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Reconfigurable Hardware to Radionuclide Identification Using Subtractive Clustering

  • Conference paper
Algorithms and Architectures for Parallel Processing (ICA3PP 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7017))

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Abstract

Radioactivity is the spontaneous emission of energy from unstable atoms. Radioactive sources have radionuclides. Radionuclide undergoes radioactive decay and emits gamma rays and subatomic particles, constituting the ionizing radiation. The gamma ray energy of a radionuclide is used to determine the identity of gamma emitters present in the source. This paper describes the hardware implementation of subtractive clustering algorithm to perform radionuclide identification.

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Author information

Authors and Affiliations

  1. Department of Instrumentation, Nuclear Engineering Institute, Brazil

    Marcos Santana Farias

  2. Department of Electronics Engineering and Telecommunications, State University of Rio de Janeiro, Brazil

    Nadia Nedjah

  3. Department of Systems Engineering and Computation, State University of Rio de Janeiro, Brazil

    Luiza de Macedo Mourelle

Authors
  1. Marcos Santana Farias
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  2. Nadia Nedjah
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  3. Luiza de Macedo Mourelle
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Editor information

Editors and Affiliations

  1. School of Information Technology, Deakin University, Melbourne Burwood Campus, 221 Burwood Highway, 3125, Burwood, VIC, Australia

    Yang Xiang  & Wanlei Zhou  & 

  2. ICAR-CNR and University of Calabria, Via P. Bucci 41 C, 87036, Rende, CS, Italy

    Alfredo Cuzzocrea

  3. School of Information Technology, Deakin University, Geelong Waurn Ponds Campus, Pigdons Road, 3217, Geelong, VIC, Australia

    Michael Hobbs

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© 2011 Springer-Verlag Berlin Heidelberg

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Santana Farias, M., Nedjah, N., de Macedo Mourelle, L. (2011). Reconfigurable Hardware to Radionuclide Identification Using Subtractive Clustering. In: Xiang, Y., Cuzzocrea, A., Hobbs, M., Zhou, W. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2011. Lecture Notes in Computer Science, vol 7017. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24669-2_37

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  • DOI: https://doi.org/10.1007/978-3-642-24669-2_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24668-5

  • Online ISBN: 978-3-642-24669-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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