• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.518-518
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• 2023

자연하천에서 오염물질의 혼합 거동은 비균일한 지형학적 요인으로 인해 매우 복잡한 특성을 나타낸다. 일반적으로 오염물질 거동 모델링에서는 수체에서의 혼합을 Fick의 법칙에 따라 유속에 의한 이송과 난류에 의한 확산으로 계산하고, 국부적인 정체현상 등에 의한 non-Fickian 혼합을 야기하는 하천의 특성을 기하학적 지형 형상으로 구현하여 실제 현상에 근접한 혼합 거동을 재현한다. 하지만 계산의 효율성을 위하여 모델링의 차원을 낮추는 경우, 하천의 지형을 경계조건으로 고려할 수 없게 된다. 특히, 1차원 모델링의 경우 하천의 비균일성을 무시하고 1개의 유선으로 간주하며, 이 경우 non-Fickian 물질이동 해석을 위한 추가적인 현상학적 해석이 필요하다. 지난 50년간, non-Fickian 물질이동 해석을 위한 다양한 현상학적 모형이 제시되어 왔다. 하천을 흐름영역과 정체영역으로 구분하고 두 개의 영역 사이의 물질교환 속도를 모델링하거나, Random walk 개념으로 물질이 이동하는 경우와 이동하지 않는 경우를 확률론적으로 모델링하거나, 물질이 정체되었을 때 다시 빠져나오는 시간을 모델링하는 경우가 그 예이다. 본 연구에서는 선행연구에서 제시한 음함수 형태의 현상학적 모형을 기반으로, 수치적 반복계산 없이 상류 경계에서 임의의 형태의 농도곡선(shape-free breakthrough curve)을 갖는 오염물질운(cloud)이 일정 거리를 유하하며 발생하는 변화를 예측할 수 있는 해를 제시한다. 본 연구의 방법론은 추적법(routing procedure)을 활용한 Fickian 혼합 해석, 전달함수(transfer function) 형태의 정체시간분포 해석, 그리고 라플라스 도메인에서의 해석해 유도를 포함한다. 본 연구에서 제시된 해는 2020년 경상북도 김천시에 위치한 감천의 4.5 km 구간에서 수행한 추적자 실험의 현장 자료를 통해 정확도를 검증하여 타당성을 입증하였다.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.179-190
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• 2024

This study aims to compare supervised classification methods with phenology-based approaches, specifically pixel-based and segment-based methods, for accurate crop mapping in agricultural landscapes. We utilized Sentinel-2A imagery, which provides multispectral data for accurate crop mapping. 31 normalized difference vegetation index (NDVI) images were calculated from the Sentinel-2A data. Next, we employed phenology-based approaches to extract valuable information from the NDVI time series. A set of 10 phenology metrics was extracted from the NDVI data. For the supervised classification, we employed the maximum likelihood (MaxLike) algorithm. For the phenology-based approaches, we implemented both pixel-based and segment-based methods. The results indicate that phenology-based approaches outperformed the MaxLike algorithm in regions with frequent rainfall and cloudy conditions. The segment-based phenology approach demonstrated the highest kappa coefficient of 0.85, indicating a high level of agreement with the ground truth data. The pixel-based phenology approach also achieved a commendable kappa coefficient of 0.81, indicating its effectiveness in accurately classifying the crop types. On the other hand, the supervised classification method (MaxLike) yielded a lower kappa coefficient of 0.74. Our study suggests that segment-based phenology mapping is a suitable approach for regions like South Korea, where continuous cloud-free satellite images are scarce. However, establishing precise classification thresholds remains challenging due to the lack of adequately sampled NDVI data. Despite this limitation, the phenology-based approach demonstrates its potential in crop classification, particularly in regions with varying weather patterns.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.953-966
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• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

• Journal of the Korean earth science society
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• v.32 no.7
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• pp.809-831
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• 2011

Sea Surface Temperature (SST) is one of the most important oceanic variables to understand rapidly-changing climate, so that accurate and error-free SST images should be presented in school science textbooks. However, satelliteobserved SST images in the high-school textbooks presented some errors caused by various reasons. This study analyzed 36 satellite images for SST presented in 24 kinds of high-school textbooks (earth science I and II textbooks on the basis of the 7th National Curriculum) for 17 items. This study investigated errors in image processing such as cloud removal, land masking, color bar, geological and time information, and some erroneous expressions related to the fundamental information of satellites. Twenty five pre-service teachers filled out a survey about several problematic satellite images, and their responses were analyzed. As a result, most of the pre-service teachers did not recognize the errors associated with image processing and tended to comprehend the SST errors as real oceanographic phenomena such as sea ice, river outflow, or cold current. Therefore, satellite SST images in the textbooks should be accurately presented by including detailed items suggested in this study.

• Korean Journal of Environment and Ecology
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• v.28 no.4
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• pp.484-489
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• 2014

In this paper, we examined factors that influenced light pollution in Korean national parks during peak and off-peak tourist seasons. Cloud-and moonlight-free nighttime satellite images that were collected during October 2012(for peak season) and January 2013(for off-peak season) by the Day and Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor were used to estimate the levels of light pollution in 19 national parks (excluding the Bukhansan and Mudeungsan National Parks). Bootstrapping regression analyses were conducted to examine the effects of socioeconomic and policy factors on light pollution in the study national parks for peak and off-peak tourist seasons, separately. The characteristics of light pollution in the national parks varied by season. During the peak tourist season, light pollution in the national parks were affected more by night lights nearby the parks than those within in the parks, while in the off-peak season, light sources in the parks were more important. Scattering of light emitted from hotels and other recreational facilities outside the parks that led to the sky glow effect can be attributed to the greater impact of night lights nearby the parks during the peak season. This result suggests that regulating light pollution nearby the park areas is needed to mitigate light pollution in the national parks, especially in a peak tourist season.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.2
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• pp.205-213
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• 2018

Development and validation of crop models often require measurements of biomass for the crop of interest. Considerable efforts would be needed to obtain a reasonable amount of biomass data because the destructive sampling of a given crop is usually used. The Kinect sensor, which has a combination of image and depth sensors, can be used for estimating crop biomass without using destructive sampling approach. This approach could provide more data sets for model development and validation. The objective of this study was to examine the applicability of the Kinect sensor for estimation of chinese cabbage fresh weight. The fresh weight of five chinese cabbage was measured and compared with estimates using the Kinect sensor. The estimates were obtained by scanning individual chinese cabbage to create point cloud, removing noise, and building a three dimensional model with a set of free software. It was found that the 3D model created using the Kinect sensor explained about 98.7% of variation in fresh weight of chinese cabbage. Furthermore, the correlation coefficient between estimates and measurements were highly significant, which suggested that the Kinect sensor would be applicable to estimation of fresh weight for chinese cabbage. Our results demonstrated that a depth sensor allows for a non-destructive sampling approach, which enables to collect observation data for crop fresh weight over time. This would help development and validation of a crop model using a large number of reliable data sets, which merits further studies on application of various depth sensors to crop dry weight measurements.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.554-557
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• 2016

Recently, supercomputer has been increasingly adopted as a computing environment for scientific simulation as well as education, healthcare and national defence. Especially, supercomputing system with heterogeneous computing resources is gaining resurgence of interest as a next-generation problem solving environment, allowing theoretical and/or experimental research in various fields to be free of time and spatial limits. However, traditional supercomputing services have only been handled through a simple form of command-line based console, which leads to the critical limit of accessibility and usability of heterogeneous computing resources. To address this problem, in this paper, we provide the design and implementation of web-based HPC (High Performance Computing) job management framework for computational scientific simulation. The proposed framework has highly extensible design principles, providing the abstraction interfaces of job scheduler (as well as bundle scheduler plug-ins for LoadLeveler, Sun Grid Engine, OpenPBS scheduler) in order to easily incorporate the broad spectrum of heterogeneous computing resources such as cluster, computing cloud and grid. We also present the detailed specification of HTTP standard based RESTful endpoints, which manage simulation job's life-cycles such as job creation, submission, control and status monitoring, etc., enabling various 3rd-party applications to be newly created on top of the proposed framework.

• Advances in Energy Research
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• v.1 no.2
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• pp.147-163
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• 2013

The world faces several issues of energy crisis and environmental deterioration due to over-dependence on single source of which is fossil fuel. Though, fuel is needed as ingredients for industrial development and growth of any country, however the fossil fuel which is a major source of energy for this purpose has always been terrifying thus the need for alternative and renewable energy sources. The search for alternative energy sources resulted into the acceptance of a biofuel as a reliable alternative energy source. This work presents the study of optimization of process of transesterification of vegetable oil to biodiesel using NaOH as catalyst. A $2^4$ factorial design method was employed to investigate the influence of ratio of oil to methanol, temperature, NaOH concentration, and transesterification time on the yield of biodiesel from vegetable oil. Low and high levels of the key factors considered were 4:1 and 6:1 mole ratio, 30 and $60^{\circ}C$ temperatures, 0.5 and 1.0 wt% catalyst concentration, and 30 and 60 min reaction time. Results obtained revealed that oil to methanol molar ratio of 6:1, tranesetrification temperature of $60^{\circ}C$, catalyst concentration of 1.0wt % and reaction time of 30 min are the best operating conditions for the optimum yield of biofuel from vegetable oil, with optimum yield of 95.8%. Results obtained on the characterizzation of the produced biodiesel indicate that the specific gravity, cloud point, flash point, sulphur content, viscosity, diesel index, centane number, acid value, free glycerine, total glycerine and total recovery are 0.8899, 4, 13, 0.0087%, 4.83, 25, 54.6. 0.228mgKOH/g, 0.018, 0.23% and 96% respectively. Results also indicate that the qualities of the biodiesel tested for are in conformity with the set standard. A model equation was developed based on the results obtained using a statistical tool. Analysis of variance (ANOVA) of data shows that mole ratio of ground nut oil to methanol and transesterification time have the most pronounced effect on the biodiesel yield with contributions of 55.06% and 9.22% respectively. It can be inferred from the results various conducted that vegetable oil locally produced from groundnut oil can be utilized as a feedstock for biodiesel production.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.62-77
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• 2019

Open Data Cube(ODC) has been emerging and developing as the open source platform in the Committee on Earth Observation Satellites(CEOS) for the Global Earth Observation System of Systems(GEOSS) deployed by the Group on Earth Observations (GEO), ODC can be applied to the deployment of scalable and large amounts of free and open satellite images in a cloud computing environment, and ODC-based country or regional application services have been provided for public users on the high performance. This study first summarizes the status of ODC, and then presents concepts and some considering points for linking this platform with Korea Multi-Purpose Satellite (KOMPSAT) images. For the reference, the main contents of ODC with the Google Earth Engine(GEE) were compared. Application procedures of KOMPSAT satellite image to implement ODC service were explained, and an intermediate process related to data ingestion using actual data was demonstrated. As well, it suggested some practical schemes to utilize KOMPSAT satellite images for the ODC application service from the perspective of open data licensing. Policy and technical products for KOMPSAT images to ODC are expected to provide important references for GEOSS in GEO to apply new satellite images of other countries and organizations in the future.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.7
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• pp.445-454
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• 2022

Ice accretion on the aircraft components, such as wings, fuselage, and empennage, can occur when the aircraft encounters a cloud zone with high humidity and low temperature. The prevention of ice accretion is important because it causes a decrease in the aerodynamic performance and flight stability, thus leading to fatal safety problems. In this study, a shape design optimization of a multi-element airfoil is performed to minimize the amount of ice accretion on the high-lift device including leading-edge slat, main element, and trailing-edge flap. The design optimization framework proposed in this paper consists of four major parts: air flow, droplet impingement and ice accretion simulations and gradient-free optimization algorithm. Reynolds-averaged Navier-Stokes (RANS) simulation is used to predict the aerodynamic performance and flow field around the multi-element airfoil at the angle of attack 8°. Droplet impingement and ice accretion simulations are conducted using the multi-physics computational analysis tool. The objective function is to minimize the total mass of ice accretion and the design variables are the deflection angle, gap, and overhang of the flap and slat. Kriging surrogate model is used to construct the response surface, providing rapid approximations of time-consuming function evaluation, and genetic algorithm is employed to find the optimal solution. As a result of optimization, the total mass of ice accretion on the optimized multielement airfoil is reduced by about 8% compared to the baseline configuration.