• Asian Oncology Nursing
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• v.7 no.2
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• pp.107-118
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• 2007

Purpose: The purpose of this study was to provide the basic data for development of nursing intervention to decrease the uncertainty in cancer patients having chemotherapy through promoting their spiritual health and identifying the relationship between spiritual health and uncertainty. Method: 174 cancer patients who were admitted for chemotherapy at hospital were recruited from the 7th March to the 10th April, 2006. Two instruments have been used for this study. One was Highfield's Spiritual Health Inventory and the other was Mishel's MUIS(Mishel Uncertainty in Illness Scale). The collected data was analyzed by frequency, percentage, mean value, average mean, standard deviation, t-test, Scheffe's test, ANOVA and Pearson Correlation Coefficients with the SPSS PC 12.0 program. Results: The average mean value of the spiritual health $3.50{\pm}\;.48$ and the uncertainty was $1.91{\pm}\;.46$. It meant that the relationships between spiritual health and uncertainty were shown to have a moderately negative correlation(r=-.489, p= .000). This means that the greater is the spiritual health, the less is the patient's uncertainty. Conclusions: It was identified that cancer patients having chemotherapy had moderate spiritual health and uncertainty, and negative correlation between spiritual health and uncertainty. Therefore, it will be necessary for the development of spiritual nursing intervention strategies to relieve the uncertainty among cancer patients having chemotherapy.

• Korean Parent-Child Health Journal
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• v.10 no.2
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• pp.136-146
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• 2007

Purpose: The purpose of this study was to provide fundamental data in ensuring a high quality of nursing needed by hospitalized child's mother through research of the mother's perception of uncertainty and nursing need concerning child's hospitalization. Method: 173 hospitalized child's mothers at G hospital in Busan are questioned. The tools used in this study are PPUS(Parent's Perception of Uncertainty Scale) and the nursing need of hospitalized children's mother. The data was analyzed by SPSS/PC program. Results: 1) The perception of total uncertainty for the hospitalized child's mother showed average 2.37 and the nursing need showed very high level, 3.37. 2) The perception of uncertainty in accordance with general character of the hospitalized child's mother shows non significant difference 3) Significant correlation indicated between the perception of uncertainty of hospitalized children's mother and nursing need. Conclusion: It is to be desired to prepare a program which can raise the level of perception developing a method that is able to practically assess and manage the level of perception of hospitalized children's mother.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.2803-2815
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• 2021

This paper addresses the uncertainty quantification and sensitivity analysis of a depleted light-water fuel assembly of the Turkey Point-3 benchmark. The uncertainty of the fuel assembly decay heat and isotopic densities is quantified with respect to three different groups of diverse parameters: nuclear data, assembly design, and reactor core operation. The uncertainty propagation is conducted using a two-step analysis code system comprising the lattice code STREAM, nodal code RAST-K, and spent nuclear fuel module SNF through the random sampling of microscopic cross-sections, fuel rod sizes, number densities, reactor core total power, and temperature distributions. Overall, the statistical analysis of the calculated samples demonstrates that the decay heat uncertainty decreases with the cooling time. The nuclear data and assembly design parameters are proven to be the largest contributors to the decay heat uncertainty, whereas the reactor core power and inlet coolant temperature have a minor effect. The majority of the decay heat uncertainties are delivered by a small number of isotopes such as ²⁴¹Am, ¹³⁷Ba, ²⁴⁴Cm, ²³⁸Pu, and ⁹⁰Y.

• Journal of The Korean Association For Science Education
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• v.31 no.1
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• pp.115-127
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• 2011

Analysis frame for undergraduate physics laboratory reports in collecting, processing, and analyzing data was developed. Using the frame and questionaries, we analyzed what difficulties students have in the concepts of error and uncertainty in writing laboratory reports. Students considered repetitive measurement for collecting data, but they didn't express it distinctly in their reports. They also had difficulties in measuring data around the extreme value or the large slope. Especially, most students have had difficulties with error and uncertainty. They can't apply the basic formulation to propagation of error and uncertainty. They also had the difficulties in analyzing data with concepts of error and uncertainty. While most students responded that error and uncertainty is important, there were few students who analyzed the influence of the cause of error on the results quantitatively. The result of the study showed that students have difficulties in writing the laboratory reports because they didn't have the correct concept of the error and uncertainty. So, it is needed to not only teach the physics concept about experiment but to teach basic concept of data collecting, processing, and analyzing specially about error and uncertainty for students as well.

• Journal of Distribution Science
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• v.9 no.2
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• pp.123-129
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• 2011

The restaurant franchise industry is one that could benefit significantly from the use of intranet technology, from its potential for improving communications between franchisors and franchisees, to providing easier inventory and ordering processes. However, there is a level of trepidation among potential users about whether the technology would improve their work performance. This study sought to examine the relationships between perceived uncertainty and perceived usefulness of intranet technology in the restaurant franchise industry. Through a review of available literature, 10 sub-dimensions of perceived uncertainty (Duncan, 1972) and six sub-dimensions of perceived usefulness (Davis, 1989) were derived. Canonical correlation analysis was used to examine the relationships between these concepts using data collected from 163 franchising restaurant managers in South Korea. Findings from the data analysis demonstrates two negative factors and one positive factor in perceived uncertainty that influence perceived usefulness, thus offering some implications of what to consider when implementing an intranet system in a restaurant franchise.

• Journal of Information Technology Applications and Management
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• v.15 no.1
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• pp.43-65
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• 2008

This study investigates the effects of business environment on the e-business strategy and performance of venture firms. The development of the research model is based on the empirical studies on the strategy literature. The data from the survey was analyzed using Partial Least Squares(PLS). For Daedeok Valley Venture Firms, product innovation differentiation strategy is affected by environmental uncertainty. And, cost leadership strategy tend to be influence by environmental uncertainty. Finally, venture firm's performance is effected by cost leadership strategy and marketing differentiation strategy. However, for in Hsinchu Science Park Venture Firms, product innovation differentiation strategy is affected by environmental uncertainty and heterogeneity. And, marketing differentiation strategy is enhanced by environment uncertainty and industry growth. In addition, cost leadership strategy tend to be influence by environmental uncertainty and heterogeneity. Finally, venture firm's performance is effected by cost leadership strategy and product innovation differentiation strategy.

• Structural Engineering and Mechanics
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• v.46 no.3
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• pp.433-445
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• 2013

Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.

• Nuclear Engineering and Technology
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• v.46 no.3
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• pp.313-342
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• 2014

A Nuclear Energy Agency (NEA), Organization for Economic Co-operation and Development (OECD) benchmark for Uncertainty Analysis in Modeling (UAM) is defined in order to facilitate the development and validation of available uncertainty analysis and sensitivity analysis methods for best-estimate Light water Reactor (LWR) design and safety calculations. The benchmark has been named the OECD/NEA UAM-LWR benchmark, and has been divided into three phases each of which focuses on a different portion of the uncertainty propagation in LWR multi-physics and multi-scale analysis. Several different reactor cases are modeled at various phases of a reactor calculation. This paper discusses Phase I, known as the "Neutronics Phase", which is devoted mostly to the propagation of nuclear data (cross-section) uncertainty throughout steady-state stand-alone neutronics core calculations. Three reactor systems (for which design, operation and measured data are available) are rigorously studied in this benchmark: Peach Bottom Unit 2 BWR, Three Mile Island Unit 1 PWR, and VVER-1000 Kozloduy-6/Kalinin-3. Additional measured data is analyzed such as the KRITZ LEU criticality experiments and the SNEAK-7A and 7B experiments of the Karlsruhe Fast Critical Facility. Analyzed results include the top five neutron-nuclide reactions, which contribute the most to the prediction uncertainty in keff, as well as the uncertainty in key parameters of neutronics analysis such as microscopic and macroscopic cross-sections, six-group decay constants, assembly discontinuity factors, and axial and radial core power distributions. Conclusions are drawn regarding where further studies should be done to reduce uncertainties in key nuclide reaction uncertainties (i.e.: $^{238}U$ radiative capture and inelastic scattering (n, n') as well as the average number of neutrons released per fission event of $^{239}Pu$).

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.208-208
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• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.

• Journal of Korea Water Resources Association
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• v.42 no.10
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• pp.773-783
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• 2009

The effects of rainfall input uncertainty on predictions of stream flow are studied based extended GLUE (Generalized Likelihood Uncertainty Estimation) approach. The uncertainty in the rainfall data is implemented by systematic/non-systematic rainfall measurement analysis in Weida catchment, Germany. PDM (Probability Distribution Model) rainfall runoff model is selected for hydrological representation of the catchment. Using general correction procedure and DUE(Data Uncertainty Engine), feasible rainfall time series are generated. These series are applied to PDM in MC(Monte Carlo) and GLUE method; Posterior distributions of the model parameters are examined and behavioural model parameters are selected for simplified GLUE prediction of stream flow. All predictions are combined to develop ensemble prediction and 90 percentile of ensemble prediction, which are used to show the effects of uncertainty sources of input data and model parameters. The results show acceptable performances in all flow regime, except underestimation of the peak flows. These results are not definite proof of the effects of rainfall uncertainty on parameter estimation; however, extended GLUE approach in this study is a potential method which can include major uncertainty in the rainfall-runoff modelling.