Data Structures Using C

Michael McMillan provides a complete presentation of the object-oriented features of the Visual Basic .NET language for advanced Visual Basic programmers. Beginning with an introduction to abstract data types and their initial implementation using structures, he explains standard OOP topics including class design, inheritance, access modifiers and scoping issues, abstract classes, design and implemention of interfaces and design patterns, and refactoring in VB.NET. More advanced OOP topics are included as well, such as reflection, object persistence, and serialization. To tie everything together, McMillan demonstrates sound OOP design and implementation principles through practical examples of standard Windows applications, database applications using ADO.NET, Web-based applications using ASP.NET, and Windows service applications.

Survival Analysis Using S: Analysis of Time-to-Event Data is designed as a text for a one-semester or one-quarter course in survival analysis for upper-level or graduate students in statistics, biosta

Spreadsheet skills are important for a first job, and DATA ANALYSIS USING MICROSOFT EXCEL prepares students to enter the world of work with stronger spreadsheet skills. Designed as a supplement to a m

Ideal for intermediate or advanced programmers, Object-Oriented Programming Using C++ for Engineering encourages users to adopt a pure object-oriented approach to problem solving. Introductory chapter

Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling method. Corporate data is increasingly important as companies

Microsoft Data Mining approaches data mining from the particular perspective of IT professionals using Microsoft data management technologies. The author explains the new data mining capabilities in

Computer simulations provide a powerful tool for understanding ecological and evolutionary systems. Simulating Ecological and Evolutionary Systems in C models a diverse range of biological processes and systems, including competition, foraging, predation, mating systems, and life-history optimization, by simulating large collections of interacting individuals. Using the widely available computer programming language C, the book starts with elementary programs modeling stochastic birth-death processes, slowly increasing programming complexity as the chapters progress. All the important features of C are covered, including arrays, files, pointers, and structures, within biologically motivated simulations. Although computer simulations of extremely complicated biological processes are released from rigid mathematical constraints, each of the simulations is also placed in the context of a mathematical formulation examined either analytically or numerically. Procedures covered include testi

A complete guide to radio data transmission Data Over Radio: Data and Digital Processing Techniques in Mobile and Cellular Radio is a comprehensive guide to data transmission and processing using radi

The combinatorial theory of species, introduced by Joyal in 1980, provides a unified understanding of the use of generating functions for both labelled and unlabelled structures and as a tool for the specification and analysis of these structures. Of particular importance is their capacity to transform recursive definitions of tree-like structures into functional or differential equations, and vice versa. The goal of this book is to present the basic elements of the theory and to give a unified account of its developments and applications. It offers a modern introduction to the use of various generating functions, with applications to graphical enumeration, Polya theory and analysis of data structures in computer science, and to other areas such as special functions, functional equations, asymptotic analysis and differential equations. This book will be a valuable reference to graduate students and researchers in combinatorics, analysis, and theoretical computer science.

本書根據東大技術高中英文(C 版) 第六冊，收錄完整課文中英對照、單字、片語例句，及句型說明、對話，與閱讀素養練習題。

本書根據東大技術高中英文(C 版) 第一冊，收錄完整課文中英對照、單字、片語例句，及句型說明、對話，與閱讀素養練習題。

This new volume addresses the growing interest in and use of big data analytics in many industries and in many research fields around the globe; it is a comprehensive resource on the core concepts of big data analytics and the tools, techniques, and methodologies. The book gives the why and the how of big data analytics in an organized and straightforward manner, using both theoretical and practical approaches.The book's authors have organized the contents in a systematic manner, starting with an introduction and overview of big data analytics and then delving into pre-processing methods, feature selection methods and algorithms, big data streams, and big data classification. Such terms and methods as swarm intelligence, data mining, the bat algorithm and genetic algorithms, big data streams, and many more are discussed. The authors explain how deep learning and machine learning along with other methods and tools are applied in big data analytics. The last section of the book presents

Straightforward, clear, and applied, this book will give you the theoretical and practical basis you need to apply data analysis techniques to real data. Combining key statistical concepts with detailed technical advice, it addresses common themes and problems presented by real research, and shows you how to adjust your techniques and apply your statistical knowledge to a range of datasets. It also embeds code and software output throughout and is supported by online resources to enable practice and safe experimentation. The book includes: · Original case studies and data sets · Practical exercises and lists of commands for each chapter · Downloadable Stata programmes created to work alongside chapters · A wide range of detailed applications using Stata · Step-by-step guidance on writing the relevant code. This is the perfect text for anyone doing statistical research in the social sciences getting started using Stata for data analysis.

As the world becomes increasingly connected, it is also more exposed to a myriad of cyber threats. We need to use multiple types of tools and techniques to learn and understand the evolving threat landscape. Data is a common thread linking various types of devices and end users. Analyzing data across different segments of cybersecurity domains, particularly data generated during cyber-attacks, can help us understand threats better, prevent future cyber-attacks, and provide insights into the evolving cyber threat landscape. This book takes a data oriented approach to studying cyber threats, showing in depth how traditional methods such as anomaly detection can be extended using data analytics and also applies data analytics to non-traditional views of cybersecurity, such as multi domain analysis, time series and spatial data analysis, and human-centered cybersecurity.

Excel Power Pivot & Power Query For Dummies, 2nd Edtion will give data professionals a foundation in the using Excel to transform their data. Use Power Query to get your data into Excel, and then enrich that data using Power Pivot. Integrate your data from multiple platforms, improve business intelligence, and analyze at a higher level when you follow the step-by-step guides in this book. Excel enables professionals to save time and increase efficiency. Trust Dummies to help you reach your full data potential!

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.

This textbook is a complete rewrite, and expansion of Hugh Rollinson's highly successful 1993 book Using Geochemical Data: Evaluation, Presentation, Interpretation. Rollinson and Pease's new book covers the explosion in geochemical thinking over the past three decades, as new instruments and techniques have come online. It provides a comprehensive overview of how modern geochemical data are used in the understanding of geological and petrological processes. It covers major element, trace element, and radiogenic and stable isotope geochemistry. It explains the potential of many geochemical techniques, provides examples of their application, and emphasizes how to interpret the resulting data. Additional topics covered include the critical statistical analysis of geochemical data, current geochemical techniques, effective display of geochemical data, and the application of data in problem solving and identifying petrogenetic processes within a geological context. It will be invaluable for

Work with data like a pro using this guide that breaks down how to organize, apply, and most importantly, understand what you are analyzing in order to become a true data ninja.From the stock market t

Learn how to deploy and monitor databases in the cloud, manipulate documents, visualize data, and build applications running on MongoDB using Node.jsKey FeaturesLearn the fundamentals of NoSQL databases with MongoDBCreate, manage, and optimize a MongoDB database in the cloud using AtlasUse a real-world dataset to gain practical experience of handling big dataBook DescriptionMongoDB is one of the most popular database technologies for handling large collections of data. This book will help MongoDB beginners develop the knowledge and skills to create databases and process data efficiently.Unlike other MongoDB books, MongoDB Fundamentals dives into cloud computing from the very start - showing you how to get started with Atlas in the first chapter. You will discover how to modify existing data, add new data into a database, and handle complex queries by creating aggregation pipelines. As you progress, you'll learn about the MongoDB replication architecture and configure a simple cluster.

The massive volume of data generated in modern applications can overwhelm our ability to conveniently transmit, store, and index it. For many scenarios, building a compact summary of a dataset that is vastly smaller enables flexibility and efficiency in a range of queries over the data, in exchange for some approximation. This comprehensive introduction to data summarization, aimed at practitioners and students, showcases the algorithms, their behavior, and the mathematical underpinnings of their operation. The coverage starts with simple sums and approximate counts, building to more advanced probabilistic structures such as the Bloom Filter, distinct value summaries, sketches, and quantile summaries. Summaries are described for specific types of data, such as geometric data, graphs, and vectors and matrices. The authors offer detailed descriptions of and pseudocode for key algorithms that have been incorporated in systems from companies such as Google, Apple, Microsoft, Netflix and T

Recent observational results from space- and ground-based telescopes have demonstrated that a unified approach to the relationships between solar and stellar magnetism is necessary to advance our understanding of magnetic fields. The Proceedings of IAU Symposium 354 present recent results and discussions of emerging topics, including: magnetic field diagnostics using high-resolution observation; initial data from ALMA, Chinese Radio Spectroheliograph and other instruments; the detection of stellar magnetospheres; and the detailed mapping of magnetic fields on the surface of stars using new unique instrumentation. These observations stimulate comparisons of solar and stellar results, and improve our understanding of how surface magnetic structures and their evolution are related to the generation of magnetic fields by dynamos in solar and stellar interiors. This volume benefits graduate students and researchers interested in the recent advances and key problems of solar and stellar magn

This book serves as a current resource for Photoplethysmogram (PPG) signal analysis using MATLAB®. This technology is critical in the evaluation of medical and diagnostic data utilized in mobile devic

Academic Writing with Corpora offers a step-by-step accessible guide to using concordancers and aims to help introduce data-driven learning into the academic English classroom.

Academic Writing with Corpora offers a step-by-step accessible guide to using concordancers and aims to help introduce data-driven learning into the academic English classroom.

Tackling structural geology problems today requires a quantitative understanding of the underlying physical principles, and the ability to apply mathematical models to deformation processes within the Earth. Accessible yet rigorous, this unique textbook demonstrates how to approach structural geology quantitatively using calculus and mechanics, and prepares students to interface with professional geophysicists and engineers who appreciate and utilize the same tools and computational methods to solve multidisciplinary problems. Clearly explained methods are used throughout the book to quantify field data, set up mathematical models for the formation of structures, and compare model results to field observations. An extensive online package of coordinated laboratory exercises enables students to consolidate their learning and put it into practice by analyzing structural data and building insightful models. Designed for single-semester undergraduate courses, this pioneering text prepares

This book introduces the field of data science in a practical and accessible manner, using a hands-on approach that assumes no prior knowledge of the subject. The foundational ideas and techniques of data science are provided independently from technology, allowing students to easily develop a firm understanding of the subject without a strong technical background, as well as being presented with material that will have continual relevance even after tools and technologies change. Using popular data science tools such as Python and R, the book offers many examples of real-life applications, with practice ranging from small to big data. A suite of online material for both instructors and students provides a strong supplement to the book, including datasets, chapter slides, solutions, sample exams and curriculum suggestions. This entry-level textbook is ideally suited to readers from a range of disciplines wishing to build a practical, working knowledge of data science.

This Progress with Oxford Numbers and Data Handling Age 8-9 workbook will help your child to progress with these core maths skills while having fun so they will become confident with using numbers an

Learn about the state-of-the-art at the interface between information theory and data science with this first unified treatment of the subject. Written by leading experts in a clear, tutorial style, and using consistent notation and definitions throughout, it shows how information-theoretic methods are being used in data acquisition, data representation, data analysis, and statistics and machine learning. Coverage is broad, with chapters on signal acquisition, data compression, compressive sensing, data communication, representation learning, emerging topics in statistics, and much more. Each chapter includes a topic overview, definition of the key problems, emerging and open problems, and an extensive reference list, allowing readers to develop in-depth knowledge and understanding. Providing a thorough survey of the current research area and cutting-edge trends, this is essential reading for graduate students and researchers working in information theory, signal processing, machine le

Seismic data must be interpreted using digital signal processing techniques in order to create accurate representations of petroleum reservoirs and the interior structure of the Earth. This book provides an advanced overview of digital signal processing (DSP) and its applications to exploration seismology using real-world examples. The book begins by introducing seismic theory, describing how to identify seismic events in terms of signals and noise, and how to convert seismic data into the language of DSP. Deterministic DSP is then covered, together with non-conventional sampling techniques. The final part covers statistical seismic signal processing via Wiener optimum filtering, deconvolution, linear-prediction filtering and seismic wavelet processing. With over sixty end-of-chapter exercises, seismic data sets and data processing MATLAB codes included, this is an ideal resource for electrical engineering students unfamiliar with seismic data, and for Earth Scientists and petroleum pr

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry, academia, an

When you need answers about using C# 8.0, this tightly focused and practical book tells you exactly what you need to know without long intros or bloated samples. Easy to browse, C# 8.0 Pocket Referenc

Evaluation for Health Policy and Health Care: A Contemporary Data-Driven Approach explores the best practices and applications for producing, synthesizing, visualizing, using, and disseminating health

Engaging and accessible, this book offers students a complete guide to using NVivo for qualitative data analysis. Drawing on their wealth of expertise, the authors offer detailed, practical advice tha

Using secondary data offers unique challenges. In this practical guide, the authors take you through finding, managing and analysing secondary data in an error-free way, using quantitative and qualita

Engaging and accessible, this book offers students a complete guide to using NVivo for qualitative data analysis. Drawing on their wealth of expertise, the authors offer detailed, practical advice tha

Using secondary data offers unique challenges. In this practical guide, the authors take you through finding, managing and analysing secondary data in an error-free way, using quantitative and qualita

The Educational Leader’s Guide to Improvement Science: Data, Design and Cases for Reflection is a collection illustrating applied organizational problem-solving using methods of Improvement Scien

This book shows how to analyze spatial and spatial-temporal data. It focuses on key datasets and data analysis, using the open source software WinBUGS, R, and GeoDa. It examines a range of different s

Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapt