• Bulletin of the Korean Chemical Society
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• v.16 no.11
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• pp.1113-1118
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• 1995

The Schlo'gl model with the first order transition for a photochemical reaction is considered to study the dynamic behaviors in the neighborhood of the Gaussian white noise by obtaining the explicit results of the time-dependent variance and time correlation function with the aid of approximate methods based on the stationary properties of the system. Then, we discuss the effect of external noise strength on the stability of the model at steady states in detail.

• Proceedings of the Optical Society of Korea Conference
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• 1989.02a
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• pp.95-98
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• 1989

A new associative memory model using the SDF filter, one of the multiple filter for pattern recognition, is suggested in this paper. The SDF filter characteristics such as pattern classification lets the memorized patterns have orthogonal characteristics one another, so that enhances the associative memory's retrieval ability to the original pattern. The computer simulation shows that this new model is very useful in case that the imput patterns are seriously distorted and the cross-correlation between the memorized patterns is very high.

• The Journal of Engineering Geology
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• v.18 no.1
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• pp.27-36
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• 2008

To derive easily the coefficient of permeability from several other soil properties, the estimation model of coefficient of permeability was proposed using linear regression analysis. The coefficient of permeability is one of the major factors to evaluate the soil characteristics. The study area is located in Kangwon-do Pyeongchang-gun Jinbu-Myeon. Soil samples of 45 spots were taken from the study area and various soil tests were carried out in laboratory. After selecting the soil factor influenced by the coefficient of permeability through the correlation analysis, the estimation model of coefficient of permeability was developed using the linear regression analysis between the selected soil factor and the coefficient of permeability from permeability test. Also, the estimation model of coefficient of permeability was compared with the results from permeability test and empirical equation, and the suitability of proposed model was proved. As the result of correlation analysis between various soil factors and the coefficient of permeability using SPSS(statistical package for the social sciences), the largest influence factor of coefficient of permeability were the effective grain size, porosity and dry unit weight. The coefficient of permeability calculated from the proposed model was similar to that resulted from permeability test. Therefore, the proposed model can be used in case of estimating the coefficient of permeability at the same soil condition like study area.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.3_4
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• pp.34-47
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• 1995

It is experienced fact as a regular annual event that the structure to he designed on unreasonable flood for the agricultural structures including reservoirs have been brought not only loss of lives, but also enormous property damage. For the solution of this problem at issue, this study was conducted to develop an optimal runoff hydrograph model by comparison of the peak flows and time to peak between observed and simulated flows derived by linear time-invariant and linear time-variant models under the condition of having a short duration of heavy rainfall with uniform rainfall intensity at nine small watersheds which are within the range of 55.9 to 140.7 square kilometers in area in Han, Geum, Nagdong and Yeongsan Rivers. The results obtained through this study can be summarized as follows. 1. Storage constants and Gamma function arguments were calculated within the range of 1.2 to 6.42 and of 1.28 to 8.05 respectively by the moment method as the parameters for the analysis of runoff hydrograph based on linear time-invariant model. 2. Parameters for both linear time-invariant and linear time-variant models were calibrated with nine gaged watershed data, using a trial and error method. The resulting parameters including Gamma function argument, N and storage constant, K for linear time-invariant model were related statistically to watershed characteristic variables such as area, slope, length of main stream and the centroid length of the basin. 3. Average relative errors of the simulated peak discharge of calibrated runoff hydrographs by using linear time-variant and linear time-invariant models were shown to be 0.75 and 5.42 percent respectively to the peak of observed runoff hydrographs. Correlation coefficients for the statistical analysis in the same condition were shown to be 0.999 and 0.978 with a high significance respectively. Therefore, it can be concluded that the accuracy of a linear time-variant model is approaching more closely to the observed runoff hydrograph than that of a linear time-invariant model in the applied watersheds. 4. Average relative errors of the time to peak of calibrated runoff hydrographs by using linear time-variant and linear time-invariant models were shown to be 16.44 and 19.89 percent respectively to the time to peak of observed runoff hydrographs. Correlation coefficients in the same condition were also shown to be 0.999 and 0.886 with a high significance respectively. 5. It can be seen that the shape of simulated hydrograph based on a linear time- variant model is getting closer to the observed runoff hydrograph than that of a linear time-invariant model in the applied watersheds. 6. Two different models were verified with different rainfall-runoff events from data for the calibration by relative error and correlation analysis. Consequently, it can be generally concluded that verification results for the peak discharge and time to peak of simulated runoff hydrographs were in good agreement with those of calibrated runoff hydrographs.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2196-2203
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• 2020

A dryout mechanism model for rectangular narrow channels at high pressure conditions is developed by assuming that the Kelvin-Helmholtz instability triggered the occurrence of dryout. This model combines the advantages of theoretical analysis and empirical correlation. The unknown coefficients in the theoretical derivation are supported by the experimental data. Meanwhile, the decisive restriction of the experimental conditions on the applicability of the empirical correlation is avoided. The expression of vapor phase velocity at the time of dryout is derived, and the empirical correlation of liquid film thickness is introduced. Since the CHF value obtained from the liquid film thickness should be the same as the value obtained from the Kelvin-Helmholtz critical stability under the same condition, the convergent CHF value is obtained by iteratively calculating. Comparing with the experimental data under the pressure of 6.89-13.79 MPa, the average error of the model is -15.4% with the 95% confidence interval [-20.5%, -10.4%]. And the pressure has a decisive influence on the prediction accuracy of this model. Compared with the existing dryout code, the calculation speed of this model is faster, and the calculation accuracy is improved. This model, with great portability, could be applied to different objects and working conditions by changing the expression of the vapor phase velocity when the dryout phenomenon is triggered and the calculation formula of the liquid film.

• Journal of the Korean Statistical Society
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• v.29 no.1
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• pp.81-94
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• 2000

For the balanced variance component model, sometimes intraclass correlation coefficient is of interest. If there is little information about the parameter, then the reference prior(Berger and Bernardo, 1992) is widely used. Pettit nd Young(1990) considered a measrue of the effect of a single observation on a logarithmic Bayes factor. However, under such a reference prior, the Bayes factor depends on the ratio of unspecified constants. In order to discard this problem, influence diagnostic measures using the intrinsic Bayes factor(Berger and Pericchi, 1996) is presented. Finally, one simulated dataset is provided which illustrates the methodology with appropriate simulation based computational formulas. In order to overcome the difficult Bayesian computation, MCMC methods, such as Gibbs sampler(Gelfand and Smith, 1990) and Metropolis algorithm, are empolyed.

• Journal of Environmental Impact Assessment
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• v.6 no.2
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• pp.81-92
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• 1997

This paper presents the results from the comparison analysis and evaluation between the air pollutant dispersion modeling results and the observation data in the area within a 10 km radius from the Boryong thermal power plants. The observation data used in this study were the air pollutant concentrations which had been continuously measured from 8 locations around the Boryong power plants by TMS(tele-monitoring system) for 3 months from September to November, 1996. The short-term and long-term predictions were carried out using ISC3 model and LPDM(Lagrangian Panicle Dispersion Model). The results of ISC3 modeling in a short-term showed highly as 0.7 in a correlation coefficient, but in a long-term showed just 0.54. On the other hand, LPDM showed 0.78 in a correlation coefficient for a long-term, but in a short-term showed highly value than the observation concentrations.

• Atmosphere
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• v.25 no.1
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• pp.179-183
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• 2015

Even though state-of-the-art general circulation models is improved step by step, the seasonal predictability of the East Asian summer monsoon still remains poor. In contrast, the seasonal predictability of western North Pacific and Indian monsoon region using dynamic models is relatively high. This study builds canonical correlation analysis model for seasonal prediction using wind fields over western North Pacific and Indian Ocean from the Global Seasonal Forecasting System version 5 (GloSea5), and then assesses the predictability of so-called hybrid model. In addition, we suggest improvement method for forecast skill by introducing the lagged ensemble technique.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.173-186
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• 2014

This study outlines possible risk factors in the SCM of a company and correlates risk assessment, the strategy of risk management, and the supply chain performance. The data is surveyed from an international Korean company and is analyzed by the structure equation model of actual proof. The research model verifies the correlation between the risk assessment, the strategy of risk management, and the supply chain performance as dependent variables after the risk factors of the SCM are defined as independent variables. The research shows that there are consecutive links among the risk factors of the SCM, the risk assessment, and the strategy of risk management. The strategy of risk management was conclusively determined to have an effect on supply chain performance. Therefore, improving the supply chain performance of a company requires the constructive process for risk management based on a correlation between risk assessment and the strategy of risk management.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.135-141
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• 2000

The major role of temperature sensors in thermal error compensation system of machine tools is improving machining accuracy by supplying reliable temperature data on the machine structure. This paper presents a new method for fault diagnosis of temperature sensors and recovery of faulted data to establish the reliability of thermal error compensation system. The detection of fault and its location is based on the correlation coefficients among temperature data from the sensors. The multiple linear regression model which is prepared using complete normal data is also used fur the recovery of faulted data. The effectiveness of this method was tested by comparing the computer simulation results and measured data in a CNC machining center.