• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1491-1506
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• 2021

To estimate errors in GEMS retrievals for bromine monoxide (BrO) total vertical column densities(VCDs), we perform a sensitivity test using synthetic spectra generated by a radiative transfer model. Hourly synthetic data are produced for 00-07 UTC on the first day of every month in Jul 2013- Jun 2014. Solution errors estimated by the optimal estimation method tend to decrease with increasing air mass factors (AMFs) but increase when AMFs are larger than 5. Interference errors induced by formaldehyde (HCHO) absorption appear to be larger with smaller BrO AMFs. Total BrO retrieval errors estimated by combining solution and interference errors show an average of 26.74±30.18% for all data samples and 60.39±133.78% for those with solar zenith angles higher than 80°. Due to interfering spectral features and measurement errors not considered in thisstudy, errorsin BrO retrievals from actual GEMS measurements may have different magnitudes from our estimates. However, the variability of errors assessed in this study is still expected to appear in the actual BrO retrievals.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.174-178
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• 1987

In the design of reference model based STC (self-tuning controllers), parameters of the controllers are determined not from the true plant but from the estimated model. In this paper, we suggest a power spectrum estimation method for visualling the sensitivity of the closed loop system without knowing the explicit original plant.

• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.87-96
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• 2000

Nonlinear time series prediction is derived and compared between statistic of modeling and neural network method. In particular mean squared errors of predication are obtained in generalized random coefficient model and generalized autoregressive conditional heteroscedastic model and compared with them by neural network forecasting.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.2
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• pp.65-75
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• 1989

A general software reliability model is developed, which includes the Jelinski-Moranda model, the Goel-Okumoto model, the Shanthikumar model and the Ross model as special cases. In each of above models estimators of the software failure rate and the number of remaining errors are presented and compared in terms of the expected absolute error loss and the expected squared error loss by a Monte Carlo simulation.

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.55-67
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• 1998

Recent work by Shin and Sarkar (1996) examines model misspecification problems for nonstationary time series. Shin and Sarkar introduce a general regression model with integrated errors and one system of integrated regressors and discuss the limiting distributions of the OLS estimators and the usual OLS statistics such as $\hat{\sigma^2}$t, DW and $R^2$. We analyze three different model misspecification problems through a Monte Carlo study and investigate each model misspecification problem. Our Monte Carlo experiments show that DW and $R^2$ can be in general used as diagnostic tools to detect spurious regression, misspecification of nonstationary autoregressive and polynomial regression models.

• Journal of the Korean Statistical Society
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• v.29 no.2
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• pp.231-245
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• 2000

This paper considers a linear regression model with space and time data in where the disturbances follow spatially correlated error components. We provide the best linear unbiased predictor for the one way error components. We provide the best linear unbiased predictor for the one way error component model with spatial autocorrelation. Further, we derive two diagnostic test statistics for the assessment of model specification due to spatial dependence and random effects as an application of the Lagrange Multiplier principle.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.9
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• pp.1378-1385
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• 1990

In this paper we propose a model which can predict well the logical errors come from the charge redistribution in domino gates. In this model the effect of the intrinsic capacitance between gate and channel of MOSFET's is considered. This effect is more important than the parasitic capacitance effect. The error by the proposed model is only 8% of that by the currently used model. This model can be used as a guide-line in the design of domino circuits.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.1009-1019
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• 2006

In this paper, we consider the simultaneous estimation problem for the normal means. We set up the model structure using the several different distributions of the errors for observing their effects of model perturbation for the error terms in obtaining the empirical Bayes and hierarchical Bayes estimators. We compare the performance of those estimators under model perturbation based on a simulation study.

• The Journal of the Korean dental association
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• v.44 no.2 s.441
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• pp.115-122
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• 2006

Objective : The purpose of this study was to evaluate the dimensional errors between real tooth, 3D CT image and CARP model. Materials and Methods : Two maxilla and two mandible block bones with intact teeth were taken from two cadavers. Computed tomography was taken either in dry state and in wet state. After then, all teeth were extracted and the dimensions of the real teeth were measured using a digital caliper at mesio-distal and bucco-lingual width both in crown and cervical portion. 3D CT image was generated using the V-works $4.0^{TM}$ (Cybemed Inc., Seoul, Korea) software. Twelve teeth were randomly selected for CARP model fabrication. All the measurements of 3D Ct images and CARP models were made in the same manner of the real tooth group. Dimensional errors between real tooth, 3D CT image model and CARP model was calculated. Results : 1) Average of absolute error was 0.199 mm between real teeth and 3D CT image model, 0.169 mm between 3D CT image model and CARP model and 0.291 mm between real teeth and CARP model, respectively. 2) Average size of 3D CT image was smaller than real teeth by 0.149 mm and that of CARP model was smalier than 3D CT image model by 0.067mm. Conclusion : Within the scope of this study, CARP model with the 0.291 mm average of absolute eror can aid to enhance the success rate cf autogenous tooth transplantation due to the increased accuracy of recipient bone and donor tooth.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1418-1423
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• 2003

In this paper, a nonlinear controller based on sliding mode control is applied to a two -wheeled Welding Mobile Robot (WMR) to track a smooth-curved welding path at a constant velocity of the welding point. T he mobile robot is considered in terms of dynamics model in Cartesian coordinates and its parameters are exactly known . To obtain the controller, the tracking errors are defined, and the two sliding surfaces are chosen to guarantee that the errors converge to zero asymptotically. Two cases are to be considered: fixed torch and controllable torch. In addition, a simple way of measuring the errors is introduced using two potentiometers. The simulation results are included to illustrate the performance of the control law.