• Atmosphere
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• v.26 no.1
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• pp.35-45
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• 2016

Initialization of the global seasonal forecast system is as much important as the quality of the embedded climate model for the climate prediction in sub-seasonal time scale. Recent studies have emphasized the important role of soil moisture initialization, suggesting a significant increase in the prediction skill particularly in the mid-latitude land area where the influence of sea surface temperature in the tropics is less crucial and the potential predictability is supplemented by land-atmosphere interaction. This study developed a new soil moisture initialization method applicable to the KMA operational seasonal forecasting system. The method includes first the long-term integration of the offline land surface model driven by observed atmospheric forcing and precipitation. This soil moisture reanalysis is given for the initial state in the ensemble seasonal forecasts through a simple anomaly initialization technique to avoid the simulation drift caused by the systematic model bias. To evaluate the impact of the soil moisture initialization, two sets of long-term, 10-member ensemble experiment runs have been conducted for 1996~2009. As a result, the soil moisture initialization improves the prediction skill of surface air temperature significantly at the zero to one month forecast lead (up to ~60 days forecast lead), although the skill increase in precipitation is less significant. This study suggests that improvements of the prediction in the sub-seasonal timescale require the improvement in the quality of initial data as well as the adequate treatment of the model systematic bias.

• Journal of the Korean Society for Marine Environment & Energy
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• v.5 no.4
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• pp.27-40
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• 2002

The circulation of sea water was simulated by two dimensional tide model using the main four tidal components and permanent current driven by inflow/outflow across open boundaries. According to the residt of tide model, the maximum speed of eastward flow on the Cheju Strait is twice higher than that of westward flow. According to the result of permanent current, the flow of permanent current showing semi-circle pattern in the southern part of Kojedo was due to variation of topography. According to the result of circulation model in the Cheju Strait, eastward flow entering in the southern waters from the Yellow Sea of Korea were dominant, but outflows westward were weak. These results suggest that it was difficult to move for suspended particulate matter into the Yellow sea from the southern waters through Cheju Strait.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.59-67
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• 2011

This paper proposes a model to analyze the fault factors of air-to-ground weapon delivery utilizing software fault localization methods. In the previous study, to figure out the factors to affect the accuracy of air-to-ground weapon delivery, the FBEL (Factor-based Error Localization) method had been proposed and the fault factors were analyzed based on the method. But in the study, the correlation between weapon delivery accuracy and the fault factors could not be revealed because the firing accuracy among several factors was fixed. In this paper we propose a more precise fault analysis model driven through a study of the correlation among the fault factors of weapon delivery, and a method to estimate the possibility of faults with the limited number of test cases utilizing the model. The effectiveness of proposed method is verified through the simulation utilizing real delivery data. and weapons delivery testing in the evaluation of which element affecting the accuracy of analysis that was available to be used successfully.

• Journal of Korea Water Resources Association
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• v.35 no.1
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• pp.65-75
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• 2002

The objectives of this study are to analyse model-based soil moisture variations depending on model parameters m and $T_0$ and to evaluate the model performance for the simulation of soil moisture variations by the comparison of observed groundwater levels and model-driven soil moisture amounts and observed and simulated river discharges at the basin outlet. The selected study area is the Pyungchang IHP river basin with outlet at Sanganmi station and the summer flooding events during '94-'98 are used for the analysis. As a result, soil moisture holding capacity is increased according to increase the parameter m that represents effective groundwater depth. This phenomenon is especially dominant when higher m and $T_0$ values are used. The qualitative comparison of computed base flow and observed groundwater level shows that the base flow peaks are reasonably simulated and the decreasing limbs of hydrograph are mainly caused by base flows. It is concluded that TOPMODEL can be used effectively for simulating basin-averaged soil moisture variations in addition to river flow generations.

• Journal of the Korean Geotechnical Society
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• v.19 no.2
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• pp.49-55
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• 2003

In this study, based on the relationship of the vertical force - settlement of batter piles obtained by pressure chamber model tests, the vertical bearing capacity of vertical and batter piles according to the increase of pile inclination was analyzed. A model open - ended steel pipe pile with the inclination of 5$^\circ$, 10$^\circ$ and 15$^\circ$ was driven into saturated fine sand with relative density of 50 %, and the static compression load tests were performed under each confining pressure of 35, 70 and 120 kPa in pressure chamber. The vertical bearing capacity of pile obtained from pressure chamber tests increased with the pile inclination. In the case of the inclination of 5$^\circ$, 10$^\circ$, 15$^\circ$, increasing ratios of pile bearing capacity were 111, 121, 127 ~ 140 % of vertical bearing capacity respectively. In the case of the inclination of above 20$^\circ$, the model tests could not be performed because of pile of pile head during compressive loading on the pile head.

• Korean Journal of Construction Engineering and Management
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• v.15 no.2
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• pp.53-61
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• 2014

Previous studies reveal the need for a tool to cost estimation of building design in early design stages. This paper proposes an internal finishes cost model tool to address this need. The tool allows users to evaluate the functionality, economics and quality of finishes concurrently with high-rise building design. Lack of information in the early stages of the project enables a relatively accurate estimates of work to raise up. Measurements are automatically extracted from simple design information and profile driven estimates are revised in real-time. The data model uses a flexible unit rate system that can easily be extended to other estimate dimensions such as mix-use building surcharge rate estimation. The approach illustrated in this paper is applicable to BIM tool conceptual estimation that support for massing purposes other than the one chosen for this study.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.6 no.3
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• pp.205-215
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• 1994

A 3-dimensional numerical model of wind-induced flows has been established. and comparative evaluation of determination methods of vertical eddy viscosity has been performed. The model uses turbulence models to calculate vertical eddy viscosity. The examined methods arp 0-equation model of functional form, 1-equation model of turbulence kinetic energy, and two 2-equation models ($textsc{k}$-$\varepsilon$ and $textsc{k}$-ι models). The evaluation includes the verification tests against experimental data for wind-driven current On a closed one-dimensional channel and a recirculating one-dimensional channel. Comparative study of turbulence models has shown that the proper distribution of turbulence scale is parabolic and the eddy viscosity is depending strongly on mixing depth due to wind.

• Journal of Korean Academy of Nursing
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• v.49 no.5
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• pp.575-585
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• 2019

Purpose: The purpose of this study was to develop predictive models for pressure ulcer incidence using electronic health record (EHR) data and to compare their predictive validity performance indicators with that of the Braden Scale used in the study hospital. Methods: A retrospective case-control study was conducted in a tertiary teaching hospital in Korea. Data of 202 pressure ulcer patients and 14,705 non-pressure ulcer patients admitted between January 2015 and May 2016 were extracted from the EHRs. Three predictive models for pressure ulcer incidence were developed using logistic regression, Cox proportional hazards regression, and decision tree modeling. The predictive validity performance indicators of the three models were compared with those of the Braden Scale. Results: The logistic regression model was most efficient with a high area under the receiver operating characteristics curve (AUC) estimate of 0.97, followed by the decision tree model (AUC 0.95), Cox proportional hazards regression model (AUC 0.95), and the Braden Scale (AUC 0.82). Decreased mobility was the most significant factor in the logistic regression and Cox proportional hazards models, and the endotracheal tube was the most important factor in the decision tree model. Conclusion: Predictive validity performance indicators of the Braden Scale were lower than those of the logistic regression, Cox proportional hazards regression, and decision tree models. The models developed in this study can be used to develop a clinical decision support system that automatically assesses risk for pressure ulcers to aid nurses.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.621-635
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• 2020

Water quality models are scientific tools that simulate and interpret the relationship between physical, chemical and biological reactions to external pollutant loads in water systems. They are actively used as a key technology in environmental water management. With recent advances in computational power, water quality modeling technology has evolved into a coupled three-dimensional modeling of hydrodynamics, water quality, and ecological inputs. However, there is uncertainty in the simulated results due to the increasing model complexity, knowledge gaps in simulating complex aquatic ecosystem, and the distrust of stakeholders due to nontransparent modeling processes. These issues have become difficult obstacles for the practical use of water quality models in the water management decision process. The objectives of this paper were to review the theoretical background, needs, and development status of water quality modeling technology. Additionally, we present the potential future directions of water quality modeling technology as a scientific tool for national environmental water management. The main development directions can be summarized as follows: quantification of parameter sensitivities and model uncertainty, acquisition and use of high frequency and high resolution data based on IoT sensor technology, conjunctive use of mechanistic models and data-driven models, and securing transparency in the water quality modeling process. These advances in the field of water quality modeling warrant joint research with modeling experts, statisticians, and ecologists, combined with active communication between policy makers and stakeholders.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.1
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• pp.93-100
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• 2021

Forward osmosis (FO) process is a chemical potential driven process, where highly concentrated draw solution (DS) is used to take water through semi-permeable membrane from feed solution (FS) with lower concentration. Recently, commercial FO membrane modules have been developed so that full-scale FO process can be applied to seawater desalination or water reuse. In order to design a real-scale FO plant, the performance prediction of FO membrane modules installed in the plant is essential. Especially, the flux prediction is the most important task because the amount of diluted draw solution and concentrate solution flowing out of FO modules can be expected from the flux. Through a previous study, a theoretical based FO module model to predict flux was developed. However it needs an intensive numerical calculation work and a fitting process to reflect a complex module geometry. The idea of this work is to introduce deep learning to predict flux of FO membrane modules using 116 experimental data set, which include six input variables (flow rate, pressure, and ion concentration of DS and FS) and one output variable (flux). The procedure of optimizing a deep learning model to minimize prediction error and overfitting problem was developed and tested. The optimized deep learning model (error of 3.87%) was found to predict flux better than the theoretical based FO module model (error of 10.13%) in the data set which were not used in machine learning.