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Author: National Research Council Publisher: National Academies Press ISBN: 0309051789 Category : Social Science Languages : en Pages : 239
Book Description
How do you count a nation of more than 250 million peopleâ€"many of whom are on the move and some of whom may not want to be counted? How can you obtain accurate population information for apportioning the House of Representatives, allocating government resources, and characterizing who we are and how we live? This book attempts to answer these questions by reviewing the recent census operations and ongoing research and by offering detailed proposals for ways to improve the census.
Author: National Research Council Publisher: National Academies Press ISBN: 0309051789 Category : Social Science Languages : en Pages : 239
Book Description
How do you count a nation of more than 250 million peopleâ€"many of whom are on the move and some of whom may not want to be counted? How can you obtain accurate population information for apportioning the House of Representatives, allocating government resources, and characterizing who we are and how we live? This book attempts to answer these questions by reviewing the recent census operations and ongoing research and by offering detailed proposals for ways to improve the census.
Author: Maciej Wygralak Publisher: Springer ISBN: 3642346855 Category : Technology & Engineering Languages : en Pages : 294
Book Description
Counting belongs to the most elementary and frequent mental activities of human beings. Its results are a basis for coming to a decision in a lot of situations and dimensions of our life. This book presents a novel approach to the advanced and sophisticated case, called intelligent counting, in which the objects of counting are imprecisely, fuzzily specified. Formally, this collapses to counting in fuzzy sets, interval-valued fuzzy sets or I-fuzzy sets (Atanassov's intuitionistic fuzzy sets). The monograph is the first one showing and emphasizing that the presented methods of intelligent counting are human-consistent: are reflections and formalizations of real, human counting procedures performed under imprecision and, possibly, incompleteness of information. Other applications of intelligent counting in various areas of intelligent systems and decision support will be discussed, too. The whole presentation is self-contained, systematic, and equipped with many examples, figures and tables. Computer and information scientists, researchers, engineers and practitioners, applied mathematicians, and postgraduate students interested in information imprecision are the target readers.
Author: Institute of Medicine Publisher: National Academies Press ISBN: 0309316324 Category : Medical Languages : en Pages : 236
Book Description
Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients.
Author: New York (State). Court of Appeals. Publisher: ISBN: Category : Law Languages : en Pages : 968
Book Description
Volume contains: (Ppl of the State of NY against Manhattan Egg Co Inc) (Ppl of the State of NY against Manhattan Egg Co Inc) (Ppl of the State of NY against Manhattan Egg Co Inc) (Ppl of the State of NY against Robert Leslie Pohl & Charles Nelis Ploss) (Ppl of the State of NY against Robert Leslie Pohl & Charles Nelis Ploss) (Ppl of the State of NY against John Russo & Milton Singer & Jose DePeralta) (Ppl of the State of NY against John Russo & Milton Singer & Jose DePeralta) (Ppl of the State of NY against John Russo & Milton Singer & Jose DePeralta) (Ppl of the State of NY against Joseph Skolnick ) (Ppl of the State of NY against Joseph Skolnick ) (Ppl of the State of NY against Joseph Skolnick ) (Ppl of the State of NY against David Wichter & Edward Labis) (Ppl of the State of NY against David Wichter & Edward Labis) (Lillian Perelman against Samuel Spitzer) (Lillian Perelman against Samuel Spitzer) (Application; Patrick J. Picariello against William J. Heffernan et al) (Application; Patrick J. Picariello against William J. Heffernan et al) (Ppl of the State of NY against Anna Strasser) (Ppl of the State of NY against Anna Strasser) (Ppl of the State of NY against Anna Strasser) (Ppl of the State of NY against Anna Strasser) (Ppl of the State of NY against J.Vernel Jackson & Ppl of the State of NY) (Ppl of the State of NY against J.Vernel Jackson & Ppl of the State of NY) (Ppl of the State of NY against J.Vernel Jackson & Ppl of the State of NY) (Raleigh Assoc Inc against Ryder Henry, II) (Raleigh Assoc Inc against Ryder Henry, II) (Freda K. Ralph against the Board of Estimate of the City of NY et al ) (Freda K. Ralph against the Board of Estimate of the City of NY et al ) (Emil T. Rinas et al against Perry P. Duryea et al ) (Emil T. Rinas et al against Perry P. Duryea et al ) (Emil T. Rinas et al against Perry P. Duryea et al ) (Mary Rivers against Curtiss-Wright Corp & Insurance Carrier)
Author: Paul Clough Publisher: Springer ISBN: 364220161X Category : Computers Languages : en Pages : 821
Book Description
This book constitutes the refereed proceedings of the 33rd annual European Conference on Information Retrieval Research, ECIR 2011, held in Dublin, Ireland, in April 2010. The 45 revised full papers presented together with 24 poster papers, 17 short papers, and 6 tool demonstrations were carefully reviewed and selected from 223 full research paper submissions and 64 poster/demo submissions. The papers are organized in topical sections on text categorization, recommender systems, Web IR, IR evaluation, IR for Social Networks, cross-language IR, IR theory, multimedia IR, IR applications, interactive IR, and question answering /NLP.
Author: Catherine D'Ignazio Publisher: MIT Press ISBN: 0262358530 Category : Social Science Languages : en Pages : 328
Book Description
A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.
Author: National Research Council
Author: National Research Council
Author: Maciej Wygralak
Author: W. R. GRAY
Author: Louisiana. Supreme Court
Author: Institute of Medicine
Author: New York (State). Court of Appeals.
Author: Montana. Supreme Court
Author: Paul Clough
Author: Catherine D'Ignazio
Author: