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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
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Background: It is very difficult to distinguish between a radioactive contamination source and background radiation from natural radionuclides in the marine environment by means of online monitoring system. The objective of this study was to investigate a statistical process for triggering abnormal level of count rate data measured from our on-line seawater radioactivity monitoring. Materials and Methods: Count rate data sets in time series were collected from 9 monitoring posts. All of the count rate data were measured every 15 minutes from the region of interest (ROI) for $^{137}Cs$ ($E_{\gamma}=661.6keV$) on the gamma-ray energy spectrum. The Shewhart ($3{\sigma}$), CUSUM, and Bayesian S-R control chart methods were evaluated and the comparative analysis of determination methods for count rate data was carried out in terms of the false positive incidence rate. All statistical algorithms were developed using R Programming by the authors. Results and Discussion: The $3{\sigma}$, CUSUM, and S-R analyses resulted in the average false positive incidence rate of $0.164{\pm}0.047%$, $0.064{\pm}0.0367%$, and $0.030{\pm}0.018%$, respectively. The S-R method has a lower value than that of the $3{\sigma}$ and CUSUM method, because the Bayesian S-R method use the information to evaluate a posterior distribution, even though the CUSUM control chart accumulate information from recent data points. As the result of comparison between net count rate and gross count rate measured in time series all the year at a monitoring post using the $3{\sigma}$ control charts, the two methods resulted in the false positive incidence rate of 0.142% and 0.219%, respectively. Conclusion: Bayesian S-R and CUSUM control charts are better suited for on-line seawater radioactivity monitoring with an count rate data in time series than $3{\sigma}$ control chart. However, it requires a continuous increasing trend to differentiate between a false positive and actual radioactive contamination. For the determination of count rate, the net count method is better than the gross count method because of relatively a small variation in the data points.
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참고문헌 (11)
참고문헌 신청
Watson MM / 2018 / Evaluation of Shiryaev-Roberts procedure for on-line environmental radiation monitoring / J. Environ. Radioact 192:587~591
DeVol TA / 2009 / Application of classical versus Bayesian statistical control charts to on-line radiological monitoring / J. of Radioanal. Nucl. Chem 282(3):933~938
Luo P / 2010 / Sequential probability ratio test using scaled time-intervals for environmental radiation monitoring / IEEE Trans. Nucl. Sci 57(3):1556~1562
Montgomery DC / 2009 / Introduction to Statistical Quality Control / John Wiley & Sons
Marshall RAG / 1977 / Cumulative sum charts for monitoring of radioactivity background count rates / Anal. Chem 49(14):2193~2196
DeVol TA / 2009 / Application of classical versus Bayesian statistical control charts to on-line radiological monitoring / J. of Radioanal. Nucl. Chem 282(3):933~938
Luo P / 2010 / Sequential probability ratio test using scaled time-intervals for environmental radiation monitoring / IEEE Trans. Nucl. Sci 57(3):1556~1562
Montgomery DC / 2009 / Introduction to Statistical Quality Control / John Wiley & Sons
Marshall RAG / 1977 / Cumulative sum charts for monitoring of radioactivity background count rates / Anal. Chem 49(14):2193~2196
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