• Korean Journal of Remote Sensing
• /
• v.39 no.6_3
• /
• pp.1779-1790
• /
• 2023

Satellite-based fog detection algorithms are being developed to detect fog in real-time over a wide area, with a focus on the Korean Peninsula (KorPen). The GEO-KOMPSAT-2A/Advanced Meteorological Imager (GK2A/AMI, GK2A) satellite offers an excellent temporal resolution (10 min) and a spatial resolution (500 m), while GEO-KOMPSAT-2B/Geostationary Ocean Color Imager-II (GK2B/GOCI-II, GK2B) provides an excellent spatial resolution (250 m) but poor temporal resolution (1 h) with only visible channels. To enhance the fog detection level (10 min, 250 m), we developed a fused GK2AB fog detection algorithm (FDA) of GK2A and GK2B. The GK2AB FDA comprises three main steps. First, the Korea Meteorological Satellite Center's GK2A daytime fog detection algorithm is utilized to detect fog, considering various optical and physical characteristics. In the second step, GK2B data is extrapolated to 10-min intervals by matching GK2A pixels based on the closest time and location when GK2B observes the KorPen. For reflectance, GK2B normalized visible (NVIS) is corrected using GK2A NVIS of the same time, considering the difference in wavelength range and observation geometry. GK2B NVIS is extrapolated at 10-min intervals using the 10-min changes in GK2A NVIS. In the final step, the extrapolated GK2B NVIS, solar zenith angle, and outputs of GK2A FDA are utilized as input data for machine learning (decision tree) to develop the GK2AB FDA, which detects fog at a resolution of 250 m and a 10-min interval based on geographical locations. Six and four cases were used for the training and validation of GK2AB FDA, respectively. Quantitative verification of GK2AB FDA utilized ground observation data on visibility, wind speed, and relative humidity. Compared to GK2A FDA, GK2AB FDA exhibited a fourfold increase in spatial resolution, resulting in more detailed discrimination between fog and non-fog pixels. In general, irrespective of the validation method, the probability of detection (POD) and the Hanssen-Kuiper Skill score (KSS) are high or similar, indicating that it better detects previously undetected fog pixels. However, GK2AB FDA, compared to GK2A FDA, tends to over-detect fog with a higher false alarm ratio and bias.

• Korean Journal of Microbiology
• /
• v.46 no.4
• /
• pp.375-382
• /
• 2010

In present study, five strains of Lactobacillus acidophilus GK20, Lactobacillus brevis GK55, Lactobacillus paracasei GK74, Lactobacillus plantarum GK81, and Leuconostoc mesenteroides GK104 isolated from the mustard leaf kimchi were investigated for resistance to reactive oxygen species (ROS) and antioxidant activity. L. acidophilus GK20, L. brevis GK55, L. paracasei GK74, and L. plantarum GK81 were resistant to hydrogen peroxide (0.5 mM), showing a survival rate of 50% or more. In particular, L. acidophilus GK20 and L. paracasei GK74 were the most superoxide anions-resistant and L. paracasei GK74 and L. plantarum GK81 were most likely survive hydroxyl radicals. Meanwhile, the intracellular cell-free extract (ICFE) from L. plantarum GK81 exhibited significantly higher DPPH radical scavenging values ($96.4{\pm}2.8%$) than the intact cells (IC). The ICFE of L. plantarum GK81 showed the highest superoxide radical scavenging ability and chelating activity for $Fe^{2+}$ ions among the 5 lactic acid bacteria (LAB) tested, and IC and ICFE from L. plantarum GK81 demonstrated excellent reducing activity, which was higher than those of BHA and vitamin C as a positive control.

• Journal of Microbiology and Biotechnology
• /
• v.22 no.12
• /
• pp.1731-1739
• /
• 2012

In this study, seven strains isolated from mustard leaf kimchi were screened for their tolerance to simulated gastric and bile juices, the adhesive properties to Caco-2 cells, and the inhibition ability of Salmonella Typhimurium ATCC 29631 adhesion. Lactobacillus acidophilus GK20, Lactobacillus paracasei GK74, and Lactobacillus plantarum GK81, which were resistant to bile as well as gastric juices, possessed high bile-salt hydrolase (BSH) activity towards both sodium glycocholate and sodium taurocholate. The strongest in vitro adherence of $53.96{\pm}4.49%$ was exhibited by L. plantarum GK81 followed by L. acidophilus GK20 with adhesion levels of $40.72{\pm}9.46%$. The adhesion of these strains was significantly (p < 0.05) reduced after exposure to pepsin and heating for 30 min at $80^{\circ}C$. Addition of $Ca^{2+}$ led to a significant (p < 0.05) increase of the adhesion of L. acidophilus GK20, but the adhesion ability of L. plantarum GK81 was not different from the control by the addition of calcium. In the competition and exclusion experiment, the adhesion inhibition of S. Typhimurium by L. plantarum GK81 strain was much higher than the other strains. Moreover, the exclusion inhibition of S. Typhimurium by L. acidophilus GK20 was considerably high, although the inhibition activity of this strain was lower than L. plantarum GK81.

• Korean Journal of Remote Sensing
• /
• v.36 no.4
• /
• pp.645-652
• /
• 2020

GK2A(GEO-KOMPSAT-2A)satellite has been operating excellently since its launch in Dec 2018. The secondary payload called KSEM (Korean Space Environment Monitor) was equipped into the GK2A satellite along with AMI (Advanced Meteorological Imager) sensor. KSEM is the Korea's first operational geostationary space weather sensor and has been developed collaboratively by KHU (Kyung Hee University) and KARI (Korea Aerospace Research Institute). The interface works between KSEM and GK2A were conducted by KARI. Various interface tests, which aim for evaluating effective functionality of KSEM with the spacecraft, were intensively conducted at KARI facilities. Main tests consisted of mechanical and electrical check-up activities between the KSEM and GK2A. Interface tests of KSEM, which involve pre-launch tests such as ETB and GK2A system level tests, were conducted to evaluate functional and performance of KSEM before the launch. The tests carried out during the GK2A LEOP (Launch and Early Orbit Phase) and IOT (In Orbit Test) period (Dec 2018 ~ June 2019) showed excellent in-orbit performance of KSEM data.

• Journal of Ginseng Research
• /
• v.45 no.2
• /
• pp.228-235
• /
• 2021

Backgroud: Ginsenoside compound K (GK) is a major metabolite of protopanaxadiol-type ginsenosides and has remarkable anticancer activities in vitro and in vivo. This work used an ionic cross-linking method to entrap GK within O-carboxymethyl chitosan (OCMC) nanoparticles (Nps) to form GK-loaded OCMC Nps (GK-OCMC Nps), which enhance the aqueous solubility and stability of GK. Methods: The GK-OCMC Nps were characterized using several physicochemical techniques, including x-ray diffraction, transmission electron microscopy, zeta potential analysis, and particle size analysis via dynamic light scattering. GK was released from GK-OCMC Nps and was conducted using the dialysis bag diffusion method. The effects of GK and GK-OCMC Nps on PC3 cell viability were measured by using the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide assay. Fluorescent technology based on Cy5.5-labeled probes was used to explore the cellular uptake of GK-OCMC Nps. Results: The GK-OCMC NPs had a suitable particle size and zeta potential; they were spherical with good dispersion. In vitro drug release from GK-OCMC NPs was pH dependent. Moreover, the in vitro cytotoxicity study and cellular uptake assays indicated that the GK-OCMC Nps significantly enhanced the cytotoxicity and cellular uptake of GK toward the PC3 cells. GK-OCMC Nps also significantly promoted the activities of both caspase-3 and caspase-9. Conclusion: GK-OCMC Nps are potential nanocarriers for delivering hydrophobic drugs, thereby enhancing water solubility and permeability and improving the antiproliferative effects of GK.

• Journal of the Korea Society for Simulation
• /
• v.11 no.4
• /
• pp.1-14
• /
• 2002

This paper presents bounding space(BS) management for real-time visual simulation when using GK-DEVS models. Since GK-DEVS, extended from DEVS formalism, has information of 3D geometry and 3D hierarchical structure, we employs three types of bounding spaces: BS of its own shape, BS of its children GK-DEVS, and total BS. In addition to next-event scheduling functionality of previous GK-Simulator, its abstract simulation algorithms is extended to manage the three types of BSs so that BSs can be utilized in the rendering process of a renderer, so called GK-Renderer, We have implemented the method and evaluated it with an automated manufacturing system. In the case study, the proposed BSs management method showed about 2 times improvement in terms of rendering process speed.

• BMB Reports
• /
• v.35 no.2
• /
• pp.244-247
• /
• 2002

Replacement of the Asp-84 residue of the deoxyguanosine kinase subunit of the tandem deoxyadenosine kinase/deoxyguanosine kinase (dAK/dGK) from Lactobacillus acidophilus R-26 by Ala, Asn, or Glu produced increased $K_m$ values for deoxyguanosine on dGK. However, it did not seem to affect the binding of Mg-ATP. The Asp-84 dGK replacements bad no apparent effect on the binding of deoxyadenosine by dAK. However, the mutant dGKs were no longer inhibited by dGTP, normally a potent distal end-product inhibitor of dGK. Moreover, the allosteric activation of dAK activity by dGTP or dGuo was lost in the modified heterodimeric dAK/dGK enzyme. Therefore, it seems very likely that Asp-84 participates in dGuo binding at the active site of the dGK subunit of dAK/dGK from Lactobacillus acidophilus R-26.

• Korean Journal of Remote Sensing
• /
• v.38 no.2
• /
• pp.179-188
• /
• 2022

Global warming causes climate change and increases extreme weather events worldwide, and the occurrence of heatwaves and droughts is also increasing in Korea. For the monitoring of extreme weather, various satellite data such as LST (Land Surface Temperature), TCI (Temperature Condition Index), NDVI (Normalized Difference Vegetation Index), VCI (Vegetation Condition Index), and VHI (Vegetation Health Index) have been used. VHI, the combination of TCI and VCI, represents the vegetation stress affected by meteorological factors like precipitation and temperature and is frequently used to assess droughts under climate change. TCI and VCI require historical reference values for the LST and NDVI for each date and location. So, it is complicated to produce the VHI from the recent satellite GK2A (Geostationary Korea Multi-Purpose Satellite-2A). This study examined the retrieval of VHI using GK2A AMI (Advanced Meteorological Imager) by referencing the historical data from VIIRS (Visible Infrared Imaging Radiometer Suite) NDVI and LST as a proxy data. We found a close relationship between GK2A and VIIRS data needed for the retrieval of VHI. We produced the TCI, VCI, and VHI for GK2A during 2020-2021 at intervals of 8 days and carried out the interpretations of recent extreme weather events in Korea. GK2A VHI could express the changes in vegetation stress in 2020 due to various extreme weather events such as heatwaves (in March and June) and low temperatures (in April and July), and heavy rainfall (in August), while NOAA (National Oceanic and Atmospheric Administration) VHI could not well represent such characteristics. The GK2A VHI presented in this study can be utilized to monitor the vegetation stress due to heatwaves and droughts if the historical reference values of LST and NDVI can be adjusted in a more statistically significant way in the future work.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_1
• /
• pp.1767-1772
• /
• 2021

Global satellite observation surface albedo data over a long period of time are actively used to monitor changes in the global climate and environment, and their utilization and importance are great. Through the generational shift of geostationary satellites COMS (Communication, Ocean and Meteorological Satellite)/MI (Meteorological Imager sensor) and GK-2A (GEO-KOMPSAT-2A)/AMI (Advanced Meteorological Imager sensor), it is possible to continuously secure surface albedo outputs. However, the surface albedo outputs of COMS/MI and GK-2A/AMI differ between outputs due to Differences in retrieval algorithms. Therefore, in order to expand the retrieval period of the surface albedo of COMS/MI and GK-2A/AMI to secure continuous climate change monitoring linkage, the analysis of the two satellite outputs and errors should be preceded. In this study, error characteristics were analyzed by performing comparative analysis with ground observation data AERONET (Aerosol Robotic Network) and other satellite data GLASS (Global Land Surface Satellite) for the overlapping period of COMS/MI and GK-2A/AMI surface albedo data. As a result of error analysis, it was confirmed that the RMSE of COMS/MI was 0.043, higher than the RMSE of GK-2A/AMI, 0.015. In addition, compared to other satellite (GLASS) data, the RMSE of COMS/MI was 0.029, slightly lower than that of GK-2A/AMI 0.038. When understanding these error characteristics and using COMS/MI and GK-2A/AMI's surface albedo data, it will be possible to actively utilize them for long-term climate change monitoring.

• Atmosphere
• /
• v.26 no.2
• /
• pp.215-226
• /
• 2016

Conceptual models to analyze both typhoon and Changma using products extracted by the GEO-KOMPSAT-2A (GK-2A) are suggested in this study. The GK-2A which is scheduled to be launched in 2018 has a high resolution, 16 channels, and 52 products. This means GK-2A is expected to obtain high quality images and products, which can detect severe weather earlier than the Communications, Ocean and Meteorological Satellite (COMS). Since there are not enough conceptual models for typhoon and Changma using satellite images and products, our conceptual model can increase both the applicability of satellite data and the accuracy of analysis. In the conceptual model, typhoons are classified as three types by prevailing factors; 1) heavy-rainfall type, 2) wind type, and 3) complex type. For Changma, two types are divided by the characteristics; band type and heavy-rainfall type. Among the high resolution 52 products, each type of typhoon and Changma are selected. In addition, the numerical products and dynamic factors are considered in order to improve conceptual models.