• Journal of Korean Academy of Nursing
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• v.35 no.5
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• pp.879-887
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• 2005

Purpose: The purpose of this study was to understand depression in women with endometriosis and to identify the factors influencing depression. Method: The instruments used were the Beck Depression Inventory for depression, Lemaire Scale for endometriosis syndrome, Mishel Uncertainty in Illness Scale-Community form (MUIS-C), the Rosenberg Self-esteem Scale, and Quality of Life (Endometriosis Health Profile Questionnaire; EHP-5) by Jones et al. The Subjects of Study were 118 outpatients diagnosed with endometriosis from 7 hospitals in Busan City and Kyungsangnam-do. Data was collected from Aug 1, 2004 to Jan 31, 2005. For statistical analysis of collected data, frequency analysis, analysis of variance, and stepwise multiple regression analysis were used with the SPSS statistical program. Result: The general characteristic showing a statistically significant difference in depression in the women with endometriosis was marital status. The score of the depression showed a significantly positive correlation with the score of endometriosis TSD(r= .464, p= .000), uncertainty(r= .393, p= .000), and quality of life(r= .543, p= .000). Depression showed a significantly negative correlation with the score of self esteem(r= - .557, p= .000). Stepwise multiple regression analysis revealed that the most powerful predictor of depression in the women with endometriosis was self-esteem ($R^2$=0.311). A combination of self esteem, quality of life, and total symptom distress accounted for $50.0\%$ of the variance in depression in women with endometriosis. Conclusion: The influencing factor on depression in women with endometriosis was self- esteem, quality of life, and endometriosis TSD. Further studies need to be done to identify methods of overcoming and the presentation of depression in endometriosis.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.41 no.2
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• pp.107-112
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• 2008

To evaluate uncertainty and risk in biological reference points, we applied a bootstrapping method and a Bayesian procedure to estimate the related confidence intervals. Here we provide an example of the maximum sustainable yield (MSY) of turban shell, Batillus cornutus, estimated by the Schaefer and Fox models. Fitting the time series of catch and effort from 1968 to 2006 showed that the Fox model performs better than the Schaefer model. The estimated MSY and its bootstrap percentile confidence interval (CI) at ${\alpha}=0.05$ were 1,680 (1,420-1,950) tons for the Fox model and 2,170 (1,860-2,500) tons for the Schaefer model. The CIs estimated by the Bayesian approach gave similar ranges: 1,710 (1,450-2,000) tons for the Fox model and 2,230 (1,760-2,930) tons for the Schaefer model. Because uncertainty in effort and catch data is believed to be greater for earlier years, we evaluated the influence of sequentially excluding old data points by varying the first year of the time series from 1968 to 1992 to run 'backward' bootstrap resampling. The results showed that the means and upper 2.5% confidence limit (CL) of MSY varied greatly depending on the first year chosen whereas the lower 2.5% CL was robust against the arbitrary selection of data, especially for the Schaefer model. We demonstrated that the bootstrap and Bayesian approach could be useful in precautionary fisheries management, and we advise that the lower 2.5% CL derived by the Fox model is robust and a better biological reference point for the turban shells of Jeju Island.

• Radiation Oncology Journal
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• v.36 no.2
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• pp.122-128
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• 2018

Purpose: To investigate positional uncertainty and its correlation with clinical parameters in spine stereotactic body radiotherapy (SBRT) using thermoplastic mask (TM) immobilization. Materials and Methods: A total of 21 patients who underwent spine SBRT for cervical or upper thoracic spinal lesions were retrospectively analyzed. All patients were treated with image guidance using cone beam computed tomography (CBCT) and 4 degrees-of-freedom (DoF) positional correction. Initial, pre-treatment, and post-treatment CBCTs were analyzed. Setup error (SE), pre-treatment residual error (preRE), post-treatment residual error (postRE), intrafraction motion before treatment (IM1), and intrafraction motion during treatment (IM2) were determined from 6 DoF manual rigid registration. Results: The three-dimensional (3D) magnitudes of translational uncertainties (mean ${\pm}$ 2 standard deviation) were $3.7{\pm}3.5mm$ (SE), $0.9{\pm}0.9mm$ (preRE), $1.2{\pm}1.5mm$ (postRE), $1.4{\pm}2.4mm$ (IM1), and $0.9{\pm}1.0mm$ (IM2), and average angular differences were $1.1^{\circ}{\pm}1.2^{\circ}$ (SE), $0.9^{\circ}{\pm}1.1^{\circ}$ (preRE), $0.9^{\circ}{\pm}1.1^{\circ}$ (postRE), $0.6^{\circ}{\pm}0.9^{\circ}$ (IM1), and $0.5^{\circ}{\pm}0.5^{\circ}$ (IM2). The 3D magnitude of SE, preRE, postRE, IM1, and IM2 exceeded 2 mm in 18, 0, 3, 3, and 1 patients, respectively. No association were found between all positional uncertainties and body mass index, pain score, and treatment location (p > 0.05, Mann-Whitney test). There was a tendency of intrafraction motion to increase with overall treatment time; however, the correlation was not statistically significant (p > 0.05, Spearman rank correlation test). Conclusion: In spine SBRT using TM immobilization, CBCT and 4 DoF alignment correction, a minimum residual translational uncertainty was 2 mm. Shortening overall treatment time and 6 DoF positional correction may further reduce positional uncertainties.

• The Research Journal of the Costume Culture
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• v.21 no.2
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• pp.220-233
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• 2013

This study examined regarding the moderating effect of length of relationship in the relationship among the antecedent variables (i.e., specific investment, opportunistic behavior, communication, uncertainty, interdependence, power imbalance, shared value, and flexibility) of trust and commitment, trust and commitment and firm performance and relationship satisfaction. A total of 128 apparel manufacturers participated in this study. Flexibility exerted the most positive effect on trust in short-term relationship, followed by specific investment. And opportunistic behavior was found to exert negative effect on trust. Commitment was found to be most negatively affected by power imbalance, followed by interdependence. Trust was shown to be significantly affected by communication, shared value and flexibility in short-term relationship. In the case of long-term relationship, commitment was shown to be significantly affected by uncertainty, interdependence, power imbalance and flexibility. Firm performance was positively affected by both trust and commitment. As for the effect of trust and commitment on relationship satisfaction, relationship satisfaction was also affected by both trust and commitment. In case the length of relationship, firm performance was affected by both trust and commitment. As for the effect of trust and commitment on relationship satisfaction, relationship satisfaction was also affected by both trust and commitment. The result of this research provides valuable data for making a concrete suggestion regarding the strategy for improving trust and commitment for the sake of the desirable relationship between apparel manufacturers and contractors.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.47-58
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• 2018

In this study, we evaluated the uncertainty in the process of selecting GCM and downscaling method for assessing the impact of climate change, and influence of user-centered climate change information on reproducibility of Chungju Dam inflow was analyzed. First, we selected the top 16 GCMs through the evaluation of spatio-temporal reproducibility of 29 raw GCMs using 30-year average of 10-day precipitation without any bias-correction. The climate extreme indices including annual total precipitation and annual maximum 1-day precipitation were selected as the relevant indices to the dam inflow. The Simple Quantile Mapping (SQM) downscaling method was selected through the evaluation of reproducibility of selected indices and spatial correlation among weather stations. SWAT simulation results for the past 30 years period by considering limitations in weather input showed the satisfactory results with monthly model efficiency of 0.92. The error in average dam inflow according to selection of GCMs and downscaling method showed the bests result when 16 GCMs selected raw GCM analysi were used. It was found that selection of downscaling method rather than selection of GCM is more is important in overall uncertainties. The average inflow for the future period increased in all RCP scenarios as time goes on from near-future to far-future periods. Also, it was predicted that the inflow volume will be higher in the RCP 8.5 scenario than in the RCP 4.5 scenario in all future periods. Maximum daily inflow, which is important for flood control, showed a high changing rate more than twice as much as the average inflow amount. It is also important to understand the seasonal fluctuation of the inflow for the dam management purpose. Both average inflow and maximum inflow showed a tendency to increase mainly in July and August during near-future period while average and maximum inflows increased through the whole period of months in both mid-future and far-future periods.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.329-337
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• 2017

In this study, land-use changes from 1990 to 2010 in Jeju Island by different approaches were produced and compared to suggest a more efficient approach. In a sample-based method, land-use changes were analyzed with different sampling intensities of 2 km and 4 km grids, which were distributed by the fifth National Forest Inventory (NFI5), and their uncertainty was assessed. When comparing the uncertainty for different sampling intensities, the one with the grid of 2 km provided more precise information; ranged from 6.6 to 31.3% of the relative standard error for remaining land-use categories for 20 years. On the other hand, land-cover maps by a wall-to-wall approach were produced by using time-series Landsat imageries. Forest land increased from 34,194 ha to 44,154 ha for 20 years, where about 69% of total forest land were remained as forest land and 19% and 8% within forest lands were converted to grassland and cropland, respectively. In the case of grassland, only about 40% of which were remained as grassland and most of the area were converted to forest land and cropland. When comparing land-cover area by land-use categories with land-use statistics, forest areas were underestimated while areas of cropland and grassland were overestimated. In order to analyze land use change, it is necessary to establish a clear and consistent definition on the six land use classification.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.97-109
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• 2020

On March 11, 2011, an earthquake followed by a tsunami caused an extended station blackout (SBO) at the Fukushima Dai-ichi NPP Units. The accident was initiated by a total loss of both onsite and offsite electrical power resulting in the loss of the ultimate heat sink for several days, and a consequent core melt in some units where proper mitigation strategies could not be implemented in a timely fashion. To enhance the plant's coping capability, the Diverse and Flexible Strategies (FLEX) were proposed to append the Emergency Operation Procedures (EOPs) by relying on portable equipment as an additional line of defense. To assess the success window of FLEX strategies, all sources of uncertainties need to be considered, using a physics-based model or system code. This necessitates conducting a large number of simulations to reflect all potential variations in initial, boundary, and design conditions as well as thermophysical properties, empirical models, and scenario uncertainties. Alternatively, data-driven models may provide a fast tool to predict the success window of FLEX strategies given the underlying uncertainties. This paper explores the applicability of Artificial Intelligence (AI) to identify the success window of FLEX strategy for extended SBO. The developed model can be trained and validated using data produced by the lumped parameter thermal-hydraulic code, MARS-KS, as best estimate system code loosely coupled with Dakota for uncertainty quantification. A Systems Engineering (SE) approach is used to plan and manage the process of using AI to predict the success window of FLEX strategies under extended SBO conditions.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.349-358
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• 2022

This study was aim to understand the relationship between uncertainty, social isolation, social support and resilience of coronavirus infectious diseases-19 (COVID-19) patients and to identify factors related to resilience. Data were carried out from March 7 to May 5, 2021, and a total of 200 questionnaires were used for data analysis. Data were analyzed with descriptive statistics, t-test, ANOVA, Pearson correlation coefficient and multiple regression using SPSS WIN 24.0 program. As a result of the analysis, the lower the sense of social isolation, the higher the social support, the satisfaction with the explanation of isolation and the economic status of 'medium' were identified as related factors for resilience. Based on the above results, a systematic program should be developed and applied to improve the resilience of COVID-19 patients including strengthening social support through families and health care providers, reducing social isolation through non-face-to-face counseling, providing sufficient information about diseases, and providing economic support.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.175-184
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• 2008

Uncertainties are unavoidable in engineering applications. In this paper we propose an alpha reliable multi-variable network design problem under demand uncertainty. In order to decide the optimal capacity enhancement, three performance measures based on 3E(Efficiency, Equity, and Environmental) are considered. The objective is to minimize the total budget required to satisfy alpha reliability constraint of total travel time, equity ratio, and total emission, while considering the route choice behavior of network users. The problem is formulated as the chance-constrained model for application of alpha confidence level and solved as a lexicographic optimization problem to consider the multi-variable. A simulation-based genetic algorithm procedure is developed to solve this complex network design problem(NDP). A simple numerical example ispresented to illustrate the features of the proposed NDP model.

• Journal of the Korean earth science society
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• v.41 no.4
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• pp.323-343
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• 2020

Observation data measured at Ieodo Ocean Research Station (IORS) have been utilized in oceanographic and atmospheric studies since 2003. Sea level data observed at the IORS have not been paid attention as compared with many other variables such as aerosol, radiation, turbulent flux, wind, wave, fog, temperature, and salinity. Total sea level rises at the IORS (5.6 mm yr^-1) from both satellite and tide-gauge observations were higher than those in the northeast Asian marginal seas (5.4 mm yr^-1) and the world (4.6 mm yr^-1) from satellite observation from 2009 to 2018. The rates of thermosteric, halosteric, and steric sea level rises were 2.7-4.8, -0.7-2.6, 2.3-7.4 mm yr^-1 from four different calculating methods using observations. The rising rate of the steric sea level was higher than that of the total sea level in the case with additional data quality control. Calculating the non-steric sea level was not found to yield meaningful results, despite the ability to calculate non-steric sea level by simply subtracting the steric sea level from total sea level. This uncertainty did not arise from the data analysis but from a lack of good data, even though tide, temperature, and salinity data were quality controlled two times by Korea Hydrographic and Oceanography Agency. The status of the IORS data suggests that the maintenance management of observation systems, equipment, and data quality control should be improved to facilitate data use from the IORS.