• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.367-376
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• 2021

Strawberry cultivation in Korea is grown in greenhouse, but most farms manage their water supply using a timer control method based on the experience of growers. The timer control has problems in that it is difficult to consider the weather condition, the growth stage of crops, and the moisture content of the substrate, so that the crops cannot be managed at an optimal level, and the accuracy of cultivation management are lacking. The watering methods using integrated solar irradiance and substrate moisture contents are control systems that provide eco-friendly and precise water supply considering the growth conditions of crops. The purpose of this study was to compare the combined water supply control with integrated solar irradiance and substrate moisture contents and timer control method in hydroponic cultivation of strawberries using coir, and to set the optimal integrated solar irradiance level for complex water supply control. The irrigation system was automatically watered when it reached 100, 150, 250 J·cm^-2 based on the external solar irradiance, and forced irrigation was performed at a substrate moisture content of less than 60% in all treatments. The amount of irrigation at once was 50 mL. The timer treatment was applied as a control. The smaller the level of integrated radiation to start watering, the greater the daily amount of irrigation. Both the fresh weight and dry weight per plant were higher in the complex irrigation control method than the timer control, and the 100 and 150 J·cm^-2 treatment had the highest fresh weight, and the 100 J·cm^-2 treatment showed a significantly higher dry weight. The yield was also significantly higher in the complex control method than in the timer, and the early yield increased as the level of integrated solar irradiance was smaller. The fresh weight of fruit was the lowest in the timer-controlled irrigation. As a result of this study, the possibility of combined control irrigation method using integrated solar irradiance and substrate moisture content was confirmed for precise water supply management of strawberries in hydroponics.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1631-1645
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• 2021

This research aims to provide the characteristics of the world's first active lidar sensor Atmospheric Laser Doppler Instrument (ALADIN) wind data and Geostationary Korea Multi Purpose Satellite 2A (GK2A) Atmospheric Motion Vector (AMV) data by comparing two wind data. As a result of comparing the data from September 2019 to August 1, 2020, The total number of collocated data for the AMV (using IR channel) and Mie channel ALADIN data is 177,681 which gives the Root Mean Square Error (RMSE) of 3.73 m/s and the correlation coefficient is 0.98. For a more detailed analysis, Comparison result considering altitude and latitude, the Normalized Root Mean Squared Error (NRMSE) is 0.2-0.3 at most latitude bands. However, the upper and middle layers in the lower latitudes and the lower layer in the southern hemispheric are larger than 0.4 at specific latitudes. These results are the same for the water vapor channel and the visible channel regardless of the season, and the channel-specific and seasonal characteristics do not appear prominently. Furthermore, as a result of analyzing the distribution of clouds in the latitude band with a large difference between the two wind data, Cirrus or cumulus clouds, which can lower the accuracy of height assignment of AMV, are distributed more than at other latitude bands. Accordingly, it is suggested that ALADIN wind data in the southern hemisphere and low latitude band, where the error of the AMV is large, can have a positive effect on the numerical forecast model.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1829-1836
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• 2021

Cloud detection means determining the presence or absence of clouds in a pixel in a satellite image, and acts as an important factor affecting the utility and accuracy of the satellite image. In this study, among the satellites of various advanced organizations that provide cloud detection data, we intend to perform quantitative and qualitative comparative analysis on the difference between the cloud detection data of GK-2A/AMI, Terra/MODIS, and Suomi-NPP/VIIRS. As a result of quantitative comparison, the Proportion Correct (PC) index values in January were 74.16% for GK-2A & MODIS, 75.39% for GK-2A & VIIRS, and 87.35% for GK-2A & MODIS in April, and GK-2A & VIIRS showed that 87.71% of clouds were detected in April compared to January without much difference by satellite. As for the qualitative comparison results, when compared with RGB images, it was confirmed that the results corresponding to April rather than January detected clouds better than the previous quantitative results. However, if thin clouds or snow cover exist, each satellite were some differences in the cloud detection results.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.321-335
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• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.36-49
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• 2019

The objectives of this study were to extract "Field Survey Based Infection Tree of Pine Wilt Disease(FSB_ITPWD)" and "Object Classification Based Infection Tree of Pine Wilt Disease(OCB_ITPWD)" from the Research Forest at Kangwon National University, and evaluate the spatial distribution characteristics and occurrence intensity of wood infested by pine wood nematode. It was found that the OCB optimum weights (OCB) were 11 for Scale, 0.1 for Shape, 0.9 for Color, 0.9 for Compactness, and 0.1 for Smoothness. The overall classification accuracy was approximately 94%, and the Kappa coefficient was 0.85, which was very high. OCB_ITPWD area is approximately 2.4ha, which is approximately 0.05% of the total area. When the stand structure, distribution characteristics, and topographic and geographic factors of OCB_ITPWD and those of FSB_ITPWD were compared, age class IV was the most abundant age class in FSB_ITPWD (approximately 55%) and OCB_ITPWD (approximately 44%) - the latter was 11% lower than the former. The diameter at breast heigh (DBH at 1.2m from the ground) results showed that (below 14cm) and (below 28cm) DBH trees were the majority (approximately 93%) in OCB_ITPWD, while medium and (more then 30cm) DBH trees were the majority (approximately 87%) in FSB_ITPWD, indicating different DBH distribution. On the other hand, the elevation distribution rate of OCB_ITPWD was mostly between 401 and 500m (approximately 30%), while that of FSB_ITPWD was mostly between 301 and 400m (approximately 45%). Additionally, the accessibility from the forest road was the highest at "100m or less" for both OCB_ITPWD (24%) and FSB_ITPWD (31%), indicating that more trees were infected when a stand was closer to a forest road with higher accessibility. OCB_ITPWD hotspots were 31 and 32 compartments, and it was highly distributed in areas with a higher age class and a higher DBH class.

• Journal of the Korean Society of Radiology
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• v.12 no.6
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• pp.737-743
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• 2018

Patient exposure dose exposure test, which is one of the items of accuracy control of Computed Tomography, conducts measurements every year based on the installation and operation of special medical equipment under Article 38 of the Medical Law, And keep records. The CT-Dose phantom used for dosimetry can accurately measure doses, but has the disadvantage of high price. Therefore, through this research, the existing CT - Dose phantom was similarly manufactured with a 3D printer and compared with the existing phantom to examine the usefulness. In order to produce the same phantom as the conventional CT-Dose phantom, a 3D printer of the FFF method is used by using a PLA filament, and in order to calculate the CTDIw value, Ion chambers were inserted into the central part and the central part, and measurements were made ten times each. Measurement results The CT-Dose phantom was measured at $30.44{\pm}0.31mGy$ in the periphery, $29.55{\pm}0.34mGy$ CTDIw value was measured at $30.14{\pm}0.30mGy$ in the center, and the phantom fabricated using the 3D printer was measured at the periphery $30.59{\pm}0.18mGy$, the central part was $29.01{\pm}0.04mGy$, and the CTDIw value was measured at $30.06{\pm}0.13mGy$. Analysis using the Mann - Whiteney U-test of the SPSS statistical program showed that there was a statistically significant difference in the result values in the central part, but statistically significant differences were observed between the peripheral part and CTDIw results I did not show. In conclusion, even in the CT-Dose phantom made with a 3D printer, we showed dose measurement performance like existing CT-Dose phantom and confirmed the possibility of low-cost phantom production using 3D printer through this research did it.

• The Journal of Korean Academy of Prosthodontics
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• v.57 no.3
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• pp.211-218
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• 2019

Purpose: The purpose of the present study was to compare the accuracy of four different metal copings fabricated by CAD/CAM technology and to evaluate clinical effectiveness. Materials and methods: Composite resin tooth of the maxillary central incisor was prepared for a metal ceramic crown and duplicated metal die was fabricated. Then scan the metal die for 12 times to obtain STL files using a confocal microscopy type oral scanner. Metal copings with a thickness of 0.5 mm and a cement space of $50{\mu}m$ were designed on a CAD program. The Co-Cr metal copings were fabricated by the following four methods: Wax pattern milling & Casting (WM), Resin pattern 3D Printing & casting (RP), Milling & Sintering (MS), Selective laser melting (SLM). Silicone replica technique was used to measure marginal and internal discrepancies. The data was statistically analyzed with One-way analysis of variance and appropriate post hoc test (Scheffe test) (${\alpha}=.05$). Results: Mean marginal discrepancy was significantly smaller in the Group WM ($27.66{\pm}9.85{\mu}m$) and Group MS ($28.88{\pm}10.13{\mu}m$) than in the Group RP ($38.09{\pm}11.14{\mu}m$). Mean cervical discrepancy was significantly smaller in the Group MS than in the Group RP. Mean axial discrepancy was significantly smaller in the Group WM and Group MS then in the Group RP and Group SLM. Mean incisal discrepancies was significantly smaller in the Group RP than in all other groups. Conclusion: The marginal and axial discrepancies of the Co-Cr coping fabricated by the Wax pattern milling and Milling/Sintering method were better than those of the other groups. The marginal, cervical and axial fit of Co-Cr copings in all groups are within a clinically acceptable range.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.82-98
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• 2019

The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.4
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• pp.94-104
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• 2018

This study examined photogrammetric reconstruction techniques that can measure the original form of a cultural property utilizing photographs taken in the past. During the research process, photographs taken in the past as well as photograph on the internet of Soswaewon Garden in Damyang(scenic site 40) were collected and utilized. The landscaping structures of Maedae, Aiyangdan, Ogokmun Wall, and Yakjak and natural scenery Gwangseok, of which photographs can be taken from any 360 degree direction from a close distance or a far distance without any barriers in the way, were selected and tested for the possibility of reproducing three-dimensional shapes. The photography method of 151 landscape photographs (58.6%) from internet portal sites for the aforementioned five landscape subjects containing information on the date the photograph was taken, focal length, and exposure were analyzed. As a result of the analysis, it was revealed that the majority of the photographs tend to focus on important parts of each subject. In addition, we discovered that there are two or three photography methods that internet users preferred in regards to each landscape subject. For the purposes of the experiment, photographs in which a single scene consistently appears for each landscape subject and it was determined that there was a high level of preference related to the photography method were analyzed, and three-dimensional mesh shape model was produced with a photoscan program to analyze the reproducibility of three-dimensional shapes. Based on the results of the reproduction, it was relatively possible to reproduce three-dimensional shapes for artifacts such as Ogukmun wall, Maedae, and Aeyangdan, but it was impossible to reproduce three-dimensional images for natural scenery or an object that has similar texture such as Yakjak and Gwangseok. As a result of experimentation related to the reconstruction of three-dimensional shapes with the photographs taken on site using a photography method similar to that of the photographs selected as previously mentioned, there was success related to reproducing the three-dimensional shapes of Yakjak and Gwangseok, of which it was not possible to do so through the photographs that had been collected previously. In addition, through comparison of past and present images, it was possible to measure the exact sizes as well as discover any changes that have taken place. If past photographs taken by tourists or landscape architects of cultural properties can be obtained, the three-dimensional shapes from a particular period of time can be reproduced. If this technology becomes widespread, it will increase the level of accuracy and reliability in regards to measuring the past shapes of cultural landscape properties and examining any changes to the properties.

• Economic and Environmental Geology
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• v.54 no.2
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• pp.177-186
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• 2021

For disaster management and mitigation of earthquakes in Korea Peninsula, active fault investigation has been conducted for the past 5 years. In particular, investigation of sediment-covered active faults integrates geomorphological analysis on airborne LiDAR data, surface geological survey, and geophysical exploration, and unearths subsurface active faults by trench survey. However, the fault traces revealed by trench surveys are only available for investigation during a limited time and restored to the previous condition. Thus, the geological data describing the fault trench sites remain as the qualitative data in terms of research articles and reports. To extend the limitations due to temporal nature of geological studies, we utilized a terrestrial LiDAR to produce 3D point clouds for the fault trench sites and restored them in a digital space. The terrestrial LiDAR scanning was conducted at two trench sites located near the Yangsan Fault and acquired amplitude and reflectance from the surveyed area as well as color information by combining photogrammetry with the LiDAR system. The scanned data were merged to form the 3D point clouds having the average geometric error of 0.003 m, which exhibited the sufficient accuracy to restore the details of the surveyed trench sites. However, we found more post-processing on the scanned data would be necessary because the amplitudes and reflectances of the point clouds varied depending on the scan positions and the colors of the trench surfaces were captured differently depending on the light exposures available at the time. Such point clouds are pretty large in size and visualized through a limited set of softwares, which limits data sharing among researchers. As an alternative, we suggested Potree, an open-source web-based platform, to visualize the point clouds of the trench sites. In this study, as a result, we identified that terrestrial LiDAR data can be practical to increase reproducibility of geological field studies and easily accessible by researchers and students in Earth Sciences.