• Title/Summary/Keyword: Principal Components Factor

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A Study on Road Characteristic Classification using Exploratory Factor Analysis (탐색적 요인분석을 이용한 도로특성분류에 관한 연구)

  • Cho, Jun-Han;Kim, Seong-Ho;Rho, Jeong-Hyun
    • Journal of Korean Society of Transportation
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    • v.26 no.3
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    • pp.53-66
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    • 2008
  • This research is to the establishment of a conceptual framework that supports road characteristic classification from a new point of view in order to complement of the existing road functional classification and examine of traffic pattern. The road characteristic classification(RCC) is expected to use important performance criteria that produced a policy guidelines for transportation planning and operational management. For this study, the traffic data used the permanent traffic counters(PTCs) located within the national highway between 2002 and 2006. The research has described for a systematic review and assessment of how exploratory factor analysis should be applied from 12 explanatory variables. The optimal number of components and clusters are determined by interpretation of the factor analysis results. As a result, the scenario including all 12 explanatory variables is better than other scenarios. The four components is produced the optimal number of factors. This research made contributions to the understanding of the exploratory factor analysis for the road characteristic classification, further applying the objective input data for various analysis method, such as cluster analysis, regression analysis and discriminant analysis.

The Factor Clustering of Growing Stock Changes by Forest Policy using Principal Component Analysis (주성분 분석을 이용한 산림정책별 입목축적변화의 요인 군집)

  • Shin, Hye-Jin;Kim, Eui-Gyeong;Kim, Dong-Hyeon;Kim, Hyeon-Guen
    • Journal of agriculture & life science
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    • v.46 no.2
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    • pp.1-8
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    • 2012
  • This study is a precedent study for deriving transfer function model between growing stock and forest management policies. Its goal is to solve the multicollinearity between forest works inducing growing stock changes through principal component analysis using annual time series data from 1997 to 2008. As the results, the total explanatory power showed 91.4% on the summarized 3 principal components. They were renamed 'good forest management' 'pest & insets management' 'forest fires' for conceptualization on the derived each component.

Assessment of Water Quality in the Miho Stream Using Multivariate Statistics (다변량 통계기법을 이용한 미호천 본류 수질특성 평가)

  • Yoon, Hyeyoung;Kim, Jeehyun;Chae, Minhee;Cho, Yoonhae;Cheon, Seuk
    • Journal of Environmental Impact Assessment
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    • v.28 no.4
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    • pp.373-386
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    • 2019
  • In The study, is to investigate the spatial characteristics of the Miho stream, which is the main tributary of the Geum River system, and to identify the main factors influencing the water quality using water quality analysis and multivariate analysis. The survey subjects were selected as 7 main sites in the Miho stream water system, From 2012 to 2017, 16 items including weather temperature and weather data were used for multivariate analysis. As a result of the water quality analysis, the average concentration of BOD and COD for 6 years was 3grade (normal) compared with the water quality environmental standard (river) of conditions. The concentrations of nitrogen and phosphorus were highest at th upstream site, then decreased and then increased again by the hydrogeological and geomorphological effect. Cluster analysis of spatial and water quality characteristics, it was evaluated as three clusters and the pollution sources is the greatest impact. As a result of principal component analysis and factor analysis on each cluster and mainstream, three to four major components were extracted. Main stream and the Cluster 1, Cluster 3 first principal factor included nitrogen and seasonal factors,first factor of Cluster 2 included nitrogen and water temperature. Nitrogen is the principal factor which affects water quality in Miho stream.

Accuracy of combination rules and individual effect correlation: MDOF vs SDOF systems

  • Reyes-Salazar, Alfredo;Valenzuela-Beltran, Federico;de, Leon-Escobedo, David;Bojorquez, Eden;Lopez-Barraza, Arturo
    • Steel and Composite Structures
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    • v.12 no.4
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    • pp.353-379
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    • 2012
  • The accuracy of the 30% and SRSS rules, commonly used to estimate the combined response of structures, and some related issues, are studied. For complex systems and earthquake loading, the principal components give the maximum seismic response. Both rules underestimate the axial load by about 10% and the COV of the underestimation is about 20%. Both rules overestimate the base shear by about 10%. The uncertainty in the estimation is much larger for axial load than for base shear, and, for axial load, it is much larger for inelastic than for elastic behavior. The effect of individual components may be highly correlated, not only for normal components, but also for totally uncorrelated components. The rules are not always inaccurate for large values of correlation coefficients of the individual effects, and small values of such coefficients are not always related to an accurate estimation of the response. Only for perfectly uncorrelated harmonic excitations and elastic analysis of SDOF systems, the individual effects of the components are uncorrelated and the rules accurately estimate the combined response. In the general case, the level of underestimation or overestimation depends on the degree of correlation of the components, the type of structural system, the response parameter, the location of the structural member and the level of structural deformation. The codes should be more specific regarding the application of these rules. If the percentage rule is used for MDOF systems and earthquake loading, at least a value of 45% should be used for the combination factor.

Assessment and spatial variation of water quality using statistical techniques: Case study of Nakdong river, Korea

  • Kim, Shin
    • Membrane and Water Treatment
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    • v.13 no.5
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    • pp.245-257
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    • 2022
  • Water quality characteristics and their spatial variations in the Nakdong River were statistically analyzed by multivariate techniques including correlation analysis, CA, and FA/PCA based on water quality parameters for 17 sites over 2017-2019, yielding PI values for primary factors. Site 10 indicated the highest parameter concentrations, and results of pearson's correlation analysis suggest that non-biodegradable organic matter had been distributed on the site. Five clusters were identified in order of descending pollution levels: I (Ib > Ia) > II (IIa > IIb) > III. Spatial variations started from sub-cluster Ib in which Daegu city and Geumho-river are joined. T-P, PO4-P, SS, COD, and TOC corresponded to VF 1 and 2, which were found to be principal components with strong influence on water quality. Sub-cluster Ib was strongly influenced by NO3-N and T-N compared to other clusters. According to the PIs, water quality pollution deteriorated due to non-biodegradable organic matter, nitrogen- and phosphorus-based nutrient salts in the middle and lower reaches, illustrating worsening water pollution due to inflows of anthropogenic sources on the Geumho-river, i.e., sewage and wastewater, discharged from Site 10, at which there is a concentration of urban, agricultural, and industrial areas.

Evaluation of a Traditional Korean Medicine Content Factor and Satisfaction with the Drama "Daejanggeum" (드라마 "대장금"의 한의학 콘텐츠 요소 및 만족도 평가)

  • Kim, Song-Yi;Kim, Ho-Sun;Nam, Min-Ho;Li, Yuejuan;Chung, Hung-Chiang;Park, Hi-Joon;Lee, Hye-Jung;Chae, Youn-Byoung
    • Journal of Acupuncture Research
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    • v.27 no.1
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    • pp.11-20
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    • 2010
  • Objectives : The study was performed to evaluate a traditional Korean Medicine content in drama "Daejanggeum". Methods : One hundred sixty-nine participants in Taiwan responded to the survey with 10 items, regarding components of success of drama "Daejanggeum". Principal component factor analysis and multiple regression analysis were performed to identify the possible factors to satisfaction with watching drama "Daejanggeum". Results : Factor analysis revealed that dramatic factor(44.8%), content factor(12.3%), and cultural factor(11.3%) were the most important factors to success of drama "Daejanggeum". Multiple regression analysis showed that dramatic factor(beta = .342), content factor(beta = .278), and cultural factor(beta = .131) were associated with the satisfaction with watching drama "Daejanggeum"($R^2$ = .394, with F = 32.280, p<.001). Conclusions : This study demonstrated that dramatic factor, content factor, and cultural factor are the most important factors associated with satisfaction with drama "Daejanggeum" in Taiwan. These findings suggest that a traditional Korean Medicine as a content factor would be very influential in enhancing the possibility of success of drama.

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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Pattern Recognition of the Herbal Drug, Magnoliae Flos According to their Essential Oil Components

  • Jeong, Eun-Sook;Choi, Kyu-Yeol;Kim, Sun-Chun;Son, In-Seop;Cho, Hwang-Eui;Ahn, Su-Youn;Woo, Mi-Hee;Hong, Jin-Tae;Moon, Dong-Cheul
    • Bulletin of the Korean Chemical Society
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    • v.30 no.5
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    • pp.1121-1126
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    • 2009
  • This paper describes a pattern recognition method of Magnoliae flos based on a gas chromatographic/mass spectrometric (GC/MS) analysis of the essential oil components. The botanical drug is mainly comprised of the four magnolia species (M. denudata, M. biondii, M. kobus, and M. liliflora) in Korea, although some other species are also being dealt with the drug. The GC/MS separation of the volatile components, which was extracted by the simultaneous distillation and extraction (SDE), was performed on a carbowax column (supelcowax 10; 30 m{\time}0.25 mm{\time}0.25{\mu}m$) using temperature programming. Variance in the retention times for all peaks of interests was within RSD 2% for repeated analyses (n = 9). Of the 74 essential oil components identified from the magnolia species, approximately 10 major components, which is $\alpha$-pinene, $\beta$-pinene, sabinene, myrcene, d-limonene, eucarlyptol (1,8-cineol), $\gamma$-terpinene, p-cymene, linalool, $\alpha$-terpineol, were commonly present in the four species. For statistical analysis, the original dataset was reduced to the 13 variables by Fisher criterion and factor analysis (FA). The essential oil patterns were processed by means of the multivariate statistical analysis including hierarchical cluster analysis (HCA), principal component analysis (PCA) and discriminant analysis (DA). All samples were divided into four groups with three principal components by PCA and according to the plant origins by HCA. Thirty-three samples (23 training sets and 10 test samples to be assessed) were correctly classified into the four groups predicted by PCA. This method would provide a practical strategy for assessing the authenticity or quality of the well-known herbal drug, Magnoliae flos.

Preliminary Psychometric Properties of the Chinese Version of the Work-Related Quality of Life Scale-2 in the Nursing Profession

  • Lin, Shike;Chaiear, Naesinee;Khiewyoo, Jiraporn;Wu, Bin;Johns, Nutjaree Pratheepawanit
    • Safety and Health at Work
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    • v.4 no.1
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    • pp.37-45
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    • 2013
  • Objectives: As quality of work-life (QWL) among nurses affects both patient care and institutional standards, assessment regarding QWL for the profession is important. Work-related Quality of Life Scale (WRQOLS) is a reliable QWL assessment tool for the nursing profession. To develop a Chinese version of the WRQOLS-2 and to examine its psychometric properties as an instrument to assess QWL for the nursing profession in China. Methods: Forward and back translating procedures were used to develop the Chinese version of WRQOLS-2. Six nursing experts participated in content validity evaluation and 352 registered nurses (RNs) participated in the tests. After a two-week interval, 70 of the RNs were retested. Structural validity was examined by principal components analysis and the Cronbach's alphas calculated. The respective independent sample t-test and intra-class correlation coefficient were used to analyze known-group validity and test-retest reliability. Results: One item was rephrased for adaptation to Chinese organizational cultures. The content validity index of the scale was 0.98. Principal components analysis resulted in a seven-factor model, accounting for 62% of total variance, with Cronbach's alphas for subscales ranging from 0.71 to 0.88. Known-group validity was established in the assessment results of the participants in permanent employment vs. contract employment (t = 2.895, p < 0.01). Good test-retest reliability was observed (r = 0.88, p < 0.01). Conclusion: The translated Chinese version of the WRQOLS-2 has sufficient validity and reliability so that it can be used to evaluate the QWL among nurses in mainland China.

The Analysis of Children's Torso using Photographic Anthropometry(II):A Classification of Clusters by Principal Component Score (사진 계측에 의한 아동의 동체 형상 분석(II): 주성분 점수에 의한 군집 유형의 분류)

  • Jeon, Eun-Kyung;Kwon, Sook-Hee
    • Korean Journal of Human Ecology
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    • v.8 no.2
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    • pp.313-325
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    • 1999
  • This study aimed to classify the data of children's bodies into several clusters by principal component scores that were extracted through the factor analysis in the former study, and to describe the distribution and body characteristics of the clusters. The sample was 308 elementary school children aged from 6 to 8 and the anthropometric measurements were performed indirectly from the photographs of the subjects, which was the same as the first analysis. The data were analysed statistically using SPSSWIN Ver. 8.0. Through the statistical analysis, 3 clusters were obtained from the data. The first cluster distributed more in the children aged 7 and 8 than in the children aged 6. The somatotype of this group was the tallest among the three groups, and they were the most developed group compared to the two other groups in lateral component as well as in linear component. The second cluster group wasn't well developed in lateral components, and had lowest level in Rohrer Index, so this group had thin figures compared to the other groups. The third cluster revealed dominant distribution in the group aged 6, and the group had the least developed linear components but higher level in Rohrer Index. Each cluster group revealed peculiar somatotype that was dominant in one group but rarely in other cluster groups. Lateral views of these characteristics were showed using the average of the measurements of clusters.

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