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| Author | : José-Marie Griffiths |
| Publisher | : |
| Total Pages | : |
| Release | : 1984 |
| Genre | : Data structures (Computer science) |
| ISBN | : |
| Author | : José-Marie Griffiths |
| Publisher | : |
| Total Pages | : |
| Release | : 1984 |
| Genre | : Data structures (Computer science) |
| ISBN | : |
| Author | : Patricia Bazeley |
| Publisher | : SAGE |
| Total Pages | : 345 |
| Release | : 2017-09-25 |
| Genre | : Social Science |
| ISBN | : 1526417189 |
Integrating Analyses in Mixed Methods Research goes beyond mixed methods research design and data collection, providing a pragmatic discussion of the challenges of effectively integrating data to facilitate a more comprehensive and rigorous level of analysis. Showcasing a range of strategies for integrating different sources and forms of data as well as different approaches in analysis, it helps you plan, conduct, and disseminate complex analyses with confidence. Key techniques include: Building an integrative framework Analysing sequential, complementary and comparative data Identifying patterns and contrasts in linked data Categorizing, counting, and blending mixed data Managing dissonance and divergence Transforming analysis into warranted assertions With clear steps that can be tailored to any project, this book is perfect for students and researchers undertaking their own mixed methods research.
| Author | : Li-Chun Zhang |
| Publisher | : CRC Press |
| Total Pages | : 215 |
| Release | : 2019-04-18 |
| Genre | : Mathematics |
| ISBN | : 1351646729 |
The advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and recorded for different reasons. Data integration involves combining data residing in different sources to enable statistical inference, or to generate new statistical data for purposes that cannot be served by each source on its own. This can yield significant gains for scientific as well as commercial investigations. However, valid analysis of such data should allow for the additional uncertainty due to entity ambiguity, whenever it is not possible to state with certainty that the integrated source is the target population of interest. Analysis of Integrated Data aims to provide a solid theoretical basis for this statistical analysis in three generic settings of entity ambiguity: statistical analysis of linked datasets that may contain linkage errors; datasets created by a data fusion process, where joint statistical information is simulated using the information in marginal data from non-overlapping sources; and estimation of target population size when target units are either partially or erroneously covered in each source. Covers a range of topics under an overarching perspective of data integration. Focuses on statistical uncertainty and inference issues arising from entity ambiguity. Features state of the art methods for analysis of integrated data. Identifies the important themes that will define future research and teaching in the statistical analysis of integrated data. Analysis of Integrated Data is aimed primarily at researchers and methodologists interested in statistical methods for data from multiple sources, with a focus on data analysts in the social sciences, and in the public and private sectors.
| Author | : João M. F. Rodrigues |
| Publisher | : Springer |
| Total Pages | : 744 |
| Release | : 2019-06-07 |
| Genre | : Computers |
| ISBN | : 3030227448 |
The five-volume set LNCS 11536, 11537, 11538, 11539 and 11540 constitutes the proceedings of the 19th International Conference on Computational Science, ICCS 2019, held in Faro, Portugal, in June 2019. The total of 65 full papers and 168 workshop papers presented in this book set were carefully reviewed and selected from 573 submissions (228 submissions to the main track and 345 submissions to the workshops). The papers were organized in topical sections named: Part I: ICCS Main Track Part II: ICCS Main Track; Track of Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Track of Agent-Based Simulations, Adaptive Algorithms and Solvers; Track of Applications of Matrix Methods in Artificial Intelligence and Machine Learning; Track of Architecture, Languages, Compilation and Hardware Support for Emerging and Heterogeneous Systems Part III: Track of Biomedical and Bioinformatics Challenges for Computer Science; Track of Classifier Learning from Difficult Data; Track of Computational Finance and Business Intelligence; Track of Computational Optimization, Modelling and Simulation; Track of Computational Science in IoT and Smart Systems Part IV: Track of Data-Driven Computational Sciences; Track of Machine Learning and Data Assimilation for Dynamical Systems; Track of Marine Computing in the Interconnected World for the Benefit of the Society; Track of Multiscale Modelling and Simulation; Track of Simulations of Flow and Transport: Modeling, Algorithms and Computation Part V: Track of Smart Systems: Computer Vision, Sensor Networks and Machine Learning; Track of Solving Problems with Uncertainties; Track of Teaching Computational Science; Poster Track ICCS 2019 Chapter “Comparing Domain-decomposition Methods for the Parallelization of Distributed Land Surface Models” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
| Author | : Alexander Denev |
| Publisher | : John Wiley & Sons |
| Total Pages | : 416 |
| Release | : 2020-07-21 |
| Genre | : Business & Economics |
| ISBN | : 1119601797 |
The first and only book to systematically address methodologies and processes of leveraging non-traditional information sources in the context of investing and risk management Harnessing non-traditional data sources to generate alpha, analyze markets, and forecast risk is a subject of intense interest for financial professionals. A growing number of regularly-held conferences on alternative data are being established, complemented by an upsurge in new papers on the subject. Alternative data is starting to be steadily incorporated by conventional institutional investors and risk managers throughout the financial world. Methodologies to analyze and extract value from alternative data, guidance on how to source data and integrate data flows within existing systems is currently not treated in literature. Filling this significant gap in knowledge, The Book of Alternative Data is the first and only book to offer a coherent, systematic treatment of the subject. This groundbreaking volume provides readers with a roadmap for navigating the complexities of an array of alternative data sources, and delivers the appropriate techniques to analyze them. The authors—leading experts in financial modeling, machine learning, and quantitative research and analytics—employ a step-by-step approach to guide readers through the dense jungle of generated data. A first-of-its kind treatment of alternative data types, sources, and methodologies, this innovative book: Provides an integrated modeling approach to extract value from multiple types of datasets Treats the processes needed to make alternative data signals operational Helps investors and risk managers rethink how they engage with alternative datasets Features practical use case studies in many different financial markets and real-world techniques Describes how to avoid potential pitfalls and missteps in starting the alternative data journey Explains how to integrate information from different datasets to maximize informational value The Book of Alternative Data is an indispensable resource for anyone wishing to analyze or monetize different non-traditional datasets, including Chief Investment Officers, Chief Risk Officers, risk professionals, investment professionals, traders, economists, and machine learning developers and users.
| Author | : Phillip Chen-yu Sheu |
| Publisher | : World Scientific Publishing Company |
| Total Pages | : 250 |
| Release | : 2017-08-23 |
| Genre | : Computers |
| ISBN | : 9813227931 |
As the first volume of World Scientific Encyclopedia with Semantic Computing and Robotic Intelligence, this volume is designed to lay the foundation for the understanding of the Semantic Computing (SC), as a core concept to study Robotic Intelligence in the subsequent volumes.This volume aims to provide a reference to the development of Semantic Computing, in the terms of 'meaning', 'context', and 'intention'. It brings together a series of technical notes, in average, no longer than 10 pages in length, each focuses on one topic in Semantic Computing; being review article or research paper, to explain the fundamental concepts, models or algorithms, and possible applications of the technology concerned.This volume will address three core areas in Semantic Computing:
| Author | : Anthony J. Onwuegbuzie |
| Publisher | : Routledge |
| Total Pages | : 407 |
| Release | : 2021-07-12 |
| Genre | : Psychology |
| ISBN | : 1351395521 |
The Routledge Reviewer’s Guide to Mixed Methods Analysis is a groundbreaking edited book – the first devoted solely to mixed methods research analyses, or mixed analyses. Each of the 30 seminal chapters, authored by internationally renowned scholars, provides a simple and practical introduction to a method of mixed analysis. Each chapter demonstrates "how to conduct the analysis" in easy-to-understand language. Many of the chapters present new topics that have never been written before, and all chapters offer cutting-edge approaches to analysis. The book contains the following four sections: Part I Quantitative Approaches to Qualitative Data (e.g., factor analysis of text, multidimensional scaling of qualitative data); Part II Qualitative Approaches to Quantitative Data (e.g., qualitizing data, mixed methodological discourse analysis); Part III "Inherently" Mixed Analysis Approaches (e.g., qualitative comparative analysis, mixed methods social network analysis, social media analytics as mixed analysis, GIS as mixed analysis); and Part IV Use of Software for Mixed Data Analysis (e.g., QDA Miner, WordStat, MAXQDA, NVivo, SPSS). The audience for this book includes (a) researchers, evaluators, and practitioners who conduct a variety of research projects and who are interested in using innovative analyses that will allow them to extract more from their data; (b) academics, including faculty who would use this book in their scholarship, as well as in their graduate-level courses, and graduate students who need access to a comprehensive set of mixed analysis tools for their dissertations/theses and other research assignments and projects; and (c) computer-assisted data analysis software developers who are seeking additional mixed analyses to include within their software programs. Chapter 24 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.
| Author | : Liudmila Nickelson |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 348 |
| Release | : 2018-11-05 |
| Genre | : Mathematics |
| ISBN | : 3110941961 |
This book describes the solution of electrodynamic boundary problems, which arose in the practical life of a designer. It presents the results of computations of microstrip lines on magnetized (longitudinally and transversally) ferrite and semiconductor substrates taking into account all the geometric sizes. The book will be useful for students, engineers, designers and researchers. It contains a lot of computed results, which are verified experimentally and can be used immediately.
| Author | : Serge Tichkiewitch |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 489 |
| Release | : 2013-03-14 |
| Genre | : Technology & Engineering |
| ISBN | : 9401722560 |
SMC COLOMBIER FONTAINE is a company in the AFE METAL group, which uses a sand casting process to manufacture steel primary parts. To reduce the "time to market", primary part producers need to reduce the time and cost of the industrialisation process. These factors, in addition to the global goal of improving process performance levels, brought SMC to develop numerical technologies and traceability from quotation to part delivery [1]. Nowadays, these improvements are incorporated into company culture. The next step in reducing the time and cost of the production process is to introduce a complete methodology of use and experience feedback of these new models and methods. To be able to generalise this approach, a CAD methodology is essential and thus becomes a step in the industrialisation process. The amount of improvements engendered by the numerical technologies largely justifies the time investment made to obtain a numerical definition of all the different elements in the sand casting process [2]. The objective of our approach is to optimise the product and its production process by generating a complete numerical reference, through the integration of quotation, CAD, simulation, new manufacturing technologies and effective production processes.
