VO-Neural Group G. Longo – P.I. M. Brescia – P.M. Team Corazza ( models ) O. Laurino (System and models for image segmentation ) S. Cavuoti & E. Russo ( Models – SVM) N. Deniskina ( Grid manager and interfacing with V.O. )
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Cf. isophotal, petrosian, aperture magnitudesconcentrationindexes, shapeparameters, tc.
The scientificexploitationof a multi band, multiepoch (K epochs) surveyimpliestosearchforpatterns, trends, etc. among
N points in a DxKdimensionalparameterspace
N >109, D>>100, K>10
Dimensionality reduction (without a significant loss of information) is a critical need!
International Virtual Observatory Alliance
Started in 2000
Implementation of interface between ASTROGRID and GRID- SCOPE with different CA
ASTROGRID – GRID Launcher (N. Deniskina)
Forms directory on Lupalberto (i.e. executable file, input data) and wraps it
Makes connection with SCOPE U.I. (checking certificate)
Sends wrapped directory from Lupalberto to Scope U.I.
Unzips the wrapped job directory on SCOPE U.I. & forms JDL job
Sends job to GRID and waits for the results
Wraps the output and sends it to Lupalberto
First results: AGN classification (Cavuoti, D’Abrusco & D’Angelo)
Differentclusters in parameterspace
BUT, STILL THE SAME OBJECT !
SVM on AGN dataset extracted from SDSS for automatic classification of galaxies
BoK from spectroscopically confirmed sample
SVM code implemented from LIB-SVM
13 parameters for 89.000 objects
SVM – RBF needs optimization against 2 parameters (C and g)Maximum of classification rate must be found in a given range
110 grid points in parameter space (each at least 1 h)
110 computers in GRID-SCOPE (Na-CT-CA)
Seyfert 1 vs Seyfert 2
AGN vs non-AGN
a special thank to S. Pardi
Applications:High dimensionality Massive Data sets (from astronomical survey but also any other high dimensionality data space)
Output of results
Execution of job