• Journal of Korean Academy of Nursing
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• v.49 no.3
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• pp.274-285
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• 2019

Purpose: This study aimed to examine the effects of a mobile navigation program on uncertainty, resilience, and growth through uncertainty in colorectal cancer patients. Methods: To verify the effectiveness of the mobile navigation program, 61 participants diagnosed with colorectal cancer undergoing surgery were selected. A nonequivalent control group nonsynchronized design was used to evaluate the program. Uncertainty was measured using the Korean version of the Uncertainty in Illness Scale, resilience was measured using the Korean version of the Connor-Davidson Resilience Scale, and growth through uncertainty was measured using the Growth through Uncertainty Scale. Results: Compared with the control group, patients in the mobile navigation program group showed significant differences in scores for uncertainty (F=7.22, p=.009) and resilience (F=4.31, p=.042), but not for growth through uncertainty (F=2.76, p=.102). Conclusion: These results suggest that the mobile navigation program has positive effects on decreasing uncertainty and increasing resilience among colorectal cancer patients. The mobile navigation program could play a significant role in assisting colorectal cancer patients in regard to the continuity and usability of the program.

• 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.

• Atmosphere
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• v.25 no.3
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• pp.511-520
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• 2015

Existing studies on radar rainfall uncertainties were performed to reduce the uncertainty for each stage by using bias correction during the quantitative radar rainfall estimation process. However, the studies do not provide quantitative comparison with the uncertainties for all stages. Consequently, this study proposes a suitable approach that can quantify the uncertainties at each stage of the quantitative radar rainfall estimation process. First, the new approach can present initial and final uncertainties, increasing or decreasing the uncertainty, and the uncertainty percentage at each stage. Furthermore, Maximum Entropy (ME) was applied to quantify the uncertainty in the entire process. Second, for the uncertainty quantification of radar rainfall estimation at each stage, this study used two quality control algorithms, two rainfall estimation relations, and two bias correction techniques as post-processing and progressed through all stages of the radar rainfall estimation. For the proposed approach, the final uncertainty (ME = 3.81) from the ME of the bias correction stage was the smallest while the uncertainty of the rainfall estimation stage was higher because of the use of an unsuitable relation. Additionally, the ME of the quality control was at 4.28 (112.34%), while that of the rainfall estimation was at 4.53 (118.90%), and that of the bias correction at 3.81 (100%). However, this study also determined that selecting the appropriate method for each stage would gradually reduce the uncertainty at each stage. Finally, the uncertainty due to natural variability was 93.70% of the final uncertainty. Thus, the results indicate that this new approach can contribute significantly to the field of uncertainty estimation and help with estimating more accurate radar rainfall.

• Korean Journal of Veterinary Research
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• v.47 no.2
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• pp.139-145
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• 2007

Measurement uncertainty could play an important role in the assessment of test results in laboratories and industries. We investigated measurement uncertainties possibly included in determination of flubendazole, a benzimidazole anthelmintic, in pork by HPLC. The concentration of flubendazole was 62.69 ng/g in a sample of pork. Uncertainty was estimated in the analytical procedure of flubendazole. A model equation was made for determination of flubendazole in pork. The four uncertainty components such as weight of sample, volume of sample, calibration curve, and recovery were selected to estimate measurement uncertainties. Standard uncertainty was calculated for each component and all the standard uncertainties were combined. The combined standard uncertainty was expanded to a sample population as an expanded uncertainty. The expanded uncertainty was calculated using k value on Student's t-table and effective degrees of freedom from Welch-Satterthwaite formula. The expanded uncertainty was calculated as 3.45 with the combined standard uncertainty, 1.584 6 and the k value, 2.18. The final expression can be ($62.69{\pm}3.45$) ng/g (confidence level 95%, k = 2.18). The uncertainty value might be estimated differently depending on the selection of the uncertainty components. It is difficult to estimate all the uncertainty factors. Therefore, it is better to take several big effecting components instead of many small effecting components.

• Proceedings of the Safety Management and Science Conference
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• 2005.11a
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• pp.401-404
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• 2005

The ISO 'Guide to the Expression of Uncertainty in Measurement (GUH) establishes a unified method for evaluating uncertainty in measurement worldwide. This paper discusses the concepts and procedures of uncertainty evaluation.

• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.46-50
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• 2013

In insurance statistics, the sum of homogeneous insurance is often needed. The sum is called individual risk model which is a fundamental model in risk analysis for insurance. This paper first presents an individual risk model based on the uncertainty theory. Then its uncertainty distribution is provided. Finally, its arithmetic is shown by a numerical example.

• Research in Community and Public Health Nursing
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• v.13 no.2
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• pp.249-259
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• 2002

Objectives: This study was conducted to investigate the effects of mastery on appraisal of uncertainty in women patients with rheumatoid arthritis. Methods : The study subjects consisted of 168 patients who were recruited from the outpatient clinic of a rheumatic center in Seoul. Self report questionnaires were used to measure the study variables that included uncertainty, mastery, danger appraisal of uncertainty, and opportunity appraisal of uncertainty. Cronbach's alpha reliabilities of these instruments ranged from .72 to .93. For data analysis. the SPSSWIN 10.0 program was utilized to exam descriptive statistics. Pearson's correlation. and regression analysis. Results: The results were as follows.: 1) The uncertainty scores of the subjects ranged from 33 to 87 with the mean score of 63.27. 2) The mastery scores of the subjects ranged from 10 to 27 with a mean score of 18.70. 3) The danger appraisal of uncertainty scores of the subjects ranged from 8 to 32 with a mean score of 20.22. 4) The opportunity appraisal of uncertainty scores of the subjects ranged from 7 to 28 with a mean score of 17.80. 5) Significant factors that explained the danger appraisal of uncertainty were mastery (=-.444. p<.001), and education level (=-.184. p<.05). 6) Significant factor that explained the opportunity appraisal of uncertainty was level of uncertainty (=-.328. p<.001). Conclusion: Among the independent variables. the most significant factor that explained the danger appraisal of uncertainty in the women patients with rheumatoid arthritis was mastery. Therefore, a nursing intervention with strategies to improve sense of mastery should be developed for women patients with rheumatoid arthritis.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.8
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• pp.107-114
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• 2003

The effect of uncertainties caused by measured parameters, which are propagated to the uncertainty of total-to-total efficiency, are analyzed from a turbine performance test. The degree of reaction is 0.373 at the mean radius on a tested 3-D axial type turbine, and the performance test is conducted at the low pressure and cold temperature status. The uncertainty of turbine inlet and exit total pressure shows the strong propagation effect to the uncertainty of total-to-total efficiency. This means that a high precision pressure measuring system is required to reduce the uncertainty propagated by the pressure. In the uncertainty portion of each measured parameters to the uncertainty of total- to-total efficiency, the uncertainty by torque is the highest and the uncertainty by RPM is the lowest. In case of the total pressure, the effect of the uncertainty by torque is increased with the increasing RPM. The uncertainty of total pressure at the turbine exit is more important than that at the turbine exit.

• Bulletin of the Korean Chemical Society
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• v.34 no.8
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• pp.2394-2398
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• 2013

Nicotine is the main component of environmental tobacco smoke, and its presence in indoor air is widely used as a secondhand-smoke indicator. Environmental tobacco smoke is a major source of indoor air pollution, but sufficient investigation of the uncertainty of its measurement, which mirrors the reliability of nicotine measurement, has not been performed. We calculated the uncertainty of measurement of indoor air nicotine concentration at low, medium, and high concentrations of 11.3798, 10.1977, $98.3768{\mu}g/m^3$, respectively, and we employed the Guide to the Expression of Uncertainty in Measurements (GUM), proposed by the International Organization for Standardization (ISO). The factors considered in determining the uncertainty were uncertainty of the calibration curve (calibration curve and repeated measurements), desorption efficiency, extraction volume, and sampling airflow (accuracy and acceptable limits of flowmeter). The measurement uncertainty was highest at low concentrations; the expanded measurement uncertainty is $0.9435{\mu}g/m^3$ and is represented as a relative uncertainty of 63.38%. At medium and high (concentrations, the relative uncertainty was 13.1% and 9.1%, respectively. The uncertainty of the calibration curve was largest for low indoor nicotine concentrations. To increase reliability of measurement in assessing the effect of secondhand smoke, measures such as increasing the sample injection rate ($1{\mu}L$ or more), increasing sampling volume to increase collected nicotine, and using gas chromatography-mass spectrometry (GC/MS) or GC/MS/MS, which has a lower quantitation threshold, rather than gas chromatography with nitrogen phosphorous detector, should be considered.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.155-155
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• 2018

Uncertainty in flood forecasting using a coupled meteorological and hydrological model is arisen from various sources, especially the uncertainty comes from the inaccuracy of Quantitative Precipitation Forecasts (QPFs). In order to improve the capability of flood forecast, the uncertainty estimation and mitigation are required to perform. This study is conducted to investigate and reduce such uncertainty. First, ensemble QPFs are generated by using Monte - Carlo simulation, then each ensemble member is forced as input for a hydrological model to obtain ensemble streamflow prediction. Likelihood measures are evaluated to identify feasible member. These members are retained to define upper and lower limits of the uncertainty interval and assess the uncertainty. To mitigate the uncertainty for very short lead time, a blending method, which merges the ensemble QPFs with radar-based rainfall prediction considering both qualitative and quantitative skills, is proposed. Finally, blending bias ratios, which are estimated from previous time step, are used to update the members over total lead time. The proposed method is verified for the two flood events in 2013 and 2016 in the Yeonguol and Soyang watersheds that are located in the Han River basin, South Korea. The uncertainty in flood forecasting using a coupled Local Data Assimilation and Prediction System (LDAPS) and Sejong University Rainfall - Runoff (SURR) model is investigated and then mitigated by blending the generated ensemble LDAPS members with radar-based rainfall prediction that uses McGill algorithm for precipitation nowcasting by Lagrangian extrapolation (MAPLE). The results show that the uncertainty of flood forecasting using the coupled model increases when the lead time is longer. The mitigation method indicates its effectiveness for mitigating the uncertainty with the increases of the percentage of feasible member (POFM) and the ratio of the number of observations that fall into the uncertainty interval (p-factor).