• 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.

• Korean Journal of Plant Resources
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• v.11 no.2
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• pp.210-216
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• 1998

Taxonomic studies in external morphology, principal component analysis and cluster analysis were conducted to understand the intraspecific relationship among three habitats (Jirisan, Odaesan and Ulleungdo) of allium voctorialis var. platyphyllum. External morphology such as bulb color, leaf blade length and width, petiole length, total leaf length, peduncle length, perianth lobe length and width, length of anther and filament were useful characters for identification of poplations in three habitats. The results obtained based on the principal component (Pc) analysis of treated 72 OTUs(included outgroup) were divided into three groups by the PC 1 ,2,3 and the sums of contributions for the total variance were 84.1%(PC1 51.0%, PC2 24.9% and PC3 8.2%, respectively). In cluster analysis by the UPGMA and Ward's methods , there was similarities in the compostion of clustered taxa, and only Ulleungdo population was distinctly identified from population of other two habitats.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.1035-1046
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• 2015

Variance components models incorporate various random factors in the form of linear models. There are two experimental Layouts for the classification of factors under variance components models: nested classification and crossed classification. We consider two-way variance components models and investigate the effect of experimental Layout on the performance of model selection criteria AIC and BIC. The effect of experimental Layout is studied through a simulation study with various combinations of parameters in a systematic fashion. The simulation study shows differences in performance of model selection methods between the two classification. There is a particular tendency to prefer the smaller model than the true model when the variance component of a nested factor becomes relatively larger than a nesting factor that is persistent even when the sample size is not small.

• Korean Journal of Plant Resources
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• v.12 no.3
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• pp.186-191
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• 1999

This study was conducted to evaluate the growth characteristics and grain component of 10 collected colored rice cultivars to find out the possibilities of using the agronomically usefull characters to provide information for colored rice breeding and cultivation. The coefficients of variation of culm length, grains number, ripening rate, maturity time, and coat color of grain and seed were higher than those of other characters. The positive correlations were observed among heading dates, grain numbers per panicle, and 1000 grain weight, as well as between culm length and panicle length, panicle length and grain numbers per panicle, 1000 grain weight and darkness of seed coat color, while negative correlations were observed between heading dates and panicle numbers per hill, grain yield and seed coat color as well as among culm length, length, number per hill and seed coat color of brown rice, respectively. The first component of principal component analysis was consist of panicle numbers per hill, 1000 grain weight, and grain yield showing higher correlations among them which explained the variance of the sink size of respective cultivars. The second component of principal component analysis was consist of heading date, grain numbers per panicle and maturing date showing higher correlations among them which explained the variance of maturity of respective cultivars.

• 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 Korea Game Society
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• v.13 no.2
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• pp.59-70
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• 2013

Although the history of the game of Go is more than 2,500 years, the theoretical studies of Go are still insufficient. In recent years a lot of studies using Artificial Intelligent(AI) have been conducted, but they do not provide the prominent theoretical reality. We applied Principal Component Analysis(PCA) to the professional Go openings, which are the early stage in Go, to analyze them especially focused on the Go game records of the professional 9-dan player Lee Sedol who is the world's top professional Go player. The results showed that among the 361 eigenvectors the 48 most significant eigenvectors capture most of the variance (99.9%) and the 30 most significant eigenvectors enable to possess 90.5 percent of the total variance. This result would be expected to considerably contribute to pattern recognition research of the professional Go openings in the near future.

• Transactions of the Korean Society of Automotive Engineers
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• v.25 no.3
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• pp.344-349
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• 2017

Suspension noise from under a passenger car is one of the important factors that impact the perceptual quality for drivers. However, it is difficult to validate this by component level testing in the early stage of development, because suspension noise caused by interaction of the related parts has been found at saleable vehicles late during development or at the manufacturing stage, when many customers have already filed for claims. This study proposed a validation testing under research by the DFSS process that enables reproduction of vehicle level noise by component level testing using a shock absorber with the related parts, such as urethane bumper and top mount. This study also developed a compromised test matrix while analyzing the noise factors through experimental design and analysis of variance to determine what factors can affect noise. Based on this study, we expect that the vehicle level and customer claim can be validated during initial development timing by a more reliable component noise validation test.

• Journal of Korean Society for Atmospheric Environment
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• v.10 no.E
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• pp.343-356
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• 1994

In this study, a statistical investigation was carried out for the evaluation of any relationship between polycyclic aromatic hydrocarbons (PAHss) associated with ambient aerosols and other air quality parameters under varying meteorological conditions. Daily measurements for PAHs and air quality/meteorological parameters were selected from a data-base constructed by a comprehensive air monitoring in London during 1985-1987. Correlation coefficients were calculated to examine any significant relationship between the PAHs and other individual variables. Statistical analysis was further Performed for the air quality/meteorological data set using a principal component analysis to derive important factors inherent in the interactions among the variables. A total of six components were identified, representing vehicle emission, photochemical activity/volatilization, space heating, atmospheric humidity, atmospheric stability, and wet deposition. It was found from a stepwise multiple regression analysis that the vehicle emission component is overall the most important factor contributing to the variability of PAHs concentrations at the monitoring site. The photochemical activity/volatilzation component appeared to be also an important factor particularly for the lower molecular weight PAHs. In general, the space heating component was found to be next important factor, while the contributions of other three components to the variance of each PAHs did not appear to be as much important as the first three components in most cases. However, a consistency for these components in their negative correlations with PAHs data was found, indicating their roles in the depletion of PAHs concentrations in the urban atmosphere.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.285-288
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• 2001

In this paper, we proposed new method of speech feature extraction using ICA(Independent Component Analysis) which minimized the dependency and correlation among speech signals on purpose to separate each component in the speech signal. ICA removes the repeating of data after finding the axis direction which has the greatest variance in input dimension. We verified improvement of speech recognition ability with training and recognition experiments when ICA compared with conventional mel-cepstrum features using HMM. Also, we can see that ICA dealt with the situation of recognition ability decline that is caused by environmental noise.

• Korean Journal of Adult Nursing
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• v.26 no.4
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• pp.403-412
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• 2014

Purpose: The purpose of this study was to validate the Korean version of shortened Nursing Decision-Making Instrument developed by Lauri & $Salanter{\ddot{a}}$(2002). Methods: The subjects were 247 nurses working in eight hospitals of Korea. Data were collected by questionnaires from June to July, 2012 and were analyzed by Principal Component Analysis for construct validity and Cronbach's ${\alpha}$ coefficient for reliability. Results: Factor loadings of the four subscales ranged from .32 to .73. The explained variance from the four factors was 48.54% of the total variance. The factors were named 'implementation of plan, monitoring and evaluation', 'plans of action', 'data collection', and 'data processing and identification'. The first factor consisted of 6 items which explained 13.21% of the total variance and the second factor contained 8 items. The Cronbach's ${\alpha}$ coefficients of the four subscales were from .64 to .81. Conclusion: The Korean version of the shortened Nursing Decision-Making Instrument has satisfactory construct validity and reliability. However, that the scores of the analytic items weren't reversed unlike the analysis method of the original tools is the biggest limitation of this study. In addition, based on the fact that there were several discrepancies for item interpretation of Korean comparing to the findings of the instrument development study, repetitive researches would be suggested.