• The International Journal of Costume Culture
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• v.2 no.2
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• pp.71-79
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• 1999

The purposes of this study were to 1) identify types and usage levels of production 2) classify apparel manufacturers based on production systems and 3) investigate relationship between characteristics of apparel manufacturers and production system. Apparel manufacturer's characteristics included product line and the number of employees. For this study, the questionnaires were administered to 215 apparel manufacturers in metropolitan area from Feb. to Mar. 1998. Employing a sample of 201, data were analyzed by using factor analysis, descriptive statistics, cluster analysis, discriminant analysis, and multivariate analysis of variance(MANOVA). The following are the results or this study : 1. The production system was identified as three types of production system such as the management centered system, the product centered system and the worker centered system. 2. Based on the three types of the production system, apparel manufacturer were classified into manager centered and product centered groups. 3. With respect to product line, men's wear manufactures were operated the most frequently by manager centered and product centered groups. 3. With respect to product line, men's wear manufacturers were operated the most frequently by management centered system and women's wear manufacturers were operated the most frequently by worker centered system. With respect to the number of employees, apparel manufacturers comprising 5∼19 employees were performed the least frequently worker centered system, while those comprising 50∼99 and 100∼299 employees the least frequently worker centered system.

• Horticulture, Environment, and Biotechnology : HEB
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• v.59 no.6
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• pp.919-927
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• 2018

To compare the antioxidant properties and flavonols in various parts; dry skin (DS) and edible portion (EP), of 8 red onions (Allium cepa L, ROs), total content of phenolics (TPC), flavonoids (TFC), and anthocyanins (TAC) and DPPH radical scavenging properties were estimated and the content of six flavonols were quantified by HPLC-PDA analysis. The major component of DS and EP of RO was quercetin and quercetin-4'-glucoside, respectively. Score plots of the PCA and PLS-DA were segregated by flavonols content and antioxidant properties according to the EP and DS of ROs. Loading plot of the PCA showed that the quercetin and sum of flavonol content were highly correlated with antioxidant activity of ROs. Therefore, flavonol content and antioxidant activity can be used as markers for distinct parts of ROs.

• Journal of the Korean Society of International Agriculture
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• v.31 no.4
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• pp.378-383
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• 2019

To determine whether FT-IR spectral analysis based on multivariate analysis for whole cell extracts can be used to discriminate papaya at metabolic level. FT-IR spectral data from leaves were analyzed by principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA). FT-IR spectra confirmed typical spectral differences between the frequency regions of 1,700-1,500, 1,500-1,300 and 1,100-950 cm^-1, respectively. These spectral regions were reflecting the quantitative and qualitative variations of amide I, II from amino acids and proteins (1,700-1,500 cm^-1), phosphodiester groups from nucleic acid and phospholipid (1,500-1,300 cm^-1) and carbohydrate compounds (1,100-950 cm^-1). The result of PCA analysis showed that papaya leaves could be separated into clusters depending on different growth temperature. In this case, showed discrimination confirmed according to metabolite content of growth condition from papaya. And PLS-DA analysis also showed more clear discrimination pattern than PCA result. Furthermore, these metabolic discrimination systems could be applied for rapid selection and classification of useful papaya cultivars.

• Biomolecules & Therapeutics
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• v.25 no.6
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• pp.559-568
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• 2017

Metabolomics has been used as a powerful tool for the analysis and quality assessment of the natural product (NP)-derived medicines. It is increasingly being used in the quality control and standardization of NP-derived medicines because they are composed of hundreds of natural compounds. The most common techniques that are used in metabolomics consist of NMR, GC-MS, and LC-MS in combination with multivariate statistical analyses including principal components analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). Currently, the quality control of the NP-derived medicines is usually conducted using HPLC and is specified by one or two indicators. To create a superior quality control framework and avoid adulterated drugs, it is necessary to be able to determine and establish standards based on multiple ingredients using metabolic profiling and fingerprinting. Therefore, the application of various analytical tools in the quality control of NP-derived medicines forms the major part of this review. $Veregen^{(R)}$ (Medigene AG, Planegg/Martinsried, Germany), which is the first botanical prescription drug approved by US Food and Drug Administration, is reviewed as an example that will hopefully provide future directions and perspectives on metabolomics technologies available for the quality control of NP-derived medicines.

• Bulletin of the Korean Chemical Society
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• v.34 no.5
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• pp.1467-1472
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• 2013

Metabolomics is a field that studies systematic dynamics and secretion of metabolites from cells to understand biological pathways based on metabolite changes. The metabolic profiling of intact human colorectal tissues was performed using high-resolution magic angle spinning (HR-MAS) NMR spectroscopy, which was unnecessary to extract metabolites from tissues. We used two different groups of samples, which were defined as normal and cancer, from 9 patients with colorectal cancer and investigated the samples in NMR experiments with a water suppression pulse sequence. We applied target profiling and multivariative statistical analysis to the analyzed 1D NMR spectra to identify the metabolites and discriminate between normal and cancer tissues. Cancer tissue showed higher levels of arginine, betaine, glutamate, lysine, taurine and lower levels of glutamine, hypoxanthine, isoleucine, lactate, methionine, pyruvate, tyrosine relative to normal tissue. In the OPLS-DA (orthogonal partial least square discriminant analysis), the score plot showed good separation between the normal and cancer groups. These results suggest that metabolic profiling of colorectal cancer could provide new biomarkers.

• Journal of Information Technology Applications and Management
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• v.17 no.2
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• pp.71-90
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• 2010

Electronic learning(or e-learning) has created hype for companies, universities, and other educational institutions. It has led to the phenomenal growth in the use of web-based learning and experimentation with multimedia, video conferencing, and internet-based technologies. Many researchers are interested in the factors that affect to the performance of e-learning or e-learning services. In this sense, this study is aimed at proposing e-learning system reuse prediction models in which e-learner intention to reuse influence factors(i.e., system accessibility, system stability, information clarity, information validity, self-regulated efficacy, computer self-efficacy, perceived usefulness, perceived ease of use, flow, and parental expectation) affect e-learner intention to reuse positively. A web survey was conducted for the full members of the e-learning education institute A in Seoul, Republic of Korea, an exclusive e-learning company that provides real time video lectures via the desktop conferencing system. The web survey was conducted for 20 days from November 5, 2009, through the e-learning web site of the company A. In this study, three data mining techniques were used : the multivariate discriminant analysis, CART, and C5.0 algorithm. This study was conducted to provide the e-learning service providers, e-learning operators, and contents developers with marketing and management strategies for improving the e-learning service companies, based on the data mining analysis results.

• Journal of Microbiology and Biotechnology
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• v.21 no.1
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• pp.5-13
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• 2011

In this study, seven Trichoderma species (33 strains) were classified using secondary metabolite profile-based chemotaxonomy. Secondary metabolites were analyzed by liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS-MS) and multivariate statistical methods. T. longibrachiatum and T. virens were independently clustered based on both internal transcribed spacer (ITS) sequence and secondary metabolite analyses. T. harzianum formed three subclusters in the ITS-based phylogenetic tree and two subclusters in the metabolitebased dendrogram. In contrast, T. koningii and T. atroviride strains were mixed in one cluster in the phylogenetic tree, whereas T. koningii was grouped in a different subcluster from T. atroviride and T. hamatum in the chemotaxonomic tree. Partial least-squares discriminant analysis (PLS-DA) was applied to determine which metabolites were responsible for the clustering patterns observed for the different Trichoderma strains. The metabolites were hetelidic acid, sorbicillinol, trichodermanone C, giocladic acid, bisorbicillinol, and three unidentified compounds in the comparison of T. virens and T. longibrachiatum; harzianic acid, demethylharzianic acid, homoharzianic acid, and three unidentified compounds in T. harzianum I and II; and koninginin B, E, and D, and six unidentified compounds in T. koningii and T. atroviride. The results of this study demonstrate that secondary metabolite profiling-based chemotaxonomy has distinct advantages relative to ITS-based classification, since it identified new Trichoderma clusters that were not found using the latter approach.

• Speech Sciences
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• v.10 no.4
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• pp.201-219
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• 2003

Background: The perceptual assessment is generally performed by the voice specialist. The objective evaluation is performed in a voice laboratory. Research in voice laboratories has generated a variety of different objective tests and parameters. The perceptual evaluation is one of the most controversial topics in voice research. Review of literature reveals a wide variety of rating scales and reliability data fluctuating from study to study. Unfortunately, there is no widely accepted valid method for classifying voice disorders and assessing outcome after voice treatment. Objectives: The goals of this research were to identify important objective acoustic parameters of vocal quality, and to establish an objective and quantitative correlate of the perceived vocal quality. Materials and Methods : We evaluated the voice analyzed data from 122 dysphonic patients and 20 normal volunteers. A computerized speech lab. 4300B(CSL) was used to carry out the analysis of each voice sample. Results: Three dysphonia severity indices(DSI) were created using discriminant analysis. DSI is based on the weighted combination of the following selected set of acoustic parameters: absolute jitter(Jita in us), smoothed pitch period perturbation (sPPQ in %), amplitude perturbation quotient(APQ in %), soft phonation index(SPI), average fundamental frequency(Fo in Hz), lowest fundamental frequency(Flo in Hz), and smoothed amplitude perturbation quotient(sAPQ in %). The DSI, being the discriminating rule calculated by the logistic regression, consists of three equation based on statistically significant acoustic parameters. Three DSI were created to reflects best the degree of hoarseness as expressed by G from the GRBAS scale. The more positive this DSI is for a patient, the worse the vocal quality. The more it is negative, the better it is. The effect of sex is included implicitly in the DSI-1 and DSI-2, so that a separate DSI-1 and DSI-2 for males and females need not be used. The DSI is objective because no perceptual input is required for its calculation. Conculsion : This research demonstrates that the voice function values calculated from three different multivariate objective dysphonia severity indices are significantly associated with subjective voice assessments. These multivariate objective dysphonia severity indices may be appropriate for use in clinical trials and outcomes research on treatment effectiveness for voice disorders.

• Journal of Korean Society of Forest Science
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• v.102 no.3
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• pp.407-414
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• 2013

This study was conducted to classify forest cover types using the multivariate statistical analysis in the natural forest of western Mt. Jiri. On the basis of the vegetation data by point quarter sampling, the adopted analytical methods were species-area curve (SAC), hierarchical cluster analysis (HCA), indicator species analysis (ISA), and multiple discriminant analysis (MDA). SAC selected the outlier tree species which was likely to have no influence on the classification of forest cover types, excluded from all analytical process. Based on forest vegetative information, HCA classified the study area into 2 to 10 clusters and ISA indicated that the optimal number of clusters were seven. MDA was taken to test the clusters that classified with HCA and ISA. The seven clusters were classified appropriately as overall classification success were 91.3%. The classified forest cover types were named by the ratio of the dominant species in the upper layer of each cluster. They were (1) Quercus mongolica Pure forest, (2) Mixed mesophytic forest, (3) Q. mongolica - Q. serrata forest, (4) Abies koreana - Q. mongolica forest, (5) Fraxinus mandshurica forest, (6) Q. serrata forest, and (7) Carpinus laxiflora forest.

• Journal of Korean Society of Water and Wastewater
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• v.37 no.6
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• pp.425-435
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• 2023

Organoleptic parameters such as color, odor, and flavor influence consumer perception of drinking water quality. This study aims to evaluate the taste of the selected bottled and tap water samples using an electronic tongue (E-tongue) instead of a sensory test. Bottled and tap water's mineral components are related to the overall preference for water taste. Contrary to the sensory test, the potentiometric E-tongue method presented in this study distinguishes taste by measuring the mineral components in water, and the data obtained can be statistically analyzed. Eleven bottled water products from various brands and one tap water from I city in Korea were evaluated. The E-tongue data were statistically analyzed using multivariate statistical tools such as hierarchical clustering analysis (HCA), principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). The results show that the E-tongue method can clearly distinguish taste discrimination in drinking water differing in water quality based on the ion-related water quality parameters. The water quality parameters that affect taste discrimination were found to be total dissolved solids (TDS), sodium (Na+), calcium (Ca²⁺), magnesium (Mg²⁺), sulfate (SO₄^2-), chloride (Cl^-), potassium (K⁺) and pH. The distance calculation of HCA was used to quantify the differences between 12 different types of drinking water. The proposed E-tongue method is a practical tool to quantitatively evaluate the differences between samples in water quality items related to the ionic components. It can be helpful in quality control of drinking water.