• Journal of Korea Society of Industrial Information Systems
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• v.2 no.2
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• pp.159-179
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• 1997

Traditionally, the evaluation and selection of suppliers have been a major purchasing function. A growing concern for just in-time purchasing, global sourcing, and long-term partnership between buyers and suppliers makes selecting a righ supplier become more critical decision making process. Consequently, a rigorous and systematic method for evaluation suppliers is a must. However, assessing the values of factors(e.g. qulaity , delivery, and service) selected for evaluating suppliers contains elements of uncertainty. Although several methods have been developed for uncertainty analysis, they may not be proper tools for evaluating suppliers under uncertainty. In this paper, a methodology using a fuzzy-set approach in combination with a multicriterion decision-making (MCDM) technique is developed to use as a tool for evaluating suppliers under uncertainty. An numerical example is presented to demonstrate the method in practice.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.415-420
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• 1996

The main objective of the present study is to propose a new measure of uncertainty importance based on distributional sensitivity analysis. The new measure is developed to utilize a metric distance obtained from cumulative distribution functions (cdfs). The measure is evaluated for two cases: one is a cdf given by a known analytical distribution and the other given by an empirical distribution generated by a crude Monte Carlo simulation. To study its applicability, the present measure has been applied to two different cases. The results are compared with those of existing three methods. The present approach is a useful measure of uncertainty importance which is based on cdfs. This method is simple and easy to calculate uncertainty importance without any complex process. On the basis of the results obtained in the present work, the present method is recommended to be used as a tool for the analysis of uncertainty importance.

• Environmental and Resource Economics Review
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• v.27 no.4
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• pp.639-666
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• 2018

This paper analyses the investment options of groundwater development project under water price uncertainty. The optimal investment threshold price which trigger the investment are calibrated base on monopolistic real options model. Stochastic dynamic model is set to reflect the uncertainty of water price which follows the GBM (Geometric Brownian Motion) process. Our finding from non-cooperative investment decision model is that uncertainty of water price could deter the groundwater investment by considering the existence of option values. For policy markers, it is easy to manage 'charges for utilization of groundwater' rather than 'performance guarantee ratio' when managing groundwater investment with pricing policy. And it is necessary to make comprehensive and well-designed policies considering the characteristics of regional groundwater reservoir and groundwater developers.

• Management & Information Systems Review
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• v.31 no.1
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• pp.183-203
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• 2012

This paper investigates how small-medium firms deploy organizational culture, job stability and environmental uncertainty for technological innovation(product and process innovation). This paper suggests that organizational culture has significant effects on technological innovation, that job stability and environmental uncertainty moderate relationship between organizational culture and technological innovation. To test the hypotheses, data were collected from small-medium firms. The survey data of 258 firms were collected and integrated as the empirical base for testing the hypotheses. Major results are as follows: Firstly, when organizational culture as well as control variables are considered, organizational culture had significant and positive effects on product innovation. This result implies that organizational culture is an important means by which small-medium firms can promote innovation. Secondly, the interaction between organizational culture and job stability had a positive and significant effects on product innovation. Thirdly, the interaction between organizational culture and environmental uncertainty had a positive and significant effects on product innovation and process innovation. This paper suggests implications and several future researches need to overcome the limitations of this paper.

• Women's Health Nursing
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• v.21 no.4
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• pp.321-331
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• 2015

Purpose: Purpose of this study was to identify the effect of structured information on immediate preoperative anxiety and uncertainty for women undergoing total laparoscopic hysterectomy. Methods: Sixty women who were admitted for total laparoscopic hysterectomy were recruited at a university hospital in Gyeonggi-do from June to October 2014. Thirty women were assigned to either the experimental or the control group. Women in the experimental group were provided structured information, which consisted of visual and auditory materials about surgical preparation and process, practical experience on devices such as IV-PCA pump and Inspiro-meter and actual experience on route to go to the operating room. State-anxiety, uncertainty, and blood pressure and pulse rate as biological indicators were measured before and after the intervention to examine the effect. Results: Significant group differences were found on state anxiety, uncertainty, including ambiguity, inconsistency, and unpredictability at the holding area. There was a significant difference on pulse rate in the operating room between the two groups. Conclusion: Findings demonstrated that the structured information provided for women undergoing laparoscopic hysterectomy preoperatively was effective on immediate preoperative anxiety and uncertainty. Nurses may contribute to decreasing patients' anxiety and uncertainty by utilizing this structured information preoperatively.

• Nuclear Engineering and Technology
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• v.46 no.5
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• pp.619-632
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• 2014

The Best Estimate Plus Uncertainty (BEPU) method has been widely used to evaluate the uncertainty of a best-estimate thermal hydraulic system code against a figure of merit. This uncertainty is typically evaluated based on the physical model's uncertainties determined by expert judgment. This paper introduces the application of data assimilation methodology to determine the uncertainty bands of the physical models, e.g., the mean value and standard deviation of the parameters, based upon the statistical approach rather than expert judgment. Data assimilation suggests a mathematical methodology for the best estimate bias and the uncertainties of the physical models which optimize the system response following the calibration of model parameters and responses. The mathematical approaches include deterministic and probabilistic methods of data assimilation to solve both linear and nonlinear problems with the a posteriori distribution of parameters derived based on Bayes' theorem. The inverse problem was solved analytically to obtain the mean value and standard deviation of the parameters assuming Gaussian distributions for the parameters and responses, and a sampling method was utilized to illustrate the non-Gaussian a posteriori distributions of parameters. SPACE is used to demonstrate the data assimilation method by determining the bias and the uncertainty bands of the physical models employing Bennett's heated tube test data and Becker's post critical heat flux experimental data. Based on the results of the data assimilation process, the major sources of the modeling uncertainties were identified for further model development.

• Journal of the Microelectronics and Packaging Society
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• v.26 no.1
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• pp.29-33
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• 2019

With shrinking form factor and improving performance of electronic packages, high input/output (I/O) density is considered as an important factor. Fan out wafer-level packaging (FO-WLP) has been paid great attention as an alternative. However, FO-WLP is vulnerable to warpage during its manufacturing process. Minimizing warpage is essential for controlling production yield, and in turn, package reliability. While many studies investigated the effect of process and design parameters on warpage using finite element analysis, they did not take uncertainty into consideration. As parameters, including material properties, chip positions, have uncertainty from the point of manufacturing view, the uncertainty should be considered to reduce the gap between the results from the field and the finite element analysis. This paper focuses on the effect of uncertainty of Young's modulus of chip on fan-out wafer level packaging warpage using finite element analysis. It is assumed that Young's modulus of each chip follows the normal distribution. Simulation results show that the uncertainty of Young's modulus affects the maximum von Mises stress. As a result, it is necessary to control the uncertainty of Young's modulus of silicon chip since the maximum von Mises stress is a parameter related to the package reliability.

• Journal of Environmental Science International
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• v.3 no.4
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• pp.349-356
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• 1994

The purpose of this study is to develop a linear reservoir model with Kalman filter using Kalman filter theory which removes a physical uncertainty of :ainfall-runoff process. A linear reservoir model, which is the basic model of Kalman filter, is used to calculate runoff from rainfall in river basin. A linear reservoir model with Kalman filter is composed of a state-space model using a system model and a observation model. The state-vector of system model in linear. The average value of the ordinate of IUH for a linear reservoir model with Kalman filter is used as the initial value of state-vector. A .linear reservoir model with Kalman filter shows better results than those by linear reserevoir model, and decreases a physical uncertainty of rainfall-runoff process in river basin.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1897-1902
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• 2005

The objective of this paper is to estimate the concentration distribution in flow field inside the pipeline based on electrical impedance tomography. Special emphasis is given to the development of dynamic imaging technique for two-phase field undergoing a rapid transient change. Nonlinearity-compensation extended Kalman filter is employed to cope with unexpected measurement uncertainty. The nonlinearity-compensation extended Kalman filter compensates for the influence of measurement uncertainty and solves the instability of extended Kalman filter. Extensive computer simulations are carried out to show that nonlinearity-compensation extended Kalman filter has enhanced estimation performance especially in the unexpected measurement environment.

• STI Policy Review
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• v.2 no.3
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• pp.35-44
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• 2011

Korea has rapidly increased R&D investment over the last few decades and the intensity of R&D investment is among the highest in the world; however, there are serious concerns about R&D performance and R&D efficiency. This study is to improve the economic assessment methodology regarding a feasibility study for national R&D programs that are thought to be one of the most prominent ways to enhance R&D efficiency. In order to improve the methodology of economic assessment, a few of important factors such as technical or market uncertainty, spillover effect, and R&D contribution ratio should be covered in the model. The focus of this article is technological and market uncertainty that has a close relation with strategic flexibility and utilization potential to increase the value of R&D programs. To improve the current linear and definitive R&D process, a new framework with strategic flexibility is suggested, in which the result of economic assessment that considers technological and market uncertainty is reflected in planning. That kind of feedback process is expected to enhance the value of the program/project as well as R&D efficiency.