• 멤브레인
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• 제10권1호
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• pp.19-29
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• 2000

고분자/용매계에서 물질전달현상에 이용되는 용매의 상호확산계수를 예측하기 위하여 기존의 UNFACFV을 적용한 확산식을 유도하였으며, 상호확산계수를 계산하였다. 또한, 새로운 모델식에 의하여 계산한 값을 실험치 및 Vrentas-Duda의 이론치와 비교하였다. 상화확산계수를 구하는데 필요한 자기확산계수는 Vrentas-Duda의 이론을 이용하고, 용매의 화학포텐셜의 농도 미분항은 original UNIFAC-FA와 modified UNIFAC-FV를 사용하였다. Flory-Hugginstlr을 이용한 Vrentas-Duda의 상호확산식은 용매의 화학포텐셜의 농도 미분항을 표현하기 위하여 매개변수 x를 온도와 농도에 무관한 상수로 가정한 단점을 가지고 있으나, 본 연구에서 제시한 방법에서는 이러한 가정이 없으며, 여러 가지 고분자/용매계(polyisobutylene homopolymer 및 polyisobutylene-poly(pmethylstyrene) copolymer와 cyclohexane, n-hexane, n-pentane, chloroform, toluene)에서의 상호확산계수를 잘예측하였다. 특히 PIB/toluene계의 경우, 본 논문에서 사용된 방법이 Vrentas-Duda 이론에 의한 것보다 실험치에 더 가까웠다. 또한, 아무런 가정이나 제약없이, 넓은 온도 및 농도 영역에서 고분자/용매계의 상호확산계수를 예측할 수 있는 좋은 방법임을 알 수 있었다.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.585-594
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• 2003

It has been generally recognized that conventional binomial or Poisson model provides poor fits to the actual correlated binary data due to the extra-binomial variation. A number of generalized statistical models have been proposed to account for this additional variation. Among them, beta-binomial, correlated-binomial, and modified-binomial models are binomial-related models which are frequently used in modeling the sum of n correlated binary data. In many situations, it is reasonable to assume that n correlated binary data are exchangeable, which is a special case of correlated binary data. The sum of n exchangeable correlated binary data is modeled relatively well when the above three binomial-related models are applied. But the estimation results of correlation coefficient turn to be quite different. Hence, it is important to identify which model provides better estimates of model parameters(success probability, correlation coefficient). For this purpose, a small-scale simulation study is performed to compare the behavior of above three models.

• Communications for Statistical Applications and Methods
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• 제22권3호
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• pp.305-312
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• 2015

We extend a generalized partially linear single-index model and newly define a generalized partially double-index model (GPDIM). The philosophy of sufficient dimension reduction is adopted in GPDIM to estimate unknown coefficient vectors in the model. Subsequently, various combinations of popular sufficient dimension reduction methods are constructed with the best combination among many candidates determined through a bootstrapping procedure that measures distances between subspaces. Distinguishing values are newly defined to match the estimates to the corresponding population coefficient vectors. One of the strengths of the proposed model is that it can investigate the appropriateness of GPDIM over a single-index model. Various numerical studies confirm the proposed approach, and real data application are presented for illustration purposes.

• Journal of the Korean Data and Information Science Society
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• 제24권2호
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• pp.401-408
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• 2013

Soil moisture is a very important variable in various area of hydrological processes. We predict the soil moisture using a support vector regression. The model is trained and tested using the soil moisture data observed in five sites in the Yongdam dam basin. With respect to soil moisture data of of four sites-Jucheon, Bugui, Sangieon and Ahncheon which are used to train the model, the correlation coefficient between the esimtates and the observed values is about 0.976. As the result of the application to Cheoncheon2 for validating the model, the correlation coefficient between the estimates and the observed values of soil moisture is about 0.835. We compare those results with those of artificial neural network models.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2002년도 International Meeting on Information Display
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• pp.487-490
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• 2002

In this paper, we report a novel way to evaluate the anticlinic interlayer coupling coefficient U between smectic layers of an antiferroelectric liquid crystal, by utilizing a small field-induced perturbation of the molecular orientation. U was found to exhibit an unusual "S-shaped" dependence on temperature, with values ranging between $0.4{\times}10^4$ and $0.4{\times}10^{-1}$ erg $cm^{-3}$ over a 10$^{\circ}C$ temperature range below smectic A-smectic $C_A$ phase transition temperature. The results are good agreement with estimates for U based upon the threshold field for the onset of solitary waves, and provide strong supporting the low-field regime for the single Fourier component model.

• 한국구조물진단유지관리공학회 논문집
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• 제7권2호
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• pp.239-246
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• 2003

In the PCA Load Contour Method, the biaxial bending design coefficient of columns(${\beta}$) is based on the equivalent rectangular stress block (RSB). And coefficient of ${\beta}$ estimates the reinforcement index to be a influencing parameter on biaxial moment strength of RC columns without considering the arbitrary condition of bar arrangement. The experimental results of high strength concrete (HSC) columns subjected to combined axial load and biaxial bending moment were compared to the analysis results of RSB method. As result, the accuracy of RSB method is still acceptable for HSC columns and, as the reinforcement is placed densely in each corner of column section, the ${\beta}$ is decreased.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2007년도 학술발표회 논문집
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• pp.1592-1596
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• 2007

Accuracy of flood forecasting is an important non-structural measure on the flood control and mitigation. Hence, combination of horologic model with real time error correction became an important issue. It is one of the efficient ways to improve the forecasting precision. In this work, an approach based on Kalman Filter (KF) is proposed to continuously revise state estimates to promote the accuracy of flood forecasting results. The case study refers to the Wi River in Korea, with the flood forecasting results of Xinanjiang model. Compared to the results, the corrected results based on the Kalman filter are more accurate. It proved that this method can take good effect on hydrologic forecasting of Wi River, Korea, although there are also flood peak discharge and flood reach time biases. The average determined coefficient and the peak discharge are quite improved, with the determined coefficient exceeding 0.95 for every year.

• 물과 미래
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• 제27권1호
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• pp.133-140
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• 1994

주변 관측지점의 자료가 유용한 경우 관측자료가 짧은 지점의 평균과 분산 추정치를 개선하기 위하여 상관계수를 이용한 수문자료 확충을 이용하여왔다. 본 연구에서는 관측지점의 분산 추정치를 개선하기 위한 다중 상관계수의 한계최소치를 얻기 위하여, 다변량 정규분포에 근거하여 Moran이 유도한 확충자료 분산( ${{\sigma}_v}^2$ )의 불편 최우도추정량의 분산식을 Matalas와 Jacobs가 2변량 정규분포에 근거하여 유도한 식의 형태로 변형하였으며, 다양한 자료수와 지점수에 따라 다중상관계수의 한계최소치를 도표화했다.

• 한국농공학회논문집
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• 제48권1호
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• pp.13-23
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• 2006

In 1998, Food and Agriculture Organization addressed that FAO Modified Penman method possibly over-estimates consumptive use of water comparing to the measured reference crop evapotranspiration (PET) and Penman-Monteith method can be better choice for accurate PET estimation. Nevertheless it is still difficult to find research efforts about paddy rice crop coefficient for Penman-Monteith method. This study aims to estimate paddy rice crop coefficients for Penman-Monteith and FAO modified Penman methods in the manner of comparing two equations. To estimate the crop coefficients, measured evapotranspiration data during 1982-1986 and 1995-1997 were used. The average Penman-Monteith crop coefficients ranged from 0.78 to 1.58 for translated paddy rice and from 0.87 to 1.74 for flood-direct seeded paddy rice. The average FAO Modified Penman crop coefficients ranged from 0.65 to 1.35 for translated paddy rice and from 0.70 to 1.58 for flood-direct seeded paddy rice.

• 한국환경과학회지
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• 제11권7호
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• pp.679-686
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• 2002

Turbulence greatly influence on atmospheric flow field. In the atmosphere, turbulence is represented as turbulent diffusion coefficients. To estimate turbulent diffusion coefficients in previous studies, it has been used constants or 2-level method which divides surface layer and Ekman layer. In this study, it was introduced Smagorinsky method which estimates turbulent diffusion coefficient not to divide the layer but to continue in vertical direction. We simulated 3-D flow model and TKE equation applied turbulent diffusion coefficients using two methods, respectively. Then we showed the values of TKE and the condition of each term to TKE. The results of Smagorinsky method were reasonable. But the results of 2-level method were not reasonable. Therefor, it had better use Smagorinsky method to estimate turbulent diffusion coefficients. We are expected that if it is developed better TKE equation and model with study of computational method in several turbulent diffusion coefficients for reasonably turbulent diffusion, we will able to predict precise wind field and movements of air pollutants.