• Tunnel and Underground Space
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• v.15 no.4 s.57
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• pp.275-287
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• 2005

At the planning and design stages of a development of underground space or tunneling project, the information regarding ground conditions is very important to enhance economical efficiency and overall safety In general, the information can be expressed using RMR or Q-system and with the geophysical exploration image. RMR or Q-system can provide direct information of rock mass in a local scale for the design scheme. Oppositely, the image of geophysical exploration can provide an exthaustive but indirect information. These two types of the information have inherent uncertainties from various sources and are given in different scales and with their own physical meanings. Recently, RMR has been estimated in unsampled areas based on given data using geostatistical methods like Kriging and conditional simulation. In this study, simulated annealing(SA) is applied to overcome the shortcomings of Kriging methods or conditional simulations just using a primary variable. Using this technique, RMR and the image of geophysical exploration can be integrated to construct the spatial distribution of RM and to evaluate its uncertainty. The SA method was applied to solve an optimization problem with constraints. We have suggested the practical procedure of the SA technique for the uncertainty evaluation of RMR and also demonstrated this technique through an application, where it was used to identify the spatial distribution of RMR and quantify the uncertainty. For a geotechnical application, the objective functions of SA are defined using statistical models of RMR and the correlations between RMR and the reference image. The applicability and validity of this application are examined and then the result of uncertainty evaluation can be used to optimize the tunnel layout.

• Journal of the korean academy of Pediatric Dentistry
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• v.47 no.4
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• pp.416-426
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• 2020

The purpose of this study was to calculate uncertainty of orthodontic measurement in skeletal class III malocclusion children using lateral cephalometry analysis software which obtained traceability in previous study. Using this data, standard reference of measurement value for skeletal class III malocclusion was obtained. Lateral cephalometric data was collected from 144 children who visited Pediatric Dentistry from 2017 to 2020 for orthodontic treatment. Orthodontic measurement was analyzed with software which obtained traceability. Type A evaluation of uncertainty and type B evaluation of uncertainty was calculated to obtain combined standard uncertainty and expanded uncertainty. Standard reference of skeletal class III children was compared to standard reference of skeletal class I children. Distribution range for skeletal class III malocclusion children aged 6 to 10 with 95% confidence interval was provided using calculated uncertainty of orthodontic measurement value.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.4
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• pp.699-712
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• 2000

Juam lake is a major water resource for the industrial and agricultural activities as well as the resident life of Kwangju and Chonnam regions. However, the water quality of the lake is getting worse due to a large quantity of pollutant inflowing to the lake. Thus, the strategy for achieving the water quality goal of the lake should be developed as soon as possible. When there are various alternatives that can be used as the strategy, several criteria based on the achievement degree of water quality goal, the applicability of technique and social environment, and the reasonableness of the cost required are made to evaluate and rank the alternatives. However, it is difficult to make a decision when there are multiple criteria and conflicting objectives and specifically the estimated values of criteria contain elements of uncertainty. The uncertainty stems from the lack of available information, the randomness of future situation, and the incomplete knowledge of expert. As the degree of uncertainty is higher, the decision becomes more difficult. In this study, a fuzzy decision-making method is presented to assist decision makers in evaluating various alternatives under uncertainty. The method allows decision makers to characterize the associated uncertainty by applying fuzzy theory and incorporate the uncertainty directly into the decision making process for selecting the "best" alternative so decisions can be made that are more appropriate and realistic than those made without taking uncertainty in account.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.3
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• pp.247-271
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• 2019

Uncertainty in scientific knowledge means an uncertain state where propositions are neither true or false at present. The existing studies have analyzed the propositions written in the academic literature, and have conducted the performance evaluation based on the rule based and machine learning based approaches by using the corpus. Although they recognized that the importance of word construction, there are insufficient attempts to expand the word by analyzing the meaning of uncertainty words. On the other hand, studies for analyzing the structure of networks by using bibliometrics and text mining techniques are widely used as methods for understanding intellectual structure and relationship in various disciplines. Therefore, in this study, semantic relations were analyzed by applying Word2Vec to existing uncertainty words. In addition, WordNet, which is an English vocabulary database and thesaurus, was applied to perform a network analysis based on hypernyms, hyponyms, and synonyms relations linked to uncertainty words. The semantic and lexical relationships of uncertainty words were structurally identified. As a result, we identified the possibility of automatically expanding uncertainty words.

• 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 electromagnetic engineering and science
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• v.15 no.3
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• pp.181-184
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• 2015

Evaluation of radiating radiofrequency fields from hand-held and body-mounted wireless communication devices to human bodies are conducted by measuring the specific absorption rate (SAR). The uncertainty of system validation and probe calibration in SAR measurement depend on the variation of RF power used for the validation and calibration. RF input power for system validation or probe calibration is controlled manually during the test process of the existing systems in the laboratories. Consequently, a long time is required to reach the stable power needed for testing that will cause less uncertainty. The standard uncertainty due to this power drift is typically 2.89%, which can be obtained by applying IEC 62209 in a normal operating condition. The principle of the Automatic Input Power Level Control System (AIPLC), which controls the equipment by a program that maintains a stable input power level, is suggested in this paper. The power drift is reduced to less than ${\pm}1.16dB$ by AIPLC, which reduces the standard uncertainty of power drift to 0.67%.

• Journal of the Korean Geotechnical Society
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• v.29 no.3
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• pp.41-50
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• 2013

There always exists uncertainty which is mainly due to uncertainty of the evaluation of a geotechnical structure at a site. The uncertainty in the geotechnical analysis can be considered in the probabilistic analysis using the Monte Carlo Simulation. It needs various soil profiles which could be possible at the target site. In this study, a new method is proposed to generate soil profiles which are probable at the site. The proposed method analyzes a structure of a site and generates one dimensional soil profiles for a probabilistic analysis. Through the field application, the applicability of the prosed method was shown.

• Tunnel and Underground Space
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• v.15 no.6 s.59
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• pp.441-451
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• 2005

It is the unavoidable problem that the RMR rock classification method has the uncertainty resulted from uncertain definition of measured value in RMR grade table, hence in this paper, the estimation of probability density function$(p{\cdot}d{\cdot}f)$ graph with the evaluation of continuos RMR and the Monte Carlo Simulation and statistic reasoning were carried out to evaluate the uncertainty quantitatively. Also, the modified RMR rock classification table was presented in order to apply the uncertainty of RMR to the practice, and then the design process of standard support pattern and the tunnel support material was proposed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.4
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• pp.653-659
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• 2015

In the last few years, the regulations for efficiency grade of the three phase induction motor are internationally being discussed and upgraded for the protection of environment and energy saving. So the efficiency improvement and the reliable test result are essential to determine the premium grade three phase induction motor. While a study on developing the efficiency motor is active, there is little research about the guarantee for efficiency. So in this paper, the dispersion characteristic of the efficiency is studied using uncertainty theory for the three phase induction motor to improve the reliability of efficiency. The values such as input voltage, current, speed, torque were obtained by loss separation method to evaluate the uncertainty. From the result, it was known that the important loss factor could affect the uncertainty is the stray loss.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.151-151
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• 2018

The present study is aimed to quantifying the uncertainty in the general circulation model (GCM) selection and its impacts on hydrology studies in the basins. For this reason, 13 GCMs was selected among the 26 GCM models of the Fifth Assessment Report (AR5) scenarios. Then, the climate data and hydrologic data with two Representative Concentration Pathways (RCPs) of the best model (INMCM4) and worst model (HadGEM2-AO) were compared to understand the uncertainty associated with GCM models. In order to project the runoff, the Precipitation-Runoff Modelling System (PRMS) was driven to simulate daily river discharge by using daily precipitation, maximum and minimum temperature as inputs of this model. For simulating the discharge, the model has been calibrated and validated for daily data. Root mean square error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were applied as evaluation criteria. Then parameters of the model were applied for the periods 2011-2040, and 2070-2099 to project the future discharge the five large basins of South Korea. Then, uncertainty caused by projected temperature, precipitation and runoff changes were compared in seasonal and annual time scale for two future periods and RCPs compared to the reference period (1976-2005). The findings of this study indicated that more caution will be needed for selecting the GCMs and using the results of the climate change analysis.