• YAKHAK HOEJI
• /
• v.53 no.2
• /
• pp.51-59
• /
• 2009

Quantitative analysis of (+)-catechin (C), (-)-epigallocatechin (EGC), (-)-epicatechin (EC), (-)-epigallocatechin gallate (EGCG), (-)-epicatechin gallate (ECG) and caffeine in commercial green tea was carried out by HPLC employing gradient elution of 0.1% acetic acid and acetonitrile on ODS column. The optimized HPLC method provided satisfactory linearity, accuracy and precision. The relationship between the concentration of the components and cultivated region of the commercial green tea was not significant, while the concentration of EGCG, ECG and caffeine decreased significantly in the later harvested green tea samples (p<0.01). Multivariate analysis of the components was performed in order to characterize and evaluate the cultivated region and harvest period-related variation. Hierarchical clustering and discriminant analysis were applied to classify the geographical and seasonal origins of the green tea samples. The classification accuracy of the cultivated region and harvest period by discriminant analysis was 95% and 91%, respectively, indicating that this method could be reliable and convenient for the quality control of herbal products with different origin.

• Horticultural Science & Technology
• /
• v.34 no.1
• /
• pp.163-171
• /
• 2016

We investigated the intensity and pattern of the scent produced by diploid and tetraploid Cymbidium flowers, using an electronic nose with 6 metal oxide sensors (MOS). The MOS responses were evaluated by principal component analysis, discriminant function analysis, and sensor data. These analyses revealed that tetraploid flowers had a stronger scent than diploid flowers in Cymbidium Golden Elf 'Sundust'. Furthermore, among the different flower parts-column, lip, and petals-the column produced the strongest scent. There was no significant difference between the flowering periods of diploid and tetraploid potted Cymbidium Golden Elf 'Sundust' and Cymbidium Elma 'Orient Toyo' grown in a greenhouse. Moreover, there were no significant differences between the number of flowers per flower stem and the length of flower stems on the diploid and tetraploid plants of these two Cymbidium cultivars. This study provides potentially useful information for the breeding of polyploidy Cymbidium in the floriculture industry.

• Korean Journal of Plant Resources
• /
• v.31 no.6
• /
• pp.641-651
• /
• 2018

Floral scents and metabolites from cut flowers of 14 peony cultivars (Paeonia lactiflora Pall.) were analyzed to discriminate different cultivars and to compare the Korean cultivar with the other cut peonies imported to Korea using electronic nose (E-nose) and Fourier transform infrared (FT-IR) spectroscopy combined with multivariate analysis, respectively. Principal component analysis (PCA) and discriminant function analysis (DFA) dendrogram of peony floral scents were not precisely same but there were 3 groups including same cultivars. PCA and partial least squares-discriminant analysis (PLS-DA) dendrograms of peony metabolites showed that different cut peony cultivars were clustered into two major groups including same cultivars. Fragrance pattern of Korean 'Taebaek' was classified to same group with 'Jubilee' on the PCA and DFA results and its metabolite pattern was clearly discriminated by the PCA and PLS-DA compared to the other cultivars. These results show that the 14 peony cut flowers could be discriminated corresponding to their chemical relationship and the metabolic profile of Korean 'Taebaek' has distinctive characteristics. Furthermore, we suggest that these results could be used as the preliminary data for breeding new cut peony cultivars and for improving the availability of Korean cut peony in cosmetic industry.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.15 no.4
• /
• pp.520-530
• /
• 1996

In this study, the artificial defects in rotary compressor are classified using pattern recognition of acoustic emission signal. For this purpose the computer program is developed. The neural network classifier is compared with the statistical classifier such as the linear discriminant function classifier and empirical Bayesian classifier. It is concluded that the former is better. It is possible to acquire the recognition rate of above 99% by neural network classifier.

• Journal of Families and Better Life
• /
• v.22 no.4
• /
• pp.29-41
• /
• 2004

The patterns of mother-child personality match were investigated in the study. Further, the impact of goodness-of-fit between mother′s and child′s personality on maternal childrearing behaviors, child′s self-esteem, and child′s emotional intelligence was explored. The participants of this study were 1,060 fifth graders and their mothers from four different cities(Seoul. Suwon, Daejon, and Daegu). Six patterns of mother-child personality match were derived through cluster analysis and discriminant analysis. The most harmonious pattern in which maternal childrearing behavior was positive and child′s self-esteem and emotional intelligence were high appeared between mothers and children with high "stability" and "superiority" The least harmonious pattern was shown for the mothers with low "responsibility" and "reflectiveness" and high "dominance′and "sociability", and the children with low "stability" and "superiority".

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2006.05a
• /
• pp.1214-1220
• /
• 2006

In this article, it will be shown that a nonparametric and data-adaptive approach to the variance change point (VCP) detection problem is possible by formulating it as a pattern classification problem. Technical aspects of the VCP detector are discussed, which include its training strategy and selection of proper classification tool.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.25 no.5
• /
• pp.845-855
• /
• 2001

Now the most important thing in fashion industry is find out the fashion sensibility and preference of customers exactly. Thus it is needed that fashion sensibility is connected with formative properties in clothing. The purpose of this study is to clarify the relationship between the fashion sensibility and the formative properties in clothing. 91 kinds of costume samples have been selected from photographs in fashion magazines under color combination, inside form, texture, pattern type in clothing. I have measured fashion sensibility by using Semantic Differential method. The obtained data were analyzed by GLM, discriminant analysis. The results of analysis are as follow; 1. The discriminative images were significant difference in formative properties - color combination was related to attractiveness, inner form to decorativeness, pattern to harmony and texture to surface of soft and hard in clothing. 2. fashion sensibility was significant relationship with formative properties especially inner form in clothing. And the trimming was identified as gorgeous and feminine. 3. Preference, Buying needs, Riches and Pleasant were significant relationship with formative properties in clothing especially color combination and texture.

• Proceedings of the IEEK Conference
• /
• 2002.07c
• /
• pp.1670-1673
• /
• 2002

For pattern recognition on high-dimensional data, such as images, the dimensionality reduction as a preprocessing is effective. By dimensionality reduction, we can (1) reduce storage capacity or amount of calculation, and (2) avoid "the curse of dimensionality" and improve classification performance. Popular tools for dimensionality reduction are Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Independent Component Analysis (ICA) recently. Among them, only LDA takes the class labels into consideration. Nevertheless, it, has been reported that, the classification performance with ICA is better than that with LDA because LDA has restriction on the number of dimensions after reduction. To overcome this dilemma, we propose a new dimensionality reduction technique based on an information theoretic measure for difference of distribution. It takes the class labels into consideration and still it does not, have restriction on number of dimensions after reduction. Improvement of classification performance has been confirmed experimentally.

• Korean Journal of Optics and Photonics
• /
• v.1 no.2
• /
• pp.130-134
• /
• 1990

In this paper, pSDF-based referance image is reahzed. Using BJTC(binary joint transform correlator) as nonlinear correlator, optical pattern recognition for interclass discrimination is performed. Experimental results show that correlation peak intensity of one calss is two times higher than that of the other class, which indicates its superiority in discrimination sensitivity.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.438-441
• /
• 1996

Spinal deformity is a serious disease especially for teenagers and it is desirable for school children to be checked possible spinal deformity by moire photographic inspection method. The moire images of children's backs are visually inspected by doctors, which may cause misjudge because of a large amount of data they have to examine. A technique is proposed in this paper for automating this inspection by computer. Two characteristic axes, a potential symmetry axis approximating the human middle line and a principal axis representing the direction of a moire pattern are employed. Two principal axes are extracted locally on a back and their gradients against the potential symmetry axis are calculated. These gradients compose a 2D feature space and a linear discriminant function (LDF) is defined there which separates normal cases from suspicious cases. The LDF defined by 40 training, data was employed in the experiment to examine 40 test data and 77.5% of them were classified correctly. This amounts to 88.8% if the training data is included.