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R 341.00
Advanced Applications of Python Data Structures and Algorithms
Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision.Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.
R 10,420.70
R 1,221.00
Introduction to Java Programming and Data Structures, Global Edition
For courses in Java programming. A fundamentals-first approach. Introduction to Java Programming and Data Structures, Global Edition integrates programming, data structures and algorithms into 1 text. It takes a fundamentals-first approach, building a strong foundation of basic concepts and techniques before teaching object-oriented and advanced programming. Programming is explained in a problem-driven way that focuses on problem solving rather than syntax, illustrating concepts by example and providing many exercises with various levels of difficulty for practice. The 13th Edition reflects Java 18 technology and is completely revised in every detail to enhance clarity, content, examples and exercises.
R 3,546.00
Data Wrangling with R
This guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of information. Data wrangling, which is also commonly referred to as data munging, transformation, manipulation, janitor work, etc., can be a painstakingly laborious process. Roughly 80% of data analysis is spent on cleaning and preparing data; however, being a prerequisite to the rest of the data analysis workflow (visualization, analysis, reporting), it is essential that one become fluent and efficient in data wrangling techniques.This book will guide the user through the data wrangling process via a step-by-step tutorial approach and provide a solid foundation for working with data in R. The author's goal is to teach the user how to easily wrangle data in order to spend more time on understanding the content of the data. By the end of the book, the user will have learned: How to work with different types of data such as numerics, characters, regular expressions, factors, and datesThe difference between different data structures and how to create, add additional components to, and subset each data structureHow to acquire and parse data from locations previously inaccessibleHow to develop functions and use loop control structures to reduce code redundancyHow to use pipe operators to simplify code and make it more readableHow to reshape the layout of data and manipulate, summarize, and join data sets
R 3,176.98
R 393.25
R 1,172.00
Data Clustering in C++
Data clustering is a highly interdisciplinary field, the goal of which is to divide a set of objects into homogeneous groups such that objects in the same group are similar and objects in different groups are quite distinct. Thousands of theoretical papers and a number of books on data clustering have been published over the past 50 years. However, few books exist to teach people how to implement data clustering algorithms. This book was written for anyone who wants to implement or improve their data clustering algorithms. Using object-oriented design and programming techniques, Data Clustering in C++ exploits the commonalities of all data clustering algorithms to create a flexible set of reusable classes that simplifies the implementation of any data clustering algorithm. Readers can follow the development of the base data clustering classes and several popular data clustering algorithms. Additional topics such as data pre-processing, data visualization, cluster visualization, and cluster interpretation are briefly covered.This book is divided into three parts-- Data Clustering and C++ Preliminaries: A review of basic concepts of data clustering, the unified modeling language, object-oriented programming in C++, and design patterns A C++ Data Clustering Framework: The development of data clustering base classes Data Clustering Algorithms: The implementation of several popular data clustering algorithms A key to learning a clustering algorithm is to implement and experiment the clustering algorithm. Complete listings of classes, examples, unit test cases, and GNU configuration files are included in the appendices of this book as well as in the downloadable resources. The only requirements to compile the code are a modern C++ compiler and the Boost C++ libraries.
R 3,863.85
R 1,221.00
Structural Bioinformatics: Applications in Preclinical Drug Discovery Process
This book reviews the advances and challenges of structure-based drug design in the preclinical drug discovery process, addressing various diseases, including malaria, tuberculosis and cancer. Written by internationally recognized researchers, this edited book discusses how the application of the various in-silico techniques, such as molecular docking, virtual screening, pharmacophore modeling, molecular dynamics simulations, and residue interaction networks offers insights into pharmacologically active novel molecular entities. It presents a clear concept of the molecular mechanism of different drug targets and explores methods to help understand drug resistance. In addition, it includes chapters dedicated to natural-product- derived medicines, combinatorial drug discovery, the CryoEM technique for structure-based drug design and big data in drug discovery.The book offers an invaluable resource for graduate and postgraduate students, as well as for researchers in academic and industrial laboratories working in the areas of chemoinformatics, medicinal and pharmaceutical chemistry and pharmacoinformatics.
R 5,832.30
Computational Physics - A Practical Introduction to Computational Physics and Scientific Computing (Using C++), Vol. I
This book is an introduction to the computational methods used in physics and other related scientific fields. It is addressed to an audience that has already been exposed to the introductory level of college physics, usually taught during the first two years of an undergraduate program in science and engineering. It assumes no prior knowledge of numerical analysis, programming or computers and teaches whatever is necessary for the solution of the problems addressed in the text. C++ is used for programming the core programs and data analysis is performed using the powerful tools of the GNU/Linux environment. All the necessary software is open source and freely available. The book starts with very simple problems in particle motion and ends with an in-depth discussion of advanced techniques used in Monte Carlo simulations in statistical mechanics. The level of instruction rises slowly, while discussing problems like the diffusion equation, electrostatics on the plane, quantum mechanics and random walks.
R 1,283.99
Design of Dynamic Data Structures
In numerous computer applications there is a need of storing large sets of objects in such a way that some questions about those objects can be answered efficiently. Data structures that store such sets of objects can be either static (built for a fixed set of objects) or dynamic (insertions of new objects and deletions of existing objects can be performed). Especially for more complex searching problems as they arise in such fields as computational geometry, database design and computer graphics, only static data structures are available. This book aims at remedying this lack of flexibility by providing a number of general techniques for turning static data structures for searching problems into dynamic structures. Although the approach is basically theoretical, the techniques offered are often practically applicable. The book is written in such a way that it is readable for those who have some elementary knowledge of data structures and algorithms. Although this monograph was first published in 1983, it is still unique as a general treatment of methods for constructing dynamic data structures.
R 1,538.58
Learning JavaScript Data Structures and Algorithms
If you are a JavaScript developer or someone who has basic knowledge of JavaScript, and want to explore its optimum ability, this fast-paced book is definitely for you. Programming logic is the only thing you need to know to start having fun with algorithms.
R 1,661.00
R 1,713.92
People and Data
Organizational data can be one of the most valuable assets in a business. However, too often an organization's structure prevents the effective analysis of this data. This book solves that problem. People and Data is a practical guide for Organization Development (OD) professionals which explains how to structure an organization so that the business can collect data that is accurate, useful and impactful. This is the foundation of achieving valuable insights from organizational data. This book is full of practical tips and advice on how to design an organization where data is accessible to the whole workforce and not just kept in silos by those with data in their job title. This book also explains how to build data into the design of company culture as well as into workforce design, learning and development (L&D) and talent management initiatives. Finally, People and Data includes a toolkit with eight specific tools that can be used to build a better organization for data. Full of practical advice, key takeaways and real-world examples from companies including AT&T, Shell and J.P. Morgan this book is essential reading for all Organization Development (OD) professionals needing to ensure that their organization is structured to achieve the performance gains made possible by data and analytics.
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R 1,466.00
Computer–Based Structure Elucidation from Spectral Data
Here, the authors introduce readers to solving molecular structure elucidation problems using the expert system ACD/Structure Elucidator. They explain in detail the concepts of the Computer-Assisted Structure Elucidation (CASE) approach and point out the crucial role of understanding the axiomatic nature of the data used to deduce the structure. Aspects covered include the main blocks of the expert system and essential features of the mathematical algorithms used. Graduate and PhD students as well as practicing chemists are provided with a detailed explanation of the various practical approaches depending on available spectral data peculiarities and the complexity of the unknown structure. This is supported by a large number of real-world completed examples, most of which are related to the structure elucidation of natural product molecules containing unusual skeletons. Dedicated software and further supplementary material are available at www.acdlabs.com/TeachingSE.
R 4,030.00
Automatic Coding: Choice of Data Structures
1.0 2 information structures, and the runtime efficiency available using lower level data structures. We believe these runtime inefficiencies can be remedied by providing a library of representations for the information structures and a user assisted automatic system to choose appropriate elements from this library for the user's programs. The main problems in such an automatic approach are: 1). Building a library of representations; 2). Characterizing the properties of these representations; 3). understanding how the user's program actually uses the abstract information structures; and -4). efficiently matching the user program needs with the properties of the known representations. The research reported here is an attempt to demonstrate the feasibility of such automatic representation selection. We allow the user to express data in terms of relations, sets, and sequences. Our system then obtains information by analysis of the program, execution statement profiles and interrogation of the user. Using that information, the system selects efficient (in terms of time and space) low level implementations for the user's information structures from a fixed library of information structure representations. Though we have considered only a few abstract information structures (those available in our programming language, SAIL) we believe the techniques used in this system are generally applicable.
R 1,254.00
Adaptive Processing of Sequences and Data Structures
This book is devoted to adaptive processing of structured information similar to flexible and intelligent information processing by humans - in contrast to merely sequential processing of predominantly symbolic information within a deterministic framework. Adaptive information processing allows for a mixture of sequential and parallel processing of symbolic as well as subsymbolic information within deterministic and probabilistic frameworks.The book originates from a summer school held in September 1997 and thus is ideally suited for advanced courses on adaptive information processing and advanced learning techniques or for self-instruction. Research and design professionals active in the area of neural information processing will find it a valuable state-of-the-art survey.
R 1,580.61
R 877.00
Data Mining Algorithms in C++
Discover hidden relationships among the variables in your data, and learn how to exploit these relationships. This book presents a collection of data-mining algorithms that are effective in a wide variety of prediction and classification applications. All algorithms include an intuitive explanation of operation, essential equations, references to more rigorous theory, and commented C++ source code.Many of these techniques are recent developments, still not in widespread use. Others are standard algorithms given a fresh look. In every case, the focus is on practical applicability, with all code written in such a way that it can easily be included into any program. The Windows-based DATAMINE program lets you experiment with the techniques before incorporating them into your own work.What You'll LearnUse Monte-Carlo permutation tests to provide statistically sound assessments of relationships present in your dataDiscover how combinatorially symmetric cross validation reveals whether your model has true power or has just learned noise by overfitting the dataWork with feature weighting as regularized energy-based learning to rank variables according to their predictive power when there is too little data for traditional methodsSee how the eigenstructure of a dataset enables clustering of variables into groups that exist only within meaningful subspaces of the dataPlot regions of the variable space where there is disagreement between marginal and actual densities, or where contribution to mutual information is highWho This Book Is ForAnyone interested in discovering and exploiting relationships among variables. Although all code examples are written in C++, the algorithms are described in sufficient detail that they can easily be programmed in any language.
R 1,980.80
Data Structure and Software Engineering
This title includes a number of Open Access chapters.Data structure and software engineering is an integral part of computer science. This volume presents new approaches and methods to knowledge sharing, brain mapping, data integration, and data storage. The author describes how to manage an organization’s business process and domain data and presents new software and hardware testing methods. The book introduces a game development framework used as a learning aid in a software engineering at the university level. It also features a review of social software engineering metrics and methods for processing business information. It explains how to use Pegasys to create and manage sequence analysis workflows.
R 4,020.83
R 1,600.01
R 550.00
Computational Modelling of Concrete and Concrete Structures
Computational Modelling of Concrete and Concrete Structures contains the contributions to the EURO-C 2026 conference (March 9-12, 2026, Seefeld in Tirol, Austria).The papers review and discuss research advancements and assess the applicability and robustness of methods and models for the analysis and design of concrete, fibre-reinforced, and prestressed concrete structures, as well as masonry structures. Recent developments encompass data-driven approaches, artificial intelligence, and machine learning methods, as well as novel discretization techniques, probabilistic models, and an increasing focus on microstructural aspects in a multi-scale and multi-physics context. Additionally, there is a noticeable trend towards material-scale innovations, including the use of more eco-efficient binders, new fibres, and 3D-printable concretes, along with life-cycle-oriented models that address the aging and durability of both new and existing concrete infrastructure.Overall computational robustness, mathematical and mechanical rigour, and the quality of predictions and have further increased, accompanied by careful model validation based on respective experimental programmes. The book will serve as an important reference for both academics and professionals, stimulating new research directions in the field of computational modelling of concrete and its application to the analysis of concrete structures.EURO-C 2026 is the ninth edition of the EURO-C conference series after Innsbruck 1994, Bad Gastein 1998, St. Johann im Pongau 2003, Mayrhofen 2006, Schladming 2010, St. Anton am Arlberg 2014, Bad Hofgastein 2018, and Vienna 2022. The overarching focus of the conferences is on computational methods and numerical models for the analysis of concrete and concrete structures.
R 12,679.85
Data Structures for Raster Graphics
Raster graphics differs from the more traditional vector or line graphics in the sense that images are not made up from line segments but from discrete elements orderly arranged in a two-dimensional rectangular region. There are two reasons for the growing popularity of raster graphics or bit-mapped displays: I) the possibilities they offer to show extremely realistic pictures 2) the dropping prices of those displays and associated processors and memories. With the rise of raster graphics, all kinds of new techniques, methods, algorithms and data representations are associated -such as ray tracing, raster operations, and quadtrees-bringing with them a lot of fruitful research. As stated above raster graphics allows to create extremely realistic (synthesized) pictures. There are important applications in such diverse areas as industrial deSign, flight Simulation, education, image processing and animation. Unfortunately many applications are hampered by the fact that with the present state of the art they reqUire an excessive amount of computing resources. Hence it is worthwhile to investigate methods and techniques which may be of help in redudng computer costs associated with raster graphics applications. Since the choice of data srtuc tures influences the efficiency of algorithms in a crudal way, a workshop was set up in order to bring together a (limited) number of experienced researchers to dis cuss this topic. The workshop was held from 24 to 28 June 1985 at Steensel, a tiny village in the neighbourhood of Eindhoven, the Netherlands.
R 4,335.32
Fundamentals of OOP and Data Structures in Java
Fundamentals of OOP and Data Structures in Java is a text for an introductory course on classical data structures. Part One of the book presents the basic principles of Object-Oriented Programming (OOP) and Graphical User Interface (GUI) programming with Java as the example language. Part Two introduces each of the major data structures with supporting, GUI-based laboratory programs designed to reinforce the basic concepts and principles of the text. These laboratories allow the reader to explore and experiment with the properties of each data structure. All source code for the laboratories is available on the web. By integrating the principles of OOP and GUI programming, this book takes the unique path of presenting the fundamental issues of data structures within the context of paradigms that are essential to today's professional software developer. The authors assume the reader has only an elementary understanding of Java and no experience with OOP.
R 4,574.54
Data Structures and Efficient Algorithms
Algorithms are a central concept in computer science. TheGerman Science Foundation (DFG) started a special jointinitiative on data structures and efficient algorithms in1986 with the aim of encouraging collaborative research onalgorithms. For a period of five years about a dozenprojects were funded with an emphasis on algorithms and datastructures for geometric problems, on the one hand, andparallel and distributed algorithms, on the other.This volume contains 18 papers that are intended to give animpression of the achievements of this joint researchinitiative. The first group of papers addresses research onfundamental data structures, computational geometry, graphalgorithms, computer graphics, and spatial databases. Thesecond group of papers centers on the following problems:the design of parallel architectures and routing strategies,simulation of parallel machines, and the design ofdistributed algorithms for solving difficult problems.
R 1,573.86
Assigning Structures to Ions in Mass Spectrometry
Summarizing our present knowledge of the structures and chemistry of small organic cations in the gas phase, Assigning Structures to Ions in Mass Spectrometry presents the methods necessary for determining gas-phase ion structures. It is a comprehensive resource of background material that is essential for the interpretation and understanding of organic mass spectra.Following a historical introduction of chief discoveries, the book surveys current experimental methods for ion production and separation as well as those designed to reveal qualitative and quantitative aspects of gas-phase ions. It also examines the computational chemistry and theoretical calculations that provide complementary thermochemical, structural, and mechanistic information. Five selected case studies illustrate specific challenges associated with ion structure assignment and thermochemical problems. The last major section of the book contains the data for describing or identifying all ions containing C alone and C with H, O, N, S, P, halogens, and small organic cations. Presenting material written by leading researchers in the field, Assigning Structures to Ions in Mass Spectrometry underscores the importance of understanding the behavior of small organic ions and gas-phase ion chemistry for making new ion structure assignments
R 2,907.20
Algorithms and Data Structures
This book constitutes the refereed proceedings of the 10th International Workshop on Algorithms and Data Structures, WADS 2007, held in Halifax, Canada, in August 2007. The papers present original research on the theory and application of algorithms and data structures in all areas, including combinatorics, computational geometry, databases, graphics, parallel and distributed computing.
R 3,099.49
