• Journal of Korean Academy of Nursing
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• v.45 no.2
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• pp.271-279
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• 2015

Purpose: This study was done to examine the relation of uncertainty, uncertainty appraisal, and self-management in patients undergoing hemodialysis, and to identify factors influencing self-management. Methods: A convenience sample of 92 patients receiving hemodialysis was selected. Data were collected using a structured questionnaire and medical records. The collected data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlations and multiple regression analysis with the SPSS/WIN 20.0 program. Results: The participants showed a moderate level of uncertainty with the highest score being for ambiguity among the four uncertainty subdomains. Scores for uncertainty danger or opportunity appraisals were under the mid points. The participants were found to perform a high level of self-management such as diet control, management of arteriovenous fistula, exercise, medication, physical management, measurements of body weight and blood pressure, and social activity. The self-management of participants undergoing hemodialysis showed a significant relationship with uncertainty and uncertainty appraisal. The significant factors influencing self-management were uncertainty, uncertainty opportunity appraisal, hemodialysis duration, and having a spouse. These variables explained 32.8% of the variance in self-management. Conclusion: The results suggest that intervention programs to reduce the level of uncertainty and to increase the level of uncertainty opportunity appraisal among patients would improve the self-management of hemodialysis patients.

• Journal of Environmental Health Sciences
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• v.41 no.6
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• pp.425-437
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• 2015

Objectives: Risk assessment is a tool for predicting and reducing uncertainty related to the effects of future activities. Probability approaches are the main elements in risk assessment, but confusion about the interpretation and use of assessment factors often undermines the message of the analyses. The aim of this study is to provide a guideline for systematic reduction plans regarding uncertainty in risk assessment. Methods: Articles and reports were collected online using the key words "uncertainty analysis" on risk assessment. Uncertainty analysis was conducted based on reports focusing on procedures for analysis methods by the World Health Organization (WHO) and U.S. Environmental Protection Agency (USEPA). In addition, case studies were performed in order to verify suggested methods qualitatively and quantitatively with exposure data, including measured data on toluene and styrene in residential spaces and multi-use facilities. Results: Based on an analysis of the data on uncertainty, three major factors including scenario, model, and parameters were identified as the main sources of uncertainty, and tiered approaches were determined. In the case study, the risk of toluene and styrene was evaluated and the most influential factors were also determined. Five reduction plans were presented: providing standard guidelines, using reliable exposure factors, possessing quality controls for analysis and scientific expertise, and introducing a peer review system. Conclusion: In this study, we established a method for reducing uncertainty by taking into account the major factors. Also, we showed a method for uncertainty analysis with tiered approaches. However, uncertainties are difficult to define because they are generated by many factors. Therefore, further studies are needed for the development of technical guidelines based on the representative scenario, model, and parameters developed in this study.

• Journal of Korean Society on Water Environment
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• v.29 no.5
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• pp.681-690
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• 2013

Watershed models have been increasingly used to support an integrated management of land and water, non-point source pollutants, and implement total daily maximum load policy. However, these models demand a great amount of input data, process parameters, a proper calibration, and sometimes result in significant uncertainty in the simulation results. For this reason, uncertainty analysis is necessary to minimize the risk in the use of the models for an important decision making. The objectives of this study were to evaluate three different uncertainty analysis algorithms (SUFI-2: Sequential Uncertainty Fitting-Ver.2, GLUE: Generalized Likelihood Uncertainty Estimation, ParaSol: Parameter Solution) that used to analyze the sensitivity of the SWAT(Soil and Water Assessment Tool) parameters and auto-calibration in a watershed, evaluate the uncertainties on the simulations of runoff and sediment load, and suggest alternatives to reduce the uncertainty. The results confirmed that the parameters which are most sensitive to runoff and sediment simulations were consistent in three algorithms although the order of importance is slightly different. In addition, there was no significant difference in the performance of auto-calibration results for runoff simulations. On the other hand, sediment calibration results showed less modeling efficiency compared to runoff simulations, which is probably due to the lack of measurement data. It is obvious that the parameter uncertainty in the sediment simulation is much grater than that in the runoff simulation. To decrease the uncertainty of SWAT simulations, it is recommended to estimate feasible ranges of model parameters, and obtain sufficient and reliable measurement data for the study site.

• Architectural research
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• v.8 no.2
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• pp.27-36
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• 2006

Structural uncertainties are generally modeled using probabilistic approaches in order to quantify uncertainties in behaviors of structures. This uncertainty results from the uncertainties of structural parameters. Monte Carlo methods have been usually carried out for analyses of uncertainty problems where no analytical expression is available for the forward relationship between data and model parameters. In such cases any direct mathematical treatment is impossible, however the forward relation materializes itself as an algorithm allowing data to be calculated for any given model. This study addresses a new method which is utilized as a basis for the uncertainty estimates of structural responses. It applies double uniform random numbers (i.e. DURN technique) to conventional Monte Carlo algorithm. In DURN method, the scenarios of uncertainties are sequentially selected and executed in its simulation. Numerical examples demonstrate the beneficial effect that the technique can increase uncertainty degree of structural properties with maintaining structural stability and safety up to the limit point of a breakdown of structural systems.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.285-292
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• 2024

When calculating sonar detection probability, underwater acoustic uncertainty is assumed to be normal distributed with a standard deviation of 8 dB to 9 dB. However, due to the variability in experimental areas and ocean environmental conditions, predicting detection performance requires accounting for underwater acoustic uncertainty based on ocean experimental data. In this study, underwater acoustic uncertainty was determined using measured mid-frequency (2.3 kHz, 3 kHz) noise level and transmission loss data collected in the shallow water of the East Sea. After calculating the predictable probability of detection reflecting underwater acoustic uncertainty based on ocean experimental data, we compared it with the conventional detection probability results, as well as the predictable probability of detection results considering the uncertainty of the Rayleigh distribution and a negatively skewed distribution. As a result, we confirmed that differences in the detection area occur depending on each underwater acoustic uncertainty.

• Journal of muscle and joint health
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• v.23 no.2
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• pp.114-124
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• 2016

Purpose: The purpose of this study was to investigate the level of uncertainty, physiological risk factors, self-efficacy, and self-management among stroke patients and to identify factors influencing their self-management. Methods: A descriptive correlational design was used for this study. A convenience sample of 149 patients with stroke were enrolled at C national university hospital from February to April in 2016. Data were collected using a structured questionnaire and electronic medical record. Collected data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlations, and multiple regression analysis with the SPSS/WIN 21.0 program. Results: There were significant negative correlations between uncertainty and self-efficacy (r=-.56, p<.001); between uncertainty and self-management (r=-.56, p<.001); and between total cholesterol and self-management (r=-.23, p=.005). There were significant positive correlations between self-efficacy and self-management (r=.78, p<.001); between uncertainty and total cholesterol (r=.24, p=.003). The significant factors influencing self-management were uncertainty and self-efficacy. Theses variables explained 62.7% of the variance in self-management. Conclusion: The results suggest that intervention programs to reduce the level of uncertainty and to increase the level of self-efficacy among patients would improve the self-management of stroke patients.

• Women's Health Nursing
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• v.11 no.4
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• pp.316-323
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• 2005

Purpose: The purpose of this study was to explore the relationships among women's total symptom distress, uncertainty and quality of life in women with endometriosis. Method: A total of 121 women who had been diagnosed with endometriosis was given a questionnaire. Data was collected from August 2004 to January 2005. The data was analyzed by frequency, mean, t-test, ANOVA, Pearson correlation coefficient, and multiple linear regression analysis using SPSS WIN 10.0 software. Result: The mean score of TSD was 3.23. 'Menstrual cramping' showed the highest score. The mean score of uncertainty, and quality of life of the subject was 56.6, and 38.3 respectively. TSD was significantly related with coffee intake and uncertainty was significantly related with marital status, economic status, alcohol intake, diagnosis after period, and family history. Quality of life was significantly related with age, and dysmenorrhea. There were significant relationships between total symptom distress and uncertainty, and quality of life. There were significant relationship between uncertainty and quality of life. Conclusion: Endometriosis symptoms showed a significant relationship with uncertainty and quality of life. This study will help to manage women with endometriosis.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.137-137
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• 2022

Evaluating interpolated rainfall uncertainty of hydrological models caused by different interpolation methods for basins where can not fully collect rainfall data are necessary. In this study, the adaptive MCMC method under effects of ILFs was used to analyze the interpolated rainfall uncertainty of the SURR model for Gunnam basin, Korea. Three events were used to calibrate and one event was used to validate the posterior distributions of unknown parameters. In this work, the performance of four ILFs on uncertainty of interpolated rainfall was assessed. The indicators of p_factor (percentage of observed streamflow included in the uncertainty interval) and r_factor (the average width of the uncertainty interval) were used to evaluate the uncertainty of the simulated streamflow. The results showed that the uncertainty bounds illustrated the slight differences from various ILFs. The study confirmed the importance of the likelihood function selection in the application the adaptive Bayesian MCMC method to the uncertainty assessment of the SURR model caused by interpolated rainfall.

• Journal of the Korean Solar Energy Society
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• v.31 no.3
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• pp.89-94
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• 2011

In this study, we measured the wind data as new and renewable energy resources and carried out the evaluation of uncertainty about these data with the authentic standards. These data collected at the 20 locations in korea. We carried out the processing and evaluation about these data with standards as ISO, GUM, and IEC. Whereby these data become standards data and the credibility are gained. These data include some information as direction, humidity, pressure, temperature, and energy density. The annual average of wind speed(in Hamo) was measured as 9.5m/s, then the uncertainty was evaluated as ${\pm}0.88m/s$. We judge the credibility of data by expression of reliability quantitatively. In additional, the standards data is able to approach anywhere and it will be used to support of related research and industry.

• Child Health Nursing Research
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• v.2 no.2
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• pp.5-18
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• 1996

The purposes of this study were to measure the degree of perceived uncertainty and to identify the rearing attitudes of mothers with chronically ill children, and to examine the relationship between the perceived uncertainty and the rearing attitude of these mothers. The subjects of this study consisted of 133 mothers with chronically ill children, registered at 2 university hospitals in Seoul. Data was collected from April 1 to May 31, 1996. The Parents' Perception of Uncertainty Scale(28-item 4 point scale) and the Maternal Behavior Research Instrument (49-item 5 point scale) were used. Data was analyzed by Cluster analysis, ANOVA MANOVA and t-test. Results of this study are summarized as follows : 1. Mothers perceived their uncertainty to be slightly high (Mn 2.48). The degree of perceived uncertainty by the four components slightly differed unpredictability(2.72), lack in clarity(2.58), vagueness (2.52) and lack of information(2.04) . The degree of perceived uncertainty of mothers with ill children revealed to be influenced significantly by the age of the ill children, duration of illness after the diagnosis, and the experience of hospitalization. 2. Among the rearing attitudes : moderatlely high affective(Mn 3.98) and resrictive(Mn 3.58) attitudes of mothers toward their ill children were identified. Mothers tend to give positive evaluations of their childrens' behaviors (Mn 3.38) and less rejection(Mn 2.81). 3. Mothers' rearing attitude were correlated with the degree of perceived uncertainty in illness ; mothers in the Low Perceived Uncertainty Group (Mn 1.99) revealed the highest affective (Mn 4.08), the lowest resrictive(Mn. 2.72) attitudes and tendency to give positive evaluations of their childrens' behaviors (Mn 3.54) compared to the High Perceived Uncertainty Group(Mn 3.26) and Moderate Perceived Uncertaity Group(Mn 2.57). 4. The degree of perceived uncertainty, the duration of illness after the diagnosis and the experience of hospitalization revealed to be significantly influential to the rearing attitude of mothers with chronically ill children. From the above results, it can be concluded that predicting and controlling mothers' uncertainty are necessary for improved, efficient nursing interventions and normal growth & development of the chronically ill children.