Bayesian algorithms for automated isotope identification

Stinnett, Jacob

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Description

Title

Bayesian algorithms for automated isotope identification

Author(s)

Stinnett, Jacob

Issue Date

2014-05-30T16:46:38Z

Director of Research (if dissertation) or Advisor (if thesis)

Sullivan, Clair Julia

Committee Member(s)

Meng, Ling Jian

Department of Study

Nuclear, Plasma, & Rad Engr

Discipline

Nuclear, Plasma, Radiolgc Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Bayesian
• isotope identification
• gamma ray spectroscopy
• decision algorithm

Abstract

Handheld radio-isotope identifiers (RIIDs) are widely used in the United States for nuclear security, but these detectors generally have poor performance in isotope identification. While much research is being conducted on alternative detector materials, there is much evidence that the primary problem with these automated identifiers is with the algorithms used for making identifications. We propose a new algorithm using Bayesian statistics that uses peak positions and areas to identify the source while allowing for calibration drift and shielding.

Graduation Semester

2014-05

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Copyright and License Information

Copyright 2014 Jacob Stinnett

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