• The Korean Journal of Financial Management
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• v.25 no.2
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• pp.1-31
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• 2008

Before the financial crisis in 1997, Korean bond markets had been those of corporate bonds with relatively high market yield. During the period, most of major institutional investors tend to utilize passive strategies such as buying and holding. After the crisis, however, they could not help choosing active bond management strategies because of lowed yield level and intensified competition among the financial institutions. This study is forced on the yield curve, which is the reflection of all information on the bond investment environments. The study also make analysis on the major economic and securities market factors and its structural relationship with the shape of the curve such as level, curvature and slope. For these purposes, an empirical model based on the Nelson-Siegel Model is estimated with the data during $1999{\sim}2006$. Out-of-sample forecasting is also made to test the usefulness of the estimated model. In addition, the dependent variables which are the estimates of level and slope are estimated on the macro variables and securities market variables. VAR and SUR models are used for the estimation. Estimation results show that level and slope of the yield curve are influenced by the target call rate change, exchange rate change rate, inflation rate. These results provide practical implications for the active managements in the overall treasury bond markets.

• Journal of the Korea Concrete Institute
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• v.21 no.5
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• pp.629-638
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• 2009

In this paper, the existing formulas of the step-by-step method were generalized for effective estimation of responses of complicated composite sections due to long-term deformation of concrete. The initial transformed section properties of the composite section were derived from material and section properties of concrete section and sections which confine the longterm deformation of concrete. The transformed section properties at each step were derived from the effective modulus of elasticity considered the creep coefficient variation. Improved formulas of the step-by-step method for generalized responses were derived by introducing 5 generalized parameters. The formulas can be more simplified by applying constant increment of creep coefficient at each step. The constant increment of creep coefficient at each step can also reduce computing time and make equal computing error of each step. The generalized responses for axial elastic strain of concrete section were most sensitive to the area rate of concrete section, and the ratio of the second moment of the confining section area was more sensitive than that of the concrete section. Those for elastic curvature of concrete section were most sensitive to the ratio of the second moment of concrete section area.

• Journal of the Korean GEO-environmental Society
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• v.16 no.9
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• pp.43-51
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• 2015

In this paper, a 3D shell-spring model that can perform time history analysis of buried pipelines is used to evaluate the effect of the incident direction of the earthquake motion. When applying harmonic motions, it is shown that the period of vibration has pronounced influence on the response of buried pipelines. With decrease in the period, the curvature of the pipeline and corresponding response are shown to increase. To evaluate the effect of the incident angle, the motions are applied in the direction of the pipleline, horizontal, and vertical planes. When the motion is applied parallel to the direction of the pipeline, it only induces bending strains and therefore, the response is the lowest. Under motions subjected in horizontal and vertical planes at an angle of $45^{\circ}$ from the longitudinal axis of the buried pipeline, the axial deformation is shown to contribute greatly to the response of the pipelines. When imposing two-components simultaneously, the calculated response is similar to the case where only single-component is imposed. It is because one component only induces bending strain, resulting in very small increase in the response. The trend of the response is shown to be quite similar for recorded motions. Therefore, it is concluded that use of a single-component is sufficient for estimation of the longitudinal response of buried pipelines.

• Journal of Korea Water Resources Association
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• v.46 no.12
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• pp.1221-1234
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• 2013

The purpose of this study is to suggest the methodology for the computation of uplift pressure and discharge of the seepage flow under gravity dam. A 3-dimensional FDM model is developed for this purpose and this model can simulate the saturated Darcian flow in heterogeneous media. For the verification of the numeric model, test simulation has been executed and the mass balance has been checked. The error does not exceed 3%. Using the developed model, The uplift pressure and seepage flow discharge under gravity dam has been calculated. The uplift pressure shows the similar pattern, comparing with the result of flow-net method. As the length of grout curtain increases, the uplift pressure decreases linearly, but the seepage flow discharge shows the non-linear decreasing pattern. The coefficients of the formulas in the dam-design criteria have been analysed, and ${\alpha}=1/3$ corresponds to the value when the length of curtain grout is 70% of the aquifer height. The uplift pressure near the pressure relief drain has the big curvature vertically and horizontally. The developed model in this study can be used for the evaluation of the effects of seepage flow under gravity dam.

• Journal of Korea Multimedia Society
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• v.5 no.4
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• pp.458-467
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• 2002

There has been proposed many simplification algorithms for effectively decreasing large-volumed polygonal surface data. These algorithms apply their own cost function for collapse to one of fundamental simplification unit, such as vertex, edge and triangle, and minimize the simplification error occurred in each simplification steps. Most of cost functions adopted in existing works use the error estimation method based on distance optimization. Unfortunately, it is hard to define the local characteristics of surface data using distance factor alone, which is basically scalar component. Therefore, the algorithms cannot preserve the characteristic features in surface areas with high curvature and, consequently, loss the detailed shape of original mesh in high simplification ratio. In this paper, we consider the vector component, such as surface orientation, as one of factors for cost function. The surface orientation is independent upon scalar component, distance value. This means that we can reconsider whether or not to preserve them as the amount of vector component, although they are elements with low scalar values. In addition, we develop a simplification algorithm based on half-edge collapse manner, which use the proposed cost function as the criterion for removing elements. In half-edge collapse, using one of endpoints in the edge represents a new vertex after collapse operation. The approach is memory efficient and effectively applicable to the rendering system requiring real-time transmission of large-volumed surface data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.121-132
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• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.