• Journal of Korean Society for Atmospheric Environment
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• v.15 no.6
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• pp.779-789
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• 1999

To support daily ground-level $O_3$ forecasting in Seoul, a transfer function model(TFM) has been developed by using surface meteorological data and pollutant data(previous-day [$O_3$] and [$NO_2$]) from 1 May to 31 August in 1997. The forecast performance of the TFM was evaluated by statistical comparison with $O_3$ concentration observed during September it is shown that correlation coefficient(R), root mean squared error(RMSE), normalized mean squared error(NMSE) and mean relative error(MRE) were 0.73, 15.64, 0.006 and 0.101, respectively. The TFM appeared to have some difficulty forecasting very high $O_3$ concentrations. To compare with this model, multiple regression model(MRM) was developed for the same period. According to statistical comparison between the TFM and MRM. two models had similar predictive capability but TFM based on $O_3$ concentration higher than 60 ppb provided more accurate forecast than MRM. It was concluded that statistical model based on TFM can be useful for improving the accuracy of local $O_3$ forecast.

• Journal of Drive and Control
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• v.13 no.3
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• pp.1-7
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• 2016

A cold gas blow-down hydraulic actuation system is widely used in missiles that require an actuation system with a fast response time under a limited space with a short operating time and large loads on the actuators. The system consists of a pneumatic part that supplies the regulated high-pressure gas to a reservoir, and a hydraulic part that supplies pressurized hydraulic oil to the actuators by the pressurized gas in the reservoir. This paper proposes a mathematical model to analyze and simulate the pneumatic part of an actuation system that supplies the operating power to the actuators. The mathematical model is based on the ideal gas equation and also considers the models for heat transfer. The model is applied to the pressure vessel and the gas part of the reservoir, and the model for the pneumatic part is established by connecting the two models for the parts. The model is validated through a comparison of the simulation results with the experimental results. The comparison shows that the suggested model could be useful in the design of the pneumatic part of a cold gas blow-down type hydraulic actuation system.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.19-19
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• 2011

The appraisals of hydrology model behavior for flow and water quality are generally performed through comparison of simulated data with observed ones. To perform appraisal of hydrology model, some criteria are often used, such as coefficient of determination ($R^2$), Nash and Sutcliffe model efficiency coefficient (NSE), index of agreement (d), modified forms of NSE and d, and relative efficiency criteria NSE and d. These criteria are used not only for hydrology model estimations also for various comparisons of two data sets; This NSE has been often used for SWAT calibration. However, it has been known that the NSE value has some limitations in evaluating hydrology at watersheds under monsoon climate because this statistic is largely affected by higher values in the data set. To overcome these limitations, the SWAT auto-calibration module was enhanced with K-means clustering and direct runoff/baseflow modules. However the NSE is still being used in this module to evaluate model performance. Therefore, the SWAT Auto-calibration module was modified to incorporate alternative efficiency criteria into the SWAT K-means/direct runoff-baseflow auto-calibration module. It is expected that this enhanced SWAT auto-calibration module will provide better calibration capability of SWAT model for all flow regime.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.4
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• pp.124-131
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• 2007

The numerical study on behavior of impinging spray from high-pressure swirl injector under various ambient temperatures was performed by using spray vaporization model and spray-wall impingement model implemented in modified KIVA code, and these spray models were estimated by comparison with experimental results. To compute the spray-wall impingement process, the Gosman model, which is based on the droplet behavior after impingement determined by experimental correlations, was used. The modified Abramzon and Sirignano model, that includes the effects of variable thermodynamic properties and non-unitary Lewis number in the gas film, was adapted for spray vaporization process. The exciplex fluorescence measurements were also conducted for comparison. The experimental and numerical analysis were carried out at the ambient pressures of 0.1 MPa and at the ambient temperature of 293 K and 473 K, and the spray characteristics, such as spray-wall impingement process, gas velocity field, SMD and vapor concentration, were acquired. It was found that the impinging spray develops active and SMD is small at vaporization conditions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.851-856
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• 2016

Wind speed is heavily fluctuated and quite local than other weather elements. It is difficult to improve the accuracy of prediction only in a numerical prediction model. An MOS (Model Output Statistics) technique is used to correct the systematic errors of the model using a statistical data analysis. The Most of previous MOS has used a linear regression model for weather prediction, but it is hard to manage an irregular nature of prediction of wind speed. In order to solve the problem, a nonlinear regression method using SVR (Support Vector Regression) is introduced for a development of MOS for wind speed prediction. Experiments are performed for KLAPS (Korea Local Analysis and Prediction System) re-analysis data from 2007 to 2013 year for Jeju Island and Busan area in South Korea. The MLR and SVR based linear and nonlinear methods are compared to each other for prediction accuracy of wind speed. Also, the comparison experiments are executed for the variation in the number of UM elements.

• Journal of the Society of Naval Architects of Korea
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• v.48 no.1
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• pp.15-22
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• 2011

In this paper, cavitation patterns of model tests were compared with those of full-scale measurement for a propeller of crude oil carrier which was suffered from erosions on suction side of blade tip region. Cavitation tests were performed at design and ballast draft using model and full scale nominal wakes. A model ship and wire mesh method was used for the simulation of wake patterns of model nominal wakes. For the prediction of full-scale wake patterns, a RANS solver(Fluent 6.3) was used and wire mesh method was used for the simulation of the full scale wakes. Comparison results show that cavitation patterns using predicted full-scale wake patterns are closer to cavitation patterns of full-scale measurement at ballast draft condition. Also, cloud cavitations were observed on the position of eroded area at both full-scale measurement and cavitation tests using simulated full-scale wake patterns.

• International Journal of Highway Engineering
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• v.18 no.1
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• pp.91-97
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• 2016

PURPOSES : The objective of this paper is to develop a pavement performance model based on the Bayesian algorithm, and compare the measured and predicted performance data. METHODS : In this paper, several pavement types such as SMA (stone mastic asphalt), PSMA (polymer-modified stone mastic asphalt), PMA (polymer-modified asphalt), SBS (styrene-butadiene-styrene) modified asphalt, and DGA (dense-graded asphalt) are modeled in terms of the performance evaluation of pavement structures, using the Bayesian algorithm. RESULTS : From case studies related to the performance model development, the statistical parameters of the mean value and standard deviation can be obtained through the Bayesian algorithm, using the initial performance data of two different pavement cases. Furthermore, an accurate performance model can be developed, based on the comparison between the measured and predicted performance data. CONCLUSIONS : Based on the results of the case studies, it is concluded that the determined coefficients of the nonlinear performance models can be used to accurately predict the long-term performance behaviors of DGA and modified asphalt concrete pavements. In addition, the developed models were evaluated through comparison studies between the initial measurement and prediction data, as well as between the final measurement and prediction data. In the model development, the initial measured data were used.

• Journal of Korean Clinical Nursing Research
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• v.17 no.1
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• pp.101-112
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• 2011

Purpose: The purpose of this study is to develop a detailed clinical model for recording initial nursing assessment items, and to test the applicability of the model to facilitate semantic interoperability for sharing and exchanging nursing information. Methods: First, the researchers extracted items by analyzing initial nursing assessment records. Second, defining characteristics were identified by analyzing nursing records and reviewing the literature. Third, value sets for defining characteristics were identified and types and cardinalities of defining characteristics were defined based on the value sets. Finally, the detailed clinical model was tested through evaluation by experts and comparison with the initial nursing assessment in a clinical setting. Results: Sixty-one detailed clinical models were developed with 178 defining characteristics and value sets. The experts evaluation and comparison with the initial nursing assessment in a clinical setting showed that the detailed clinical model developed in this study was valid. Conclusion: Use of this detailed clinical model can ensure that the Electronic Health Record contains meaningful and valid information and supports semantic interoperability of nursing information. This use will promote quality in the nursing records and eventually quality of nursing care.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.3027-3033
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• 2022

Background: In this study, various types of deep-learning models for predicting in vitro radiosensitivity from gene-expression profiling were compared. Methods: The clonogenic surviving fractions at 2 Gy from previous publications and microarray gene-expression data from the National Cancer Institute-60 cell lines were used to measure the radiosensitivity. Seven different prediction models including three distinct multi-layered perceptrons (MLP), four different convolutional neural networks (CNN) were compared. Folded cross-validation was applied to train and evaluate model performance. The criteria for correct prediction were absolute error < 0.02 or relative error < 10%. The models were compared in terms of prediction accuracy, training time per epoch, training fluctuations, and required calculation resources. Results: The strength of MLP-based models was their fast initial convergence and short training time per epoch. They represented significantly different prediction accuracy depending on the model configuration. The CNN-based models showed relatively high prediction accuracy, low training fluctuations, and a relatively small increase in the memory requirement as the model deepens. Conclusion: Our findings suggest that a CNN-based model with moderate depth would be appropriate when the prediction accuracy is important, and a shallow MLP-based model can be recommended when either the training resources or time are limited.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2000.04a
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• pp.52-55
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• 2000

Investigated via a series of finite element process simulation is the effect of diverse process variables on some selected non-dimensional parameters characterizing the strip in hot strip rolling. Then on the basis of these parameters an on-line model is derived for the precise prediction of roll and roll power. The prediction accuracy of the proposed model is examined through comparison with predictions from a finite element process model.