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Introduction to Numerical Methods
Written primarily for students in mechanical engineering programs and designed to give them the math preparation they need to succeed in higher level courses, Introduction to Numerical Methods introduces key theories, practical engineering-related examples, and relevant laboratory exercises to help students develop and test their knowledge.The book covers errors in computation, solving nonlinear equations with numerical techniques, matrixes and vectors, and complex numbers. The material also includes an introduction to linear programming problems and instruction in probability and statistics. Many of the exercises in the book suggest the use of a Ti-83/Ti-84 calculator, and tips for using the calculator successfully are integrated into the text. The second edition features significant updates throughout the text, including the addition of learning objectives at the start of each chapter, clarified and reorganized chapter exercises, and additional introductory and contextual information for key concepts to better frame students' understanding. This edition also has an appendix that includes a brief introduction of popular statistical software, Minitab. Introduction to Numerical Methods is a well-organized, useful addition to undergraduate course work in engineering programs.
R 3,172.70
Introduction to Discrete Mathematics with ISETL
Intended for first- or second-year undergraduates, this introduction to discrete mathematics covers the usual topics of such a course, but applies constructivist principles that promote - indeed, require - active participation by the student. Working with the programming language ISETL, whose syntax is close to that of standard mathematical language, the student constructs the concepts in her or his mind as a result of constructing them on the computer in the syntax of ISETL. This dramatically different approach allows students to attempt to discover concepts in a "Socratic" dialog with the computer. The discussion avoids the formal "definition-theorem" approach and promotes active involvement by the reader by its questioning style. An instructor using this text can expect a lively class whose students develop a deep conceptual understanding rather than simply manipulative skills. Topics covered in this book include: the propositional calculus, operations on sets, basic counting methods, predicate calculus, relations, graphs, functions, and mathematical induction.
R 2,159.79
Introduction to Middleware
"A stereotype of computer science textbooks is that they are dry, boring, and sometimes even intimidating. As a result, they turn students’ interests off from the subject matter instead of enticing them into it. This textbook is the opposite of such a stereotype. The author presents the subject matter in a refreshing story-telling style and aims to bring the Internet-generation of students closer to her stories." --Yingcai Xiao, The University of AkronIntroduction to Middleware: Web Services, Object Components, and Cloud Computing provides a comparison of different middleware technologies and the overarching middleware concepts they are based on. The various major paradigms of middleware are introduced and their pros and cons are discussed. This includes modern cloud interfaces, including the utility of Service Oriented Architectures. The text discusses pros and cons of RESTful vs. non-RESTful web services, and also compares these to older but still heavily used distributed object/component middleware. The text guides readers to select an appropriate middleware technology to use for any given task, and to learn new middleware technologies as they appear over time without being greatly overwhelmed by any new concept. The book begins with an introduction to different distributed computing paradigms, and a review of the different kinds of architectures, architectural styles/patterns, and properties that various researchers have used in the past to examine distributed applications and determine the quality of distributed applications. Then it includes appropriate background material in networking and the web, security, and encoding necessary to understand detailed discussion in this area. The major middleware paradigms are compared, and a comparison methodology is developed. Readers will learn how to select a paradigm and technology for a particular task, after reading this text.Detailed middleware technology review sections allow students or industry practitioners working to expand their knowledge to achieve practical skills based on real projects so as to become well-functional in that technology in industry. Major technologies examined include: RESTful web services (RESTful cloud interfaces such as OpenStack, AWS EC2 interface, CloudStack; AJAX, JAX-RS, ASP.NET MVC and ASP.NET Core), non-RESTful (SOAP and WSDL-based) web services (JAX-WS, Windows Communication Foundation), distributed objects/ components (Enterprise Java Beans, .NET Remoting, CORBA).The book presents two projects that can be used to illustrate the practical use of middleware, and provides implementations of these projects over different technologies.This versatile and class-tested textbook is suitable (depending on chapters selected) for undergraduate or first-year graduate courses on client server architectures, middleware, and cloud computing, web services, and web programming.
R 7,716.58
Introduction to Computational Physics for Undergraduates
This is an introductory textbook on computational methods and techniques intended for undergraduates at the sophomore or junior level in the fields of science, mathematics, and engineering. It provides an introduction to programming languages such as FORTRAN 90/95/2000 and covers numerical techniques such as differentiation, integration, root finding, and data fitting. The textbook also entails the use of the Linux/Unix operating system and other relevant software such as plotting programs, text editors, and mark up languages such as LaTeX. It includes multiple homework assignments.
R 2,015.00
R 306.00
Introduction to Symbolic Dynamics and Coding
Symbolic dynamics is a mature yet rapidly developing area of dynamical systems. It has established strong connections with many areas, including linear algebra, graph theory, probability, group theory, and the theory of computation, as well as data storage, statistical mechanics, and $C^*$-algebras. This Second Edition maintains the introductory character of the original 1995 edition as a general textbook on symbolic dynamics and its applications to coding. It is written at an elementary level and aimed at students, well-established researchers, and experts in mathematics, electrical engineering, and computer science. Topics are carefully developed and motivated with many illustrative examples. There are more than 500 exercises to test the reader's understanding. In addition to a chapter in the First Edition on advanced topics and a comprehensive bibliography, the Second Edition includes a detailed Addendum, with companion bibliography, describing major developments and new research directions since publication of the First Edition.
R 2,848.67
Programmer's Introduction to Windows DNA
This is the first book designed to help Windows developers decide not only which technologies to use but also how to use them. It teaches them to combine the wide variety of technologies that make up Windows DNA into effective solutions for their own enterprise application requirements. The author makes use of his long consulting experience in the client-server world to describe "best practices" that apply to building Windows DNA applications.
R 1,367.00
Introduction to Bootstrap Methods with Applications to R
A comprehensive introduction to bootstrap methods in the R programming environment Bootstrap methods provide a powerful approach to statistical data analysis, as they have more general applications than standard parametric methods. An Introduction to Bootstrap Methods with Applications to R explores the practicality of this approach and successfully utilizes R to illustrate applications for the bootstrap and other resampling methods. This book provides a modern introduction to bootstrap methods for readers who do not have an extensive background in advanced mathematics. Emphasis throughout is on the use of bootstrap methods as an exploratory tool, including its value in variable selection and other modeling environments. The authors begin with a description of bootstrap methods and its relationship to other resampling methods, along with an overview of the wide variety of applications of the approach. Subsequent chapters offer coverage of improved confidence set estimation, estimation of error rates in discriminant analysis, and applications to a wide variety of hypothesis testing and estimation problems, including pharmaceutical, genomics, and economics. To inform readers on the limitations of the method, the book also exhibits counterexamples to the consistency of bootstrap methods. An introduction to R programming provides the needed preparation to work with the numerous exercises and applications presented throughout the book. A related website houses the book's R subroutines, and an extensive listing of references provides resources for further study. Discussing the topic at a remarkably practical and accessible level, An Introduction to Bootstrap Methods with Applications to R is an excellent book for introductory courses on bootstrap and resampling methods at the upper-undergraduate and graduate levels. It also serves as an insightful reference for practitioners working with data in engineering, medicine, and the social sciences who would like to acquire a basic understanding of bootstrap methods.
R 3,824.00
Introduction to Choreographies
In concurrent and distributed systems, processes can complete tasks together by playing their parts in a joint plan. The plan, or protocol, can be written as a choreography: a formal description of overall behaviour that processes should collaborate to implement, like authenticating a user or purchasing an item online. Formality brings clarity, but not only that. Choreographies can contribute to important safety and liveness properties. This book is an ideal introduction to theory of choreographies for students, researchers, and professionals in computer science and applied mathematics. It covers languages for writing choreographies and their semantics, and principles for implementing choreographies correctly. The text treats the study of choreographies as a discipline in its own right, following a systematic approach that starts from simple foundations and proceeds to more advanced features in incremental steps. Each chapter includes examples and exercises aimed at helping with understanding the theory and its relation to practice.
R 2,353.00
R 790.40
Introduction to Reconfigurable Computing
This work is a comprehensive study of the field. It provides an entry point to the novice willing to move in the research field reconfigurable computing, FPGA and system on programmable chip design. The book can also be used as teaching reference for a graduate course in computer engineering, or as reference to advance electrical and computer engineers. It provides a very strong theoretical and practical background to the field, from the early Estrin’s machine to the very modern architecture such as embedded logic devices.
R 3,860.51
R 878.00
Introduction to Maple
The fully revised edition of this best-selling title presents the modern computer algebra system Maple. It teaches the reader not only what can be done by Maple but also how and why it can be done. It provides the necessary background for those who want the most of Maple or want to extend its built-in knowledge, and it includes both elementary and more sophisticated examples as well as many exercises.
R 1,644.07
Introduction to Needle Felting
The introduction to the book will cover a brief history of felting and felting /wool terms. It will also list what items you need to purchase to make yourself a starter Needle felting kit and then for each chapter subject, the wool and anything else you will need to complete that project. There will also be a suppliers list from which you can purchase anything you will need.There will then follow 6 subject chapters , a 7th chapter introducing wet felting and Needle felting combined , chapter 8 will be some seasonal creations with chapter 9 showing you how all these things can be made into gifts for your family and friends or simply something lovely to keep for yourself. Each subject will be fully supported with both diagrams and photographs of how to achieve each item with suggestions and tips along the way .The subjects covered start from basic simple shapes and how to build on these shapes and will advance in difficulty as you go through the book but everything covered is suitable for a complete novice or someone who wants to try some different ideas.
R 210.00
R 1,283.86
Introduction to Computer Simulation
Computer simulation is increasingly used in physics and engineering to predict the probable outcome of experiments and to aid in their interpretation. The methods of simulation are based on a range of numerical techniques for treating ordinary and partial differential equations. Since much of physics can be broken down into a relatively small set of fundamental equations, there is a set of very general methods which can be widely applied. This text aims to give anintroduction to those methods suitable for readers at an undergraduate level and those meeting the subject for the first time at postgraduate level. The methods are illustrated with simple programs and problems. The book covers a range of material not available in a simple form in a single textelsewhere.
R 3,403.00
Introduction to Fluid Dynamics in Physics and Astrophysics
This textbook provides an accessible and self-contained introduction to the physics behind fluid dynamics; exploring the laws of nature describing three out of four fundamental states of matter (liquids, gases, and plasmas). Based on years of teaching of fluid dynamics theory and computation at advanced undergraduate level, it provides readers with the tools to understand and model fluid dynamical systems across a wide range of applications, from dense liquids to dilute space plasmas. The book covers the principles of fluid dynamics for an audience without prior exposure to fluid dynamics specifically. Discussion of relevant vector algebra, thermodynamics and electromagnetism is included, to ensure that the book is accessible both to readers experienced in these topics and readers starting from a basic understanding.Example applications are drawn both from astrophysics and physics, touching upon topical research such as relativistic blast waves from neutron star mergers and the implications of plasma nature of the atmosphere for present and future radio observatories. These are contrasted and complemented with examples from general physics (e.g. contrasting the incompressible nature of water with the dilute interstellar medium). It is an ideal textbook for advanced undergraduates studying the topic and will provide a solid foundation for further (postgraduate) studies into fluid dynamics in physics or astrophysics.Key Features:• Introduction to fluid dynamics pitched at advanced undergraduate level, accessible to students who are still learning relevant mathematical techniques.• Includes over 60 exercises and selected worked solutions, in addition to timely examples and easily accessible numerical demonstrations written in C and python for readers to experiment with (https://github.com/hveerten/codefluiddynamicsbook).• Up-to-date selection of topics including fluid dynamics in special relativity and computational fluid dynamics, written by an expert in the field. The book covers all that is needed to independently write a finite-volume solver for Euler’s equations and/or reproduce the provided Python and C software.• Covers a wide range of applications in astrophysics, including first-order Fermi acceleration in shocks, accretion discs, self-similarity in cosmic explosions and interstellar turbulence.Dr Hendrik van Eerten is a Reader in Theoretical and Computational Astrophysics at the University of Bath, United Kingdom. His area of research is transients in high-energy astrophysics, with a focus on theoretical and computational fluid dynamics of relativistic jets and cosmic explosions, in particular gamma-ray bursts.
R 3,911.87
Introduction to Fuzzy Logic using MATLAB
This book provides a broad-ranging, but detailed overview of the basics of Fuzzy Logic. The fundamentals of Fuzzy Logic are discussed in detail, and illustrated with various solved examples. The book also deals with applications of Fuzzy Logic, to help readers more fully understand the concepts involved. Solutions to the problems are programmed using MATLAB 6.0, with simulated results. The MATLAB Fuzzy Logic toolbox is provided for easy reference.
R 5,485.70
R 214.00
Introduction to Modern Fortran for the Earth System Sciences
This work provides a short "getting started" guide to Fortran 90/95. The main target audience consists of newcomers to the field of numerical computation within Earth system sciences (students, researchers or scientific programmers). Furthermore, readers accustomed to other programming languages may also benefit from this work, by discovering how some programming techniques they are familiar with map to Fortran 95. The main goal is to enable readers to quickly start using Fortran 95 for writing useful programs. It also introduces a gradual discussion of Input/Output facilities relevant for Earth system sciences, from the simplest ones to the more advanced netCDF library (which has become a de facto standard for handling the massive datasets used within Earth system sciences). While related works already treat these disciplines separately (each often providing much more information than needed by the beginning practitioner), the reader finds in this book a shorter guide which links them. Compared to other books, this work provides a much more compact view of the language, while also placing the language-elements in a more applied setting, by providing examples related to numerical computing and more advanced Input/Output facilities for Earth system sciences. Naturally, the coverage of the programming language is relatively shallow, since many details are skipped. However, many of these details can be learned gradually by the practitioner, after getting an overview and some practice with the language through this book.
R 4,030.00
Practical Introduction to Computer Architecture
It is a great pleasure to write a preface to this book. In my view, the content is unique in that it blends traditional teaching approaches with the use of mathematics and a mainstream Hardware Design Language (HDL) as formalisms to describe key concepts. The book keeps the “machine” separate from the “application” by strictly following a bottom-up approach: it starts with transistors and logic gates and only introduces assembly language programs once their execution by a processor is clearly de ned. Using a HDL, Verilog in this case, rather than static circuit diagrams is a big deviation from traditional books on computer architecture. Static circuit diagrams cannot be explored in a hands-on way like the corresponding Verilog model can. In order to understand why I consider this shift so important, one must consider how computer architecture, a subject that has been studied for more than 50 years, has evolved. In the pioneering days computers were constructed by hand. An entire computer could (just about) be described by drawing a circuit diagram. Initially, such d- grams consisted mostly of analogue components before later moving toward d- ital logic gates. The advent of digital electronics led to more complex cells, such as half-adders, ip- ops, and decoders being recognised as useful building blocks.
R 1,842.34
Introduction to Project Management
This book presents the fundamentals of project management in simple language and an easy-to-understand format. It is targeted principally at those who are learning or desiring to learn project management as well as those who are already taking project management as a course of study or as a profession. It covers all the basic aspects of project management including the core areas prescribed by the Project Management Institute (PMI) in the Project Management Body of Knowledge (PMBOK) sixth edition. Although the PMBOK Guide seventh edition has significantly shifted focus from a process based standard to a principle based standard, it does not invalidate nor replace the detailed knowledge base contained in the sixth edition, which substantially emphasizes project management processes and knowledge areas. This is particularly apt for the traditional approach to project delivery, which is predictive in nature and has the bulk of the planning done upfront. The sections of the book are arranged in order of Project Management Processes as they fall within the respective Project Management Knowledge Areas. Experienced project manager, Davies Igberaese, presents all the basic content of traditional project management in a straightforward practical sequence as a typical project manager would go about the processes of initiating, planning, executing, monitoring, and closing a project without losing sight of the iterative nature of project management. The inclusion of Project Management Templates gives students and other users of the book the confidence required to effectively understand the basics of managing a wide variety of projects across disciplines including construction, building, industrial engineering, petroleum engineering, software engineering, information technology, business administration, and event management. Introduction to Project Management: A Source Book for Traditional PM Basics can serve as a core textbook for academic courses in project management, for preparing for PMP and CAPM Certification exams, as an excellent resource for new project managers, as well as a handy reference book for project sponsors.
R 9,949.94
Introduction to Computing with Fuzzy Sets
This book provides concise yet thorough coverage of the fundamentals and technology of fuzzy sets. Readers will find a lucid and systematic introduction to the essential concepts of fuzzy set-based information granules, their processing and detailed algorithms. Timely topics and recent advances in fuzzy modeling and its principles, neurocomputing, fuzzy set estimation, granulation–degranulation, and fuzzy sets of higher type and order are discussed. In turn, a wealth of examples, case studies, problems and motivating arguments, spread throughout the text and linked with various areas of artificial intelligence, will help readers acquire a solid working knowledge. Given the book’s well-balanced combination of the theory and applied facets of fuzzy sets, it will appeal to a broad readership in both academe and industry. It is also ideally suited as a textbook for graduate and undergraduate students in science, engineering, and operations research.
R 4,014.47
R 618.00
R 430.06
R 1,313.51
Introduction to Statistical Learning
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naïve Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.
R 3,663.00
Introduction to Project Management
This book presents the fundamentals of project management in simple language and an easy-to-understand format. It is targeted principally at those who are learning or desiring to learn project management as well as those who are already taking project management as a course of study or as a profession. It covers all the basic aspects of project management including the core areas prescribed by the Project Management Institute (PMI) in the Project Management Body of Knowledge (PMBOK) sixth edition. Although the PMBOK Guide seventh edition has significantly shifted focus from a process based standard to a principle based standard, it does not invalidate nor replace the detailed knowledge base contained in the sixth edition, which substantially emphasizes project management processes and knowledge areas. This is particularly apt for the traditional approach to project delivery, which is predictive in nature and has the bulk of the planning done upfront. The sections of the book are arranged in order of Project Management Processes as they fall within the respective Project Management Knowledge Areas. Experienced project manager, Davies Igberaese, presents all the basic content of traditional project management in a straightforward practical sequence as a typical project manager would go about the processes of initiating, planning, executing, monitoring, and closing a project without losing sight of the iterative nature of project management. The inclusion of Project Management Templates gives students and other users of the book the confidence required to effectively understand the basics of managing a wide variety of projects across disciplines including construction, building, industrial engineering, petroleum engineering, software engineering, information technology, business administration, and event management. Introduction to Project Management: A Source Book for Traditional PM Basics can serve as a core textbook for academic courses in project management, for preparing for PMP and CAPM Certification exams, as an excellent resource for new project managers, as well as a handy reference book for project sponsors.
R 2,167.02
R 1,459.53
Readable Introduction to Real Mathematics
Designed for an undergraduate course or for independent study, this text presents sophisticated mathematical ideas in an elementary and friendly fashion. The fundamental purpose of this book is to teach mathematical thinking while conveying the beauty and elegance of mathematics. The book contains a large number of exercises of varying difficulty, some of which are designed to help reinforce basic concepts and others of which will challenge virtually all readers. The sole prerequisite for reading this text is high school algebra. Topics covered include: * mathematical induction * modular arithmetic * the Fundamental Theorem of Arithmetic * Fermat's Little Theorem * RSA encryption * the Euclidean algorithm * rational and irrational numbers * complex numbers * cardinality * Euclidean plane geometry * constructibility (including a proof that an angle of 60 degrees cannot be trisected with a straightedge and compass)* infinite series * higher dimensional spaces.This textbook is suitable for a wide variety of courses and for a broad range of students of mathematics and other subjects. Mathematically inclined senior high school students will also be able to read this book.From the reviews of the first edition:“It is carefully written in a precise but readable and engaging style… I thoroughly enjoyed reading this recent addition to the Springer Undergraduate Texts in Mathematics series and commend this clear, well-organised, unfussy text to its target audiences.” (Nick Lord, The Mathematical Gazette, Vol. 100 (547), 2016) “The book is an introduction to real mathematics and is very readable. … The book is indeed a joy to read, and would be an excellent text for an ‘appreciation of mathematics’ course, among other possibilities.” (G.A. Heuer, Mathematical Reviews, February, 2015)“Many a benighted book misguidedly addresses the need [to teach mathematical thinking] by framing reasoning, or narrowly, proof, not as pervasive modality but somehow as itself an autonomous mathematical subject. Fortunately, the present book gets it right.... [presenting] well-chosen, basic, conceptual mathematics, suitably accessible after a K-12 education, in a detailed, self-conscious way that emphasizes methodology alongside content and crucially leads to an ultimate clear payoff. … Summing Up: Recommended. Lower-division undergraduates and two-year technical program students; general readers.” (D.V. Feldman, Choice, Vol. 52 (6), February, 2015)
R 1,546.39
Introduction to Error Analysis, third edition
This remarkable text by John R. Taylor has been a non-stop best-selling international hit since it was first published forty years ago. However, the two-plus decades since the second edition was released have seen two dramatic developments; the huge rise in popularity of Bayesian statistics, and the continued increase in the power and availability of computers and calculators. In response to the former, Taylor has added a full chapter dedicated to Bayesian thinking, introducing conditional probabilities and Bayes’ theorem. The several examples presented in the new third edition are intentionally very simple, designed to give readers a clear understanding of what Bayesian statistics is all about as their first step on a journey to become practicing Bayesians. In response to the second development, Taylor has added a number of chapter-ending problems that will encourage readers to learn how to solve problems using computers. While many of these can be solved using programs such as Matlab or Mathematica, almost all of them are stated to apply to commonly available spreadsheet programs like Microsoft Excel. These programs provide a convenient way to record and process data and to calculate quantities like standard deviations, correlation coefficients, and normal distributions; they also have the wonderful ability – if students construct their own spreadsheets and avoid the temptation to use built-in functions – to teach the meaning of these concepts.
R 2,325.00
Introduction to Reversible Computing
Few books comprehensively cover the software and programming aspects of reversible computing. Filling this gap, Introduction to Reversible Computing offers an expanded view of the field that includes the traditional energy-motivated hardware viewpoint as well as the emerging application-motivated software approach. Collecting scattered knowledge into one coherent account, the book provides a compendium of both classical and recently developed results on reversible computing. It explores up-and-coming theories, techniques, and tools for the application of reversible computing—the logical next step in the evolution of computing systems.The book covers theory, hardware and software aspects, fundamental limits, complexity analyses, practical algorithms, compilers, efficiency improvement techniques, and application areas. The topics span several areas of computer science, including high-performance computing, parallel/distributed systems, computational theory, compilers, power-aware computing, and supercomputing. The book presents sufficient material for newcomers to easily get started. It provides citations to original articles on seminal results so that readers can consult the corresponding publications in the literature. Pointers to additional resources are included for more advanced topics. For those already familiar with a certain topic within reversible computing, the book can serve as a one-stop reference to other topics in the field.
R 9,955.66
Introduction to Computation and Modeling for Differential Equations
Uses mathematical, numerical, and programming tools to solve differential equations for physical phenomena and engineering problems Introduction to Computation and Modeling for Differential Equations, Second Edition features the essential principles and applications of problem solving across disciplines such as engineering, physics, and chemistry. The Second Edition integrates the science of solving differential equations with mathematical, numerical, and programming tools, specifically with methods involving ordinary differential equations; numerical methods for initial value problems (IVPs); numerical methods for boundary value problems (BVPs); partial differential equations (PDEs); numerical methods for parabolic, elliptic, and hyperbolic PDEs; mathematical modeling with differential equations; numerical solutions; and finite difference and finite element methods. The author features a unique “Five-M” approach: Modeling, Mathematics, Methods, MATLAB®, and Multiphysics, which facilitates a thorough understanding of how models are created and preprocessed mathematically with scaling, classification, and approximation and also demonstrates how a problem is solved numerically using the appropriate mathematical methods. With numerous real-world examples to aid in the visualization of the solutions, Introduction to Computation and Modeling for Differential Equations, Second Edition includes: New sections on topics including variational formulation, the finite element method, examples of discretization, ansatz methods such as Galerkin’s method for BVPs, parabolic and elliptic PDEs, and finite volume methodsNumerous practical examples with applications in mechanics, fluid dynamics, solid mechanics, chemical engineering, heat conduction, electromagnetic field theory, and control theory, some of which are solved with computer programs MATLAB and COMSOL Multiphysics®Additional exercises that introduce new methods, projects, and problems to further illustrate possible applicationsA related website with select solutions to the exercises, as well as the MATLAB data sets for ordinary differential equations (ODEs) and PDEs Introduction to Computation and Modeling for Differential Equations, Second Edition is a useful textbook for upper-undergraduate and graduate-level courses in scientific computing, differential equations, ordinary differential equations, partial differential equations, and numerical methods. The book is also an excellent self-study guide for mathematics, science, computer science, physics, and engineering students, as well as an excellent reference for practitioners and consultants who use differential equations and numerical methods in everyday situations.
R 3,294.00
General Introduction to Data Analytics
A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-to-understand terms and does not require familiarity with statistics or programming. The authors—noted experts in the field—highlight an explanation of the intuition behind the basic data analytics techniques. The text also contains exercises and illustrative examples. Thought to be easily accessible to non-experts, the book provides motivation to the necessity of analyzing data. It explains how to visualize and summarize data, and how to find natural groups and frequent patterns in a dataset. The book also explores predictive tasks, be them classification or regression. Finally, the book discusses popular data analytic applications, like mining the web, information retrieval, social network analysis, working with text, and recommender systems. The learning resources offer: A guide to the reasoning behind data mining techniquesA unique illustrative example that extends throughout all the chaptersExercises at the end of each chapter and larger projects at the end of each of the text’s two main parts Together with these learning resources, the book can be used in a 13-week course guide, one chapter per course topic. The book was written in a format that allows the understanding of the main data analytics concepts by non-mathematicians, non-statisticians and non-computer scientists interested in getting an introduction to data science. A General Introduction to Data Analytics is a basic guide to data analytics written in highly accessible terms.
R 3,353.00
Introduction to Probabilistic and Statistical Methods with Examples in R
This book strikes a healthy balance between theory and applications, ensuring that it doesn’t offer a set of tools with no mathematical roots. It is intended as a comprehensive and largely self-contained introduction to probability and statistics for university students from various faculties, with accompanying implementations of some rudimentary statistical techniques in the language R. The content is divided into three basic parts: the first includes elements of probability theory, the second introduces readers to the basics of descriptive and inferential statistics (estimation, hypothesis testing), and the third presents the elements of correlation and linear regression analysis. Thanks to examples showing how to approach real-world problems using statistics, readers will acquire stronger analytical thinking skills, which are essential for analysts and data scientists alike.
R 3,294.06
R 639.00
Introduction to MultiAgent Systems
The study of multi-agent systems (MAS) focuses on systems in which many intelligent agents interact with each other. These agents are considered to be autonomous entities such as software programs or robots. Their interactions can either be cooperative (for example as in an ant colony) or selfish (as in a free market economy). This book assumes only basic knowledge of algorithms and discrete maths, both of which are taught as standard in the first or second year of computer science degree programmes. A basic knowledge of artificial intelligence would useful to help understand some of the issues, but is not essential. The book’s main aims are: To introduce the student to the concept of agents and multi-agent systems, and the main applications for which they are appropriateTo introduce the main issues surrounding the design of intelligent agentsTo introduce the main issues surrounding the design of a multi-agent societyTo introduce a number of typical applications for agent technology After reading the book the student should understand: The notion of an agent, how agents are distinct from other software paradigms (e.g. objects) and the characteristics of applications that lend themselves to agent-oriented softwareThe key issues associated with constructing agents capable of intelligent autonomous action and the main approaches taken to developing such agentsThe key issues in designing societies of agents that can effectively cooperate in order to solve problems, including an understanding of the key types of multi-agent interactions possible in such systemsThe main application areas of agent-based systems
R 2,176.00
R 553.74
Introduction to the Simulation of Dynamics Using Simulink
Designed for undergraduate students in the general science, engineering, and mathematics community, Introduction to the Simulation of Dynamics Using Simulink® shows how to use the powerful tool of Simulink to investigate and form intuitions about the behavior of dynamical systems. Requiring no prior programming experience, it clearly explains how to transition from physical models described by mathematical equations directly to executable Simulink simulations.Teaches students how to model and explore the dynamics of systemsStep by step, the author presents the basics of building a simulation in Simulink. He begins with finite difference equations and simple discrete models, such as annual population models, to introduce the concept of state. The text then covers ordinary differential equations, numerical integration algorithms, and time-step simulation. The final chapter offers overviews of some advanced topics, including the simulation of chaotic dynamics and partial differential equations.A one-semester undergraduate course on simulationWritten in an informal, accessible style, this guide includes many diagrams and graphics as well as exercises embedded within the text. It also draws on numerous examples from the science, engineering, and technology fields. The book deepens students’ understanding of simulated systems and prepares them for advanced and specialized studies in simulation. Ancillary materials are available at http://nw08.american.edu/~gray
R 4,249.00
R 367.00
R 762.00
