Data Structures Using C

C語言是學習其他程序設計語言的基礎，也是編寫硬體相關的嵌入式系統等系統級程式的優秀工具。本書從貼近CPU和內存原理的角度，給讀者提供了一個學習—實踐—應用C語言的逐步掌握C語言並成為C程序員的技能提升方案。全書分5篇17章。前3篇分別講述C語言的起步知識、控制程式流程的基礎、編寫基本C代碼的組織工具；第4篇包含了編寫系統級程式所需要的C指標、結構體、編譯預處理等關鍵知識；第5篇提供了應用C開發程式

學完Scratch就學C++吧！《從Scratch到C++輕鬆學》是專門為學過Scratch編程的青少年編寫的C++編程入門教材，採用雙語(Scratch語言和C++語言)教學的方式講授編程知識，以解決問題為導向，培養青少年的編程思維。本書分為：程序設計基礎、數據結構和算法、趣味數學探秘，以及神奇的分形圖四個部分，採用青少年喜聞樂見的趣味案例進行教學，指導青少年從Scratch編程順利過渡到C++

● 燃動心跳+甜到上頭● 2020現象級甜寵電競文● 電子競技，菜是原罪/戀愛關係，甜是必備● 你是電競世界第一C位，更是我心中完美的C位戀人當世界第一C位遭遇御姐戰隊經理人，一場眼花繚亂的防守反擊正式打響“什麼是電子競技？”“是夢想、是激情、是榮耀、是信念、是一個時代，一個屬於少年人的時代。”“什麼是愛？”“是攜手並進，是心有靈犀，是你！”蘇敘，電競界的遠古傳說，曾經的世界第一C位，玩家心中不滅

Building upon the success of the first edition, Statistics Using Stata uses the latest version of Stata to meet the needs of today's students. Engaging and accessible for students from a variety of mathematical backgrounds, this textbook integrates statistical concepts with the Stata (version 16) software package. It aligns Stata commands with examples based on real data, enabling students to understand statistics in a way that reflects statistical practice. Capitalizing on Stata's menu-driven 'point and click' and program syntax interface, the chapters guide students from the comfortable 'point and click' environment to the beginnings of statistical programming. Its coverage of essential topics gives instructors flexibility in curriculum planning and provides students with more advanced material to prepare for future work. Online resources - including solutions to exercises, PowerPoint slides, and Stata syntax (do-files) for each chapter - allow students to review independently and ad

Qualitative Data Collection Tools is a new and unique supplementary text that will guide students and new researchers to design, develop, pilot, and employ qualitative tools in order to collect qualit

Fundamental tenets of colonial historiography are challenged by showing that US capital investment into this colony did not lead to the disappearance of the small farmer. Contrary to well-established narratives, quantitative data show that the increasing integration of rural producers within the US market led to differential outcomes, depending on pre-existing land tenure structures, capital requirements to initiate production, and demographics. These new data suggest that the colonial economy was not polarized into landless Puerto Rican rural workers on one side and corporate US capitalists on the other. The persistence of Puerto Rican small farmers in some regions and the expansion of local property ownership and production disprove this socioeconomic model. Other aspects of extant Puerto Rican historiography are confronted in order to make room for thorough analyses and new conclusions on the economy of colonial Puerto Rico during the early twentieth century.

In Digital Data Collection and Information Privacy Law, Mark Burdon argues for the reformulation of information privacy law to regulate new power consequences of ubiquitous data collection. Examining developing business models, based on collections of sensor data - with a focus on the 'smart home' - Burdon demonstrates the challenges that are arising for information privacy's control-model and its application of principled protections of personal information exchange. By reformulating information privacy's primary role of individual control as an interrupter of modulated power, Burdon provides a foundation for future law reform and calls for stronger information privacy law protections. This book should be read by anyone interested in the role of privacy in a world of ubiquitous and pervasive data collection.

Getting numbers is easy; getting numbers you can trust is hard. This practical guide by experimentation leaders at Google, LinkedIn, and Microsoft will teach you how to accelerate innovation using trustworthy online controlled experiments, or A/B tests. Based on practical experiences at companies that each run more than 20,000 controlled experiments a year, the authors share examples, pitfalls, and advice for students and industry professionals getting started with experiments, plus deeper dives into advanced topics for practitioners who want to improve the way they make data-driven decisions. Learn how to • Use the scientific method to evaluate hypotheses using controlled experiments • Define key metrics and ideally an Overall Evaluation Criterion • Test for trustworthiness of the results and alert experimenters to violated assumptions • Build a scalable platform that lowers the marginal cost of experiments close to zero • Avoid pitfalls like carryover effects and Twyman's law • Unde

Specifically designed for linguists, this book provides an introduction to programming using Python for those with little to no experience of coding. Python is one of the most popular and widely-used programming languages as it's also available for free and runs on any operating system. All examples in the text involve language data and can be adapted or used directly for language research. The text focuses on key language-related issues: searching, text manipulation, text encoding and internet data, providing an excellent resource for language research. More experienced users of Python will also benefit from the advanced chapters on graphical user interfaces and functional programming.

Specifically designed for linguists, this book provides an introduction to programming using Python for those with little to no experience of coding. Python is one of the most popular and widely-used programming languages as it's also available for free and runs on any operating system. All examples in the text involve language data and can be adapted or used directly for language research. The text focuses on key language-related issues: searching, text manipulation, text encoding and internet data, providing an excellent resource for language research. More experienced users of Python will also benefit from the advanced chapters on graphical user interfaces and functional programming.

This is an introductory textbook on spatial analysis and spatial statistics through GIS. Each chapter presents methods and metrics, explains how to interpret results, and provides worked examples. Topics include: describing and mapping data through exploratory spatial data analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression and OLS regression; and spatial econometrics. The worked examples link theory to practice through a single real-world case study, with software and illustrated guidance. Exercises are solved twice: first through ArcGIS, and then GeoDa. Through a simple methodological framework the book describes the dataset, explores spatial relations and associations, and builds models. Results are critically interpreted, and the advantages and pitfalls of using various spatial analysis methods are discussed. This is a valuable resource for graduate students and researchers analyzing geospa

This is an introductory textbook on spatial analysis and spatial statistics through GIS. Each chapter presents methods and metrics, explains how to interpret results, and provides worked examples. Topics include: describing and mapping data through exploratory spatial data analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression and OLS regression; and spatial econometrics. The worked examples link theory to practice through a single real-world case study, with software and illustrated guidance. Exercises are solved twice: first through ArcGIS, and then GeoDa. Through a simple methodological framework the book describes the dataset, explores spatial relations and associations, and builds models. Results are critically interpreted, and the advantages and pitfalls of using various spatial analysis methods are discussed. This is a valuable resource for graduate students and researchers analyzing geospa

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts. New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning.

This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix no

Social media data can be vast and understanding which data source works best for a research project, as well as the ethical considerations it requires and how to go about extracting and analysing this

本書共12章,主要內容包括C&.C++語言的程序實例簡介、3種控制結構、函數、數組、字符串、自定義數據類型、文件和基本的面向對象程序設計。本書選取工程應用中的數據處理、數學運算等實例及重要算法, 引導學生充分掌握C++標準庫。

The Vintage Recordings and Data A5 Journal from Galison features a series of analog images from the past such as a vinyl album, floppy disc, VHS tape, cassette tape, and many more. The journal has sle

Why do governments backtrack on major policy reforms? Reversals of pension privatization provide insight into why governments abandon potentially path-departing policy changes. Academics and policymakers will find this work relevant in understanding market-oriented reform, authoritarian and post-communist politics, and the politics of aging populations. The clear presentation and multi-method approach make the findings broadly accessible in understanding social security reform, an issue of increasing importance around the world. Survival analysis using global data is complemented by detailed case studies of reversal in Russia, Hungary, and Poland including original survey data. The findings support an innovative argument countering the conventional wisdom that more extensive reforms are more likely to survive. Indeed, governments pursuing moderate reform - neither the least nor most extensive reformers - were the most likely to retract. This lends insight into the stickiness of many so

C++是在C語言基礎上開發的一種集面向對象編程、通用編程和傳統的過程化編程於一體的編程語言，是C語言的超集。《C++ Primer Plus（第6版）（中文版）》是根據2003年的ISO/ANSI C++標準編寫的。通過大量短小精悍的程序詳細而闡述了C++的基本概念和技術。全書分為18章和10個附錄，分別介紹了C++程序的運行方式、基本數據類型、複合數據類型、循環和關系表達式、分支語句和邏輯操作符、函數重載和函數模板、內存模型和名稱空間、類的設計和使用、多態、虛函數、動態內存分配、繼承、代碼重用、友元、異常處理技術、string類和標準模板庫、輸入/輸出等內容。本書針對C++初學者，從C語言基礎知識開始介紹，然後在此基礎上詳細闡述C++新增的特性，因此不要求讀者有較多C語言方面的背景知識。本書可以作為高等院校C++課程的教材，也可以供初學者自學C++時使用。

眾多高級語言都從C/C++有所借鑒，所以說C/C++的語言基礎對從事軟件開發的人員來說非常重要。 《

本書從基本的C++概念入手，由淺入深，以典型實例、綜合實例剖析講解，一步一步引導初學者掌握C++知識。本書共18章，其中第1～4章是C++基礎篇；第5～9章是C++核心篇；第10～13章是C++面向對象程序設計篇；第14～17章是C++提高篇；第18章是綜合案例實戰篇，通過職工信息管理系統的編寫，使初學者提高對C++編程的綜合認識，並真正掌握編程的核心思想及技巧，從而學以致用。 在講解過程中既考

The idea of a right to privacy, which arose in reaction to the rapid rise of newspapers, instant photography and the “paparazzi” of the 19th century, has evolved into a constitutional right in much of the developed world. It is enshrined in Hong Kong through Articles 28, 29, 30 and 39 of the Basic Law. Hong Kong stands proud as the first jurisdiction in Asia to enact legislation to safeguard personal data in the form of the Personal Data (Privacy) Ordinance, Cap 486 (“the Ordinance”) which came into force in 1996. At its centre are the six Data Protection Principles based on the 1980 OECD Guidelines. The office of the Privacy Commissioner for Personal Data was created under this legislation to provide oversight and ensure compliance. The Octopus scandal in mid-2010 eventually led to substantial changes being made to the Ordinance that were enacted in 2012 and 2013, the main amendments being the Direct Marketing provisions and the provision of legal assistance and representation to aggr

Biology has entered the age of Big Data. A technical revolution has transformed the field, and extracting meaningful information from large biological data sets is now a central methodological challenge. Algebraic topology is a well-established branch of pure mathematics that studies qualitative descriptors of the shape of geometric objects. It aims to reduce comparisons of shape to a comparison of algebraic invariants, such as numbers, which are typically easier to work with. Topological data analysis is a rapidly developing subfield that leverages the tools of algebraic topology to provide robust multiscale analysis of data sets. This book introduces the central ideas and techniques of topological data analysis and its specific applications to biology, including the evolution of viruses, bacteria and humans, genomics of cancer, and single cell characterization of developmental processes. Bridging two disciplines, the book is for researchers and graduate students in genomics and evolu

Ｃ語言大師經典名作至今仍然歷久不衰 幫助你避開編寫Ｃ語言時各種意外陷阱 無論是新手老手高手都應該要案頭備存 作者以自己1985年在Bell實驗室時發表的一篇論文為基礎，結合自己的工作經驗，進而成為這本對C語言程式設計師具有珍貴價值的經典著作。寫作本書的出發點並不是要批判C語言，而是要幫助C語言程式設計師繞過編寫過程中的陷阱和障礙。 全書分為8章，分別從詞法分析、語法語義、連接、庫函數、預處理器、可

The question of what types of data and evidence can be used is one of the most important topics in linguistics. This book is the first to comprehensively present the methodological problems associated with linguistic data and evidence. Its originality is twofold. First, the authors' approach accounts for a series of unexplained characteristics of linguistic theorising: the uncertainty and diversity of data, the role of evidence in the evaluation of hypotheses, and the problem solving strategies, as well as the emergence and resolution of inconsistencies. Second, the findings are obtained by the application of a new model of plausible argumentation which is also of relevance from a general argumentation theoretical point of view. All concepts and theses are systematically introduced and illustrated by a number of examples from different linguistic theories, and a detailed case-study section shows how the proposed model can be applied to specific linguistic problems.

Your logical, linear guide to the fundamentals of data science programming Data science is exploding--in a good way--with a forecast of 1.7 megabytes of new information created every second for each h

Statistics, Data Mining, and Machine Learning in Astronomy is the essential introduction to the statistical methods needed to analyze complex data sets from astronomical surveys such as the Panoramic

《深入理解C#(第3版)》是C#領域不可多得的經典著作。作者在詳盡地展示C#各個知識點的同時，更注重從現象中挖掘本質。《深入理解C#(第3版)》深入探索了C#的核心概念和經典特性，并將這些特性融入到代碼中，讓讀者能夠真正領會到C#之“深入”與“精妙”。在第2版的基礎上，《深入理解C#(第3版)》新增了C# 5的新特性——異步，并更新了隨著技術的發展，已經不再適用的內容，確保整本書能達到讀者期望

The successful collection of data is a key challenge to obtaining reliable and valid results in applied linguistics research. Data Collection Research Methods in Applied Linguistics investigates how r

本書為安徽省高等學校“十二五”省級規劃教材《C/C++規範設計簡明教程》的修訂版。書中引入C/C++語言最新標準，並對某些概念和案例進行了重新描述，重點對團隊開發合作編程提出了git工作流設計方案，將理論學習與實戰結合起來。 本書體現編程思想（世界觀）->方法（方法論）->規範（規 則）的統一思想，這種思想是教材編寫的核心。本書既可作為高等院校計算機類相關專業的C/C++程序設計教材，也可供C/C

本書結合C++語言系統地介紹了面向對象技術的基本知識及其應用。本書以C++面向對象為基礎, 與Visual C++應用融會貫通, 為讀者構架了一個完整的體系。本書共分三大部分。第一部分: 第12章是基礎部分, 主要介紹面向對象技術的基本概念和基本特徵, C++對C語言基礎的擴展, 說明與C語言基礎的不同; 第二部分: 第38章是核心部分, 主要介紹C++面向對象技術, 圍繞抽象性、封裝性、繼承性、

ICCGS 2019 is intended for naval architects, marine engineers and academics, and focusses on: collision and grounding of ships, collisions between ships and icebergs, offshore structures, bridges

After a short description of the key concepts of big data the book explores on the secrecy and security threats posed especially by cloud based data storage. It delivers conceptual frameworks and mode

Intelligent Data Mining and Fusion Systems in Agriculture presents methods of computational intelligence and data fusion that have applications in agriculture for the non-destructive testing of agricu

Topics covered in the book include: Methods and tools for loads and load effects, Methods and tools for strength assessment, Experimental analysis of structures, Materials and fabrication of structure

Gathering Social Network Data provides an important complement to existing books that focus on social network analysis, and offers more detailed coverage than is available in existing chapter-length t

本書以計算思維的運用與訓練為目標, 以程序設計實訓為手段, 闡述了運用C語言和C++語言分析問題和解決問題的方法與技巧。本書內容分為C語言篇與C++語言篇, 由簡入難, 向讀者展現面向過程思維到面向對象思維的發展過程。本書可作為高等院校“C&C++語言程序設計”的教學用書, 也可以作為高等院校單獨課程“C語言程序設計”和“C++語言程序設計”教學用書, 還可以作為C語言和 C++語言的自學或教學參考書。

Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-cl

This book provides a self-contained introduction to the simulation of flow and transport in porous media, written by a developer of numerical methods. The reader will learn how to implement reservoir simulation models and computational algorithms in a robust and efficient manner. The book contains a large number of numerical examples, all fully equipped with online code and data, allowing the reader to reproduce results, and use them as a starting point for their own work. All of the examples in the book are based on the MATLAB Reservoir Simulation Toolbox (MRST), an open-source toolbox popular popularity in both academic institutions and the petroleum industry. The book can also be seen as a user guide to the MRST software. It will prove invaluable for researchers, professionals and advanced students using reservoir simulation methods. This title is also available as Open Access on Cambridge Core.

Big Data is everywhere. It shapes our lives in more ways than we know and understand. This comprehensive introduction unravels the complex terabytes that will continue to shape our lives in ways imagi