• The Journal of Korean Medicine
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• v.38 no.4
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• pp.55-61
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• 2017

Objectives: In order to accurately measure skin moisture and accumulate normal skin moisture data, analyzing the uncertainty of the skin moisture measurement and establishing standard reference data is essential. It helps to evaluate the skin's condition and has great significance in diagnosis and treatment. In this study, the traceability of the equipment and the uncertainty of the results were analyzed for their potential use in the field of Korean medicine. The data was collected measuring skin moisture on the sole of the foot. Methods: One professional measured the moisture of the adult male's foot 10 times following a determined protocol. The standard uncertainty of repeated measurements was calculated from the mean value of 10 repeated measurements. Ten trainee participants also measured the adult male's foot following a determined protocol. The standard uncertainty by tester was calculated from the value of repeated measurements. Results: As a result of analyzing the difference between the mean and standard uncertainties in both the expert and trainees, it was confirmed that the variance in this study did not satisfy the normal distribution. In addition, the Mann-Whitney U-test was carried out, and it was found that there was no significant difference in the measured values of the two groups. The authorized uncertainty of measurements and traceability of all the equipment was not confirmed. Conclusions: This paper establishes the basis for later measurement-equipment research to provide the objective indicators to approach the dryness of plantar skin from dehydration, the Korean medicine perspective.

• Journal of Korea Game Society
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• v.18 no.1
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• pp.105-114
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• 2018

Various data analysis methods used for customer type analysis are very important for game companies to understand their type and characteristics in an attempt to plan customized content for our customers and to provide more convenient services. In this paper, we propose a k-mode cluster analysis algorithm that uses information uncertainty by extending information entropy to reduce information loss. Therefore, the measurement of the similarity of attributes is considered in two aspects. One is to measure the uncertainty between each attribute on the center of each partition and the other is to measure the uncertainty about the probability distribution of the uncertainty of each property. In particular, the uncertainty in attributes is taken into account in the non-probabilistic and probabilistic scales because the entropy of the attribute is transformed into probabilistic information to measure the uncertainty. The accuracy of the algorithm is observable to the result of cluster analysis based on the optimal initial value through extensive performance analysis and various indexes.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.117-127
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• 2009

This study analyzed the uncertainty of the forecasted link traffic flow, and estimated of the interval link flow using Korea Transport Data Base (KTDB) to consider those risks into the feasibility study. In the paper, the uncertainty was analyzed according to the stochastic variation of the KTDB origin-destination traffic. It was found that the uncertainty of the entire network traffic forecasts was 15.4% in average,. when the stochastic variation of the KTDB was considered. The results showed that the more congested the roads were, the bigger the uncertainty of forecasted link traffic flow were found. In particular, we estimated the variance of the forecasted traffic flow, and suggested interval estimates of the forecasted traffic flow instead of point estimates which were presented in the common feasibility studies. These results are expected to contribute the quantitative evaluation of uncertain road investment projects and to provide valuable information to the decision makers for the transport investment.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.85-110
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• 2008

Ground investigation data to be used as a basis for geotechnical analysis and foundation design are usually troubled with large uncertainty, due to natural variability and limited number of data. Statistical methods can be a rational tool for handling such uncertain ground data, in particular with a view to the selection of characteristic values for estimating ground design parameters used in design. The characteristic values of soil properties for use in geotechnical design have oftenly based on not only a subjective judgment but also engineer's past acumulated experience. This paper discussed some statistical methods which can handle such intrinsic ground uncertainty data with a case design in a rational manner.

• The KSFM Journal of Fluid Machinery
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• v.14 no.1
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• pp.42-47
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• 2011

Measurement uncertainty analysis of fuel flow using turbine flowmeter was performed for the case of altitude engine test. SAE ARP4990 was used as the fuel flow calculation procedure, as well as the mathematical model for the measurement uncertainty assessment. The assessment was performed using Sensitivity Coefficient Method. 11 parameters involved in the calculation of the flow rate were considered. For the given equipment setup, the measurement uncertainty of fuel flow was assessed in the range of 1.19~1.86 % for high flow rate case, and 1.47~3.31 % for low flow rate case. Fluctuation in frequency signal from the flowmeter had the largest influence on the fuel flow measurement uncertainty for most cases. Fuel temperature measurement had the largest for the case of low temperature and low flow rate. Calibration of K-factor and the interpolation of the calibration data also had large influence, especially for the case of very low temperature. Reference temperature, at which the reference viscosity of the sample fuel was measured, had relatively small contribution, but it became larger when the operating fuel temperature was far from reference temperature. Measurement of reference density had small contribution on the flow rate uncertainty. Fuel pressure and atmospheric pressure measurement had virtually no contribution on the flow rate uncertainty.

• Journal of muscle and joint health
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• v.19 no.3
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• pp.294-307
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• 2012

Purpose: The purpose of this study is to identify main factors affecting patients' uncertainty following lumbar spinal surgery. Methods: A survey was conducted of a sample 155 post -operative patients in April to June 2010. Uncertainty and knowledge about self-care after spinal surgery and the back pain evaluation were measured. Data were analyzed with t-test, ANOVA, Pearson correlation, and multiple regressions. Results: The mean score of uncertainty level was $27.66{\pm}6.32$. Levels of uncertainty were different by age, gender, educational level, pain duration, and number of types of pain. Uncertainty was positively correlated with knowledge of post-op self-care, back pain, and mental health. The results of multiple regression indicated that knowledge of post-op self-care and mental health were significant predictors with 35.1% of the variance in uncertainty. Conclusion: A program including post-operative self-care education and mental health promotion is required to reduce uncertainty of patients with lumbar spinal surgery.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.20 no.1
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• pp.32-38
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• 2024

The best estimate plus uncertainty methodologies for loss-of-coolant accident analyses make use of the best-estimate codes and relevant experimental databases. Inherently, best-estimate codes have various uncertainties in the model parameters, which can be quantified by the dedicated experimental database. Therefore, this study was devoted to establishing procedures for identifying the input parameters of predictive models and quantifying their uncertainty ranges. The rod bundle heat transfer experiments were employed as a representative reflood separate effect test, and the TRACE code was utilized as a best-estimate code. In accordance with the present procedure for uncertainty quantification, the integrated list of the influential input parameters and their uncertainty ranges was obtained through local sensitivity calculations and screening criteria. The validity of the procedure was confirmed by applying it to uncertainty analyses, which checks whether the measured data are within computed ranges of the variables of interest. The uncertainty quantification procedure proposed in this study is anticipated to provide comprehensive guidance for the conduct of uncertainty analyses.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.233-238
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• 2016

In this paper, we propose the algorithms of processing the uncertainty data using data fusion for the next generation intrusion detection. In the next generation intrusion detection, a lot of data are collected by many of network sensors to discover knowledge from generating information in cyber space. It is necessary the data fusion process to extract knowledge from collected sensors data. In this paper, we have proposed method to represent the uncertainty data, by classifying where is a confidence interval in interval of uncertainty data through feature analysis of different data using inference method with Dempster-Shafer Evidence Theory. In this paper, we have implemented a detection experiment that is classified by the confidence interval using IRIS plant Data Set for anomaly detection of uncertainty data. As a result, we found that it is possible to classify data by confidence interval.

• Structural Engineering and Mechanics
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• v.63 no.1
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• pp.47-53
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• 2017

The fundamental goal of this study is to minimize the uncertainty of the median fragility curve and to assess the structural vulnerability under earthquake excitation. Bayesian Inference with Markov Chain Monte Carlo (MCMC) simulation has been presented for efficient collapse response assessment of the independent intake water tower. The intake tower is significantly used as a diversion type of the hydropower station for maintaining power plant, reservoir and spillway tunnel. Therefore, the seismic fragility assessment of the intake tower is a pivotal component for estimating total system risk of the reservoir. In this investigation, an asymmetrical independent slender reinforced concrete structure is considered. The Bayesian Inference method provides the flexibility to integrate the prior information of collapse response data with the numerical analysis results. The preliminary information of risk data can be obtained from various sources like experiments, existing studies, and simplified linear dynamic analysis or nonlinear static analysis. The conventional lognormal model is used for plotting the fragility curve using the data from time history simulation and nonlinear static pushover analysis respectively. The Bayesian Inference approach is applied for integrating the data from both analyses with the help of MCMC simulation. The method achieves meaningful improvement of uncertainty associated with the fragility curve, and provides significant statistical and computational efficiency.

• Journal of Information Technology Applications and Management
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• v.11 no.2
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• pp.15-27
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• 2004

Most software projects inevitably involve various types and degrees of uncertainty. Without proper risk assessment and coordination, software projects can easily run out of control and consume significant additional resource. Thus, risk management techniques are critical issues to information system researchers. Previous empirical studies of U.S. software firms support the adoption of development standardization and user requirement analysis techniques in risk-based software project management. Using data collected from software projects developed in Korea during 1999-2000, we conduct a comparative study to determine how risk management strategies impact software product and process performance in countries with dissimilar IT capabilities. In addition, we offer an alternative conceptualization of residual performance risk. We show that the use of residual performance risk as an intervening variable is inappropriate in IT developing countries like Korea where the role of late stage risk control remedies are critical. A revised model is proposed that generates more reliable empirical implications for Korean software projects.