• 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 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.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.3
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• pp.105-117
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• 2001

This paper models supply uncertainty in the dynamic Newsboy problem context. The system consists of one supplier and one retailer who places an order to the supplier every period to meet stochastic demand. Supply uncertainty is modeled as the uncertainty in quantities delivered by the supplier. That is, the supplier delivers exactly the amount ordered by the retailer with probability of $\beta$ and the amount minus K with probability of (1-$\beta$). We formulate the problem as a dynamic programming problem and prove that retailer’s optimal replenishment policy is a stationary base-stock policy. Through a numerical study, we found that the cost increase due to supply uncertainty is significant and that the costs increase more rapidly as supply uncertainty increases. We also identified the effects of various system parameters. One of the interesting results is that as retailer’s demand uncertainty, the other uncertainty in our model, increases, the cost increase due to supply uncertainty becomes less significant.

• 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.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.39-52
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• 2022

This study examines whether accounting conservatism can support real earnings management by reducing accrual earnings management techniques. The net impact of conservative reporting on earnings management is also analyzed. It is assumed that moderating the role of conservative financial reporting during uncertainty can mitigate earnings management practices. For our analysis, 5354 firm-year observations for the period 2007-2020 of nonfinancial companies listed on the Pakistan Stock Exchange are applied. To measure conservatism in the non-financial sector of Pakistan, Khan and Watts' (2009) model is used to provide evidence that conservatism is a way to restrict earnings management during uncertainty. "Prospector" and "Defender" Business strategy is applied for measuring firm-level uncertainty. To measure accrual earnings management Modified Jones (1995) model and Dechow and Dichev (2002) approach and Kasznik (1999) model are applied, and for real earnings management Roychowdhury model is applied which follows three approaches to measure real earnings management i.e. cash flow manipulation, Overproduction, and discretionary expenses. The estimations support our hypothesis by providing statistically significant proof that conservative financial reporting in a developing economy like Pakistan may be used to overcome the net impact of earnings management during uncertainty. Our results provide critical and practical implications for investors, researchers, and standard setters.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.1
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• pp.31-36
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• 2015

There are many uncertainty items when we're working on a software. Especially, if we don't have experience in similar field, ambiguity items have a strong influence on the system entirely. Management of ambiguity items such like uncertainty things is important the factor for reliability of software. Therefore, this research is processing the evaluation criteria for remove of uncertainty items by identify of ambiguity items. Also, this research provides criteria of uncertainty identify and processing of uncertainty items, quantitative evaluation criteria to the remove of ambiguity on software development.

• Journal of the Korea Safety Management & Science
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• v.9 no.1
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• pp.145-156
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• 2007

This paper is to propose model classification and evaluation of measurement uncertainty. In order to obtain type A and B uncertainty, variety of measurement mathematical models are illustrated by example. The four steps to evaluate expanded uncertainty are indicated as following; First, to get type A standard uncertainty, measurement mathematical models of single, double, multiple, design of experiment and serial autocorrelation are shown. Second, to solve type B standard uncertainty measurement mathematical models of empirical probability distributions and multivariate are presented. Third, type A and B combined uncertainty, considering sensitivity coefficient, linearity and correlation are discussed. Lastly, expanded uncertainty, considering degree of freedom for type A, B uncertainty and coverage factor are presented with uncertainty budget. SPC control chart to control expanded uncertainty is shown.

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.419-434
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• 2023

Purpose: Measurement results obtained under non-ideal measurement environment conditions may contain uncertain factors. As a result, the reliability of measurement results may be deteriorated. In this study, we tried to find ways to improve quality by evaluating and applying measurement uncertainty based on GUM. Methods: In the flatness measurement of semiconductor parts, uncertainty factors that could occur under actual environmental conditions of workers were derived, and measurement uncertainties were calculated, and methods for minimizing the main factors affecting the measurement results were analyzed. Results: Depending on the part and the coordinate measuring machine, it was shown that the effect of dispersion caused by repeated measurements as type A uncertainty and the effect of the calibration results of equipment as type B uncertainty have the main influence. Conclusion: Depending on the uncertainty factors of type A and type B and the influence of the total expanded uncertainty, the central value and confidence interval of the initial measurement results showed fluctuations. It is considered that analysis and measures for the main uncertainty factors are needed as quality improvement in the industrial field.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.329-338
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• 1993

The main objective of this paper is analyzing the effects of task uncertainty on EUC characteristics and end user satisfaction. Task uncertainty were identified as an important determinant of EUC characteristics. And the moderating effect of task uncertainty on the relationship between EUC characteristics and end user satisfaction was suggested. A field study was undertaken to test the hypothesized relationships among task uncertainty, EUC characteristics, and end user satisfaction Data were collected from 138 end-user of 19 Korean business organizations. The empirical results indicated that task uncertainty was significantly related to EUC characteristics and that task uncertainty had significant effect on the relationship between EUC characteristics and end user satisfaction. Implications and future research directions are drawn for the management of EUC and for further research on EUC.

• Journal of Korean Society on Water Environment
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• v.22 no.3
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• pp.427-430
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• 2006

Uncertainty is one of the key issues of the water quality management. Uncertainty occurs in the course of all water quality management stages including monitoring, modeling, and regulation enforcement. To reduce uncertainties of water quality monitoring, manualized monitoring methodology should be developed and implemented. In addition, long-term monitoring is essential for acquiring reliable water quality data which enables best water quality management. For the water quality management in the watershed scale, fate of pollutant including its generation, transport and impact should be considered while regarding each stage of water quality management as an unit process. Uncertainties of each stage of water quality management should be treated properly to prevent error propagation transferred to the next stage of management for successful achievement of water quality conservation.