Data Structures Using C

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STANintroduces the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in

Collecting sensory data about people and the environment is now achievable using the latest advances of sensor and networking technologies such as environmental sensors, wearable sensors and social ne

Data stewards in any organization are the backbone of a successful data governance implementation because they do the work to make data trusted, dependable, and high quality. Since the publication of the first edition, there have been critical new developments in the field, such as integrating Data Stewardship into project management, handling Data Stewardship in large international companies, handling "big data" and Data Lakes, and a pivot in the overall thinking around the best way to align data stewardship to the data-moving from business/organizational function to data domain. Furthermore, the role of process in data stewardship is now recognized as key and needed to be covered.Data Stewardship, Second Edition provides clear and concise practical advice on implementing and running data stewardship, including guidelines on how to organize based on organizational/company structure, business functions, and data ownership. The book shows data managers how to gain support for a stewards

Federal Data Science serves as a guide for federal software engineers, government analysts, economists, researchers, data scientists, and engineering managers in deploying data analytics methods to go

Applications of Big Data in Healthcare: Theory and Practice begins with the basics of Big Data analysis and introduces the tools, processes and procedures associated with Big Data analytics. The book unites healthcare with Big Data analysis and uses the advantages of the latter to solve the problems faced by the former. The authors present the challenges faced by the healthcare industry, including capturing, storing, searching, sharing and analyzing data.This book illustrates the challenges in the applications of Big Data and suggests ways to overcome them, with a primary emphasis on data repositories, challenges, and concepts for data scientists, engineers and clinicians. The applications of Big Data have grown tremendously within the past few years and its growth can not only be attributed to its competence to handle large data streams but also to its abilities to find insights from complex, noisy, heterogeneous, longitudinal and voluminous data. The main objectives of Big Data in th

Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying

Chemometrics in Spectroscopy, Second Edition, provides the reader with the methodology crucial to apply chemometrics to real world data. It allows scientists using spectroscopic instruments to find ex

The Econometric Analysis of Network Data serves as an entry point for advanced students, researchers and data scientists who are seeking to perform effective analyses of networks, especially inference

Sweet Biochemistry: Remembering Structures, Cycles, and Pathways by Mnemonics makes biochemistry lively, interesting and memorable. by connecting objects, images and stories. Dr. Kumari has converted

Big Mechanisms in Systems Biology: Big Data Mining, Network Modeling, and Genome-Wide Data Identification explains big mechanisms of systems biology by system identification and big data mining method

Predictive Modeling of Drug Sensitivity gives an overview of drug sensitivity modeling for personalized medicine that includes data characterizations, modeling techniques, applications, and research c

Zoonotic Viruses of Northern Eurasia: Taxonomy and Ecology provides a review of modern data of the taxonomy, distribution, and ecology of zoonotic viruses in the ecosystems of Northern Eurasia. With c

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

Leveraging Biomedical and Healthcare Data: Semantics, Analytics and Knowledge provides an overview of the approaches used in semantic systems biology, introduces novel areas of its application, and de

Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for h

Viral Polymerases: Structures, Functions and Roles as Antiviral Drug Targets presents in-depth study information on the structure and functions of polymerases and their roles in the lifecycle of virus

Ranked Set Sampling: 65 Years Improving the Accuracy in Data Gathering is an advanced survey technique which seeks to improve the likelihood that collected sample data presents a good representation o

Numerical Methods: Using MATLAB, Fourth Edition, provides a clear, rigorous introduction to a wide range of numerical methods and their practical applications. The authors integrate MATLAB with numeri

Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the pr

Survey Data Analysis in Applied Settings provides readers with an accessible hands-on approach to modern day applied survey data analysis. It offers detailed insights and step-by-step methods and tech

Geophysical Data Analysis: Diverse Inverse Theory, Fourth Edition is a revised and expanded introduction to inverse theory and tomography as it is practiced by geophysicists. It demonstrates the metho

Data Literacy: How to Make Your Experiments Robust and Reproducible provides an overview of basic concepts and skills in handling data which are common to diverse areas of science. Readers will gain a

Heavy tailed data appears frequently in social science, internet traffic, insurance and finance. Statistical inference has been studied for many years, which includes recent bias-reduction estimation

Sliding Mode Control Using MATLAB provides many sliding mode controller design examples, along with simulation examples and MATLAB® programs. Following the review of sliding mode control, the book inc

Survival Analysis for Bivariate Truncated Data provides readers with a comprehensive review on the existing works on survival analysis for truncated data, mainly focusing on the estimation of univaria

Since 1984, Geophysical Data Analysis has filled the need for a short, concise reference on inverse theory for individuals who have an intermediate background in science and mathematics. The new editi

Formative Assessment, Learning Data Analytics and Gamification: An ICT Education discusses the challenges associated with assessing student progress given the explosion of e-learning environments, suc

Pervasive Computing: Next Generation Platforms for Intelligent Data Collection presents current advances and state-of-the-art work on methods, techniques, and algorithms designed to support pervasive

Numerical Methods using MATLAB, 3rd edition is an extensive reference offering hundreds of useful and important numerical algorithms that can be implemented into MATLAB for a graphical interpretation

This book contains 60 quality 2D NMR data sets following an introductory section describing the methodology employed. Many other books describe the methods used, but none offer a large number of probl

*Covers the latest standards and those being developed in an ever-evolving field *Provides insight into the latest technology of video and data over wireless networks and how convergence will be a dri

Web Semantics strengthen the description of web resources to exploit them better and make them more meaningful for both humans and machines, thereby contributing to the development of a knowledgeintensive data web. The world is experiencing the movement of concept from data to knowledge and the movement of web from document model to data model. The underlying idea is making the data machine understandable and processable.In the light of these trends, conciliation of Semantic and the Web is of paramount importance for further progress in the area. Web Semantics: Cutting Edge and Future Directions in Healthcare describes the three major components of the study of Semantic Web, namely Representation, Reasoning, and Security with a special focus on the healthcare domain. This book summarizes the trends and current research advances in web semantics, emphasizing the existing tools and techniques, methodologies, and research solutions.It provides easily comprehensible information on Web Sema

Dog Behavior: Modern Science and Our Canine Companions provides readers with a better understanding of canine science, including evolutionary concepts, ethograms, brain structures and development, sen

Translational Inflammation links laboratory and clinical data within primary and secondary care to clinical research data and offers a holistic and innovative approach to chronic inflammation and agei

Geographical and Fingerprinting Data for Positioning and Navigation Systems: Challenges, Experiences and Technology Roadmap explores the state-of-the -art software tools and innovative strategies to p

Tailored Thin Coatings for Corrosion Inhibition Using a Molecular Approach discusses the fundamentals and applications of various thin coatings for the inhibition of fouling and corrosion from a molec

Introduction to Quantitative Macroeconomics Using Julia: From Basic to State-of-the-Art Computational Techniques facilitates access to fundamental techniques in computational and quantitative macroeco

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary a

This elegantly edited landmark edition of Gert Kjærgård Pedersen’s C*-Algebras and their Automorphism Groups (1979) carefully and sensitively extends the classic work to reflect the wealth of relevant

Principles and Practice of Big Data: Preparing, Sharing, and Analyzing Complex Information, Second Edition updates and expands on the first edition, bringing a set of techniques and algorithms that ar