 13 data anomalies, why they are important, how to find them, and some options for addressing them. Subsequent chapters introduce the mechanics of working with external data, structured query language (SQL) for interacting with relational databases, linear regression analysis (the simplest and historically most important class of predictive models), and crafting data stories to explain our results to others. These chapters use R as an interactive data analysis platform, while Chapter 9 turns to writing programs in R, focusing on creating custom functions that can greatly simplify repetitive analysis tasks. Further chapters expand the scope to more advanced topics and techniques: special considerations for working with text data, a second look at exploratory data analysis, and more general predictive models. The book is designed for both advanced undergraduate, entry-level graduate students, and working professionals with little to no prior exposure to data analysis, modeling, statistics, or programming. It keeps the treatment relatively non-mathematical, even though data analysis is an inherently mathematical subject. Exercises are included at the end of most chapters, and an instructor's solution manual is available.
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Conceptual Structures in Practice
Exploring fundamental research questions, Conceptual Structures in Practice takes you through the basic yet nontrivial task of establishing conceptual relations as the foundation for research in knowledge representation and knowledge mining. It includes contributions from leading researchers in both the conceptual graph and formal concept analysis (FCA) communities.This accessible, self-contained book begins by providing the formal background in FCA and conceptual graphs. It then describes various software tools for analysis and computation, including the ToscanaJ suite. Written by the original visionaries of the field, the next section discusses the history and future directions of conceptual structures. The final chapters explore prominent application areas in computer science, including text analysis, web semantics, and intelligent systems.An unprecedented, state-of-the-art overview from innovators in the field, this volume discusses how FCA and conceptual graphs can be used in many computer science areas. It serves as a benchmark of research on conceptual structures, inspiring further exploration in this discipline.
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Student's Guide to Data and Error Analysis
All students taking laboratory courses within the physical sciences and engineering will benefit from this book, whilst researchers will find it an invaluable reference. This concise, practical guide brings the reader up-to-speed on the proper handling and presentation of scientific data and its inaccuracies. It covers all the vital topics with practical guidelines, computer programs (in Python), and recipes for handling experimental errors and reporting experimental data. In addition to the essentials, it also provides further background material for advanced readers who want to understand how the methods work. Plenty of examples, exercises and solutions are provided to aid and test understanding, whilst useful data, tables and formulas are compiled in a handy section for easy reference.
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Applied Discrete Structures - Part 1: Fundamentals
This is Part 1 of Applied Discrete Structures, containing the fundamental concepts taught in a one semester course in discrete mathematics. It corresponds with the content of Discrete Structures I at UMass Lowell, which is a required course for students in Computer Science, Mathematics and Information Technology. Part II - Applied Abstract Algebra would normally be used in a second semester course such as Discrete Structures II at UMass Lowell. Applied Discrete Structures has been approved by the American Institute of Mathematics as part of their Open Textbook Initiative. For more information on open textbooks, visit http://www.aimath.org/textbooks/. This version was created using Mathbook XML (https://mathbook.pugetsound.edu/) Version 3.6 - May 2019
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Computational Analysis and Design of Bridge Structures
Gain Confidence in Modeling Techniques Used for Complicated Bridge StructuresBridge structures vary considerably in form, size, complexity, and importance. The methods for their computational analysis and design range from approximate to refined analyses, and rapidly improving computer technology has made the more refined and complex methods of analyses more commonplace. The key methods of analysis and related modeling techniques are set out, mainly for highway bridges, but also with some information on railway bridges. Special topics such as strut-and-tie modeling, linear and nonlinear buckling analysis, redundancy analysis, integral bridges, dynamic/earthquake analysis, and bridge geometry are also covered. The material is largely code independent. The book is written for students, especially at MSc level, and for practicing professionals in bridge design offices and bridge design authorities worldwide. Effectively Analyze Structures Using Simple Mathematical Models Divided into three parts and comprised of 18 chapters, this text: Covers the methods of computational analysis and design suitable for bridge structuresProvides information on the methods of analysis and related modeling techniques suitable for the design and evaluation of various types of bridgesPresents material on a wide range of bridge structural types and is fairly code independentComputational Analysis and Design of Bridge Structures covers the general aspects of bridges, bridge behavior and the modeling of bridges, and special topics on bridges. This text explores the physical meanings behind modeling, and reveals how bridge structures can be analyzed using mathematical models.
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Structures
Using aspects of structural behaviour, good design practice and effective computational techniques to illustrate the importance of the fundamental theoretical concepts presented, this book provides a comprehensive introduction to the analysis and design of structures.The over-riding importance of equilibrium is emphasized and, together with related topics, is the subject of the first five chapters. After deflections have been introduced in chapter six, elastic theory, buckling, plastic theory and energy methods are all introduced and their range of applicability discussed. Numerous case studies are included to help readers gain an appreciation of how theory relates in practice to real life structures.With a broad range of worked examples, questions and references to further reading, Structures is the ideal course text for entry-level students on degree, HNC and HND courses.
R 4,396.75
Algorithms and Data Structures - Applications to Graphics and Geometry
This is a college-level introductory textbook of algorithms and data structures with application to graphics and geometry. This textbook, released under a Creative Commons Share Alike (CC BY SA) license, is presented in its original format with the academic content unchanged. It was authored by Jurg Nievergelt (ETH Zurich) and Klaus Hinrichs (Institut fur Informatik) and provided by the University of Georgia's Global Textbook Project. Textbookequity.org/algorithms-and-data-structures/ Photo Credit: Renato Keshet (GFDL) commons.wikimedia.org Contents Part I: Programming environments for motion, graphics, and geometry Part II: Programming concepts: beyond notation Part IV: Complexity of problems and algorithms Part V: Data structures Textbook Equity Edition http://textbookequity.org/algorithms-and-data-structures
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Efficient Algorithms for Listing Combinatorial Structures
First published in 1993, this thesis is concerned with the design of efficient algorithms for listing combinatorial structures. The research described here gives some answers to the following questions: which families of combinatorial structures have fast computer algorithms for listing their members? What general methods are useful for listing combinatorial structures? How can these be applied to those families which are of interest to theoretical computer scientists and combinatorialists? Amongst those families considered are unlabelled graphs, first order one properties, Hamiltonian graphs, graphs with cliques of specified order, and k-colourable graphs. Some related work is also included, which compares the listing problem with the difficulty of solving the existence problem, the construction problem, the random sampling problem, and the counting problem. In particular, the difficulty of evaluating Pólya's cycle polynomial is demonstrated.
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Mathematics of Discrete Structures for Computer Science
Mathematics plays a key role in computer science, some researchers would consider computers as nothing but the physical embodiment of mathematical systems. And whether you are designing a digital circuit, a computer program or a new programming language, you need mathematics to be able to reason about the design -- its correctness, robustness and dependability. This book covers the foundational mathematics necessary for courses in computer science.The common approach to presenting mathematical concepts and operators is to define them in terms of properties they satisfy, and then based on these definitions develop ways of computing the result of applying the operators and prove them correct. This book is mainly written for computer science students, so here the author takes a different approach: he starts by defining ways of calculating the results of applying the operators and then proves that they satisfy various properties. After justifying his underlying approach the author offers detailed chapters covering propositional logic, predicate calculus, sets, relations, discrete structures, structured types, numbers, and reasoning about programs.The book contains chapter and section summaries, detailed proofs and many end-of-section exercises -- key to the learning process. The book is suitable for undergraduate and graduate students, and although the treatment focuses on areas with frequent applications in computer science, the book is also suitable for students of mathematics and engineering.
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Mechanics of Aircraft Structures
MECHANICS OF AIRCRAFT STRUCTURES Explore the most up-to-date overview of the foundations of aircraft structures combined with a review of new aircraft materials The newly revised Third Edition of Mechanics of Aircraft Structures delivers a combination of the fundamentals of aircraft structure with an overview of new materials in the industry and a collection of rigorous analysis tools into a single one-stop resource. Perfect for a one-semester introductory course in structural mechanics and aerospace engineering, the distinguished authors have created a textbook that is also ideal for mechanical or aerospace engineers who wish to stay updated on recent advances in the industry. The new edition contains new problems and worked examples in each chapter and improves student accessibility. A new chapter on aircraft loads and new material on elasticity and structural idealization form part of the expanded content in the book. Readers will also benefit from the inclusion of: A thorough introduction to the characteristics of aircraft structures and materials, including the different types of aircraft structures and their basic structural elementsAn exploration of load on aircraft structures, including loads on wing, fuselage, landing gear, and stabilizer structuresAn examination of the concept of elasticity, including the concepts of displacement, strain, and stress, and the equations of equilibrium in a nonuniform stress fieldA treatment of the concept of torsion Perfect for senior undergraduate and graduate students in aerospace engineering, Mechanics of Aircraft Structures will also earn a place in the libraries of aerospace engineers seeking a one-stop reference to solidify their understanding of the fundamentals of aircraft structures and discover an overview of new materials in the field.
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Using SQLite
Developers, take note: databases aren't just for the IS group any more. You can build database-backed applications for the desktop, Web, embedded systems, or operating systems without linking to heavy-duty client-server databases such as Oracle and MySQL. This book shows how you to use SQLite, a small and lightweight database that you can build right into your application during development. Applications that handle data have an enormous advantage today, and with SQLite, you'll discover how to develop a database-backed application that remains manageable in size and complexity. This book guides you every step of the way. You'll get a crash course in data modeling, become familiar with SQLite's dialect of the SQL database language, and learn how you to work with SQLite using either a scripting language or a C-based language, such as C# or Objective C. Now, even relatively small and nimble applications can be a part of the data revolution. Using SQLite shows you how.
R 1,730.00
Conceptual Structures: Current Practices
This book is the proceedings of the Second International Conference on Conceptual Structures, ICCS '94, held at College Park, Maryland, USA in August 1994.This proceedings presents, on an international scale, up-to- the-minute research results on theoretical and applicational aspects of conceptual graphs, particularly on the use of contexts in knowledge representation. The concept of contexts is highly important for all kinds of knowledge-intensive systems. The book is organized into sections on natural language understanding, rational problem solving, conceptual graph theory, contexts and canons, and data modeling.
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Categorical Data Analysis with Structural Equation Models
Multivariate categorical outcomes, such as Likert scale responses and disease diagnoses, require specialized structural equation modeling (SEM) software to be analyzed properly. Providing needed skills for applied researchers and graduate students, this book leads readers from regression analysis with categorical outcomes to complex SEMs with latent variables for categorical indicators. The initial section sets the stage by demonstrating regression analyses for binary, ordered, or count outcomes using R. Chapters then reanalyze the same data using Mplus and R lavaan to show how univariate models for categorical outcomes can be estimated and interpreted with SEM programs. Subsequently, the book turns to multivariate models, discussing path models, confirmatory factor models, and latent variable path models with categorical outcomes. Concluding chapters cover advanced SEM with categorical outcomes, including growth models, latent class models, and survival models. Worked-through examples are featured throughout. The companion website provides R (including lavaan), Mplus, and SAS code, as applicable, for the examples.
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Conceptual Structures: Theory and Implementation
This volume contains revised and expanded versions of paperspresented at the Seventh Annual Workshop on ConceptualGraphs, held at New Mexico State University in Las Cruces,and sponsored by the American Association for ArtificialIntelligence and the NMSU Computer Science Department. Thecontents of the volume fall in the areas of representationissues, reasoning, data modeling and databases, algorithmsand tools, and applications and natural language. One of thehighlights reported in the volume is the landmark meetingof the first PEIRCE Project Workshop. The PEIRCE Projectaims to build a state-of-the-art, industrial strengthconceptual graphs workbench.
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Transport Barriers and Coherent Structures in Flow Data
Transport barriers are observed inhibitors of the spread of substances in flows. The collection of such barriers offers a powerful geometric template that frames the main pathways, or lack thereof, in any transport process. This book surveys effective and mathematically grounded methods for defining, locating and leveraging transport barriers in numerical simulations, laboratory experiments, technological processes and nature. It provides a unified treatment of material developed over the past two decades, focusing on the methods that have a solid foundation and broad applicability to data sets beyond simple model flows. The intended audience ranges from advanced undergraduates to researchers in the areas of turbulence, geophysical flows, aerodynamics, chemical engineering, environmental engineering, flow visualization, computational mathematics and dynamical systems. Detailed open-source implementations of the numerical methods are provided in an accompanying collection of Jupyter notebooks linked from the electronic version of the book.
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Logic of Typed Feature Structures
This book develops the theory of typed feature structures, a data structure that generalizes both first-order terms and feature structures of unification-based grammars to include inheritance, typing, inequality, cycles and intensionality. The resulting synthesis serves as a logical foundation for grammars, logic programming and constraint-based reasoning systems. A logical perspective is adopted which employs an attribute-value description language along with complete equational axiomatizations of the various systems of feature structures. At the same time, efficiency concerns are kept in mind and complexity and representability results are provided. The application of feature structures to phrase structure grammars is described and completeness results are shown for standard evaluation strategies. Definite clause logic programs are treated as a special case of phrase structure grammars. Constraint systems are introduced and an enumeration technique is developed for solving arbitrary attribute-value logic constraints. This book, with its innovative approach to data structure, will be essential reading for researchers in computational linguistics, logic programming and knowledge representation. Its self-contained presentation makes it flexible enough to serve as both a research tool and a text book.
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Boolean Structures: Combinatorics, Codification, Representation
Boolean Structures: Combinatorics, Codification, Representation offers the first analytical and architectural approach to Boolean algebras based combinatorial calculus and codification with applications in IT, quantum information and classification of data.
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Data Classification
Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification: Algorithms and Applications explores the underlying algorithms of classification as well as applications of classification in a variety of problem domains, including text, multimedia, social network, and biological data.This comprehensive book focuses on three primary aspects of data classification: Methods: The book first describes common techniques used for classification, including probabilistic methods, decision trees, rule-based methods, instance-based methods, support vector machine methods, and neural networks. Domains: The book then examines specific methods used for data domains such as multimedia, text, time-series, network, discrete sequence, and uncertain data. It also covers large data sets and data streams due to the recent importance of the big data paradigm. Variations: The book concludes with insight on variations of the classification process. It discusses ensembles, rare-class learning, distance function learning, active learning, visual learning, transfer learning, and semi-supervised learning as well as evaluation aspects of classifiers.
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Dependence Models via Hierarchical Structures
Bringing together years of research into one useful resource, this text empowers the reader to creatively construct their own dependence models. Intended for senior undergraduate and postgraduate students, it takes a step-by-step look at the construction of specific dependence models, including exchangeable, Markov, moving average and, in general, spatio-temporal models. All constructions maintain a desired property of pre-specifying the marginal distribution and keeping it invariant. They do not separate the dependence from the marginals and the mechanisms followed to induce dependence are so general that they can be applied to a very large class of parametric distributions. All the constructions are based on appropriate definitions of three building blocks: prior distribution, likelihood function and posterior distribution, in a Bayesian analysis context. All results are illustrated with examples and graphical representations. Applications with data and code are interspersed throughout the book, covering fields including insurance and epidemiology.
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Applied Discrete Structures
Applied Discrete Structures, is a two semester undergraduate text in discrete mathematics, focusing on the structural properties of mathematical objects. These include matrices, functions, graphs, trees, lattices and algebraic structures. The algebraic structures that are discussed are monoids, groups, rings, fields and vector spaces. Website: http://discretemath.org Applied Discrete Structures has been approved by the American Institute of Mathematics as part of their Open Textbook Initiative. For more information on open textbooks, visit http://www.aimath.org/textbooks/. This version was created using Mathbook XML (https://mathbook.pugetsound.edu/) Al Doerr is Emeritus Professor of Mathematical Sciences at UMass Lowell. His interests include abstract algebra and discrete mathematics. Ken Levasseur is a Professor of Mathematical Sciences at UMass Lowell. His interests include discrete mathematics and abstract algebra, and their implementation using computer algebra systems.
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Data Structures For Particle Physics Experiments: Evolution Or Revolution? - Proceedings Of The 14th Workshop On The Infn Eloisatron Project
HEP data structure systems, such as ADAMO, BOS, CHEETAH, JAZELLE, ZEBRA, etc., are not static but continue to evolve, some slowly, others more quickly. Large systems have been built on them, and by a careful comparison of their usage in experiments, one should be able to better understand which way to go. It is crucial to preserve the current investment while exploiting new computing technology.Experiments at large colliders are taking data and doing physics (or about to do so), so one can now compare practical experiences with different data management solutions in the area of: Simulation of Interactions and their Detection, Data Acquisition, On Line Management, Description of Detector and other Equipment, Experiment and Data Processing Bookkeeping, Reconstruction Algorithms, Event Display and Statistical Data Analysis.The articles in these proceedings are by contributors who are active in developing computer systems for Experimental Particle Physics where the organisation of the data plays an important role, as well as those who are building systems and packages to make this work easier.
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Learning to Build and Comprehend Complex Information Structures
Complex information structures are found in many disciplines including physics, genetics, biology and all branches of the information sciences. The current increasing, widespread use of information technology in all academic activities' emphasizes the need to understand how people construct and use such structures. The practices and activities found within the community of programmers provides a rich study area. The contents of this book are devoted to fundamental research that directly informs: the teaching community about some of the recent issues and problems that should help readers to increase their awareness when designing systems to support teaching, learning and using information technology; the psychology of the programming community about work in the area of learning to build, and debug programs; and the software engineering community in terms of the issues that implementors need to take into account when designing and building tools and environments for computer-based systems.
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TYPIX — Standardized Data and Crystal Chemical Characterization of Inorganic Structure Types
The crystaLLographer usuaLLy needs, as a compLement to his experimentaL work, a smaLL structure data compiLation. My first, some 25 years ago, was a hand-written List of structure types containing space group, unit ceLL data and positionaL atom coordinates. Some 20 years ago, when computers had become a more easiLy accessibLe tooL, a smaLL computer test fiLe was created with the help of Dr. Jan Portheine, which was LabeLLed TYPIX. Assisted by Dr. KLaus Yvon I inserted in the fiLe the somewhat more than 200 inorganic crystaL structure types which were of interest for our research or with which I was famiLiar from my previous experimentaL crystaL structure studies on intermetalLics and tetrahedraL structure compounds. We soon stopped our work on TYPIX because we reaLized that simpLy storing structure data copied from the Literature did not serve our finaL objective. I had, for exampLe, Listed the structures of certain isotypic compounds as separate distinct structure types because, due to a different setting or description given in the originaL Literature, I missed their isotypism.In other cases, with good Luck, I found the isotypism and succeeded in correctLy transforming one description to the other but then did not know which of the different but equivaLent descriptions I shouLd retain in my data coLLection.
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Introduction to Scientific Programming and Simulation Using R
Learn How to Program Stochastic ModelsHighly recommended, the best-selling first edition of Introduction to Scientific Programming and Simulation Using R was lauded as an excellent, easy-to-read introduction with extensive examples and exercises. This second edition continues to introduce scientific programming and stochastic modelling in a clear, practical, and thorough way. Readers learn programming by experimenting with the provided R code and data.The book’s four parts teach: Core knowledge of R and programming conceptsHow to think about mathematics from a numerical point of view, including the application of these concepts to root finding, numerical integration, and optimisationEssentials of probability, random variables, and expectation required to understand simulationStochastic modelling and simulation, including random number generation and Monte Carlo integration In a new chapter on systems of ordinary differential equations (ODEs), the authors cover the Euler, midpoint, and fourth-order Runge-Kutta (RK4) schemes for solving systems of first-order ODEs. They compare the numerical efficiency of the different schemes experimentally and show how to improve the RK4 scheme by using an adaptive step size. Another new chapter focuses on both discrete- and continuous-time Markov chains. It describes transition and rate matrices, classification of states, limiting behaviour, Kolmogorov forward and backward equations, finite absorbing chains, and expected hitting times. It also presents methods for simulating discrete- and continuous-time chains as well as techniques for defining the state space, including lumping states and supplementary variables.Building readers’ statistical intuition, Introduction to Scientific Programming and Simulation Using R, Second Edition shows how to turn algorithms into code. It is designed for those who want to make tools, not just use them. The code and data are available for download from CRAN.
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State Machines using VHDL
This textbook teaches students techniques for the design of advanced digital systems using Field Programmable Gate Arrays (FPGAs). The authors focus on communication between FPGAs and peripheral devices (such as EEPROM, analog-to-digital converters, sensors, digital-to-analog converters, displays etc.) and in particular state machines and timed state machines for the implementation of serial communication protocols, such as UART, SPI, I²C, and display protocols, such as VGA, HDMI. VHDL is used as the programming language and all topics are covered in a structured, step-by-step manner.
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State Machines using VHDL
This textbook teaches students techniques for the design of advanced digital systems using Field Programmable Gate Arrays (FPGAs). The authors focus on communication between FPGAs and peripheral devices (such as EEPROM, analog-to-digital converters, sensors, digital-to-analog converters, displays etc.) and in particular state machines and timed state machines for the implementation of serial communication protocols, such as UART, SPI, I²C, and display protocols, such as VGA, HDMI. VHDL is used as the programming language and all topics are covered in a structured, step-by-step manner.
R 2,381.00
Social Network Data Analytics
Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Properties of Social Networks, Algorithms for Structural Discovery of Social Networks and Content Analysis in Social Networks. This book is also unique in focussing on the data analytical aspects of social networks in the internet scenario, rather than the traditional sociology-driven emphasis prevalent in the existing books, which do not focus on the unique data-intensive characteristics of online social networks. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book. This book targets advanced level students and researchers concentrating on computer science as a secondary text or reference book. Data mining, database, information security, electronic commerce and machine learning professionals will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science.
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Data-driven Modelling of Structured Populations
This book is a “How To” guide for modeling population dynamics using Integral Projection Models (IPM) starting from observational data. It is written by a leading research team in this area and includes code in the R language (in the text and online) to carry out all computations. The intended audience are ecologists, evolutionary biologists, and mathematical biologists interested in developing data-driven models for animal and plant populations. IPMs may seem hard as they involve integrals. The aim of this book is to demystify IPMs, so they become the model of choice for populations structured by size or other continuously varying traits. The book uses real examples of increasing complexity to show how the life-cycle of the study organism naturally leads to the appropriate statistical analysis, which leads directly to the IPM itself. A wide range of model types and analyses are presented, including model construction, computational methods, and the underlying theory, with the more technical material in Boxes and Appendices. Self-contained R code which replicates all of the figures and calculations within the text is available to readers on GitHub.Stephen P. Ellner is Horace White Professor of Ecology and Evolutionary Biology at Cornell University, USA; Dylan Z. Childs is Lecturer and NERC Postdoctoral Fellow in the Department of Animal and Plant Sciences at The University of Sheffield, UK; Mark Rees is Professor in the Department of Animal and Plant Sciences at The University of Sheffield, UK.
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Hydraulic Structures
Now includes Worked Examples for lectutrers in a companion pdf!The fourth edition of this volume presents design principles and practical guidance for key hydraulic structures. Fully revised and updated, this new edition contains enhanced texts and sections on:environmental issues and the World Commission on Damspartially saturated soils, small amenity dams, tailing dams, upstream dam face protection and the rehabilitation of embankment damsRCC dams and the upgrading of masonry and concrete damsflow over stepped spillways and scour in plunge poolscavitation, aeration and vibration of gatesrisk analysis and contingency planning in dam safetysmall hydroelectric power development and tidal and wave powerwave statistics, pipeline stability, wave–structure interaction and coastal modellingcomputational models in hydraulic engineering.The book's key topics are explored in two parts - dam engineering and other hydraulic structures – and the text concludes with a chapter on models in hydraulic engineering. Worked numerical examples supplement the main text and extensive lists of references conclude each chapter. Hydraulic Structures provides advanced students with a solid foundation in the subject and is a useful reference source for researchers, designers and other professionals.
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Using the STL
A comprehensive introduction and guide to the STL, pitched at the level of readers already familiar with C++. It presents a thorough overview of the capabilities of the STL, detailed discussions of the use of containers, descriptions of the algorithms and how they may be used, and how the STL may be extended. An appendix provides an alphabetical reference to the entire STL, making this an extremely useful hands-on text for programmers of C++ and students coming to the STL for the first time.
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Concrete Structures
This text presents the most effective analysis for predicting the true stresses and deflections of concrete structures, accounting for creep and shrinkage of concrete and relaxation of prestressed reinforcement. Sustainability has become a major requirement in modern structures, which need to sustain satisfactory service over a longer life. It is not rare to specify a life span of 100 years for infrastructure such as bridges. This complete and wide-ranging study of stresses and deformations of reinforced and prestressed concrete structures focuses on design methods for avoiding the deflections and cracking that diminish serviceability. This fourth edition has a new emphasis on designing for serviceability. It has been comprehensively updated. It now includes 65 solved examples and more than 45 instructive problems with answers given at the end of the book. An accompanying website contains design calculation programs, which allow interactive data input. Independent of codes of practice, the book is universally applicable, and is especially suitable for practising engineers and graduate students.
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Hyper-lattice Algebraic Model for Data Warehousing
This book presents Hyper-lattice, a new algebraic model for partially ordered sets, and an alternative to lattice. The authors analyze some of the shortcomings of conventional lattice structure and propose a novel algebraic structure in the form of Hyper-lattice to overcome problems with lattice. They establish how Hyper-lattice supports dynamic insertion of elements in a partial order set with a partial hierarchy between the set members. The authors present the characteristics and the different properties, showing how propositions and lemmas formalize Hyper-lattice as a new algebraic structure.
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Modeling, Learning, and Processing of Text-Technological Data Structures
Researchers in many disciplines have been concerned with modeling textual data in order to account for texts as the primary information unit of written communication. The book “Modelling, Learning and Processing of Text-Technological Data Structures” deals with this challenging information unit. It focuses on theoretical foundations of representing natural language texts as well as on concrete operations of automatic text processing. Following this integrated approach, the present volume includes contributions to a wide range of topics in the context of processing of textual data. This relates to the learning of ontologies from natural language texts, the annotation and automatic parsing of texts as well as the detection and tracking of topics in texts and hypertexts. In this way, the book brings together a wide range of approaches to procedural aspects of text technology as an emerging scientific discipline.
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Student's Guide to Data and Error Analysis
All students taking laboratory courses within the physical sciences and engineering will benefit from this book, whilst researchers will find it an invaluable reference. This concise, practical guide brings the reader up-to-speed on the proper handling and presentation of scientific data and its inaccuracies. It covers all the vital topics with practical guidelines, computer programs (in Python), and recipes for handling experimental errors and reporting experimental data. In addition to the essentials, it also provides further background material for advanced readers who want to understand how the methods work. Plenty of examples, exercises and solutions are provided to aid and test understanding, whilst useful data, tables and formulas are compiled in a handy section for easy reference.
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