• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2002.04a
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• pp.110-113
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• 2002

Statistical- based, principal component analysis (PCA) was applied to chemical data from two underground storage systems containing LPG to assess the usefulness of such technique at the initial stage (Pyeongtaek) or middle stage (Ulsan) of hydrochemical studies. For the first case, both natural and anthropogenic contamination characterize regional groundwater. Saline water buffered by Namyang lake affects as a natural factor, whereas cement grouting influence as an artificial factor. For the second study area, contaminations due to operation of LPG caverns, such as disinfection activity and cement grouting effect, deteriorate groundwater quality. This study indicates that principal component analysis would be particularly useful for summarizing large data set for the purpose of subsurface characterization, assessing their vulnerability to contamination and protecting recharge zones.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.2
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• pp.465-472
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• 2016

Principal Component Analysis (PCA) is useful statistical technique for finding patterns in data, and expressing the data in such a way as to highlight their similarities and differences. In this paper, 1417 marine casualties occurred in Korean littoral sea in recent 5 years, were examined by the PCA. The main results obtained were as follows : 1. Most of marine casualties resulted from the human factors such as careless operation and insufficient engine maintenance. 2. Collision and standing mainly resulted from steering room-related human factors such as careless guard, inadequate ship-handling, however engine damage and fire explosion mainly resulted from engine room-related human factor such as bad handling of engine system. 3. No. 1 principal component represents accident frequency, No. 2 principal component represents the cause and No. 3 principal component represents the pattern of marine casualties, respectively.

• Journal of Environmental Impact Assessment
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• v.23 no.3
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• pp.187-196
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• 2014

The objective of this study is to evaluate and analyze Osu stream watershed water environment system. The data were collected from January 2009 to December 2011 including water temperature, pH, DO, EC, BOD, COD, TOC, SS, T-N, T-P and discharge. The data were used for principle component analysis and factor analysis. The results are as followes. The primary factors obtained from both the principal component analysis and the factor analysis were BOD, COD, TOC, SS and T-P. Once principal component analysis and factor analysis have been performed with the collected data and then the results will be applied to both simple regression model and multiple regression model. The regression model was developed into case 1 using concentrations of water quality parameters and case 2 using delivery loads. The value of the coefficient of determination on case 1 fell between 0.629 and 0.866; this was lower than case 2 value which fell between 0.946 and 0.998. Therefore, case 2 model would be a reliable choice.The coefficient of determination between the estimated figure using data which was developed to the regression model in 2012 and the actual measurement value was over 0.6, overall. It can be safely deduced that the correlation value between the two findings was high. The same model can be applied to get TOC concentrations in future.

• Journal of Ecology and Environment
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• v.38 no.2
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• pp.145-156
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• 2015

This study was based on water quality data of the Lake Doam watershed, monitored from 2010 to 2013 at eight different sites with multiple physiochemical parameters. The dataset was divided into two sub-datasets, namely, non-rainy and rainy. Principal component analysis (PCA) and factor analysis (FA) techniques were applied to evaluate seasonal correlations of water quality parameters and extract the most significant parameters influencing stream water quality. The first five principal components identified by PCA techniques explained greater than 80% of the total variance for both datasets. PCA and FA results indicated that total nitrogen, nitrate nitrogen, total phosphorus, and dissolved inorganic phosphorus were the most significant parameters under the non-rainy condition. This indicates that organic and inorganic pollutants loads in the streams can be related to discharges from point sources (domestic discharges) and non-point sources (agriculture, forest) of pollution. During the rainy period, turbidity, suspended solids, nitrate nitrogen, and dissolved inorganic phosphorus were identified as the most significant parameters. Physical parameters, suspended solids, and turbidity, are related to soil erosion and runoff from the basin. Organic and inorganic pollutants during the rainy period can be linked to decayed matters, manure, and inorganic fertilizers used in farming. Thus, the results of this study suggest that principal component analysis techniques are useful for analysis and interpretation of data and identification of pollution factors, which are valuable for understanding seasonal variations in water quality for effective management.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.2
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• pp.71-78
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• 2016

The study of water environment system in Changnyeong-Haman weir section using a statistical analysis has been conducted. Statistical analyses used in this study were the correlation analysis, the principal components, and the factor analysis. The purpose of the study is to establish better understanding of relationships between water quality factors in the Changnyeong-Haman weir section which can provide useful information to manage Nakdong river. According to correlation analyses on COD and TOC, it revealed that the value of correlation coefficient was 0.844. Furthermore, the results from the principal component analysis categorized the water quality factors into three factor groups, the first principal factor group included COD, TOC, BOD, pH, water temperature (WT). And, it was observed that the concentration of cyanobacteria in the water body decreased, while the concentrations of the diatoms and the green algae increased after the events of rainfall.

• Journal of Biosystems Engineering
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• v.34 no.2
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• pp.114-119
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• 2009

Field test was conducted to investigate primary factors reducing rapeseed harvesting using a reciprocating cutter-bar of combine. The results showed that the correlation between crop moisture content and yield loss had a U-type, which indicated that the yield reduction increased at too high and too low crop moisture contents. The proper ranges of crop moisture contents were 27${\sim}$35%, 21${\sim}$56%, and 62${\sim}$73% in case of grain, pod and stem, respectively. Crop moisture content was negatively correlated with header loss, but positively correlated with threshing loss. In contrary, stem moisture content showed positive correlations with total loss, threshing loss and separation loss. Working speed was positively correlated with header loss. Total flow rate, pod flow rate and stem flow rate were highly correlated with threshing loss and separation loss. However, grain flow rate did not show any correlation with total loss. According to the principal component analysis, two principal components were derived as components with eigenvalues greater than 1.0. The contribution rates of the first and the second components were 52.7% and 38.9%, which accounted for 91.6% of total variance. As a contributive factor influencing total loss of rapeseed mechanical harvesting, a crop moisture content factor was greater than a crop flow rate factor. The stepwise multiple regression analysis for total loss was conducted using crop moisture content factor, crop flow rate factor and coefficient. However, the model did not show any correlation among independent and dependent factors ($R^2$=0.060).

• Journal of the Korean Home Economics Association
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• v.36 no.12
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• pp.43-54
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• 1998

From the viewpoint of clothing construction, it is necessary to grasp exactly the shapes of the neck and the shouder, such as the line of the neck base, the neck gradient, the shoulder gradient, the shape of the scapular, and the shape of the breast. In this report, factor analysis was applied to 39 items of neck & shoulder level measurements, including stature, weight, but grith, waist girth, to demonstrate the most relevant measurements for collar and bodice pattern designing, and to classify the neck and shoulder level shapes. The subjects investigated were 126 women of the age 20-29. The main results are follows : 1. For factors of body form were extracted by the factor analysis. The 1st principal component can be interpreted as "size" component, the 2nd-3th principal component is "shape" component relating to neck and shoulder level, and the 4th principal component is "shoulder shape" component. 2. With regard to factor loadings, we were able to extract the most relevant measurements for collar and bodice pattern designing. M16, M22, S26, S30, S34, S35, S36, C37, C38, C39.

• Journal of Soil and Groundwater Environment
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• v.7 no.3
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• pp.19-32
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• 2002

This study is objected to identify the relations between surface- and shallow ground-water and the seasonal variation of their qualities in watersheds near Muju area. The water type shows mainly Ca-$HCO_3$type. Heavy-metal contamination of surface water is locally detected, due to the mixing with mine drainage. In October nitrate concentration is especially high in densely populated area. Cluster Analysis and Principal Component Analysis are implemented to interpret the complexity of the chemical variation of surface- and ground-water with large amount of chemical data. Based on the cluster analysis, surface-water was divided into five groups and ground-water into three groups. Principal Component Analysis efficiently supports the result of cluster analysis, allowing the identification of three main factors controlling the water quality. There are (1) hydrogeochemical factor, (2) anthropogenic factor and (3) heavy metal contaminated by mine drainage.

• Proceedings of the ESK Conference
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• 1996.10a
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• pp.225-231
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• 1996

The purpose of this study is providing basic information to make torso and original design of clothing of the old. Grasping the body of the old was advanced and made specific types. The objects of this study are 320 people whose age is 60 .approx. 85 and we extracted forming factors of a body by factor analysis about 57 items and we made types of a body by cluster analysis. Principal component analysis which is one of the basic methods in factor analysis was applied to the interpretation of anthropometric data. As a result of data are able to be decided into appropriate group

• Asian-Australasian Journal of Animal Sciences
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• v.11 no.5
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• pp.463-469
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• 1998

Factor analysis was applied as a multivariate statistical technique to official genetic evaluations of type classification traits for 1,265,785 Holstein cows and 10,321 sires computed from data collected between August 1982 and June 1994 in Canada. Type traits included eighteen linear descriptive traits and eight major score card traits. Principal components of the factor analysis showed that only five factors explain the information of the genetic value of linear descriptive traits for both cows and sires. Factor 1 included traits related to mammary system, like texture, median suspensory, fore attachment, fore teat placement and rear attachment height and width. Factor 2 described stature, size, chest width and pin width. These two factors had a similar pattern for both cows and sires. In constrast, Factor 3 for cows involved only bone-quality, while in addition for sires, Factor 3 included foot angle, rear legs desirability and legs set. Factor 4 for cows related to foot angle, set of rear leg and leg desirability, while Factor 4 related to loin strenth and pin setting for sires. Finally, Factor 5 included loin strength and pin setting for cows and described only pin setting for sires. Two factors only were required to describe score card traits of cows and sires. Factor 1 related to final score, feet and legs, udder traits, mammary system and dairy character, while frame/capacity and rump were described by Factor 2. Communality estimates which determine the proportion of variance of a type trait that is shared with other type traits via the common factor variant were high, the highest ${\geq}$ 80% for final score, stature, size and chest width. Pin width and pin desirability had the lowest communality, 56% and 37%. Results indicated shifts in emphasis over the twelve-year period away from udder traits and dairy character, and towards size, scale and width traits. A new system that computes fmal score from type components has been initiated.