896 resultados para computation- and data-intensive applications
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Mode of access: Internet.
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"Education is everyone's future."
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"Sections 3-14.27,10-21.4 and 34-8 of the School Code (105 ILCS 5/3-14.27,10-21.4 and 5/34-8 require all public school district superintendents to report to their regional superintendents the number of high school students who are enrolled in community college courses for which high school credit is awarded. These data are to be provided by the regional superintendents to the State Board of Education in February of each year."
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CD-ROM includes corresponding database and GIS datasets.
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Cover title.
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Vol. II has been published separately and has special t.p., preface and index.
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Mode of access: Internet.
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Mode of access: Internet.
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Includes index.
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Description based on: 1890.
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Title Varies: 1898-1905, Statement of the Computation and Apportionment of the State Levy of Taxes; ?-1897, Statement of the Expenses To Which the State of Oregon Will Be Subjected for the Year 18?-1897 and of the Items of Deficiencies More
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"In this edition the main features of the book remain unaltered, although a considerable amount of new material has been added."--Pref.
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Mode of access: Internet.
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Mode of access: Internet.
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Research in conditioning (all the processes of preparation for competition) has used group research designs, where multiple athletes are observed at one or more points in time. However, empirical reports of large inter-individual differences in response to conditioning regimens suggest that applied conditioning research would greatly benefit from single-subject research designs. Single-subject research designs allow us to find out the extent to which a specific conditioning regimen works for a specific athlete, as opposed to the average athlete, who is the focal point of group research designs. The aim of the following review is to outline the strategies and procedures of single-subject research as they pertain to.. the assessment of conditioning for individual athletes. The four main experimental designs in single-subject research are: the AB design, reversal (withdrawal) designs and their extensions, multiple baseline designs and alternating treatment designs. Visual and statistical analyses commonly used to analyse single-subject data, and advantages and limitations are discussed. Modelling of multivariate single-subject data using techniques such as dynamic factor analysis and structural equation modelling may identify individualised models of conditioning leading to better prediction of performance. Despite problems associated with data analyses in single-subject research (e.g. serial dependency), sports scientists should use single-subject research designs in applied conditioning research to understand how well an intervention (e.g. a training method) works and to predict performance for a particular athlete.