Java Data Object

With the onslaught of the Big Data revolution, data-based decision making and analytics are now the rage. However, many key decision makers often make complementary judgments based on intuition. This

The recent pursuits emerging in the realm of big data processing, interpretation, collection and organization have emerged in numerous sectors including business, industry and government organizations

This text provides both an introduction to and an advanced understanding of statistical modeling of ICU data. It addresses clinical endpoints used in ICU, such as different measures of mortality and t

Bitemporal data is coming, and major database management systems are beginning to support it. You need to know what is going on "under the hood" and this book that will make you the expert on bitempor

Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine

Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that

Cloud Networking: Developing Cloud-based Data Center Networks explains the evolution of established networking technologies into distributed, cloud-based systems. Starting with an overview of cloud te

These four volumes provide a collection of key publications on categorical data analysis, carefully put together so that the reader can easily navigate, understand and put in context the major concept

Find guidance on using SAS for multiple imputation and solving common missing data issues.Multiple Imputation of Missing Data Using SAS provides both theoretical background and constructive solutions

One of the first to do so, this book integrates the major approaches to APC analysis for aggregate-level data, such as uniform crime reports, vital statistics, and census data. It connects the traditi

This collection of essays brings together many of the world's most distinguished statisticians to discuss a wide array of the most important recent developments in data analysis. The book honors John

Insurers: use analytics to drive far more value from your most important asset -- data! Today, many insurers radically underutilize their data, leaving them vulnerable to traditional and non-tradition

This book explores the EU Dicode project, which facilitates collaboration and decision making in data-intensive and cognitively complex settings. The emphasis is on exploitation of big data, and on co

Get Ahead Medicine: OSCEs and Data Interpretation, the latest addition to the essential Get ahead! revision series, provides practical and invaluable revision for all medical students preparing for th

《21世紀應用型本科計算機專業實驗系列教材:Java語言實驗與課程設計指導（第2版）》針對應用型本科院校

Reference questions seeking the raw data that lies behind statistics is a service that has been mostly handled by academic research libraries. Yet with the growth of the Internet and the rise of relat

Massive amounts of data on human beings can now be analyzed. Pragmatic purposes abound, including selling goods and services, winning political campaigns, and identifying possible terrorists. Yet 'big data' can also be harnessed to serve the public good: scientists can use big data to do research that improves the lives of human beings, improves government services, and reduces taxpayer costs. In order to achieve this goal, researchers must have access to this data - raising important privacy questions. What are the ethical and legal requirements? What are the rules of engagement? What are the best ways to provide access while also protecting confidentiality? Are there reasonable mechanisms to compensate citizens for privacy loss? The goal of this book is to answer some of these questions. The book's authors paint an intellectual landscape that includes legal, economic, and statistical frameworks. The authors also identify new practical approaches that simultaneously maximize the utili

Massive amounts of data on human beings can now be analyzed. Pragmatic purposes abound, including selling goods and services, winning political campaigns, and identifying possible terrorists. Yet 'big data' can also be harnessed to serve the public good: scientists can use big data to do research that improves the lives of human beings, improves government services, and reduces taxpayer costs. In order to achieve this goal, researchers must have access to this data - raising important privacy questions. What are the ethical and legal requirements? What are the rules of engagement? What are the best ways to provide access while also protecting confidentiality? Are there reasonable mechanisms to compensate citizens for privacy loss? The goal of this book is to answer some of these questions. The book's authors paint an intellectual landscape that includes legal, economic, and statistical frameworks. The authors also identify new practical approaches that simultaneously maximize the utili

"This book concentrates on one particular and fast-growing application of mobile technologies: data acquisition for the tourism industry, providing travel agents, visitors, and hosts with the most adv

This entry-level text offers clear and concise guidelines on how to select, construct, interpret, and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models using numerous tables, insets, and detailed modeling suggestions. It begins by demonstrating the fundamentals of modeling count data, including a thorough presentation of the Poisson model. It then works up to an analysis of the problem of overdispersion and of the negative binomial model, and finally to the many variations that can be made to the base count models. Examples in Stata, R, and SAS code enable readers to adapt models for their own purposes, making the text an ideal resource for researchers working in health, ecology, econometrics, transportation, and other fields.

This entry-level text offers clear and concise guidelines on how to select, construct, interpret, and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models using numerous tables, insets, and detailed modeling suggestions. It begins by demonstrating the fundamentals of modeling count data, including a thorough presentation of the Poisson model. It then works up to an analysis of the problem of overdispersion and of the negative binomial model, and finally to the many variations that can be made to the base count models. Examples in Stata, R, and SAS code enable readers to adapt models for their own purposes, making the text an ideal resource for researchers working in health, ecology, econometrics, transportation, and other fields.

《Java語言程序設計(第2版):習題解答·實驗指導及實訓》是與《Java語言程序設計》（第二版）配套的輔助書，全書由三部分內容組成：第一部分是Java語言程序設計的精選習題解答，涵蓋了相關知識點，參考程序思路清晰、結構嚴謹、代碼優化；第二部分為實驗指導，共14個實驗，強調邊做邊學，理論聯系實際，鞏固基礎知識，可作為實驗課程的參考內容；第三部分為6個綜合實訓，階段性地給出了一些難度相當的綜合實訓題

This is a new edition of a highly praised, successful reference on data mining, now more important than ever due to the growth of the field and wide range of applications. This edition features new ch

This book emphasizes the collaborative analysis of data that is used to collect increments of time or space. Written at a readily accessible level, but with the necessary theory in mind, the author us

One of the grand challenges in our digital world are the large, complex and often weakly structured data sets, and massive amounts of unstructured information. This “big data” challenge is most eviden

In this comprehensive guide to using data to plan differentiated instruction, the authors present step-by-step techniques and planning tools to help teachers design learning that allows all students t

A modern and practical guide to the essential concepts and ideas for analyzing data with missing observations in the field of biostatisticsWith an emphasis on hands-on applications, Applied Missing Da

Addressing recent challenges and developments in this growing field, Multisensor Data Fusion Uncertainty Theory first discusses basic questions such as: Why and when is multiple sensor fusion necessar

Learn the value of conceptual, logical, and physical data modeling and how each stage increases our knowledge of the data and reduces assumptions and poor design decisions in MongoDB.

In many languages, the objects of transitive verbs are either marked by grammatical case or agreement on the verb, or they remain unmarked: this is differential object marking. This book is a cross-linguistic study of how differential object marking is affected by information structure, the structuring of the utterance in accordance with the informational value of its elements and contextual factors. Marked objects tend to be associated with old information or information that the sentence is about, while unmarked objects tend to express new information. The book also sheds light on grammatical patterning in languages with differential object marking: in some languages marked and unmarked objects have identical grammatical properties, whereas in other languages marked objects are more active in syntax. Finally, it provides a theory of the historical changes that lead to the emergence of various patterns of differential object marking.

"This book provides a central source of reference on the various data management techniques of large scale data processing and its technology application. This book presents chapters written by leadin

Rather than the broad array of topics in most textbooks on business databases, Umanath and Scamell focus on data modeling and database design to provide a robust understanding of these core areas. Thi

This book provides a comprehensive overview of calibration and validation techniques for traffic simulation models. It details the data required as an input for the calibration and validation processe

In four studies written during the first and second decades of the century, Csatar considers some of the basic questions of methodology and data structure in the cognitive research of metaphor. They c

What are the most effective methods to code and analyze data for a particular study? This thoughtful and engaging book reviews the selection criteria for coding and analyzing any set of data--whether

What are the most effective methods to code and analyze data for a particular study? This thoughtful and engaging book reviews the selection criteria for coding and analyzing any set of data--whether

Traditional Database Management Systems are built on the concept of persistent data sets, that are stored reliably in stable storage and queried/updated several times throughout their lifetime. For se

This revised and updated edition focuses on constrained ordination (RDA, CCA), variation partitioning and the use of permutation tests of statistical hypotheses about multivariate data. Both classification and modern regression methods (GLM, GAM, loess) are reviewed and species functional traits and spatial structures analysed. Nine case studies of varying difficulty help to illustrate the suggested analytical methods, using the latest version of Canoco 5. All studies utilise descriptive and manipulative approaches, and are supported by data sets and project files available from the book website: http://regent.prf.jcu.cz/maed2/. Written primarily for community ecologists needing to analyse data resulting from field observations and experiments, this book is a valuable resource to students and researchers dealing with both simple and complex ecological problems, such as the variation of biotic communities with environmental conditions or their response to experimental manipulation.

"This book highlights contemporary findings in the area of biologically-inspired techniques in data mining domains and their implementation in real-life problems"--

"This book explores current research in data mining, including the important trends and patterns and their impact in fields such as software engineering, and focuses on modern techniques as well as pa