• Journal of Korean Society on Water Environment
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• v.39 no.1
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• pp.9-19
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• 2023

Drought is a natural disaster that can have serious social impacts. Drought's impact ranges from water supply for humans to ecosystems, but the impact of drought on river water quality requires careful investigation. In general, drought occurs meteorologically and is classified as agricultural drought, hydrological drought, and environmental drought. In this study, the BOD environmental drought is defined using the bivariate copula joint probability distribution model between the meteorological drought index and the river BOD, and based on this, the environmental drought condition index (EDCI-BOD) was proposed. The results of examining the proposed index using past precipitation and BOD observation data showed that EDCI-BOD expressed environmental drought well in terms of river BOD water quality. In addition, by classifying the calculated EDCI-BOD into four levels, namely, 'attention', 'caution', 'alert', and 'seriousness', a practical monitoring stage for environmental drought of BOD was constructed. We further estimated the sensitivity of the stream BOD to meteorological drought, and through this, we could identify the stream section in which the stream BOD responded relatively more sensitively to the occurrence of meteorological drought. The results of this study are expected to provide information necessary for river BOD management in the event of meteorological droughts.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.23-29
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• 2015

In this study, the spatial relevance between the regional housing price data and the spatial distribution of the location-based social media data is explored. The spatial analysis with rasterization was applied to this study, because the both data have a different form to analyze. The geo-tagged Twitter data had been collected for a month and the regional housing price index about sales and lease were used. The spatial range of both data includes Seoul and the some parts of the metropolitan area. 2,000m grid was constructed to consider the different spatial measure between two data, and they were combined into the constructed grids. The Hotspot Analysis was operated using the combined dataset to see the comparison of spatial distribution, and the bivariate spatial correlation coefficients between two data were measured for the quantitative analysis. The result of this study shows that Seocho-gu area is detected as a common hotspot of tweet and housing sales price index data. though the spatial relevance is not detected between tweet and housing lease price index data.

• Korean Journal of Plant Taxonomy
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• v.41 no.4
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• pp.329-337
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• 2011

The Acer wilsonii complex including A. wilsonii, A. tutcheri, and A. confertifoilum is distributed in southern China. Morphological variation was examined to delimit the species and to determine whether recognition at the specific level was warranted. Univariate and bivariate statistical methods, based on data taken from herbarium specimens, were used to examine morphological variation between and within species. This study showed that A. tutcheri differed from A. wilsonii by its rather short inflorescence, small leaf blades, and three leaf lobes with distinctive serrate leaf lobes. In contrast, there was virtually no separation of taxa with respect to the paniculate-corymbose or short paniculate inflorescence between A. confertifolium and A. tutcheri, suggesting that A. confertifolium morphologically resembled A. tutcheri and is a rather smaller form of it. Circumscription of Acer wilsonii has been quite troublesome, because the important holotype and isotype specimens contained different species under the same number and were misleading with respect to the correct application of the name. Furthermore, lobation is very weak within ser. Sinensia, but diversified inflorescences usually occur in China. A three lobed leaves species, A. wilsonii, represents the reduction in lobation without any modification of panicle inflorescences and seems to be closely related to A. sinense. However, A. tutcheri, which shows a reduction in panicle inflorescence with four petals and sepals, may not be closely related to A. sinense. Three lobed taxa may not correctly reflect the true relationship within ser. Sinensia. The designated lectotype of A. wilsonii, line drawings of representative leaves of related species, a key, and distribution maps of these taxa are presented.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1201-1212
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• 2016

Value at Risk (VaR) for market risk management is a favorite method used by financial companies; however, there are some problems that cannot be explained for the amount of loss when a specific investment fails. Conditional Tail Expectation (CTE) is an alternative risk measure defined as the conditional expectation exceeded VaR. Multivariate loss rates are transformed into a univariate distribution in real financial markets in order to obtain CTE for some portfolio as well as to estimate CTE. We propose multivariate CTEs using multivariate quantile vectors. A relationship among multivariate CTEs is also derived by extending univariate CTEs. Multivariate CTEs are obtained from bivariate and trivariate normal distributions; in addition, relationships among multivariate CTEs are also explored. We then discuss the extensibility to high dimension as well as illustrate some examples. Multivariate CTEs (using variance-covariance matrix and multivariate quantile vector) are found to have smaller values than CTEs transformed to univariate. Therefore, it can be concluded that the proposed multivariate CTEs provides smaller estimates that represent less risk than others and that a drastic investment using this CTE is also possible when a diversified investment strategy includes many companies in a portfolio.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.473-480
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• 2005

We can obtain useful information by deploying large scale sensor networks in various situations. Security is also a major concern in sensor networks, and we need to establish pairwise keys between sensor nodes for secure communication. In this paper, we propose new pairwise key establishment mechanism based on clustering and polynomial sharing. In the mechanism, we divide the network field into clusters, and based on the polynomial-based key distribution mechanism we create bivariate Polynomials and assign unique polynomial to each cluster. Each pair of sensor nodes located in the same cluster can compute their own pairwise keys through assigned polynomial shares from the same polynomial. Also, in our proposed scheme, sensors, which are in each other's transmission range and located in different clusters, can establish path key through their clusterheads. However, path key establishment can increase the network overhead. The number of the path keys and tine for path key establishment of our scheme depend on the number of sensors, cluster size, sensor density and sensor transmission range. The simulation result indicates that these schemes can achieve better performance if suitable conditions are met.

• Journal of Periodontal and Implant Science
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• v.36 no.3
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• pp.591-600
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• 2006

Purpose: This study assessed the impact of self-reported periodontal health on the oral health-related quality of life among elderly Koreans. Methods: Four hundred twenty one elderly Koreans in Seoul and suburban areas were selected with a cluster (institution) sampling method, and were requested to take oral examinations and finish questionnaires on the Oral Health Impact Profile-14(OHIP-14). and self-reported periodontal health status, such as periodontal symptoms, self-rated periodontal health and periodontal treatment need. As the dependent variable, OHIP-14 showed a positive skewed distribution (skewness: 1.17), we transformed to square-root form to apply parametric analyses. Bivariate analysis by t-test and ANOVA, and multivariate analysis with the two-level regression model accounting clusters were implemented. Results: Mean age of the subjects was 74.6 years and 66.5% were women. Fourteen items of OHIP-14 were summarized to one factor explaining 78.6% of total variance and produced the Chronbach alpha coefficient of 0.92. Results from the multivariate model, adjusting for age, sex, type of institutions, ability to pay, and number of teeth present, showed significantly lower OHIP-14 with reporting less than 3 periodontal symptoms (p(O.OOO1), rating their own periodontal health as above average level (p=O.0144), and thinking they don't need any periodontal treatments in the near future (p=O.0148), than their counterparts. The intraclass-corrrelation estimated by the final model was 0.028. Conclusion: This study demonstrates a significant association between self-reported periodontal health status and the oral health-related quality of life.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.252-266
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• 2019

The purpose of this study was to identify the type of health behaviors in Korean adults and to identify related factors. The data used in the analysis was the Korea Health and Nutrition Examination Survey 2014., which was representative of the Korean population. Cluster analysis was used to find the pattern of clustering of smoking, drinking, exercising and nutrition. Differences in the pattern of clustering was examined, first by bivariate chi-square test, and then by multinomial logit regression. Lastly, the association between the clusters of health behaviors and other behavioral risk factors was tested by chi-square test and logistic regression. The distribution of the clusters varied not only across socioeconomic characteristics and local size, but also between individuals with certain chronic diseases and those without. The results of this study can be used as a basis for the usefulness of approaching the cluster rather than individually approaching the health behavior.

• Economic and Environmental Geology
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• v.55 no.4
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• pp.353-366
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• 2022

Spatial estimation of geoscience data (geo-data) is challenging due to spatial heterogeneity, data scarcity, and high dimensionality. A novel spatial estimation method is needed to consider the characteristics of geo-data. In this study, we proposed the application of Gaussian Mixture Model (GMM) among machine learning algorithms with multivariate data for robust spatial predictions. The performance of the proposed approach was tested through soil chemical concentration data from a former smelting area. The concentrations of As and Pb determined by ex-situ ICP-AES were the primary variables to be interpolated, while the other metal concentrations by ICP-AES and all data determined by in-situ portable X-ray fluorescence (PXRF) were used as auxiliary variables in GMM and ordinary cokriging (OCK). Among the multidimensional auxiliary variables, important variables were selected using a variable selection method based on the random forest. The results of GMM with important multivariate auxiliary data decreased the root mean-squared error (RMSE) down to 0.11 for As and 0.33 for Pb and increased the correlations (r) up to 0.31 for As and 0.46 for Pb compared to those from ordinary kriging and OCK using univariate or bivariate data. The use of GMM improved the performance of spatial interpretation of anthropogenic metals in soil. The multivariate spatial approach can be applied to understand complex and heterogeneous geological and geochemical features.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.157-175
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• 2021

This study categorized 3,214 companies out of the tech firms supported by the Korea Technology Finance Corporation's "technology guarantee scheme" through technology assessment from 2017 to 2019 into Fourth Industrial Revolution-related companies and general SMEs. The impact of the management characteristics of these 1,752 tech firms on the determination of high-growth firms was then empirically analyzed. This study used the OECD(2007) definition to define a "high-growth firm" as "an enterprise with average revenue growth greater than 20% per annum, over a two-year period." As the two sample groups showed non-normal distribution, this study conducted the Mann-Whitney U test, a nonparametric test, to analyze the mean differences and bivariate logistic regression in which the normality assumption is less stringent. The independent variables include fundamental characteristics; a regional dummy; a technological level dummy; and the capabilities of company representatives, human capital, and technological innovation. The corresponding sub-variables are representatives' level of education and experience in the same industry, full-time workers, research personnel, the extent of intellectual property rights, investment in research and development, firm age, total assets, region_metropolitan area, region_central region, technological level_high technology, and technological level_medium technology. As a result, the research hypothesis about representatives' level of experience in the same industry, full-time workers, total assets, and technological level_high technology was supported for the Fourth Industrial Revolution-related companies. For the general SMEs, the research hypothesis about representatives' level of experience in the same industry, research personnel, total assets, and region_metropolitan area was supported.