• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1314-1319
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• 2008

Fatigue reliability problems are nowadays actively considered in the design of mechanical components. Recently, Dimension Reduction Method using Kriging approximation (KDRM) was proposed by the authors to efficiently calculate statistical moments of the response function. This method, which is more tractable for its sensitivity-free nature and providing the response PDF in a few number of analyses, is adopted in this study for the reliability analysis. Before applying this method to the practical fatigue problems, accuracies are studied in terms of parameters of the KDRM through a number of numerical examples, from which best set of parameters are suggested. In the fatigue reliability problems, good number of experimental data are necessary to get the statistical distribution of the S-N parameters. The information, however, are not always available due to the limited expense and time. In this case, a family of curves with prediction interval, called P-S-N curve, is constructed from regression analysis. Using the KDRM, once a set of responses are available at the sample points at the mean, all the reliability analyses for each P-S-N curve can be efficiently studied without additional response evaluations. The method is applied to a spring design problem as an illustration of practical applications, in which reliability-based design optimization (RBDO) is conducted by employing stochastic response surface method which includes probabilistic constraints in itself. Resulting information is of great practical value and will be very helpful for making trade-off decision during the fatigue design.

• Human Ecology Research
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• v.51 no.4
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• pp.413-424
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• 2013

The purpose of this study is to examine the influence of social face sensitivity on vanity and consumption behavior. Questionnaires were administered to 461 college students living in Deagu Metropolitan City and Kyungbook province. Frequency, factor analysis, reliability analysis, regression analysis, and t-test were used for data analysis. Social face sensitivity was categorized into consciousness of being embarrassed, social formality, other consciousness and prestigiousness. Vanity factors were found as physical price, achievement concern, achievement price, and physical concern. Consumption behavior were categorized into 5 factors such as ostentatious consumption, impulsive buying, external information search, brand trust, utilization of internet information and material-oriented. Consciousness of being embarrassed, social formality, and other consciousness, the sub-variables of social face sensitivity had significant effects on achievement concerns and physical concerns. Other consciousness of social face sensitivity had significant effects on all factors of consumption behaviors. There was significant differences in the prestige of social face sensitivity and physical concerns of vanity and ostentatious consumption, impulsive buying, and also in external information search and utilization of internet information of consumer behavior. This indicates that women showed high physical concerns for vanity and ostentatious consumption, impulsive buying, external information search and utilization of internet information of consumption behavior while men care more about prestigiousness of social face sensitivity.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2343-2349
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• 1999

The hyper-geometric distribution software reliability growth model (HGDM) was recently developed and successfully applied to real data sets. The HGDM considers the sensitivity factor as a parameter to be estimated. In order to reflect the random behavior of the test-and-debug process, this paper generalizes the HGDM by assuming that the sensitivity factor is a binomial random variable. Such a generalization enables us to easily understand the statistical characteristics of the HGDM. It is shown that the least squares method produces the identical results for both the HGDM and the generalized HGDM. Methods for computing the maximum likelihood estimates and predicting the future outcomes are also presented.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.1
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• pp.142-154
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• 1994

In this paper, stochastic imperfection sensitivity analyses of stiffened cylindrical shells under static load are presented. Multimode formulation is performed for the buckling load calculation based on the Donnell's theory and Galerkin approximation. Random imperfection field theory and response surface method are combined with deterministic bucking analysis scheme to perform stochastic imperfection sensitivity analyses of stiffened cylindrical shells considering random geometric imperfection. From the characteristics of probabilistic bucking load, the relation between reliability index and safety parameter can be obtained in addition to the relation between load and reliability index. Those results can be used to determine the range of required safety parameter and acceptable imperfection.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1103-1111
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• 2000

The hyper-geometric distribution software reliability growth model (HGDM) usually assumes that all the software faults detected are perfectly removed without introducing new faults. However, since new faults can be introduced during the test-and-debug phase, the perfect debugging assumption should be relaxed. In this context, Hou, Kuo and Chang [7] developed a modified HGDM for imperfect debugging environment, assuming tat the learning factor is constant. In this paper we extend the existing imperfect debugging HGDM for tow respects: introduction of random sensitivity factor and allowance of variable learning factor. Then the statistical characteristics of he suggested model are studied and its applications to two real data sets are demonstrated.

• Structural Engineering and Mechanics
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• v.52 no.6
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• pp.1099-1120
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• 2014

In this paper, reliability-based design optimization (RBDO) of structures is addressed. For this purpose, the global search and optimization capabilities of genetic algorithm (GA) are combined with the efficiency and reasonable accuracy of an advanced moment-based finite element reliability method. For performing RBDO, three variants of GA including a real-coded, a binary-coded and an improved binary-coded GA are developed. In these methods, GA performs (finite element) reliability analyses to evaluate reliability constraints. For truss structures which include finite element modeling, reliability constraints are evaluated using finite element reliability analysis. Response sensitivity required for finite element reliability analysis is obtained by direct differentiation method (DDM) rather than finite difference method (FDM). The proposed methods are examined within four standard test examples and real-world design problems. The results illustrate the superiority and efficiency of the improved binary-coded GA. Results also illustrate that DDM significantly reduces the computational cost and improves the efficiency of the optimization procedure.

• Earthquakes and Structures
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• v.14 no.5
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• pp.425-436
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• 2018

The design of seismically isolated structures considering the stochastic nature of excitations, base isolators' design parameters, and superstructure properties requires robust reliability analysis methods to calculate the failure probability of the entire system. Here, by applying artificial neural networks, we proposed a robust technique to accelerate the estimation of failure probability of equipped isolated structures. A three-story isolated building with susceptible facilities is considered as the analytical model to evaluate our technique. First, we employed a sensitivity analysis method to identify the critical sources of uncertainty. Next, we calculated the probability of failure for a particular set of random variables, performing Monte Carlo simulations based on the dynamic nonlinear time-history analysis. Finally, using a set of designed neural networks as a surrogate model for the structural analysis, we assessed once again the probability of the failure. Comparing the obtained results demonstrates that the surrogate model can attain precise estimations of the probability of failure. Moreover, our proposed approach significantly increases the computational efficiency corresponding to the dynamic time-history analysis of the structure.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.275-282
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• 2006

System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolernce of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or etimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte Carlo simulation and got the probabilistic sensitivity. The sensitivity of structural response with respect to in constant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.7
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• pp.18-27
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• 2006

The conventional reliability based design optimization(RBDO) methods require high computational cost compared with the deterministic design optimization(DO) methods, therefore it is hard to apply directly to large-scaled problems such as an aerodynamic shape design optimization. In this study, to overcome this computational limitation the efficient RBDO procedure with the two-point approximation(TPA) and adjoint sensitivity analysis is proposed, that the computational requirement is nearly the same as DO and the reliability accuracy is good compared with that of RBDO. Using this, the 3-D aerodynamic shape design optimization is performed very efficiently.

• Journal of muscle and joint health
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• v.21 no.1
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• pp.75-84
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• 2014

Purpose: The purpose of this study was to test the validity and reliability of the Korean version of the Geriatric Anxiety Inventory (K-GAI). Methods: Two hundreds and thirty six elderly were participated to test K-GAI. Goldberg's short screening scale for anxiety was tested for criterion validity. Receiver operating characteristics (ROC) analysis was used for measuring sensitivity and specificity. Results: The obtained internal consistency was 0.88. There were significant associations between test and retest results. K-GAI scores was significantly associated with Goldberg's short screening scale for anxiety (r=.694, p<.001). We found that a score of seven and greater was optimal for a criterion of anxiety among elderly Koreans. At this cut point, sensitivity was 78.9% and specificity was 73.1%. Conclusion: The K-GAI displayed good psychometric properties. This tool would be useful for early detection of anxiety among elderly Koreans with various situations including cognitive disorder, low education, or physical disability.