• Journal of Radiation Protection and Research
• /
• v.42 no.2
• /
• pp.91-97
• /
• 2017

Background: A gamma energy identifying algorithm using spectral decomposition combined with smoothing method was suggested to confirm the existence of the artificial radio isotopes. The algorithm is composed by original pattern recognition method and smoothing method to enhance the performance to identify gamma energy of radiation sensors that have low energy resolution. Materials and Methods: The gamma energy identifying algorithm for the compact radiation sensor is a three-step of refinement process. Firstly, the magnitude set is calculated by the original spectral decomposition. Secondly, the magnitude of modeling error in the magnitude set is reduced by the smoothing method. Thirdly, the expected gamma energy is finally decided based on the enhanced magnitude set as a result of the spectral decomposition with the smoothing method. The algorithm was optimized for the designed radiation sensor composed of a CsI (Tl) scintillator and a silicon pin diode. Results and Discussion: The two performance parameters used to estimate the algorithm are the accuracy of expected gamma energy and the number of repeated calculations. The original gamma energy was accurately identified with the single energy of gamma radiation by adapting this modeling error reduction method. Also the average error decreased by half with the multi energies of gamma radiation in comparison to the original spectral decomposition. In addition, the number of repeated calculations also decreased by half even in low fluence conditions under $10^4$ ($/0.09cm^2$ of the scintillator surface). Conclusion: Through the development of this algorithm, we have confirmed the possibility of developing a product that can identify artificial radionuclides nearby using inexpensive radiation sensors that are easy to use by the public. Therefore, it can contribute to reduce the anxiety of the public exposure by determining the presence of artificial radionuclides in the vicinity.

• Nuclear Engineering and Technology
• /
• v.56 no.7
• /
• pp.2835-2841
• /
• 2024

Real-time analysis of metallic mineral grade and slurry concentration is significant for improving flotation efficiency and product quality. This study proposes an online detection method of ore slurry combining the Prompt Gamma Neutron Activation Analysis (PGNAA) technology and artificial neural network (ANN), which can provide mineral information rapidly and accurately. Firstly, a PGNAA analyzer based on a D-T neutron generator and a BGO detector was used to obtain a gamma-ray spectrum dataset of ore slurry samples, which was used to construct and optimize the ANN model for adaptive analysis. The evaluation metrics calculated by leave-one-out cross-validation indicated that, compared with the weighted library least squares (WLLS) approach, ANN obtained more precise and stable results, with mean absolute percentage errors of 4.66% and 2.80% for Fe grade and slurry concentration, respectively, and the highest average standard deviation of only 0.0119. Meanwhile, the analytical errors of the samples most affected by matrix effects was reduced to 0.61 times and 0.56 times of the WLLS method, respectively.

• Journal of the Korean Society of Radiology
• /
• v.13 no.5
• /
• pp.819-824
• /
• 2019

In this study, we proposed a method for identifying isotopes generated from high-energy proton $^{nat}Pb$(p,xn) nuclear reactions through the difference of gamma rays generated through nuclear reactions using different proton energies. The experiment was performed by using a high energy proton generated from a 100 MeV proton linear accelerator of the Korea Atomic Energy Research Institute. Gamma rays generated by various nuclides generated through proton nuclear reactions were measured using a gamma-ray spectroscopy system composed of HPGe detectors. Gamma-ray standard sources were used for accurate energy calibration and efficiency measurements of HPGe gamma-ray detectors. For the proposed method, 100 and 60 MeV proton energy beams were used for the same natural lead samples. This method was found to be very effective in identifying nuclides produced by comparing gamma rays generated from the same sample with each other. The results of this study are expected to be very effective in obtaining other proton nuclear reaction results in the future.

• Nuclear Engineering and Technology
• /
• v.55 no.5
• /
• pp.1708-1717
• /
• 2023

The grade analysis of lead-zinc ore is the basis for the optimal development and utilization of deposits. In this study, a method combining Prompt Gamma Neutron Activation Analysis (PGNAA) technology and machine learning is proposed for lead-zinc mine borehole logging, which can identify lead-zinc ores of different grades and gangue in the formation, providing real-time grade information qualitatively and semi-quantitatively. Firstly, Monte Carlo simulation is used to obtain a gamma-ray spectrum data set for training and testing machine learning classification algorithms. These spectra are broadened, normalized and separated into inelastic scattering and capture spectra, and then used to fit different classifier models. When the comprehensive grade boundary of high- and low-grade ores is set to 5%, the evaluation metrics calculated by the 5-fold cross-validation show that the SVM (Support Vector Machine), KNN (K-Nearest Neighbor), GNB (Gaussian Naive Bayes) and RF (Random Forest) models can effectively distinguish lead-zinc ore from gangue. At the same time, the GNB model has achieved the optimal accuracy of 91.45% when identifying high- and low-grade ores, and the F₁ score for both types of ores is greater than 0.9.

• The Korean Journal of Physiology and Pharmacology
• /
• v.3 no.3
• /
• pp.245-250
• /
• 1999

The effects of an antipsychotic, chlorpromazine, on the electroencephalogram (EEG) were observed while rats were awake but immobile. The time course and the dose-dependency of the EEG changes were examined. The method of the power spectrum analysis was used to examine the EEG changes by the drug. The bands were divided into delta $(1{\sim}3.5\;Hz),$ theta $(3.5{\sim}8\;Hz),$ alpha $(8{\sim}13\;Hz),$ beta1 $(13{\sim}21\;Hz),$ beta2 $(21{\sim}30\;Hz)$ and gamma $(30{\sim}50\;Hz).$ In rats, the low dose of chlropromazine (1 mg/kg, i.p.) produced a significant increase in the power of the beta1 band. The higher doses (5, 10 mg/kg, i.p.) produced a significant increase in the power of the delta, theta, alpha and beta1 bands, and the decrease in the power of the gamma band. The powers of the bands changed dose-dependently. Then, the authors discussed whether the EEG effects produced by a drug are associated with the accompanying behavioral changes specifically.

• Nuclear Engineering and Technology
• /
• v.50 no.6
• /
• pp.929-936
• /
• 2018

A basic characterization of uranium samples was performed using gamma- and X-ray spectroscopy. The studied uranium samples were eight types of certified reference materials with $^{235}U$ enrichments in the range of 1-97%, and the measurements were performed over 24 h using a high-resolution and high-purity planar germanium detector. A general peak analysis of the spectrum and the $XK_{\alpha}$ region of the uranium spectra was carried out by using HyperGam and HyperGam-U, respectively. The standard reference sources were used to calibrate the spectroscopy system. To obtain the absolute detection efficiency, an effective solid angle code, EXVol, was run for each sample. Hence, the peak activities and isotopic activities were determined, and then, the total U content and $^{234}U$, $^{235}U$, and $^{238}U$ isotopic contents were determined and compared with those of the certified reference values. A new method to determine the model age based on the ratio of the activities of $^{223}Ra$ and $^{235}U$ in the sample was studied, and the model age was compared with the known true age. In summary, the present study developed a method for basic characterization of uranium samples by nondestructive gamma-ray spectrometry in 24 h and to obtain information on the sample age.

• Analytical Science and Technology
• /
• v.16 no.5
• /
• pp.1041-1051
• /
• 2003

Neutron induced prompt gamma activation analysis (PGAA) offers a nondestructive, sensitive and relatively rapid method for the determination of trace and major elements and is proven to be convenient for online analysis of minerals, metals, coal, cement, petrochemical, coating, paper as well as many other materials and products. The technique has found many uses in medicine, industry, research, security and the detection of contraband items. This report reviews the present status and future trends of the PGAA techniques. Requirements for the system are neutron source, high resolution HPGe detectors with a high-voltage power supply, an amplifier, analog-to-digital converter, and a multichannel analyzer for the detection and measurement of prompt ${\gamma}$-ray emit form the neutron capture elements. Introducing a ${\gamma}$-${\gamma}$ coincidence system also improves the quality of the ${\gamma}$-ray spectrum by suppressing the background created from the Compton scattering of high energy prompt ${\gamma}$-rays. A PGAA system using a $^{252}Cf$ neutron source is currently under construction for the on-line measurement of several elements in aqueous samples at KAERI. The system can be applied for the detection of chemical weapons and explosives as well as various narcotics.

• Journal of IKEEE
• /
• v.26 no.3
• /
• pp.515-519
• /
• 2022

In this paper, we propose the development of a high-sensitivity entry-level nuclide analysis module. The proposed measurement sensor module consists of an electronic driving circuit for nuclide analysis resolution, prototype production with nuclide analysis function, and GUI development applied to prototypes. The electronic part driving circuit for nuclide analysis resolution is divided into nuclide analysis resolution process by the electronic part driving circuit block diagram, MCU circuit design used for radiation measurement, and PC program design for Spectrum acquisition. Prototyping with nuclide analysis function is made by adding a 128×128 pixel OLED display, three buttons for operation, a Li-ion battery, and a USB-C type port for charging the battery. The GUI development department applied to the prototype develops the screen composition such as the current time, elapsed measurement time, total count, and nuclide Spectrum. To evaluate the performance of the proposed measurement sensor module, an expert witness test was conducted. As a result of the test, it was confirmed that the calculated result by applying the resolution formula to the Spectrum (FWHM@662keV) obtained using the Cs-137 standard source in the nuclide analysis device had a resolution of 17.77%. Therefore, it was confirmed that the nuclide analysis resolution method proposed in this paper produces improved performance while being cheaper than the existing commercial nuclide analysis module.

• Journal of Radiation Protection and Research
• /
• v.44 no.2
• /
• pp.64-71
• /
• 2019

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.

• Nuclear Engineering and Technology
• /
• v.34 no.6
• /
• pp.566-573
• /
• 2002

Neutron activation analysis based on $textsc{k}$$_{o}$-standardization method＃ ($textsc{k}$o-NAA) is Com as one of the most remarkable progresses of the NAA with advantages of experimental simplicity, high accuracy, excellent flexibility with respect to irradiation and counting conditions, and suitability for computerization. This study was carried out to determine the reactor neutron spectrum parameters, i.e. $\alpha$ and f as the main factors of irradiation quality at NAA ＃1 irradiation hole on HANARO research reactor, to evaluate peak detection efficiency of the gamma-ray spectrometer for the use in the $textsc{k}$$_{o}$ experiments and to compare the measured concentration results with the certified values of some SRMs applying the experimentally determined to-parameters.ers.