• Journal of the Korean Society of Industry Convergence
• /
• v.23 no.5
• /
• pp.799-807
• /
• 2020

This paper deals with identification of probabilistic design using reliability based robust optimization in structure design of automatic salt collector. The thickness sizing variables of main structure member in the automatic salt collector were considered the random design variables including the uncertainty of corrosion that would be an inevitable hazardousness in the saltern work environment. The probabilistic constraint functions were selected from the strength performances of the automatic salt collector. The reliability based robust optimum design problem was formulated such that the random design variables were determined by minimizing the weight of the automatic salt collector subject to the probabilistic strength performance constraints evaluating from reliability analysis. Mean value reliability method and adaptive importance sampling method were applied to the reliability evaluation in the reliability based robust optimization. The three sigma level quality was considered robustness in side constraints. The probabilistic optimum design results according to the reliability analysis methods were compared to deterministic optimum design results. The reliability based robust optimization using the mean value reliability method showed the most rational results for the probabilistic optimum structure design of the automatic salt collector.

• Structural Engineering and Mechanics
• /
• v.9 no.6
• /
• pp.557-568
• /
• 2000

As time-variant reliability approaches become increasingly used for service life prediction of the aging infrastructure, the demand for computer solution methods continues to increase. Effcient computer techniques have become well established for the reliability analysis of structural systems. Thus far, however, this is largely limited to time-invariant reliability problems. Therefore, the requirements for time-variant reliability prediction of deteriorating structural systems under time-variant loads have remained incomplete. This study presents a computer program for $\underline{REL}$iability of $\underline{T}$ime-Variant $\underline{SYS}$tems, RELTSYS. This program uses a combined technique of adaptive importance sampling, numerical integration, and fault tree analysis to compute time-variant reliabilities of individual components and systems. Time-invariant quantities are generated using Monte Carlo simulation, whereas time-variant quantities are evaluated using numerical integration. Load distribution and post-failure redistribution are considered using fault tree analysis. The strengths and limitations of RELTSYS are presented via a numerical example.

• The KIPS Transactions:PartB
• /
• v.10B no.6
• /
• pp.711-718
• /
• 2003

In this paper, we propose a robust face tracking algorithm. It is based on Condensation algorithm [7] and uses skin color and facial shape as the observation measure. It is hard to integrate color weight and shape weight. So we propose the method that has two separate trackers which uses skin color and facial shape as the observation measure respectively. One tracker tracks skin colored region and the other tracks facial shape. We used importance sampling technique to limit sampling region of two trackers. For skin-colored region tracker, we propose an adaptive color model to avoid the effect of illumination change. The proposed face tracker performs robustly in clutter background and in the illumination changes.

• The Korean Journal of Applied Statistics
• /
• v.33 no.4
• /
• pp.379-393
• /
• 2020

A terminal event such as death may censor an intermediate event such as relapse, but not vice versa in semi-competing risks data, which is often seen in medicine, public health, and epidemiology. We propose a Weibull regression model with a normal frailty to analyze semi-competing risks data when all three transition times of the illness-death model are possibly interval-censored. We construct the conditional likelihood separately depending on the types of subjects: still alive with or without the intermediate event, dead with or without the intermediate event, and dead with the intermediate event missing. Optimal parameter estimates are obtained from the iterative quasi-Newton algorithm after the marginalization of the full likelihood using the adaptive importance sampling. We illustrate the proposed method with extensive simulation studies and PAQUID (Personnes Agées Quid) data.

• Journal of the Korean housing association
• /
• v.20 no.6
• /
• pp.1-10
• /
• 2009

Rapid social change affects residential environments and this in turn creates new stimuli to which people have to adapt. These stimuli have been seen to increase stress levels. Therefore, dwellers in these environments try to reduce stress through various methods. The purpose of this paper is to: 1) identify the general trends of coping styles about residential environmental stress, 2) analyze the differences in socio-demographic characteristics and how the physical characteristics of buildings affect stress, find out how personal backgrounds affect stress levels and the ability to get rid of environmental-related stress. The subjects in this study consisted of people living in multi-family housing in Gwangju. The city is divided into 5 districts and used quota sampling. 324 housewives were surveyed from the households by self-administered questionnaires. The survey was conducted in December, 2006, after the questionnaire was revised based on the results of preliminary survey. After all the questionnaires were collected, the data was coded and analyzed using the SPSS 12.0 program. This study confirmed that the manner in which those in multi-family housing coped with stress. Especially, we need a policy which seriously considers residents who are of low social-economic standing. As well as being exposed to residential environmental stress, they also have no means to deal with it. The age of a building had a strong impact on coping styles about residential environmental stress. We have to make special studies about the adaptive reuse of buildings for the reduction of residential environmental stress and to greatly improve coping styles. In conclusion, it emphasized the importance of education, information, and economic aid. Reasonable housing management would surely lead to a rise in residential satisfaction and the promotion of residential welfare.

• The Korean Journal of Applied Statistics
• /
• v.30 no.4
• /
• pp.539-553
• /
• 2017

We propose a multi-state model to analyze semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the three states of the illness-death model: healthy, disease, and dead. The 'diseased' state can be considered as the intermediate event. Two more states are added into the illness-death model to incorporate the missing events, which are caused by a loss of follow-up before the end of a study. One of them is a state of the lost-to-follow-up (LTF), and the other is an unobservable state that represents an intermediate event experienced after the occurrence of LTF. Given covariates, we employ the Lin and Ying additive hazards model with log-normal frailty and construct a conditional likelihood to estimate transition intensities between states in the multi-state model. A marginalization of the full likelihood is completed using adaptive importance sampling, and the optimal solution of the regression parameters is achieved through an iterative quasi-Newton algorithm. Simulation studies are performed to investigate the finite-sample performance of the proposed estimation method in terms of empirical coverage probability of true regression parameters. Our proposed method is also illustrated with a dataset adapted from Helmer et al. (2001).