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Dr Homer Neal (SLAC)29/11/2011, 09:00Recently there have been significant developments in high energy physics (HEP) data preservation projects while other large data volume experiments are now also facing for the first time insuring the long term accessibility of their data. In this presentation, the status of advanced HEP data preservation projects as well as the challenges and plans for projects newly facing this task will be...Go to contribution page
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Fons Rademaker (CERN)29/11/2011, 09:30Invited oral presentationThe ROOT system has become the de facto standard in High Energy and Nuclear Physics for the experiment independent software. ROOT provides a powerful object data store that supports vertical data storage for highly efficient data access during data mining. In addition the system comes with a rich set of mathematical and statistical tools and a full set of 2D and 3D graphical data...Go to contribution page
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Dr Peter Elmer (Princeton University)29/11/2011, 10:00Invited oral presentationHigh Energy Physics (HEP) has a long tradition of pushing scientific computing to its limits. In particular the use of very large datasets has always been required in order to search for the rare phenomonen of interest in the field. This presentation will describe the manner in which large datesets are acquired, processed, managed and analyzed in HEP, using the Large Hadron Collider...Go to contribution page
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Prof. Giuseppe Longo (NA)29/11/2011, 11:00The last decade has witnessed an exponential growth in both size and quality of scientific data sets. The exploitation of the useful information in these Massive Data Sets (MDS) has triggered the birth of new disciplines, the so called X-informatics, which are at the crossroads of domain expertise, computer science, mathematics and statistics. X-informatics is being recognized as the "fourth...Go to contribution page
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Prof. Alexander Gammerman (University of London (Royal Holloway College))29/11/2011, 11:30Invited oral presentationThe application of traditional machine-learning algorithms to modern high-throughput and high-dimensional (with many thousands of features) data sets often leads to serious computational diculties. Several new algorithms, foremost support vector machines (SVM) and other kernel methods, have been developed recently with the goal of tackling highdimensional problems. However, a typical...Go to contribution page
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Dr JESUS VEGA (ASOCIACION EURATOM/CIEMAT)29/11/2011, 12:00Invited oral presentationJ. Vega, A. Murari*, S. González, A. Pereira, I. Pastor Asociación EURATOM/CIEMAT para Fusión. Madrid (Spain) *Associazione EURATOM/ENEA per la Fusione, Consorzio RFX. Padova (Italy) Conformal predictors (CP) are a particular case of machine learning methods. Two important characteristics of conformal predictors should be mentioned. On the one hand, a unique hypothesis about the samples...Go to contribution page
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Dr Andrea Murari (Consorzio RFX)29/11/2011, 12:30Invited oral presentationby A.Murari, J.Vega et al Modelling is a fundamental aspect of scientific research. The typical goal of the scientific process is indeed the development of a successful mathematical model of the systems under study. In the last years, the role of data has increased in every aspect of the modelling phase. The availability of a large number of cheap measurements has resulted in many fields in...Go to contribution page
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Prof. John Howard (The Australian National University)29/11/2011, 13:00Invited oral presentationMotional Stark effect polarimetry of D-alpha emission from heating neutral beams is a standard diagnostic for inferring the internal magnetic field pitch angle in toroidal confinement devices. Due to technical limitations, the measurement is restricted to a modest number of independent measurement channels viewing across the machine mid-plane. We have developed a simple and compact spatial...Go to contribution page
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