• Communications for Statistical Applications and Methods
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• v.27 no.5
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• pp.511-521
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• 2020

In this paper, a partially linear multivariate model with error in the explanatory variable of the nonparametric part, and an m dimensional response variable is considered. Using the uniform consistency results found for the estimator of the nonparametric part, we derive an estimator of the parametric part. The dependence of the convergence rates on the errors distributions is examined and demonstrated that proposed estimator is asymptotically normal. In main results, both ordinary and super smooth error distributions are considered. Moreover, the derived estimators are applied to the economic behaviors of consumers. Our method handles contaminated data is founded more effectively than the semiparametric method ignores measurement errors.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.4
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• pp.38-47
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• 2020

A parametric study for analytical correction using measurement results was performed to minimize errors in the predictions of column shortening in RC tall building. The parameters of the column shortening analytical correction are the execution standard of analytical correction, the value of the analytical correction, and the measurement location, and the analytical correction models with the parameters were applied to the construction sequence analysis of a 41-story RC building to compare and analyze the correction effect according to the parameter. The reduction ratio of the error value for each floor was compared with the number of corrections and the total corrected value, and it was confirmed that the error tended to be minimized when the execution standard of analytical correction was performed based on a regular interval, when the analysis correction value was corrected by the error value, and when the measurement position was measured every floor. From this, it was confirmed that the most appropriate analytical correction model can be derived by applying multiple analytical correction models to the actual analysis model.

• Geomechanics and Engineering
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• v.33 no.1
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• pp.1-9
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• 2023

The unconfined compression strength (UCS) of soils is commonly used either before or during the construction of geo-structures. In the pre-design stage, UCS as a mechanical property is obtained through a laboratory test that requires cumbersome procedures and high costs from in-situ sampling and sample preparation. As an alternative way, the empirical model established from limited testing cases is used to economically estimate the UCS. However, many parameters affecting the 1D soil compression response hinder employing the traditional statistical analysis. In this study, gene expression programming (GEP) is adopted to develop a prediction model of UCS with common affecting soil properties. A total of 79 undisturbed soil samples are collected, of which 54 samples are utilized for the generation of a predictive model and 25 samples are used to validate the proposed model. Experimental studies are conducted to measure the unconfined compression strength and basic soil index properties. A performance assessment of the prediction model is carried out using statistical checks including the correlation coefficient (R), the root mean square error (RMSE), the mean absolute error (MAE), the relatively squared error (RSE), and external criteria checks. The prediction model has achieved excellent accuracy with values of R, RMSE, MAE, and RSE of 0.98, 10.01, 7.94, and 0.03, respectively for the training data and 0.92, 19.82, 14.56, and 0.15, respectively for the testing data. From the sensitivity analysis and parametric study, the liquid limit and fine content are found to be the most sensitive parameters whereas the sand content is the least critical parameter.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.109-110
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• 2006

Various parametric methods, Larson-Miller (L-M), Orr-Sherby-Dorn (O-S-D), Manson-Haferd (M-H) parameters, and minimum commitment method (MCM), were used to predict longer rupture time from short-term creep data. A number of the creep data were collected through literature surveys and experimental data produced in KAERI for predicting the creep type of type 316LN SS. Polynomial equations for predicting the creep life were obtained by the time-temperature parameters (TTP) and the MCM. standard error (SE) and standard error or mean (SEM) values were compared for the each method with temperatures. The TTP methods were good in the creep-life prediction, but the MCM was much superior to the TTP ones at $700^{\circ}C\;and\;750^{\circ}C$. The MCM was found to be lower in the SE values compared to the TTP methods

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.2 s.257
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• pp.160-165
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• 2007

To predict long-term creep life from short-term creep life data, various parametric methods such as Larson-Mille. (L-M), Orr-Sherby-Dorn (O-S-D), Manson-Haferd (M-H) parameters, and a Minimum Commitment Method (MCM) were suggested. A number of the creep data were collected through literature surveys and experimental data produced in KAERI. The polynomial equations for type 316LN SS were obtained by the time-temperature parameters (TTP) and the MCM. Standard error (SE) and standard error of mean (SEM) values were obtained and compared with the each method for various temperatures. The TTP methods showed good creep-life prediction, but the MCM was much superior to the TTP ones at $700^{\circ}C$ and $750^{\circ}C$. It was found that the MCM were lower in the SE values when compared to the TTP methods.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.10
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• pp.845-850
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• 2016

A direct laser lithography system is widely used to fabricate various types of DOEs (Diffractive Optical Elements) including lenses made as CGH (Computer Generated Hologram). However, a parametric study that uniformly and precisely fabricates the diffractive patterns on a large area (up to $200mm{\times}200mm$) has not yet been reported. In this paper, four parameters (Focal Position Error, Intensity Variation of the Lithographic Beam, Patterning Speed, and Etching Time) were considered for stabilization of the direct laser lithography system, and the experimental results were presented.

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.971-979
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• 2009

In this paper, we introduce the method that reduces the bias when the transformation and back-transformation approach is applied in GARCH models. A parametric bootstrap is employed to compute the conditional expectation which is the prediction value to minimize mean square errors in the original scale. Through the analyese of returns of KOSPI and KOSDAQ, we verified that the proposed method provides a bias-reduced estimation for the prediction value.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.21-28
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• 2006

Vibration of a non-linear system with multiple degrees of freedom under random parametric excitations was evaluated by probabilistic method. The non-linear characteristic terms of system structure were quasi-linearized and excitation terms were remained as they were. An analytical method where the expectation values of square mean of error was minimized was used. The numerical results were compared with those obtained by Monte Carlo simulation. A linear congruential generator and Box-Muller method were used in Monte Carlo simulation. The comparison showed the results by probabilistic method agreed well with those by Monte Carlo simulation.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.871-881
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• 2011

In this paper we propose a logistic regression method to estimate the survival function and the median survival time in interval-censored data. The proposed method is motivated by the data augmentation technique with no sacrifice in augmenting data. In addition, we develop a cross validation criterion to determine the size of data augmentation. We compare the proposed estimator with other existing methods such as the parametric method, the single point imputation method, and the nonparametric maximum likelihood estimator through extensive numerical studies to show that the proposed estimator performs better than others in the sense of the mean squared error. An illustrative example based on a real data set is given.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.346-349
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• 1994

This paper is concerned with a motion control of a manipulator under parametric uncertainties and external disturbances. The parametric uncertainties are regarded as internally generated disturbances in the manipulator. Based on this idea, we formulate a model reference control problem with desired disturbance attenuation. The solution of this control problem not only reduces the worst-case effect on tracking error due to internal and external disturbances (combined disturbances) as much as possible, but also achieve optimal tracking when perturbations are absent. In order to solve the control problem which is formulated in this paper we reduce it to a constrained minmax cost control problem. A differential game theory is used to treat this constrained minmax cost control problem. The differential game theory leads to a sufficient condition for the global solvability of the model reference control problem with desired disturbance attenuation.