• Asian Oncology Nursing
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• v.12 no.2
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• pp.139-146
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• 2012

Purpose: This study was designed to identify the impact of uncertainty degree and uncertainty appraisal on cancer patients resilience. Methods: A sample of 181 patients with cancer was recruited from a hospital in Incheon. Data were collected from May 20 to August 25, 2011. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient and multiple regression with the SPSS/WIN 12.0 program. Results: The resilience for cancer patients showed a significant relationship with uncertainty degree and uncertainty appraisal. The significant factors influencing resilience were uncertainty degree and uncertainty appraisal, they explained 26.5% of the variance. Conclusion: Patients with cancer were adversely affected by uncertaint which led to a negative effect on resilience. The result suggests that intervention programs to reduce the level of uncertainty among patients could improve the resilience of cancer patients.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.17-22
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• 2002

A major impediment in using the Dempster-chafer evidence combination scheme is its computational complexity, which in general is exponential since DS scheme allows any subsets over the frame of discernment as focal elements. To avoid this problem, we propose a method called approximate evidence combination scheme. This scheme is applied to a few sample applications and the experiment results are compared with those of VBS. The results show that the approximation scheme achieves a great amount of computational speedup and produces belief values within the range of deviation that the expert allows.

• Journal of the Korean Society of Visualization
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• v.3 no.2
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• pp.71-78
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• 2005

Uncertainty introduced by a cross-correlation algorithm based on FFT has been investigated using PIV standard images. The standard images were generated by the Monte Carlo simulation method. Both bias and random errors from the velocity vector have been analyzed with regard to the particle diameter, displacement, and the number of particles. The uncertainty of velocity is evaluated based upon the IS0/IEC standard. As a result, a total error of $0.26\%$ is included in the PIV cross-correlation algorithm. In addition, the uncertainty budget is presented, where the effect of the above three variables is examined. According to the budget, the variation of the number of particles within the interrogation window mainly contributes to the combined standard uncertainty of the real measured velocity field when excluding the effect of errors by the experiments itself. Finally, the expanded uncertainty is found to be about $12\%$ at the $95\%$ confidence level.