• Korean Journal of Ecology and Environment
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• v.43 no.1
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• pp.82-90
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• 2010

The ecological characteristics of the Korean Aucha perch, Coreoperca herzi, were determined in order to estimate stock of the mid-upper system of the Seomjin River. The age was determined by counting the otolith annuli. The oldest fish observed in this study was 5 years old. Relationships between body length (BL) and body weight (BW) were $BW=0.0195BL^{3.08}$ ($R^2=0.966$) (p<0.01). Relationships between the otolith radius (R) and body length (BL) were BL=3.882R+1.66 ($R^2=0.944$). The von Bertalanffy growth parameters estimated from a non-linear regression method were $L_{\infty}=19.68\;cm$, $W_{\infty}=188.64\;g$, $K=0.17\;year^{-1}$ and $t_0=-1.46$ year. Therefore, growth in length of the fish was expressed by the von Bertalanffy's growth equation as $L_t=19.68$ ($1-e^{-0.17(t+1.46)}$) ($R^2=0.997$). The annual survival rate (S) was estimated to be $0.666\;year^{-1}$. The instantaneous coefficient of natural mortality (M) of estimated from the Zhang and Megrey method was $0.346\;year^{-1}$, and instantaneous coefficient of fishing mortality (F) was calculated $0.061\;year^{-1}$. From the estimates of survival rate (S), the instantaneous coefficient of total mortality(Z) was estimated to be $0.407\;year^{-1}$.

• Korea Real Estate Review
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• v.28 no.1
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• pp.79-90
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• 2018

The purpose of this study was to estimate the pricing factors of residential lands in new cities by estimating the pricing model of residential lands. For this purpose, hedonic equations for each quantile of the conditional distribution of land prices were estimated using quantile regression methods and the sale price date of Jangyu New Town in Gimhae. In this study, a quantile regression method that models the relation between a set of explanatory variables and each quantile of land price was adopted. As a result, the differences in the effects of the characteristics by price quantile were confirmed. The number of years that elapsed after the completion of land construction is the quadratic effect in the model because its impact may give rise to a non-linear price pattern. Age appears to decrease the price until certain years after the construction, and increases the price afterward. In the estimation of the quantile regression, land age appears to have a statistically significant impact on land price at the traditional level, and the turning point appears to be shorter for the low quantiles than for the higher quantiles. The positive effects of the use of land for commercial and residential purposes were found to be the biggest. Land demand is preferred if there are more than two roads on the ground. In this case, the amount of sunshine will improve. It appears that the shape of a square wave is preferred to a free-looking land. This is because the square land is favorable for development. The variables of the land used for commercial and residential purposes have a greater impact on low-priced residential lands. This is because such lands tend to be mostly used for rental housing and have different characteristics from residential houses. Residential land prices have different characteristics depending on the price level, and it is necessary to consider this in the evaluation of the collateral value and the drafting of real estate policy.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.5
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• pp.335-347
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• 2013

In February 2008, high storm waves due to a developed atmospheric low pressure system propagating from the west off Hokkaido, Japan, to the south and southwest throughout the East Sea (ES) caused extensive damages along the central coast of Japan and along the east coast of Korea. This study consists of two parts. In the first part, we estimate extreme storm wave characteristics in the Toyama Bay where heavy coastal damages occurred, using a non-hydrostatic meteorological model and a spectral wave model by considering the extreme conditions for two factors for wind wave growth, such as wind intensity and duration. The estimated extreme significant wave height and corresponding wave period were 6.78 m and 18.28 sec, respectively, at the Fushiki Toyama. In the second part, we perform numerical experiments on wave-structure interaction in the Fushiki Port, Toyama Bay, where the long North-Breakwater was heavily damaged by the storm waves in February 2008. The experiments are conducted using a non-linear shallow-water equation model with adaptive mesh refinement (AMR) and wet-dry scheme. The estimated extreme storm waves of 6.78 m and 18.28 sec are used for incident wave profile. The results show that the Fushiki Port would be overtopped and flooded by extreme storm waves if the North-Breakwater does not function properly after being damaged. Also the storm waves would overtop seawalls and sidewalls of the Manyou Pier behind the North-Breakwater. The results also depict that refined meshes by AMR method with wet-dry scheme applied capture the coastline and coastal structure well while keeping the computational load efficiently.

• Korean Journal of Environment and Ecology
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• v.25 no.3
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• pp.318-326
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• 2011

The population ecological characteristics of the Crucian carp, Carassius auratus, were determined in order to estimate stock of the mid-upper system of the Seomjin River. The fish ranged in size from 95 to 288mm total length. The age was determined by counting the scale annulus. The scales displayed clear annulus that were used to estimate the age. The oldest fish observed in this study was 5 years old. Age-2 fishes were the most numerous in the sample(n=38), followed in frequency be age-3(n=22). Marginal index analysis validated the formation of a single annulus per year. The relationship between body length and body weight was BW = $0.0038BL^{3.73}$($R^2$=0.96) (p<0.01). The relationship between the scale radius and body length was BL = 2.362R+2.76($R^2$=0.89). The von Bertalanffy growth parameters estimated from a non-linear regression method were $L_{\infty}$=33.2 cm, $W_{\infty}$=1,798.4 g, $K=0.20year^{-1}$ and $t_0$=-0.51year. Therefore, Growth in length of the fish was expressed by the von Bertalanffy's growth equation as $L_t=33.23$($1-e^{-0.20(t+0.51)}$)($R^2$=0.98). The annual survival rate was estimated to be 0.427year$^{-1}$. The instantaneous coefficient of natural mortality of estimated from the Zhang and Megrey method was $0.784year^{-1}$, and instantaneous coefficient of fishing mortality was calculated $0.067year^{-1}$. From the estimates of survival rate, the instantaneous coefficient of total mortality was estimated to be $0.851year^{-1}$.

• Radiation Oncology Journal
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• v.16 no.4
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• pp.409-423
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• 1998

Purpose : This retrospective study was tried to evaluate the clinical characteristics of patients, patterns of failure, survival rates, prognostic factors affecting survival, and treatment related toxicities when non-small cell lung cancer patients was treated by definitive radiotherapy alone or combined with chemotherapy. Materials and Methods : We evaluated the treatment results of 70 patients who were treated by definitive radiation therapy for non-small cell lung cancer at the Department of Radiation Oncology, Ewha Womans University Hospital, between March 1982 and April 1996. The number of patients of each stage was 2 in stage I, 6 in stage II, 30 in stage III-A, 29 in stage III-B, 3 in stage IV. Radiation therapy was administered by 6 MV linear accelerator and daily dose was 1.8-2.0 Gy and total radiation dose was ranged from 50.4 Gy to 72.0 Gy with median dose 59.4 Gy. Thirty four patients was treated with combined therapy with neoadjuvant or concurrent chemotherapy and radiotherapy, and most of them were administered with the multi-drug combined chemotherapy including etoposide and cisplatin. The survival rate was calculated with the Kaplan-Meier methods. Results : The overall 1-year, 2-year, and 3-year survival rates were 63$\%$, 29$\%$, and 26$\%$, respectively. The median survival time of all patients was 17 months. The disease-free survival rate for 1-year and 2-year were 23$\%$ and 16$\%$, respectively. The overall 1-year survival rates according to the stage was 100$\%$ for stage I, 80$\%$ for stage II, 61$\%$ for stage III, and 50$\%$ for stage IV. The overall 1-year 2-year, and 3-year survival rates for stage III patients only were 61$\%$, 23$\%$, and 20$\%$, respectively. The median survival time of stage III patients only was 15 months. The complete response rates by radiation therapy was 10$\%$ and partial response rate was 50$\%$. Thirty patients (43$\%$) among 70 patients assessed local control at initial 3 months follow-up duration. Twenty four (80$\%$) of these 30 Patients was possible to evaluate the pattern of failure after achievement of local control. And then, treatment failure occured in 14 patients (58$\%$): local relapse in 6 patients (43$\%$), distant metastasis in 6 patients (43$\%$) and local relapse with distant metastasis in 2 patients (14$\%$). Therefore, 10 patients (23$\%$) were controlled of disease of primary site with or without distant metastases. Twenty three patients (46$\%$) among 50 patients who were possible to follow-up had distant metastasis. The overall 1-year survival rate according to the treatment modalities was 59$\%$ in radiotherapy alone and 66$\%$ in chemoirradiation group. The overall 1-year survival rates for stage III patients only was 51$\%$ in radiotherapy alone and 68$\%$ in chemoirradiation group which was significant different. The significant prognostic factors affecting survival rate were the stage and the achievement of local control for all patients at univariate- analysis. Use of neoadjuvant or concurrent chemotherapy, use of chemotherapy and the achievement of local control for stage III patients only were also prognostic factors. The stage, pretreatment performance status, use of neoadjuvant or concurrent chemotherapy, total radiation dose and the achievement of local control were significant at multivariate analysis. The treatment-related toxicities were esophagitis, radiation pneunonitis, hematologic toxicity and dermatitis, which were spontaneously improved, but 2 patients were died with radiation pneumonitis. Conclusion : The conventional radiation therapy was not sufficient therapy for achievement of long-term survival in locally advanced non-small cell lung cancer. Therefore, aggressive treatment including the addition of appropriate chemotherapeutic drug to decrease distant metastasis and preoperative radiotherapy combined with surgery, hyperfractionation radiotherapy or 3-D conformal radiation therapy for increase local control are needed.

• 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.

• 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.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.123-139
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• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• Radiation Oncology Journal
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• v.28 no.1
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• pp.32-38
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• 2010

Purpose: Although radiation-induced fibrosis is one of the common sequelae occurring after irradiation of skin and soft tissues, the treatment methods are not well standardized. This study aimed to establish the skin fibrosis mouse model by fractionated radiation for the further mechanism studies or testing the efficacy of therapeutic candidates. Materials and Methods: The right hind limbs of BALB/c mice received two fractions of 20 Gy using a therapeutic linear accelerator. Early skin damages were scored and tissue fibrosis was assessed by the measurement of a leg extension. Morphological changes were assessed by H&E staining and by Masson's Trichrome staining. TGF-${\beta}1$ expression from soft tissues was also detected by immunohistochemistry and PCR. Results: Two fractions of 20 Gy irradiation were demonstrated as being enough to induce early skin damage effects such as erythema, mild skin dryness, dry and wet desquamation within several weeks of radiation. After 13 weeks of irradiation, the average radiation-induced leg contraction was $11.1{\pm}6.2mm$. Morphologic changes in irradiated skin biopsies exhibited disorganized collagen and extracellular matrix fibers, as well as the accumulation of myofibroblasts compared to the non-irradiated skin. Moreover, TGF-${\beta}1$ expression in tissue was increased by radiation. Conclusion: These results show that two fractions of 20 Gy irradiation can induce skin fibrosis in BALB/c mice accompanied by other common characteristics of skin damages. This animal model can be a useful tool for studying skin fibrosis induced by radiation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.2
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• pp.70-80
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• 2003

We report the first direct measurement of $CO_2$ flux over Kwangneung broadleaf deciduous forest, one of the tower flux sites in KoFlux network. Eddy covariance system was installed on a 30 m tower along with other meteorological instruments from June to August in 2002. Although the study site was non-ideal (with valley-like terrain), turbulence characteristics from limited wind directions (i.e., 90$\pm$45$^{\circ}$) was not significantly different from those obtained at simple, homogeneous terrains with an ideal fetch. Despite very low rate of data retrieval, preliminary results from our analysis are encouraging and worthy of further investigation. Ignoring the role of advection terms, the averaged net ecosystem exchange (NEE) of $CO_2$ ranged from -1.2 to 0.7 mg m$^{-2}$ s$^{-1}$ from June to August in 2002. The effect of weak turbulence on nocturnal NEE was examined in terms of friction velocity (u*) along with the estimation of storage term. The effect of low uf u* NEE was obvious with a threshold value of about 0.2 m s$^{-1}$ . The contribution of storage term to nocturnal NEE was insignificant; suggesting that the $CO_2$ stored within the forest canopy at night was probably removed by the drainage flow along the hilly terrain. This could be also an artifact of uncertainty in calculations of storage term based on a single-level concentration. The hyperbolic light response curves explained ＞80% of variation in the observed NEE, indicating that $CO_2$ exchange at the site was notably light-dependent. Such a relationship can be used effectively in filling up the missing gaps in NEE data through the season. Finally, a simple scaling analysis based on a linear flow model suggested that advection might play a significant role in NEE evaluation at this site.