Data-driven modeling of background radiation structure utilizing matrix profile in nuclear security
Abstract The inherently stochastic nature of radiation emissions makes modeling background radiation structure a particularly challenging research area. In source identification scenarios, which are critical to nuclear security, the complexity of background radiation modeling is intensified by dynam...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-88390-w |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832571790959837184 |
|---|---|
| author | Miltiadis Alamaniotis |
| author_facet | Miltiadis Alamaniotis |
| author_sort | Miltiadis Alamaniotis |
| collection | DOAJ |
| description | Abstract The inherently stochastic nature of radiation emissions makes modeling background radiation structure a particularly challenging research area. In source identification scenarios, which are critical to nuclear security, the complexity of background radiation modeling is intensified by dynamically changing factors that influence radiation measurements. Consequently, accurately modeling and estimating background radiation can significantly improve our nuclear security capabilities by enhancing the detection of anomalies within radiation data. This study introduces a new data-driven approach to modeling background radiation from spectral measurements. By leveraging the novel data mining technique, Matrix Profile (MP), this approach identifies structural patterns within radiation measurements. The method was tested on real-world background 1-second spectral data collected across various locations, with results demonstrating MP’s effectiveness in modeling background structures for measurements taken in the same location. Additionally, MP modeling outperformed the traditional method of using raw measurement averages, particularly in generating distinct models for low-count backgrounds from different locations. |
| format | Article |
| id | doaj-art-61d96284ec8a46efbacafe347fc5258c |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-61d96284ec8a46efbacafe347fc5258c2025-02-02T12:18:08ZengNature PortfolioScientific Reports2045-23222025-01-0115111510.1038/s41598-025-88390-wData-driven modeling of background radiation structure utilizing matrix profile in nuclear securityMiltiadis Alamaniotis0Department of Electrical and Computer Engineering, University of Texas at San AntonioAbstract The inherently stochastic nature of radiation emissions makes modeling background radiation structure a particularly challenging research area. In source identification scenarios, which are critical to nuclear security, the complexity of background radiation modeling is intensified by dynamically changing factors that influence radiation measurements. Consequently, accurately modeling and estimating background radiation can significantly improve our nuclear security capabilities by enhancing the detection of anomalies within radiation data. This study introduces a new data-driven approach to modeling background radiation from spectral measurements. By leveraging the novel data mining technique, Matrix Profile (MP), this approach identifies structural patterns within radiation measurements. The method was tested on real-world background 1-second spectral data collected across various locations, with results demonstrating MP’s effectiveness in modeling background structures for measurements taken in the same location. Additionally, MP modeling outperformed the traditional method of using raw measurement averages, particularly in generating distinct models for low-count backgrounds from different locations.https://doi.org/10.1038/s41598-025-88390-wBackground radiationSpectral structureData miningMatrix profileNuclear security |
| spellingShingle | Miltiadis Alamaniotis Data-driven modeling of background radiation structure utilizing matrix profile in nuclear security Scientific Reports Background radiation Spectral structure Data mining Matrix profile Nuclear security |
| title | Data-driven modeling of background radiation structure utilizing matrix profile in nuclear security |
| title_full | Data-driven modeling of background radiation structure utilizing matrix profile in nuclear security |
| title_fullStr | Data-driven modeling of background radiation structure utilizing matrix profile in nuclear security |
| title_full_unstemmed | Data-driven modeling of background radiation structure utilizing matrix profile in nuclear security |
| title_short | Data-driven modeling of background radiation structure utilizing matrix profile in nuclear security |
| title_sort | data driven modeling of background radiation structure utilizing matrix profile in nuclear security |
| topic | Background radiation Spectral structure Data mining Matrix profile Nuclear security |
| url | https://doi.org/10.1038/s41598-025-88390-w |
| work_keys_str_mv | AT miltiadisalamaniotis datadrivenmodelingofbackgroundradiationstructureutilizingmatrixprofileinnuclearsecurity |