• Journal of Bio-Environment Control
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• v.3 no.2
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• pp.119-127
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• 1994

This study was conducted to investigate the effects of temperature and light conditions on the vigor and growth responses of red pepper(Capsicum annuum L.) seedlings in the nonheated plastic houses with triple and quadruple coverings during winter. The results obtained were as follows ; 1. The growth in terms of plant height, number of leaves, leaf area and dry weight of each organ was reduced up to 50% in the triple coverings compared to quadruple ones. The greatest difference between the triple coverings and quadruple ones was the leaf area, showing two to five times larger in the quadruple ones. Therefore, the differences of the early environmental conditions during raising seedling stage was well reflected. 2. The leaf expansion in the early stage of seedling was delayed in the triple coverings and subsequently crop growth rate(CGR) significantly reduced. The specific leaf area (SLA) in the triple coverings was less than quadruple ones. The net assimilation rate (NAR) was increased in the early stage of seedlings and then reduced in the quadruple coverings. In triple ones, however, the great reduction showed at six weeks after sowing and then increased sharply. 3. The linear relationship among leaf area, total dry weight and leaf dry weight was observed in the all experimental areas, while between leaf area and crop growth rate only in the quadruple coverings, and between leaf area and net assimilation rate in both triple and quadruple ones. 4. The dry matter partitioned to the leaf increased up to six weeks after sowing in the triple coverings but reduced in the stem and root. However, the adverse results were obtained in the quadruple ones. 5. In the triple coverings, the number of branches showed the exponential increment while fruit weight showed linear increment in both triple and quadruple ones. Higher yield was obtained in the quadruple ones. 6. The shoot dry weight among the characteristics of seedlings was greatly contributed to the yield of red pepper after transplanting. Accordingly, one of the decisive criterion for good quality of red pepper seedlings was determined by the highest correlation between shoot dry weight of growing plant and fruit yield of pepper plant.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.69-85
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• 2016

Successful relationship with loving partners is one of the most important factors in life. In psychology, there have been some previous researches studying the factors influencing romantic relationships. However, most of these researches were performed based on statistical analysis; thus they have limitations in analyzing complex non-linear relationships or rules based reasoning. This research analyzes commitment and persistence in heterosexual involvement according to styles of loving using a datamining technique as well as statistical methods. In this research, we consider six different styles of loving - 'eros', 'ludus', 'stroge', 'pragma', 'mania' and 'agape' which influence romantic relationships between lovers, besides the factors suggested by the previous researches. These six types of love are defined by Lee (1977) as follows: 'eros' is romantic, passionate love; 'ludus' is a game-playing or uncommitted love; 'storge' is a slow developing, friendship-based love; 'pragma' is a pragmatic, practical, mutually beneficial relationship; 'mania' is an obsessive or possessive love and, lastly, 'agape' is a gentle, caring, giving type of love, brotherly love, not concerned with the self. In order to do this research, data from 105 heterosexual couples were collected. Using the data, a linear regression method was first performed to find out the important factors associated with a commitment to partners. The result shows that 'satisfaction', 'eros' and 'agape' are significant factors associated with the commitment level for both male and female. Interestingly, in male cases, 'agape' has a greater effect on commitment than 'eros'. On the other hand, in female cases, 'eros' is a more significant factor than 'agape' to commitment. In addition to that, 'investment' of the male is also crucial factor for male commitment. Next, decision tree analysis was performed to find out the characteristics of high commitment couples and low commitment couples. In order to build decision tree models in this experiment, 'decision tree' operator in the datamining tool, Rapid Miner was used. The experimental result shows that males having a high satisfaction level in relationship show a high commitment level. However, even though a male may not have a high satisfaction level, if he has made a lot of financial or mental investment in relationship, and his partner shows him a certain amount of 'agape', then he also shows a high commitment level to the female. In the case of female, a women having a high 'eros' and 'satisfaction' level shows a high commitment level. Otherwise, even though a female may not have a high satisfaction level, if her partner shows a certain amount of 'mania' then the female also shows a high commitment level. Finally, this research built a prediction model to establish whether the relationship will persist or break up using a decision tree. The result shows that the most important factor influencing to the break up is a 'narcissistic tendency' of the male. In addition to that, 'satisfaction', 'investment' and 'mania' of both male and female also affect a break up. Interestingly, while the 'mania' level of a male works positively to maintain the relationship, that of a female has a negative influence. The contribution of this research is adopting a new technique of analysis using a datamining method for psychology. In addition, the results of this research can provide useful advice to couples for building a harmonious relationship with each other. This research has several limitations. First, the experimental data was sampled based on oversampling technique to balance the size of each classes. Thus, it has a limitation of evaluating performances of the predictive models objectively. Second, the result data, whether the relationship persists of not, was collected relatively in short periods - 6 months after the initial data collection. Lastly, most of the respondents of the survey is in their 20's. In order to get more general results, we would like to extend this research to general populations.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.175-197
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• 2021

Recently, with the development of deep learning technology, research on unstructured data analysis is being actively conducted, and it is showing remarkable results in various fields such as classification, summary, and generation. Among various text analysis fields, text classification is the most widely used technology in academia and industry. Text classification includes binary class classification with one label among two classes, multi-class classification with one label among several classes, and multi-label classification with multiple labels among several classes. In particular, multi-label classification requires a different training method from binary class classification and multi-class classification because of the characteristic of having multiple labels. In addition, since the number of labels to be predicted increases as the number of labels and classes increases, there is a limitation in that performance improvement is difficult due to an increase in prediction difficulty. To overcome these limitations, (i) compressing the initially given high-dimensional label space into a low-dimensional latent label space, (ii) after performing training to predict the compressed label, (iii) restoring the predicted label to the high-dimensional original label space, research on label embedding is being actively conducted. Typical label embedding techniques include Principal Label Space Transformation (PLST), Multi-Label Classification via Boolean Matrix Decomposition (MLC-BMaD), and Bayesian Multi-Label Compressed Sensing (BML-CS). However, since these techniques consider only the linear relationship between labels or compress the labels by random transformation, it is difficult to understand the non-linear relationship between labels, so there is a limitation in that it is not possible to create a latent label space sufficiently containing the information of the original label. Recently, there have been increasing attempts to improve performance by applying deep learning technology to label embedding. Label embedding using an autoencoder, a deep learning model that is effective for data compression and restoration, is representative. However, the traditional autoencoder-based label embedding has a limitation in that a large amount of information loss occurs when compressing a high-dimensional label space having a myriad of classes into a low-dimensional latent label space. This can be found in the gradient loss problem that occurs in the backpropagation process of learning. To solve this problem, skip connection was devised, and by adding the input of the layer to the output to prevent gradient loss during backpropagation, efficient learning is possible even when the layer is deep. Skip connection is mainly used for image feature extraction in convolutional neural networks, but studies using skip connection in autoencoder or label embedding process are still lacking. Therefore, in this study, we propose an autoencoder-based label embedding methodology in which skip connections are added to each of the encoder and decoder to form a low-dimensional latent label space that reflects the information of the high-dimensional label space well. In addition, the proposed methodology was applied to actual paper keywords to derive the high-dimensional keyword label space and the low-dimensional latent label space. Using this, we conducted an experiment to predict the compressed keyword vector existing in the latent label space from the paper abstract and to evaluate the multi-label classification by restoring the predicted keyword vector back to the original label space. As a result, the accuracy, precision, recall, and F1 score used as performance indicators showed far superior performance in multi-label classification based on the proposed methodology compared to traditional multi-label classification methods. This can be seen that the low-dimensional latent label space derived through the proposed methodology well reflected the information of the high-dimensional label space, which ultimately led to the improvement of the performance of the multi-label classification itself. In addition, the utility of the proposed methodology was identified by comparing the performance of the proposed methodology according to the domain characteristics and the number of dimensions of the latent label space.

• 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.