• KDI Journal of Economic Policy
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• v.42 no.2
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• pp.57-84
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• 2020

This study analyzes global inflation synchronization and derives policy implications for the Korean economy. Unlike previous studies that assume a single global inflation factor, this study investigates if inflation in Korea can be explained further by other global inflation factors. Our principal component analysis provides three principal components for global inflation that are linked to the Korea inflation rate - the first component is closely related to OECD inflation, and the second and third components reflect China's inflation. This study empirically demonstrates via in-sample fitting and out-of-sample forecasting that the three principal components of global inflation play a significant role in explaining and predicting Korean inflation in the short-term, while their role is limited in the mid-term. Domestic macroeconomic variables are found to be more important for the mid-term movements of the Korean inflation rate. The empirical results here suggest that the Bank of Korea should focus more on domestic economic conditions than on global inflation when implementing monetary policy because global factors are likely to be already reflected in domestic macro-variables in the mid-term.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.298-303
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• 2000

A procedure to predict the fatigue life of rubber components based on the signed principal strain method was proposed. A tension-compression rubber specimen with Jang-gu shape was designed and principal strain distribution was obtained by using the nonlinear finite element analysis. Finite element analysis and fatigue test of strut rubber mount were conducted to evaluate the fatigue life prediction procedure proposed. A procedure was employed to predict the fatigue life of strut rubber mount. Predicted fatigue lives have a good agreement with tested lives within a factor of 3.

• Journal of the Korean Society of Clothing and Textiles
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• v.19 no.2
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• pp.366-379
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• 1995

This study was performed to provide fundamental data on middle-aged women's upper torso by classifying the upper torso somatotype and analyzing the characteristics of their somatotype. Factor analysis of principal component model was used to 38 directly measured items, and cluster analysis was applied for classification of upper torso forms. Seven factors were extracted from the factor analysis. The first factor represented the items of circumference, breadth, and depth which were related with body size. On the basis of the cluster analysis using factor scores trom factor analysis as being independent variables, the subjects were classified into three groups. Three dress forms were constructed according to the characteristics for each somatotype of subjects, the three-dimensional characteristics of somatotype were analyzied by the moire pattern and horizontal section map of proposed dress forms. Wearing test by moire topography was used to evaluate wearing outline, the ease of clothes and garment space. Moire pattern and horizontal section map were useful to evaluate wearing conditions, and garment space was changed by the characteristics of the body shape.

• Korean Journal of Community Nutrition
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• v.5 no.1
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• pp.83-91
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• 2000

The aims of this study are to evaluate the quality of hospital food services and the evaluate the quality in selected hospitals trough the use of the questionnaires. A survey of 30 hospital food and nutrition service department was undertaken and detailed information was collected from each, including, surveys of 1, 016 patient. Statistical data analysis was completed using the SAS/win 6.11 package for descriptive analysis, t-test X$^2$-test ANOVA principal component analysis , and cluster analysis and cluster analysis. In the case of patient satisfaction with hospital food and food services, overall satisfaction scores of male and female were 3.54 and 3.45 showing higher levels than the average score(3.00) The aspect of the food and food service which received the lowest ratings by patients was 'meal rounding while dining'. After conduction of factor analysis of variables affecting the patients meal satisfaction 3 groups including the 'menu satisfaction factor', 'service satisfaction factor ' and 'nutrition management satisfaction factor ' were selected. 3 clusters were categorized by the 'service cluster' 'nutrition management cluster', 'men cluster', and 'menu nutrition service cluster' after conducting a cluster analysis with influencing variables affecting patients meal satisfaction. The overview results of patient satisfaction by cluster were : in the case of the service group, such factors as taste, portion size, dealing with complaints while dining meal rounding while dining should be managed with caution In case of the nutrition management group, such factors as taste, portion size, temperature of the food intake, and dependence on hospital food should be managed with care, In the case of the menu groups, such factors as punctuality of meal times, contaminated substances in meals and serving mistakes, cleanliness of dishes, kindness of the server meal rounding while dining should by particularly managed with importance.

• 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.

• Journal of Animal Science and Technology
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• v.52 no.3
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• pp.167-174
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• 2010

The objectives of this study were to quantify the combination values of the principal components and factors calculated using body measurements of Hanwoo (Korean Cattle) and estimate their heritabilities. The technique of multivariate analysis was used to reduce a large number of variables to a smaller number of new variables and characterize cattle according to body shape. The analyses were performed using 1,979 cattle at 12 months of age and 936 cattle at 24 months of age. The data for the analyses was obtained from progeny tests performed on Korean Cattle for 6 years from 2003 to 2008. The phenotypic correlations among these traits were estimated to range from 0.32 to 0.90 at 12 months of age and from 0.21 to 0.82 at 24 months of age. The first principal components (PC1s) indicated a weighed average of overall body measurements, accounting for 99.91% of the total variation for both periods of test. The two first PCs had positive coefficients for all body measurements. The major sources of PC, such as chest girth (CG), body length (BL), rump height (RH), and wither height (WH) were similar for both test periods. The heritabilities for PC1, the first factor score (FS1), and the second factor score (FS2) were estimated by multivariate REML method. The estimated heritabilities for PC1, FS1, and FS2 were 0.33, 0.38, and 0.40, respectively, at 12 months of age and 0.26, 0.76, and 0.58 at 24 months of age. Further studies are needed to determine whether the heritabilities of FS1 and FS2 at 24 months of age were overestimated.

• 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)'.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.82-86
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• 2006

The design of a pattern recognition system generally involves the three aspects: preprocessing, feature extraction, and decision making. Among them, a feature extraction method determines an appropriate subspace of dimensionality in the original feature space of dimensionality so that it can reduce the complexity of the system and help to improve successful recognition rates. Linear transforms, such as principal component analysis, factor analysis, and linear discriminant analysis have been widely used in pattern recognition for feature extraction. This paper shows that singular value decomposition (SVD) can be applied usefully in feature extraction stage of pattern recognition. As an application, a remote sensing problem is applied to verify the usefulness of SVD. The experimental result indicates that the feature extraction using SVD can improve the recognition rate about 25% compared with that of PCA.

• Journal of Korean Society for Atmospheric Environment
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• v.6 no.2
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• pp.155-160
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• 1990

During the period from Mar. 1985 to Feb. 1988, airborne particulate matters were collected and size fractionated by the ANdersen high volume air sampler in Seoul. The concentrations of several heavy metals (Pb, Cu, Zn, Fe, Mn) and benzo(a)pyrene were determined to investigate the size distributions and seasonal variations. And with respect to seven components in the total suspended particulate (TSP), the factor analysis was performed for three groups such as the coarse particles (> 2 $\mu$m), fine particles (< $\mu$m) and TSP. As a result of factor analysis by using the varimax method, the chemical components in the TSP were able to characterize with two principal factors. The first factor, F1 was considered to be a factor indicating the contribution of natural sources and the second factor, F2 was a factor indicating the degree of artificial sources. Each components in the TSP was divided into two main groups of components originated from soil and/or road dust and pollutants originated from automobiles and/or human work.

• Korean Journal of Food Science and Technology
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• v.28 no.6
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• pp.1171-1176
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• 1996

The changes in volatiles of the model system were analyzed by GC and GC-MS before and after retorting. The GC data were analyzed statistically by applying the analysis of variance, and 42 peaks were selected at 5% significance level. Multivariate statistical analysis was performed with these 42 peaks as independent variables. Through the stepwise discriminant analysis, 8 peaks, which corresponded to the compounds such as 2-heptanone, cis-3-hexenal, 2-pentyl-furan, 1-methyl-trans-1,2-cyclohexanediol, 2-hexanone, 3-octanone, trans, trans-nona-2,4-dienal and 1-octen-3-ol, were obtained in sequence to distinguish the samples with and without retorting. The principal component analysis of a set of 8 independent variables resulted in 3 principal components which accounted for 96.1% of the variance, while the first principal component (PC 1) explained 76.5% of the total variance. In addition, through the factor analysis of the principal components, the peaks 11, 20 and 21 could be grouped togather in accordance with the direction and the size while the peaks 9, 33 and 39 constituted the second group in the direction.