• Journal of Korea Technology Innovation Society
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• v.6 no.3
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• pp.279-297
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• 2003

The purpose of this paper is to analyze the determinants of company R＆D investment with zero observations by using the data of R＆D Scoreboard published by Ministry of Science and Technology(2002). Conventional parametric approach to dealing with zero investments is not robust to heteroscedastic and/or non-normal error structure. Thus, this study applies symmetrically trimmed least squares(STLS) estimation as a semi-parametric approach to dealing with zero R&D investments. The result of specification test indicates the semi-parametric approach outperforms the parametric approach significantly. Moreover, the results of the study provide various implications as summarized below. The R&D investment of IT company is larger than that of non-IT company. The R&D investment has a positive relation to foreigners' investment ratio. The higher degree of financial self-reliance is, the larger the R&D investment is. Firm size variables such as sales amount and the number of workers are positively related to R&D investment. The sales elasticity of R&D investment is larger than one. However, the workers elasticity of R&D investment is smaller than one.

• Fashion & Textile Research Journal
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• v.16 no.2
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• pp.266-274
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• 2014

Parametric bodies reproduce the actual shape of human body parts and should be convenient for general users to change size to judge the visual fit of clothes on-line. In this study, three parametric bodies(i.e. I, C, D ) were compared to verify the accuracy of the provided body dimensions and reproducibility to a target model. To compare reproducibility, the 20s female standard virtual model developed for an apparel industry by Korean agency for technology and standards is used. The investigation of existing parameters showed that the numbers and kinds of parameters provided by each program were different with some errors in notation; in addition, some of virtual body dimensions went beyond the maximum allowable error. The result of changing each parametric body to the 20s female standard body showed that D, C, I in order produced better reproducibility for body dimensions. There were different levels of protrusion and concavity in the virtual cross sections and virtual longitudinal sections despite the small differences in body dimensions and cross sectional areas; in addition, some parametric body was not bilateral symmetry. The results of this study can be used as basic information in the standardization of a virtual model used in a virtual garment program.

• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.501-508
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• 2003

Although the estimate of regression function is important, some have focused the variance estimation of error term in regression model. Different variance estimators perform well under different conditions. In many practical situations, it is rather hard to assess which conditions are approximately satisfied so as to identify the best variance estimator for the given data. In this article, we suggest SHM estimator compared to LS estimator, which is common estimator using in parametric multiple regression analysis. Moreover, a combined estimator of variance, VEM, is suggested. In the simulation study it is shown that VEM performs well in practice.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.64-71
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• 2004

The growing need for higher precision and productivity in manufacturing industry has lead to an increased interest in computer numerical control (CNC) systems. It is well known fact that the cross-coupling controller (CCC) is an effective method for contouring applications. In this paper, a multi-axis contour error controller (CEC) based on a contour error vector using parametric curve interpolator is introduced. The contour error vector is a vector from the actual tool position to the nearest point on the desired path. The contour error vector is the closest error model to the contour error. The simulation results show that the CEC is more accurate than the conventional CCC for a biaxial motion system. In addition, the experimental results on 3-axis motion system show that the CEC is simply applied to 3-axis motions and contouring accuracy is significantly improved.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.6
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• pp.152-157
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• 2000

In the control of CNC machine tools, it is significant for precise machining to reduce the contour error. The object of servo-control is reduction of contour error and tracking error. In past studies, there were two approaches to control a servo-system. One was to eliminate axial tracking errors, and the other was to control contour errors. The Cross-coupled controller(CCC) was introduced fro ma veiwpoint of contour error model. Recently, for machining part with free form surfaces, we propose a new contour error model based on curve interpolator. It is presented here that performance of CCC using proposed model is enhanced. Therefore, we can make more precise parts with the curve interpolator and the new contour error model.

• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.45-57
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• 2001

A parametric scheme is proposed for the numerical solution of the nonlinear Boussinesq equation. The numerical method is developed by approximating the time and the space partical derivatives by finite-difference re placements and the nonlinear term by an appropriate linearized scheme. The resulting finite-difference method is analyzed for local truncation error and stability. The results of a number of numerical experiments are given for both the single and the double-soliton wave. AMS Mathematics Subject Classification : 65J15, 47H17, 49D15.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.283-290
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• 1996

The simulation study shows that the rank transform test has relatively superior power advantages over the parametric analysis of variance test in many cases for a $2^3$ factorial design, particularly with heavy-tailed distributions of the error terms. However the rank transform test should be cautiously used when all main effects and interactions related to a testing effect are possibly present at the same time.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.523-532
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• 1997

We propose several estimators of the reliability function R of the two-parameter exponential distribution, and then compare those estimator in terms of the mean square error (MSE) through Monte Carlo method. We also consider the parametric bootstrap estimation. Using the parametric bootstrap estimator, we obtain the bootstrap confidence intervals for reliability function and compare the proposed bootstrap confidence intervals in terms of the length and the coverage probability through Monte Carlo method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.1
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• pp.159-166
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• 1987

A new family of sinusoidal orthogoal trnasform is introduced. For a derivation, a parametric sinusoidal matrix whose transform might be implemented by a suitable FFT algorithm is modeled basically on the analogy of well-known sinusoidal transform such as DCT,SCT, etc., and its orthogonality condition is calculated. The parameters satisfying orthogonality condition are determined, in a sense, by particular solution after trial and error. However more than then transform matrices not yet known are obtained. It is also shown that these transforms can be computed by a DFT. of an image.

• International Journal of Reliability and Applications
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• v.2 no.1
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• pp.49-56
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• 2001

In this paper we consider empirical Bayes estimation of the hazard rate and survival probabilities with right censored data under the assumption that the hazard function is constant over the period of observation and the prior distribution is gamma. We provide an estimator of the first derivative of the prior moment generating function that converges at each point to the true value in $L_2$ and use it to obtain, easy to compute, asymptotically optimal estimators under the squared error loss function.