• Korean Journal of Environment and Ecology
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• v.7 no.2
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• pp.118-134
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• 1994

This study was conducted to investigated the plant community structure and to revaluate the part of plant ecosystem on statement of environmental impact assessment in Muju resort golf course, Solch'on area, Tokyusan National Park. The actual vegetation was comprised of Pinus densiflora-Quercus mongolica-Q. serrata community(33.21%), Q. spp. community(27.30%), P. densiflora community(20.68%) and high mountain marsh(4.93%) etc., which communities were the major vegetation and the forest vegetation was came to being a peculiar to environmental condition. The degree of green naturality 8, 9 was covered 93% in survey area, and so this result reflect the stability of ecosystem. There was all the difference between the statement of environmental impact assessment of development concerned and this study result in the estimation of degree of green naturality. The plant community were divided into six groups in fifty-four plots by DCA and the dividing groups were P. densiflora, P. densiflora-Q. mongolica, P. densiflora-Q. serrata-F. mandschurica-B. davurica, Q. mongolica-Q. serrata-P. densiflora, Q. mongolica-Q. variabilis, Salix koreansis- B. davurica community. Except P. densiflora forest in survey site, the ecological succession trend of the other communities was seemed to be from P. densiflora to Q. spp.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6236-6246
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• 2015

In the paper, we reduce non-pregnant conditions and improve impregnation rate by unmanned estrus detection and decide proper time for artificial insemination. It is too hard to detect estrus only by using activities, we develop unmanned estrus detection system that consist of RF activity sensors, cow management program and estrus detection algorithm that uses information of activities and breeding. We verify performance by experiments in four similar scale stockbreeding farmhouse. Each stockbreeding farmhouse breeds 87, 81, 93, 82 cows and expected estrus cows are 14, 19, 15, 17. In expected estrus cow, we fail in weak estrus detection - 3, 2, 1, 3 cows, but detect successfully normal estrus - 11, 17, 14, 14 cows. After artificial insemination, 10, 17, 13, 14 cows became pregnant successfully confirming that proposed unmanned estrus detection system is effective for deciding proper time for artificial insemination in normal estrus.

• Parasites, Hosts and Diseases
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• v.33 no.4
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• pp.323-330
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• 1995

Protease activity was identified in crude extracts of Pnrqgonimw westermnni eggs which were purified from infected dog lungs, isolated on 14 weeks after metacercarial challenge. The eggs were used after removing possibly contaminated host or worm tissues on their shell surfaces. In the crude egg extracts, high proteolytic activities against carboBfrb enzoyl - ph enylalanyl - arginyl-4- methoxy- β- naphthylamide (Cbz - phe - arg- MNA) and Azocoll were detected whereas those against succinyl-alanyl-propyl-phenylalanyl-p- nitroanilide (Suc-ala-pro-phe-pNA) were not revealed. The eVe eBdlibited the maximal activity at pH 6. Its activity was inhibited by specific cysteine protease inhibitors, 105 M I- trans-epoxysuccinylleucylamido (4-guanidino) butane (E-64) and 1 mM iodoacetamide (LAA) while potentiated by 6.5-fold in the presence of 2.5 mM dithiothreitol (DTT) . When the enzyme was purified partially by Sephacryl S-300 High Resolution gel filtration, it migrated as a single homogeneous band at 35 kDa. The 35 kDa cysteine protease has been recognized neither in the metacercariae nor in the adult. These findings indicated the presence of at least one protease of cathepsin family in immature eggs of f westernani.

• The Korean Journal of Mycology
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• v.26 no.2 s.85
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• pp.246-255
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• 1998

Ganoderan (GAN), an immunomodulating ${\beta}-glucan$ of G. lucidum, induces potent antitumor immunity in tumor-bearing mice. This study was set up to elucidate the ability of macrophage activation of GANs. GAN-treated Raw 264.7 macrophages showed enhanced production of nitric oxide (NO). The ability of GANs to produce NO was based on differences in chemical composition of GANs obtained from the mycelium on various carbon sources and mycelial fractionation. The highest NO production was observed in CW-AS-WS polysaccharide which was extracted from the mycelial wall. GAN-treated Raw 264.7 cells gave a 2-to 5-fold (24 hr) formation of NO levels compared with those treated with medium only. Partial removal of the protein in the extracellular GAN by TCA treatment did appreciably reduce its capacity to secrete NO. The mixture effect of GAN and LPS increased the nitric oxide secretion from RAW 264.7. The cell proliferation of GAN-treated Raw 264.7 cell tines inhibited as compared with its control. Of the culture supernatant of macrophage activated by GAN, the percentage of cytotoxicity against mouse leukemia L1210 cells was slightly dependent on the amount of NO in the culture supernatants of the activated-macrophages. These results indicate that the ${\beta}-glucan-related$ polysaccharides of the higher fungus activate macrophage and release nitric oxide. It also suggests that murine macrophages possess certain receptors for ${\beta}-anomeric$ glucans and play a critical role of ${\beta}-glucan-related$ tumor killing mechanism.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.