• Korean Journal of Environment and Ecology
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• v.32 no.3
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• pp.313-322
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• 2018

To investigate the changing patterns of sub-alpine forest vegetation due to climate change requires accumulation of contiguous reference data and continuous monitoring. Furthermore, it is crucial to monitor short-term ecological change of lower level vegetation to understand the trend of long-term vegetation change. Therefore, this study carried out a vegetation survey and tree diameter measurement in 36 plots of Mt. Jiri inhabited by Abies koreana species from 2015 to 2017 to examine the short-term dynamics of Abies koreana seedling and the change of vegetation distribution according to altitude. We analyzed the importance value and MIV (mean importance value) of major species by each stratum as well as the importance value and species diversity index of major species and the change of seedling population by altitude. The results showed that Abies koreana had the highest importance value on tree layer, Rhododendron schlippenbachii on shrub layer and Tripterygium regelii on herb layer. MIV was high in the order of Abies koreana, Rhododendron schlippenbachii and Acer pseudosieboldianum. Regarding the species composition and species diversity index (H') along the altitudinal gradient, Sasa borealis showed high MI and low H' in the elevation less than 1,500 m, and IV of Tripterygium regelii and H' of herb layer were high in the elevation of 1,700 - 1,800 m. Abies koreana seedling decreased by 22.4% from 1,250 n/ha in 2015 to 970 n/ha in 2017 (p <0.05) throughout the investigated area. The decline rate along seedling and sapling height were 22.9% in less than 10 cm, 3.4% in 10-30 cm, 8.9% in 30-50 cm, 39.3% in 50-100 cm, and 55.1% more than 100 cm. Few of A. koreana seedlings appeared due to the dominance of Sasa borealis in the elevation of 1,500 m or less and due to the dominance and high species diversity of Tripterygium regelii in the elevation of 1,700-1,800 m. On the other hand, many of A. koreana seedlings appeared in the elevation of 1,600-1,700 m due to no distribution of S. borealis and T. regelii species in that altitude range. Therefore, we concluded that those seedlings and saplings of A. koreana could be more stable in the altitude of 1,600-1,700 m.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• The Korean Journal of Financial Management
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• v.24 no.2
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• pp.41-79
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• 2007

This study examines the expiration-day effects of stock index futures and options in the Korean stock market. The so-called 'expiration-day effects', which are the abnormal stock price movements on derivatives expiration days, arise mainly from cash settlement. Index arbitragers have to bear the risk of their positions unless they liquidate their index stocks on the expiration day. If many arbitragers execute large buy or sell orders on the expiration day, abnormal trading volumes are likely to be observed. If a lot of arbitragers unwind positions in the same direction, temporary trading imbalances induce abnormal stock market volatility. By contrast, if some information arrives at market, the abnormal trading activity must be considered a normal process of price discovery. Stoll and Whaley(1987) investigated the aggregate price and volume effects of the S&P 500 index on the expiration day. In a related study, Stoll and Whaley(1990) found a similarity between the price behavior of stocks that are subject to program trading and of the stocks that are not. Thus far, there have been few studies about the expiration-day effects in the Korean stock market. While previous Korean studies use the KOSPI 200 index data, we analyze the price and trading volume behavior of individual stocks as well as the index. Analyzing individual stocks is important for two reasons. First, stock index is a market average. Consequently, it cannot reflect the behavior of many individual stocks. For example, if the expiration-day effects are mainly related to a specific group, it cannot be said that the expiration of derivatives itself destabilizes the stock market. Analyzing individual stocks enables us to investigate the scope of the expiration-day effects. Second, we can find the relationship between the firm characteristics and the expiration-day effects. For example, if the expiration-day effects exist in large stocks not belonging to the KOSPI 200 index, program trading may not be related to the expiration-day effects. The examination of individual stocks has led us to the cause of the expiration-day effects. Using the intraday data during the period May 3, 1996 through December 30, 2003, we first examine the price and volume effects of the KOSPI 200 and NON-KOSPI 200 index following the Stoll and Whaley(1987) methodology. We calculate the NON-KOSPI 200 index by using the returns and market capitalization of the KOSPI and KOSPI 200 index. In individual stocks, we divide KOSPI 200 stocks by size into three groups and match NON-KOSPI 200 stocks with KOSPI 200 stocks having the closest firm characteristics. We compare KOSPI 200 stocks with NON-KOSPI 200 stocks. To test whether the expiration-day effects are related to order imbalances or new information, we check price reversals on the next day. Finally, we perform a cross-sectional regression analysis to elaborate on the impact of the firm characteristics on price reversals. The main results seem to support the expiration-day effects, especially on stock index futures expiration days. The price behavior of stocks that are subject to program trading is shown to have price effects, abnormal return volatility, and large volumes during the last half hour of trading on the expiration day. Return reversals are also found in the KOSPI 200 index and stocks. However, there is no evidence of abnormal trading volume, or price reversals in the NON-KOSPI 200 index and stocks. The expiration-day effects are proportional to the size of stocks and the nearness to the settlement time. Since program trading is often said to be concentrated in high capitalization stocks, these results imply that the expiration-day effects seem to be associated with program trading and the settlement price determination procedure. In summary, the expiration-day effects in the Korean stock market do not exist in all stocks, but in large capitalization stocks belonging to the KOSPI 200 index. Additionally, the expiration-day effects in the Korean stock market are generally due, not to information, but to trading imbalances.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.10
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• pp.1312-1317
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• 2008

Physicochemical changes were investigated for the shelf-life extension of cultured wild-ginseng roots during storage with various pre-treatments with blanching, CAMICA-SD and DF-100 and treatments with citric acid and vitamin C. The pH of cultured wild-ginseng roots showed the range of $6.06{\sim}6.42$ at $10^{\circ}C$, but showed higher ranges of $6.08{\sim}6.91$ and $6.08{\sim}8.68$ at 20 and $30^{\circ}C$, respectively. Browning index (a/b) was increased with increasing storage temperature, and the index at 10 and $30^{\circ}C$ were 0.405 and 0.469 after 2 weeks, respectively. Browning index and viable cell number of CAMICA-SD pre-treatment showed little changes compared to pre-teatment with blanching or DF-100. When the cultured wild-ginseng roots were treated with 1.0% citric acid and 0.2% DF-100 after pre-treatments with CAMICA-SD, viable cell number was slightly increased to $4.9{\times}10^2CFU/g$ for 3 weeks storage at $10^{\circ}C$. The mixture of citric acid and DF-100 was also used to prevent the growth of microbiology and to reduce browning reaction, especially enzymatic browning reaction. The mixture might effectively extend shelf life of the cultured wild-ginseng roots.

• Korean Journal of Materials Research
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• v.4 no.5
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• pp.550-555
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• 1994

The effects of RTA treatment on the leakage current have been studied for tantalum pentoxide( $Ta_2O_5$) films deposited by PECVD on P-type(100) Si substrate using $TaCl_5$(99.99%) and $N_2O$(99.99%) gaseous mixture. The refractive index increased with increasing the deposition temperature and the maximum deposition rate was obtained at $500^{\circ}C$. The Ta-0 bond peak intensity of as-deposited $Ta_2O_5$ increased with increasing the deposition temperature through FT-IR analysis and the leakage current value was decreased with increasing the deposition temperature. The small leakage current value obtained after RTA treatment of as-deposited $Ta_2O_5$ was found to be due to the reduction of 0-deficient structure in the film. The increases of the oxygen coacentration and the Ta-0 bond peak intensity in the film after RTA treatment were measured by AES and FT-IR analyses.

• Journal of the Korean Solar Energy Society
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• v.33 no.2
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• pp.11-17
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• 2013

Silicon nitride($SiN_x:H$) deposited by radio frequency plasma enhanced chemical vapor deposition(RF-PECVD) is commonly used for anti-reflection coating and passivation in crystalline silicon solar cell fabrication. In this paper, characteristics of the deposited silicon nitride was studied with change of working pressure, deposition temperature, gas ratio of $NH_3$ and $SiH_4$, and RF power during deposition. The deposition rate, refractive index and effective lifetime were analyzed. The (100) p-type silicon wafers with one-side polished, $660-690{\mu}m$, and resistivity $1-10{\Omega}{\cdot}cm$ were used. As a result, when the working pressure increased, the deposition rate of SiNx was increased while the effective life time for the $SiN_x$-deposited wafer was decreased. The result regarding deposition temperature, gas ratio and RF power changes would be explained in detail below. In this paper, the optimized condition in silicon nitride deposition for silicon solar cell was obtained as 1.0 Torr for the working pressure, $400^{\circ}C$ for deposition temperature, 500 W for RF power and 0.88 for $NH_3/SiH_4$ gas ratio. The silicon nitride layer deposited in this condition showed the effective life time of > $1400{\mu}s$ and the surface recombination rate of 25 cm/s. The crystalline silicon solar cell fabricated with this SiNx coating showed 18.1% conversion efficiency.

• 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%.

• Korean Journal of Community Nutrition
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• v.10 no.4
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• pp.493-500
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• 2005

There is some evidence that soy isoflavone has beneficial effects on the concentration of blood lipids. In this study, we investigated habitual isoflavone intake levels and the relation among dietary isoflavone intake, blood pressure, and blood lipids of adult men (n = 149) and women (n = 205). Anthropometric measurements including blood pressure, dietary in-take assessment using 24-hour recall method, and biochemical assessment using blood were conducted. The average age, height, weight, and BMI were 54.7 years, 168.5 cm, 67.3 kg, and 24.5 $kg/m^2$ for men and 53.9 years, 153.8 cm, 59.2 kg, and 25.0 $kg/m^2$ for women, respectively. The mean daily intakes of total food and energy were 1219.1 g and 1740.9 kcal for men and 1071.3 g and 1432.6 kcal for women, respectively. The mean daily isoflavones (daidzein + genistein) intake of men and women were 20.0 mg and 14.2 mg, respectively. Blood pressure of the subjects was 128.3/75.5 mmHg for men and 124.1/73.7 mmHg for women. Serum lipids of men and women were 180.2 and 184.9 mg/dL for total cholesterol, 160.8 and 137.6 mg/dL for triglyceride, 41.5 and 44.7 mg/dL for HDL-cholesterol, 106.6 and 112.7 mg/dL for LDL-cholesterol, and 3.5 and 3.3 for atherogenic index, respectively. Serum triglyceride and atherogenic index of men were significantly higher than those of women. In men, isoflavone intake and the level of total serum cholesterol were negatively (p < 0.05) correlated, after adjusted age. In women, there were significant correlations between isoflavone intake and blood pressure (systolic and diastolic), after adjusted age (p < 0.05). Based on these results, we concluded that higher isoflavone intake seemed to be related to a better lipid profile in men and lower blood pressure in women. But more epidemiological studies and controlled clinical trials would help to confirm the optimal amount required for the prevention and treatment of cardiovascular disease.

• Journal of the Korea Organic Resources Recycling Association
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• v.13 no.2
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• pp.107-120
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• 2005

To study the development of solid waste compost to use sewage sludge and paper mill sludge for reclaiming damage soil in forest, the changes of temperature, moisture, chemical properties, heavy metals and harmful compound during the aerobic decomposition were investigated, and the compost decomposition of final products investigated the round paper chromatography method and G.I(Germination index) value. The results were summarized as follows. Temperature was changed a little during early 5days because of air temperature too low. That was rapidly increased to over $50^{\circ}C$ at 4days after first turning and then decreased gradually fallen to $40{\sim}50^{\circ}C$ at 15days after aerobic decomposition in A and C treatments. The second turning was conducted at 18 days after aerobic decomposition, and then the temperature was little changed. At the compare first with terminal product, The moisture content was decreased all treatments but the change was little in A and B treatments. pH was decreased to below 1 in all treatments. EC was increased to below 5dS/m. The content of total carbon, C/N ratio, $NH_4{^+}-N$ were decreased with 4~7%, below 8 and below 500mg/kg in all treatments, respectively. The content of total nitrogen, $NO_3{^-}-N$, CEC were increased with below 0.5%, below 173mg/kg and over $30cmol^+/kg$ in all treatments, respectively. The content of heavy metals and harmful compound were similar during aerobic decomposition and suited to standard of 가 grade in all treatments. The result of round paper chromatography method and G.I. value, The C treatment concluded well aerobic decomposition. Especially, the G.I. value in C treatment was 64.1 and 66.2 at cabbage and grass, respectively.

• Korean Journal of Ecology and Environment
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• v.39 no.3 s.117
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• pp.340-351
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• 2006

To reveal physicochemical factors contributing to variation of phytoplankton communities, the study was carried out biweekly at 6 stations from Feb. 2004 to Feb. 2005 in the lower part of the Han River, Korea. As results, water temperature was changed from $0.3^{\circ}C$ to $26.6^{\circ}C$, pH: 6.6${\sim}$9.1, DO: 1.89${\sim}$22.23 mg $L^{-1}$, BOD: 0.38${\sim}$9.20 mg $L^{-1}$, COD: 1.4${\sim}$15.2 mg $L^{-1}$, Conductivity: $62.5{\sim}500.0\;{\mu}s\;cm^{-1}$, SS: 3.00${\sim}$159.3 mg $L^{-1}$, and Chl a $1.7{\sim}71.3\;{\mu}g\;L^{-1}$. Phytoplankton standing crops ranged from min. $3.6{\times}10^2\;cells\;mL^{-1}$ (July 2004, St. 3) to max. $2.3{\times}10^4\;cells\;mL^{-1}$ (Feb. 2005, St. 6), and mean of those varied from $5.9{\times}10^3\;cells\;mL^{-1}$in spring, $2.1{\times}10^3\;cells\;mL^{-1}$ in summer, $4.1{\times}10^3\;cells\;mL^{-1}$ in autumn and $8.5{\times}10^3\;cells\;mL^{-1}$ in winter, respectively. In order to investigate factors influencing the total phytoplankton standing crops a multiple regression analysis was adopted for the correlation between standing crops and environmental factors. The coefficient of determination ($R^2$) value of the regression was 0.465, it showed that environmental factors which predominantly influenced phytoplankton standing crops were water temperature, COD, $NO_2-N$, $PO_4-N$, Discharge and pH. six stations could be divided into 3 groups based on similarity index in terms of environmental factors. In ANOVA analysis for physicochemical and biological factors, water temperature, chlorophyll a, silicate, phytoplankton standing crops were the same group differed little from stations. However, Station 1and 2 were grouped followed in dissolved oxygen, conductivity, COD, nitrite, nitrate, ammonia and phosphate, and Station 3, 4 and 5 were followed in dissolved oxygen, conductivity, pH and phosphate.