• 한국전산유체공학회:학술대회논문집
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• 2001.05a
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• pp.111-115
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• 2001

The study of nonlinear gas transport in rarefied condition or associated with the microscale length of the geometry has emerged as an interesting topic in recent years. Along with the DSMC method, several fluid dynamic models that come under the general category of the moment method or the Chapman-Enskog method have been used for this type of problem. In the present study, on the basis of Eu's generalized hydrodynamics, a computational model for diatomic gases is proposed. The preliminary result indicates that the bulk viscosity plays a considerable role in fundamental flow problems such as the shock structure and shear flow. The general properties of the constitutive equations are obtained through a simple mathematical analysis. With an iterative computational algorithm of the constitutive equations, numerical solutions for the multi-dimensional problem can be obtained.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1339-1345
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• 2017

In the framework of the EU funded project NURESAFE, the subchannel code CTF and the neutronics code DYN3D were integrated and coupled on the NURESIM platform. The developments achieved during this 3-year project include assembly-level and pin-by-pin multiphysics thermal hydraulics/neutron kinetics coupling. In order to test this coupling, a PWR rod ejection transient was simulated on a MOX/UOX minicore. The transient is simulated using two different models of the minicore. In the first simulation, both codes model the core with an assembly-wise resolution. In the second simulation, a pin-by-pin fuel-centered model is used in CTF for the central assembly, and a pin power reconstruction method is applied in DYN3D. The analysis shows the influence of the different models on global parameters, such as the power and the average fuel temperature, but also on local parameters such as the maximum fuel temperature.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.105-127
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• 2024

We propose recurrent neural network (RNN) methods for forecasting realized volatility (RV). The data are RVs of ten major stock price indices, four from the US, and six from the EU. Forecasts are made for relative ratio of adjacent RVs instead of the RV itself in order to avoid the out-of-scale issue. Forecasts of RV ratios distribution are first constructed from which those of RVs are computed which are shown to be better than forecasts constructed directly from RV. The apparent asymmetry of RV ratio is addressed by the Piecewise Min-max (PM) normalization. The serial dependence of the ratio data renders us to consider two architectures, long short-term memory (LSTM) and gated recurrent unit (GRU). The hyperparameters of LSTM and GRU are tuned by the nested cross validation. The RNN forecast with the PM normalization and ratio transformation is shown to outperform other forecasts by other RNN models and by benchmarking models of the AR model, the support vector machine (SVM), the deep neural network (DNN), and the convolutional neural network (CNN).

• Journal of Korean Society of Transportation
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• v.31 no.3
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• pp.3-18
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• 2013

This study develops a forecasting method to estimate air cargo demand from ICN(Incheon International Airport) to all airports in EU with Seasonal Autoregressive Integrated Moving Average (SARIMA) Model using volumes from the first quarter of 2000 to the fourth quarter of 2009. This paper shows the superiority of SARIMA Model by comparing the forecasting accuracy of SARIMA with that of other ARIMA (Autoregressive Integrated Moving Average) models. Given that very few papers and researches focuses on air route, this paper will be helpful to researchers concerned with air cargo.

• Journal of Microbiology and Biotechnology
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• v.21 no.4
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• pp.430-437
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• 2011

The effects of the agitation and aeration rates on the production of serratiopeptidase (SRP) in a 5-L fermentor (working volume 2-l) were systematically investigated using Serratia marcescens NRRL B-23112. The dissolved oxygen concentration, pH, biomass, SRP yield, and maltose utilization were all continuously measured during the course of the fermentation runs. The efficiencies of the aeration and agitation were evaluated based on the volumetric mass transfer coefficient ($K_La$). The maximum SRP production of 11,580 EU/ml with a specific SRP productivity of 78.8 EU/g/h was obtained with an agitation of 400 rpm and aeration of 0.075 vvm, which was 58% higher than the shake-flask level. The $K_La$ for the fermentation system supporting the maximum production (400 rpm, 0.075 vvm) was 11.3 $h^{-1}$. Under these fermentor optimized conditions, kinetic modeling was performed to understand the detailed course of the fermentation process. The resulting logistic and Luedeking-Piret models provided an effective description of the SRP fermentation, where the correlation coefficients for cell growth, SRP formation, and substrate consumption were 0.99, 0.94, and 0.84, respectively, revealing a good agreement between the model-predicted and experimental results. The kinetic analysis of the batch fermentation process for the production of SRP demonstrated the SRP production to be mixed growth associated.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.83-92
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• 2022

The purpose of this research is to analyze the European paradigm of health investment and its implication. Conventional content analysis of WHO/EU(/EC)/European countries' policy data, and articles shows that the European paradigm of health investment is consist of the basic and extended models, twelve life-course-based health investment policies, and SROI evaluation method. The analyses and discussion points provide policy implications for making virtuous cycle of Korean sustainable healthcare system with economic development in the post Covid-19 era.

• The Journal of the Korea Contents Association
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• v.10 no.8
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• pp.381-390
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• 2010

Recently major developed countries such as U.S. and EU selected u-health as future growth engine industry, and concentrated their capabilities. Major companies all around the world entered this u-health business, too. Most of the research in this field have confined their research focus on the elementary technologies for infrastructure building. This research systematically investigates u-health business models with various objectives in various sub-fields. For this purpose, the value chain of u-health industry is analyzed, and then various business model cases are explored all around the world. Finally, the future changes possible to occur in the life insurance industries are analyzed.

• Journal of the Korean Society of Safety
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• v.23 no.4
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• pp.90-98
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• 2008

Presently, pedestrian's signal time models in korea are not considering Vulnerable-Pedestrian. So, the safety of Vulnerable-Pedestrian is being threatener and the number of accidents is increasing. Besides, the existing operational system for pedestrians can't offer the cross signal time in road corresponded the changing environment when the school zone is revitalized and the Silver zone is introduced for Vulnerable-Pedestrian. Conclusively, Vulnerable-Pedestrian's signal time models which are able to consider classified Vulnerable-Pedestrian speed, Vulnerable-Pedestrian perception-reaction time, Vulnerable-Pedestrian Spare(congestion-delay) time are suggested by the result of experiment in virtual crosswalk. the application of suggested models in this study to the site. It is possible to use as a basic stuff on study of pedestrian's signal time and expected to contribute the safety and mobility in future.

• Economic and Environmental Geology
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• v.56 no.5
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• pp.515-532
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• 2023

Bentonite, predominantly consists of expandable clay minerals, is considered to be the suitable buffering material in high-level radioactive waste disposal repository due to its large swelling property and low permeability. Additionally, the bentonite has large cation exchange capacity and specific surface area, and thus, it effectively retards the transport of leaked radionuclides to surrounding environments. This study aims to review the thermodynamic sorption models for four radionuclides (U, Am, Se, and Eu) and eight bentonites. Then, the thermodynamic sorption models and optimized sorption parameters were precisely analyzed by considering the experimental conditions in previous study. Here, the optimized sorption parameters showed that thermodynamic sorption models were related to experimental conditions such as types and concentrations of radionuclides, ionic strength, major competing cation, temperature, solid-to-liquid ratio, carbonate species, and mineralogical properties of bentonite. These results implied that the thermodynamic sorption models suggested by the optimization at specific experimental conditions had large uncertainty for application to various environmental conditions.

• Analytical Science and Technology
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• v.24 no.6
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• pp.544-555
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• 2011

The acute toxicity in the rainbow trout (Oncorhynchus mykiss) was analyzed and predicted using quantitative structure-activity relationships (QSAR). The aquatic toxicity, 96h $LC_{50}$ (median lethal concentration) of 275 organic pesticides, was obtained from EU-funded project DEMETRA. Prediction models were derived from 558 2D molecular descriptors, calculated in PreADMET. The linear (multiple linear regression) and nonlinear (support vector machine and artificial neural network) learning methods were optimized by taking into account the statistical parameters between the experimental and predicted p$LC_{50}$. After preprocessing, population based forward selection were used to select the best subsets of descriptors in the learning methods including 5-fold cross-validation procedure. The support vector machine model was used as the best model ($R^2_{CV}$=0.677, RMSECV=0.887, MSECV=0.674) and also correctly classified 87% for the training set according to EU regulation criteria. The MLR model could describe the structural characteristics of toxic chemicals and interaction with lipid membrane of fish. All the developed models were validated by 5 fold cross-validation and Y-scrambling test.