• Atmosphere
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• v.22 no.2
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• pp.149-161
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• 2012

Going by the research results of the past, of all the uncertainties resulting from the research on climate change, the uncertainty caused by the climate change scenario has the highest degree of uncertainty. Therefore, depending upon what kind of climate change scenario one adopts, the projection of the water resources in the future will differ significantly. As a matter of principle, it is highly recommended to utilize all the GCM scenarios offered by the IPCC. However, this could be considered to be an impractical alternative if a decision has to be made at an action officer's level. Hence, as an alternative, it is deemed necessary to select several scenarios so as to express the possible number of cases to the maximum extent possible. The objective standards in selecting the climate change scenarios have not been properly established and the scenarios have been selected, either at random or subject to the researcher's discretion. In this research, a new scenario selection process, in which it is possible to have the effect of having utilized all the possible scenarios, with using only a few principal scenarios and maintaining some of the uncertainties, has been suggested. In this research, the use of cluster analysis and the selection of a representative scenario in each cluster have efficiently reduced the number of climate change scenarios. In the cluster analysis method, the K-means clustering method, which takes advantage of the statistical features of scenarios has been employed; in the selection of a representative scenario in each cluster, the selection method was analyzed and reviewed and the PDF method was used to select the best scenarios with the closest simulation accuracy and the principal scenarios that is suggested by this research. In the selection of the best scenarios, it has been shown that the GCM scenario which demonstrated high level of simulation accuracy in the past need not necessarily demonstrate the similarly high level of simulation accuracy in the future and various GCM scenarios were selected for the principal scenarios. Secondly, the "Maximum entropy" which can quantify the uncertainties of the climate change scenario has been used to both quantify and compare the uncertainties associated with all the scenarios, best scenarios and the principal scenarios. Comparison has shown that the principal scenarios do maintain and are able to better explain the uncertainties of all the scenarios than the best scenarios. Therefore, through the scenario selection process, it has been proven that the principal scenarios have the effect of having utilized all the scenarios and retaining the uncertainties associated with the climate change to the maximum extent possible, while reducing the number of scenarios at the same time. Lastly, the climate change scenario most suitable for the climate on the Korean peninsula has been suggested. Through the scenario selection process, of all the scenarios found in the 4th IPCC report, principal climate change scenarios, which are suitable for the Korean peninsula and maintain most of the uncertainties, have been suggested. Therefore, it is assessed that the use of the scenario most suitable for the future projection of water resources on the Korean peninsula will be able to provide the projection of the water resources management that maintains more than 70~80% level of uncertainties of all the scenarios.

• Journal of Korea Port Economic Association
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• v.31 no.1
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• pp.1-14
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• 2015

The standard GARCH model imposing symmetry on the conditional variance, tends to fail in capturing some important features of the data. This paper, hence, introduces the models capturing asymmetric effect. They are the EGARCH model and the GJR model. We provide the systematic comparison of volatility models focusing on the asymmetric effect of news on volatility. Specifically, three diagnostic tests are provided: the sign bias test, the negative size bias test, and the positive size bias test. This paper shows that there is significant evidence of GARCH-type process in the data, as shown by the test for the Ljung-Box Q statistic on the squared residual data. The estimated unconditional density function for squared residual is clearly skewed to the left and markedly leptokurtic when compared with the standard normal distribution. The observation of volatility clustering is also clearly reinforced by the plot of the squared value of residuals of export volume and values. The unconditional variance of both export volumes and export value indicates that large shocks of either sign tend to be followed by large shocks, and small shocks of either sign tend to follow small shocks. The estimated export volume news impact curve for the GARCH also suggests that $h_t$ is overestimated for large negative and positive shocks. The conditional variance equation of the GARCH model for export volumes contains two parameters ${\alpha}$ and ${\beta}$ that are insignificant, indicating that the GARCH model is a poor characterization of the conditional variance of export volumes. The conditional variance equation of the EGARCH model for export value, however, shows a positive sign of parameter ${\delta}$, which is contrary to our expectation, while the GJR model exhibits that parameters ${\alpha}$ and ${\beta}$ are insignificant, and ${\delta}$ is marginally significant. That indicates that the asymmetric volatility models are poor characterization of the conditional variance of export value. It is concluded that the asymmetric EGARCH and GJR model are appropriate in explaining the volatility of export volume, while the symmetric standard GARCH model is good for capturing the volatility.

• The Korean Journal of Financial Management
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• v.24 no.3
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• pp.91-131
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• 2007

In the paper, the effects of sidecar on index arbitrage trading and non-index arbitrage trading in the Korean stock market are examined. The analyses of return, volatility, and liquidity dynamics illustrate that there are no distinct differences for index arbitrage group and non-index arbitrage group surrounding the sidecar events. For further analysis, we construct pseudo-sidecar sample and analyse the effects of the actual sidecar and pseudo-sidecar on arbitrage sample and non-index arbitrage sample. The result of analysis using pseudo-sidecar shows that the differences between index arbitrage group and non-index arbitrage group are larger in pseudo-sidecar sample than in actual sidecar sample. This means that former results can be explained by temporary order clustering in one side before and after the event. Sidecar has little effect on non-index arbitrage group, however, it has relatively large effect on arbitrage group. These results imply that it needs to redesign the sidecar system of the Korean stock market which applies for all program trading including arbitrage and non-index arbitrage trading.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.1
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• pp.42-62
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• 2012

This paper suggests a genuine method to estimate the agglomeration effects of Industrial Cluster focusing on the FOODPOLIS (KOREA NATIONAL FOOD CLUSTER). In this study, we will focus on two issues related to the clustering effect. First, Clusters affect productivity, and a cluster allows companies to operate more productively in inputs; accessing technology, human resource, information, services, and needed institutions. Second, we assume that the effects of Industrial Cluster can be estimated from measurement on differency of an added value between large-scale enterprises and smaller ones. To demonstrate effectiveness of this approach, the estimated effect was compared with that from the related study (A Mini-Cluster). Industry Clusters have been considered as critical factors for regional competitiveness and economic revitalization. For this, the government and local government should find a way and strategy to provide useful contents that can attract the participation of firms and to secure strategic positioning and competition strategies.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.25-33
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• 2016

In order to visualize point based Location-Based Social Network Services(LBSNS) data on multi-scaled tile map effectively, it is necessary to apply tile-based clustering method. Then determinating reasonable numbers and size of tiles is required. However, there is no such criteria and the numbers and size of tiles are modified based on data type and the purpose of analysis. In other words, researchers' subjectivity is always involved in this type of study. This is when Modifiable Areal Unit Problem(MAUP) occurs, that affects the results of analysis. Among LBSNS, geotagged Twitter data were chosen to find the influence of MAUP in scale effects perspective. For this purpose, the degree of spatial autocorrelation using spatial error model was altered, and change of distributions was analyzed using Morna's I. As a result, positive spatial autocorrelation showed in the original data and the spatial autocorrelation was decreased as the value of spatial autoregressive coefficient was increasing. Therefore, the intensity of the spatial autocorrelation of Twitter data was adjusted to five levels, and for each level, nine different size of grid was created. For each level and different grid sizes, Moran's I was calculated. It was found that the spatial autocorrelation was increased when the aggregation level was being increased and decreased in a certainpoint. Another tendency was found that the scale effect of MAUP was decreased when the spatial autocorrelation was high.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.59-67
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• 2019

Most of the prior researches in brand extension evaluation have utilized purchase intention as a n effective variable to assess the effectiveness of brand extensions. In contrast, the author proposes that trial intention is to better predict consumers' behavioral response in the newly launched brand extension markets where relate to high risk and uncertainty. Furthermore, the study explores the effects of attitude toward parent brand and consumers' characteristics (perceived similarity and consumption experience) on trial intention of brand extensions. In order to achieve the purpose of the study, the data collection was conducted for actual consumers who had experience using parent brand products. This study employed experiment and questionnaire survey and collected data of 186 was analyzed using clustering analysis and regression analysis. The main results are as follows. First, attitude toward parent brand has a positive effect on trial intention of the extensions. Second, perceived similarity and consumption experience of parent brand have moderating effects on the relation of attitude toward parent brand and trial intention of brand extensions. The results provide that both industry and academic researchers with a guide to process trial intention of brand extension from a comprehensive perspective.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.45-67
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• 2017

According to the Internet Usage Research performed in 2016, the number of internet users and the internet usage have been increasing. Smartphone, compared to the computer, is taking a more dominant role as an internet access device. As the number of smart devices have been increasing, some views that the demand on high-speed internet will decrease; however, Despite the increase in smart devices, the high-speed Internet market is expected to slightly increase for a while due to the speedup of Giga Internet and the growth of the IoT market. As the broadband Internet market saturates, telecom operators are over-competing to win new customers, but if they know the cause of customer exit, it is expected to reduce marketing costs by more effective marketing. In this study, we analyzed the relationship between the cancellation rates of telecommunication products and the factors affecting them by combining the data of 3 cities, Anyang, Gunpo, and Uiwang owned by a telecommunication company with the regional data from KOSIS(Korean Statistical Information Service). Especially, we focused on the assumption that the neighboring areas affect the distribution of the cancellation rates by coupling type, so we conducted spatial cluster analysis on the 3 types of cancellation rates of each region using the spatial analysis tool, SatScan, and analyzed the various relationships between the cancellation rates and the regional data. In the analysis phase, we first summarized the characteristics of the clusters derived by combining spatial information and the cancellation data. Next, based on the results of the cluster analysis, Variance analysis, Correlation analysis, and regression analysis were used to analyze the relationship between the cancellation rates data and regional data. Based on the results of analysis, we proposed appropriate marketing methods according to the region. Unlike previous studies on regional characteristics analysis, In this study has academic differentiation in that it performs clustering based on spatial information so that the regions with similar cancellation types on adjacent regions. In addition, there have been few studies considering the regional characteristics in the previous study on the determinants of subscription to high-speed Internet services, In this study, we tried to analyze the relationship between the clusters and the regional characteristics data, assuming that there are different factors depending on the region. In this study, we tried to get more efficient marketing method considering the characteristics of each region in the new subscription and customer management in high-speed internet. As a result of analysis of variance, it was confirmed that there were significant differences in regional characteristics among the clusters, Correlation analysis shows that there is a stronger correlation the clusters than all region. and Regression analysis was used to analyze the relationship between the cancellation rate and the regional characteristics. As a result, we found that there is a difference in the cancellation rate depending on the regional characteristics, and it is possible to target differentiated marketing each region. As the biggest limitation of this study and it was difficult to obtain enough data to carry out the analyze. In particular, it is difficult to find the variables that represent the regional characteristics in the Dong unit. In other words, most of the data was disclosed to the city rather than the Dong unit, so it was limited to analyze it in detail. The data such as income, card usage information and telecommunications company policies or characteristics that could affect its cause are not available at that time. The most urgent part for a more sophisticated analysis is to obtain the Dong unit data for the regional characteristics. Direction of the next studies be target marketing based on the results. It is also meaningful to analyze the effect of marketing by comparing and analyzing the difference of results before and after target marketing. It is also effective to use clusters based on new subscription data as well as cancellation data.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.111-124
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• 2010

To monitor the environment of land surface change is considered as an important research field since those parameters are related with land use, climate change, meteorological study, agriculture modulation, surface energy balance, and surface environment system. For the change detection, many different methods have been presented for distributing more detailed information with various tools from ground based measurement to satellite multi-spectral sensor. Recently, using high resolution satellite data is considered the most efficient way to monitor extensive land environmental system especially for higher spatial and temporal resolution. In this study, we use two different spatial resolution satellites; the one is SPOT/VEGETATION with 1 km spatial resolution to detect coarse resolution of the area change and determine objective threshold. The other is Landsat satellite having high resolution to figure out detailed land environmental change. According to their spatial resolution, they show different observation characteristics such as repeat cycle, and the global coverage. By correlating two kinds of satellites, we can detect land surface change from mid resolution to high resolution. The K-mean clustering algorithm is applied to detect changed area with two different temporal images. When using solar spectral band, there are complicate surface reflectance scattering characteristics which make surface change detection difficult. That effect would be leading serious problems when interpreting surface characteristics. For example, in spite of constant their own surface reflectance value, it could be changed according to solar, and sensor relative observation location. To reduce those affects, in this study, long-term Normalized Difference Vegetation Index (NDVI) with solar spectral channels performed for atmospheric and bi-directional correction from SPOT/VEGETATION data are utilized to offer objective threshold value for detecting land surface change, since that NDVI has less sensitivity for solar geometry than solar channel. The surface change detection based on long-term NDVI shows improved results than when only using Landsat.

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.1
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• pp.54-63
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• 2010

Baicalin, a flavonoid, was shown to have diverse effects such as anti-inflammatory, anti-cancer, anti-viral, anti-bacterial and others. Recently, we found that the baicalin inhibits adipogenesis through the modulations of anti-adipogenic and pro-adipogenic factors of the adipogenesis pathway. In the present study, we further characterized the molecular mechanism of the anti-adipogenic effect of baicalin using microarray technology. Microarray analyses were conducted to analyze the gene expression profiles during the differentiation time course (0 day, 2 day, 4 day and 7 day) in 3T3-L1 cells with or without baicalin treatment. We identified a total of 3972 genes of which expressions were changed more than 2 fold. These 3972 genes were further analyzed using hierarchical clustering analysis, resulting in 20 clusters. Four clusters among 20 showed clearly up-regulated expression patterns (cluster 8 and cluster 10) or clearly down-regulated expression patterns (cluster 12 and cluster 14) by baicalin treatment for over-all differentiation period. The cluster 8 and cluster 10 included many genes which enhance cell proliferation or inhibit adipogenesis. On the other hand, the cluster 12 and cluster 14 included many genes which are related with proliferation inhibition, cell cycle arrest, cell growth suppression or adipogenesis induction. In conclusion, these data provide detailed information on the molecular mechanism of baicalin-induced inhibition of adipogenesis.

• Journal of Crop Science and Biotechnology
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• v.11 no.1
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• pp.51-56
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• 2008

Azuki bean has never been commercially grown in Thailand, due in part to a lack of suitable varieties. A core collection of 114 azuki bean accessions, originally from different parts of China(northern, central, southern) representing the germplasm of Chinese land races, were evaluated in the experimental field of the Institute of Vegetable Crops, Jiangsu Academy of Agricultural Sciences, China from June to October 2004. The same experiment was repeated at Kamphaeng Saen campus of Kasetsart University, Thailand from February to May 2005. Yield, yield components, and agronomic traits were recorded in all accessions in order to identify certain genotypes for further investigation. The statistical parameters that were used as indicators of phenotypic variation were mean, coefficient of variability(CV), correlation coefficient(r), range, mean difference, and phenotypic clustering of the accessions. The results indicated that the azuki bean varieties planted in Kamphaeng Saen were shorter, earlier in growing duration, and lower in plant height, seed yield per plant, 100-seed weight, and pods per plant as compared to when they were grown in China. This discrepancy was caused largely by the combined effect of temperature, rainfall, and day length. The traits that were rather stable in both locations were branches per plant and seeds per pod. Azuki bean varieties from northern China showed higher response to the changing environments compared with those from central and southern China. Some agronomic traits showed high correlation coefficient between the environments in Thailand and China. The CV of agronomic traits in both locations were ranked in descending order as follows: seed yield per plant, pods per plant, branches per plant, plant height, 100-seed weight, seeds per pod, and growing duration. The CV of seeds per pod and branches per plant were almost the same in both locations. Yield per plant in China correlated well(r=0.75) with pods per plant, but not with the other traits. Based on their response to both environments, the azuki bean accessions can be broadly divided into four groups, viz. northern 1, northern 2, central, and southern. This implied that there was more diversity, but probably less stability among the accessions originating from northern China.