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Enhancing Test Statistics by Utilizing Data Patterns in Sequential Measurement Strings in Radiation Detection

Brogan, J.; Brandl, A.1

doi: 10.1097/HP.0000000000000928
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Operational health physics applications, such as radiological and nuclear monitoring and detection for homeland security or radiation protection purposes, generate time sequences of independent individual measurement data. Statistical algorithms have been developed that utilize the analysis of patterns in data strings to enhance the test statistic for the decision on the absence or presence of a radiological source. Theoretical expectations have been verified in laboratory measurements for various lengths of data strings. Null hypothesis test performance and source detection efficacy have been shown to improve compared to the traditional method of achieving a detection decision by the comparison of a measured value to a fixed decision threshold.

1Environmental and Radiological Health Sciences, 1618 Campus Delivery, Colorado State University, Fort Collins, CO 80526.

The authors declare no conflicts of interest.

For correspondence contact: Alexander Brandl at the above address, or email at alexander.brandl@colostate.edu.

(Manuscript accepted 29 May 2018)

© 2018 by the Health Physics Society