• 응용통계연구
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• 제27권6호
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• pp.1069-1076
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• 2014

기후 온난화의 한 현상으로 받아들여지는 집중호우로 인한 관심이 늘어난 만큼 강우량에 대한 예측 모형이 필요하다. 이러 환경 문제를 다룰 때, 모형을 설정하는 방법 중에 하나로 일반화 파레토 모형을 활용하는 연구가 이루어지고 있다. 본 논문에서는 서울특별시에 대한 1973년부터 2011년까지 매 7월 일별강우량 자료를 가지고 일반화 파레토 모형을 사용하여 강우량의 임계값(70mm) 이상의 분포가 어떻게 되는지 연구한다. 모수의 사전분포는 감마분포랑 역감마분포를 정의하고, 또는 제프리의 정보가 없는 사전분포를 두고, 깁스 표본방법을 통해 베이지안 사후예측분포를 구하고 얻어진 결과를 비교해 본다.

• 대한산업공학회지
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• 제16권2호
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• pp.135-147
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• 1990

A nuclear power plant can be viewed as a large complex man-machine system where high system reliability is obtained by ensuring that sub-systems are designed to operate at a very high level of performance. The chance of severe accident involving at least partial core-melt is very low but once it happens the consequence is very catastrophic. The prediction of risk in low probability, high-risk incidents must be examined in the contest of general engineering knowledge and operational experience. Engineering knowledge forms part of the prior information that must be quantified and then updated by statistical evidence gathered from operational experience. Recently, Bayesian procedures have been used to estimate rate of accident and to predict future risks. The Bayesian procedure has advantages in that it efficiently incorporates experts opinions and, if properly applied, it adaptively updates the model parameters such as the rate or probability of accidents. But at the same time it has the disadvantages of computational complexity. The predictive distribution for the time to next incident can not always be expected to end up with a nice closed form even with conjugate priors. Thus we often encounter a numerical integration problem with high dimensions to obtain a predictive distribution, which is practically unsolvable for a model that involves many parameters. In order to circumvent this difficulty, we propose a method of approximation that essentially breaks down a problem involving many integrations into several repetitive steps so that each step involves only a small number of integrations.

• 응용통계연구
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• 제13권2호
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• pp.427-436
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• 2000

이 논문에서는 신뢰수명자료의 분석에 많이 사용되는 지수분포, 와이블분포, 로그정규분포에 대해, 현재의 자료가 어느 분포에 가장 적합한가를 알아보기 위한 베이자안 모형 선택방법을 제안한다. 일반적으로, 모수에 대한 사전분포가 부적절 분포인 경우, 베이즈 요인(Bayes factor)은 미지의 상수를 포함한다. 이러한 문제점을 해결하기 위하여 O’Hagan(1995)에 의해 제안된 fractional Bayes factor를 이용하여 자료를 가장 적합시키는 모형을 찾는다. 특히, 제2종 중도절단자료가 주어진 경우. 이 자료를 이용한 베이지안 모형선택에 대한 연구는 거의 이루어진 바가 없다. 실제 자료와 인위적인 자료를 이용하여 로그정규분포, 지수분포, 와이블모형중 어느 모형에 가장 잘 적합한지를 검정하는 예를 보인다.

• The Journal of Asian Finance, Economics and Business
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• 제7권9호
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• pp.229-239
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• 2020

This paper examines the impact of gender on access to debt finance among Vietnamese enterprises. The paper investigates data and variables retrieved from the World Bank Enterprise Survey dataset using five Probit models. The regression results suggest that there exist more unfavourable debt financing conditions for women-led firms (WLF), measured as a lower probability of having loan applications fully approved. Firm's age, working sector, and perception of access to finance as a difficulty are found to have explanatory power on the discrimination. More importantly, the perception of debt finance as a difficulty or firms' level of confidence significantly explains the variance of the dependent variable of probability of loan approval, or gender effect would be more pronounced if the firm already has a low level of confidence. The paper also contributes in testing for the gender effect on Vietnamese enterprises from different sectors and scale, unlike other prior research papers focusing on specific sectors and/or small and medium enterprises only. The findings are highly useful for Vietnamese credit institutions to set out a specific business policy to attract more WLFs and help promoting gender equality in the working environment, especially in debt financing, which is often neglected in existing regulation and policy frameworks.

• International Journal of Naval Architecture and Ocean Engineering
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• 제3권1호
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• pp.80-85
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• 2011

For the assessment of statistical characteristics of wave loads in the real sea state, the probability distribution of wave loads are computed based on the sufficient duration of computations in irregular waves. First of all, the estimation of wave impact loads is well modified applying the displacement potential formulation, which was proposed by one of authors, for solving Wagner's flow model. Consequently, the present computation method is also modified. Prior to the computation in irregular waves, preliminary computation to determine the adequate number of realization of irregular waves is examined. The effect of hull girder vibration on the statistical characteristics is examined by means of the computation with/without hull girder vibration. It is found that hull girder vibration has a certain effect on the probability of occurrence of wave loads. Furthermore, computations taking account of the effect of operation, that is the effects of ship speed and course change, is conducted for the rational evaluation of the effects of hull girder vibration. It is clarified that the effect of operation on the statistical characteristics of wave loads is significant. It is verified that the evaluation without the effect of operation may overestimate the effect of hull girder vibration.

• Journal of Communications and Networks
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• 제15권3호
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• pp.283-291
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• 2013

In this paper, we propose new multiuser detectors (MUDs) based on compressed sensing approaches for the large-scale multiple antenna systems equipped with dozens of low-power antennas. We consider the scenarios where the number of receiver antennas is smaller than the total number of users, but the number of active users is relatively small. This prior information motivates sparsity-embracing MUDs such as sparsity-embracing linear/nonlinear MUDs where the detection of active users and their symbol detection are employed. In addition, sparsity-embracing MUDs with maximum a posteriori probability criterion (MAP-MUDs) are presented. They jointly detect active users and their symbols by exploiting the probability of user activity, and it can be solved efficiently by introducing convex relaxing senses. Furthermore, it is shown that sparsity-embracing MUDs exploiting common users' activity across multiple symbols, i.e., frame-by-frame, can be considered to improve performance. Also, in multiple multiple-input and multiple-output networks with aggressive frequency reuse, we propose the interference cancellation strategy for the proposed sparsity-embracing MUDs. That first cancels out the interference induced by adjacent networks and then recovers the desired users' information by exploiting the low user activity. In simulation studies for binary phase shift keying modulation, numerical evidences establish the effectiveness of our proposed MUDs exploiting low user activity, as compared with the conventional MUD.

• 한국군사과학기술학회지
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• 제17권4호
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• pp.544-550
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• 2014

In this paper, we have proposed a novel method which can analysis the direction finding ambiguity analysis for array geometry in 3 channel and 4 channel multiple baseline direction finding system. Generally, the direction finding ambiguity in the 3 element and 4 element phase interferometer direction finding system is calculated by the simulation for the array spacing or by the probability with the selected antenna array spacing. There are some restrictions to obtain the ambiguity of direction finding system in these methods. The former performs a simulation with every antenna array spacing and the latter calculates the ambiguity with the selected antenna array spacing. To overcome those restrictions, This paper proposed the novel method to calculate the ambiguity using the imaginary antenna array spacing and the phase difference prior to the modular operation in direction finder. Using the proposed method, we obtain the ambiguity probability for each of array geometry composed of multiple baseline. After performing the simulation with the selected antenna array spacing to verify the proposed method, we compared the calculated result data with the simulation data.

• 대한안전경영과학회지
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• 제23권2호
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• pp.9-17
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• 2021

As interest in vocational competency development projects increases, support is increasing. In this study, in order to study ways to improve participation in vocational competency development training, related factors are selected and the main factors influencing them are derived. The main factors were influencing factors were identified and ways to improve participation rate of vocational competency development were studied. Variables were selected through prior research, and data were collected and analyzed through in-depth group interviews. Based on factor analysis and reliability analysis, as a result of confirming the factors that influence the plan for improving participation in vocational competency development training by applying the backward stage selection (condition) method of logistic regression analysis, the case of respect for minorities in the 7-point Likert scale The closer to 7 was, the higher the probability of being classified as having never participated, and the other factors except minority respect, Likert scale closer to 7 indicates higher probability of bening classified as having never participated, except for the minority respect factor. Therefore, it was confirmed that lowering the scale of the factor of respect for minority, which is job satisfaction, and increasing the factors of individual characteristics such as annual salary and organizational commitment, training system for job satisfaction, and quality assurance have effects on improving participation rates in vocational competency development training.

• Earthquakes and Structures
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• 제22권6호
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• pp.571-584
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• 2022

The residual displacement ratio (RDRs) response spectra have been generally used as an important means to evaluate the post-earthquake repairability, and the ratios of residual to maximum inelastic displacement are considered to be more appropriate for development of the spectra. This methodology, however, assumes that the expected residual displacement can be computed as the product of the RDRs and maximum inelastic displacement, without considering the correlation between these two variables, which inevitably introduces potential systematic error. For providing an adequately accurate estimate of residual displacement, while accounting for the collapse resistance performance prior to the repairability evaluation, a probability-based procedure to estimate the residual displacement demands using the nonlinear static analysis (NSA) is developed for single-degree-of-freedom (SDOF) systems. To this end, the energy-based equivalent damping ratio used for NSA is revised to obtain the maximum displacement coincident with the nonlinear time history analysis (NTHA) results in the mean sense. Then, the possible systematic error resulted from RDRs spectra methodology is examined based on the NTHA results of SDOF systems. Finally, the statistical relation between the residual displacement and the NSA-based maximum displacement is established. The results indicate that the energy-based equivalent damping ratio will underestimate the damping for short period ranges, and overestimate the damping for longer period ranges. The RDRs spectra methodology generally leads to the results being non-conservative, depending on post-yield stiffness. The proposed approach emphasizes that the repairability evaluation should be based on the premise of no collapse, which matches with the current performance-based seismic assessment procedure.

• Structural Engineering and Mechanics
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• 제37권4호
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• pp.427-442
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• 2011

In fatigue life design of mechanical components, uncertainties arising from materials and manufacturing processes should be taken into account for ensuring reliability. A common practice is to apply a safety factor in conjunction with a physics model for evaluating the lifecycle, which most likely relies on the designer's experience. Due to conservative design, predictions are often in disagreement with field observations, which makes it difficult to schedule maintenance. In this paper, the Bayesian technique, which incorporates the field failure data into prior knowledge, is used to obtain a more dependable prediction of fatigue life. The effects of prior knowledge, noise in data, and bias in measurements on the distribution of fatigue life are discussed in detail. By assuming a distribution type of fatigue life, its parameters are identified first, followed by estimating the distribution of fatigue life, which represents the degree of belief of the fatigue life conditional to the observed data. As more data are provided, the values will be updated to reduce the credible interval. The results can be used in various needs such as a risk analysis, reliability based design optimization, maintenance scheduling, or validation of reliability analysis codes. In order to obtain the posterior distribution, the Markov Chain Monte Carlo technique is employed, which is a modern statistical computational method which effectively draws the samples of the given distribution. Field data of turbine components are exploited to illustrate our approach, which counts as a regular inspection of the number of failed blades in a turbine disk.