Clustering analysis for muon tomography data elaboration in the Muon Portal project
Date Issued
2015
Author(s)
Bandieramonte, M.
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La Rocca, P.
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Massimino, P.
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Petta, C.
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Pistagna, C.
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Riggi, F.
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Abstract
Clustering analysis is one of multivariate data analysis techniques which allows to gather statistical data units into groups, in order to minimize the logical distance within each group and to maximize the one between different groups. In these proceedings, the authors present a novel approach to the muontomography data analysis based on clustering algorithms. As a case study we present the Muon Portal project that aims to build and operate a dedicated particle detector for the inspection of harbor containers to hinder the smuggling of nuclear materials. Clustering techniques, working directly on scattering points, help to detect the presence of suspicious items inside the container, acting, as it will be shown, as a filter for a preliminary analysis of the data.
Coverage
16th International Workshop on Advanced Computing and Analysis Techniques in Physics Research: Bridging Disciplines, ACAT 2014
Volume
608
Issue
1
Start page
012046
Conferenece
16th International Workshop on Advanced Computing and Analysis Techniques in Physics Research: Bridging Disciplines, ACAT 2014
Conferenece place
Prague, Czech Republic
Conferenece date
1-5 September, 2014
Issn Identifier
1742-6588
Ads BibCode
2015JPhCS.608a2046B
Rights
open.access
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