• Korean Journal of Mineralogy and Petrology
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• v.34 no.3
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• pp.169-176
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• 2021

This study aimed to fundamentally understand structural changes of zeolite under pressure and in the presence of different pressure-transmitting media (PTM) for application studies such as immobilization of heavy metal cation or CO₂ storage using pressure. High-pressure X-ray powder diffraction study was conducted on the zeolite-W (K_6.4Al_6.5Si_25.8O₆₄× 15.3H₂O, K-MER) to understand linear compressibility and the bulk moduli in different PTM conditions. Zeolite-w is a synthetic material having the same framework as natural zeolite merlinoite ((K, Ca_0.5, Ba_0.5, Na)₁₀ Al₁₀Si₂₂O₆₄× 22H₂O). The space group of the sample was identified as I4/mmm belonging to the tetragonal crystal system. Water, carbon dioxide, and silicone-oil were used as pressure-transmitting media. The mixture of sample and each PTM was mounted in a diamond anvil cell (DAC) and then pressurized up to 3 GPa with an increment of ca. 0.5 GPa. Pressure-induced changes of powder diffraction patterns were measured using a synchrotron X-ray light source. Lattice constants, and bulk moduli were calculated using the Le-Bail method and the Birch-Murnaghan equation. In all PTM conditions, linear compressibility of c-axis (𝛽^c) was 0.006(1) GPa^-1 or 0.007(1) GPa^-1. On the other hand, the linear compressibility of a(b)-axis (𝛽^a) was 0.013(1) GPa^-1 in silicone-oil run, which is twice more compressible than the a(b)-axis in water and carbon dioxide runs, 𝛽^a = 0.006(1) GPa^-1. The bulk moduli were measured as 50(3) GPa, 52(3) GPa, and 29(2) GPa in water, carbon dioxide, and silicone-oil run, respectively. The orthorhombicities of ac-plane in the water, and carbon dioxide runs were comparatively constant, near 0.350~0.353, whereas the value decreased abruptly in the silicone-oil run following formula, y = -0.005(1)x + 0.351(1) by non-penetrating pressure fluid condition.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.320-327
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• 2021

Freezing damage to fruit trees is frequently occurring due to cold in winter and low temperature in spring to abnormal weather caused by global warming. In particular, the freezing injury of deciduous fruit trees is highly dependent on the developmental stages of the flower buds. And the cold resistance is weakened as the growth progresses, so it is most vulnerable period from flowering to petal fall(post-bloom). Therefore, this study was conducted to analyze the cause of the freezing injury caused by severe low temperature to 'Fuji', which has a late flowering period more than 'Hongro' in April 2020. We investigated freezing injury rate in 'Fuji' and 'Hongro' apple trees damaged by natural low temperature at Boeun-gun, Chungbuk province in Korea. In addition, flower buds in the same developmental stage (tight cluster) were treated artificially low temperature to investigate the injury rate for accurate comparative analysis between varieties, and to analyze the soluble sugar and hormone contents in the flower buds. As a result of survey in natural low temperature, 'Fuji' had a higher injury rate than 'Hongro' in both orchards, and in particular, B orchard 'Fuji' had the highest injury rate of 60.5%. Also there were significantly difference in the freezing injury rate between 'Fuji' and 'Hongro' in artificially low temperature treatments. As a result of analyzing the soluble sugar contents in 'Hongro' was higher than 'Fuji'. Also ABA, IAA and SA contents were more increased in the damaged tissue than in the normal flower buds by low temperature treatments. Consequently, it was assumed that the freezing injury was closely related to soluble sugar contents in the flower buds. In particular, the freezing injury rate was negatively correlated with the sorbitol contents.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.73-82
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• 2021

Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.

• Journal of Integrative Natural Science
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• v.14 no.1
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• pp.11-20
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• 2021

On November 17, 2019, an infectious disease with symptoms of pneumonia, called the Wuhan virus at the time, occurred in Wuhan, China. Since then, the name has been changed to COVID-19, and the virus has spread all over the world, and the WHO has declared the highest warning level for infectious diseases, "Pandemic". The coronavirus has also caused great confusion in South Korea. This resulted in large infected people.The first confirmed cases occurred on January 20, 2020, and the number of infected patients is steadily increasing after experiencing several waves, and many corona confirmed cases are also occurring in 2021 after the year. As the whole world enters a pandemic, walls are created between people and people, companies and businesses, and countries and countries, and all growth stops or declines, including human relationships, domestic companies and industries, and foreign industries. As a result, society in general is experiencing a lot of stagnation. Among them, small and medium-sized enterprises (SMEs), which are the basis of all growth in Korea, and youth who are trying to contribute to the national development by entering society, are struggling to find jobs. Even before the coronavirus outbreak, the difficulty of job hunting and the prospect of small and medium-sized businesses were not very good. In this situation, as the country's overall economic situation is poor, the vitality of SMEs has decreased a lot, the prospects are not good, so jobs are reduced, and there are many difficulties due to reluctance to hire new employees. In this study, with 2019 before the corona era and 2020 after the corona era, we compare SMEs before and after the corona era and overall job search and job search activities through average difference analysis, and whether they are affecting through correlation analysis. Through this, it suggests a direction to increase job search through corporate and government policies after raising the prospects of SMEs first.

• Journal of the Korean Society for information Management
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• v.38 no.3
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• pp.141-174
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• 2021

In this study, by examining the actual usage data of the university library website before and after COVID-19 outbreak, the usage behavior of users was analyzed, and the data before and after the virus outbreak was compared, so that university libraries can provide more efficient information services in a pandemic situation. We would like to suggest ways to improve it. In this study, the user traffic made on the website of University C was 'using Google Analytics', from January 2018 to December 2018 before the oneself of the COVID-19 virus and from January 2020 to 2020 after the outbreak of the virus. A comparative analysis was conducted until December. Web traffic variables were analyzed by classifying them into three characteristics: 'User information', 'Path', and 'Site behavior' based on metrics such as session, user, number of pageviews, number of pages per session time, and bounce rate. To summarize the study results, first, when compared with data from January 1 to January 20 before the oneself of COVID-19, users, new visitors, and sessions all increased compared to the previous year, and the number of sessions per user, number of pageviews, and number of pages per session, which showed an upward trend before the virus outbreak in 2020, increased significantly. Second, as social distancing was upgraded to the second stage, there was also a change in the use of university library websites. In 2020 and 2018, when the number os students was the lowest, the number of page views increased by 100,000 more in 2020 compared to 2018, and the number of pages per session also recorded10.46, which was about 2 more pages compared to 2018. The bounce rate also recorded 14.38 in 2018 and 2019, but decreased by 1 percentage point to 13.05 in 2020, which led to more active use of the website at a time when social distancing was raised.

• Korean Journal of Plant Taxonomy
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• v.51 no.3
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• pp.250-293
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• 2021

Limestone areas are sedimentary rock outcrops consisting of calcium carbonate created several hundreds of millions of years ago by calcium-secreting marine organisms and subsequently lifted above sea level by tectonic movement. Limestone areas support very high levels of endemic species of plants and are recognized as biodiversity areas with much biological information. The purpose of this study is to devise a strategy for the comprehensive conservation of the vegetation of limestone areas through analyses of the floristics and plant species compositions in ten limestone areas on the Korean Peninsula. The results of 153 field surveys from April of 2010 to October of 2016 identified 1,202 taxa in total, representing 1,096 species, 18 subspecies, 84 varieties, 2 forms, and 2 hybrids in 530 genera and 133 families. Among them, 55 taxa were endemic plants to Korea, and 38 taxa were red data plants. The floristic target plants amounted to 102 taxa, specifically 27 taxa of grade V and 75 taxa of grade IV. In all, 121 alien plants were recorded in the investigated area. Calciphilous plants amounted to 102 taxa, specifically 14 taxa of calciphilous indicator plants, 30 taxa of superlative most calciphilous plants, and 58 taxa of comparative more calciphilous plants. A cluster analysis showed a high degree of similarity between sites that are geographically adjacent with similar habitat environments. Limestone areas also supported groups distinct from those in non-limestone areas, demonstrating the specificity of limestone flora. Plant geography approaches therefore appear to be crucial to gain a better understanding of the level of biodiversity in limestone areas, not only at the interspecific but also at the intraspecific level. These results highlight the importance of protecting limestone habitats to preserve not only their interspecific but also the intraspecific diversity, which is highly threatened.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1143-1154
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• 2021

The selection of activation function has a great influence on the groundwater level prediction performance of artificial neural network (ANN) model. In this study, five activation functions were applied to ANN model for two groundwater level observation wells in the middle mountainous area of the Pyoseon watershed in Jeju Island. The results of the prediction of the groundwater level were compared and analyzed, and the optimal activation function was derived. In addition, the results of LSTM model, which is a widely used recurrent neural network model, were compared and analyzed with the results of the ANN models with each activation function. As a result, ELU and Leaky ReLU functions were derived as the optimal activation functions for the prediction of the groundwater level for observation well with relatively large fluctuations in groundwater level and for observation well with relatively small fluctuations, respectively. On the other hand, sigmoid function had the lowest predictive performance among the five activation functions for training period, and produced inappropriate results in peak and lowest groundwater level prediction. The ANN-ELU and ANN-Leaky ReLU models showed groundwater level prediction performance comparable to that of the LSTM model, and thus had sufficient potential for application. The methods and results of this study can be usefully used in other studies.

• Korean Journal of Heritage: History & Science
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• v.54 no.4
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• pp.246-259
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• 2021

Research has been conducted in various fields on a local fortress (eupseong) in the Joseon Dynasty, but the archaeological research on the prison (獄), which is part of the internal government, has not been conducted properly. Since the prison was first discovered in Gyeongju in 1997, there has been a necessity for research on the deployment and structure of the prison. This includes the office where jailers worked and had night duty and also the enclosure that keeps the prisoners inside. But the research came to a standstill because there was no comparative data. However, compared to the more recent findings of the Yeonil Prison and the Gonju Prison, we can identify that the structure was built during the early to the late Joseon Dynasty. King Sejong designed the standard prison blueprint called Anokdo (犴獄圖) in 1426 to manage prisoners nationwide and revised it once in 1439 to give better treatment during the winter and summer seasons. The Yeonil Prison operated from 1421 to 1743 and shows the structure of the prisons during the early to mid-Joseon period. It was very similar to the Gyeongju Prison on a smaller scale, which was operated until the late Joseon Dynasty with two main structures, one east and one west, and a circular fence. This structure was maintained even in the Gongju Prison during the late Joseon Dynasty, and it remains visible in photographs. The prison of the Joseon Dynasty had a circular fence with an estimated height of 3 meters and two buildings that separated male and female prisoners. The prison was divided into men on the east and women on the west with tile-roofed house structures that were difficult to escape. In front of the circular fence, there was an office with a thatched roof for the jailers and access to the prison was only possible through a double prison gate. The layout of the building reflects the improvements of the king's prison design made during Joseon Dynasty improving the environment of prisoners who are on trial and separating men and women in order to embody humanism.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1829-1836
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• 2021

Cloud detection means determining the presence or absence of clouds in a pixel in a satellite image, and acts as an important factor affecting the utility and accuracy of the satellite image. In this study, among the satellites of various advanced organizations that provide cloud detection data, we intend to perform quantitative and qualitative comparative analysis on the difference between the cloud detection data of GK-2A/AMI, Terra/MODIS, and Suomi-NPP/VIIRS. As a result of quantitative comparison, the Proportion Correct (PC) index values in January were 74.16% for GK-2A & MODIS, 75.39% for GK-2A & VIIRS, and 87.35% for GK-2A & MODIS in April, and GK-2A & VIIRS showed that 87.71% of clouds were detected in April compared to January without much difference by satellite. As for the qualitative comparison results, when compared with RGB images, it was confirmed that the results corresponding to April rather than January detected clouds better than the previous quantitative results. However, if thin clouds or snow cover exist, each satellite were some differences in the cloud detection results.

• Journal of Life Science
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• v.31 no.12
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• pp.1079-1087
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• 2021

To analyze gut microbiota of livestock in Korea and compare taxonomic differences, we conducted 16S rRNA metagenomic analysis through next-generation sequencing. Fecal samples from broiler chickens, pigs, and cattle were collected from domestic feedlots randomly. α-diversity results showed that significant differences in estimated species richness estimates (Chao1 and ACE, Abundance-based coverage estimators) and species richness index (OUTs, Operational taxonomic units) were identified among the three groups. However, NPShannon, Shannon, and Simpson indices revealed that abundance and evenness of the species were statistically significant only for poultry (broiler chickens) and mammals (pigs and cattle). Firmicutes was the most predominant phylum in the three groups of fecal samples. Linear discriminant (LDA) effect size (LEfSe) analysis was conducted to reveal the ranking order of abundant taxa in each of the fecal samples. A size-effect over 2.0 on the logarithmic LDA score was used as a discriminative functional biomarker. As shown by the fecal analysis at the genus level, broiler chickens were characterized by the presence of Weissella and Lactobacillus, as well as pigs were characterized by the presence of provetella and cattele were characterized by the presence of Acinetobacter. A permutational multivariate analysis of variance (PERMANOVA) showed that differences of microbial clusters among three groups were significant at the confidence level. (p=0.001). This study provides basic data that could be useful in future research on microorganisms associated with performance growth, as well as in studies on the livestock gut microbiome to increase productivity in the domestic livestock industry.