• DocumentCode
    2847392
  • Title

    Engineering Solution to Nuclear Material Detection at Ports: Introducing the Novel iMASS Paradigm

  • Author

    Alamaniotis, M. ; Young, J. ; Perry, J. ; Xiao, S. ; Agarwal, V. ; Forsberg, P. ; Gao, R. ; Choi, C. ; Tsoukalas, L.H. ; Jevremovic, T.

  • Author_Institution
    Sch. of Nucl. Eng., Purdue Univ., West Lafayette, IN, USA
  • fYear
    2009
  • fDate
    2-4 Nov. 2009
  • Firstpage
    679
  • Lastpage
    682
  • Abstract
    Detection of special nuclear material (SNM) hidden in cargo containers is considered to be one of the major challenges for homeland security. SNM impose a significant threat for public safety since they can be converted into nuclear weaponry and used for potential terrorist attacks. In this paper we present who we can fill the existing gap in quickly but accurately detecting hidden SNM. Synergism of Monte Carlo methods and intelligent control paradigm provides a novel frame for automated cargo interrogation and final decision making. Human operator is assumed to not be the part of the procedure while the powerful detection algorithms are used with fuzzy logic tools to indicate whether the container should be singled out for manual search or not. In this paper the general frame of our so called iMASS (intelligent Model Assisted Sensing System) is presented.
  • Keywords
    Monte Carlo methods; freight handling; fuzzy control; intelligent control; Monte Carlo methods; automated cargo interrogation; fuzzy logic; homeland security; intelligent control paradigm; intelligent model assisted sensing system; port cargo material detection; special nuclear material detection; Containers; Decision making; Detection algorithms; Fuzzy logic; Humans; Intelligent control; Power system modeling; Safety; Terrorism; Weapons; detection of nuclear materials; fuzzy logic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 2009. ICTAI '09. 21st International Conference on
  • Conference_Location
    Newark, NJ
  • ISSN
    1082-3409
  • Print_ISBN
    978-1-4244-5619-2
  • Electronic_ISBN
    1082-3409
  • Type

    conf

  • DOI
    10.1109/ICTAI.2009.94
  • Filename
    5365162