• Journal of Korea Water Resources Association
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• v.42 no.2
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• pp.149-160
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• 2009

The objective of this study is to suggest parameter regionalization scheme which is integrated two multivariate statistical methods: principal components analysis(PCA) and hierarchical cluster analysis(HCA). This technique is to apply semi-distributed rainfall-runoff model on ungauged catchments. 7 catchment characteristics (area, mean altitude, mean slope, ratio of forest, water content at saturation, field capacity and wilting point) are estimated for 109 mid-sized sub-basins. The first two components from PCA results account for 82.11% of the total variance in the dataset. Component 1 is related to the location of the catchments relevant to the altitude and Component 2 is connected with the area of these. 103 ungauged catchments are clustered using HCA as the following 6 groups: Goesan 23, Andong 6, Imha 5, Hapcheon 21, Yongdam 4, Seomjin 44. SWAT model is used to simulate runoff and the parameters of the model on the 6 gauged basins are estimated. The model parameters were regionalized for Soyang, Chungju and Daecheong dam basins which are assumed as ungauged ones. The model efficiency coefficients of the simulated inflows for these three dams were at least 0.8. These results also mean that goodness of fit is high to the observed inflows. This research will contribute to estimate and analyze hydrologic components on the ungauged catchments.

• Preventive Nutrition and Food Science
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• v.17 no.3
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• pp.184-191
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• 2012

The purpose of this study was to investigate the fatty acid profiles in 18 soybean cultivars grown in Korea. A total of eleven fatty acids were identified in the sample set, which was comprised of myristic (C14:0), palmitic (C16:0), palmitoleic (C16:1, ${\omega}7$), stearic (C18:0), oleic (C18:1, ${\omega}9$), linoleic (C18:2, ${\omega}6$), linolenic (C18:3, ${\omega}3$), arachidic (C20:0), gondoic (C20:1, ${\omega}9$), behenic (C22:0), and lignoceric (C24:0) acids by gas-liquid chromatography with flame ionization detector (GC-FID). Based on their color, yellow-, black-, brown-, and green-colored cultivars were denoted. Correlation coefficients (r) between the nine major fatty acids identified (two trace fatty acids, myristic and palmitoleic, were not included in the study) were generated and revealed an inverse association between oleic and linoleic acids (r=-0.94, p<0.05), while stearic acid was positively correlated to arachidic acid (r=0.72, p<0.05). Principal component analysis (PCA) of the fatty acid data yielded four significant principal components (PCs; i.e., eigenvalues>1), which together account for 81.49% of the total variance in the data set; with PC1 contributing 28.16% of the total. Eigen analysis of the correlation matrix loadings of the four significant PCs revealed that PC1 was mainly contributed to by oleic, linoleic, and gondoic acids, PC2 by stearic, linolenic and arachidic acids, PC3 by behenic and lignoceric acids, and PC4 by palmitic acid. The score plots generated between PC1-PC2 and PC3-PC4 segregated soybean cultivars based on fatty acid composition.

• Journal of the Korean Society of Food Culture
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• v.22 no.4
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• pp.462-467
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• 2007

Volatile components of six commercial $sauces(A{\sim}F)$ and $\hat{O}yuk-jang$(G, H), a Korean traditional fermented sauce, were analyzed by electronic nose based on GC with surface acoustic wave(SAW) sensor. The obtained data were used for pattern recognition and a visual pattern called a $VaporPrint^{TM}$, derived from the frequency and chromatogram of the GC-SAW sensor. Volatile components of sauces and $\hat{O}yuk-jang$ were well discriminated with the direct use of $VaporPrint^{TM}$. Commercial sauces and $\hat{O}yuk-jang$ showed different volatile patterns, respectively, due to different major material, which meju, beef extract, pickled anchovies, and Katsuobushi were used. Volatile components of Oyuk-jang were decreased drastically during the fermentation time. After boiling $\hat{O}yuk-jang$, new several peaks were found. The responses by electronic nose were used for principal component analysis. The PCA plot showed that volatile components pattern were well discriminated by first principal component score(proportion: 96.8%), and first principal component score of $\hat{O}yuk-jang$ was between soy sauce of the liquid extracted from beef and sauce of pickled anchovies.

• 한국문화재보존과학회:학술대회논문집
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• 2004.10a
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• pp.131-134
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• 2004

A lot of foreign objects(ceramics, pottery, bronze, glassware and coins, etc.) have been found in the archaeological sites in Korea. These foreign objects are the evidences of the cultural exchanges of that time, whose scale and routes are an important part of the studies in ancient history. So it is crucial to accumulate basic reference information such as the raw materials and the production method of these objects through scientific researches, along with archeological researches. These scientific research materials provide a basis for finding the importing route and the origin of these objects. Besides, we can find out extraordinary and distinctive production technique by comparison with tile domestic objects. This article reports the result of an analysis, performing on 36 samples of the glassware fragments excavated from the South Tomb of the Hwangnamdaechong, to verify their components and note peculiar features. We have analyzed the major and minor components of 10 elements, and then by using these data examined the differences in the composition of components, varying with the origin and color of glassware. We used the PCA(principal component analysis) as the statistical method to classify the sample in order to find out how the samples formed groups.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.407-410
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• 2003

We propose a new logo watermark scheme for digital images which embed a watermark by modifying middle-frequency sub-bands of wavelet transform. Independent component analysis (ICA) is introduced to authenticate and copyright protect multimedia products by extracting the watermark. To exploit the Human visual system (HVS) and the robustness, a perceptual model is applied with a stochastic approach based on noise visibility function (NVF) for adaptive watermarking algorithm. Experimental results demonstrated that the watermark is perfectly extracted by ICA technique with excellent invisibility, robust against various image and digital processing operators, and almost all compression algorithms such as Jpeg, jpeg 2000, SPIHT, EZW, and principal components analysis (PCA) based compression.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.4-6
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• 2006

Tree-dependent component analysis (TCA) is a generalization of independent component analysis (ICA), the goal of which is to model the multivariate data by a linear transformation of latent variables, while latent variables fit by a tree-structured graphical model. In contrast to ICA, TCA allows dependent structure of latent variables and also consider non-spanning trees (forests). In this paper, we present a TCA-based method of clustering gene expression data. Empirical study with yeast cell cycle-related data, yeast metaboiic shift data, and yeast sporulation data, shows that TCA is more suitable for gene clustering, compared to principal component analysis (PCA) as well as ICA.

• Journal of Biosystems Engineering
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• v.30 no.2 s.109
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• pp.121-126
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• 2005

In this study, a commercial electronic nose system was used to detect contamination of Salmonella bacteria. Odors from growth media contaminated with Salmonella typhimurium, Salmonella enteritidis, or Escherichia coli were collected and analyzed to evaluate a possibility of rapid detection of pathogen. Odor chromatograph showed that S. typhimurium, S. enteritidis, and E. coli had 7,6, and 9 main peaks, respectively. Retention time and intensity of the peaks were distinct for different bacteria species. Principal component analysis (PCA) were also performed to clarify odor differences. Analysis results showed that the odors for uncontaminated growth medium were differently grouped from the odors of contaminated one. The odor from the bacteria growth identified with two principal components, PC 1 and PC2. In PCA figures, odor groups were moved from left to right of PC 1 with elapse of the bacteria growth time. The electronic nose system could detect odors of S. typhimurium, S. enteritidis, E. coli when their concentration were $1.85\times10^6\;cfu/g,\;2.25\times10^6\;cfu/g,\;and\;1.8\times10^5 cfu/g$, respectively.

• Journal of the Korean Society of Tobacco Science
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• v.27 no.1 s.53
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• pp.134-140
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• 2005

The purpose of this study was the discrimination of different tobacco types by the E-Nose/tongue and the analysis of what human sensory attributes are correlated with e-instrument's sensors. Samples were made from five groups of Korean domestic tobacco leaves, aged burley and not aged, aged flue-cured and not aged and blending types of the four. Instrumental tests were conducted to discriminate characteristics among different tobacco samples by the E-Nose and the E-Tongue. Sensory attributes of tobacco tastes were impact, irritation, bitterness, hay-like, tobacco taste, smoke volume, smoke pungent and mouth cleanness. STATISTICA software was used to analyze correlation between the human sensory data and the raw data of e-instruments. Discrimination analysis can be achieved using principal components analysis (PCA) and discriminant factorial analysis(DFA). As a result, impact, bitterness, irritation, smoke volume and smoke pungent of human sensory attributes were correlated with data from the several clustered E-Nose sensors(p < 0.10). And bitterness, irritation, and smoke pungent of human sensory attributes were correlated with data from the E-Tongue sensors(p < 0.10). PCA plot by the E-Nose shows that aged tobacco and not aged were discriminated and DFA plot shows that three groups(aged burley, not aged burley and flue-cured) were discriminated. PCA plot by the E- Tongue shows that flue-cured tobacco was separated from burley. Our results indicated that the e-instruments are sensitive enough to distinguish among tobacco types and their several sensors are reacted to the human sensory attributes.

• Korean Journal of Ecology and Environment
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• v.43 no.4
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• pp.459-470
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• 2010

In this study, we analyzed fish tolerance guilds in mainstems and tributaries of 65 streams and rivers arid their relations to water quality using dataset sampled from April to November, 2009. For the study, water quality parameters including biochemical oxygen demand (BOD), electric conductivity (EC), total nitrogen (TN), total phosphorus (TP), ammonia nitrogen ($NH_3$-N), nitrate nitrogen ($NO_3$-N) and phosphate phosphorus ($PO_4$-P) were analyzed in the laboratory and also tolerance ranges in 3 category fishes of sensitive, intermediate, and tolerant species with high abundance were analyzed. According to fish guild analysis, tolerant species was 58% of the total community and the proportion of omnivore species was 63% of the total, indicating a degradation of habitats and water quality. Water quality was shown typical longitudinal gradients from the headwater to the down-river; TN and TP increased toward the down-rivers except for the big point-source area and ionic contents, based on, electric conductivity showed same pattern. Tolerance guild analysis of 9 major species with high abundance indicated that sensitive groups had narrower tolerance range in the water quality than the groups of intermediate and tolerant species. In contrast, tolerant groups including Zacco platypus, Carassius auratus, and Opsarichthys uncirostris amurensis had wider tolerance ranges than the groups of sensitive and intermediate species. Thus, each group was evidently segregated from the tolerance levels. Principal Component Analysis (PCA) employed for the relations of water quality to fish species in each groups suggests that water quality had highest eigenvalues with fish species in the 1st axis of the PCA and nitrogen (TN, $NH_3$-N, $NO_3$-N) and phosphorus (TP) were key components differentiating three groups of sensitive, intermediate and tolerance guilds.

• Food Science and Preservation
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• v.30 no.4
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• pp.602-616
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• 2023

Fifteen types of rice collected from Kurdistan region-Iraq were investigated by principal component analysis (PCA) in terms of physical properties and cooking characteristics. The dimensions of evaluated grains correspond to 5.05-8.75 mm for length, 1.54-2.47 mm for width, and 1.37-1.95 for thickness. The equivalent diameter was in the range of 5.23-10.03 mm, and the area took 13.30-28.25 mm². The sphericity analysis values varied from 0.32 to 0.56, the aspect ratio from 0.17 to 0.39, and the volume of the grain was measured in the range from 4.48 to 17.74 mm³, hectoliter weight values were 730-820 kg/m³, and true density from 0.6 to 0.96 g/cm³. The broken grain ratio was 1.5-18.3%, thousand kernel weight corresponded to 15.88 to 22.42 g. The water uptake ratios for 30 min of soaking were increased at 60℃ compared to 30 and 45℃. The PCA was used to study the correlation of the most effective factors. Results of PCA showed that the first (PC1) and second (PC2) components retained 63.4% and 34.8% of the total variance, which PC1 was mostly related to hectoliter, broken ratio, and moisture content characteristics while PC2 was mostly concerned with hardness and true density. For cooking properties, the PC1 and PC2 retained 88.5% and 9.3% of the total variance, respectively. PC1 was mostly related to viscosity, spring value, and hardness after cooking, while PC2 was mostly concerned with spring value, hardness before cooking, and hardness after cooking.