Measurement of Low-Activity Uranium Contamination using Bayesian Statistical Decision Theory

Amongst the various technical challenges in the field of radiation detection is the need to carry out accurate low-level radioactivity measurements in the presence of large fluctuations in the natural radiation background, while lowering the false alarm rates. Several studies, using statistical inference, have been proposed to overcome this challenge. This work presents an advanced statistical approach for decision-making in the field of nuclear decommissioning. The results indicate that the proposed method allows to adjust the confidence degree in the stationarity of the background signal. It also ensures an acceptable tradeoff between the True Detection Rate (TDR), the False Alarm Rate (FAR) and the response time, and is consistent with the users requirements.

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