The Experts below are selected from a list of 12 Experts worldwide ranked by ideXlab platform

Larry Wos - One of the best experts on this subject based on the ideXlab platform.

  • Hilbert's Twenty-Fourth Problem
    Journal of Automated Reasoning, 2002
    Co-Authors: Ruediger Thiele, Larry Wos
    Abstract:

    For almost a century, a treasure lay hidden in a library in Germany, hidden until a remarkable discovery was made. Indeed, for most of the twentieth century, all of science thought that Hilbert had posed twenty-three Problems, and no others. In the mid-1990s, however, as a result of a thorough reading of Hilbert's files, a twenty-fourth Problem was found (in a notebook, in file Cod. ms. D. Hilbert 600:3), a Problem that might have a profound effect on research. This newly Discovered Problem focuses on the finding of simpler proofs and criteria for measuring simplicity. A proof may be simpler than previously known in one or more ways that include length, size (measured in terms of the total symbol count), and term structure. A simpler proof not only is more appealing aesthetically (and has fascinated masters of logic including C. A. Meredith, A. Prior, and I. Thomas) but is relevant to practical applications such as circuit design and program synthesis. This article presents Hilbert's twenty-fourth Problem, discusses its relation to certain studies in automated reasoning, and offers researchers with varying interests the challenge of addressing this newly Discovered Problem. In particular, we include open questions to be attacked, questions that (in different ways and with diverse proof refinements as the focus) may prove of substantial interest to mathematicians, to logicians, and (perhaps in a slightly different manner) to those researchers primarily concerned with automated reasoning.

Liu Yuan-hai - One of the best experts on this subject based on the ideXlab platform.

  • Study on the Present Situation and Countermeasure of Xianning City Community Sport
    Journal of Xianning University, 2008
    Co-Authors: Liu Yuan-hai
    Abstract:

    Using literature methods and so on material law,social investigation method,data method of average,the article carried out investigation and studied on community sports in Xianning City,Discovered Problem existing in community sport,such as the number of participate was small,consuming concept fall behind,instructor and organization was short,the utilization of public facilities was limited,provided measure and reference ideas for developing the community sports.

Ruediger Thiele - One of the best experts on this subject based on the ideXlab platform.

  • Hilbert's Twenty-Fourth Problem
    Journal of Automated Reasoning, 2002
    Co-Authors: Ruediger Thiele, Larry Wos
    Abstract:

    For almost a century, a treasure lay hidden in a library in Germany, hidden until a remarkable discovery was made. Indeed, for most of the twentieth century, all of science thought that Hilbert had posed twenty-three Problems, and no others. In the mid-1990s, however, as a result of a thorough reading of Hilbert's files, a twenty-fourth Problem was found (in a notebook, in file Cod. ms. D. Hilbert 600:3), a Problem that might have a profound effect on research. This newly Discovered Problem focuses on the finding of simpler proofs and criteria for measuring simplicity. A proof may be simpler than previously known in one or more ways that include length, size (measured in terms of the total symbol count), and term structure. A simpler proof not only is more appealing aesthetically (and has fascinated masters of logic including C. A. Meredith, A. Prior, and I. Thomas) but is relevant to practical applications such as circuit design and program synthesis. This article presents Hilbert's twenty-fourth Problem, discusses its relation to certain studies in automated reasoning, and offers researchers with varying interests the challenge of addressing this newly Discovered Problem. In particular, we include open questions to be attacked, questions that (in different ways and with diverse proof refinements as the focus) may prove of substantial interest to mathematicians, to logicians, and (perhaps in a slightly different manner) to those researchers primarily concerned with automated reasoning.

Thomas Loubrieu - One of the best experts on this subject based on the ideXlab platform.

  • Quality Control of Large Argo Datasets
    Journal of Atmospheric and Oceanic Technology, 2009
    Co-Authors: Fabienne Gaillard, Emmanuelle Autret, Virginie Thierry, Philippe Galaup, Christine Coatanoan, Thomas Loubrieu
    Abstract:

    Argo floats have significantly improved the observation of the global ocean interior, but as the size of the database increases, so does the need for efficient tools to perform reliable quality control. It is shown here how the classical method of optimal analysis can be used to validate very large datasets before operational or scientific use. The analysis system employed is the one implemented at the Coriolis data center to produce the weekly fields of temperature and salinity, and the key data are the analysis residuals. The impacts of the various sensor errors are evaluated and twin experiments are performed to measure the system capacity in identifying these errors. It appears that for a typical data distribution, the analysis residuals extract 2/3 of the sensor error after a single analysis. The method has been applied on the full Argo Atlantic real-time dataset for the 2000–04 period (482 floats) and 15% of the floats were detected as having salinity drifts or offset. A second test was performed on the delayed mode dataset (120 floats) to check the overall consistency, and except for a few isolated anomalous profiles, the corrected datasets were found to be globally good. The last experiment performed on the Coriolis real-time products takes into account the recently Discovered Problem in the pressure labeling. For this experiment, a sample of 36 floats, mixing well-behaved and anomalous instruments of the 2003–06 period, was considered and the simple test designed to detect the most common systematic anomalies successfully identified the deficient floats.

Fabienne Gaillard - One of the best experts on this subject based on the ideXlab platform.

  • Quality Control of Large Argo Datasets
    Journal of Atmospheric and Oceanic Technology, 2009
    Co-Authors: Fabienne Gaillard, Emmanuelle Autret, Virginie Thierry, Philippe Galaup, Christine Coatanoan, Thomas Loubrieu
    Abstract:

    Argo floats have significantly improved the observation of the global ocean interior, but as the size of the database increases, so does the need for efficient tools to perform reliable quality control. It is shown here how the classical method of optimal analysis can be used to validate very large datasets before operational or scientific use. The analysis system employed is the one implemented at the Coriolis data center to produce the weekly fields of temperature and salinity, and the key data are the analysis residuals. The impacts of the various sensor errors are evaluated and twin experiments are performed to measure the system capacity in identifying these errors. It appears that for a typical data distribution, the analysis residuals extract 2/3 of the sensor error after a single analysis. The method has been applied on the full Argo Atlantic real-time dataset for the 2000–04 period (482 floats) and 15% of the floats were detected as having salinity drifts or offset. A second test was performed on the delayed mode dataset (120 floats) to check the overall consistency, and except for a few isolated anomalous profiles, the corrected datasets were found to be globally good. The last experiment performed on the Coriolis real-time products takes into account the recently Discovered Problem in the pressure labeling. For this experiment, a sample of 36 floats, mixing well-behaved and anomalous instruments of the 2003–06 period, was considered and the simple test designed to detect the most common systematic anomalies successfully identified the deficient floats.