• Applied Biological Chemistry
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• v.43 no.2
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• pp.86-94
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• 2000

In order to develop the enzymatic hydrolysis system concerned with taste and flavor, strains having the high hydrolyzing activity on the soy protein were selected from some traditional Mejus. Two molds and one bacterium producing enzymes which were different in character of hydrolysis were isolated and identified. Leucine and azodye enzyme activities of both M4 and M5 were relatively high among in the isolated molds. And, leucine enzyme activity of B16 was the lowest in the isolated bacteria. These strains were isolated as microorganisms having a dissimilar hydrolysis pattern on the soy protein by enzymatic reactions. Mold M4 on the culture solid media was mycelium colors of white and its sclerotia colors were changed from white to black. According to the result of slide culture, radial conidial head, subclavate vesicle, conidia of subglobose, stipes of uncolored with smooth walls and metula and phialides were existed. Because M4 was taxonomically similar to the characteristics of Aspergillus oryzae (ahlburg) species, M4 was identified and named as Aspergillus oryzae M4.Mold M5 showed white and black mycelium on the MEA medium. Mold M5 colony exhibited grayish-green color and have long(7 mm) sporangiophores at slide culture. Sporangia became brownish-gray and the wall of larger sporangia was broken to form small collars, and smaller sporangia were fomed continually from large basal membrane. Columella is globose and hyaline, and sporangiospores are ellipsoidal of small diameter$(80\;{\mu}m)$. Because M5 was taxonomically similar to the Mucor circinelloides of zygomycetes, M5 was was identified and named as Mucor circinelloides M5. Bacteria B16 colony was opaque white, circular and lobate, and had rod shaped endospore. B16 was found positive in stain, catalase, ${\beta}-glucosidse$ and V-P tests. B16 was found to utilize D-fructose, ${\alpha}-D-glucose$, maltose, D-mannose, D-raffinose, stachyose and sucrose. By the morphological and physiological results, the characteristics of B16 was thought to correspond to that of Bacillus megaterium. However, fatty acid composition was similar to Paenibacillus marcerans, requiring further study for the definite identification. Accordingly, Bacteria B16 was provisionally classified and named as Bacillus megaterium B16.

• Economic and Environmental Geology
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• v.52 no.3
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• pp.251-258
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• 2019

During the detailed geological survey around the southern Yangsan Fault, we newly found a Quaternary fault outcrop, which cuts unconsolidated sediments. The fault named the Sinwoo site, located in the Sinwoo pasture, Miho-ri, Duseo-myeon, Ulsan metropolitan city, is the first discovered Quaternary fault near the western part of the south Yangsan Fault. In this study, we provide information on characteristics of fault geometry and unconsolidated sediment at Sinwoo site based on the analysis data of topography, drainage, and lineament around the study site. The fault site is situated at pediment slope, but fan-shaped middle terrace, as well as thick sediment exposed at low terrace, indicates that the unconsolidated sediments have been deposited in the alluvial fan environment. The drainage develops to the third-order drainage system, and the first and the second drainage system meet at right angles to each other and form a radial drainage pattern. In addition, the NE-SW direction lineaments can be identified on the basis of the curvature of the river and the step of the topographic relief, running over the Sinwoo site. The fault of $N30-35^{\circ}E/79-82^{\circ}SE$ shows ~ 5.8 m apparent vertical offset and dominantly reverse-slip sense based on slickenline, rotation of pebbles, and drag folding at footwall. However, some discontinuous sediments observed in the footwall are interpreted as fissure-filling materials due to the strike-slip movement. Now, we are under multidisciplinary investigations of additional field survey and age dating in order to determine the evolution of Sinwoo site fault during the Quaternary.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.119-133
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• 2020

Fama asserted that in an efficient market, we can't make a trading rule that consistently outperforms the average stock market returns. This study aims to suggest a machine learning algorithm to improve the trading performance of an intraday short volatility strategy applying asymmetric volatility spillover effect, and analyze its trading performance improvement. Generally stock market volatility has a negative relation with stock market return and the Korean stock market volatility is influenced by the US stock market volatility. This volatility spillover effect is asymmetric. The asymmetric volatility spillover effect refers to the phenomenon that the US stock market volatility up and down differently influence the next day's volatility of the Korean stock market. We collected the S&P 500 index, VIX, KOSPI 200 index, and V-KOSPI 200 from 2008 to 2018. We found the negative relation between the S&P 500 and VIX, and the KOSPI 200 and V-KOSPI 200. We also documented the strong volatility spillover effect from the VIX to the V-KOSPI 200. Interestingly, the asymmetric volatility spillover was also found. Whereas the VIX up is fully reflected in the opening volatility of the V-KOSPI 200, the VIX down influences partially in the opening volatility and its influence lasts to the Korean market close. If the stock market is efficient, there is no reason why there exists the asymmetric volatility spillover effect. It is a counter example of the efficient market hypothesis. To utilize this type of anomalous volatility spillover pattern, we analyzed the intraday volatility selling strategy. This strategy sells short the Korean volatility market in the morning after the US stock market volatility closes down and takes no position in the volatility market after the VIX closes up. It produced profit every year between 2008 and 2018 and the percent profitable is 68%. The trading performance showed the higher average annual return of 129% relative to the benchmark average annual return of 33%. The maximum draw down, MDD, is -41%, which is lower than that of benchmark -101%. The Sharpe ratio 0.32 of SVS strategy is much greater than the Sharpe ratio 0.08 of the Benchmark strategy. The Sharpe ratio simultaneously considers return and risk and is calculated as return divided by risk. Therefore, high Sharpe ratio means high performance when comparing different strategies with different risk and return structure. Real world trading gives rise to the trading costs including brokerage cost and slippage cost. When the trading cost is considered, the performance difference between 76% and -10% average annual returns becomes clear. To improve the performance of the suggested volatility trading strategy, we used the well-known SVM algorithm. Input variables include the VIX close to close return at day t-1, the VIX open to close return at day t-1, the VK open return at day t, and output is the up and down classification of the VK open to close return at day t. The training period is from 2008 to 2014 and the testing period is from 2015 to 2018. The kernel functions are linear function, radial basis function, and polynomial function. We suggested the modified-short volatility strategy that sells the VK in the morning when the SVM output is Down and takes no position when the SVM output is Up. The trading performance was remarkably improved. The 5-year testing period trading results of the m-SVS strategy showed very high profit and low risk relative to the benchmark SVS strategy. The annual return of the m-SVS strategy is 123% and it is higher than that of SVS strategy. The risk factor, MDD, was also significantly improved from -41% to -29%.