• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.57.1-57.1
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• 2013

We investigate the method to measure both the present value of the matter energy density contrast and the Hubble parameter directly from the measurement of the linear growth rate which is obtained from the large scale structure of the Universe. From this method, one can obtain the value of the nuisance cosmological parameter $\Omo$ (the present value of the matter energy density contrast) within 3% error if the growth rate measurement can be reached $z >3.5$. One can also investigate the evolution of the Hubble parameter without any prior on the value of $H_0$ (the current value of the Hubble parameter). Especially, estimating the Hubble parameter are insensitive to the errors on the measurement of the normalized growth rate $f \sigma_8$. However, this method requires the high $z$ ($z >3.5$) measurement of the growth rate in order to get the less than 5% errors on the measurements of $H(z)$ at $z \leq 1.2$ with the redshift bin $\Delta z = 0.2$. Thus, this will be suitable for the next generation large scale structure galaxy surveys like WFMOS and LSST.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.3
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• pp.62-67
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• 2003

The grinding force generated during the grinding process causes an elastic deformation of the workpiece, grinding wheel, and machine system. Thus, the true depth of cut is always smaller than the apparent depth of cut. This is known as machining elasticity phenomenon. The machining elasticity parameter is defined as a ratio between the true depth of cut and the apparent depth of cut. It is an important factor to understand the material removal mechanism of the grinding process. To increase productivity, the value of this machining elasticity parameter must be large. Therefore, it is essential to know the characteristics of this parameter. The objective of this research is to study the effect of the major grinding conditions, such as table speed, depth of cut, on this parameter experimentally, Through this research, it is found that this parameter value is increasing when the table speed is decreasing or the depth of cut is increasing. Also, this parameter value depends on the grinding mode (up grinding, down grinding).

• The Journal of Society for e-Business Studies
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• v.7 no.1
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• pp.107-127
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• 2002

Database system parameter tuning is one of database system tuning that achieve to improve performance of database system with application program tuning and data model tuning. By parameter tuning adjusts value of entry that is staled in data dictionary's parameter file that is included to database system, it is thing which make relevant database system can display performance of most suitable. And, it is that achievement is one o( possible tuning method immediately without occurrence of additional expense or involved hardware for database system performance elevation and ashes composition of software. But, it is actuality that administration about parameter practical use is not achieved, and is using Default Value of parameter that database management system offers just as it is systematically. So, this paper presents parameter tuning process that can ：achieve Parameter tuning of database system that is operating present systematically, and parameter tuning process each activity important input urea and tuning achievement product. And explain about effect and result that happen by sort database system performance and parameters that it is affinity systematically, and grasp relationships between parameter, and change parameter of string database system. And not that parameter uses contents that specify by fixing when establish database administration system, is going to emphasize and explain that must utilize changing continuously during database system operation. It changes parameter entry value how in various kinds different operation environment and present if must apply, and will arrange effect that this parameter enoy value alteration gets in performance liking into account point that is actuality that is using parameter that define database administrators when install the database system just as it is continually without alteration.

• Communications of the Korean Mathematical Society
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• v.38 no.1
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• pp.299-318
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• 2023

This article devises an exponentially fitted method for the numerical solution of two parameter singularly perturbed parabolic boundary value problems. The proposed scheme is able to resolve the two lateral boundary layers of the solution. Error estimates show that the constructed scheme is parameter-uniformly convergent with a quadratic numerical rate of convergence. Some numerical test examples are taken from recently published articles to confirm the theoretical results and demonstrate a good performance of the current scheme.

• Journal of the Korean Statistical Society
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• v.35 no.1
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• pp.91-103
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• 2006

Yun (2005) introduced an estimator of the second order parameter characterizing the tail behavior of probability distributions and proved its consistency. In this paper we prove its asymptotic normality under a third order condition.

• East Asian mathematical journal
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• v.32 no.5
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• pp.621-633
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• 2016

We establish the existence of positive solutions to nonlocal boundary value problems with integral boundary condition and non-negative real boundary parameter by mainly using the Schauder-Fixed point theorem.

• Journal of the Korean Statistical Society
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• v.34 no.4
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• pp.273-280
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• 2005

In this paper we introduce an estimator of the second order parameter characterizing the tail behavior of probability distributions and prove its consistency.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.8
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• pp.26-32
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• 1998

The grinding force generated during the grinding process causes an elastic deformation of the workpiece, grinding wheel, and machine system. Thus, the true depth of cut is always smaller than the apparent depth of cut. This is known as machining elasticity phenomenon. The machining elasticity parameter is defined as a ratio between the true depth of cut and the apparent depth of cut. It is an important factor to understand the material removal mechanism of the grinding process. To increase productivity, the value of this machining elasticity parameter must be large. Therefore, it is essential to know the characteristics of this parameter. The objective of this research is to study the effect of the major grinding conditions, such as table speed and depth of cut, on this parameter experimentally. Through this research, it is found that this parameter value is increasing when the table speed is decreasing or the depth of cut is increasing. Also, this parameter value depends on the grinding mode (up grinding, down grinding).

• Structural Engineering and Mechanics
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• v.22 no.4
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• pp.401-418
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• 2006

Solutions to the problems of structural parameter estimation from modal response using leastsquares minimization of force or displacement residuals are generally sensitive to noise in the response measurements. The sensitivity of the parameter estimates is governed by the physical characteristics of the structure and certain features of the noisy measurements. It has been shown that the regularization method can be used to reduce effects of the measurement noise on the estimation error through adding a regularization function to the parameter estimation objective function. In this paper, we adopt the regularization function as the Euclidean norm of the difference between the values of the currently estimated parameters and the a priori parameter estimates. The effect of the regularization function on the outcome of parameter estimation is determined by a regularization factor. Based on a singular value decomposition of the sensitivity matrix of the structural response, it is shown that the optimal regularization factor is obtained by using the maximum singular value of the sensitivity matrix. This selection exhibits the condition where the effect of the a priori estimates on the solutions to the parameter estimation problem is minimal. The performance of the proposed algorithm is investigated in comparison with certain algorithms selected from the literature by using a numerical example.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.463-477
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• 2009

Parameter estimation methods such as maximum likelihood estimation method, probability weighted moments method, regression method have been popularly applied to various extreme value models in numerous literature. Among three methods above, the performance of regression method has not been rigorously investigated yet. In this paper the regression method is compared with the other methods via Monte Carlo simulation studies for estimation of parameters of the Generalized Extreme Value(GEV) distribution and the Generalized Pareto(GP) distribution. Our simulation results indicate that the regression method tends to outperform other methods under small samples by providing smaller biases and root mean square errors for estimation of location parameter of the GEV model. For the scale parameter estimation of the GP model under small samples, the regression method tends to report smaller biases than the other methods. The regression method tends to be superior to other methods for the shape parameter estimation of the GEV model and GP model when the shape parameter is -0.4 under small and moderately large samples.