• Journal of the Korean Chemical Society
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• v.47 no.1
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• pp.31-37
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• 2003

The expanded uncertainties calculated by the application of GUM -approximation and Monte-Carlo simulation were compared about the model equation of one-point calibration which is widely used for the measurements and chemical analysis. For the comparisons, we assumed a set of artificial data at the various level of concentration and dispersion of t or normal distribution. Mistakes of more then 50 % was revealed at the values calculated by GUM-approximation in comparison with those of Monte-Carlo simulation because of the excess dispersion from t-distribution and non-linearity by division in the equation. In contrary, the mistake of calculation due to non-linearity of the equation was not observed in the level of detection limits with the equation of one-point calibration, because of the relatively large values of uncertainty in response.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.545-557
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• 2018

The inclusion of covariates in the model often affects not only the estimates of meaningful variables of interest but also its statistical significance. Such gap between statistical and subject-matter significance is a critical issue in huge sample studies. A popular huge sample study, the sample cohort data from Korean National Health Insurance Service, showed such gap of significance in the inference for the effect of obesity on cause of mortality, requiring careful consideration. In this regard, this paper proposes a sample size calibration method based on a Monte Carlo t (or z)-test approach without Monte Carlo simulation, and also proposes a test procedure for subject-matter significance using this calibration method in order to complement the deflated p-value in the huge sample size. Our calibration method shows no subject-matter significance of the obesity paradox regardless of race, sex, and age groups, unlike traditional statistical suggestions based on p-values.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4167-4172
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• 2023

Miniaturized tissue equivalent proportional counters (mini-TEPCs) are proper for radiation dosimetry in medical application because the small size of the dosimeter could prevent pile-up effect under the high intensity of therapeutic beam. However, traditional methods of calibrating mini-TEPCs using internal alpha sources are not feasible due to their small size. In this study, we investigated the use of electron and proton edges on Monte Carlo-generated lineal energy spectra as markers for calibrating a 0.9 mm diameter and length mini-TEPC. Three possible markers for each spectrum were calculated and compared using different simulation tools. Our simulations showed that the electron edge markers were more consistent across different simulation tools than the proton edge markers, which showed greater variation due to differences in the microdosimetric spectra. In most cases, the second marker, y_δδ, had the smallest uncertainty. Our findings suggest that the lineal energy spectra from mini-TEPCs can be calibrated using Monte Carlo simulations that closely resemble real-world detector and source geometries.

• The Journal of the Korea Contents Association
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• v.9 no.5
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• pp.355-364
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• 2009

This study investigated the labor market outcomes between IT graduates and non-IT graduates in terms of employment, wage, and work period through Monte-Carlo and Calibration method. The empirical result of the movement from work to unemployment implied that IT major graduates have stable work period irrespective of continuous employment, and but the number of work period of non-IT graduates decreases. It also showed that IT related department graduates got relatively paid more than non-IT graduates and IT major graduates was 0.8% higher wage premium than non-IT graduates.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.93-102
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• 2009

A prediction of streamflow based on multi-objective function is presented to check the performance of Probability Distributed Model(PDM) in Miho stream basin, Chungcheongbuk-do, Korea. PDM is a lumped conceptual rainfall runoff model which has been widely used for flood prevention activities in UK Environmental Agency. The Monte Carlo Analysis Toolkit(MCAT) is a numerical analysis tools based on population sampling, which allows evaluation of performance, identifiability, regional sensitivity and etc. PDM is calibrated for five model parameters by using MCAT. The results show that the performance of model parameters(cmax and k(q)) indicates high identifiability and the others obtain equifinality. In addition, the multi-objective function is applied to PDM for seeking suitable model parameters. The solution of the multi-objective function consists of the Pareto solution accounting to various trade-offs between the different objective functions considering properties of hydrograph. The result indicated the performance of model and simulated hydrograph are acceptable in terms on Nash Sutcliffe Effciency*(=0.035), FSB(=0.161), and FDBH(=0.809) to calibration periods, validation periods as well.

• Nuclear Engineering and Technology
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• v.35 no.3
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• pp.234-242
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• 2003

The full energy peak efficiency of a hyper pure germanium (HPGe) detector was calibrated in a wide energy range from 0.06 to 11 MeV. Both the experimental technique and the Monte Carlo method were used for the efficiency calibration. The measurement was performed using the standard radioisotopes in the low energy region of $60{\sim}1408$ keV, which was further extended up to 11 MeV by using the $^{14}N(n,r)\;and\;^{35}Cl(n,r)$ reactions. The GEANT Monte Carlo code was used for efficiency calculation. The calculated efficiency had the same dependency on the r-ray energy with the measurement, and the discrepancy between the calculation and the measurement was minimized by fine-tuning of the detector geometry. From the calculated result, the efficiency curve of the HPGe detector was reliably determined particularly in the high energy region above several MeV, where the number of measured efficiency points is relatively small despite the wide energy region. The calculated efficiency agreed with the measurement within about $7\%$. In addition to the efficiency calculation, the origin of the local minimum near 600 keV on the efficiency curve was analyzed as a general characteristics of a HPGe detector.

• Journal of Korea Water Resources Association
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• v.37 no.9
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• pp.719-727
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• 2004

Water quality models can be applied to manage the regional water quality problems and to estimate the target and allowable pollution load in watershed effectively. The optimization of state variables in the given water quality model Is necessary to build up more effective model. The least-squares method is applied to fit field observations in QUAL2E developed by U.S. EPA, which is most widely used one in the world to simulate the stream water quality, and the optimization model with constraints is constructed to estimate the parameters. The objective function of the optimization model is solved by Solver in Microsoft Excel and Monte Carlo simulation is conducted to know the influence of parameter in conventional pollutants. It is found that this technique is easily implemented and rapidly convergent computational procedure to calibrate the parameters after appling this approach in Anyang stream located in Kyonggi province mainly.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.860-863
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• 1996

In this paper, we formulate the extended Kalman filter for calibration of gimballed inertial navigation system (GINS) at a pure navigation mode with 1500 ft/sec initial velocity and compare its performance to the linear Kalman filter's by using Monte-Carlo analysis method. It has been shown that estimation performance of the extended Kalman filter is better than that of the linear Kalman filter.

• Journal of Radiation Protection and Research
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• v.42 no.1
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• pp.48-55
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• 2017

Background: Simultaneous detection of neutrons and gamma rays have become much more practicable, by taking advantage of good gamma-ray discrimination properties using pulse shape discrimination (PSD) technique. Recently, we introduced a commercial CLYC system in Korea, and performed an initial characterization and simulation studies for the CLYC detector system to provide references for the future implementation of the dual-mode scintillator system in various studies and applications. Materials and Methods: We evaluated a CLYC detector with 95% $^6Li$ enrichment using various gamma-ray sources and a $^{252}Cf$ neutron source, with validation of our Monte Carlo simulation results via measurement experiments. Absolute full-energy peak efficiency values were calculated for gamma-ray sources and neutron source using MCNP6 and compared with measurement experiments of the calibration sources. In addition, behavioral characteristics of neutrons were validated by comparing simulations and experiments on neutron moderation with various polyethylene (PE) moderator thicknesses. Results and Discussion: Both results showed good agreements in overall characteristics of the gamma and neutron detection efficiencies, with consistent ~20% discrepancy. Furthermore, moderation of neutrons emitted from $^{252}Cf$ showed similarities between the simulation and the experiment, in terms of their relative ratios depending on the thickness of the PE moderator. Conclusion: A CLYC detector system was characterized for its energy resolution and detection efficiency, and Monte Carlo simulations on the detector system was validated experimentally. Validation of the simulation results in overall trend of the CLYC detector behavior will provide the fundamental basis and validity of follow-up Monte Carlo simulation studies for the development of our dual-particle imager using a rotational modulation collimator.

• Journal of Preventive Medicine and Public Health
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• v.55 no.1
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• pp.28-36
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• 2022

The current multimorbidity correction method in the Global Burden of Disease studies assumes the independent occurrence of diseases. Those studies use Monte-Carlo simulations to adjust for the presence of multiple disease conditions for all diseases. The present study investigated whether the above-mentioned assumption is reasonable based on the prevalence confirmed from actual data. This study compared multimorbidity-adjusted years of lived with disability (YLD) obtained by Monte-Carlo simulations and multimorbidity-adjusted YLD using multimorbidity prevalence derived from National Health Insurance Service data. The 5 most common diseases by sex and age groups were selected as diseases of interest. No significant differences were found between YLD estimations made using actual data and Monte-Carlo simulations, even though assumptions about the independent occurrence of diseases should be carefully applied. The prevalence was not well reflected according to disease characteristics in those under the age of 30, among whom there was a difference in YLD between the 2 methods. Therefore, when calculating the burden of diseases for Koreans over the age of 30, it is possible to calculate the YLD with correction for multimorbidity through Monte-Carlo simulation, but care should be taken with under-30s. It is useful to apply the efficiency and suitability of calibration for multiplicative methods using Monte-Carlo simulations in research on the domestic disease burden, especially in adults in their 30s and older. Further research should be carried out on multimorbidity correction methodology according to the characteristics of multiple diseases by sex and age.