• Title/Summary/Keyword: Principal Component Factor

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Anthropometry for Clothing Construction and the Factorial Structure Analysis (II) (피복구성학적 인체계측과 요인구조분석 (II) - 여자고교생을 중심으로 -)

  • 김구자
    • Journal of the Korean Home Economics Association
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    • v.20 no.4
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    • pp.83-89
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    • 1982
  • The purpose of this study was to analyze the 45 measuring items for the clothing construction in order to observe the factorial structure of items and to extract the common factor and the special unique factor from data. The sample for the study was drawn randomly out of senior high schoolgirls in Seoul urban area. The size of sample was 301 girls between age 16 and 18. The method of analysis was applied by the principal component analysis with orthogonal rotation after extraction of 9 major factors. All of the above data was analyzed by the computer installed at Seoul National University. From these analyses, the major findings can be summerized as follows: 1. The results of factor analysis generally indicated that the first factor was clustered with 15 items, length measures and height measures. The eigenvalue of the first factor was 16.5 and the cumulative percentage of variables 36.6%. 2. The second factor was clustered with width measures, girth measures and weight of 19 items. The eigenvalue of the second factor was 6.5 and the cumulative percentage of variables 51.0%.

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Development of Work Stress Measurement Tool for Academic Librarians (대학도서관 사서의 직무스트레스 측정 도구 개발)

  • Lee, Jong Yoon;Cho, Hyun Yang
    • Journal of the Korean Society for Library and Information Science
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    • v.47 no.3
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    • pp.181-205
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    • 2013
  • The purpose of this study is to develop a job-stress scale for librarians who work in university libraries. The study was first conducted by analyzing existing representative job-stress scales that are used domestically and internationally. To understand the characteristic of particular job stress that academic librarians have, the in-depth interview among qualitative research methods was selected, and 15 librarians who work at a 4-year system university libraries participated in this study. Based on the results of the questionnaire survey, the reliability and validity were verified. To analyze the validity, exploratory factor analysis was carried out. To extract factors, principal component analysis was used. To extract factors, principal component analysis was used. For the rotation method, a varimax rotation was applied. A tertiary measurement tool with a total of 46 questions for 11 factors was developed after removing measurement questions that were rejected as a result of the analysis. As a result of factor analysis on the tertiary measurement tool, 11 factors were extracted. Those 11 factors include 'peer relation conflict factor(factor 1)', 'superior-subordinate relation conflict factor (factor 2)', 'work compensation evaluation factor(factor 3)', 'emotional labor factor(factor 4)', 'physical environmental factor(factor 5)', 'employment stability(factor 6)', 'job demand factor(psychological) (factor 7)', 'decision-making and responsibility factor(factor 8)', 'work complexity factor(factor 9)', 'work boundary conflict factor(factor 10)', and 'job demand factor(physical)(factor 11)'.

Performance Improvement of General Regression Neural Network Using Principal Component Analysis (주요성분분석에 의한 일반회귀 신경망의 성능개선)

  • Cho, Yong-Hyun
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.11
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    • pp.3408-3416
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    • 2000
  • This paper proposes an efficient method for improving the performance of a general regression neural network by using the feature to the independent variables as the center for partern-layer neurons. The adaptive principal component analysis is applied for extracting, efficiently the fcarures by reducing the dimension of given independent variables. In can acluevc a supertor property of the principal component analysis that converts input data into set of statistically independent features and the general regression neuralnetwork, espedtively. The proposed general regression neural network has been applied to regress the Solow's economy(2-independent variable set) and the wie elephone(1-independent vanable set). The simulation results show that the proposed meural networks have better performances of the regressionfor the lest data, in comparison with those using the means or the weighted means of independent variables. Also,it is affected less by the number of neurons and the scope of the smoothing factor.

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The Performance Advancement of Power Analysis Attack Using Principal Component Analysis (주성분 분석을 이용한 전력 분석 공격의 성능 향상)

  • Kim, Hee-Seok;Kim, Hyun-Min;Park, Il-Hwan;Kim, Chang-Kyun;Ryu, Heui-Su;Park, Young-Ho
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.20 no.6
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    • pp.15-21
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    • 2010
  • In the recent years, various researches about the signal processing have been presented to improve the performance of power analysis. Among these signal processing techniques, the research about the signal compression is not enough than a signal alignment and a noise reduction; even though that can reduce considerably the computation time for the power analysis. But, the existing compression method can sometimes reduce the performance of the power analysis because those are the unsophisticated method not considering the characteristic of the signal. In this paper, we propose the new PCA (principal component analysis)-based signal compression method, which can block the loss of the meaningful factor of the original signal as much as possible, considering the characteristic of the signal. Also, we prove the performance of our method by carrying out the experiment.

Factor Analysis of Genetic Evaluations For Type Traits of Canadian Holstein Sires and Cows

  • Ali, A.K.;Koots, K.R.;Burnside, E.B.
    • 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.

Seasonal Variation and Statistical Analysis of Particulate Pollutants in Urban Air (도시대기립자상물질중 오염성분의 계절적 변동 및 통계적 해석)

  • 이승일
    • Journal of environmental and Sanitary engineering
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    • v.9 no.2
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    • pp.8-23
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    • 1994
  • During the period from Mar., 1991 to Feb., 1992 66 tSP samples were collected by Hi volume air sampler at 1 sampling site in Seoul and the amount of concentration of 21 components(SO$_{4}$$^{2-}$, NO$_{3}$$^{-}$, NH$_{4}$$^{+}$, Cl$^{-}$, Al, Ba, Ca, Cd, Cr, Cu, Fe, It Mg, Mn, Na, Ni, Pt Si, Ti, Zn, Zr ) were measured. And monthly and seasonal variation were surveyed and the principal component analysis( PCA ) were carried out with respect to these amount of pollutants, minimum of visibility and radiation on a horizontal surface. The total amount of soluble ion in water was high in order o(SO$_{4}$$^{2-}$> NO$_{3}$$^{-}$> N%'>Cl$^{-}$ and metal ion was high in order of Na> Ca>Si> Fe> Al> K> Mg> Zn> Pb> Cu>Ti> Mn > Ba> Cr> Zr> Ni> Cd. There was Seasonal variation in concentration for SO$_{4}$$^{2-}$, NH$_{4}$$^{+}$, Cl$^{-}$, Na, Al, Ca, Bt Mg, Fe and Si. It was assumed that the components of the highest concentration on April were depend on yellow sand and the frequency of wind velocity and direction. As the results of PCA, the amount of pollution components was able to characterized with two principal components(Z$_{1}$, Z$_{2}$ ). The first principal components Z$_{1}$ was considered to be a factor indicating the pollutants originated from natural generation and The second principal components Z$_{2}$ was considered to be a factor indicating the pollutants originated from human work. The monthly concentration of pollutants in ISP, minimum of visibility and radiation on a horizontal surface was possible to evaluate by the use of these two principal components Z$_{1}$ and Z$_{2}$ .

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An Analytical Study on Stem Growth of Chamaecyparis obtusa (편백(扁栢)의 수간성장(樹幹成長)에 관(關)한 해석적(解析的) 연구(硏究))

  • An, Jong Man;Lee, Kwang Nam
    • Journal of Korean Society of Forest Science
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    • v.77 no.4
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    • pp.429-444
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    • 1988
  • Considering the recent trent toward the development of multiple-use of forest trees, investigations for comprehensive information on these young stands of Hinoki cypress are necessary for rational forest management. From this point of view, 83 sample trees were selected and cut down from 23-ear old stands of Hinoki cypress at Changsung-gun, Chonnam-do. Various stem growth factors of felled trees were measured and canonical correlaton analysis, principal component analysis and factor analysis were applied to investigate the stem growth characteristics, relationships among stem growth factors, and to get potential information and comprehensive information. The results are as follows ; Canonical correlation coefficient between stem volume and quality growth factor was 0.9877. Coefficient of canonical variates showed that DBH among diameter growth factors and height among height growth factors had important effects on stem volume. From the analysis of relationship between stem-volume and canonical variates, which were linearly combined DBH with height as one set, DBH had greater influence on volume growth than height. The 1st-2nd principal components here adopted to fit the effective value of 85% from the pincipal component analysis for 12 stem growth factors. The result showed that the 1st-2nd principal component had cumulative contribution rate of 88.10%. The 1st and the 2nd principal components were interpreted as "size factor" and "shape factor", respectively. From summed proportion of the efficient principal component fur each variate, information of variates except crown diameter, clear length and form height explained more than 87%. Two common factors were set by the eigen value obtained from SMC (squared multiple correlation) of diagonal elements of canonical matrix. There were 2 latent factors, $f_1$ and $f_2$. The former way interpreted as nature of diameter growth system. In inherent phenomenon of 12 growth factor, communalities except clear length and crown diameter had great explanatory poorer of 78.62-98.30%. Eighty three sample trees could he classified into 5 stem types as follows ; medium type within a radius of ${\pm}1$ standard deviation of factor scores, uniformity type in diameter and height growth in the 1st quadrant, slim type in the 2nd quadrant, dwarfish type in the 3rd quadrant, and fall-holed type in the 4 th quadrant.

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Estimation of Source Contribution of Particulate Matter in Taegu Area using Factor Analysis (다변량 통계분석법을 이용한 대구지역 부유분진의 오염원 기여도 추정)

  • 최성우;송형도
    • Journal of Environmental Health Sciences
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    • v.26 no.4
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    • pp.1-8
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    • 2000
  • The objective of this study was to identify the sources and to estimate the source contributions to the atmospheric TSP(total suspended particulate matter) and PM-10(particulate matter with aerodynamic diameters less than 10$\mu\textrm{m}$) concentration in Taegu area. A total of 84 samples was collected during the January to December 1999. TSP and PM-10 were collected on filters by portable air sampler, and heavy metals in TSP and PM-배 were analyzed by ICO(Inductively Coupled Plasma Spectrometery) after preliminary treatment. The results were follow as : First, annual average of TSP and PM-10 concentration was 123 and 69$\mu\textrm{g}$/㎥ respectively. The concentration of TSP and PM-10 were highest in winter season compared to other seasons. Second, the concentration of Al, Fe, Mn were higher in TSP than in PM-10, indicating that these heavy metals are generally associate with natural contributions. Third, metal combinations showed that a high correlation among concentrations of heavy metals were follows: As Al, Fe and Mn in TSP ; Ni, Cr, Cd and Pb in PM-10. Finally, Statistical analysis was performed using Principal Components Analysis(PCA) in order to find possible sources of the pollutants. The factor analysis was permitted to identify four major sources(soil/road dust resuspension, waste incineration, furl combustion, vehicular emission) in each fraction. These source accounted for at least 83, 85% of variance of TSP and PM-10 concentration in Taegu area.

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A Study on Forest Land Classification Using Multivariate Statistical Methods : A Case Study at Mt. Kwanak (다변수통계방법을 이용한 산지분류에 관한 연구)

  • 정순오
    • Journal of the Korean Institute of Landscape Architecture
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    • v.13 no.1
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    • pp.43-66
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    • 1985
  • Korea needs proper and rational public policies on conservation and use of forest land and other natural resources because of the accelerating expansion of national land developments in recent years. Unfortunately, there is no systematic planning system to support the needs. Generally, forest land use planning needs suitability analysis based on efficient land classification system. The goal of this study was to classify a forest land using multivariate satistical methods. A case study was carried out in winter of 1983 on a mountainous area higher than 100m above sea level located at Mt. Kwanak in Anyang -city, Kyung-gi-do (province). The study area was 19.80 km$^2$wide and was divided into 1, 383 Operational Taxonomic Units (OTU's) by a 120m$\times$120m grid. Fourteen descriptors were identified and quantified for each OTU from existing national land data : elevation, slope, aspect, terrain form, geologic material, surface soil permeability, topsoil type, depth of the solum, soil acidity, forest cover type, stand size class, stand age class, stand density class, and simple forest soil capability class. For this study, a FORTRAN IV program was written for input and output map data, and the computer statistics packages, SPSS and BMD, were used to perform the multivariate statistical analysis. Fourteen variables were analyzed to investigate the characteristics of their fire quench distribution and to estimate the correlation coefficients among them. Principal component analysis was executed to find the dimensions of forest land characteristics, and factor scores were used for proper samples of OTU throughout the study area. In order to develop the classes of forest land classification based on 102 surrogates, cluster and discriminant analyses of principal descriptor variable matrix were undertaken. Results obtained through a series of multivariate statistical analyses were as follows ; 1) Principal component analysis was proved to be a useful tool for data selection and identification of principal descriptor variables which represented the characteristics of forest land and facilitated the selection of samples.

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Characteristics of Water Quality and factor Analysis on the Variations of Water Quality in Coastal Sea around the Keum River Estuary in Summer (하계 금강하구 주변해역의 수질특성과 수질변동 요인분석)

  • Kwon Jung-No;Kim Jong-Gu;You Sun-Jae
    • Journal of the Korean Society for Marine Environment & Energy
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    • v.3 no.4
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    • pp.3-22
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    • 2000
  • To know characteristics of water quality in coastal sea around the Keum river estuary in summer, we studied the water quality of surface, middle and bottom level during Jun e~september, 1998. The mean concentrations of COD, DIN, DIP & chlorophyll-a were 1.36mg/L, 28.60㎍-at/L, 0.48㎍-at/L and 4.14㎍/L, respectively, which were over eutrophication criteria in sea water. After the Keum river dyke was constructed, seasonal freshwater discharge was largely changed. About 80% of total annual freshwater discharge was concentrated in summer as rainy season from July to September. The correlation coefficient of DIN versus salinity was shown to be high, and thus the concentration of DIN was closely related to freshwater discharge. Maximum Chlorophyll-a concentration was occurred in September, due to increased DIP concentration, high water temperature and low salinity after heavy rainfall in August. The results of Principal Component Analysis showed that the first factor represented a series of eutrophication factors, the second factor w3s a valiance of seasonal fluctuation, and the third was a variance of progress of mass change.

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