Abstract：
:The detection, identification, and localization of illicit nuclear materials in urban environments is of utmost importance for national security. Most often, the process of performing these operations consists of a team of trained individuals equipped with radiation detection devices that have built-in algorithms to alert the user to the presence nuclear material and, if possible, to identify the type of nuclear material present. To encourage the development of new detection, radioisotope identification, and source localization algorithms, a dataset consisting of realistic Monte Carlo-simulated radiation detection data from a 2 in. × 4 in. × 16 in. NaI(Tl) scintillation detector moving through a simulated urban environment based on Knoxville, Tennessee, was developed and made public in the form of a Topcoder competition. The methodology used to create this dataset has been verified using experimental data collected at the Fort Indiantown Gap National Guard facility. Realistic signals from special nuclear material and industrial and medical sources are included in the data for developing and testing algorithms in a dynamic real-world background.
journal_name
Sci Datajournal_title
Scientific dataauthors
Ghawaly JM Jr,Nicholson AD,Peplow DE,Anderson-Cook CM,Myers KL,Archer DE,Willis MJ,Quiter BJdoi
10.1038/s41597-020-00672-2subject
Has Abstractpub_date
2020-10-05 00:00:00pages
328issue
1issn
2052-4463pii
10.1038/s41597-020-00672-2journal_volume
7pub_type
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