• Archives of Pharmacal Research
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• v.29 no.9
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• pp.752-756
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• 2006

Artemisia princeps Pampanini, which is called Ssajuarissuk in Korean (SS-1), was fermented with lactic acid bacteria (LAB) and their passive cutaneous anaphylaxis reaction-inhibitory activity was investigated. Of these fermented agents, SS-1 extract fermented with Bifidobacterium infantis K-525 (F-SS-1) most effectively inhibited the release of ${\beta}$-hexosamindase from RBL-2H3 cells induced IgE. In IgE-induced RBL-2H3 cells, F-SS-1 inhibited proinflammatory cytokines IL-6 and $TNF-{\alpha}$ mRNA expression. Oral administration of SS-1 and F-SS-1 to mice inhibited passive cutaneous anaphylaxis (PCA) reaction induced by IgE and scratching behaviors induced by compound 48/80. The inhibitory activity of F-SS-1 against scratching behaviors was more effective than that of SS-1. These findings suggest that the fermentation of SS-1 with LAB can increase its antiallergic activity.

• Korean Journal of Ecology and Environment
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• v.51 no.4
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• pp.354-364
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• 2018

In this study, we surveyed the fish community at the four sites(St. 1, 3, 5, 7) in Jungrang Stream from 2008 to 2016. We found 37 species grouped into nine families. There were three exotic species; Cyprinus carpio, Carassius cuvieri and Micropterus salmoides after rainfall. Dominant species was Zacco platypus (57.3%) and subdominant species was Carassius auratus(10.4%) in a community. The water quality, surveyed at the six sites(St. 1, 2, 3, 4, 5, 6), based on eight factors(Water temperature, pH, DO, BOD, SS, EC, TN and TP), largely varied depending on each site and period. Minimum values in four factors(BOD, EC, TN and TP) were observed in rainy season, indicating an ionic and nutrient dilution of stream water by precipitation. In contrast, a maximum value in SS was occurred in rainy season at St. 2 and St. 5. The precipitation, Maximum value observed in July ($497.5{\pm}297.2mm$), minimum value in January ($12.9{\pm}8.6mm$). In July and August, the precipitation was divided into before and after the rainfall season in Jungrang stream. Using cluster analysis three fish sites (St. 1, 3, 5) were identified as significantly influence 11 fish species; Hemiculter eigenmanni, Squalidus japonicus coreanus, Hemibarbus labeo, Gnathopogon strigatus, Pungtungia herzi, Rhynchocypris oxycephalus, Pseudogobio esocinus, Pseudorasbora parva, Cyprinus carpio, Carassius auratus and Zacco platypus by rainfall.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.43-57
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• 2009

Integrating 3D data acquired in multiple views is one of the most important techniques in 3D modeling. However, the existing integration methods are sensitive to registration errors and surface scanning noise. In this paper, we propose a integration algorithm using the local surface topology. We first find all boundary vertex pairs satisfying a prescribed geometric condition in the areas between neighboring surfaces, and then separates areas to several regions by using boundary vertex pairs. We next compute best fitting planes suitable to each regions through PCA(Principal Component Analysis). They are used to produce triangles that be inserted into empty areas between neighboring surfaces. Since each regions between neighboring surfaces can be integrated by using local surface topology, a proposed method is robust to registration errors and surface scanning noise. We also propose a method integrating of textures by using parameterization technique. We first transforms integrated surface into initial viewpoints of each surfaces. We then project each textures to transformed integrated surface. They will be then assigned into parameter domain for integrated surface and be integrated according to the seaming lines for surfaces. Experimental results show that the proposed method is efficient to face modeling.

• Journal of Korea Water Resources Association
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• v.35 no.2
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• pp.221-229
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• 2002

For the efficient design of baffled Powdered activated carbon(PAC) contractor, which has been widely used in water treatment plant(WTP) against the algae-related odor problems, a CFD(computational fluid dynamics) program was applied. In order to verify the performance of FLOW-3D program, the previously reported results of tracer tests from a pilot-scale PAC contractor(working volume of 288 liters) were compared to those from FLOW 3D. The results of FLOW-3D simulation were very similar to those from tracer tests conducted with the Pilot-scale PAC contactor. On the other hand, the hydrodynamic characteristics of baffled contractor in the P-WTP were simulated by using FLOW-3D. Simulation results on the distribution of PAC particles showed that there are some stagnant parts in the back side of baffles in which PAC Particles are not present. These stagnant parts might decrease the adsorption capacity of PAC particles. When the baffles were changed to maze-type intra-basin baffling, PAC particles were evenly distributed and the amount of stagnant parts reduced. In conclusion, it is anticipated that FLOW-3D simulation could be a viab1e tool for analyzing the hydrodynamic characteristics of structures used in drinking water treatment plant.

• Bulletin of the Korean Chemical Society
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• v.30 no.5
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• pp.1121-1126
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• 2009

This paper describes a pattern recognition method of Magnoliae flos based on a gas chromatographic/mass spectrometric (GC/MS) analysis of the essential oil components. The botanical drug is mainly comprised of the four magnolia species (M. denudata, M. biondii, M. kobus, and M. liliflora) in Korea, although some other species are also being dealt with the drug. The GC/MS separation of the volatile components, which was extracted by the simultaneous distillation and extraction (SDE), was performed on a carbowax column (supelcowax 10; 30 m{\time}0.25 mm{\time}0.25{\mu}m$) using temperature programming. Variance in the retention times for all peaks of interests was within RSD 2% for repeated analyses (n = 9). Of the 74 essential oil components identified from the magnolia species, approximately 10 major components, which is $\alpha$-pinene, $\beta$-pinene, sabinene, myrcene, d-limonene, eucarlyptol (1,8-cineol), $\gamma$-terpinene, p-cymene, linalool, $\alpha$-terpineol, were commonly present in the four species. For statistical analysis, the original dataset was reduced to the 13 variables by Fisher criterion and factor analysis (FA). The essential oil patterns were processed by means of the multivariate statistical analysis including hierarchical cluster analysis (HCA), principal component analysis (PCA) and discriminant analysis (DA). All samples were divided into four groups with three principal components by PCA and according to the plant origins by HCA. Thirty-three samples (23 training sets and 10 test samples to be assessed) were correctly classified into the four groups predicted by PCA. This method would provide a practical strategy for assessing the authenticity or quality of the well-known herbal drug, Magnoliae flos.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.2
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• pp.201-208
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• 2007

Functional oils (FOs) were produced from commercial diacylglycerol oil and red yeast rice extracts from 80% ethanol for 1 hr in a shaking water bath at $35^{\circ}C$ and 175 rpm. FOs contained (A) 600, (B) 1200, (C) 1800, and (D) 2280 ppm of red yeast-rice extracts, respectively. The Hunter a value and b value were risen whereas L value was reduced along with the increase of extract concentration. Content of monacolin K and total phenolic compounds in FOs significantly increased according to the increase of extract concentration. The oxidation stability of FOs was observed by Rancimat at $98^{\circ}C$. Induction time decreased according to the increase of extract concentration. The major volatile compounds of FOs were compared using the electronic nose (EN) system and solid phase microextraction (SPME) method combined with gas chromatograph/mass spectrometry (GC/MS). EN was composed of 12 different metal oxide sensors. Sensitivities (Rgas/Rair) of sensors from EN were analyzed by principal component analysis (PCA), whose proportion was 99.66%. For qualitative or quantitative analysis of volatile compounds by SPME-GC/MS, the divinylbenzene/carboxene/polydimethyl-siloxane fiber and sampling temperature of $50^{\circ}C$ were applied.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.1
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• pp.33-39
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• 2017

In this paper, an effective feature which is capable of classifying targets among the detections obtained from 2D range-bearing maps generated in active sonar environments is proposed. Most conventional approaches for target classification with the 2D maps have considered magnitude of peak and statistical features of the area surrounding the peak. To improve the classification performance, HOG(Histogram of Gradient) feature, which is popular for their robustness in the image textures analysis is applied. In order to classify the target signal, SVM(Support Vector Machine) method with reduced HOG feature by the PCA(Principal Component Analysis) algorithm is incorporated. The various simulations are conducted with the real clutter signal data and the synthesized target signal data. According to the simulated results, the proposed method considering HOG feature is claimed to be effective when classifying the active sonar target compared to the conventional methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.20-26
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• 2008

As they have more and more intelligence robots or computers these days, so the interaction between intelligence robot(computer) - human is getting more and more important also the emotion recognition and expression are indispensable for interaction between intelligence robot(computer) - human. In this paper, firstly we extract emotional features at speech signal and facial image. Secondly we apply both BL(Bayesian Learning) and PCA(Principal Component Analysis), lastly we classify five emotions patterns(normal, happy, anger, surprise and sad) also, we experiment with decision fusion and feature fusion to enhance emotion recognition rate. The decision fusion method experiment on emotion recognition that result values of each recognition system apply Fuzzy membership function and the feature fusion method selects superior features through SFS(Sequential Forward Selection) method and superior features are applied to Neural Networks based on MLP(Multi Layer Perceptron) for classifying five emotions patterns. and recognized result apply to 2D facial shape for express emotion.

• Korean Journal of Cognitive Science
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• v.13 no.3
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• pp.1-10
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• 2002

This study was performed to analyze the physical attributes of the faces and affective words on the fares. For analyzing physical attributes inside of a face, 36 facial features were selected and almost of them were the lengths or distance values. For analyzing facial contour 14 points were selected and the lengths from nose-end to them were measured. The values of these features except ratio values normalized by facial vortical length or facial horizontal length because the face size of each person is different. The principal component analysis (PCA) was performed and four major factors were extracted: 'facial contour' component, 'vortical length of eye' component, 'facial width' component, 'eyebrow region' component. We supposed the five-dimensional imaginary space of faces using factor scores of PCA, and selected representative faces evenly in this space. On the other hand, the affective words on faces were collected from magazines and through surveys. The factor analysis and multidimensional scaling method were performed and two orthogonal dimensions for the affections on faces were suggested: babyish-mature and sharp-soft.

• Journal of the Korean Wood Science and Technology
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• v.45 no.2
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• pp.202-212
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• 2017

This study was to establish the interrelation between chemical compositions and near infrared (NIR) spectra for the classification on distinguishability of domestic gymnosperms. Traditional wet chemistry methods and infrared spectral analyses were performed. In chemical compositions of five softwood species including larch (Larix kaempferi), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), cypress (Chamaecyparis obtusa), and cedar (Cryptomeria japonica), their extractives and lignin contents provided the major information for distinction between the wood species. However, depending on the production region and purchasing time of woods, chemical compositions were different even though in same species. Especially, red pine harvested from Naju showed the highest extractive content about 16.3%, whereas that from Donghae showed about 5.0%. These results were expected due to different environmental conditions such as sunshine amount, nutrients and moisture contents, and these phenomena were also observed in other species. As a result of the principal component analysis (PCA) using NIR between five species (total 19 samples), the samples were divided into three groups in the score plot based on principal component (PC) 1 and principal component (PC) 2; group 1) red pine and Korean pine, group 2) larch, and group 3) cypress and cedar. Based on the chemical composition results, it was concluded that extractive content was highly relevant to wood classification by NIR analysis.