• 한국응용과학기술학회지
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• 제25권1호
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• pp.107-114
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• 2008

In this article a reliable and rapid method based on specific turbidimetry is proposed for the determination of sizes of nanoparticles. Conventionally in specific turbidimetry specific turbidities for a colloidal dispersion are measured as a function of light wavelength, and compared to theoretical values calculated from Mie scattering theory for presumed particle sizes. In contrast specific turbidity at a fixed wavelength is measured in the proposed method, and particle sizes are determined from the prepared calibration curve. The calibration curve is a plot of specific turbidity vs particle size and in this case the specific turbidities are measured for a couple of samples of known sizes.

• Bulletin of the Korean Chemical Society
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• 제33권12호
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• pp.3971-3976
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• 2012

A simple method was developed for the analysis of seven stilbene-type fluorescent whitening agents (FWAs) in paper materials by ion-pair reversed-phase high-performance liquid chromatography with fluorescence detection. These stilbene-type FWAs included two disulfonate, two tetrasulfonate, and three hexasulfonate compounds. After optimization of chromatographic conditions, the FWAs were satisfactorily separated using a reversed-phase column (RP-18) with the following isocratic mobile phase: methanol-water (60:40) containing 17.5 mM TBABr and 10 mM citrate buffer (pH = 7.0). The calibration plot was linear in the range from 5 to 500 ng/mL for two disulfo-FWAs and from 1 to 500 ng/mL for the other five FWAs. Precision levels of the calibration curve as indicated by RSD of response factors were 1.2 and 8.1%. Limits of quantitation (LOQ) ranged from 1.2 to 11 ng/mL.

• Korean Journal of Radiology
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• 제22권10호
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• pp.1697-1707
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• 2021

The recent introduction of various high-dimensional modeling methods, such as radiomics and deep learning, has created a much greater diversity in modeling approaches for survival prediction (or, more generally, time-to-event prediction). The newness of the recent modeling approaches and unfamiliarity with the model outputs may confuse some researchers and practitioners about the evaluation of the performance of such models. Methodological literacy to critically appraise the performance evaluation of the models and, ideally, the ability to conduct such an evaluation would be needed for those who want to develop models or apply them in practice. This article intends to provide intuitive, conceptual, and practical explanations of the statistical methods for evaluating the performance of survival prediction models with minimal usage of mathematical descriptions. It covers from conventional to deep learning methods, and emphasis has been placed on recent modeling approaches. This review article includes straightforward explanations of C indices (Harrell's C index, etc.), time-dependent receiver operating characteristic curve analysis, calibration plot, other methods for evaluating the calibration performance, and Brier score.

• 응용통계연구
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• 제33권5호
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• pp.555-567
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• 2020

고혈압은 발병률이 꾸준히 증가하고 있을 뿐 아니라, 심혈관 질환과 같은 2차 질병의 주된 위험 요인이 되었다. 게다가 고혈압은 뇌졸중, 혈관성 치매와 같은 다른 합병증을 유발하는 질병이다. 따라서 고혈압 발병률을 예측하는 것은 중요한 일이다. 본 연구에서, 고혈압 발병률을 예측할 수 있는 노모그램을 구축하였다. 데이터는 2013년부터 2016년까지의 국민건강영양조사로부터 얻어졌다. 복합 표본의 특성을 고려하여 Rao-Scott chi-squared test를 통해 고혈압에 영향을 미치는 10가지 요인을 규명하였다. 하지만 로지스틱 회귀분석 시, 흡연 상태와, 운동 유무는 유의하지 않았다. 따라서 8개의 주 효과를 고혈압의 위험요인으로 최종 선별하였다. 그리고 최종 선별된 위험 요인들로 로지스틱 노모그램과 베이지안 노모그램을 제시 및 비교하였다. 마지막으로 ROC curve 그래프와 calibration plot을 통해 노모그램을 검증하였다.

• 응용통계연구
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• 제30권4호
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• pp.591-602
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• 2017

최근 미세먼지 농도가 올라감에 따라 사람들은 호흡기 질환에 큰 관심을 가지고 있다. 본 연구는 인구학적 및 임상적 특징을 통한 만성 폐쇄성 폐질환(chronic obstructive pulmonary disease)의 위험요인을 선별하고 이에 따른 노모그램을 구축하였다. 먼저 국민건강영양조사(KNHANES) 6기 (2013-2015)의 인구학적 및 임상적 특징, 폐기능 검사 결과를 사용하여 로지스틱 회귀분석을 실시 하였고 비전공자들도 분석 결과에 대한 해석을 쉽게 할 수 있도록 만성 폐쇄성폐질환의 위험 요 인을 시각화한 노모그램을 구축하였다. 또한 ROC curve와 Calibration plot을 이용하여 만성 폐쇄 성 폐질환의 노모그램을 검증하였다.

• 한국환경농학회지
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• 제30권4호
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• pp.357-366
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• 2011

BACKGROUND: Mathematical model such as GLEAMS have been developed and successfully applied to upland fields to estimate the level of pesticide residues in soil. But, the GLEAMS model rarely applied to the Korean conditions. METHODS AND RESULTS: To evaluate pesticide transport in soil residue using the GLEAMS model from pepper plot, Alachlor, Endosulfan, Cypermethrin and Fenvalerate were applied for standard and double rate. Soil sampling was conducted and decaying patterns of pesticides were investigated. Observed climate data such as temperature and irrigation amount were used for hydrology simulation. The observed pesticide residue data of 2008 were used for parameter calibration, and validation of GLEAMS model was conducted with observed data of 2009. After calibration, the $K_{oc}$ (Organic carbon distribution coefficient) and WSHFRC (Washoff fraction) parameters were identified as key parameters. The simulated concentrations of the pesticides except Fenvalerate were sensitive to $K_{oc}$ parameter. Overall, soil residue concentrations of Alachlor, Cypermethrin and Fenvalerate were fairly simulated compared to those of Endosulfan. The applicability of the GLEAMS model was also confirmed by statistical analysis. CONCLUSION(s): GLEAMS model was eligible for evaluation of pesticide soil residue for Alachlor, Cypermethrin and Fenvalerate.

• 응용통계연구
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• 제32권4호
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• pp.619-630
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• 2019

이상지질혈증은 한국인의 대표적인 성인병이며 지속적인 관리가 필요한 만성질환이다. 또한 고혈압이나 당뇨병과 함께 심혈관계 질환의 위험 요인으로 잘 알려져 있다. 하지만 혈관 질환은 검사 없이는 질병 판단을 하기 어려운 것이 현실이다. 본 연구에서는 이상지질혈증의 인지와 예방을 위하여 관련된 위험 요인을 확인한다. 이들을 종합하여 시각화하면서 발병률 예측까지 가능한 통계적 도구 노모그램을 구축하였다. 데이터는 국민건강영양조사 6기, 7기 제1차년도 (2013-2016) 데이터를 사용하였다. 분석 순서로는 먼저 이상지질혈증의 총 12가지 위험 요인을 교차분석을 통해 확인하였다. 그리고 순수 베이지안 분류기를 이용하여 이상지질혈증에 대한 모형으로 노모그램을 구축하였다. 구축한 노모그램은 ROC 곡선과 Calibration plot을 사용하여 신뢰성을 검증하였다. 마지막으로 이전에 제시했던 로지스틱 노모그램과 본 연구에서 제안한 베이지안 노모그램을 비교하였다.

• Bulletin of the Korean Chemical Society
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• 제27권9호
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• pp.1433-1438
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• 2006

An AsFlFFF channel was designed and built, and then tested for analysis of pullulans and proteins. Pullulans and proteins having various nominal molecular weights were injected at various conditions of the cross-flow rate ($F_c$) and the channel-out flow rate ($F_{out}$). The retention (measured by the retention ratio R) and the zone broadening (measured by the plate height H) were measured, and then compared with theory. When the incoming flow rate, $f_{in}$ (and thus $F_{out}$) was varied with $F_c$ fixed at 2.5 mL/min, the plate height measured for the pullulan with nominal molecular weight (M) of about 100,000 showed the trend expected by the longitudinal diffusion theory (H decreases with increasing flow rate). In contrast, when $F_{out}$ was varied with the flow rate ratio, $F_c/F_{out}$, fixed constant at 5, the plate height measured for the same sample showed the trend expected from the non-equilibrium theory (H increases with increasing flow rate). Calibration plots (log D vs. log M) obtained with pullulans and proteins were not coincide, probably due to the difference in molecular conformation, suggesting the analysis of pullulans and proteins using AsFlFFF requires independent calibration. It was found that the linearity of the protein-calibration plot was improved by using a buffer solution as the carrier.

• 한국작물학회지
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• 제56권1호
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• pp.88-93
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• 2011

This experiment was carried out to find suitable sample type for the more accurate prediction and non-destructive way in the application of near infrared reflectance spectroscopy (NIRS) technique for estimation the protein, total amino acids, and total isoflavone of soybean by comparing three different sample types, single seed, whole seeds, and milled seeds powder. The coefficient of determination in calibration ($R^2$) and coefficient of determination in cross-validation (1-VR) for three components analyzed using NIRS revealed that milled powder sample type yielded the highest, followed by single seed, and the whole seeds as the lowest. The coefficient of determination in calibration for single seed was moderately low($R^2$ 0.70-0.84), while the calibration equation developed with NIRS data scanned with whole seeds showed the lowest accuracy and reliability compared with other sample groups. The scatter plot for NIRS data versus the reference data of whole seeds showed the widest data cloud, in contrary with the milled powder type which showed flatter data cloud. By comparison of NIRS results for total isoflavone, total amino acids, and protein of soybean seeds with three sample types, the powder sample could be estimated for the most accurate prediction. However, based from the results, the use of single bean samples, without grinding the seeds and in consideration with NIRS application for more nondestructive and faster prediction, is proven to be a promising strategy for soybean component estimation using NIRS.

• 한국농공학회논문집
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• 제50권2호
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• pp.3-10
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• 2008

The main objectives of this study are to calibrate the RICEWQ model with Korean field data and then analyse the sensitivity of the parameters to identify sensitive parameters. The RICEWQ is widely used to predict pesticide fate in a paddy plot. An experimental paddy plot of 0.2 ha($100{\times}20\;m$) at Seobyeon-dong, Daegu, Korea was selected, and field observations for water and pesticide balance were performed from 4 June to 2 September 2006. The molinate, which is a herbicide widely used for weed control in rice culture, was selected. The RICEWQ model was successfully calibrated both for the water and pesticide mass balance. The calibrated model showed a RMSE of 0.537 cm for ponded water depths and a RMSE of 0.036 mg/L for the molinate concentrations in the ponded water. The most sensitive parameters for molinate concentrations in ponded water were the metabolism degradation rate in water, volatilization coefficient, and release rate for slow release formulation. In contrast, the RICEWQ model was not sensitive to parameters such as hydrolysis degradation rate in water and degradation rate in unsaturated soil.