• Asian-Australasian Journal of Animal Sciences
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• v.31 no.2
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• pp.167-179
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• 2018

Objective: The aim of this study was to create a set of microsatellite markers with high polymorphism for the genetic monitoring and genetic structure analysis of local goose populations. Methods: Novel microsatellite markers were isolated from the genomic DNA of white Roman geese using short tandem repeated probes. The DNA segments, including short tandem repeats, were tested for their variability among four populations of geese from the Changhua Animal Propagation Station (CAPS). The selected microsatellite markers could then be used to monitor genetic variability and study the genetic structures of geese from local geese farms. Results: 14 novel microsatellite loci were isolated. In addition to seven known loci, two multiplex sets were constructed for the detection of genetic variations in geese populations. The average of allele number, the effective number of alleles, the observed heterozygosity, the expected heterozygosity, and the polymorphism information content were 11.09, 5.145, 0.499, 0.745, and 0.705, respectively. The results of analysis of molecular variance and principal component analysis indicated a contracting white Roman cluster and a spreading Chinese cluster. In white Roman populations, the CAPS populations were depleted to roughly two clusters when K was set equal to 6 in the Bayesian cluster analysis. The founders of private farm populations had a similar genetic structure. Among the Chinese geese populations, the CAPS populations and private populations represented different clads of the phylogenetic tree and individuals from the private populations had uneven genetic characteristics according to various analyses. Conclusion: Based on this study's analyses, we suggest that the CAPS should institute a proper breeding strategy for white Roman geese to avoid further clustering. In addition, for preservation and stable quality, the Chinese geese in the CAPS and the aforementioned proper breeding scheme should be introduced to geese breeders.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.2
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• pp.10-17
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• 2011

The paradigm of the use and management of natural resources is changing. Wise use of natural resources can be achieved by enhancing their conservation value and, at the same time, taking them as an opportunity for regional development. It leads to an idea of pursuing regional development by making good use of natural resources. In this paper, natural resources were classified as living species resources, ecosystem and landscape resources, and non-living resources. The resources were divided into 27 detailed analysis indices. The administrative boundaries of 165 municipalities in Korea were defined as spatial analysis units. Finally, a spatial database of natural resources was built. To classify the regional types, we conducted factor analyses with a detailed index of natural resources and a cluster analysis with the factor value. As the result of the factor analysis, six factors have been deduced as follows: forest resources, landscape resources, coastal ecology resources, inland water resources, landform resources, and ecology visit resources. In addition, the cluster analyses were conducted for the points of the factors drawn. The final classification consists of nine groups, and appropriate methods for each regional development have been suggested. Results of this study will contribute to providing fundamental materials for site selection and objective-setting for regional development policies and planning in consideration of natural resources.

• The Korean Journal of Applied Statistics
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• v.22 no.4
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• pp.745-758
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• 2009

Cluster analysis is the automated search for groups of related observations in a data set. To group the observations into clusters many techniques has been proposed, and a variety measures aimed at validating the results of a cluster analysis have been suggested. In this paper, we compare complete linkage, Ward's method, K-means and model-based clustering and compute validity measures such as connectivity, Dunn Index and silhouette with simulated data from multivariate distributions. We also select a clustering algorithm and determine the number of clusters of Korean consumers based on Korean consumers' palatability scores for Hanwoo bull in BBQ cooking method.

• Journal of Veterinary Clinics
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• v.28 no.4
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• pp.422-426
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• 2011

For a national survey in which wide geographic region or an entire country is targeted, multi-stage sampling approach is widely used to overcome the problem of simple random sampling, to consider both herd- and animallevel factors associated with disease occurrence, and to adjust clustering effect of disease in the population in the calculation of sample size. The aim of this study was to establish sample size for estimating bovine tuberculosis (TB) in Korea using stratified two-stage sampling design. The sample size was determined by taking into account the possible clustering of TB-infected animals on individual herds to increase the reliability of survey results. In this study, the country was stratified into nine provinces (administrative unit) and herd, the primary sampling unit, was considered as a cluster. For all analyses, design effect of 2, between-cluster prevalence of 50% to yield maximum sample size, and mean herd size of 65 were assumed due to lack of information available. Using a two-stage sampling scheme, the number of cattle sampled per herd was 65 cattle, regardless of confidence level, prevalence, and mean herd size examined. Number of clusters to be sampled at a 95% level of confidence was estimated to be 296, 74, 33, 19, 12, and 9 for desired precision of 0.01, 0.02, 0.03, 0.04, 0.05, and 0.06, respectively. Therefore, the total sample size with a 95% confidence level was 172,872, 43,218, 19,224, 10,818, 6,930, and 4,806 for desired precision ranging from 0.01 to 0.06. The sample size was increased with desired precision and design effect. In a situation where the number of cattle sampled per herd is fixed ranging from 5 to 40 with a 5-head interval, total sample size with a 95% confidence level was estimated to be 6,480, 10,080, 13,770, 17,280, 20.925, 24,570, 28,350, and 31,680, respectively. The percent increase in total sample size resulting from the use of intra-cluster correlation coefficient of 0.3 was 22.2, 32.1, 36.3, 39.6, 41.9, 42.9, 42,2, and 44.3%, respectively in comparison to the use of coefficient of 0.2.

• Environmental Analysis Health and Toxicology
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• v.29
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• pp.5.1-5.7
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• 2014

Objectives Numerous studies have revealed the adverse health effects of acute and chronic exposure to particulate matter less than $10{\mu}m$ in aerodynamic diameter ($PM_{10}$). The aim of the present study was to examine the spatial distribution of $PM_{10}$ concentrations and cardiovascular mortality and to investigate the spatial correlation between $PM_{10}$ and cardiovascular mortality using spatial scan statistic (SaTScan) and a regression model. Methods From 2008 to 2010, the spatial distribution of $PM_{10}$ in the Seoul metropolitan area was examined via kriging. In addition, a group of cardiovascular mortality cases was analyzed using SaTScan-based cluster exploration. Geographically weighted regression (GWR) was applied to investigate the correlation between $PM_{10}$ concentrations and cardiovascular mortality. Results An examination of the regional distribution of the cardiovascular mortality was higher in provincial districts (gu) belonging to Incheon and the northern part of Gyeonggi-do than in other regions. In a comparison of $PM_{10}$ concentrations and mortality cluster (MC) regions, all those belonging to MC 1 and MC 2 were found to belong to particulate matter (PM) 1 and PM 2 with high concentrations of air pollutants. In addition, the GWR showed that $PM_{10}$ has a statistically significant relation to cardiovascular mortality. Conclusions To investigate the relation between air pollution and health impact, spatial analyses can be utilized based on kriging, cluster exploration, and GWR for a more systematic and quantitative analysis. It has been proven that cardiovascular mortality is spatially related to the concentration of $PM_{10}$.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.3
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• pp.357-364
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• 2014

In this work, we construct a CPU cluster to implement a parallel finite-difference time domain(FDTD) algorithm for fast electromagnetic analyses. This parallel FDTD algorithm can reduce the computational time significantly and also analyze electrically larger structures, compared to a single FDTD counterpart. The parallel FDTD algorithm needs communication between neighboring processors, which is performed by the MPI(Message Passing Interface) library and a 3-D domain decomposition is employed to decrease the communication time between neighboring processors. Compared to a single-processor FDTD, the speed up factor of a-CPU-cluster-based parallel FDTD algorithm is investigated for the normal mode and the hypermode and finally analyze an electrically large concrete structure by the developed parallel algorithm.

• The Journal of Korean Association of Computer Education
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• v.7 no.1
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• pp.151-165
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• 2004

The purpose of the study was to explore the potential of the Cluster Analysis and the Community Analysis of Social Network Analyses family in job-task analysis for curriculum design. These two multivariate analysis techniques were expected to bring us relevant and scientific information as well as inspiration in investigating the structure and nature of job system, which are critical in developing relevant curriculum. To pursue the purpose mentioned above, qualitative and quantitative data were collected from "S" Corporate, a major large high-tech manufacturing company, and analyzed by relevant analytic procedures. Results indicate that there are discrepancies between formal job structures and actual ones. Following Community analysis showed that the presence of center-marginal structure along with clustering structure in the current job formation. Interpretations of the results of the study are provided in light of past research and additional data collected from the study. Implications of the study are also discussed along with suggestions for future research.

• Journal of Environmental Science International
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• v.26 no.8
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• pp.927-938
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• 2017

This study was conducted to determine correlations and similarity between the ozone and $PM_{10}$ data of 19 air quality monitoring stations in Busan from 2013 to 2016, using correlation and cluster analyses. Ozone concentrations ranged from $0.0278{\pm}0.0148ppm$ at Gwangbok to $0.0378{\pm}0.017ppm$ at Taejongdae and were high in suburban areas, such as Yongsuri and Gijang, as well as in coastal areas, such as Jaw, Gwangan, Taejongdae and Noksan. $PM_{10}$ concentrations ranged from $37.2{\pm}25.0ug/m^3$ at Gijang to $58.3{\pm}32.2ug/m^3$ at and Jangrim. $PM_{10}$ concentrations were high in the west, exceeding the annual ambient air quality standard of $50ug/m^3$. Positive correlations were observed for ozone at most stations, ranging from 0.61 between Taejongdae and Sujeong to 0.92 between Bugok and Myeongjang. The correlation coefficients of $PM_{10}$ between stations ranged from 0.62 between Jangrim and Jaw to 0.9 between Gwangbok and Sujeong. Yeonsan, Daeyeon, and Myeongjang were highly correlated with other stations, so they needed to be reviewed for redundancy. Ozone monitoring stations were initially divided into two sections, north-western areas and suburban-coastal areas. The suburban-coastal areas were subsequently divided into three sections. $PM_{10}$ monitoring stations were initially divided into western and remaining areas, and then the remaining areas were subsequently divided into three sections.

• Fashion & Textile Research Journal
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• v.18 no.5
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• pp.606-616
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• 2016

We intend an empirical assessment of examining the differences in the appearance management behaviors and demographic variables among groups classified by the clothing consumption values. The questionnaires are administered to 493 female and male adults above 20 years old in Seoul, Gyeonggi-do, Daegu and Kyungpook regions. For analysis of data from 478 respondents, descriptive statistics, cluster analysis, Cronbach's ${\alpha}$, ANOVA, Duncan test and ${\chi}^2$ test were applied. We show the following results. First, Factor analyses were employed for the clothing consumption values and appearance management behaviors. Six factors were for clothing consumption values: Individuality, appearance attractive, social, functional, conditional and fashion clothing consumption value. Four factors were for appearance management behaviors: weight training, skin care, hair care, make-up and clothing selection. According to clothing consumption values, four groups were classified: the passive, functional, social, and active group. We did cluster analysis to the appearance management behaviors of weight training, skin care, hair care, make-up and clothing selection. Second, the social and active groups were more interested in individuality, appearance attractive, social, functional, conditional and fashion clothing value. And they were also more involved in appearance management behaviors. Third, among the demographic variables, the single and female in 20s and 30s with higher level of education belonged to the active group. In this contribution, we find significant differences in the appearance management behavior and demographic variables classified by the clothing consumption values.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.70-83
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• 2018

Korea's five leading industries-chemical, automobile, shipbuilding, metal and electronics-have been the growth engines of the Korean economy for the last 30 years. However, with their performance weakening in the past few years, Korea's annual growth rate has dropped to less than 2%. Just as the Japanese economy struggled through the lost decades, Korea's leading industries have been facing signals of arriving at a Strategic Inflection Point ("SIP") since the mid-2000s. The objective of this study is to present an appropriate value strategy for Korean firms in leading industries to gain sustainable competitive advantages. This paper examines the following issues : First, it diagnoses the signs and timing of SIP for the five leading industries. Second, this study examines 78 Korean and Japanese firms in order to understand the adaptation strategies of the highest and lowest performing firms from a value strategy point of view. Third, it empirically analyzes the correlation between the indicators of value strategy and the accounting performances of the Korean and Japanese firms. The data set used in the cluster analysis were collected from KISLINE database of NICE Information Service and annual reports. The findings in the case analyses of high and low performing companies show that high value-added specialty chemical materials and electronic component manufacturers that had a strong focus on value creation were defined as high performing companies. And in the cosmetic and automobile industries, companies with a strong emphasis on value appropriation gained high performance. Furthermore, the study conducted a cluster analysis based on two indicators R&D and advertisement expense. The analysis shows that a significant gap exists in the operating incomes among three groups classified under the value strategy. The study recommends that Korean firms are requested to increase R&D expenditure, conduct M&A and collaborate with companies that own source technologies to narrow the technology gap and improve their segment portfolio from commodity to value-added products.