• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.3213-3219
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• 2014

Currently, increase of greenhouse gas has had a signigicant impact on climate change in urbanization. As a result, the government has been looking for ways to take advantage of the trees that generate oxygen and reduce carbon dioxide for the prevention of climate change. It is essential to extract individual tree for calculating the amount of carbon dioxide reduction of trees. Aerial LIDAR data have three-dimensional information of building as well as trees as form of point clouds. In this study, automated model was developed to extract individual tree using aerial LIDAR data. For this purpose, we established a methodology for extracting trees and then proceeded the process of developing it as an automated model based on model builder of ArcGIS Software. In order to evaluate the applicability of the developed model, the model was compared with commercial software in study area located in Yongin City. Through the experimental result, the proposed model was extract trees 9.91% higher than commercial software. From this results, it was found that the model effectively extracted trees.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.9
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• pp.445-456
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• 2005

We propose a fast and accurate fluid solver of the Wavier-Stokes equations for the physics-based fluid simulations. Our method utilizes the solution of the Stokes equation as an initial guess for the velocity of the nonlinear term in the Wavier-Stokes equations. By guessing the initial velocity close to the exact solution of the given nonlinear differential equations, we can develop remarkably accurate and stable fluid solver. Our solver is based on the implicit scheme of finite difference methods, that makes it work well for large time steps. Since we employ the ADI method, our solver is also fast and has a uniform computation time. The experimental results show that our solver is excellent for fluids with high Reynolds numbers such as smoke and clouds.

• Smart Media Journal
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• v.6 no.2
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• pp.50-56
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• 2017

Due to new social environment, expenditure on eating out has increased over the last few year, thereafter the food-tech industries have steadily grown as well. We have studied what variable would affect customer's choices when they plan to eat out or order in. There are two variables are taken into account to prove it. Firstly, it is climate changes, such as an amount of rainfall, snowfall and clouds. Secondly, it is days, such as seasons and holidays. Based on this, we looked up the SikSin user's behaviors patterns, then did analysis of the daily data provided by the Meteorological office. By the end of the study, it turned out that two variables, climate changes and days, both have a strong influence on customer's choices. It is considered that this research outcome will make contributions to small businesses founders who want to take the initiative, marketing managers and people who are engaged in the food-tech industry.

• Korean Journal of Remote Sensing
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• v.18 no.2
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• pp.117-125
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• 2002

Multitemporal analysis with remotely sensed data is complicated by numerous intervening factors, including atmospheric attenuation and occurrence of clouds that obscure the relationship between ground and satellite observed spectral measurements. Using an adaptive reconstruction system, dynamic compositing approach was developed to recover missing/bad observations. The reconstruction method incorporates temporal variation in physical properties of targets and anisotropic spatial optical properties into image processing. The adaptive system performs the dynamic compositing by obtaining a composite image as a weighted sum of the observed value and the value predicted according to local temporal trend. The proposed system was applied to the sequence of NDVI images of AVHRR observed on the Korean Peninsula from 1999 year to 2000 year. The experiment shows that the reconstructed series can be used as an estimated series with complete data for the observations including bad/missing values. Additionally, the gradient image, which represents the amount of temporal change at the corresponding time, was generated by the proposed system. It shows more clearly temporal variation than the data image series.

• Korean Journal of Remote Sensing
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• v.20 no.4
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• pp.235-244
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• 2004

This study focuses on the assessment for proposed algorithm to discriminate cloudy pixels from snowy pixels through use of visible, near infrared, and short wave infrared channel data in VEGETATION-1 sensor embarked on SPOT-4 satellite. Traditional threshold algorithms for cloud and snow masks did not show very good accuracy. Instead of these independent masking procedures, K-Means clustering scheme is employed for cloud/snow discrimination in this study. The pixels used in clustering were selected through an integration of two threshold algorithms, which group ensemble the snow and cloud pixels. This may give a opportunity to simplify the clustering procedure and to improve the accuracy as compared with full image clustering. This paper also compared the results with threshold methods of snow cover and clouds, and assesses discrimination capability in VEGETATION channels. The quality of the cloud and snow mask even more improved when present algorithm is implemented. The discrimination errors were considerably reduced by 19.4% and 9.7% for cloud mask and snow mask as compared with traditional methods, respectively.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.305-313
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• 2000

A vicarious calibration method was developed for the OSMI sensor calibration. Employing measured aerosol optical thickness by a sunphotometer and a sky radiometer and water leaving radiance by ship measurements as inputs, TOA (top of the atmosphere) radiance at each OSMI band was simulated in conjunction with a radiative transfer model (Rstar5b) by Nakajima and Tanaka (1988). As a case of examining the accuracy of this method, we simulated TOA radiance based on water leaving radiance measured at NASA/MOBY site and aerosol optical thickness estimated nearby at Lanai, and compared simulated results with SeaWiFS-estimated TOA radiances. The difference falls within about $\pm$5%, suggesting that OMSI sensor can be calibrated with the suggested accuracy. In order to apply this method for the OSMI sensor calibration, ground-based sun photometry and ship measurements were carried out off the east coast of Korean peninsula on May 31, 2000. Simulations of TOA radiance by using these measured data as input to the radiative transfer model show that there are substantial differences between simulated and OSMI-estimated radiances. Such a discrepancy appears to be mainly due to the cloud contamination because satellite image indicates optically thin clouds over the experimental area. Nevertheless results suggest that sensor calibration can be achieved within 5% uncertainty range if there are ground-based measurements of aerosol optical thickness, and water leaving radiances under clear-sky and optically thin atmospheric conditions.

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.639-648
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• 2018

The pyranometer for observing the solar radiation reaching the surface of the earth is manufactured by various companies around the world. The sensitivity of the pyranometer at the observatory is required to be properly controlled based on the reference value of the World Radiometric Center (WRC) and the observatory environment; otherwise, the observational data may be subject to a large error. Since the sensitivity of the pyranometer can be calibrated in an indoor or outdoor calibration, this study used a CSTMUSS-4000C Integrating Sphere by Labsphere Inc. (USA) to calibrate the sensitivity of CMP22 pyranometer by Kipp&Zonen Inc. (Netherlands). Consequently, the factory sensitivity of CMP22 was corrected from $8.68{\mu}V{\cdot}(Wm^{-2})^{-1}$ to $8.98{\mu}V{\cdot}(Wm^{-2})^{-1}$, and the result from the outdoor calibration according to the observatory environment was $8.90{\mu}V{\cdot}(Wm^{-2})^{-1}$. After the indoor calibration of the pyranometer sensitivity, the root mean square error (RMSE) of the observational data at the observatory on a clear day without clouds (July 13, 2017) was $7.11Wm^{-2}$ in comparison to the reference pyranometer. After the outdoor calibration of the pyranometer sensitivity based on these results, the RMSE of the observational data was $1.74Wm^{-2}$ on the same day. Periodic inspections are required because the decrease of sensitivity over time is inevitable in the pyranometer data produced at the observatory. The initial sensitivity after indoor calibration ($8.98{\mu}V{\cdot}(Wm^{-2})^{-1}$) is important, and the sensitivity after outdoor calibration ($8.90{\mu}V{\cdot}(Wm^{-2})^{-1})$ can be compared to the data at the Baseline Surface Radiation Network (BSRN) or can be used for various studies and daily applications.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.123-132
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• 2019

This study is to estimate the spatial soil moisture using Terra MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data and machine learning technique. Using the 3 years (2015~2017) data of MODIS 16 days composite NDVI (Normalized Difference Vegetation Index) and daily Land Surface Temperature (LST), ground measured precipitation and sunshine hour of KMA (Korea Meteorological Administration), the RDA (Rural Development Administration) 10 cm~30 cm average TDR (Time Domain Reflectometry) measured soil moisture at 78 locations was tested. For daily analysis, the missing values of MODIS LST by clouds were interpolated by conditional merging method using KMA surface temperature observation data, and the 16 days NDVI was linearly interpolated to 1 day interval. By applying the RNN-LSTM (Recurrent Neural Network-Long Short Term Memory) artificial neural network model, 70% of the total period was trained and the rest 30% period was verified. The results showed that the coefficient of determination ($R^2$), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency were 0.78, 2.76%, and 0.75 respectively. In average, the clay soil moisture was estimated well comparing with the other soil types of silt, loam, and sand. This is because the clay has the intrinsic physical property for having narrow range of soil moisture variation between field capacity and wilting point.

• Journal of Soil and Groundwater Environment
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• v.23 no.2
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• pp.15-22
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• 2018

Aqua regia extraction for the quantification of heavy metals and As in contaminated soils was investigated as one of preliminary steps for on-site monitoring using sensor technology. Soil samples were taken from closed railway depot, closed mines, and closed refinery and various extraction conditions including $30^{\circ}C/15min$, $30^{\circ}C/30min$, $30^{\circ}C/60min$, $30^{\circ}C/120min$, $80^{\circ}C/15min$, $80^{\circ}C/30min$, $80^{\circ}C/60min$, $80^{\circ}C/120min$ were tested. The optimal extraction condition was determined as $80^{\circ}C/60min$ because the extraction efficiencies of Zn were relatively low and did not reach the targeted level (80-100% of original concentrations) for $30^{\circ}C$ conditions. It was found that the fractionation of heavy metals and As using the sequential extraction method was useful to understand the degree of metal extraction. In order to enhance the extraction efficiency within short extraction time, ultrasound technology using a 20 kHz horn-type sonicator was additionally used for $30^{\circ}C/15min$. It was revealed that ultrasound could significantly enhance the extraction efficiency and pulsed irradiation showed higher efficiency than continuous irradiation due to the less formation of bubble clouds. However high temperature condition ($80^{\circ}C$) was required to achieve high extraction efficiency for Zn in spite of the use of ultrasound.

• Journal of the Korean Society for Computer Game
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• v.31 no.4
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• pp.129-135
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• 2018

Electronic signatures, QR codes, and bar codes are used in payment systems used in real life. Research has begun on the payment system implemented in the VR environment. This paper proposes a VR electronic sign system that uses hand gesture recognition to implement an existing payment system in a VR environment. In a VR system, you can not hit the keyboard or touch the mouse. There can be several ways to configure a payment system with a VR controller. Electronic signage using hand gesture recognition is one of them, and hand gesture recognition can be classified by the Warping Methods, Statistical Methods, and Template Matching methods. In this paper, the payment system was configured in VR using the $p algorithm belonging to the Template Matching method. To create a VR environment, we implemented a paypal system where actual payment is made using Unity3D and Vive equipment.