• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.539-551
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• 2004

Multiple responses are often observed in many application fields, such as customer's time-of-day pattern for using internet. Some decision trees for multiple responses have been constructed by many researchers. However, if the response is a high-dimensional vector that can be thought of as a discretized function, then fitting a multivariate decision tree may be unsuccessful. Yu and Lambert (1999) suggested spline tree and principal component tree to analyze high dimensional response vector by using dimension reduction techniques. In this paper, we shall propose factor tree which would be more interpretable and competitive. Furthermore, using Korean internet company data, we will analyze time-of-day patterns for internet user.

• Journal of Korean Society for Quality Management
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• v.33 no.2
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• pp.1-12
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• 2005

An extensive literature review has been made in this paper to build the evaluation hierarchy structure for the certification of electronic commerce services. In building the evaluation hierarchy structure, major candidate evaluation factors are selected by bench marking the various certification practices, including the Malcolm Baldrige award, ISO9000, and BSC(balanced scorecard) techniques. This paper deployed principal component analysis and factor analysis techniques to develop a statistically solid and systematic evaluation model. The final evaluation model, as presented in this paper as a model for the certification of electronic commerce services, produces a numeric score on the 100% scale, which can be served as a metric for the certification decision. The AHP technique was used in converting the various qualitative and quantitative evaluation values into a single measure for the certification decision.

• 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

• ETRI Journal
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• v.32 no.6
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• pp.921-931
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• 2010

It has been shown that the principal subspace-based multichannel Wiener filter (MWF) provides better performance than the conventional MWF for suppressing interference in the case of a single target source. It can efficiently estimate the target speech component in the principal subspace which estimates the acoustic transfer function up to a scaling factor. However, as the input signal-to-interference ratio (SIR) becomes lower, larger errors are incurred in the estimation of the acoustic transfer function by the principal subspace method, degrading the performance in interference suppression. In order to alleviate this problem, a principal subspace modification method was proposed in previous work. The principal subspace modification reduces the estimation error of the acoustic transfer function vector at low SIRs. In this work, a frequency-band dependent interpolation technique is further employed for the principal subspace modification. The speech recognition test is also conducted using the Sphinx-4 system and demonstrates the practical usefulness of the proposed method as a front processing for the speech recognizer in a distant-talking and interferer-present environment.

• The Journal of Fisheries Business Administration
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• v.14 no.2
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• pp.1-14
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• 1983

This paper considers a classification of the 88 islands located at Kyong-nam area in Korea, using by examples of 12 components of the islands. By means of principal component analysis 2 principle components were extracted, which explained a total of 73.7% of the variance. Using an eigen variable criterion (λ>1), no further principle components were discussed. Principal component 1 and 2 explained 63.4% and 10.3% of the total variance respectively, The representation of the unrelated factor scores along the first and second principal axes produced a new information with respect to the classification of the islands. Based upon the representation, 88 islands were classified into 6 groups i. e. A, B, C, D, E, and F according to similarity of the components among them in this paper. The "Group F" belongs to a miscellaneous assortment that does not fit into the logical category. category.

• Advances in environmental research
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• v.6 no.1
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• pp.53-65
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• 2017

Assessment of seasonal changes in surface water quality is an important aspect for evaluating temporal variations of river pollution due to natural or anthropogenic inputs of point and non-point sources. In this study, surface water quality data for 15 physico-chemical parameters collected from 7 monitoring stations in a river during the years from 2014 to 2016 were analyzed. The principal component analysis technique was employed to evaluate the seasonal correlations of water quality parameters, while the principal factor analysis technique was used to extract the parameters that are most important in assessing seasonal variations of river water quality. Analysis shows that a parameter that is most important in contributing to water quality variation for one season may not be important for another season except alkalinity, which is always the most important parameters in contributing to water quality variations for all three seasons.

• Journal of Wetlands Research
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• v.21 no.3
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• pp.215-223
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• 2019

In this study, we analyzed the water quality characteristics of major tributaries of Nakdong River through statistical analysis such as correlation analysis, principal component and factor analysis, and cluster analysis. Organic matter and nutrients are highly correlated, and are high in spring and autumn, and seasonal water quality management is required. Principal component and factor analysis showed that 82% of total variance could be explained by 4 principal components such as organic matter, nutrients, nature, and weather. BOD, COD, TOC, and TP items were analyzed as major influencing factors. As a result of the cluster analysis, the four clusters were classified according to seasonal organic matter and nutrient pollution. Kumho River watershed showed high pollution characteristics in all seasons. Therefore, effective management of water quality in tributary streams requires measures in consideration of spatio-temporal characteristics and multivariate statistical techniques may be useful in water quality management and policy formulation.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.44 no.3
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• pp.207-213
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• 1999

Thirty-eight glutinous rice varieties were classified into nine groups on the scatter diagram by the upper two principal components (56% contribution to the total information) based on eleven physicochemical characteristics including the viscograms and physical properties of cooked rice. The first principal component was the factor mainly associated with the viscogram characteristics of rice flour emulsion and the second was the factor chiefly related to the physical properties of cooked rice and water absorbability of rice grain. Indica glutinous rices were clearly distinguished from japonica ones by the first principal component score. Javanica glutinous rices were widely distributed on the intermediate zone between indica and japonica or on several japonica rice groups. Significant positive or negative correlations were found among water absorption rates of rice grain, physical properties of cooked rice, and viscogram characteristics of rice flour. Especially in japonica glutinous rices, the breakdown and setback viscosities of rice flour were closely associated with the alkali digestion value of milled rice and the stickiness of cooked rice. The frequency ratio of short glucose chains (A-chain) to intermediate glucose chains (B-chain), the ratio of B- chains to long glucose chains (C-chain) and the relative frequency of A- or B-chain fractions representing the amylopection structure of rice starch was closely associated with the breakdown and setback viscosities of rice flour.

• Fashion & Textile Research Journal
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• v.12 no.1
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• pp.80-85
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• 2010

The purpose of this study was to examine the characteristics of armscye circumference which will be used to develop total contents for the apparel industry. The subjects of this study were 16- to 49-year-old women whose 3D body shape data were analyzed. 72 length and length-ratio measurements were taken to each subject' armscye circumference. The used analysis methods are descriptive statistics, principal component analysis, and cluster analysis. The results are follows; 1. Considering the Length of armscye circumference, the result of principal component analysis were extracted 3 factors and those factors comprised 95% of total variance. As the result of the cluster analysis of factor scores, subjects were classified into 4 cluster by their size characteristic. 2. Considering the length-ratio of armscye circumference, the result of principal component analysis were extracted 5 factors and those factors comprised 96.45% of total variance. As the result of the cluster analysis of factor scores, subjects were classified into 5 cluster by their shape characteristic. So that, this research could be useful to manufacture garment which reflected 3D body figure and improved fitting.

• Journal of Environmental Health Sciences
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• v.33 no.4
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• pp.299-305
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• 2007

Distribution of fecal pollution indicator bacteria and environmental parameter were investigated of urban artificial lakes. An average concentration of temperature, pH, SS, DO, $COD_{Mn}$, T-P, T-N, Turbidity, Chl-a were $21.5^{\circ}C$, 8.07, 116.70 mg/l, 8.66 mg/l, 2.24 mg/1, 0.52 mg/l, 1.71mg/l, 80.54 NTU, and 52.12 mg/l respectively. From the results of bivariate correlation analysis, fecal contamination indicator bacteria were found to be mutually correlated. And turbidity and suspended solid were correlated. From the results of principal component analysis, four factors were extracted. And four factors of variance explained up to 81.5 percentage. Factor 1 was pollution pattern by fecal contamination, factor 2 was physical pollution pattern by pollution source, factor 3 was natural pollution by precipitation, and factor 4 was artificial pollution pattern by organism.