• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.827-833
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• 2023

CT(Computed Tomography) contrast agents are commonly used in general hospitals and university hospitals when taking radiographic examinations. The CT contrast medium contains a mixture of a substance called "Iodine", which absorbs radiation energy and makes it appear white in the CT image, further improving the image quality. In addition, the CT contrast agent, which moves like blood in the blood vessels, clearly differentiates it from muscle and water, so CT contrast agents are widely used in hospitals. These CT contrast agents absorb X-rays, but in order to absorb X-rays, they must have a high density or a high radiation absorption coefficient. Since the CT contrast agent is injected into the blood vessels, if the density is high, the blood vessels are strained and the patient is in shock. For this reason, it is necessary to match the density similar to that of water and always pay attention to side effects. In addition, the amount of CT contrast medium is adjusted according to the patient's body shape, and the remaining contrast medium is discarded. However, This study tried to find out the idea of recycling it as a radiation shielding material. Since the CT contrast medium has a high radiation absorption coefficient at a density similar to that of water, the amount to absorb radiation is adjusted, the amount of contrast medium and the amount of water are adjusted, and the amount of radiation absorbed is determined by mixing with water. In addition, a study was conducted to find out the result of the difference in radiation absorption in various ways by comparing the radiation quality coefficient and absorption coefficient with other substances or materials in an environmentally friendly method harmless to the human body by mixing CT contrast medium and water.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.5
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• pp.483-489
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• 2016

The type approval test for USCG Phase II must be satisfied such that living natural biota occupy more than 75 % of whole biota in a test tank. Thus, we harvested a community of natural organisms using a net at Masan Bay (eutrophic) and Jangmok Bay (mesotrophic) during winter season to meet this guideline. Furthermore, cell viability was measured to determine the mortality rate. Based on the organism concentration volume (1 ton) at Masan and Jangmok Bay, abundance of ${\geq}10$ and $<50{\mu}m$ sized organisms was observed to be $4.7{\times}10^4cells\;mL^{-1}$and $0.8{\times}10^4cells\;mL^{-1}$, and their survival rates were 90.4 % and 88.0 %, respectively. In particular, chain-forming small diatoms such as Skeletonema costatum-like species were abundant at Jangmok Bay, while small flagellate ($<10{\mu}m$) and non chain-forming large dinoflagellates, such as Akashiwo sanguinea and Heterocapsa triquetra, were abundant at Masan Bay. Due to the size-difference of the dominant species, concentration efficiency was higher at Jangmok Bay than at Masan Bay. The mortality rate in samples treated by Ballast Water Treatment System (BWMS) (Day 0) was a little lower for samples from Jangmok Bay than from Masan Bay, with values of 90.4% and 93%, respectively. After 5 days, the mortality rates in control and treatment group were found to be 6.7% and >99%, respectively. Consequently, the phytoplankton concentration method alone did not easily satisfy the type approval standards of USCG Phase II ($>1.0{\times}10^3cells\;mL^{-1}$ in 500-ton tank) during winter season, and alternative options such as mass culture and/or harvesting system using natural phytoplankton communities may be helpful in meeting USCG Phase II biological criteria.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1321-1330
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• 2023

Normalized Difference Vegetation Index (NDVI) is the most widely used remote sensing data in the agricultural field and is currently provided by most optical satellites. In particular, as high-resolution optical satellite images become available, the selection of optimal optical satellite images according to agricultural applications has become a very important issue. In this study, we aim to define the most optimal optical satellite image when monitoring NDVI in rice fields in Korea and derive the resolution-related requirements necessary for this. For this purpose, we compared and analyzed the spatial distribution and time series patterns of the Dangjin rice paddy in Korea from 2019 to 2022 using NDVI images from MOD13, Landsat-8, Sentinel-2A/B, and PlanetScope satellites, which are widely used around the world. Each data is provided with a spatial resolution of 3 m to 250 m and various periods, and the area of the spectral band used to calculate NDVI also has slight differences. As a result of the analysis, Landsat-8 showed the lowest NDVI value and had very low spatial variation. In comparison, the MOD13 NDVI image showed similar spatial distribution and time series patterns as the PlanetScope data but was affected by the area surrounding the rice field due to low spatial resolution. Sentinel-2A/B showed relatively low NDVI values due to the wide near-infrared band area, and this feature was especially noticeable in the early stages of growth. PlanetScope's NDVI provides detailed spatial variation and stable time series patterns, but considering its high purchase price, it is considered to be more useful in small field areas than in spatially uniform rice paddy. Accordingly, for rice field areas, 250 m MOD13 NDVI or 10 m Sentinel-2A/B are considered to be the most efficient, but high-resolution satellite images can be used to estimate detailed physical quantities of individual crops.

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

• Journal of Venture Innovation
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• v.4 no.3
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• pp.125-139
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• 2021

As the 4th industrial revolution progresses, new technologies and services are being born, growing, and maturing. Now, beyond the mobile era, the metaverse is being discussed as a new paradigm. Therefore, in this study, in preparation for the metaverse era, we tried to analyze what factors have an important influence when consumers want to use new technologies. In particular, the research was conducted focusing on how the context in which consumers use the technology changes depending on whether they are B2C or B2B. For this, augmented reality (AR) was selected in the B2C context by linking the research subject with the metaverse era, and the smart factory was selected in the B2B context. The research model for the analysis was established by deriving and setting common influence variables by reflecting the characteristics of the research target technology based on the modified extended unified theory of acceptance and use of technology. A survey was conducted for empirical analysis, and 150 AR and 150 smart factory subjects were analyzed. The empirical study results are as follows. The relationship between performance expectancy and intention to use, technology readiness and intention to use was found to have a significant positive (+) effect on both AR and smart factory. On the other hand, it was found that effort expectancy, social influence, and trust had a positive (+) effect on intention to use only in AR. Only in smart factory, facilitating conditions had a significant positive (+) effect on intention to use. It was also found that the perceived risk had a significant negative (-) effect on the intention to use only in the smart factory. The results of this study are academically significant in that we empirically test that influencing factors of technology use varies depending on the context in which it is used by consumers. In practice, it provided an implication of what to focus on first is being implemented.

• Journal of Venture Innovation
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• v.5 no.3
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• pp.71-80
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• 2022

The real estate market is an important part of a country's economy and plays a major role in economic growth through the growth of many related industries. Changes in interest rates affect asset prices and have a significant impact on housing prices. This study analyzed housing prices by dividing them into nationwide, local, and Seoul housing prices in order to analyze whether the effect of changes in interest rates on housing prices shows regional differences. The analysis was conducted from the first quarter of 2011 to the fourth quarter of 2021, and was analyzed using the DOLS model. The main analysis results are as follows. First, interest rates were found to have a significant negative effect on national housing prices, and a drop in interest rates significantly increased national housing prices and an increase in interest rates significantly lowered national housing prices. The consumer price index and loan growth rate also had a positive effect on housing prices nationwide, but statistical significance was not high. Second, interest rates had a negative effect on local housing prices, unlike national housing prices, but were not statistically significant. On the other hand, it was found that the consumer price index and loan growth rate had a larger and significant positive effect on local housing prices compared to national housing prices. Finally, it was found that the interest rate had the only significant negative effect on housing prices in Seoul. And this effect was greater and more significant than the effect on national and local housing prices. In the end, it was found that the effect of interest rates on Korean housing prices differs locally. Interest rates have a significant negative effect on national housing prices, and local housing prices, but they are not statistically significant. In addition, the interest rate was found to have the largest and most significant negative effect on housing prices in Seoul. In addition, it was found that there was a difference in the effect of macroeconomic variables on housing prices. This means that there are differences between regions with different factors influencing local and Seoul housing prices, and this point should be considered when drafting and implementing real estate policies.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.997-1008
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• 2023

Ship detection at sea can be performed in various ways. In particular, satellites can provide wide-area surveillance, and Synthetic Aperture Radar (SAR) imagery can be utilized day and night and in all weather conditions. To propose an efficient ship detection method from SAR images, this study aimed to apply the You Only Look Once Version 5 (YOLOv5) model to Sentinel-1 images and to analyze the difference between individual vs. integrated models and the accuracy characteristics by polarization. YOLOv5s, which has fewer and lighter parameters, and YOLOv5x, which has more parameters but higher accuracy, were used for the performance tests (1) by dividing each polarization into HH, HV, VH, and VV, and (2) by using images from all polarizations. All four experiments showed very similar and high accuracy of 0.977 ≤ AP@0.5 ≤ 0.998. This result suggests that the polarization integration model using lightweight YOLO models can be the most effective in terms of real-time system deployment. 19,582 images were used in this experiment. However, if other SAR images,such as Capella and ICEYE, are included in addition to Sentinel-1 images, a more flexible and accurate model for ship detection can be built.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.68 no.3
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• pp.121-133
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• 2023

The purpose of this study was to improve weed management systems under varying carbon dioxide concentrations and temperatures by evaluating the growth of Acalypha australis and observing the efficacy of four foliar and four soil herbicides, as well as measuring phytotoxicity in soybean crops treated with these herbicides. In both growth chamber and greenhouse conditions, plant height and shoot fresh weight of Acalypha australis increased as temperature increased. The variable to maximum fluorescence ratio (Fv/Fm), relative electron transport rate (ETR), plant height, leaf area, and shoot fresh weight of Acalypha australis were higher at carbon dioxide concentrations of 800 ppm than at 400 ppm. The efficacy of a foliar herbicide, glufosinate, on Acalypha australis was lower at 30℃ than at 20℃ and 25℃ in the growth chamber condition and was also lower at 29℃ than at 21℃ and 25℃ in greenhouse conditions. In contrast, mecoprop efficacy on Acalypha australis was lower at 20℃ and 25℃ than at 30℃ in growth chamber conditions and lower at 21℃ and 25℃ than at 29℃ in greenhouse conditions. Glyphosate efficacy was lower at 21℃ than at 25℃ and 29℃ under greenhouse conditions. With soil herbicides, metolachlor and ethalfluraline, efficacies were higher at relatively high temperatures under both growth chamber and greenhouse conditions. However, in the case of linuron, the difference in efficacy was not observed under varying temperatures in both growth chamber and greenhouse conditions. When ¼ of the recommended glyphosate rates were applied to Acalypha australis, efficacy was lower under 800 ppm carbon dioxide concentrations than under 400 ppm. In contrast, when ¼ of the recommended rate of bentazone was applied to Acalypha australis, efficacy was higher under 800 ppm carbon dioxide concentrations than under 400 ppm. Despite application rates, glufosinate efficacy differed insignificantly under different carbon dioxide concentrations. When applied at ¼ of the recommended rate, the efficacy of ethalfuralin was higher under 800 ppm carbon dioxide concentrations than under 400 ppm. However, efficacies of other herbicides were not different despite varying carbon dioxide concentrations. Soybean phytotoxicity in crops treated with the recommended rate and twice the recommended rate of soil herbicides was not significantly different regardless of temperature and carbon dioxide concentrations. Overall, weed efficacy of some herbicides decreased in response to different temperatures and carbon dioxide concentrations. Therefore, new weed management methods are required to ensure high rates of weed control in conditions affected by climate change.

• Journal of Nutrition and Health
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• v.56 no.5
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• pp.573-588
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• 2023

Purpose: This study aimed to examine social networking service (SNS) use and recommended information utilization (SURU) according to the food-related lifestyles (FRLs) of consumers and analyze how the interaction between the FRL and SURU affects the practice of eating alone and visiting restaurants. Methods: Data on 4,624 adults in their 20s to 50s were collected from the 2021 Consumer Behavior Survey for Food. Statistical methods included factor analysis, K-means cluster analysis, the complex samples general linear model, the complex samples Rao-Scott χ² test, and the general linear model. Results: The following three factors were extracted from the FRL data: Convenience pursuit, rational consumption pursuit, and gastronomy pursuit, and the subjects were classified into three groups, namely the rational consumption, convenient gastronomy, and smart gourmet groups. An examination of the difference in SURU according to the FRL showed that the smart gourmet group had the highest score. The result of analyzing the effects of the FRL and SURU on eating alone revealed that both the main effect and the interaction effect were significant (p < 0.01, p < 0.001). The higher the SURU, the higher the frequency of eating alone in the convenience pursuit, and gastronomy pursuit groups. The main and interaction effects of the FRL and SURU on the frequency of eating out were also significant (p < 0.01, p < 0.001). In all the FRL groups, the higher the SURU level, the higher the frequency of visiting restaurants. Specifically, the two groups with convenience and gastronomic tendencies showed a steeper increase. Conclusion: This study provides important basic data for research on consumer behavior related to food SNS, market segmentation of restaurant consumers, and development of marketing strategies using SNS in the future.

• Journal of Life Science
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• v.33 no.12
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• pp.1052-1061
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• 2023

This study was carried out to evaluate the effect of fermentation by B. subtilis (BPLE), L. brevis (LPLE), S. cerevisiae (SPLE) and C. militaris (CPLE) on the antioxidant activity of Protaetia brevitarsis larvae fed with mushroom substrates (king oyster mushroom). The total polyphenol content of Protaetia brevitarsis larvae (PLE), BPLE, LPLE, SPLE and CPLE were 58.07±0.67, 83.33±0.98, 79.21±1.32, 61.02±0.87 and 57.90±1.02 mg GAEs/extract g, respectively. The flavonoid contents of the PLE, BPLE, LPLE, SPLE and CPLE were 17.35±1.57, 19.49±0.95, 16.90±1.57, 18.12±0.95 and 16.99±0.95 mg QEs/extract g, respectively. The DPPH radical scavenging activity showed no significant difference between the PLE, BPLE, LPLE, SPLE and CPLE at a concentration of 0.2 mg/ml. However, at a concentration of 0.4 mg/ml or more, the DPPH radical scavenging activity of the BPLE and LPLE was higher than that of the PLE. The reducing power of the BPLE and LPLE was also higher than that of the PLE, and more than twice as high at a concentration of 0.8 mg/ml or more. The ORAC value of the BPLE (79.77±0.82 uM TEs/extract g) was higher than that of the PLE (61.34±0.97 uM TEs/extract g). A WST-1 assay of the RAW 264.7 cells indicated that the PLE, BPLE, LPLE, SPLE and CPLE showed no cytotoxicity.