• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1393-1405
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• 2020

UAV (Unmanned Aerial Vehicle) can acquire high-resolution images due to low-altitude flight, and it can be photographed at any time. Therefore, the UAV images can be updated at any time in map production. Due to these advantages, studies on the possibility of producing large-scale digital maps using UAV images are actively being conducted. Precise digital maps can be used as base data for digital twins or smart cites. For producing a precise digital map, precise sensor modeling using GCPs (Ground Control Points) must be preceded. In this study, geometric models of UAV images were established through a precision sensor modeling algorithm developed in house. Then, a digital map by stereo plotting was produced to evaluate the possibility of large-scale digital map. For this study, images and GCPs were acquired for Ganseok-dong, Incheon and Yeouido, Seoul. As a result of precision sensor modeling accuracy analysis, high accuracy was confirmed within 3 pixels of the average error of the checkpoints and 4 pixels of the RMSE was confirmed for the two study regions. As a result of the mapping accuracy analysis, it satisfied the 1:1,000 mapping accuracy announced by the NGII (National Geographic information Institute). Therefore, the precision sensor modeling technology suggested the possibility of producing a 1:1,000 large-scale digital map by UAV images.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.46 no.4
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• pp.415-424
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• 2020

In the present study, we have refined gomisin N, which represents activity in the proliferation of dermal papilla cells (HFDPCs) from the fruit of Schisandra chinensis (S. chinensis), and have identified optimal extraction conditions for obtaining extracts with high content of gomisin N. The activity of the extracts and fractions was evaluated, and the results indicated approximately 29% proliferation activity in the group treated with 1 ㎍/mL of n-hexane fraction. Column chromatography was used to assess the active ingredient in the n-hexane fraction, and two compounds, namely gomisin N(1) and schisandrin(2), were isolated and identified. When the HFDPCs proliferation activity was tested for the isolated compounds, gomisin N exhibited ≥ 20% proliferation activity. Thus, via response surface methodology (RSM), the optimum extraction conditions to obtain the maximum level of gomisin N from the fruit of S. chinensis were determined, where ethanol proportion, extraction time, and extraction temperature were used as the independent variables. The results revealed coefficient of determination ≥ 0.95 and p-value ≤ 0.05, which confirmed the fit of the model. The optimum extraction conditions to achieve the maximum content of gomisin N were as follows: ethanol proportion 83.8%, extraction temperature 80 ℃, and extraction time 8.7 h. The content of gomisin N using these conditions was predicted as 378,300 ppm, and a mean value close to the predicted value (376,884 ppm) was obtained while validating the aforementioned conditions.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1579-1590
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• 2020

In this paper, spatially-adaptive denormalization (SPADE) based U-Net is proposed to detect changes by using high-resolution satellite images. The proposed network is to preserve spatial information using SPADE. Change detection methods using high-resolution satellite images can be used to resolve various urban problems such as city planning and forecasting. For using pixel-based change detection, which is a conventional method such as Iteratively Reweighted-Multivariate Alteration Detection (IR-MAD), unchanged areas will be detected as changing areas because changes in pixels are sensitive to the state of the environment such as seasonal changes between images. Therefore, in this paper, to precisely detect the changes of the objects that consist of the city in time-series satellite images, the semantic spatial objects that consist of the city are defined, extracted through deep learning based image segmentation, and then analyzed the changes between areas to carry out change detection. The semantic objects for analyzing changes were defined as six classes: building, road, farmland, vinyl house, forest area, and waterside area. Each network model learned with KOMPSAT-3A satellite images performs a change detection for the time-series KOMPSAT-3 satellite images. For objective assessments for change detection, we use F1-score, kappa. We found that the proposed method gives a better performance compared to U-Net and UNet++ by achieving an average F1-score of 0.77, kappa of 77.29.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.547-554
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• 2021

In order to quickly and accurately diagnose pneumonia on a chest X-ray image, different batch sizes of 4, 8, 16, and 32 were applied to the same Xception deep learning model, and modeling was performed 3 times, respectively. As a result of the performance evaluation of deep learning modeling, in the case of modeling to which batch size 32 was applied, the results of accuracy, loss function value, mean square error, and learning time per epoch showed the best results. And in the accuracy evaluation of the Test Metric, the modeling applied with batch size 8 showed the best results, and the precision evaluation showed excellent results in all batch sizes. In the recall evaluation, modeling applied with batch size 16 showed the best results, and for F1-score, modeling applied with batch size 16 showed the best results. And the AUC score evaluation was the same for all batch sizes. Based on these results, deep learning modeling with batch size 32 showed high accuracy, stable artificial neural network learning, and excellent speed. It is thought that accurate and rapid lesion detection will be possible if a batch size of 32 is applied in an automatic diagnosis study for feature extraction and classification of pneumonia in chest X-ray images using deep learning in the future.

• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.216-227
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• 2022

The MPEG-I (Immersive) group is working on a standardization project for immersive video that provides 6 degrees of freedom (6DoF). The MPEG Immersion Video (MIV) standard technology is intended to provide limited 6DoF based on depth map-based image rendering (DIBR) technique. Many efficient coding methods have been suggested for MIV, but efficient transmission strategies have received little attention in MPEG-I. This paper proposes group-based adaptive rendering method for immersive video streaming. Each group can be transmitted independently using group-based encoding, enabling adaptive transmission depending on the user's viewport. In the rendering process, the proposed method derives weights of group for view synthesis and allocate high quality bitstream according to a given viewport. The proposed method is implemented through the Test Model for Immersive Video (TMIV) test model. The proposed method demonstrates 17.0% Bjontegaard-delta rate (BD-rate) savings on the peak signalto-noise ratio (PSNR) and 14.6% on the Immersive Video PSNR(IV-PSNR) in terms of various end-to-end evaluation metrics in the experiment.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.283-298
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• 2022

As Synthetic Aperture Radar (SAR) image can be acquired regardless of the weather and day or night, it is highly recommended to be used for Automatic Target Recognition (ATR) in the fields of surveillance, reconnaissance, and national security. However, there are some limitations in terms of cost and operation to build various and vast amounts of target images for the SAR-ATR system. Recently, interest in the development of an ATR system based on simulated SAR images using a target model is increasing. Attributed Scattering Center (ASC) matching and template matching mainly used in SAR-ATR are applied to target classification. The method based on ASC matching was developed by World View Vector (WVV) feature reconstruction and Weighted Bipartite Graph Matching (WBGM). The template matching was carried out by calculating the correlation coefficient between two simulated images reconstructed with adjacent points to each other. For the performance analysis of the two proposed methods, the Synthetic and Measured Paired Labeled Experiment (SAMPLE) dataset was used, which has been recently published by the U.S. Defense Advanced Research Projects Agency (DARPA). We conducted experiments under standard operating conditions, partial target occlusion, and random occlusion. The performance of the ASC matching is generally superior to that of the template matching. Under the standard operating condition, the average recognition rate of the ASC matching is 85.1%, and the rate of the template matching is 74.4%. Also, the ASC matching has less performance variation across 10 targets. The ASC matching performed about 10% higher than the template matching according to the amount of target partial occlusion, and even with 60% random occlusion, the recognition rate was 73.4%.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.35-40
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• 2022

In the agricultural environment, pesticide control requires a high risk of work and a high labor force for farmers. The effectiveness of pesticide control using unmanned aerial vehicles varies according to climate, land type, and characteristics of unmanned aerial vehicles. Therefore, an effective method for pesticide control by unmanned aerial vehicles considering the spraying conditions and environmental conditions is required. In this paper, we propose an efficient pesticide control system based on agricultural unmanned aerial vehicles considering the application conditions and environmental information for each crop. The effectiveness of the proposed model was demonstrated by measuring the drop uniformity of pesticides according to the change in altitude and speed after attaching the sensory paper and measuring the penetration rate of the drug inside the canopy according to the change in crop growth conditions. Experiment result, the closer the height of the UAV is to the ground, the more evenly the crops are sprayed, but for safety reasons, 2m more is suitable, and on average a speed of 2m/s is most suitable for control. The proposed control system is expected to help develop intelligent services based on the use of various unmanned aerial vehicles in agricultural environments.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1385-1394
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• 2022

This study was to analyze the change in albedo by level-2 land cover map for 20 years(2002-2021) using MODerate resolution Imaging Spectroradiometer (MODIS) data. Also, the difference from the MODIS data was analyzed using the 10-year (2012-2021) data of Visible Infrared Imaging Radiometer Suite (VIIRS). For the albedo data of MODIS and VIIRS, daily albedo data, MCD43A3 and VNP43IA, of 500 m spatial resolution of sinusoidal tile grid produced by Bidirectional Reflectance Distribution Function (BRDF) model were prepared for the South Korea range. Reprojection was performed using the code written based on Python 3.9, and the nearest neighbor was applied as the resampling method. White sky albedo and black sky albedo of shortwave were used for analysis. As a result of 20-year albedo analysis using MODIS data, the albedo tends to rise in all land use. Compared to the 2000s (2002-2011), the average albedo of the 2010s (2012-2021) showed the most significant increase of 0.0027 in the forest area, followed by the grass increase of 0.0024. As a result of comparing the albedo of VIIRS and MODIS, it was found that the albedo of VIIRS was larger from 0.001 to 0.1, which was considered to be due to differences in the surface reflectivity according to the time of image capture and sensor characteristics.

• Research in Plant Disease
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• v.28 no.3
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• pp.143-151
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• 2022

In order to investigate the cause of wilting symptoms in red pepper field of Korea, the frequency of occurrence of red peppers showing wilting symptoms was investigated in pepper cultivation fields in Goesan, Chungcheongbuk-do for 5 years from 2010 to 2014. There was a difference in the frequency of wilting symptoms depending on the year of investigation, but the frequency of occurrence increased as the investigation period passed from June and July to August. During this period, Ralstonia solanacearum causing the bacterial wilt was isolated at a rate four times higher than Phytophthora capsica causing the Phytophthora late blight. In wilted peppers collected in Goesan of Chungbuk and Andong of Gyeongbuk in 2013 and 2014, R. solanacearum and P. capsici were isolated from 20.3% and 3.8% of the total fields, respectively. In the year with a high rate of wilting symptoms, the average temperature was high, and the disease occurrence date of the bacterial wilt, estimated with disease forecasting model, was also fast. The inconsistency between the number of days at risk of Phytophthora late blight and the frequency of occurrence of wither symptoms is thought to be due to the generalization of the use of cultivars resistant to the Phytophthora late blight in the pepper field. In our study, the wilting symptoms were caused by the bacterial wilt caused by R. solanacearum rather than the Phytophthora late blight caused by P. capsica, which is possibly caused by increasing cultivation of pepper varieties resistant to the Phytophthora late blight in the field.

• Korean Journal of School Psychology
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• v.17 no.2
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• pp.181-198
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• 2020

This study examined how the rejection sensitivity model might be applied to the link between rejection sensitivity and dating relationship satisfaction by means of investigating the mediating effect of cognitive emotion regulation strategy and conflict resolution strategy. A total of 668 college students in Seoul (232 males, 436 females, mean age of 21.59 years [SD=2.08]) participated in this study. The results illustrated that the adaptive emotion regulation strategy, among cognitive emotion regulation strategies, and the integration and compromise strategies, among conflict resolution strategies, had the double mediation effect on the association between rejection sensitivity and dating relationship satisfaction. In other words, a direct negative correlation between rejection sensitivity and dating relationship satisfation resulted in high rejection sensitivity, which was expected to generate low satisfaction in dating relationships. However, it was confirmed that the use of these two strategies-the cognitive emotion regulation and the conflict resolution strategy-could bring positive effects in terms of the dating relationship satisfaction; the former helped couples to see situations more broadly and increase positive perceptions, while the latter solve their problems each other. Based on these findings, we discuss their implications for counseling practice and therapeutic interventions