• The Korean Journal of Financial Management
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• v.27 no.1
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• pp.181-208
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• 2010

In July 2007, Korean government has passed "The Capital Market and Financial Investment Services Act" to further develop the capital markets and the Act was to become effective in February 2009. Using a large sample of Korean firms, we have examined (i) the effect of underwriting activities on the firm value (bond spread) comparing commercial bank and investment bank, and (ii) the determinants of the firm value changes following underwriting activities of bank. To test our goal, we collected a wide range of samples of data for bond issuing activities executed by Korean firms listed on the Korea Stock Exchange (KSE) between 2000 and 2003. Our paper is distinguished from previous studies on this subject in a way that we analyzed the effect of corporate bond underwriting activities with regard to commercial banking and investment banking. Initially, we set up a hypothesis that "Certification View" and "Conflict-of-interest View" are major driving forces behind cross-firm differences in performance following bond issuance. We find that, in general, underwriting by investment bank (securities company) brings a positive effect on the firm value (spread between bench mark rate and bond issuing rate). This result indicates that firm value has been negatively affected by the bank underwriting and provides the evidence for "Conflict-of-interest View" in Korea. Our studies have also revealed that any change in firm value following bond issuance is positively related with the firm size (total asset), operating performance, liquidity (cashflow), and equity ownership by foreign investors. Overall, our results support the view that bank underwriting activities can play an important role in determining firm value and financial strategies under "The Capital Market and Financial Investment Services Act" of 2007.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Cartoon and Animation Studies
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• s.30
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• pp.201-219
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• 2013

Development of digital media in education field at America, UK, Japan etc bring big progress on digital device if education. Japan bring huge progress on digital education by nationally. UK use huge a national budget at digital education development and Sweden which is advanced country of education and a welfare state. Especially UK and Sweden's digital education markets are full now aspect more high quality design. Korea which is advanced country of IT adopted digital text book 2007 with mathematics, through science and English digital text book through the state. Korea's digital text book is in a transition period. that needs case study of advanced country of education for setting design guide and educational effect to digital education media and device plan. All researches are based on LG europe design center at London. Analysis by using KJ method, survey of questionnaire, heuristic method at 4 schools in UK and Sweden. Through analytical researches want to more reality simulation at digital education, and high quality contents with digital socialization. co-work with analog, can get any where, anytime user want without any difficulty. Also interactive GUI design of digital education device to easy to access for user. When plan Digital text book content and design needs methodical design guide for target who students and environment an in-depth study of the appraisal and method. The results of the research are introduce the design plan as a basic research and giving useful design plan to make digital educational media in Korea industrial aspect.

• Korean Journal of Ecology and Environment
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• v.42 no.3
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• pp.382-393
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• 2009

The objectives of this study were to characterize long-term annual and seasonal trophic state of Topjeong Reservoir using conventional variables of Trophic State Index (TSI) and to determine the empirical relations between the trophic parameters. For the analysis, we used water quality dataset of 1995$\sim$2007, which is obtained from the Ministry of Environment, Korea and the number of parameters was 9. Annual ambient mean values of TN and TP were 1.78 mg $L^{-1}$ and 0.03 mg $L^{-1}$, respectively and TN : TP ratios averaged 76, indicating that this system was nitrogen-rich hypertrophic, and was probably phosphorus-limitation for algal growth. Therefore, nitrogen varied little with seasons and years, and total phosphorus (TP) varied depending on season and year. Monsoon dilutions of TP occurred in August and monthly fluctuations of suspended solid (SS) was similar to those of chlorophyll-$\alpha$ (CHL). Annual mean values of BOD and $COD_{Mn}$ were 1.61 mg $L^{-1}$ and 4.23 mg $L^{-1}$, respectively and the interannual values were directly influenced by the intensity of annual rainfall. There were no significant differences in the trophic variables between the two sampling sites. Mean values of Trophic State Index (TSI, Carlson, 1977), based on TN, TP, CHL, and SD (Secchi depth), turned out as eutrophic state, except for the TN (hypertrophic). Regression analyses of log-transformed seasonal CHL against TP and TN showed that variation of the CHL was explained 37% by the variation of TP ($R^2$=0.37, p<0.001, r=0.616), but not by TN ($R^2$=0.03, p>0.05). Regression coefficient of $Log_{10}$CHL vs $Log_{10}SD$ was 0.330 (p<0.003, r=0.580), indicating that transparency is regulated by the organic matter in the system. Results, data suggest that one of the ways controlling the eutrophication would be a reduction of phosphorus from the watershed.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.125-133
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• 2007

Through open-sky policy, USA and European selected market principle of multiuser. However, in Asian case, major airlines monopolize airports. It is purpose that analyzes fare competition of Asian Hub Airport and the position of Incheon airport in Asia. Passengers required longer time and distance to go to the destination because direct flights decreases. But passengers increased in airport every year. Because of routes that decrease, airlines provide more services of flights. So airlines prefer to Hub Airports. As a result, both passengers and airlines are profitable by various routs and the increased frequency. On the assumption that distance and fare are related, the final formula is as following that defined the air fare from hub(H) to destination(Z) by logarithm. Analysis showed that log Rdist is not 1 but 0.08. As distance increases, fare doesn't increase. If distance from hub to destination airports is longer, Log dist_HZ is negative. It is that fare decreases from origin to destination via hub or that fare increases from hub to destination. HHI_HZ and HHI_AZ are negative. It means that if the degree of monopolization of hub and origin airports is lager, fare decreases from origin to destination via hub. Or fare increases from hub to destination. And it compares the Incheon airport with the other Asian hub airports and it examines the competitive fare by market division. As compared with the Incheon airport, Singapore, Beijing and Narita airports are higher fares. They compete with the other ones by Asian hub airports. But Hong Kong and Taipei airports must have more passengers through fare competition yet.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.107-116
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• 2013

This study was undertaken to investigate the characteristics of retention and evapotranspiration in the extensive greening module of sloped and flat rooftops for stormwater management and urban heat island mitigation. A series of 100mm depth's weighing lysimeters planted with Sedum kamtschaticum. were constructed on a 50% slope facing four orientations(north, east, south and west) and a flat rooftop. Thereafter the retention and evapotranspiration from the greening module and the surface temperature of nongreening and greening rooftop were recorded beginning in September 2012 for a period of 1 year. The characteristics of retention and evapotranspiration in the greening module were as follows. The water storage of the sloped and flat greening modules increased to 8.7~28.4mm and 10.6~31.8mm after rainfall except in the winter season, in which it decreased to 3.3mm and 3.9mm in the longer dry period. The maximum stormwater retention of the sloped and flat greening modules was 22.2mm and 23.1mm except in the winter season. Fitted stormwater retention function was [Stormwater Retention Ratio(%)=-18.42 ln(Precipitation)+107.9, $R^2$=0.80] for sloped greening modules, and that was [Stormwater Retention Ratio(%)=-22.64 ln(X)+130.8, $R^2$=0.81] for flat greening modules. The daily evapotranspiration(mm/day) from the greening modules after rainfall decreased rapidly with a power function type in summer, and with a log function type in spring and autumn. The daily evapotranspiration(mm/day) from the greening modules after rainfall was greater in summer > spring > autumn > winter by season. This may be due to the differences in water storage, solar radiation and air temperature. The daily evapotranspiration from the greening modules decreased rapidly from 2~7mm/day to less than 1mm/day for 3~5 days after rainfall, and that decreased slowly after 3~5 days. This indicates that Sedum kamtschaticum used water rapidly when it was available and conserved water when it was not. The albedo of the concrete rooftop and greening rooftop was 0.151 and 0.137 in summer, and 0.165 and 0.165 in winter respectively. The albedo of the concrete rooftop and greening rooftop was similar. The effect of the daily mean and highest surface temperature decrease by greening during the summer season showed $1.6{\sim}13.8^{\circ}C$(mean $9.7^{\circ}C$) and $6.2{\sim}17.6^{\circ}C$(mean $11.2^{\circ}C$). The difference of the daily mean and highest surface temperature between the greening rooftop and concrete rooftop during the winter season were small, measuring $-2.4{\sim}1.3^{\circ}C$(mean $-0.4^{\circ}C$) and $-4.2{\sim}2.6^{\circ}C$(mean $0.0^{\circ}C$). The difference in the highest daily surface temperature between the greening rooftop and concrete rooftop during the summer season increased with an evapotranspiration rate increase by a linear function type. The fitted function of the highest daily surface temperature decrease was [Temperature Decrease($^{\circ}C$)=$1.4361{\times}$(Evapotranspiration rate(mm/day))+8.83, $R^2$=0.59]. The decrease of the surface temperature by greening in the longer dry period was due to sun protection by the sedum canopy. The results of this study indicate that the extensive rooftop greening will assist in managing stormwater runoff and urban heat island through retention and evapotranspiration. Sedum kamtschaticum would be the ideal plant for a non-irrigated extensive green roof. The shading effects of Sedum kamtschaticum would be important as well as the evapotranspiration effects of that for the long-term mitigation effects of an urban heat island.