• 대한기계학회논문집
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• 제17권1호
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• pp.46-50
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• 1993

본 연구에서는 실제의 하중에서 관찰되는 경우가 많고, 또한, 이론적 취급이 용이한 협대역(narrow band)파형을 대상으로 했으니, 다른 파형의 경우도 대략적인 경 향은 파악할 수 있으리라 생가되며 극치의 확률분포만 주어지면 본 수법과 마찬가지로 동일하게 적용할 수 있다.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제54권11호
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• pp.547-552
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• 2005

This paper describes a pseudo-random carrier PW technique for the power converters. The proposed method generates a new pseudo-random carrier by randomly composing a carrier with fixed frequency and a carrier with opposition phase. To confirm the validity of the proposed method, a single-phase multi-level inverter was implemented and tested. The experimental results show that the output voltage and current harmonics spectra of an inverter have broadening effect of harmonics, as only simple composition of fixed frequency carries.

• Communications for Statistical Applications and Methods
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• 제21권2호
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• pp.169-181
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• 2014

Marginalized random effects models (MREM) are commonly used to analyze longitudinal categorical data when the population-averaged effects is of interest. In these models, random effects are used to explain both subject and time variations. The estimation of the random effects covariance matrix is not simple in MREM because of the high dimension and the positive definiteness. A relatively simple structure for the correlation is assumed such as a homogeneous AR(1) structure; however, it is too strong of an assumption. In consequence, the estimates of the fixed effects can be biased. To avoid this problem, we introduce one approach to explain a heterogenous random effects covariance matrix using a modified Cholesky decomposition. The approach results in parameters that can be easily modeled without concern that the resulting estimator will not be positive definite. The interpretation of the parameters is sensible. We analyze metabolic syndrome data from a Korean Genomic Epidemiology Study using this method.

• ETRI Journal
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• 제38권1호
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• pp.141-148
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• 2016

This paper proposes a method to estimate directly the incoherent scattered intensity and radar cross section (RCS) from the effective permittivity of a random media. The proposed method is derived from the original concept of incoherent scattering. The incoherent scattered field is expressed as a simple formula. Therefore, to reduce computation time, the proposed method can estimate the incoherent scattered intensity and RCS of a random media. To verify the potential of the proposed method for the desired applications, we conducted a Monte-Carlo analysis using the method of moments; we characterized the accuracy of the proposed method using the normalized mean square error (NMSE). In addition, several medium parameters, such as the density of scatterers and analysis volume, were studied to understand their effect on the scattering characteristics of a random media. The results of the Monte-Carlo analysis show good agreement with those of the proposed method, and the NMSE values of the proposed method and Monte-Carlo analysis are relatively small at less than 0.05.

• Structural Engineering and Mechanics
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• 제3권3호
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• pp.273-287
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• 1995

Stochastic response of systems to random excitation can be estimated by direct integration methods in the time domain such as the stochastic central difference method (SCDM). In this paper, the SCDM is applied to compute the variance and covariance in response of linear and nonlinear structures subjected to random excitation. The accuracy of the SCDM is assessed using two-DOF systems with both deterministic and random material properties excited by white noise. For the former case, closed-form solutions can be obtained. Numerical results also are presented for a simply supported geometrically nonlinear beam. The stiffness of this beam is modeled as a random field, and the beam is idealized by the stochastic finite element method. A perturbation technique is applied to formulate the equations of motion of the system, and the dynamic structural response statistics are obtained in a time domain analysis. The effect of variations in structural parameters and the numerical stability of the SCDM also are examined.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1995년도 추계학술대회발표논문집; 서울대학교, 서울; 30 Sep. 1995
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• pp.88-97
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• 1995

This paper provides equation for computing the AOQ of an unreliable random FMS. The FMS is described using open central server model with network GI/G/S Queues. And the equation for AOQ is simplified due to computational complexities. Numerical example is used to show the effect of AOQ according to inspection location, reliability of equipment in an FMS, and the effect of difference of routing probability is compared after finding the AOQL of each machine center.

• Journal of the Korean Statistical Society
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• 제18권2호
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• pp.118-124
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• 1989

In the one-way random effect model, we often estimate the variance components by the ANOVA method and then estimate the population mean. Whe there are only two distint group sizes, the conventional mean estimator is represented as a weighted average of two normal means with weights being the function of variance component estimators. In this paper, we will study a method which can compute the exact variance of the mean estimator when we set the negative variance component estimate to zero.

• 산업경영시스템학회지
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• 제19권37호
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• pp.179-186
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• 1996

This paper provides equations for computing the AOQ of an unreliable random FMS. The FMS is described using an open central server model of GI/G/S Queues. The equation for AOQ is simplified due to computational complexities. A Numerical example is used to show the effect of AOQ according to inspection location, reliability of equipment in an FMS. The effect of difference in routing probability is compared after finding the AOQL of each machine center.

• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.29-37
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• 2001

In this paper, we consider the second order probability matching criterion for the ratio of the variance components under the one-way random effect model. It turns out that among all of the reference priors given in Ye(1994), the only one reference prior satisfies the second order matching criterion. Similar results are also obtained for the intraclass correlation as well.

• Journal of the Korean Data and Information Science Society
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• 제15권3호
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• pp.645-654
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• 2004

In this paper, we develop the Bayesian test procedure for the intraclass correlation coefficient in the unbalanced one-way random effect model based on the reference priors. That is, the objective is to compare two nested model such as the independent and intraclass models using the factional Bayes factor. Thus the model comparison problem in this case amounts to testing the hypotheses $H_1:\rho=0$ versus $H_2:{\rho}{\neq}0$. Some real data examples are provided.