• Communications for Statistical Applications and Methods
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• 제3권1호
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• pp.87-99
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• 1996

We construct bootstrap confidence intervals for reliability, R= P{X>Y}, where X and Y are independent normal random variables. One way ANOVA random effect models are assumed for the populations of X and Y, where standard deviations $\sigma_{x}$ and $\sigma_{y}$ are unequal. We investigate the accuracy of the proposed bootstrap confidence intervals and classical confidence intervals work better than classical confidence interval for small sample and/or large value of R.

• Journal of the Korean Statistical Society
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• 제26권2호
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• pp.231-243
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• 1997

In this paper we investigate weak convergence of the intergral processes whose index set is the non-compact infinite time interval. Our first goal is to develop the empirical central limit theorem as random elements of [0, .infty.) for an integral process which is constructed from iid variables. In developing the weak convergence as random elements of D[0, .infty.), we will use a result of Ossiander(4) whose proof heavily depends on the total boundedness of the index set. Our next goal is to establish the empirical central limit theorem for the Kaplan-Meier integral process as random elements of D[0, .infty.). In achieving the the goal, we will use the above iid result, a representation of State(6) on the Kaplan-Meier integral, and a lemma on the uniform order of convergence. The first result, in some sense, generalizes the result of empirical central limit therem of Pollard(5) where the process is regarded as random elements of D[-.infty., .infty.] and the sample paths of limiting Gaussian process may jump. The second result generalizes the first result to random censorship model. The later also generalizes one dimensional central limit theorem of Stute(6) to a process version. These results may be used in the nonparametric statistical inference.

• Communications for Statistical Applications and Methods
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• 제22권6호
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• pp.599-604
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• 2015

Kendall's tau statistic has been applied to test an association of bivariate random variables. However, incomplete bivariate data with a truncation and a censoring results in incomparable or unorderable pairs. With such a partial information, Tsai (1990) suggested a conditional tau statistic and a test procedure for a quasi independence that was extended to more diverse cases such as double truncation and a semi-competing risk data. In this paper, we also employed a conditional tau statistic to estimate an association of bivariate interval censored data. The suggested method shows a better result in simulation studies than Betensky and Finkelstein's multiple imputation method except a case in cases with strong associations. The association of incubation time and infection time from an AIDS cohort study is estimated as a real data example.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 정기총회 및 창립40주년기념 학술대회 학회본부
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• pp.106-108
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• 1987

Until now, inflow has been handled an independent log-normal random variable in the problem of planning the long-term operation of a multi-reservoir hydrothermal electric power generation system. This paper introduces the detail study for making rule curve by applying weekly time interval for handling inflows. The hydro system model consists of a set of reservoirs and ponds. Thermal units are modeld by one equivalent thermal unit. Objective is minimizing the total cost that the summation of the fuel cost of equivalent thermal unit at each time interval. For optimization, stochastic dynamic programming(SDP) algorithm using successive approximations is used.

• 반도체디스플레이기술학회지
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• 제18권3호
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• pp.1-6
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• 2019

Foreground/background segmentation in video sequences is often one of the first tasks in machine vision applications, making it a critical part of the system. In this paper, we present an improved sample-based technique that provides robust background image as well as segmentation mask. The conventional multiple interval sampling (MIS) algorithm have suffer from the unbalance of computation time per frame and the rapid change of confidence factor of background pixel. To balance the computation amount, a random-based pixel update scheme is proposed and a spatial and temporal smoothing technique is adopted to increase reliability of the confidence factor. The proposed method allows the sampling queue to have more dispersed data in time and space, and provides more continuous and reliable confidence factor. Experimental results revealed that our method works well to estimate stable background image and the foreground mask.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.743-752
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• 2004

In this paper, we develop the Bayesian model selection procedure using the reference prior for comparing two nested model such as the independent and intraclass models using the distance or divergence between the two as the basis of comparison. A suitable criterion for this is the power divergence measure as introduced by Cressie and Read(1984). Such a measure includes the Kullback -Liebler divergence measures and the Hellinger divergence measure as special cases. For this problem, the power divergence measure turns out to be a function solely of $\rho$, the intraclass correlation coefficient. Also, this function is convex, and the minimum is attained at $\rho=0$. We use reference prior for $\rho$. Due to the duality between hypothesis tests and set estimation, the hypothesis testing problem can also be solved by solving a corresponding set estimation problem. The present paper develops Bayesian method based on the Kullback-Liebler and Hellinger divergence measures, rejecting $H_0:\rho=0$ when the specified divergence measure exceeds some number d. This number d is so chosen that the resulting credible interval for the divergence measure has specified coverage probability $1-{\alpha}$. The length of such an interval is compared with the equal two-tailed credible interval and the HPD credible interval for $\rho$ with the same coverage probability which can also be inverted into acceptance regions of $H_0:\rho=0$. Example is considered where the HPD interval based on the one-at- a-time reference prior turns out to be the shortest credible interval having the same coverage probability.

• 응용통계연구
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• 제23권3호
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• pp.521-531
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• 2010

구간중도절단은 중도절단의 가장 일반적인 개념으로 구간중도절단자료는 의학 및 역학분야의 연구에서 흔히 관찰된다. 본 연구에서는 구간중도절단의 상황에서 생존함수와 중간생존시간을 추정하는 방법으로 평균대치법과 자기일치법을 비교 연구하고, 실제 자료로 혈우병환자에서 선천성면역결핍바이러스 감염시점을 추정하였다. 또한 구간중도절단자료를 생성하는 새로운 방법을 제시하였으며, 생성된 구간중도절단자료를 이용한 모의실험을 통하여 두 추정치에 대한 다양한 비교연구를 시행하였다. 구간중도절단자료에서 생존함수와 중간생존시간을 추정할 경우 중도절단율이 크지 않다면 평균대치법이 자기일치법보다 더 우수한 추정치로 판명되었다.

• 한국통신학회논문지
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• 제27권8C호
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• pp.758-770
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• 2002

본 논문은 Diffserv 방식의 Assured Service에 대한 QoS를 보장하고 서비스 수용 용량을 최대화 시킬 수 있는 자원 할당 방안을 제안하고, RIO 및 Adaptive RIO 버퍼 관리 방식을 적용하여 성능을 분석한다. Adaptive RIO 방식은 네트워크 토폴로지와 Assured Service 서브 클래스별로 할당되는 대역폭의 비율에 따라 결정되는 버퍼 크기를 기준으로 일정 시간 구간마다 도착 가능한 In-profile 패킷과 전체 패킷의 최대량을 고려하여 RIO 방식의 변수 값들을 재설정함으로써 접속제어가 수행된 상황 하에서 허용된 In-profile 패킷에 대한 Early Random Drop을 방지할 수 있다. 시뮬레이션 결과는 제안하는 자원 할당 방안 및 Adaptive RIO 방식을 적용하여 Assured Service 에 대한 QoS를 보장할 수 있고 서비스 수용 용량을 최대화 시킬 수 있음을 보인다.

• 한국통신학회논문지
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• 제27권6C호
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• pp.581-593
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• 2002

본 논문은 DiffServ 방식의 Assured Service를 이용하는 플로에게 QoS를 보장하기 위해 Admission Control이 수행된 상황 하에서 발생하는 RIO 방식의 문제점을 제시하고 이에 대한 해결 방안으로 Adaptive RIO 방식을 제안한다. 제안하는 Adaptive RIO 방식은 네트워크 토폴로지와 Assured Service 서브 클래스별로 할당되는 대역폭의 비율에 따라 결정되는 버퍼 크기를 기준으로 일정 시간 구간마다 도착 가능한 In-profile 패킷과 전체 패킷의 최대량을 고려하여 RIO의 변수 값들을 재설정함으로써 허용된 In-profile 패킷에 대한 확률적인 폐기 (Early Random Drop)를 방지한다. 시뮬레이션 결과는 Assured Service에 대해 Admission Control이 수행된 상황과 Congestion 상황에서 제안하는 Adaptive RIO 방식이 RIO 방식보다 In-profile 트래픽에 대한 보호와 수율 성능이 우수함을 보인다.

• Journal of Biosystems Engineering
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• 제24권2호
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• pp.145-152
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• 1999

Methods of discharging each graded agricultural product are divided into two according to the type of feeding. One is based on feeding objects using a series of specially designed holders mounted with an equal interval. The other is randomly feeding objects while being isolated without a specific interval. In this paper, a real time simultaneous discharge algorithm, which is good for objects randomly fed individually and for multi-objects located along a series of discharge buckets, was developed. And the developed algorithm was implemented to the controller and the performance was verified using the system developed for dried mushrooms. The discharge system used for the experiment was composed of a variable speed conveyor, a series of double channel bucket mounted along both sides of the conveyor, and a series of air nozzles and optic sensors. Developed algorithm worked perfectly and could be directly used for automatic discharge system for randomly feeding agricultural products.