• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.359-365
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• 2021

GEO-KOMPSAT-2A (GK2A) AMI (Advanced Meteorological Imager) Best Detector Select (BDS) map is pre-determined and uploaded before the satellite launch. After the launch, there is some possibility of a detector performance change driven by an abrupt temperature variation and thus the status of BDS map needs to be evaluated and updated if necessary. To investigate performance of entire elements of the detectors, AMI BDS analyses were conducted based on a technical note provided from the AMI vendor (L3HARRIS). The concept of the BDS analysis is to investigate the stability of signals from detectors while they are staring at targets (deep space and internal calibration target). For this purpose, Long Time Series (LTS) and Output Voltage vs. Bias Voltage (V-V) methods are used. The LTS for 30 secs and the V-V for two secs are spanned respectively for looking at the targets to compute noise components of detectors. To get the necessary data sets, these activities were conducted during the In-Orbit Test (IOT) period since a normal operation of AMI is stopped and special mission plans are commanded. With collected data sets during the GK2A IOT, AMI BDS map was intensively examined. It was found that about 1% of entire detector elements, which were evaluated at the ground test, showed characteristic changes and those degraded elements are replaced by alternative best ones. The stripping effects on AMI raw images due to the BDS problem were clearly removed when the new BDS map was applied.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1061-1067
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• 2023

In this letter, we simulated an atmospheric correction for Sentinel-2 images, of which spectral bands are similar to Compact Advanced Satellite 500-4 (CAS500-4). Using the second simulation of the satellite signal in the solar spectrum - vector (6SV)2.1 radiation transfer model and random forest (RF), a type of machine learning, we developed an RF-based atmospheric correction model to simulate 6SV2.1. As a result, the similarity between the reflectance calculated by 6SV2.1 and the reflectance predicted by the RF model was very high.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.925-939
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• 2018

Absorbed shortwave radiation at the surface is an important component of energy analysis among the atmosphere, land, and ocean. In this study, the absorbed shortwave radiation was calculated using a radiation model and surface broadband albedo data for application to Geostationary Earth Orbit Korea Multi-Purpose SATellite (GEO-KOMPSAT-2A; GK-2A). And the results (GWNU algorithm) were compared with CERES data and calculation results using pyranometer and MODIS (Moderate Resolution Imaging Spectroradiometer) data to be selected as the reference absorbed shortwave radiation. This GWNU algorithm was also compared with the physical and statistical algorithms of GOSE-R ABI and two algorithms (Li et al., 1993; Kim and Jeong, 2016) using regression equation. As a result, the absorbed shortwave radiation calculated by GWNU algorithm was more accurate than the values calculated by the other algorithms. However, if the problem about computing time and accuracy of albedo data arise when absorbed shortwave radiation is calculated by GWNU algorithm, then the empirical algorithms explained above should be used with GWNU algorithm.

• Journal of the Korean earth science society
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• v.45 no.1
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• pp.48-71
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• 2024

Typhoons are representative oceanic and atmospheric phenomena that cause interactions within the Earth's system with diverse influences. In recent decades, the typhoons have tended to strengthen due to rapidly changing climate. The 2022 revised science curriculum emphasizes the importance of teaching-learning activities using advanced science and technology to cultivate digital literacy as a citizen of the future society. Therefore, it is necessary to solve the temporal and spatial limitations of textbook illustrations and to develop effective instructional materials using global-scale big data covered in the field of earth science. In this study, according to the procedure of the PDIE (Preparation, Development, Implementation, Evaluation) model, the inquiry activity data was developed to visualize the track of the typhoon using the image data of GK-2A. In the preparatory stage, the 2015 and 2022 revised curriculum and the contents of the inquiry activities of the current textbooks were analyzed. In the development stage, inquiry activities were organized into a series of processes that can collect, process, visualize, and analyze observational data, and a GUI (Graphic User Interface)-based visualization program that can derive results with a simple operation was created. In the implementation and evaluation stage, classes were conducted with students, and classes using code and GUI programs were conducted respectively to compare the characteristics of each activity and confirm its applicability in the school field. The class materials presented in this study enable exploratory activities using actual observation data without professional programming knowledge which is expected to contribute to students' understanding and digital literacy in the field of earth science.

• Biomolecules & Therapeutics
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• v.27 no.1
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• pp.34-40
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• 2019

Transglutaminase 2 (TGase 2) plays a key role in p53 regulation, depleting p53 tumor suppressor through autophagy in renal cell carcinoma. We found that microtubule-associated protein 1A/1B-light chain 3 (LC3), a hallmark of autophagy, were tightly associated with the level of TGase 2 in cancer cells. TGase 2 overexpression increased LC3 levels, and TGase 2 knockdown decreased LC3 levels in cancer cells. Transcript abundance of LC3 was inversely correlated with level of wild type p53. TGase 2 knockdown using siRNA, or TGase 2 inhibition using GK921 significantly reduced autophagy through reduction of LC3 transcription, which was followed by restoration of p53 levels in cancer cells. TGase 2 overexpression promoted the autophagy process by LC3 induction, which was correlated with p53 depletion in cancer cells. Rapamycin-resistant cancer cells also showed higher expression of LC3 compared to the rapamycin-sensitive cancer cells, which was tightly correlated with TGase 2 levels. TGase 2 knockdown or TGase 2 inhibition sensitized rapamycin-resistant cancer cells to drug treatment. In summary, TGase 2 induces drug resistance by potentiating autophagy through LC3 induction via p53 regulation in cancer.

• Journal of Nutrition and Health
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• v.47 no.3
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• pp.167-175
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• 2014

Purpose: Previous studies have shown that treatment with Smilax china L. leaf extract (SCLE) produces antidiabetic effects due to ${\alpha}$-glucosidase inhibition. In this study, we examined the mechanism underlying these antidiabetic effects by examining glucose uptake in HepG2 cells cultured with SCLE. Methods: Glucose uptake and glucokinase activity were examined using an assay kit. Expression of glucose transporter (GLUT)-2, GLUT-4, and HNF-$1{\alpha}$ was measured by RT-PCR or western blot. Results: Treatment with SCLE resulted in enhanced glucose uptake in HepG2 cells, and this effect was especially pronounced when cells were cultured in an insulin-free medium. SCLE induced an increase in expression of GLUT-2 but not GLUT-4. The increase in the levels of HNF-$1{\alpha}$, a GLUT-2 transcription factor, in total protein extract and nuclear fraction suggest that the effects of SCLE may occur at the level of GLUT-2 transcription. In addition, by measuring the change in glucokinase activity following SCLE treatment, we confirmed that SCLE stimulates glucose utilization by direct activation of this enzyme. Conclusion: These results demonstrate that the potential antidiabetic activity of SCLE is due at least in part to stimulation of glucose uptake and an increase in glucokinase activity, and that SCLE-stimulated glucose uptake is mediated through enhancement of GLUT-2 expression by inducing expression of its transcription factor, HNF-$1{\alpha}$.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1181-1189
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• 2022

Clouds are composed of tiny water droplets, ice crystals, or mixtures suspended in the atmosphere and cover about two-thirds of the Earth's surface. Cloud detection in satellite images is a very difficult task to separate clouds and non-cloud areas because of similar reflectance characteristics to some other ground objects or the ground surface. In contrast to thick clouds, which have distinct characteristics, thin transparent clouds have weak contrast between clouds and background in satellite images and appear mixed with the ground surface. In order to overcome the limitations of transparent clouds in cloud detection, this study conducted cloud detection focusing on transparent clouds using machine learning techniques (Random Forest [RF], Convolutional Neural Networks [CNN]). As reference data, Cloud Mask and Cirrus Mask were used in MOD35 data provided by MOderate Resolution Imaging Spectroradiometer (MODIS), and the pixel ratio of training data was configured to be about 1:1:1 for clouds, transparent clouds, and clear sky for model training considering transparent cloud pixels. As a result of the qualitative comparison of the study, bothRF and CNN successfully detected various types of clouds, including transparent clouds, and in the case of RF+CNN, which mixed the results of the RF model and the CNN model, the cloud detection was well performed, and was confirmed that the limitations of the model were improved. As a quantitative result of the study, the overall accuracy (OA) value of RF was 92%, CNN showed 94.11%, and RF+CNN showed 94.29% accuracy.

• Journal of Integrative Natural Science
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• v.15 no.4
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• pp.137-144
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• 2022

This paper presents the effect of the supramolecular complex of GA (Glycyrrhizic acid) and Mt(menthol) and GA: Mt (4: 1) obtained on their basis can restore functional dysfunction of the liver mitochondria in alloxan diabetes, ie, inhibit lipid peroxidation. The hypoglycemic activity and mitochondrial membrane stabilizing properties of the supramolecular compound GA: Mt (4: 1) in alloxan diabetes were more pronounced than those of menthol, GA and its GK: Mt (2: 1) and GA: Mt (9: 1) compounds. According to the results obtained, the concentration of GA did not affect the peroxidation of lipid membranes of the liver mitochondria. However, a concentration of 15 μM of GA was found to reduce LPO (lipid peroxidation) formed by the effect of Fe²+ / ascorbate on the mitochondrial membrane by 58.0 ± 5.0% relative to control. The inhibitory effect of GA and its supramolecular compounds in different proportions with menthol on the peroxidation of lipids in rat heart and brain tissue has been studied

• Journal of Environmental Health Sciences
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• v.19 no.1
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• pp.30-36
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• 1993

A survey was conducted to measure concentration of airborne microbe in a hospital using RSC air sampler during October~November 1991.The result was as follows: 1) In an agar strip GK-A media for total counts of microbial particles. The highest count were 1384 CFU/m$^3$ in the main lobby, followed by 912 CFU/m$^3$, in the obstetric room, 688 CFU/m$^3$ in 1CU. By gram staining, the distribution for organisms in the air were shown 74.1% in gram possitive cocci followed by 16.8%, in gram possitive bacilli 6.7% in gram negative bacilli and 4.7% in yeast, but low organism was detected in recovery room with 194 CFU/m$^3$. 2) In agar strip S media for Staphylococci the count at the main lobby was detected in the recovery room with 92 CFU/m$^3$, Tests of coagulase were negative Staphylococci with 78%, and positive Staphylococci with 22%. The Staphylococci were highly resistance to penicillin, ampicillin and sensitive to amikacin, cefazolin, gentamycin and chloramphenicol. 3) In agar strip C media for coliform bacteria the colony counts at the main lobby was 139 CFU/m$^3$ and treatment room was 190 CFU/m$^3$, most frequently isolated microorganisms were non fermentative bacilli. 4) In agar strip HS media for yeast and molds. Most frequently colony counts 17~76 CFU/m$^3$, 0.5% lactophenol cotton blue stains were shown unidentified 77.2%, 8.1%, in Penicillium 8.1% in Aspergillus, and 3.8% in mucor.