Data Structures Using C

While covering the same spectra as the NBS registry of mass spectral data (Wiley, c.1989), this set presents the information differently to facilitate different usage. It selects from each spectrum

A knowledge of structural geology is fundamental to understanding the processes by which the earth's crust has evolved. It is a subject of fundamental importance to students of geology, experienced field geologists and academic researchers as well as to petroleum and mining engineers. In contrast to many structural textbooks which dwell upon geometrical descriptions of geological structures, this book emphasises mechanical principles and the way in which they can be used to understand how and why a wide range of geological structures develop. Structures on all scales are considered but the emphasis of the book is on those that can be seen on the scale of hand specimen or outcrop. Drawing on their considerable teaching experience the authors present a coherent and lucid analysis of geological structures which will be welcomed by a wide variety of earth scientists.

This book describes the principles and techniques needed to analyze data that form a multiway contingency table. Wickens discusses the description of association in such data using log-linear and log-

The central theme of this book is the theorem of Ambrose and Singer, which gives for a connected, complete and simply connected Riemannian manifold a necessary and sufficient condition for it to be homogeneous. This is a local condition which has to be satisfied at all points, and in this way it is a generalization of E. Cartan's method for symmetric spaces. The main aim of the authors is to use this theorem and representation theory to give a classification of homogeneous Riemannian structures on a manifold. There are eight classes, and some of these are discussed in detail. Using the constructive proof of Ambrose and Singer many examples are discussed with special attention to the natural correspondence between the homogeneous structure and the groups acting transitively and effectively as isometrics on the manifold.

Based on the popular Koffman style and self-teaching techniques, this new book teaches ANSI C to programmers who need an easy-to-understand introduction to the language. Using style standards that are

Table of Contents:1. The Where, Why, and How of Data Collection2. Graphs, Charts, and Tables–Describing Your Data3. Describing Data Using Numerical Measures1—3. Special Review Section4. Introduction t

Map out all of the key structures of the human body with examples of real human dissections...and easily place them in a clinical context! This popular atlas incorporates an unrivalled collection of c

This book describes in detail a research project dedicated to liquid-particle flow using ultrasound techniques. The project consists of theoretical, experimental, data science, finite element modeling, mechanical design and project management components. The objective of the project was to develop the ultrasonic methodology for measurement and characterization of liquid flow containing solid particles, in online (real-time) measurement conditions. The project consists of primary and complementary studies. The primary studies comprise development of the ultrasonic methodology for the simultaneous measurement of the average particle concentration and flow speed parameters. The developed methodology is based on the ultrasonic attenuation spectroscopy and the sound speed measurement methods, supported by data science programs. The complementary studies include acoustic streaming, designing a small-scale rotational test cell with an annular flow channel, testing it for various applications

Dynamic stability analysis enables the determination of unstable regions, which adversely affect a structure's durability. Unlike conventional cable-strut frameworks, tensegrity structures are characterized by a system of internal forces that hold the elements in stable equilibrium, so the initial prestress crucially affects the distribution of unstable regions. This book presents both theoretical background and examples to make a full qualitative and quantitative assessment of these structures possible. First, a geometrically non-linear model and the methods used to evaluate the behavior of tensegrity structures are explained, before a broad spectrum of different planar and spatial design solutions is considered. The book moves step-by-step from the simplest two-dimensional structure, for which solutions can be presented in explicit form, to more complex tensegrity structures such as domes, towers, and plates.

Your complete guide to Excel 365, written for newbies all the way to seasoned professionals Neatly organised and written using accessible language, Microsoft Excel 365 Bible contains everything that readers need to know to get up and running quickly with Excel. Covering the numerous updates to Excel 365 since the previous edition was published in 2022, this Second Edition contains many useful examples and tips and tricks that cover all essential aspects of Excel—from the basics, such as navigating the user interface, to more advanced topics, such as creating visualisations and crafting custom functions. Written by an accomplished team of authors with decades of Excel and business intelligence experience, this book explores topics including: Entering and editing worksheet data, with information on data types, formulas, dates, times and other cell contentsBuilding formulas with Excel table objects, correcting common formula errors and using formula variablesWorking with data series, chan

本書是廣受讚譽的《C# 圖解教程》的最新版本。作者在本書中創造了一種全新的可視化敘述方式，以圖文並茂的形式、樸實簡潔的文字，並輔以大量表格和代碼示例，全面、直觀地闡述了C# 語言的各種特性。新版本除了精心修訂舊版內容外，還全面涵蓋了C# 6.0 和C# 7.0 的新增特性，比如局部函數、throw 表達式、name of 和空條件運算符、using static 指令、異常過濾器，等等。通過本書，讀者能夠快速、深入地理解C#，為自己的編程生涯打下良好的基礎。

AI助攻！搭配ChatGPT學習效率加倍！ ★提供用書教師相關的教學資源★ 【資料結構】(Data Structures)是資訊科學領域中的基礎課程，多數資訊相關科系的研究所入學考試會將之列入考科，而諸如高考三級、地方特考、司法特考、鐵路考試中的資訊類別考試亦會將之列入考科，因此選擇一本觀念正確、條理清晰且掌握命題趨勢的書籍是很重要的。 本書以實例演練為導向，漸進式的學習架構，詳盡解說各種資料結構，期能帶領讀者了解其中的精髓，進而具備開發大型程式的功力。此外，為了因應未來報考資訊相關科系的研究所或準備國家考試，本書精選題型多元的考題，並融入相關章節、隨堂練習與學習評量，建議讀者勤加練習。 AI助攻 *使用【ChatGPT】輔助學習資料結構，例如查詢理論與實作、上傳圖片解題、出題練習、撰寫程式、優化與除錯、與其它程式語言互相轉換等，這些技巧大多不限定於ChatGPT，也可以靈活運用在【Microsoft Copilot】、【Google Gemini】等AI助理。 *本書是以C語言進行實作，讀者可以自行使用ChatGPT轉換成Python、C++、C#、Java等程式語言。 *ChatGPT相關內容統一放在本書最後一章，希望讀者以學會資料結構為主，而使用ChatGPT為輔，同時不會干擾到學習或上課的節奏。 考題觀摩 收錄研究所入學考試與資訊類別國家考試的精選考題，增加實例演練經驗，提升即戰力。

With easy-to-read language and illustrations on almost every page, the DATA Set chapter books are perfect for emerging readers.March of the Mini Beasts (The DATA Set #1)Don't Disturb the Dinosaurs (The DATA Set #2)The Sky Is Falling (The DATA Set #3)Robots Rule the School (The DATA Set #4)A Case of the Clones (The DATA Set #5)Invasion of the Insects (The DATA Set #6)Out of Remote Control (The DATA Set #7)Down the Brain Drain (The DATA Set #8)S.O.S. From Outer Space (The DATA Set #9)Revenge of Dr. von Naysayer (The DATA Set #10)A Little Snow Must Fall (The DATA Set #11)

This commentary covers all topics and critical aspects elicited by the new European General Data Protection Regulation and its interpretation. The commentary focuses on the regulation itself, including cross-references to further provisions (eg the Police and Criminal Justice Data Protection Directive, the E-Privacy-Directive or the former Data Protection Directive 95/46/EC).Article by article the purpose of a provision is classified, its background, function and structure analysed and its content interpreted. The commentary provides an independent view of all topics, presenting both an overview and specific interpretation that provide far-reaching arguments.The editors and authors are outstanding experts in the field of data protection law well known for their practical as well as structured and thorough approach to data protection issues. They offer suitable solutions and sound arguments especially for international companies, legal councils and corporate lawyers as well as data prot

Migrate from pandas and scikit-Learn to PySpark to handle vast amounts of data and achieve faster data processing time. This book will show you how to make this transition by adapting your skills and leveraging the similarities in syntax, functionality, and interoperability between these tools. Distributed Machine Learning with PySpark offers a roadmap to data scientists considering transitioning from small data libraries (pandas/scikit-learn) to big data processing and machine learning with PySpark. You will learn to translate Python code from pandas/scikit-learn to PySpark to preprocess large volumes of data and build, train, test, and evaluate popular machine learning algorithms such as linear and logistic regression, decision trees, random forests, support vector machines, Na鴳e Bayes, and neural networks. After completing this book, you will understand the foundational concepts of data preparation and machine learning and will have the skills necessary to apply these methods using

DISCOVERING COMPUTERS: DIGITAL TECHNOLOGY, DATA, AND DEVICES, 17th edition, teaches you not only the basics of technology, but also how you will use it -- and the responsibilities that go along with being a digital citizen. Focusing on current technology, the content addresses convergence of devices and platforms. Each module integrates practical how-to tips, ethics issues and security topics, while Consider This boxes woven throughout help you sharpen your critical-thinking skills. A variety of end-of-module activities -- checkpoint questions, small group activities and problem-solving exercises -- enable you to put what you learn into practice. MindTap digital learning solution is also available. Using an inviting approach that ensures understanding, DISCOVERING COMPUTERS equips you with the information you need for success at home, school and work.

Develop the analytical skills that are in high demand in businesses today with Camm/Cochran/Fry/Ohlmann's best-selling BUSINESS ANALYTICS, 5E. You master the full range of analytics as you strengthen descriptive, predictive and prescriptive analytic skills. Real examples and memorable visuals clearly illustrate data and results. Step-by-step instructions guide you through using Excel, Tableau, R or the Python-based Orange data mining software to perform advanced analytics. Practical, relevant problems at all levels of difficulty let you apply what you've learned. Updates throughout this edition address topics beyond traditional quantitative concepts, such as data wrangling, data visualization and data mining, which are increasingly important in today's business environment. MindTap and WebAssign online learning platforms are also available with an interactive eBook, algorithmic practice problems and Exploring Analytics visualizations to strengthen your understanding of key concepts.

An empirical study and analysis of heart disease prediction involves using data analysis techniques to identify patterns and risk factors associated with cardiovascular disease. This approach utilizes machine learning algorithms to classify patients based on their likelihood of developing heart disease.The study involves collecting data on risk factors such as age, gender, family history, blood pressure, cholesterol levels, smoking, and diabetes. Feature selection techniques are used to identify the most important risk factors, and a classification model is trained using these factors. The accuracy of the model is evaluated using metrics such as sensitivity, specificity, and AUC.This empirical study and analysis has several advantages, including the ability to identify new risk factors associated with heart disease, improved accuracy in predicting cardiovascular risk, and the potential to develop more personalized prevention and treatment strategies. This approach has the potential to

This book assesses data protection rules that are applicable to the processing of personal data in a law enforcement context. It offers the first extensive analysis of the LED and Regulation (EU) 2018/1725. It illustrates the challenges arising from the unclear delineation between the different data protection instruments at both national and EU level. Taking a practical approach, it exemplifies situations where the application of data protection instruments could give rise to a lowering of data protection standards where the data protection rules applicable in the law enforcement context are interpreted broadly. The scope of data protection instruments applied by law enforcement authorities impacts processing for purposes of border control, migration management and asylum because there is an unclear delineation between the different data protection instruments.

此版本中，內爾‧戴爾(Nell Dale)不再是《數據結構(C++ Plus 實現)(第 6 版)》的唯一作者。 本書加入了兩位作者――奇普‧威姆斯(Chip Weems)和蒂姆‧理查茲(Tim Richards)，並繼續保持以往版本的優良傳統。在其他論著方面，奇普與內爾合著了三十多年，如 Java Plus Data Structures，為本書及其早期版本奠定了基礎，並對教學方法的改進作出了重大貢獻。在 Programming and ProblemSolving in C++ 的最新版本中，蒂姆、奇普和內爾三人密切合作，共同致力於讓世界各地的學生能夠取得成功，同時他們對教學的熱愛也激勵著學生們每天走進教室學習。 在過去的二十年裡，傳統的數據結構課程已經發展到更廣泛的主題，包括抽象數據類型(AbstractData Type，ADT)、軟件工程和算法的基本分析。 數據結構(Data Structures)研究如何在組織關係中表示數據集合，以及如何編寫相應操作的算法。 抽象數據類型是指一個定義屬性的數據類型以及這個數據類型上的一組操作。計算機科學教育的重點向更加抽象的方向轉變。現在，在程序中除了研究如何表示對象之外，還研究數據對象類型的抽象屬性。 Johannes J．Martin 說得非常簡單：“從觀點來看，數據對象是由數據類型(對於使用者)或數據結構(對於實現者)來描述的。”a抽象的設計和實現都與軟件工程密切相關，軟件工程旨在將工程方法應用于開發可靠、健壯和高質量的軟件。一個糟糕的抽象會導致一組煩瑣的應用案例，迫使程序員要麼編寫不必要的複雜代碼，要麼忽略重要的有效性檢查。一個糟糕的實現可能導致效率低下或容易出錯。 高效實現的一個方面是能夠分析既定算法。因此，在本書中，我們將抽象和應用程序的實現分開介紹，並分析所介紹的算法。

How to use data as a tool for empowerment rather than oppression.Big data can be used for good, from tracking disease to exposing human rights violations, and for bad, implementing surveillance and control. Data inevitably represents the ideologies of those who control its use; data analytics and algorithms too often exclude women, the poor, and ethnic groups. In Data Action, Sarah Williams provides a guide for working with data in more ethical and responsible ways. Williams outlines a method that emphasizes collaboration among data scientists, policy experts, data designers, and the public. The approach generates policy debates, influences civic decisions, and informs design to help ensure that the voices of people represented in the data are neither marginalized nor left unheard.

Written by four leading experts, this book provides a comprehensive overview of sociolinguistic variation and linguistic change in Arabic. It introduces sociolinguistic theory, methods, and data step-by-step, using accessible language and extensive examples throughout. Topics covered include sociolinguistic methodology, social variables, language change, spatial variation, and contact and diffusion. Each topic is explained and illustrated using empirical data drawn from a wide array of Arabic-speaking communities in the Middle East and North Africa, as well as other parts of the world where Arabic is or was spoken, to provide a rich resource of individual dialects, as well as a comparative view of variation in Arabic. Each chapter also contains annotated suggestions for further reading and elaborate exercises. It is an essential resource for students studying Arabic in its social context, as well as anyone wishing to expand their knowledge of variation in Arabic.

Written by four leading experts, this book provides a comprehensive overview of sociolinguistic variation and linguistic change in Arabic. It introduces sociolinguistic theory, methods, and data step-by-step, using accessible language and extensive examples throughout. Topics covered include sociolinguistic methodology, social variables, language change, spatial variation, and contact and diffusion. Each topic is explained and illustrated using empirical data drawn from a wide array of Arabic-speaking communities in the Middle East and North Africa, as well as other parts of the world where Arabic is or was spoken, to provide a rich resource of individual dialects, as well as a comparative view of variation in Arabic. Each chapter also contains annotated suggestions for further reading and elaborate exercises. It is an essential resource for students studying Arabic in its social context, as well as anyone wishing to expand their knowledge of variation in Arabic.

An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deplo

CUDA is now the dominant language used for programming GPUs, one of the most exciting hardware developments of recent decades. With CUDA, you can use a desktop PC for work that would have previously required a large cluster of PCs or access to a HPC facility. As a result, CUDA is increasingly important in scientific and technical computing across the whole STEM community, from medical physics and financial modelling to big data applications and beyond. This unique book on CUDA draws on the author's passion for and long experience of developing and using computers to acquire and analyse scientific data. The result is an innovative text featuring a much richer set of examples than found in any other comparable book on GPU computing. Much attention has been paid to the C++ coding style, which is compact, elegant and efficient. A code base of examples and supporting material is available online, which readers can build on for their own projects.

A study of the Macchi Folgore and Veltro, the most successful Italian fighters in World War II. The book looks at how the fighters were conceived, their performance and their pilots’ stories.Italian fighters, such as the Fiat G.50 and Macchi C.200, had always struggled with their straight-line speed and restricted armament when engaging their Allied counterparts. To solve these problems, Macchi initially designed the C.202 Folgore using German engines, which contributed to create a faster aircraft, with a superior rate of climb and reachable altitude. Folgore’s success in various North African engagements then paved the way for the development of Macchi’s most successful fighter, the C.205V Veltro, which managed to combine increased speed and increased power. Packed with specially commissioned artwork and original photos, and written by Italian military aviation specialist Marco Mattioli, this fascinating book explores how the premier Italian fighter of the war came to life and the his

How to analyze data settings rather than data sets, acknowledging the meaning-making power of the local. In our data-driven society, it is too easy to assume the transparency of data. Instead, Yanni Loukissas argues in All Data Are Local, we should approach data sets with an awareness that data are created by humans and their dutiful machines, at a time, in a place, with the instruments at hand, for audiences that are conditioned to receive them. The term data set implies something discrete, complete, and portable, but it is none of those things. Examining a series of data sources important for understanding the state of public life in the United States--Harvard's Arnold Arboretum, the Digital Public Library of America, UCLA's Television News Archive, and the real estate marketplace Zillow--Loukissas shows us how to analyze data settings rather than data sets.Loukissas sets out six principles: all data are local; data have complex attachments to place; data are collected from heterogen

An integrated introduction to data visualization, strategic communication, and delivery best practices.Persuading with Data provides an integrated instructional guide to data visualization, strategic communication, and delivery best practices. Most books on data visualization focus on creating good graphs. This is the first book that combines both explanatory visualization and communication strategy, showing how to use visuals to create effective communications that convince an audience to accept and act on the data. In four parts that proceed from macro to micro, the book explains how our brains make sense of graphs; how to design effective graphs and slides that support your ideas; how to organize those ideas into a compelling presentation; and how to deliver and defend data to an audience. Persuading with Data is for anyone who has to explain analytical results to others. It synthesizes a wide range of skills needed by modern data professionals, providing a complete toolkit for cr

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Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets.Human-centered data science is a new interdisciplinary field that draws from human-computer interaction, social science, statistics, and computational techniques. This book, written by founders of the field, introduces best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of very large datasets. It offers a brief and accessible overview of many common statistical and algorithmic data science techniques, explains human-centered approaches to data science problems, and presents practical guidelines and real-world case studies to help readers apply these methods. The authors explain how data scientists’ choices are involved at every stage of the data science workflow―and show how a human-centered approach can enhance each one, by making the process more transparent, aski

An interdisciplinary and easy-to-understand introduction to the subject, covering fundamental theory and practical applications, and using numerous operational examples. This balanced text will allow you to begin from what the radar observes and move deeper through electromagnetic scattering theory and cloud microphysics to understand and interpret data as it appears on the display. It uses illustrations and figures of real radar observations to convey concepts and theory of atmospheric processes typically observed with weather radar, as well presenting a working knowledge of the radar system itself. In addition to covering fundamentals of scattering and atmospheric physics, topics include system hardware, signal processing, and radar networks. This is the perfect tool for scientists and engineers working on weather radars or using radars and their data, as well as senior undergraduate and graduate students studying weather radars.

Discover the world of engineering with fun, step-by-step projects. Take a closer look at the engineering behind the buildings and structures that surround us. Discover how engineers balance forces s

This volume challenges previous views of social organization focused on elites by offering innovative perspectives on 'power from below.' Using a variety of archaeological, anthropological, and historical data to question traditional narratives of complexity as inextricably linked to top-down power structures, it exemplifies how commoners have developed strategies to sustain non-hierarchical networks and contest the rise of inequalities. Through case studies from around the world – ranging from Europe to New Guinea, and from Mesoamerica to China – an international team of contributors explores the diverse and dynamic nature of power relations in premodern societies. The theoretical models discussed throughout the volume include a reassessment of key concepts such as heterarchy, collective action, and resistance. Thus, the book adds considerable nuance to our understanding of power in the past, and also opens new avenues of reflection that can help inform discussions about our collectiv

Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. This text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data science. An introductory chapter demonstrates that many standard problems in data science can be formulated as optimization problems. Next, many fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization of smooth (especially convex) functions; the stochastic gradient method, a workhorse algorithm in machine learning; the coordinate descent approach; several key algorithms for constrained optimization problems; algorithms for minimizing nonsmooth functions arising in data science; found

FIRST EDITION BRONZE RUNNER UP: Axiom Awards 2018 - Business Technology Category 90% of today's data was generated in the last two years and the amount of data we have available is predicted to double every two years. Data is an integral strategic asset for all businesses. Learn how to leverage this data and generate valuable insights from bestselling author and Big Data guru Bernard Marr. Data has massive potential for all businesses when used correctly, from small organizations to tech giants and huge multinationals. But this resource is too often not being fully utilized and is far from being arguably the world's most valuable resource. Data Strategy is the must-read guide on how to create a robust data-driven approach that will harness the power of data to revolutionize your business. Explaining how to collect, use and manage data, this book prepares any organization with the tools and strategies needed to thrive in the digital economy. This new edition of this bestselling title is

Data Science for COVID-19, Volume 2: Societal and Medical Perspectives presents the most current and leading-edge research into the applications of a variety of data science techniques to the detection, mitigation, treatment, and elimination of the COVID-19 virus around the world. At this point, Cognitive Data Science is the most powerful tool for researchers to fight COVID-19. Thanks to instant data-analysis and predictive techniques including Artificial Intelligence, Machine Learning, Deep Learning, Data Mining, and computational modeling for processing large amounts of data, recognizing patterns, modeling new techniques, and improving both research and treatment outcomes. Data Science for COVID-19, Volume 2 extends the coverage of Volume 1 into research on statistical data and applications of Data Science to a variety of perspectives for analysis and understanding of the wide variety of impacts COVID-19 is having on societies and medical practice around the world.

This book provides a general framework for doing geometric group theory for many non-locally-compact topological transformation groups that arise in mathematical practice, including homeomorphism and diffeomorphism groups of manifolds, isometry groups of separable metric spaces and automorphism groups of countable structures. Using Roe's framework of coarse structures and spaces, the author defines a natural coarse geometric structure on all topological groups. This structure is accessible to investigation, especially in the case of Polish groups, and often has an explicit description, generalising well-known structures in familiar cases including finitely generated discrete groups, compactly generated locally compact groups and Banach spaces. In most cases, the coarse geometric structure is metrisable and may even be refined to a canonical quasimetric structure on the group. The book contains many worked examples and sufficient introductory material to be accessible to beginning gradu

An examination of the phenomenon of mass shootings in America and an urgent call to implement evidence-based strategies to stop these tragedies Using data from the writers’ groundbreaking research on

Data are not only ubiquitous in society, but are increasingly complex both in size and dimensionality. Dimension reduction offers researchers and scholars the ability to make such complex, high dimensional data spaces simpler and more manageable. This Element offers readers a suite of modern unsupervised dimension reduction techniques along with hundreds of lines of R code, to efficiently represent the original high dimensional data space in a simplified, lower dimensional subspace. Launching from the earliest dimension reduction technique principal components analysis and using real social science data, I introduce and walk readers through application of the following techniques: locally linear embedding, t-distributed stochastic neighbor embedding (t-SNE), uniform manifold approximation and projection, self-organizing maps, and deep autoencoders. The result is a well-stocked toolbox of unsupervised algorithms for tackling the complexities of high dimensional data so common in modern