• Economic and Environmental Geology
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• v.48 no.3
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• pp.187-197
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• 2015

Oriental mineral medicines are single or mixture of more than one mineral species or rock/fossil which are used to treat disease. Mineral medicines remove harmful or useless substances to decrease toxicity and secondary effects, and cause the manufacture of medical compounds with increased efficacy. The extraction test is an accepted in vitro system to predict the bioaccessibility of major and minor elements from mineral medicine. It incorporates gastrointerstinal tract parameters representative of a human body that including stomach and small intestinal pH which are the same as digestion condition. The bioaccessibility of a mineral medicine is the fraction that is soluble in the gastrointestinal environment and is available for absorption. Reaction path modeling in the human body can predict digestion with gastric fluid as well as absorption in the small intestine, existence in body fluids and reaction progress of the exhaust process according to pH conditions in body. Also reaction path modeling can predict bioavailability, which is equal to existence rate in the body and the form and amount of a medicine in the body after intake. The study results from predicating the existence form mineral medicines in the body, and proving the effective ingredient using bioaccessibitily and human risk assessment, suggest these that should be necessary data for new medicine development.

• Analytical Science and Technology
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• v.7 no.1
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• pp.33-39
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• 1994

The purpose on this study was to develop a new improved chromatographic method for determination of trace phenols from environmental waste water. The research was carried out with selected 8 phenols, and solid-phase extraction was employed as sample pretreatment method. The coupling of XAD-4 and Dowex $1{\times}8$ resin as preconcentration column increased the selectivities toward interferences coexisted in matrix. Automation was accomplished with on-line process of pretreatment and HPLC system. After elution of sample through XAD-4 column, phenols were adsorbed by dispersion force, then displaced from it by ACN basified, simultaneously and selectively readsorbed via anion exchange on Dowex $1{\times}8$. Dowex $1{\times}8$ column was washed by water. Phenols readsorbed were removed from Dowex $1{\times}8$ column by a minimum volumn of methanol containing HCl. Each pretreatment step was connected by switching valves and the eluate was directly on-line injected to obtain fast and reliable results into the HPLC. Recovery of phenols was greater than 90%. To examine utility of this method, analysis of phenols from laboratory waste water sample which was added some organic pollutants to find with phenols on environmental waste water were also accomplished without their interference effects.

• Microbiology and Biotechnology Letters
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• v.26 no.2
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• pp.137-142
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• 1998

Helicobacter pylori is a Gram-negative bacterium which causes chronic gastritis and is associated with gastric ulcer, duodenal ulcer and gastric carcinoma. In the process of screening of antibacterial activities against H. pylori from soil microorganisms, fungus No. 60686 was isolated. After fermentation of No.60686, the antibacterial compound was isolated, purified and followed by extraction of mycelium with organic solvents, acetone and ethyl acetate, through silica gel chromatography, LH-20 gel chromatography and HPLC. As a result of the structural analyses of the compound by IR, $^1$H- and $^{13}$C-NMR, FAB/Mass spectrophotometer, the compound having the antimicrobial activity was identified as chaetoglobosin A ($C_{32}H_{36}N_2O_5$), a cytochalasan derivative. The antimicrobial activity of chaetoglobosin A was tested against Gram-positive and negative bacteria by paper disk method. Among the test strains of 9 Gram-positive bacteria and 18 Gram-negative bacteria containing 4 H. pylori strains, the growth of 4 H. pylori strains and 3 S. aureus strains (SG 511, 285 and 503) was only inhibited by chaetoglobosin A. Also it was shown that its growth inhibition against H. pylori strains was stronger than that against S. aureus strains at the treatment of the same concentration. Therefore it was concluded that chaetoglobosin A has a specific growth inhibition against H. pylori of the tested bacteria.

• Korean Journal of Food Science and Technology
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• v.39 no.5
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• pp.515-520
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• 2007

To establish the roasting conditions of dandelion leaves for the manufacture of processed foods such as beverages and tea, we investigated the physicochemical and sensory characteristics of dandelion leaves and their hot water extracts by roasting treatment. As the number of roasting times increased, the free sugar content of the roasted dandelion leaves decreased, and in particular, free amino acid and total polyphenol content decreased greatly after only 1 roasting treatment. The amino nitrogen and total polyphenol contents of the roasted dandelion leaf hot water extracts also decreased greatly, and their L-, a-, and b-values showed much lower values than those of the raw leaf extracts. However, a greater amount of reducing sugars was extracted in the roasted leaves than in the raw leaves, suggesting that the roasting process allows for easier extraction of the compounds in dandelion leaves. Five sensory characteristics, including astringent taste, bitter taste, peen flavor, burnt taste, and sweet odor, were deduced through quantitative descriptive analysis of the hot water extracts. Among them, astringent taste, bitter taste, and green flavor showed significant differences between roasting treatments. The sensory evaluation results show that as the number of roasting times increased, the palatability of the hot water extracts increased greatly, in terms of color and taste.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.455-467
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• 2017

When performing target detection using hyperspectral imagery, a feature extraction process is necessary to solve the problem of redundancy of adjacent spectral bands and the problem of a large amount of calculation due to high dimensional data. This study proposes a new band selection method using the $L_{2,1}$-norm regression model to apply the feature selection technique in the machine learning field to the hyperspectral band selection. In order to analyze the performance of the proposed band selection technique, we collected the hyperspectral imagery and these were used to analyze the performance of target detection with band selection. The Adaptive Cosine Estimator (ACE) detection performance is maintained or improved when the number of bands is reduced from 164 to about 30 to 40 bands in the 350 nm to 2500 nm wavelength band. Experimental results show that the proposed band selection technique extracts bands that are effective for detection in hyperspectral images and can reduce the size of the data without reducing the performance, which can help improve the processing speed of real-time target detection system in the future.

• The Korean Journal of Pesticide Science
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• v.14 no.4
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• pp.361-370
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• 2010

Considering the efficiencies of the preparation process at each stage obtained in previous studies, the analytical determination method was established for multi-pesticide residues in soils. It consist of the acetone-extraction, the dichloromethane-partition, the Florisil or silica-gel chromatography and the gas chromatography analysis equipped with the electron capture detector and the nitrogen-phosphorus detector. In the soil recovery test by Florisil clean-up system, the number of pesticides recovered in the range of 70~120% and showed less than 20% of RSD were 165 pesticides for paddy soil, 169 pesticides for upland soil and 159 pesticides in both soils through the tested 183 pesticides. And in the soil recovery test by silica-gel system, the number of pesticides recovered in the range of 70~120% and showed less than 20% of RSD were 154 pesticides for paddy soil, 145 pesticides for upland soil, and 134 pesticides in both soils.

• Journal of Life Science
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• v.21 no.5
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• pp.739-745
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• 2011

The purpose of this study was to characterize the aroma of green tea blended with dried citrus fruits containing peeler. Whether middle or low grade green tea is consumed does not have an influence on health benefits, but it does havean influence on flavor. Therefore, two kinds of citrus fruits (mandarin orange and citron) were used to infuse the teas with aromatic flavors. This process turned unflavored tea into special tea with a good color and preferable flavor. Aroma compounds were extracted by SDE method. The concentrated aroma extracts were analyzed and identified by GC and GC-MS. The main aroma components of the green tea blended with mandarin orange were limonene (72.18%), (Z)-ocimene (8.29%), phenyl acetaldehyde (6.15%), ${\gamma}$-terpinene (5.14%), ${\beta}$-elemene (1.80%) and linalool (1.00%). The main aroma components of the green tea blended with citron were limonene (71.74%), ${\gamma}$-terpinene (9.76%), (Z)-ocimene (5.38%), (E)-ocimene (4.36%), linalool (1.00%) and ${\beta}$-mycrene (0.87%). The aromas of green tea blended with dried citrus fruits were mainly mono - and sesquiterpenic compounds.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.1
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• pp.6-17
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• 2013

Recently, the color of vehicle license plate has been changed from green to white. Thus the vehicle plate recognition system used for parking management systems, speed and signal violation detection systems should be robust to the both colors. This paper presents a vehicle license plate recognition system, which works on both of green and white plate at the same time. In the proposed system, the image of license plate is taken from a captured vehicle image by using morphological information. In the next, each character region in the license plate image is extracted based on the vertical and horizontal projection of plate image and the relative position of individual characters. Finally, for the recognition process of extracted characters, PCA(Principal Component Analysis) and LDA(Linear Discriminant Analysis) are sequentially utilized. In the experiment, vehicle license plates of both green background and white background captured under irregular illumination conditions have been tested, and the relatively high extraction and recognition rates are observed.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.345-354
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• 2010

Visual tracking techniques for Augmented Reality are classified as either a marker tracking approach or a natural feature tracking approach. Marker-based tracking algorithms can be efficiently implemented sufficient to work in real-time on mobile devices. On the other hand, natural feature tracking methods require a lot of computationally expensive procedures. Most previous natural feature tracking methods include heavy feature extraction and pattern matching procedures for each of the input image frame. It is difficult to implement real-time augmented reality applications including the capability of natural feature tracking on low performance devices. The required computational time cost is also in proportion to the number of patterns to be matched. To speed up the natural feature tracking process, we propose a novel fast tracking method based on optical flow. We implemented the proposed method on mobile devices to run in real-time and be appropriately used with mobile augmented reality applications. Moreover, during tracking, we keep up the total number of feature points by inserting new feature points proportional to the number of vanished feature points. Experimental results showed that the proposed method reduces the computational cost and also stabilizes the camera pose estimation results.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.54-60
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• 2004

Face recognition is one of the problems to be solved by appearance based matching technique. However, the appearance of face image is very sensitive to variation in illumination. One of the easiest ways for better performance is to collect more training samples acquired under variable lightings but it is not practical in real world. ]:n object recognition, it is desirable to focus on feature extraction or normalization technique rather than focus on classifier. This paper presents a simple approach to normalization of faces subject to directional illumination. This is one of the significant issues that cause error in the face recognition process. The proposed method, ICR(illumination Compensation based on Multiple Linear Regression), is to find the plane that best fits the intensity distribution of the face image using the multiple linear regression, then use this plane to normalize the face image. The advantages of our method are simple and practical. The planar approximation of a face image is mathematically defined by the simple linear model. We provide experimental results to demonstrate the performance of the proposed ICR method on public face databases and our database. The experimental results show a significant improvement of the recognition accuracy.