• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.33-34
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• 2008

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.497-498
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• 2012

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.75-76
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• 2012

• Journal of the Korean Statistical Society
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• v.35 no.1
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• pp.79-90
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• 2006

We consider the subdiagonal bilinear model and ARMA model with subdiagonal bilinear errors. Sufficient conditions for geometric ergodicity of associated Markov chains are derived by using results on generalized random coefficient autoregressive models and then strict stationarity and ,a-mixing property with exponential decay rates for given processes are obtained.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.9-10
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• 2009

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.11-12
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• 2009

• Korean Journal of Remote Sensing
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• v.32 no.1
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• pp.49-60
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• 2016

This paper presents a set of methods to evaluate the image quality of smartphone cameras as compared with that of a DSLR camera. In recent years, smartphone cameras have been used broadly for many purposes. As the performance of smartphone cameras has been enhanced considerably, they can be considered to be used for precise mapping instead of metric cameras. To evaluate the possibility, we tested the quality of one DSLR camera and 3 smartphone cameras. In the first step, we compare the amount of lens distortions inherent in each camera using camera calibration sheet images. Then, we acquired target sheet images, extracted reference lines from them and evaluated the geometric quality of smartphone cameras based on the amount of errors occurring in fitting a straight line to observed points. In addition, we present a method to evaluate the radiometric quality of the images taken by each camera based on planar fitting errors. Also, we propose a method to quantify the geometric quality of the selected camera using edge displacements observed in target sheet images. The experimental results show that the geometric and radiometric qualities of smartphone cameras are comparable to those of a DSLR camera except lens distortion parameters.

• Journal of Korean Society of Steel Construction
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• v.19 no.3
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• pp.313-321
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• 2007

The study discussed in this paper presents a method of estimating sources of geometric errors in suspension bridges in use, based on geometric survey data. A geometric error is defined as the difference between the survey data and the design geometry of a main cable. It is assumed that the geometric error in a suspension bridge is caused by the variations in the weight of the stiffening girder and the deformation of the anchorage foundations due to the creep of soil. The variations in the girder weight and the deformation of the foundation were estimated by constructing a matrix of factors that affect suspension bridges due to the variations. To check the validity of the proposed method, it was applied to the Kwang-An Bridge, and the sources of geometric errors in the bridge were estimated using the survey data.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.1
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• pp.1-6
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• 2014

This paper describes a method of estimating and evaluating the volumetric errors of multi-axis machine tools. The estimation method is based on a generic model that was developed from conventional kinematic error models for the geometric and thermal errors to help predict the volumetric error easily in various configurations. To demonstrate the advantages of the model, an application in the early stages of a five-axis machine tool design is presented as an example. The model was experimentally evaluated for a four-axis machine tool by using the data from ISO230-6 and R-test measurements to compare the estimated and measured volumetric errors.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.65-77
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• 2020

Geometric charts are effective in monitoring the fraction nonconforming in high-quality processes. The in-control fraction nonconforming is unknown in most actual processes; therefore, it should be estimated using the Phase I sample. However, if the Phase I sample size is small the practitioner may not achieve the desired in-control performance because estimation errors can occur when the parameters are estimated. Therefore, in this paper, we adjust the control limits of geometric charts with the bootstrap algorithm to improve the in-control performance of charts with smaller sample sizes. The simulation results show that the adjustment with the bootstrap algorithm improves the in-control performance of geometric charts by controlling the probability that the in-control average run length has a value greater than the desired one. The out-of-control performance of geometric charts with adjusted limits is also discussed.