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The muon portal project: A dedicated muon detector for the inspection of shipping containers

Becciani Ugo, V. Antonuccio, M. Bandieramonte, F. Belluomo, M. Belluso, S. Billotta, D.L. Bonanno, G. Bonanno, A. Costa, G. Fallica, S. Garozzo, V. Indelicato, P. LaRocca, E. Leonora, F. Longhitano, S. Longo, D.L. Presti, P. Massimino, C. Petta, C. Pistagna, C. Pugliatti, M. Puglisi, N. Randazzo, F. Riggi, S. Riggi, G. Romeo, G.V. Russo, G. Santagati, G. Valvo, F. Vitello, A. Zaia, G. Zappala
Conference Papers Technologies for Homeland Security (HST), 2013 IEEE International Conference on, November 2012, Pages 423-428

Abstract

Traditional techniques, such as those based on X-rays absorption, to inspect shipping container in search of potential fissile threats cannot be employed on occupied vehicles and are of limited use in presence of a large amount of shielding materials. To overcome such limitations, prototypes of detection systems employing the muon tomography technique, based on cosmic muon scattering from high-Z materials, are being tested worldwide. The Muon Portal project aims to build a large area muon detector (18 m2) for the inspection of TEU containers with good spatial and angular resolution. The detector is made by four XY tracking planes of plastic scintillator bars with embedded WLS fibers and SiPM readout, placed above and below the volume to be inspected. Different imaging and visualization algorithms are being designed and tested over tomographic scenarios simulated with a detailed software replica of the entire detector. Experimental tests of the individual detection modules are already in progress. The design and operational parameters of the portal under construction are reported, together with the preliminary detector tests and imaging results.

Solving a Very Large-Scale Sparse Linear System with a Parallel Algorithm in the Gaia Mission

Becciani Ugo, E. Sciacca, M. Bandieramonte, A. Vecchiato, B. Bucciarelli, M. G. Lattanzi
Conference Papers The 2014 International Conference on High Performance Computing & Simulation, July 2014, Pages 104-111| ISBN: 978-1-4799-5311-0

Abstract

Gaia is a 5-year ESA (European Space Agency) cornerstone mission launched at the end of 2013. Its main goal is the production of a 5-parameter astrometric catalogue (i.e. positions, parallaxes and the two components of the proper motions) at the micro-arcsecond level for about 1 billion stars of our Galaxy by means of high-precision measurements. The main task of the code presented in this paper is the Gaia astrometric core solution, represented by a system of up to 72 billion linear observations equations and 600 million unknowns, resulting in a very large and sparse system matrix. This problem is solved by means of an ad-hoc implementation of the PC-LSQR iterative algorithm aimed at maximizing the number of adjustable stellar objects, which makes also use of a pre-conditioning technique consisting in a re-normalization of the columns of the system matrix to improve the convergence speed. After a description of the parallel algorithm, we present the results obtained on a IBM BlueGeneQ system using both the message-passing and OpenMP paradigms. We also report on the performances obtained from simulations of different stages of the mission from beginning to end.

Towards a Big Data Exploration Framework for Astronomical Archives

E. Sciacca, C. Pistagna, Ugo Becciani, A. Costa, P. Massimino, S. Riggi, F. Vitello, M. Bandieramonte, M. Krokos
Conference Papers The 2014 International Conference on High Performance Computing & Simulation, July 2014, Pages 351-357| ISBN: 978-1-4799-5311-0

Abstract

Exploiting big data astronomical archives is a mandatory and challenging activity due to dramatically increasing sizes and high complexity of datasets coming from radio telescopes or space missions. Visual exploration and discovery can be invaluable tools providing prompt and intuitive insights into the intrinsic data characteristics, enabling scientists to rapidly identify interesting areas within which to apply computationally expensive algorithms or to discover correlations in data patterns. The paper outlines a new approach for creating a user-friendly, integrated and cross-platform framework to facilitate big data access, visualization and exploration, thus empowering astrophysicists to focus on pitching new ideas for scientific advances. We present a flexible distributed architecture striking a balance between local interactive exploration tools and remote services responsible for hiding data complexity. Remote services communicate with advanced distributed computing infrastructures presenting a meaningful lightweight version of the archive dataset obtained by mining or noise filtering methods. They are interfaced with science gateway technologies in order to allow collaborative activity between users and to provide customization and scalability of data analysis/processing workflows hiding underlying technicalities. Local tools enable interactive visualization optimized for ubiquitous computing environments, intuitively controlling the resulting visualisation. The motivations behind such a framework are envisaged to meet the requirements of the exploitation of the Gaia mission outcomes and are shown in the paper by a number of case studies. The presented framework can potentially have a profound impact on astronomical and astrophysical communities in the big data era, allowing to quickly understand datasets, thus aiding in adopting novel ways for scientific discovery.

An Innovative Science Gateway for the Cherenkov Telescope Array

A. Costa, P. Massimino, M. Bandieramonte, Ugo Becciani, M. Krokos, C. Pistagna, S. Riggi, E. Sciacca, F. Vitello
Journal Journal of Grid Computing | In press

Abstract

The Cherenkov Telescope Array (CTA) is currently building the next generation, ground-based, very high-energy gamma-ray instrumentation. CTA is expected to collect very large datasets (in the order of petabytes) which will have to be stored, managed and processed. This paper presents a graphical user in- terface built inside a science gateway aiming at pro- viding CTA-users with a common working framework.The gateway is WS-PGRADE/gUSE workflow-oriented and is equipped with a flexible SSO (based on SAML) to control user access for authentication and authoriza- tion. An interactive desktop environment is provided, called Astronomical & Physics Cloud Interactive Desk- top (ACID). Users are able to exploit the graphical in- terface as provided natively by the tools included in ACID. A cloud data service shares and synchronizes data files and output results between the user desktop and the science gateway. Our solution is a first attempt towards an ecosystem of new technologies with a high level of flexibility to suit present and future require- ments of the CTA community.

Muon tomography imaging algorithms for nuclear threat detection inside large volume containers with the Muon Portal detector

S. Riggi, V. Antonuccio-Delogu, M. Bandieramonte, Ugo Becciani, A. Costa, P. La Rocca, P. Massimino, C. Petta, C. Pistagna, F. Riggi, E. Sciacca, F. Vitello
Journal Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment | vol. 728 | p. 59-68 | ISSN: 0168-9002

Abstract

Muon tomographic visualization techniques try to reconstruct a 3D image as close as possible to the real localization of the objects being probed. Statistical algorithms under test for the reconstruction of muon tomographic images in the Muon Portal Project are here discussed. Autocorrelation analysis and clustering algorithms have been employed within the context of methods based on the Point Of Closest Approach (POCA) reconstruction tool. An iterative method based on the log-likelihood approach was also implemented. Relative merits of all such methods are discussed, with reference to full Geant4 simulations of different scenarios, incorporating medium and high-Z objects inside a container.

Automated Object Recognition and Visualization Techniques for Muon Tomography Data Analysis

M. Bandieramonte, V. Antonuccio Delogu, Ugo Becciani, A. Costa, P. La Rocca, P. Massimino, C. Petta, C. Pistagna, F. Riggi, S. Riggi, E. Sciacca, F. Vitello
Conference Papers Technologies for Homeland Security (HST), 2013 IEEE International Conference on, November 2013, Pages 517-522| ISBN: 978-1-4799-3963-3

Abstract

In recent years an increasing interest has grown within the international community towards the prevention of terroristic threatenings. This traffic requires a broader international control and it becomes necessary to enhance systems for borders security. Currently, muon tomography is under study to be used as an experimental technique to be implemented in devices able to perform an efficient scanning to detect radioactive materials inside different kind of systems, like shipping containers or cargos, for borders control. In this paper the authors will focus on the automated identification and visualization of illicit materials inside cargo containers in the context of the Muon Portal project. The track reconstruction is a challenging task and consists in the elaboration of data from the detector planes in order to obtain information on the deflection occurred by the muons within the volume scanned. Latest results of different reconstruction algorithms, such as the well known POCA and the EM-Likelihood, are presented and discussed together with the novel application of clustering algorithms to the data analysis. The usage of these techniques allows to infer the implicit information in the data and clustering algorithms make the tracks reconstruction and the visualization of the containers content be independent from the grid and the 3D-voxels, acting as a filter for a preliminary analysis of the data.

VisIVO Science Gateway: a Collaborative Environment for the Astrophysics Community

E. Sciacca, M. Bandieramonte, Ugo Becciani, A. Costa, M. Krokos, P. Massimino, C. Petta, C. Pistagna, S. Riggi, F. Vitello
Conference Papers International Workshop on Science Gateways | June 2013 ISBN: 978-1-4799-3963-3

Abstract

VisIVO Science Gateway is a web based, workflow enabled environment wrapped around a WS-PGRADE/gUSE portal integrating seamlessly large-scale multi-dimensional astrophysical datasets with applications for processing and visualization based on Distributed Computing Infrastructures (DCIs). We present the main tools and services supported including an application for mobile access to the gateway. We discuss issues in sharing workflows and report our experiences in supporting specialised communities. We present a number of workflows developed recently for visualization and numerical simulations and outline future workflows currently under development. Finally, we summarise our work on the gateway with pointers to future developments.

VisIVO Workflow-Oriented Science Gateway for Astrophysical Visualization

E. Sciacca, M. Bandieramonte, Ugo Becciani, A. Costa, M. Krokos, P. Massimino, C. Petta, C. Pistagna, S. Riggi, F. Vitello
Conference Papers Parallel, Distributed and Network-Based Processing (PDP), 2013 21st Euromicro International Conference on| Pages 164-171| ISBN: 978-0-7695-4939-2

Abstract

Nowadays visualization-based knowledge discovery can play an important role in astrophysics. Collaborative visualization can enable multiple users to share visualization experiences, e.g. by interacting simultaneously with astrophysical datasets giving feedback on what other participants are doing/seeing. Further, workflow-driven applications allow reproduction of specific visualization results, a challenging task as selecting suitable visualization parameters may not be a straightforward process. This paper presents VisIVO Science Gateway, a web-based workflow-enabled framework integrating large-scale, multidimensional datasets and applications for visualization and data filtering on Distributed Computing Infrastructures (DCIs). Advanced users are able to create, change, invoke, and monitor workflows while standard users are provided with easy-to-use customised web interfaces hiding all technical aspects of the visualization algorithms and DCI configurations.

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