Java Data Object

We are living in a cyber society. Mobile devices, social media, the Internet, crime cameras, and other diverse sources can be pulled together to form massive datasets, known as big data, which make it

Pharmacokinetic and Pharmacodynamic Data Analysis: Concepts and Applications teaches everyday biological data analysis to the undergraduate and graduate levels. Through numerous examples and over 100

This book describes how the creation of new digital services -- through vertical and horizontal integration of data coming from sensors on top of existing legacy systems -- that has already had a majo

For readers who may not be statisticians or data analysts, Sarmento and Costa explain how to analyze data using the Python and R languages. They have particularly in mind, students and researchers

The overall goal of the book is to present the latest research on the new challenges of data technologies. It will offer an overview of the social, ethical and legal problems posed by group profiling,

Is there more to qualitative data collection than face-to-face interviews? Answering with a resounding 'yes', this book introduces the reader to a wide array of exciting and novel techniques for collecting qualitative data in the social and health sciences. Collecting Qualitative Data offers a practical and accessible guide to textual, media and virtual methods currently under-utilised within qualitative research. Contributors from a range of disciplines share their experiences of implementing a particular technique, provide step-by-step guidance to using that approach, and highlight both the potential and pitfalls. From gathering blog data to the story completion method to conducting focus groups online, the methods and data types featured in this book are ideally suited to student projects and other time- and resource-limited research. In presenting several innovative ways that data can be collected, new modes of scholarship and new research orientations are opened up to student rese

This book helps readers gain an in-depth understanding of electronic health record (EHR) systems, medical big data, and the regulations that govern them. It analyzes both the shortcomings and benefits of EHR systems, exploring the law's response to the creation of these systems, highlighting gaps in the current legal framework, and developing detailed recommendations for regulatory, policy, and technological improvements. Electronic Health Records and Medical Big Data addresses not only privacy and security concerns but also other important challenges, such as those related to data quality and data analysis. In addition, the author formulates a large body of recommendations to improve the technology's safety, security, and efficacy for both clinical and secondary (such as research) uses of medical data.

An essential guide to healthcare data problems, sources, and solutionsStrategies in Biomedical Data Science provides medical professionals with much-needed guidance toward managing the increasing delu

This book presents an overview of computational and statistical design and analysis of mass spectrometry-based proteomics, metabolomics, and lipidomics data. This contributed volume provides an introd

Fraud Data Analytics is the critical tool in locating and recognizing fraud scenario’s in today’s core business systems. This book will combine fraud risk assessment and the use of fraud data analytic

The first part of this book discusses institutions and mechanisms of algorithmic trading, market microstructure, high-frequency data and stylized facts, time and event aggregation, order book dynamics

This book will examine gun violence and crime in America. The emphasis in this text will be on the inadequacy of the data on firearm ownership. In addition, there will be a discussion of murder and ot

Focusing on the practical clinical and statistical issues that arise in pharmaceutical industry trials, this book summarizes the author’s experience in serving on many data monitoring committees (DMCs

Compliance with federal equal employment opportunity regulations, including civil rights laws and affirmative action requirements, requires collection and analysis of data on disparities in employment

Data structures are the fundamental building blocks of any computer program, used for storing, representing and manipulating data in a computer. This text presents the basic concepts of data structures as part of the art of writing computer programs. The author concentrates on the fundamentals of what should be done to solve a problem efficiently rather than technical implementation details. The text includes pseudocode and covers all the most common data structures, such as queues, stacks, trees, heaps, and hash tables, along with the basics of searching, sorting, and coding. This book can supplement any undergraduate algorithms or discrete math course and will also be accessible to students and researchers in other quantitative disciplines. No prerequisites beyond introductory programming and basic mathematics are required, and the accessible, conceptual presentation will appeal to undergraduates in many quantitative fields. Carefully designed problem sets with selected solutions wil

This book focuses on the analytic principles of business practice and big data. Specifically, it provides an interface between the main disciplines of engineering/technology and the organizational and

This textbook helps future data analysts comprehend aggregation function theory and methods in an accessible way, focusing on a fundamental understanding of the data and summarization tools. Offering

This book presents several compact and fast methods for online traffic measurement of big network data. It describes challenges of online traffic measurement, discusses the state of the field, and pro

From presentations to a July 2015 conference on operations and supply chain management at the University of Nottingham-Ningbo China, 12 papers that discuss big data were selected for publication he

This book is aimed at all those who wish to discover how to analyze categorical data without getting immersed in complicated mathematics and without needing to wade through a large amount of prose. It

This book introduces the reader to a new method of data assimilation with deterministic constraints (exact satisfaction of dynamic constraints)—an optimal assimilation strategy called Forecast Sensiti

This book is a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a

Libraries have begun developing services and programs to help researchers meet the demands of the data-driven research enterprise, giving librarians exciting new opportunities to use their expertise a

This edited volume gathers the proceedings of the Symposium GIS Ostrava 2016, the Rise of Big Spatial Data, held at the Technical University of Ostrava, Czech Republic, March 16–18, 2016. Combining th

Multi-state models describe stochastic processes that consist of transitions between states over time, such as the three-state illness-death model. Interval-censored data is extremely common as the ex

The ultimate objective of this book is to provide the academic and industrial communities with an in-depth introduction to the recent advances in development, theory, and impacts of Big Data, tailored

This highly original book is an ethnographic noir of how Big Data profits from patient private health information. The book follows personal health data as it is collected from inside healthcare and b

Computer scientists along with engineers in several fields address various challenges in operation management and how to overcome them using big data analytics. Among their topics are applying arti

The description for this book, Data Analysis for Scientists and Engineers, will be forthcoming.

This book provides an overview of the resources and research projects that are bringing Big Data and High Performance Computing (HPC) on converging tracks. It demystifies Big Data and HPC for the read

Philipp Meisen introduces a model, a query language, and a similarity measure enabling users to analyze time interval data. The introduced tools are combined to design and realize an information syste

Oceanographers and other environmental scientists, and engineers engaged with technology used in such fields, explore theoretical and historical aspects of cross-domain data management as applied to t

?? ?This book focuses on the uses of big data in the context of higher education. The book describes a wide range of administrative and operational data gathering processes aimed at assessing institut

Data Visualization: A Guide to Visual Storytelling for Libraries is a practical guide to the skills and tools needed to create beautiful and meaningful visual stories through data visualization. Learn

Advanced Data Analysis and Modeling in Chemical Engineering provides the mathematical foundations of different areas of chemical engineering and describes typical applications. The book presents the k

This book provides a comprehensive overview of music data analysis, from introductory material to advanced concepts. It covers various applications including transcription and segmentation as well as

Intelligence services, government administrations, businesses, and a growing majority of the population are hooked on the idea that big data can reveal patterns and correlations in everyday life. Init

This book inclusively and systematically presents the fundamental methods, models and techniques of practical application of grey data analysis, bringing together the authors’ many years of theoretica

"This book addresses the myriad of practical uses and innovative developments of data envelopment analysis, emphasizing the importance of analyzing productivity by measuring inputs, goals, economic gr

Big Data and Analytics is one of the hottest topics on the business agenda. However there are currently few (if any) industry-specific books on this topic. The book will deal with Big Data and Analyti