• Journal of the Korean Geotechnical Society
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• v.20 no.8
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• pp.49-58
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• 2004

The cone pressuremeter test (CPM) is a new in-situ test which combines a standard cone penetration test with a pressuremeter. The cone pressuremeter tests in clay are presented and analyzed. An analytical solution of CPM incorporated non-linear soil behavior with no volume change is presented, and curve fitting technique is proposed to make use of both the loading and unloading portions of the pressuremeter test. The proposed method is accomplished by putting greater emphasis on the unloading portion. Twenty CPM tests are analyzed using the proposed method, and the derived undrained shear strength of soil is compared with other tests such as field vane tests and laboratory tests. The interpreted soil parameters had resonable values when compared to other in-situ and laboratory test results. The cone pressuremeter has provided reliable measures of undrained shear strength using curve fitting method.

• Journal of the Korean Data and Information Science Society
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• v.7 no.2
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• pp.203-210
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• 1996

A linear neural unit with a modified anti-Hebbian learning rule has been shown to be able to optimally fit curves, surfaces, and hypersurfaces by adaptively extracting the minor component of the input data set. In this paper, we study how to use the robust version of this neural fitting method for linear regression analysis. Furthermore, we compare this method with other methods when data set is contaminated by outliers.

• Proceedings of the KIEE Conference
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• 2001.07c
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• pp.1366-1368
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• 2001

In this study it can be confirmed that the formula by the free-rotational dipole theory is similiar with that by the phenomenological theory and the non-linear permittivity is determined only with the third harmonic conponent of polarization. Various parameters of VDCN copolymers were obtained from fitting results with the related formula.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.687-698
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• 2000

An identification method is proposed in order to detect more than one outlying cells in multi-way contingency tables. The iterative proportional fitting method is applied to get expected values of several suspected outlying cells. Since the proposed method uses minimal sufficient statistics under quasi log-linear models, expected counts of outlying cells could be estimated under any hierarchical log-linear models. This method is an extension of the backwards-stepping method of Simonoff(1988) and requires les iteration to identify outlying cells.

• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.13-22
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• 2000

We consider local likelihood method with a smoothed version of the model density in stead of an original model density. For simplicity a model is assumed as the log-linear density then we were able to show that the proposed local density estimator is less affected by changes among observations but its bias increases little bit more than that of the currently used local density estimator. Hence if we use the existing method and the proposed method in a proper way we would derive the local density estimator fitting the data in a better way.

• Communications for Statistical Applications and Methods
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• v.1 no.1
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• pp.81-86
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• 1994

A Chi-square approximation to the distribution of product of independent Beta variates denoted by U is developed. The distribution is commonly used as a test criterion for the general linear hypothesis about the multivariate linear models. The approximation is obtained by fitting a logarithmic function of U to a Chi-square variate in terms of the first three moments. It is compared with the well known approximations due to Box(1949), Rao(1948), and Mudholkar and Trivedi(1980). It is found that the Chi-square approximation compares favorably with the other three approximations.

• Journal of the Korean Operations Research and Management Science Society
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• v.3 no.1
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• pp.75-79
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• 1978

The use of three mathematical programming techniques (quadratic programming, integer quadratic programming and linear programming) is discussed to solve some problems in linear regression analysis. When the criterion is the minimization of the sum of squared deviations and the parameters are linearly constrained, the problem may be formulated as quadratic programming problem. For the selection of variables to find "best" regression equation in statistics, the technique of integer quadratic programming is proposed and found to be a very useful tool. When the criterion of fitting a linear regression is the minimization of the sum of absolute deviations from the regression function, the problem may be reduced to a linear programming problem and can be solved reasonably well.ably well.

• Korean Journal of Environmental Biology
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• v.21 no.4
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• pp.384-391
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• 2003

The induction of chromosome aberrations in Hordeum vulgare germs after irradiation is studied for the dose range of 10 to 1,000 mGy. The relationship between the frequency of aberrant cells and the absorbed dose is shown to be non -linear and has a dose-independent plateau within the range of 56-467 mGy where the level of cytogenetic damage is statistically significantly distinguished from the spontaneous level. The comparison of the goodness of the experimental data fitting with mathematical models of different complexities, using the most common quantitative criteria, demonstrates the benefit of the piecewise linear model over the linear and polynomial ones in approximating the cytogenetical disturbance frequency. The results of our study support the conclusion about indirect mechanism of chromosome aberrations induced by low doses or dose rates mutagenesis.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.885-898
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• 2012

In this paper, we consider Bayesian approaches to partially linear models, in which a regression function is represented by a semiparametric additive form of a parametric linear regression function and a nonparametric regression function. We make a comparative study on the performance of widely used Bayesian partially linear models in terms of empirical analysis. Specifically, we deal with three Bayesian methods to estimate the nonparametric regression function, one method using Fourier series representation, the other method based on Gaussian process regression approach, and the third method based on the smoothness of the function and differencing. We compare the numerical performance of three methods by the root mean squared error(RMSE). For empirical analysis, we consider synthetic data with simulation studies and real data application by fitting each of them with three Bayesian methods and comparing the RMSEs.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1661-1666
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• 2009

This paper is analyzed the effect on characteristics of thrust force of linear induction motor(LIM) by arc type tester. Many kinds of tester have a rotational shape because of a finite length of railroad. Whereas effects by using rotational type tester are generally unknown. For reason of that, this paper is analyzed the effect on characteristics by rotational type tester using 2D finite element method(FEM), and then is compared a thrust force between linear type tester and rotational type tester. Analysis model is decided by numerical modeling for fitting the LIM for propulsion system of light rail, and it is changed to proper arc model. And then we analyzed the arc and the linear model. Consequently, arc type tester is not only useful experiment but also efficient simulation method, and small error is occurred between linear and arc model.