• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.1503-1504
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• 2008

This paper presents stochastic methodology based fault diction and diagnosis algorithm for induction motor systems. First, we construct probability distribution model from healthy motors and then probability distribution for faulty motors is recursively calculated by means of the proposed probability estimation. We measure motor current with hall sensors as system state. The estimated probability is compared to the model to generate a residue signal which is utilized for fault detection and diagnosis, that is, where a fault is occurred. We carry out real-time induction motor experiment to evaluate efficiency and reliability of the proposed approach.

• 수산경영론집
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• 제45권3호
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• pp.55-69
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• 2014

We try to test the pecking order theory of Korean fisheries firm's capital structure using debt capacity. At first, we estimate the debt capacity as the probability of assigning corporate bond rating from credit-rating agencies. We use logit regression model to estimate this probability as a proxy of debt capacity. The major results of this study are as follows. Firstly, we can confirm the fisheries firm's financing behaviour which issues new debt securities for financial deficit. Empirical test of SSM model indicates that the higher probability of assigning corporate bond rating, the higher the coefficient of financial deficit. Especially, high probability group follows this result exactly. Therefore, the pecking order theory of fisheries firm's capital structure applies well for high probability group which means high debt capacity. It also applies for medium and low probability group, but their significances are not good. Secondly, the most of fisheries firms in high probability group issue new debt securities for their financial deficit. Low probability group's fisheries firms also issue new debt securities for their financial deficit within the limit of their debt capacity, but beyond debt capacity they use equity financing for financial deficit. Therefore, the pecking order theory on debt capacity come into existence well in high probability group.

• 음성과학
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• 제9권2호
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• pp.135-146
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• 2002

Generally a speaker verification system improves its system recognition ratio by regularizing log likelihood ratio, using a speaker model and its background speaker model that are required to be verified. The speaker-based cohort method is one of the methods that are widely used for selecting background speaker model. Recently, Gaussian-based cohort model has been suggested as a virtually synthesized cohort model, and unlike a speaker-based model, this is the method that chooses only the probability distributions close to basic speaker's probability distribution among the several neighboring speakers' probability distributions and thereby synthesizes a new virtual speaker model. It shows more excellent results than the existing speaker-based method. This study compared the existing speaker-based background speaker models and virtual speaker models and then constructed new virtual background speaker model groups which combined them in a certain ratio. For this, this study constructed a speaker verification system that uses GMM (Gaussin Mixture Model), and found that the suggested method of selecting virtual background speaker model shows more improved performance.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 추계 학술발표회 논문집
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• pp.207-212
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• 2003

In this paper, we propose a class of imputed estimators using response probability. The proposed estimator can be justified under the response probability model and thus is robust against the failure of the assumed imputation model. We also propose a variance estimator that is justified under the response probability model.

• 대한수학회지
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• 제51권4호
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• pp.735-749
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• 2014

This paper studies the asymptotic behavior of the finite-time ruin probability in a jump-diffusion risk model with constant force of interest, upper tail asymptotically independent claims and a general counting arrival process. Particularly, if the claim inter-arrival times follow a certain dependence structure, the obtained result also covers the case of the infinite-time ruin probability.

• Safety and Health at Work
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• 제9권1호
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• pp.42-52
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• 2018

Background: Maintenance operations on-board ships are highly demanding. Maintenance operations are intensive activities requiring high man-machine interactions in challenging and evolving conditions. The evolving conditions are weather conditions, workplace temperature, ship motion, noise and vibration, and workload and stress. For example, extreme weather condition affects seafarers' performance, increasing the chances of error, and, consequently, can cause injuries or fatalities to personnel. An effective human error probability model is required to better manage maintenance on-board ships. The developed model would assist in developing and maintaining effective risk management protocols. Thus, the objective of this study is to develop a human error probability model considering various internal and external factors affecting seafarers' performance. Methods: The human error probability model is developed using probability theory applied to Bayesian network. The model is tested using the data received through the developed questionnaire survey of >200 experienced seafarers with >5 years of experience. The model developed in this study is used to find out the reliability of human performance on particular maintenance activities. Results: The developed methodology is tested on the maintenance of marine engine's cooling water pump for engine department and anchor windlass for deck department. In the considered case studies, human error probabilities are estimated in various scenarios and the results are compared between the scenarios and the different seafarer categories. The results of the case studies for both departments are also compared. Conclusion: The developed model is effective in assessing human error probabilities. These probabilities would get dynamically updated as and when new information is available on changes in either internal (i.e., training, experience, and fatigue) or external (i.e., environmental and operational conditions such as weather conditions, workplace temperature, ship motion, noise and vibration, and workload and stress) factors.

• 산업기술연구
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• 제21권B호
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• pp.163-174
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• 2001

A dynamic reliability model for analyzing the stability of armor units on rubble-mound breakwater is mathematically developed by using Hudson's formula and definition of single-failure mode. The probability density functions of resistance and loading functions are defined properly, the related parameters to those probability density functions are also estimated straightforwardly by the first-order analysis. It is found that probabilities of failure for the stability of armor units on rubble-mound breakwater are continuously increased as the service periods are elapsed, because of the occurrence of repeated loading of random magnitude by which the resistance may be deteriorated. In particular, the factor of safety is incorporated into the dynamic reliability model in order to evaluate the probability of failure as a function of factor of safety. It may thus be possible to take some informations for optimal design as well as managements and repairs of armor units on rubble-mound breakwater from the dynamic reliability analyses.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.630-633
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• 2004

Generally, component and FR-4 board are connected by solder joint. Because material properties of components and FR-4 board are different, component and FR-4 board show different coefficients of thermal expansion (CTE) and thus strains in component and board are different when they are heated. That is, the differences in CTE of component and FR-4 board cause the dissimilarity in shear strain and BGA solder joint s failure. The first order Taylor series expansion of the limit state function incorporating with thermal fatigue models is used in order to estimate the failure probability of solder joints under heated condition. A model based on plastic-strain rate such as the Coffin-Manson Fatigue Model is utilized in this study. The effects of random variables such as frequency, maximum temperature, and temperature variations on the failure probability of the BGA solder joint are systematically investigated by using a failure probability model with the first order reliability method(FORM).

• Journal of applied mathematics & informatics
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• 제27권5_6호
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• pp.1033-1047
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• 2009

In this paper, we consider a m-type risk model with Markov-modulated premium rate. A integral equation for the conditional ruin probability is obtained. A recursive inequality for the ruin probability with the stationary initial distribution and the upper bound for the ruin probability with no initial reserve are given. A system of Laplace transforms of non-ruin probabilities, given the initial environment state, is established from a system of integro-differential equations. In the two-state model, explicit formulas for non-ruin probabilities are obtained when the initial reserve is zero or when both claim size distributions belong to the $K_n$-family, n $\in$ $N^+$ One example is given with claim sizes that have exponential distributions.

• 대한교통학회지
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• 제25권4호
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• pp.109-121
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• 2007

자료결측의 심각성은 현실적으로 거의 대부분의 조사에서 발생한다. 비단 교통분야뿐만 아니라 인문사회 분야나 기상학, 생물학, 지구과학 등 모든 분야에서 인력식이든 기계식이든 조사 방식에 관계없이 발생한다. 교통자료 수집장비에서의 자료결측의 발생은 현실적으로 불가피한 현상으로 볼 수 있으며, 이와 같은 자료 수집과정에서 발생하는 결측을 신뢰성있게 추정하여 보정하였던 선행연구의 대부분은 교통량 자료의 결측값 보정시 통계적 검증없이 시간적인 임의의 종속성만 고려함으로서, 보정 성능이 떨어지는 단점을 노출하고 있다. 이들 연구에서 적용했던 기법들 또한, 교통량 자료가 가지고 있는 가장 큰 특징인 주기적 순환성(periodic circularity)이 제대로 반영되지 못함으로서 적용상 한계를 노출하고 있다. 본 연구는 현실적으로 거의 대부분의 조사과정에서 발생하는 자료결측의 심각성에 대한 인식을 토대로 대안으로 순환분포모형을 제안하였다. 이러한 자료결측 현상에 대응하고자 하였던 기존의 ad-hoc 또는 heuristic 보정 기법과 모형 기반 및 알고리즘 기반의 보정 기법에 관한 선행 연구의 고찰을 통하여 이들 기법들의 한계점을 확인하였다.