• Journal of Climate Change Research
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• v.2 no.2
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• pp.79-91
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• 2011

In order to study interactions between climate change and air quality, a modeling system including the downscaling scheme has been developed in the integrated manner. This research focuses on the development of a downscaling method to utilize CCSM3 outputs as the initial and boundary conditions for the regional climate model, MM5. Horizontal/vertical interpolation was performed to convert from the latitude/longitude and hybrid-vertical coordinate for the CCSM3 model to the Lambert-Conformal Arakawa-B and sigma-vertical coordinate for the MM5 model. A variable diagnosis was made to link between different variables and their units of CCSM and MM5. To evaluate the dynamic downscaling performance of this study, spatial distributions were compared between outputs of CCSM/MM5 and NRA/MM5 and statistic analysis was conducted. Temperature and precipitation patterns of CCSM/MM5 in summer and winter showed a similar pattern with those of observation data in East Asia and the Korean Peninsula. In addition, statistical analysis presented that the agreement index (AI) is more than 0.9 and correlation coefficient about 0.9. Those results indicate that the dynamic downscaling system built in this study can be used for the research of interaction between climate change and air quality.

• Journal of Korean Society of Disaster and Security
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• v.11 no.2
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• pp.37-43
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• 2018

The storm surge is caused by an typhoons and it is not easy to predict the location, strength, route of the storm. Therefore, research using a scenario for storms occurrence has been conducted. In Korea, hazard maps for various scenarios were produced using the storm surge numerical simulation. Such a method has a disadvantage in that it is difficult to predict when other scenario occurs, and it is difficult to cope with in real time because the simulation time is long. In order to compensate for this, we developed a method to predict the storm surge damage by using research database. The risk grade prediction for the storm surge was performed predominantly in the study area of the East coast. In order to estimate the equation, COMSOL developed by COMSOL AB Corporation was utilized. Using some assumptions and limitations, the form of the basic equation was derived. the constants and coefficients in the equation were estimated by the trial and error method. Compared with the results, the spatial distribution of risk grade was similar except for the upper part of the map. In the case of the upper part of the map, it was shown that the resistance coefficient, k was calculated due to absence of elevation data. The SIND model is a method for real-time disaster prediction model and it is expected that it will be able to respond quickly to disasters caused by abnormal weather.

• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.717-726
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• 2018

PM(Particulate Matter) cause serious diseases of air pollution. Most of the studies have analyzed local distribution trends using satellite images or modeling techniques. However,the method using the spatial interpolation method based on the meteorological value is insufficient in Korea. In this study, monthly spatial distribution of $PM_{10}$ and $PM_{2.5}$ in January, February, March, and April of 2018 Seoul Metropolitan City were analyzed based on 39 PM monitoring networks. In addition, a distribution map showing the difference between $PM_{10}$ and $PM_{2.5}$ was based on the distribution obtained through this study. The regions of high $PM_{10}$ and $PM_{2.5}$ emissions were selected. In addition, the correlation between $PM_{10}$ and $PM_{2.5}$ was confirmed through the distribution map. This study analyzed the spatial distribution variation results of analyzing $PM_{10}$ and $PM_{2.5}$ in Seoulthrough spatial analysis technique. As a result of this study, it was confirmed that $PM_{10}$ shows high measured value on the roadside measurement station.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.733-735
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• 2014

Example based Super Resolution(SR) is using the correspondence between the low and high resolution image from a database. This method uses only one image to estimate a high resolution image and can get the larger image than 2 times. Example based SR is proposed to solve the problem of classical SR. Neighbor embedding(NE) has been inspired by manifold learning method, particularly locally linear embedding. However, the poor generalization of NE decreases the performance of such algorithm. The sizes of local training sets are always too small to improve the performance of NE. We propose the advanced NE baesd on SVR having an excellent generalization ability to solve this problem. Given a low resolution image, we estimate a pixel in its high resolution version by using SVR based NE. Through experimental results, we quantitatively and qualitatively confirm the improved results of the proposed algorithm when comparing with conventional interpolation methods and NE.

• Journal of the Korean earth science society
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• v.40 no.3
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• pp.259-271
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• 2019

A statistical downscaling method was adopted in order to establish the high-resolution wave prediction system in the East Sea coastal area. This system used forecast data from the Global Wave Watch (GWW) model, and the East Sea and Busan Coastal Wave Watch (CWW) model operated by the Korea Meteorological Administration (KMA). We used the CWW forecast data until three days and the GWW forecast data from three to seven days to implement the statistical downscaling method (inverse distance weight interpolation and conditional merge). The two-dimensional and station wave heights as well as sea surface wind speed from the high-resolution coastal prediction system were verified with statistical analysis, using an initial analysis field and oceanic observation with buoys carried out by the KMA and the Korea Hydrographic and Oceanographic Agency (KHOA). Similar to the predictive performance of the GWW and the CWW data, the system has a high predictive performance at the initial stages that decreased gradually with forecast time. As a result, during the entire prediction period, the correlation coefficient and root mean square error of the predicted wave heights improved from 0.46 and 0.34 m to 0.6 and 0.28 m before and after applying the statistical downscaling method.

• Journal of Korea Water Resources Association
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• v.52 no.1
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• pp.21-33
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• 2019

This study performed to simulate the watershed storm runoff using data of S-band dual-polarization radar rain, GPM (Global Precipitation Mission) satellite rain, and observed rainfall at 21 ground stations operated by KMA (Korea Meteorological Administration) respectively. For the 3 water level gauge stations (Sancheong, Changchon, and Namgang) of NamgangDam watershed ($2,293km^2$), the KIMSTORM2 (KIneMatic wave STOrm Runoff Model2) was applied and calibrated with parameters of initial soil moisture contents, Manning's roughness of overland and stream to the event of typhoon CHABA (82 mm in watershed aveprage) in $5^{th}$ October 2016. The radar and GPM data was corrected with CM (Conditional Merging) method such as CM-corrected Radar and CM-corrected GPM. The CM has been used for accurate rainfall estimation in water resources and meteorological field and the method combined measured ground rainfall and spatial data such as radar and satellite images by the kriging interpolation technique. For the CM-corrected Radar and CM-corrected GPM data application, the determination coefficient ($R^2$) was 0.96 respectively. The Nash-Sutcliffe efficiency (NSE) was 0.96 and the Volume Conservation Index (VCI) was 1.03 respectively. The CM-corrected data of Radar and GPM showed good results for the CHABA peak runoff and runoff volume simulation and improved all of $R^2$, NSE, and VCI comparing with the original data application. Thus, we need to use and apply the radar and satellite data to monitor the flood within the watershed.

• Journal of Environmental Health Sciences
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• v.45 no.1
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• pp.82-96
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• 2019

Objective: The aims of this study were to provide the basic data for establishing a precautionary management policy and to develop a methodology for selecting a radon management priority target area suitable for the Korean domestic environment. Methods: A suitable mapping method for the domestic environment was derived by conducting a quantitative comparison of predicted values and measured values that were calculated through implementation of two models such as IDW and RBF methods. And a qualitative comparison including the clarity of information transmission of the written radon map was carried out. Results: The predicted and measured values were obtained through the implementation of the spatial analysis models. The IDW method showed the lowest in the calculated mean square error and had a higher correlation coefficient than the other methods. As results of comparing the uncertainty using the jackknife concept and the concept of error distance for comparison of the differences according to the model interpolation method, the sum of the error distances showed a modest increase compared with the RBF method. As a result of qualitatively comparing the information transfer clarity between the radon maps prepared with the predicted values through the model implementation, it was found that the maps plotted using the predicted values by the implementation of the IDW method had greater clarity in terms of highness and lowness of radon concentration per area compared with the maps plotted by other methods. Conclusions: The radon management priority area suggests selecting a metropolitan city including an area with a high radon concentration.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.64-74
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• 2019

Although a non-rigid registration has high demands in clinical practice, it has a high computational complexity and it is very difficult for ensuring the accuracy and robustness of registration. This study proposes a method of applying a non-rigid registration to 3D magnetic resonance images of brain in an unsupervised learning environment by using a deep-learning network. A feature vector between two images is produced through the network by receiving both images from two different patients as inputs and it transforms the target image to match the source image by creating a displacement vector field. The network is designed based on a U-Net shape so that feature vectors that consider all global and local differences between two images can be constructed when performing the registration. As a regularization term is added to a loss function, a transformation result similar to that of a real brain movement can be obtained after the application of trilinear interpolation. This method enables a non-rigid registration with a single-pass deformation by only receiving two arbitrary images as inputs through an unsupervised learning. Therefore, it can perform faster than other non-learning-based registration methods that require iterative optimization processes. Our experiment was performed with 3D magnetic resonance images of 50 human brains, and the measurement result of the dice similarity coefficient confirmed an approximately 16% similarity improvement by using our method after the registration. It also showed a similar performance compared with the non-learning-based method, with about 10,000 times speed increase. The proposed method can be used for non-rigid registration of various kinds of medical image data.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.3
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• pp.93-100
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• 2021

Since the IB (Immersed Boundary) method, which can perform coupling analysis with objects and fluids having an impermeable boundary of arbitrary shape on a fixed grid system, has been developed, the IB method in various CFD models is increasing. The representative IB methods are the directing-forcing method and the ghost cell method. The directing-forcing type method numerically satisfies the boundary condition from the fluid force calculated at the boundary surface of the structure, and the ghost-cell type method is a computational method that satisfies the boundary condition through interpolation by placing a virtual cell inside the obstacle. These IB methods have a disadvantage in that the computational algorithm is complex. In this study, the simplified immersed boundary (SIB) method enables the analysis of temporary structures on a fixed grid system and is easy to expand to three proposed dimensions. The SIB method proposed in this study is based on a one-field model for immiscible two-phase fluid that assumes that the density function of each phase moves with the center of local mass. In addition, the volume-weighted average method using the density function of the solid was applied to handle moving solid structures, and the CIP method was applied to the advection calculation to prevent numerical diffusion. To examine the analysis performance of the proposed SIB method, a numerical simulation was performed on an object falling to the free water surface. The numerical analysis result reproduced the object falling to the free water surface well.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.725-731
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• 2020

In mineral resource development, resource exploration is a task to find economical minerals on the surface and underground, and the success rate is low compared to the development and production stages, and it is necessary to collect a lot of data through exploration and accurately analyze the collected information. In this study, mine spatial information was constructed using a 3D (Three-dimensional) laser scanner, and accuracy evaluation was performed to obtain a maximum deviation of 0.140 m and an average of 0.095 m in the X, Y and Z directions, and the possibility of utilizing the construction of mine geospatial information through a 3D laser scanner could be presented. In addition, the ore body modeling was performed by applying the interpolation method of the ore body section using the resource exploration results. The ore body modeling result was superimposed with the modeling result of the mine geospatial information built through the 3D laser scanner to construct the ore body modeling result based on the precise mine geospatial information. The results of ore body modeling based on mine geospatial information built through research can increase the ease of data interpretation and the accuracy of the calculated data, which will greatly increase the efficiency of work related to mineral resource development and mine damage prevention in the future.