• The Korean Journal of Zoology
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• v.24 no.2
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• pp.91-98
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• 1981

It has been confirmed that two dendrograms resulted from two similarity matrices, average taxonomic distance and correlation coefficient matrices, are different with each other when cluster analyses were performed with 571 adults of deer mice, Peromyscus maniculatus using 30 morphometric characters. To choose one of two similarity matrices mentioned above in order to construct a dendrogram representing phenetic relationships among taxa, an objective method using the result from principal component analysis as a standard result to compare with two matrices has been suggested.

• Journal of the Korea Safety Management & Science
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• v.11 no.3
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• pp.41-48
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• 2009

The risk assessment for heavy metal pollutions were analyzed by using statistical techniques including correlation and cluster analyses. The contamination data in this investigation obtained were from the Chungcheongnam-do abandoned mines. The descriptive statistical analysis showed that the values of Pb and Zn were relatively higher than other heavy metal values. The detection of heavy metals by distance from abandoned mines within 1,000m were mostly As, Cd, Pb, and Zn. It was noted, especially, that Zn was even detected at 4,000m The results of coefficient correlation showed that Zn to Cd was the highest values. The cluster and dendogram analyses were generated. The results showed the two clear groups by heavy metal characteristics.

• Journal of the Korea Safety Management & Science
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• v.12 no.2
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• pp.231-236
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• 2010

The investigation was initiated with data from 27 abandoned mines along with 12 locations in Kyongbuk abandoned mines. The analyses for soil pollution by heavy metal pollutants were conducted by using correlation analysis, cluster analysis, and principal component analysis. The correlation analysis indicated that Ni and pH were highly correlated compared to those of other heavy metal ions. The principal component analyses showed that the heavy metal ions might be classified into two catagories, such as antropogenic and lithogenic components. The cluster analysis was also clearly divided by two groups. The respective two groups might be Pb-Zn-Cd-Cu and As-Hg-Ni.

• Korean Journal of Ecology and Environment
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• v.50 no.3
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• pp.325-336
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• 2017

The ecosystem in the Gwangju Stream has taken a wide range of disturbance such as the discharging water of sewage treatment plant, the lake water and the river water from different water system over the past decade. This study was figured out some significant influence factors by analyzing the relationship between biotic and abiotic factors in the urban stream. Abiotic components included 15 water quality variables which were measured in five sampling sites along the stream from October 2014 to July 2015, whereas the benthic macroinvertebrates found in those sites were used to estimate various biotic indices representing the ecological status of the community. The results of correlation analyses indicated that abiotic factors by human activities affected on the inhabitation of benthic macroinvertebrates more than biotic factors. The results of cluster analyses and ANOVA tests also showed that biotic and abiotic characteristics were clearly different in season. The main influence factors of cluster analysis by sites were $NH_3-N$, EPT(I) and DO. It was considered that more various statistical analyses would be necessary to find some different relationships and influence factors between biotic and abiotic variables in the urban stream.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.8
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• pp.1141-1149
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• 2018

Objective: Cluster of differentiation 4 protein (CD4) gene is an important immune related gene which plays a significant role in T cell development and host resistance during viral infection. Methods: In order to unravel the relationship of CpG island methylation level of CD4 gene with its gene expression and T lymphocyte subpopulation traits, we used one typical Chinese indigenous breed (Dapulian, DP) and one commercial breed (Landrace), then predicted the CpG island of CD4 gene, determined the methylation status of CpG sites by bisulfite sequencing polymerase chain reaction (BSP), and carried out the correlation analyses of methylation frequencies of CpG sites with mRNA expression and T lymphocyte subpopulation traits. Results: There was one CpG island predicted in the upstream -2 kb region and exon one of porcine CD4 gene, which located 333 bp upstream from the start site of gene and contained nine CpG sites. The correlation analysis results indicated that the methylation frequency of CpG_2 significantly correlated with CD4 mRNA expression in the DP and Landrace combined population, though it did not reach significance level in DP and Landrace separately. Additionally, 15 potential binding transcription factors (TFs) were predicted within the CpG island, and one of them (Jumonji) contained CpG_2 site, suggesting that it may influence the CD4 gene expression through the potential binding TFs. We also found methylation frequency of CpG_2 negatively correlated with T lymphocyte subpopulation traits CD4+CD8-CD3-, CD4-CD8+CD3- and CD4+/CD8+, and positively correlated with CD4-CD8+CD3+ and CD4+CD8+CD3+ (for all correlation, p<0.01) in DP and Landrace combined population. Thus, the CpG_2 was a critical methylation site for porcine CD4 gene expression and T lymphocyte subpopulation traits. Conclusion: We speculated that increased methylation frequency of CpG_2 may lead to the decreased expression of CD4, which may have some kind of influence on T lymphocyte subpopulation traits and the immunity of DP population.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.4
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• pp.515-533
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• 2012

Industrial cluster is adopted as a key policy for the development of regional and national economies in many developed or under-developing countries. The industrial cluster is basically concerned with knowledge sharing and exchanges among diverse functions such as firms, research institutions, and universities in a regional or innovation-network context. Therefore, activities to promote knowledge sharing and exchanges in an industrial cluster become very important activities to reach to the original purpose of an industrial cluster. In this study, factors affecting performance of those activities to promote knowledge sharing and exchanges in an industrial cluster are defined and the effects are examined through empirical study. For this research, surveys on enterprisers and employees in industrial cluster were conducted and statistical analysis methods such as correlation analysis, multiple regression analysis, and canonical correlation analysis were adopted for analyses.

• Asian Journal of Atmospheric Environment
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• v.4 no.1
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• pp.9-19
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• 2010

The size distribution of airborne particulate matter (PM) and the concentrations of associated metallic elements were investigated in a busy urban region of a typical Korean industrial city. The PM concentrations measured during the spring, except for those in the size range of 1.1 to 2.1 ${\mu}m$, were slightly higher than the PM concentrations in the summer. Coarse particles contributed greatly to the variation in PM concentrations in the spring, while fine and submicron particles contributed largely to the variation in PM concentrations in the summer. The difference in size modes of the PM concentrations between spring and summer may be explained by the Asian dust effect and its accompanying wind direction and speed. Extremely high enrichment factors (EFs) values (6,971 to 60,966) for all of the size distributions in PM were identified for cadmium (Cd). High EFs values (12 to 907) were also identified for other heavy metals including Cr, Cu, Ni, Pb, Zn and Mn. Low EF values (0.29 to 8.61) were identified for Ca, K, Mg and Na. These results support the common hypothesis that most heavy metals in ambient PM have anthropogenic sources and most light metals have crustal sources. The results of principal components analyses and cluster analyses for heavy metals indicate that the principal sources of PM and metals were emissions from non-ferrous metal smelters, oil combustion, incinerators, vehicular traffic and road dust.

• 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.

• Korean Journal of Human Ecology
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• v.20 no.6
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• pp.1135-1151
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• 2011

This study examined green consumption behavior according to the lifestyles of college students. The data were collected from 314 college students in Yeungnam region by a self-administered questionnaire. Frequencies, Cronbach's alpha, factor analysis, cluster analysis, chi-square tests, one-way analysis of variance, Duncan's multiple range tests, Pearson's correlation analysis, and multiple regression analyses were conducted by SPSS Windows V.18.0. According to the result of factor analysis, lifestyles were categorized into six factors: thrift-saving type, enthusiastic activity type, brand ostentation type, freedom-seeking type, material oriented type, and practice-seeking type. Cluster analysis showed respondents belonged to one of four groups: thrift practice group, indifference group, freedom-seeking group, and material ostentation group. The levels of green purchase behavior, green usage behavior and green disposal behavior of the respondents was not high. The thrift practice group showed higher levels of green purchase behavior, green usage behavior, and green disposal behavior. Finally, according to multiple regression analyses, environmental consciousness, knowledge about green consumption, lifestyle groups were the significant factors affecting green consumption behaviors. These results imply that green consumption education for college students should be activated to induce green life.

• Journal of Families and Better Life
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• v.6 no.1
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• pp.223-249
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• 1988

The aim of this study is to classify the life styles of urban housewives, to see their correlation with demographic and socioeconomic variables, and finally to provide some useful for their ideal home management. This study has been based on a questionnaire on the demographic characteristics of housewives, and their life styles. The selected samples were 650 and 514 of them were analyzed. The data wee analyzed by factor analysis, cluster analysis, ANOVA, Duncan test and X2-test. As a result of factor and cluster analyses of 64 items th life styles of urban housewives were classified into 5 types; 'conservative stagnant type', 'sound and thrifty type', 'passive stagnant type', realistic and stable type', modern and evolutional type', The life styles of the respondents showed significant differences by the variables of age , family life cycles, the number of family members, the number of children, family type, education, occupation, income, the type of housing, and religion.