• Analytical Science and Technology
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• v.24 no.6
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• pp.519-526
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• 2011

Chemometrics using near-infrared (NIR) and Raman spectroscopy have found significant uses in a variety quantitative and qualitative analyses of pharmaceutical products in complex matrixes. Most of the pharmaceutical can be measured directly with little or no sample preparation using these spectroscopic methods. During pharmaceutical manufacturing process, analytical techniques with no or less sample preparation are very critical to confirm the quality. This study showed NIR and Raman spectroscopy with principal component analysis (PCA) was very effective for the blending processing control. It is of utmost importance to evaluate critical parameters related to quality of products during pharmaceutical processing. The blending is confirmed by off-line determination of active pharmaceutical ingredient (API) by a conventional method such as high performance liquid chromatography (HPLC) and UV spectroscopy. These analytical methods are time-consuming and ineffective for real time control. This study showed the possibility for the determination of blend uniformity end-point of CR tablets with the use of both NIR and Raman spectroscopy. The samples were acquired from six positions during blending processing with U-type blender from 0 to 30 min. Using both collected NIR and Raman spectral data, principal component analysis (PCA) was used to follow the uniformity of blending and finally determine the end-point. The variation of homogeneity of six samples during blending was clearly found and blend uniformity end-point was successfully confirmed in the domains of principal component (PC) scores.

• Journal of Soil and Groundwater Environment
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• v.22 no.3
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• pp.10-17
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• 2017

In this study, the evolution and origin of major dissolved constituents of crystalline bedrock groundwater in a coastal area were evaluated using multivariate statistical and groundwater quality analyses. The groundwater types mostly belonged to the $Na(Ca)-HCO_3$ and $Ca-HCO_3$ types, indicating the effect of cation exchange. Stable isotopes of water showed two areas divided by first and secondary evaporative effects, indicating a pattern of rapid hydrological cycling. Saturation indices of minerals showed undersaturation states. Thus, the degree of evolution of groundwater is suggested as in the low to intermediate stage, based on field and laboratory analytical conditions. According to the principal component analysis (PCA) results, the chemical components of EC, $Ca^{2+}$, $Mg^{2+}$, $K^+$, $HCO_3{^-}$, $SO{_4}^{2-}$ (PCA 1), $F^-$ (PCA 3), $SiO_2$ (PCA 4), and $Fe^{2+}$ (PCA 5) are derived from various water-rock interactions. However, $NO_3{^-}$, $Na^+$, and $Cl^-$ (PCA 2) represented the chemical characteristics of both anthropogenic sources and natural sea spray.

• Korean Journal of Food Science and Technology
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• v.47 no.5
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• pp.567-573
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• 2015

In this study, volatile compounds in nine commercial Japanese distilled liquors (Shochu) were isolated by headspace solid-phase microexrraction (SPME) and analyzed by gas chromatography (GC) and GC-mass spectrometry (MS). A total of 76 volatile components, including 48 esters, 13 alcohols, and 15 miscellaneous components, were identified. Esters and alcohols constituted the largest groups of quantified volatiles. Differences in volatile components among the distilled liquors and possible sample grouping were examined by applying principal component analyses to the GC-MS data sets. The first and second principal components explained 77.92% of the total variation across the samples. The samples using barley koji showed higher overall concentrations of total volatile components. Additionally, the principal component analysis did not reveal any sample grouping based on the raw material used.

• Physical Therapy Korea
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• v.15 no.2
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• pp.44-53
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• 2008

The purpose of this preliminary study was to develop a measurement for assessing risk factors for falling in community-dwelling elderly persons. Rasch analysis and principal component analysis were performed to examine whether items on the Activities-Specific Balance Confidence (ABC), assessing self-efficacy, and items on the Berg Balance Scale (BBS), assessing balance function, contribute jointly to a unidimensional construct in the elderly. A total of 35 elderly persons (4 men, 31 women) participated. In this study, each item of ABC (16 items) and BBS (14 items) was scored on a 5-point ordinal rating scale from 0 to 4. The initial Rasch and principal component analysis indicated that 3 of the ABC items and 2 of the BBS items were misfit for this study. These 5 items were excluded from further study. After combining ABC and BBS, Rasch and principal component analyses were examined and finally 23 items selected; 12 items from ABC, 11 items from BBS. The 23 combined ABC-BBC items were arranged in order of difficulty. The hardest item was 'walk outside on icy sidewalks' and the easiest item was 'pivot transfer'. Although structural calibration of each 5 rating scale categories was not ordered, the other three essential criteria of Linacre's optimal rating scale were satisfied. Overall, the ABC-BBS showed sound item psychometric properties. Each of the 5 rating scale categories appeared to distinctly identify subjects at different ability levels. The findings of this study support that the new ABC-BBS scale measure balance function and self-efficacy. It will be a clinically useful assessment of risk factors for falling in the elderly. However, the number of subjects was too small to generalize our results. Further study is needed to develop a new assessment considering more risk factors of falling in elderly.

• Journal of Korean Society of Forest Science
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• v.95 no.2
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• pp.188-193
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• 2006

Volunteerism is an emerging issue in public resource management such as forest recreation management. As volunteers, forest interpreters play a significant role in supporting and educating visitors to forest recreation areas. The purpose of this study was to examine forest interpreters' motivation and their job satisfaction. To collect data, a set of self-administered questionnaire was sent to 250 members of Chungbuk Forest Interpreters' Association during August and September of 2005. 152 completed questionnaires were returned. Principal component factor analyses yield five motivation factors and four satisfaction factors. All the factors were highly correlated.

• Horticultural Science & Technology
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• v.29 no.3
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• pp.232-239
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• 2011

The genus Acorus is known as an indigenous medicinal plant. Genetic diversity of thirteen accessions of A. calamus and eight of A. gramineus, with an accession of Colocasia antiquorum and two of Iris pseudacorus as outgroups, were evaluated using RAPD markers for cluster analysis and principal coordinate analysis, and NIR spectroscopic profiles for principal component analysis.A total of 371 polymorphic bands were obtained by using the selected 12 random primers. The genetic distances were estimated from 0.03 to 0.31 within A. calamus and from 0.03 to 0.51 within A. gramineus. The dendrogram and three-dimensional plot separated the accessions into four distinct groups (A. calamus, A. gramineus, C. antiquorum, and I. pseudacorus). Moreover, for the diversity among genus Acorus, eleven A. calamus accessions, one A. gramineus accession, and two I. pseudacorus accessions were non-destructively analyzed from their leaves by NIR spectroscopy, which discriminated Acorus accessions like the RAPD analysis. Interestingly, thirteen accessions of A. calamus were clustered into two groups based on RAPD and NIR analyses, which indicates that there are two ecotypes of A. calamus in Korea. An accession (CZ) of A. calamus with yellow stripe on leaves was closely grouped with another (CX) at a genetic distance (GD) of 0.03, which shows that the stripe trait might be generated by chimeric mutation. The genetic distance between A. calamus and A. gramineus was revealed to be farthest from 0.80 to 0.88 GD. In genus Acorus the genetic diversity and genetic variation were identified by using RAPD marker technique and non-destructive NIRs.

• Investigative Magnetic Resonance Imaging
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• v.3 no.2
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• pp.188-195
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• 1999

The fMRI signals are composed of many various signals. It is very difficult to find the accurate parameter for the model of fMRI signal containing only neural activity, though we may estimating the signal patterns by the modeling of several signal components. Besides the nose by the physiologic motion, the motion of object and noise of MR instruments make it more difficult to analyze signals of fMRI. Therefore, it is not easy to select an accurate reference data that can accurately reflect neural activity, and the method of an analysis of various signal patterns containing the information of neural activity is an issue of the post-processing methods for fMRI. In the present study, fMRI data was analyzed with the Independent Component Analysis(ICA) method that doesn't need a priori-knowledge or reference data. ICA can be more effective over the analytic method using cross-correlation analysis and can separate the signal patterns of the signals with delayed response or motion related components. The Principal component Analysis (PCA) threshold, wavelet spatial filtering and analysis of a part of whole images can be used for the reduction of the freedom of data before ICA analysis, and these preceding analyses may be useful for a more effective analysis. As a result, ICA method will be effective for the degree of freedom of the data.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.383-392
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• 2000

Since late 1970, methods of influence or sensitivity analysis for detecting influential observations have been studied not only in regression and related methods but also in various multivariate methods. If results of multivariate analyses sometimes depend heavily on a small number of observations, we should be very careful to draw a conclusion. Similar phenomena may also occur in the case of incomplete data. In this research we try to study such influential observations in multivariate statistical analysis of incomplete data. Case of principal component analysis is studied with a numerical example.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.10a
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• pp.68-68
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• 2018

A total of 47 core collections of pepper (Capsicum chinense Jacq.) conserved in National Agrobiodiversity Center (NAC) were studied under field condition at Jeonju. All accessions were characterized for their 14 qualitative and 16 quantitative characters. Results revealed that both qualitative and quantitative characters exhibited wide variation among the studied germplasm. Distribution of fruit characters (fruit length, width, and fruit wall thickness) among the accessions was positively skewed. Of the 47 accessions evaluated, 38.3% accessions had conical shaped fruits and mature fruit color was predominantly red (51.1%), orange (21.3%) and yellow (14.9%). Principal component analyses revealed that (i) 56.64% of the qualitative (fruit shape, color and fruit surface) variation and (ii) 89.42% of the quantitative (plant width, height and fruit maturity days) variation were explained by the first two components. Clustering revealed two groups and dendrogram revealed morphological variation among accessions. The phenotypic diversity exists in this core collections provide valuable information to improve agronomic traits in pepper breeding program.

• Journal of Korean Society of Water and Wastewater
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• v.29 no.6
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• pp.625-632
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• 2015

The study of water environment system using a multivariate analysis in Changnyeong-Haman weir section has been conducted. The purpose of this study is to establish better understanding related water qualities in the Changnyeong-Haman weir section which can provide useful information. The data were consisted of water quality data and algae data including WT(water temperature), pH, DO, EC, COD, SS, T-N, $NH_3-N$, T-P, $PO_4-P$, Chl-a, TOC, d-silica, t-silica, Cyanobacteria, Diatoms, and Green algae. Statistical analyses used in this study were correlation analysis, principal components, and factor analysis. According to correlation analysis on COD and TOC, it revealed that the each value of correlation coefficient was 0.843. On the other result, a negative correlation was observed between diatoms and d-silica. Furthermore, the results of principal component analysis to the overall water quality were classified into four main factors with contribution rate 81.071%.