• Journal of Korean Society for Atmospheric Environment
• /
• v.18 no.6
• /
• pp.465-474
• /
• 2002

In order to reflect variability due to exposure factors as well as to assess uncertainty associated with cancer risk posed by airborne trace metals, a Monte Calro analysis has been made in this study. Input parameters for Monte Carlo analysis were developed or adjusted using body weight, lifetime, and exposure frequency of Koreans. Ambient distributions of toxic metals were founded to be lognormal distributions for most of them using goodness-of-fit tests. Thus, the 95% UCL and 95% LCL of carcinogenic metals were estimated by H-statistic method for lognormal distribution, respectively. The results of Monte Carlo analysis of 95% UCL showed that the 95th percentile risks for men and women were 1.2 and 1.1 times higher than an acceptable risk of 10$^{-5}$ , respectively. The probabilities which those risks exceed the acceptable risk were estimated to be 8% and 6%, respectively, while to be 95% and 94%, respectively on the basis of the minimum acceptable risk of 10$^{-6}$ , respectively. Approximately 90% of total cancer risk came from human carcinogens such as arsenic and hexavalent chromium. Therefore, it is necessary to properly manage both arsenic and hexavalent chromium emissions in the study area.

• Steel and Composite Structures
• /
• v.20 no.6
• /
• pp.1345-1368
• /
• 2016

This paper presents the probabilistic-based assessment of composite steel-concrete structures through an innovative framework. This framework combines model identification and reliability assessment procedures. The paper starts by describing current structural assessment algorithms and the most relevant uncertainty sources. The developed model identification algorithm is then presented. During this procedure, the model parameters are automatically adjusted, so that the numerical results best fit the experimental data. Modelling and measurement errors are respectively incorporated in this algorithm. The reliability assessment procedure aims to assess the structure performance, considering randomness in model parameters. Since monitoring and characterization tests are common measures to control and acquire information about those parameters, a Bayesian inference procedure is incorporated to update the reliability assessment. The framework is then tested with a set of composite steel-concrete beams, which behavior is complex. The experimental tests, as well as the developed numerical model and the obtained results from the proposed framework, are respectively present.

• Journal of the Korean Geosynthetics Society
• /
• v.17 no.2
• /
• pp.33-40
• /
• 2018

Characteristics of interface friction between cohesionless soils and geotechnical structure surfaces play an important role in the analysis of earth load and resistance on the structure. In general, geotechnical structures are mainly composed of either steel or concrete, and their surface roughnesses with respect to soil particle sizes influence the interface characteristics between soils and the structures. Accurate assessment of the interface friction characteristics between soils and structures is important to ensure the safety of geotechnical structures, such as mechanically stabilized earth walls reinforced with inextensible reinforcements, piles embedded into soils, retaining wall backfilled with soils. In this study, based on the database of high quality interface friction tests between frictional soils and solid surfaces from literature, equation representing peak interface friction angle is proposed. The influential factors of the peak interface friction angle are relative roughness between soil and solid surface, relative density of frictional soil, and residual (constant volume) interface friction angle. Futhermore, for the developed equation of the interface friction angle, its uncertainty was assessed statistically based on Goodness-of-fit test results.

• Women's Health Nursing
• /
• v.29 no.4
• /
• pp.302-316
• /
• 2023

Purpose: This study aimed to develop and validate a structural model for the quality of life (QoL) among high-risk pregnant women, based on Roy's adaptation model. Methods: This cross-sectional study collected data from 333 first-time mothers diagnosed with a high-risk pregnancy in two obstetrics and gynecology clinics in Cheonan, Korea, or participating in an online community, between October 20, 2021 and February 20, 2022. Structured questionnaires measured QoL, contextual stimuli (uncertainty), coping (adaptive or maladaptive), and adaptation mode (fatigue, state anxiety, antenatal depression, maternal identity, and marital adjustment). Results: The mean age of the respondents was 35.29±3.72 years, ranging from 26 to 45 years. The most common high-risk pregnancy diagnosis was gestational diabetes (26.1%). followed by preterm labor (21.6%). QoL was higher than average (18.63±3.80). Above-moderate mean scores were obtained for all domains (psychological/baby, 19.03; socioeconomic, 19.00; relational/spouse-partner, 20.99; relational/family-friends, 19.18; and health and functioning, 16.18). The final model explained 51% of variance in QoL in high-risk pregnant women, with acceptable overall model fit. Adaptation mode (β=-.81, p=.034) and maladaptive coping (β=.46 p=.043) directly affected QoL, and uncertainty (β=-. 21, p=.004), adaptive coping (β=.36 p=.026), and maladaptive coping (β=-.56 p=.023) indirectly affected QoL. Conclusion: It is essential to develop nursing interventions aimed at enhancing appropriate coping strategies to improve QoL in high-risk pregnant women. By reinforcing adaptive coping strategies and mitigating maladaptive coping, these interventions can contribute to better maternal and fetal outcomes and improve the overall well-being of high-risk pregnant women.

• Geomechanics and Engineering
• /
• v.36 no.6
• /
• pp.601-618
• /
• 2024

The joint probability distribution of uncertain geomechanical parameters of geotechnical strata is a crucial aspect in constructing the reliability functional function for roof structures. However, due to the limited number of on-site exploration and test data samples, it is challenging to conduct a scientifically reliable analysis of roof geotechnical strata. This study proposes a Copula method based on small sample exploration and test data to construct the intensity characteristics of roof geotechnical strata. Firstly, the theory of multidimensional copula is systematically introduced, especially the construction of four-dimensional Gaussian copula. Secondly, data from measurements of 176 groups of geomechanical parameters of roof geotechnical strata in 31 coal mines in China are collected. The goodness of fit and simulation error of the four-dimensional Gaussian Copula constructed using the Pearson method, Kendall method, and Spearman methods are analyzed. Finally, the fitting effects of positive and negative correlation coefficients under different copula functions are discussed respectively. The results demonstrate that the established multidimensional Gaussian Copula joint distribution model can scientifically represent the uncertainty of geomechanical parameters in roof geotechnical strata. It provides an important theoretical basis for the study of reliability functional functions for roof structures. Different construction methods for multidimensional Gaussian Copula yield varying simulation effects. The Kendall method exhibits the best fit in constructing correlations of geotechnical parameters. For the bivariate Copula fitting ability of uncertain parameters in roof geotechnical strata, when the correlation is strong, Gaussian Copula demonstrates the best fit, and other Copula functions also show remarkable fitting ability in the region of fixed correlation parameters. The research results can offer valuable reference for the stability analysis of roof geotechnical engineering.

• Journal of Information Technology Applications and Management
• /
• v.18 no.4
• /
• pp.131-148
• /
• 2011

Our work empirically investigates the cultural differences of Social Networking Service (SNS) users in China, Korea and U.S. We construct a survey questionnaire from existing literature and test it for reliability, validity, and model fit. Then we collect data and validate the cultural differences of SNS users in three nations. Our results show different rankings from existing literature in cultural dimensions about three nations. In terms of masculinity, we find China > U.S. > Korea, similar to Hofstede. In individualism, we find U.S. > Korea > China, different from Hofstede (U.S. > China > Korea). In power distance, it is shown that Korea > China > U.S., different from Hofstede (China > Korea > U.S.). Uncertainty avoidance is found that U.S. > Korea > China, lowered ranking of Korea from the top among three nations in Hofstede. We find that these outcomes would be useful in updating national culture of the three nations and for future research about cultural impacts on SNS adoption.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1816-1819
• /
• 1997

Using the vision system, robotic tasks in unstructured environments can be accompished, which reduces greatly the cost and steup time for the robotic system to fit to he well-defined and structured working environments. This paper proposes a dynamic control scheme for robot manipulator with eye-in-hand camera configuration. To perfom the tasks defined in the image plane, the camera motion Jacobian (image Jacobian) matrix is used to transform the camera motion to the objection position change. In addition, the dynamic learning controller is designed to improve the tracking performance of robotic system. the proposed control scheme is implemented for tasks of tracking moving objects and shown to outperform the conventional visual servo system in convergence and robustness to parameter uncertainty, disturbances, low sampling rate, etc.

• Structural Engineering and Mechanics
• /
• v.25 no.3
• /
• pp.331-345
• /
• 2007

Uncertainties enter a complex analysis from a variety of sources: variability, lack of data, human errors, model simplification and lack of understanding of the underlying physics. However, for many important engineering applications insufficient data are available to justify the choice of a particular probability density function (PDF). Sometimes the only data available are in the form of interval estimates which represent, often conflicting, expert opinion. In this paper we demonstrate that Bayesian estimation techniques can successfully be used in applications where only vague interval measurements are available. The proposed approach is intended to fit within a probabilistic framework, which is established and widely accepted. To circumvent the problem of selecting a specific PDF when only little or vague data are available, a hierarchical model of a continuous family of PDF's is used. The classical Bayesian estimation methods are expanded to make use of imprecise interval data. Each of the expert opinions (interval data) are interpreted as random interval samples of a parent PDF. Consequently, a partial conflict between experts is automatically accounted for through the likelihood function.

• Environmental Analysis Health and Toxicology
• /
• v.18 no.1
• /
• pp.1-13
• /
• 2003

To estimate the annual WTP for risk reduction of environmental problems such as outdoor and indoor air pollution, and drinking water contamination, a questionnaire survey was conducted by dichotomous contingent valuation method in Seoul. Several covariate models based on Turnbull, Weibull and Spike models were developed and applied to WTP estimation with uncertainty analysis. WTP estimates for risk reduction of air pollution were 13,000 won, 12,000 won, and 10,000 won per month in low-bounded Turnbull, Weibull and Spike models, respectively. The estimates for indoor air pollution were 17,000 won,20,000 won and 21,000 won and these for drinking water contamination were 10,000 won, 13,000 won and 14,000 won in each model, respectively. Goodness of fit for Weibull model was better than those for other models. WTP estimates for indoor air pollution were higher than those for other pollution problems.

• Journal of Integrative Natural Science
• /
• v.10 no.4
• /
• pp.249-257
• /
• 2017

The main focus when developing software is to improve the reliability and stability of a software system. We are enjoying a very comfortable life thanks to modern civilization, however, comfort is not guaranteed to us. Once software systems are introduced, the software systems used in the field environments are the same as or close to those used in the development-testing environment; however, the systems may be used in many different locations. Development of software system is a difficult and complex process. Generally, existing software reliability models are applied to software testing data and then used to make predictions on the software failures and reliability in the field. In this paper, we present an improved exponential NHPP software reliability model in different development environments, and examine the goodness-of-fit of improved exponential model and other model based on two datasets. The results show that the proposed model fits significantly better than other NHPP software reliability model.