• Journal of the Korean Society of Radiology
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• v.16 no.7
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• pp.975-984
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• 2022

Since a linear transducer has an area of interest equal to the length of the transducer, the area of interest can be expanded using the virtual convex function installed in the device.However, it was thought that the change in the direction of the ultrasonic sound velocity according to the change in the visual area of interest would affect the image quality, so this was objectively confirmed. For this study, image evaluation and SNR·CNR of the phantom for ultrasound quality control were measured. As a result, in the phantom image evaluation, both images were able to identify structures in functional resolution, grayscale, and dynamic range. However, it was confirmed that the standard image was excellent in the reproducibility of the size and shape of the structure. As a result of SNR·CNR evaluation, SNR·CNR of most trapezoidal images was low, except for structures at specific locations. In addition, through the statistical analysis graph, it was further confirmed that the SNR and CNR for each depth decreased as the size of the cystic structure decreased. Through this study, it was confirmed that the use of the function has the advantage of providing a wide visual area of interest, but it has an effect on the image quality. Therefore, when using the virtual convex function, it is judged that the examiner should use it in an appropriate situation and conduct various studies to acquire high-quality images and to improve the understanding and proficiency of the equipment.

• Journal of Life Science
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• v.32 no.2
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• pp.148-154
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• 2022

Focal adhesion kinase (FAK) is known to regulate cell adhesion, migration, and mechanotransduction in focal adhesions (FAs). However, studies on how FAK activity is regulated in the plasma membrane microdomains according to the composition of extracellular matrix (ECM) proteins are still lacking. A genetically encoded fluorescence resonance energy transfer (FRET)-based biosensor can provide useful information on the activity of intracellular signals with high spatiotemporal resolution. In this study, we analyzed the FAK activities in lipid raft (detergent-resistant membrane) and non-lipid raft (non-detergent-resistant membrane) microdomains using FRET-based membrane targeting FAK biosensors (FAK-Lyn and FAK-KRas biosensors) under four different ECM protein compositions: glass, type 1 collagen, fibronectin, and laminin. Interestingly, FAK activity in response to laminin in a lipid raft microdomain was lower than that in other ECM conditions. Cells subjected to fibronectin showed higher FAK activity in a lipid raft microdomain than that in a non-lipid raft microdomain. Therefore, this study demonstrates that the FAK activity can be distinctively regulated according to the ECM type and the environment of the plasma membrane microdomains.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.51-66
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• 2022

SST (Sea Surface Temperature) is based on the atmosphere-ocean interaction, one of the most important mechanisms for the Earth system. Because it is a crucial oceanic and meteorological factor for understanding climate change, gap-free grid data at a specific spatial and temporal resolution is beneficial in SST studies. This paper examined the production of daily SST grid maps from 137 stations in 2020 through the ordinary kriging with variogram optimization and their accuracy assessment. The variogram optimization was achieved by WLS (Weighted Least Squares) method, and the blind tests for the interpolation accuracy assessment were conducted by an objective and spatially unbiased sampling scheme. The four-round blind tests showed a pretty high accuracy: a root mean square error between 0.995 and 1.035℃ and a correlation coefficient between 0.981 and 0.982. In terms of season, the accuracy in summer was a bit lower, presumably because of the abrupt change in SST affected by the typhoon. The accuracy was better in the far seas than in the near seas. West Sea showed better accuracy than East or South Sea. It is because the semi-enclosed sea in the near seas can have different physical characteristics. The seasonal and regional factors should be considered for accuracy improvement in future work, and the improved SST can be a member of the SST ensemble around South Korea.

• Journal of the Korean Wood Science and Technology
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• v.51 no.3
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• pp.157-172
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• 2023

Azadirachta excelsa, is a plant belonging to the same genus as Indian neem (Azadirachta indica), and its use as a pesticide is reported by few studies. Despite being a different species, it is expected to have the same biopesticide potential as A. indica. Therefore, this study aims to investigate the anti-termite activity of n-hexane and methanol extracts of A. excelsa seed kernel at various concentrations against Coptotermes curvignathus. The methanol extract demonstrated greater termicidal activity than n-hexane at doses test of 2%, 4%, and 8%. It also showed 100% termite mortality on the third day of administering the 8% dose. According to the gas chromatography with mass spectrometry data, the putative main components of the n-hexane extract were hexadecanoic acid, ethyl ester (18.99%), 9,12-octadecadienoic acid (Z,Z)- (16.31%), and 9-octadecenal (16.23%). In contrast, the principal constituents of methanol extract were patchouli alcohol (28.1%), delta-guaiene (15.15%), and alpha-guaiene (11.93%). Furthermore, limonoids profiling of A. excelsa methanol extract was determined using Ultrahigh-performance liquid chromatography coupled with quadrupole-Orbitrap high-resolution mass spectrometry. The number of limonoids identified tentatively was fifteen, such as 6-deacetylnimbin, nimbolidin C, nimbolide, 6-acetylnimbandiol, 6-deacetyl-nimbinene, salannol, 28-deoxonimbolide, gedunin, nimbandiol, epoxyazadiradione, azadirone, 2',3'-dihydrosalannin, marrangin, nimbocinol, and azadirachtin. They were the same as those reported in the seed and leaves of A. indica, but its largest component in A. excelsa was 6-deacetylnimbin. As a result, the presence of these compounds may be responsible for the anti-termite activity of A. excelsa seed kernel extract. Additionally, column chromatography of methanol extract yielded 6-deacetylnimbin, which was found to be antifeedant and termiticide against C. curvignathus.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.5
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• pp.339-346
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• 2023

The uncertainties of microstructural features affect the properties of materials. Numerous pores that are randomly distributed in materials make it difficult to predict the properties of the materials. The distribution of pores in cementitious materials has a great influence on their mechanical properties. Existing studies focus on analyzing the statistical relationship between pore distribution and material responses, and the correlation between them is not yet fully determined. In this study, the mechanical response of cementitious materials is predicted through an image-based data approach using a convolutional neural network (CNN), and the correlation between pore distribution and material response is analyzed. The dataset for machine learning consists of high-resolution micro-CT images and the properties (tensile strength) of cementitious materials. The microstructures are characterized, and the mechanical properties are evaluated through 2D direct tension simulations using the phase-field fracture model. The attributes of input images are analyzed to identify the spot with the greatest influence on the prediction of material response through CNN. The correlation between pore distribution characteristics and material response is analyzed by comparing the active regions during the CNN process and the pore distribution.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.191-202
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• 2024

Global warming is causing abnormal climates worldwide due to the increase in greenhouse gas concentrations in the atmosphere, negatively affecting ecosystems and humanity. In response, various countries are attempting to reduce greenhouse gas emissions in numerous ways, and interest in blue carbon, carbon absorbed by coastal ecosystems, is increasing. Known to absorb carbon up to 50 times faster than green carbon, blue carbon plays a vital role in responding to climate change. Particularly, the tidal flats of South Korea, one of the world's five largest tidal flats, are valued for their rich biodiversity and exceptional carbon absorption capabilities. While previous studies on blue carbon have focused on the carbon storage and annual carbon absorption rates of tidal flats, there is a lack of research linking tidal flat area changes detected using satellite data to carbon storage. This study applied the direct difference water index to high-resolution satellite data from PlanetScope and RapidEye to analyze the area and changes of the Nakdong River estuary tidal flats over six periods between 2013 and 2023, estimating the carbon storage for each period. The analysis showed that excluding the period in 2013 with a different tidal condition, the tidal flat area changed by up to approximately 5.4% annually, ranging from about 9.38 km² (in 2022) to about 9.89 km² (in 2021), with carbon storage estimated between approximately 30,230.0 Mg C and 31,893.7 Mg C.

• Spatial Information Research
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• v.22 no.1
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• pp.55-63
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• 2014

Near surface air temperature data which are one of the essential factors in hydrology, meteorology and climatology, have drawn a substantial amount of attention from various academic domains and societies. Meteorological observations, however, have high spatio-temporal constraints with the limits in the number and distribution over the earth surface. To overcome such limits, many studies have sought to estimate the near surface air temperature from satellite image data at a regional or continental scale with simple regression methods. Alternatively, we applied various Kriging methods such as ordinary Kriging, universal Kriging, Cokriging, Regression Kriging in search of an optimal estimation method based on near surface air temperature data observed from automatic weather stations (AWS) in South Korea throughout 2010 (365 days) and MODIS land surface temperature (LST) data (MOD11A1, 365 images). Due to high spatial heterogeneity, auxiliary data have been also analyzed such as land cover, DEM (digital elevation model) to consider factors that can affect near surface air temperature. Prior to the main estimation, we calculated root mean square error (RMSE) of temperature differences from the 365-days LST and AWS data by season and landcover. The results show that the coefficient of variation (CV) of RMSE by season is 0.86, but the equivalent value of CV by landcover is 0.00746. Seasonal differences between LST and AWS data were greater than that those by landcover. Seasonal RMSE was the lowest in winter (3.72). The results from a linear regression analysis for examining the relationship among AWS, LST, and auxiliary data show that the coefficient of determination was the highest in winter (0.818) but the lowest in summer (0.078), thereby indicating a significant level of seasonal variation. Based on these results, we utilized a variety of Kriging techniques to estimate the surface temperature. The results of cross-validation in each Kriging model show that the measure of model accuracy was 1.71, 1.71, 1.848, and 1.630 for universal Kriging, ordinary Kriging, cokriging, and regression Kriging, respectively. The estimates from regression Kriging thus proved to be the most accurate among the Kriging methods compared.

• 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.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.243-248
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• 2017

Sea ice which is an important component of the global climate system is being actively detected by satellite because it have been distributed to polar and high-latitude region. and the sea ice detection method using satellite uses reflectance and temperature data. the sea ice detection method of Moderate-Resolution Imaging Spectroradiometer (MODIS), which is a technique utilizing Ice Surface Temperature (IST) have been utilized by many studies. In this study, we propose a simple and effective method of sea ice detection using the dynamic threshold technique with no IST calculation process. In order to specify the dynamic threshold, pixels with freezing point of MODIS IST of 273.0 K or less were extracted. For the extracted pixels, we analyzed the relationship between MODIS IST, MODIS $11{\mu}m$ channel brightness temperature($T_{11{\mu}m}$) and Brightness Temperature Difference ($BTD:T_{11{\mu}m}-T_{12{\mu}m}$). As a result of the analysis, the relationship between the three values showed a linear characteristic and the threshold value was designated by using this. In the case ofsea ice detection, if $T_{11{\mu}m}$ is below the specified threshold value, it is detected as sea ice on clear sky. And in order to estimate the performance of the proposed sea ice detection method, the accuracy was analyzed using MODIS Sea ice extent and then validation accuracy was higher than 99% in Producer Accuracy (PA).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.363-373
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• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.