• 응용통계연구
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• 제25권4호
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• pp.641-650
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• 2012

Spatial time series data can be viewed as a set of time series simultaneously collected at a number of spatial locations. This paper studies Bayesian inferences in a spatial time bilinear model with a Gibbs sampling algorithm to overcome problems in the numerical analysis techniques of a spatial time series model. For illustration, the data set of mumps cases reported from the Korea Center for Disease Control and Prevention monthly over the years 2001~2009 are selected for analysis.

• 대한산업공학회지
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• 제18권1호
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• pp.63-80
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• 1992

The concept of rapid prototyping intended for a significant reduction in cost and lead time becomes even more practical with the recent development of various equipments to make the concept concrete. For the purpose of real application of commercially available SLA(stereolithography apparatus), this paper is intended to develop the standard conversion procedure from CAD data to the input data for SLA. While the procedure presented in this paper is based on CAD system "CATIA" and SLA of 3D systems, Inc., which are being used in authors' company DAEWOO Motor Co., Ltd., the basic concept of this paper can be applied to any other CAD systems and machines of using stereolithography process. The algorithm presented in this paper is classified into two stages-node sampling and triangulation. First of all, point data are sampled through the node sampling procedure, and then these are triangulated so that the input data for SLA operation is finally generated. The suggested method is devised in a way to meet the input requirements of SLA and more importantly consume less computation time and generate less number of input data for SLA.

• 응용통계연구
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• 제25권6호
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• pp.999-1008
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• 2012

A Bayesian multiple change-point model for small data is proposed for multivariate means and is an extension of the univariate case of Cheon and Yu (2012). The proposed model requires data from a multivariate noncentral $t$-distribution and conjugate priors for the distributional parameters. We apply the Metropolis-Hastings-within-Gibbs Sampling algorithm to the proposed model to detecte multiple change-points. The performance of our proposed algorithm has been investigated on simulated and real dataset, Hanwoo fat content bivariate data.

• 한국응용곤충학회지
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• 제62권4호
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• pp.299-305
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• 2023

담배가루이(Bemisia tabaci)는 광식성 해충으로 토마토황화잎말림바이러스(Tomato Yellow Leaf Curl Virus; TYLCV), 카사바갈색줄무늬병(Cassava Brown Streak Disease; CBSD)를 매개하는 해충이다. 담배가루이 방제를 위해 화학적 방제가 주로 시행되지만 저항성으로 인한 한계로 인해 종합적해충방제를 위한 고정정확도를 이용한 표본조사법(Fixed precision sampling plan)을 개발하였다. 표본추출은 토마토 식물이 50 cm 높이의 레일 위에 위치한 배지를 이용해 재배되고 있어 배지로부터 130 cm 이상(지상에서 180 cm 이상)을 상단, 70 cm~100 cm (지상에서 120 cm~150 cm)를 중단, 50 cm 이하(지상에서 100 cm 이하)를 하단으로 나누어 각 위치별 토마토 7엽의 잎 뒷면에서 관찰된 담배가루이 노숙 유충 마리 수를 조사하였다. 담배가루이 노숙유충은 이동성이 거의 없어 알에서 우화한 뒤 고착화하여 용과 성충 단계를 거치기 때문에 중단, 하단에 밀도가 높았다. 공간분포분석은 Taylor's power law (TPL)를 이용하여 도출된 TPL의 회귀계수를 통해 분석하였고, TPL 계수의 차이는 공분산분석(ANCOVA)하여 차이가 없어 자료를 통합(pooling)하여 계산된 새로운 TPL 계수를 이용하여 표본추출정지선과 방제의사결정법을 개발하였다. 개발된 표본추출법의 적합성을 판단하기 위해 분석에 사용하지 않은 독립된 자료를 이용하여 Resampling Validation for Sampling Plan (RVSP) 프로그램으로 평가하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.65-67
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• 2008

An adaptive response surface method with Latin Hypercube sampling strategy is employed to optimize a magnet pole shape of large scale BLDC motor to minimize the cogging torque. The proposed algorithm consists of the multi-objective Pareto optimization and ($1+{\lambda}$) evolution strategy to find the global optimal points with relatively fewer sampling data. In the adaptive RSM, an adaptive sampling point insertion method is developed utilizing the design sensitivities computed by using finite element method to set a reasonable response surface with a relatively small number of sampling points. The developed algorithm is applied to the shape optimization of PM poles for 6MW BLDC motor.

• 대한의용생체공학회:의공학회지
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• 제16권3호
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• pp.279-288
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• 1995

Ultrasonic Doppler systems for the purpose of estimating blood flow velocity, blood flow volume, and flow imaging are commonly used due to advantages of non-invasive and real time observation. Specially, the technical developments of color flow mapping (2-D Doppler) systems have made a relatively rapid progress. However, the 2-D Doppler systems have several problems, such as the range ambiguity, low signal to noise ratio, and slow frame rate. The slow frame rate problem is resolved by using the spatial average which is a method to acquire more data samples for mean frequency estimation. In this paper, spatial average method using the 2nd order sampling instead of quadrature sampling is proposed. The experimental results show that the proposed methods have good performance and easy application to the color flow mapping system.

• 품질경영학회지
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• 제21권2호
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• pp.71-84
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• 1993

Currently the problem of air pollution caused by the motor vehicle emission is one of the most serious problems to be solved. Thus we needed the vehicle emissions audit procedure and technical innovation constraining the motor vehicle emission. The Korean Environmental Protection Agency currently audits automobiles for emissions compliance at assembly plants with multiple attribute multiple staged sampling plans. In order to establish the more reasonable audit procedure, the multiple staged sampling plan designed in this paper has been applied to the domestic vehicles by analyzing the statistic characteristics of the emission distribution. This paper summarizes the auditing procedure and develops methods for determining its statistical characteristics. Specifically, we consider how to evaluate a multiple staged sampling plan, give a procedure that efficiently estimates attribute-type probabilities from multivariate variables-type data, and quantify the effect of tightening the acceptable quality level of the sampling plan. As a result it can be proved that this audit procedure is the reasonable plan minimizing the AQL (Acceptable Quality Level) and is to be used effectively for the auditing procedure constraining the injurious gasses of the motor vehicles.

• Journal of the Korean Statistical Society
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• 제23권2호
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• pp.421-444
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• 1994

Reliability acceptance sampling is concerned with whether to accept or reject a collection of items based upon the information obtained from life testing. Although various reliability acceptance sampling plans have been developed, little is known about their relatvie performances. This paper compares reliability acceptance sampling plans under Type II censoring, Hybrid censoring, and Time-Truncated Type II censoring assuming that the lifetimes of items in a lot follow an exponential distribution. The three plans are compared in terms of the power, the expected number of failures, and the expected time required to reach a decision. Computational experiments are conducted and the results are tabulated to provide guidelines for selecting an appropriate plan for a given situation.

• Journal of the Korean Statistical Society
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• 제35권2호
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• pp.157-166
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• 2006

This research proposes an efficient Monte Carlo algorithm for computing error probability in high performance digital communication st stems. It characterizes special features of the problem and suggests an importance sampling algorithm specially designed to handle the problem. It uses a shifted exponential density as the importance sampling density, and shows an adaptive way of choosing the rate and the origin of the shifted exponential density. Instead of equal allocation, an intelligent allocation of the samples is proposed so that more samples are allocated to more important part of the error probability. The algorithm uses the nested feature of the error space and avoids redundancy in estimating the probability. The algorithm is applied to an example data set and shows a great improvement in accuracy of the error probability estimation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.701-702
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• 2008

An adaptive response surface method with Latin Hypercube sampling strategy is employed to optimize a magnet pole shape of large scale BLDC motor to minimize the cogging torque. The proposed algorithm consists of the multi-objective Pareto optimization and (1+${\lambda}$) evolution strategy to find the global optimal points with relatively fewer sampling data. In the adaptive RSM, an adaptive sampling point insertion method is developed utilizing the design sensitivities computed by using finite element method to get a reasonable response surface with a relatively small number of sampling points. The developed algorithm is applied to the shape optimization of PM poles for 6 MW BLDC motor, and the cogging torque is reduced to 19% of the initial one.