Yifan Tian , Haoran Liu , Zhijie Yang , Juncheng Liang , Hao Yang , Zihao Fan , Cong Chen , Qisheng Zhang
{"title":"A new background discrimination method using support vector machine (SVM) with gaussian kernel in low-level 3H liquid scintillation measurement","authors":"Yifan Tian , Haoran Liu , Zhijie Yang , Juncheng Liang , Hao Yang , Zihao Fan , Cong Chen , Qisheng Zhang","doi":"10.1016/j.apradiso.2025.111754","DOIUrl":null,"url":null,"abstract":"<div><div>In this study, a new background discrimination method using SVM with gaussian kernel in low-level <sup>3</sup>H liquid scintillation measurement is developed. Dimensionality reduction techniques were employed to process the full waveform data of each event following time discrimination. The reduced-dimensional data were then used to construct the classification model. To ensure a fair comparison with traditional method, the advantages of offline processing were employed to systematically traverse all possible parameter configurations within reasonable ranges, enabling the determination of the optimal parameters. In machine learning-based background event discrimination, the high-quality labeled datasets are obtained through long-term measurements of blank samples and short-term measurements of medium-activity <sup>3</sup>H samples. Additionally, a series of low-activity <sup>3</sup>H samples with activity levels of approximately 1 Bq, 3 Bq, and 5 Bq were prepared through quantitative dilution. The results demonstrate that the proposed method achieves a significant improvement in discrimination capability compared to traditional method. It effectively minimizes background levels across the entire energy range while preserving detection efficiency, significantly enhancing the measurement capability for low-activity <sup>3</sup>H samples.</div></div>","PeriodicalId":8096,"journal":{"name":"Applied Radiation and Isotopes","volume":"220 ","pages":"Article 111754"},"PeriodicalIF":1.6000,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Radiation and Isotopes","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0969804325000995","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, INORGANIC & NUCLEAR","Score":null,"Total":0}
引用次数: 0
Abstract
In this study, a new background discrimination method using SVM with gaussian kernel in low-level 3H liquid scintillation measurement is developed. Dimensionality reduction techniques were employed to process the full waveform data of each event following time discrimination. The reduced-dimensional data were then used to construct the classification model. To ensure a fair comparison with traditional method, the advantages of offline processing were employed to systematically traverse all possible parameter configurations within reasonable ranges, enabling the determination of the optimal parameters. In machine learning-based background event discrimination, the high-quality labeled datasets are obtained through long-term measurements of blank samples and short-term measurements of medium-activity 3H samples. Additionally, a series of low-activity 3H samples with activity levels of approximately 1 Bq, 3 Bq, and 5 Bq were prepared through quantitative dilution. The results demonstrate that the proposed method achieves a significant improvement in discrimination capability compared to traditional method. It effectively minimizes background levels across the entire energy range while preserving detection efficiency, significantly enhancing the measurement capability for low-activity 3H samples.
期刊介绍:
Applied Radiation and Isotopes provides a high quality medium for the publication of substantial, original and scientific and technological papers on the development and peaceful application of nuclear, radiation and radionuclide techniques in chemistry, physics, biochemistry, biology, medicine, security, engineering and in the earth, planetary and environmental sciences, all including dosimetry. Nuclear techniques are defined in the broadest sense and both experimental and theoretical papers are welcome. They include the development and use of α- and β-particles, X-rays and γ-rays, neutrons and other nuclear particles and radiations from all sources, including radionuclides, synchrotron sources, cyclotrons and reactors and from the natural environment.
The journal aims to publish papers with significance to an international audience, containing substantial novelty and scientific impact. The Editors reserve the rights to reject, with or without external review, papers that do not meet these criteria.
Papers dealing with radiation processing, i.e., where radiation is used to bring about a biological, chemical or physical change in a material, should be directed to our sister journal Radiation Physics and Chemistry.