• 천문학회보
• /
• 제41권2호
• /
• pp.35.3-36
• /
• 2016

Density and velocity perturbations in scales most relevant for the first galaxy formation are strongly affected by large-scale density perturbations, velocity-divergence perturbations and the baryon-cold dark matter (CDM) streaming velocities. Even at redshifts as high as z~200, this mode-mode coupling imprints a significant impact on the small-scale perturbations, at the wavenumber k >${\sim}100Mpc^{-1}$, as was calculated in our recent work. This implies that cosmological initial conditions based on the usual linear theory is no longer valid in these scales. We present a new cosmological initial condition generator, BCCOMICS, which generates initial conditions for the cold dark matter (CDM) and baryons in scales most relevant for the first galaxy formation. BCCOMICS is based on the linear perturbation theory including the mode-mode coupling terms, and generates cosmological initial conditions for the SPH-basded code GADGET and the AMR-based code ENZO. We also present our preliminary result on the cosmic variance of the first galaxy formation, studied by using BCCOMICS.

• Journal of the Korean Data and Information Science Society
• /
• 제14권3호
• /
• pp.673-685
• /
• 2003

In this paper we consider the problem of identifying and testing outliers in linear regression. First we consider the problem for testing the null hypothesis of no outliers. A test based on the ratio of two residual scale estimates is proposed. We show the asymptotic distribution of the test statistics by Monte Carlo simulation and investigate its properties. Next we consider the problem of identifying the outliers. A forward sequential procedure using the suggested test is proposed and shown to perform fairly well. Unlike other forward procedures, the present one is unaffected by masking and swamping effects because the test statistic is based on robust scale estimate.

• Journal of the Korean Data and Information Science Society
• /
• 제21권3호
• /
• pp.555-560
• /
• 2010

One-dimensional approach to two-dimensional warranty data involves modeling us- age as a function of time. Iskandar (1993) suggests a simple linear model for usage. However, simple linear form of intensity function is of limited value to model the situa-tion where the intensity varies over time. In this study Weibull intensity is considered where the scale parameter is expressed in terms of different models. We will nd out how each parameter in the model a ects the warranty cost and which model gives a bigger number of failures within the two-dimensional warranty region.

• Journal of the Korean Data and Information Science Society
• /
• 제16권4호
• /
• pp.1053-1066
• /
• 2005

In this paper we consider the problem of identifying and testing outliers in linear regression. First we consider the use of the so-called scale ratio tests for testing the null hypothesis of no outliers. This test is based on the ratio of two residual scale estimates. We show the asymptotic distribution of the test statistics and investigate its properties. Next we consider the problem of identifying the outliers. A forward sequential procedure using the suggested test is proposed. The new method is compared with classical procedure in the real data example. Unlike other forward procedures, the present one is unaffected by masking and swamping effects because the test statistic is based on robust scale estimate.

• Journal of Electrical Engineering and Technology
• /
• 제11권3호
• /
• pp.724-732
• /
• 2016

In this paper, a sampled-data observer-based decentralized fuzzy control technique is proposed for a class of nonlinear large-scale systems, which can be represented to a Takagi-Sugeno fuzzy system. The premise variable is assumed to be measurable for the design of the observer-based fuzzy controller, and the closed-loop system is obtained. Based on an exact discretized model of the closed-loop system, the stability condition is derived for the closed-loop system. Also, the stability condition is converted into the linear matrix inequality (LMI) format. Finally, an example is provided to verify the effectiveness of the proposed techniques.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 1997년도 가을 학술발표회 논문집
• /
• pp.16-23
• /
• 1997

The Reproducing Kernel Particle Method (RKPM), one of the popular meshless methods, is developed and applied to stress concentration problems. Since the meshless methods require only a set of particles (or nodes) and the description of boundaries in their formulation, the adaptivity can be implemented with much more ease than finite element method. In addition, due to its intrinsic property of multiresolution, the shape function of RKPM provides us a new criterion for adaptivity. Recently, this multiple scale Reproducing Kernel Particle Method and its adaptive procedure have been formulated for large deformation problems by the authors. They are also under development for damage materials and localization problems. In this paper the multiple scale RKPM for linear elasticity is presented and the adaptive procedure is applied to stress concentration problems. Therefore, this work may be regarded as the edition of linear elasticity in the complete framework of multiple scale RKPM and the associated adaptivity.

• Communications for Statistical Applications and Methods
• /
• 제26권2호
• /
• pp.91-102
• /
• 2019

In this paper, we propose a new estimation method based on a weighted linear regression framework to obtain some estimators for unknown parameters in a two-parameter Rayleigh distribution under a progressive Type-II censoring scheme. We also provide unbiased estimators of the location parameter and scale parameter which have a nuisance parameter, and an estimator based on a pivotal quantity which does not depend on the other parameter. The proposed weighted least square estimator (WLSE) of the location parameter is not dependent on the scale parameter. In addition, the WLSE of the scale parameter is not dependent on the location parameter. The results are compared with the maximum likelihood method and pivot-based estimation method. The assessments and comparisons are done using Monte Carlo simulations and real data analysis. The simulation results show that the estimators ${\hat{\mu}}_u({\hat{\theta}}_p)$ and ${\hat{\theta}}_p({\hat{\mu}}_u)$ are superior to the other estimators in terms of the mean squared error (MSE) and bias.

• 대한수학회논문집
• /
• 제18권3호
• /
• pp.559-568
• /
• 2003

We introduce the notion of two-scale convergence for partial differential equations with random coefficients that gives a very efficient way of finding homogenized differential equations with random coefficients. For an application, we find the homogenized matrices for linear second order elliptic equations with random coefficients. We suggest a natural way of finding the two-scale limit of second order equations by considering the flux term.

• 제어로봇시스템학회논문지
• /
• 제5권2호
• /
• pp.139-144
• /
• 1999

The present paper is concerned with the robust decentralized stabilization problem of large-scale systems with time delays in the interconnections using sliding mode control. Based on Lyapunov stability theorem and H$_{\infty}$ theory, an existence condition of the sliding mode and a robust decentralized sliding mode controller are newly derived for large-scale systems under mismatched uncertainties. Finally, a numerical example is given to verify the validity of the results developed in this paper.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2010년도 춘계학술대회 논문집
• /
• pp.813-814
• /
• 2010