Nuclear technology industries have increased their interest in using data-driven methods to
improve safety, reliability, and availability of assets. To do so, it is important to understand …

The detection of illicit radiological materials is critical to establishing a robust second line of
defence in nuclear security. Neutron-capture prompt-gamma activation analysis (PGAA) can …

In this manuscript, we propose an algorithm based on an artificial neural network (ANN) for
the analysis of the NaI (Tl) gamma-ray spectra with radioisotope (RI) mixtures to identify RIs …

One of the well-known online monitoring techniques used for quality control of bulk samples
is Prompt Gamma Neutron Activation Analysis (PGNAA). PGNAA suffers from the so-called …

This study introduces an explainable artificial intelligence (XAI) approach designed to
estimate background spectra in unknown spectral measurements. The approach combines …

The increasing concerns over the use of nuclear materials for malevolent purposes (ie,
terrorist attacks) have fueled the interest in develo** technologies that can detect hidden …

The detection and identification of radioactive sources in search applications involve
analyzing passive gamma-ray emissions from high-level radioactive materials. This process …

Abstract Analysis of gamma-ray spectra is an important step for identification and
quantification of radionuclides in a sample. In this paper a new gamma-ray spectra analysis …

A novel approach for analyzing complex gamma-ray spectra using a sequential algorithm is
introduced. The developed Sequential Gamma-ray Spectrum Deconvolution (SGSD) …

In this study, a dynamic nuclide identification algorithm based on fuzzy probability factor
superposition (FPFS) was proposed for γ spectrum analysis, and the algorithm was tested …