• Bulletin of the Korean Chemical Society
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• v.19 no.10
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• pp.1036-1042
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• 1998

The preconcentration and determination of trace elements in water samples were studied by a solvent sublation utilizing dithizonate complexation. After metal dithizonates were formed, trace amounts of cadmium, cobalt, copper and lead were floated and extracted into small volume of a water-immiscible organic solvent on the surface of sample solution and determined in the solvent directly by GF-AAS. Several experimental conditions as formation condition of metal-dithizonate complexes, pH of solution, amount of dithizone, stirring time, the type and amount of surfactants, N2 bubbling rate and so on were optimized for the complete formation and effective flotation of the complexes. And also four kinds of light solvents were compared each other to extract the floated complexes, effectively. After the pH was adjusted to 4.0 with 5 M HNO3, 8.0 mL of 0.05% acetone solution of dithizone was added to 1.00 L water sample. The dithizonate complexes were flotated and extracted into the upper methyl isobutylketone (MIBK) layer by the addition of 2.0 mL 0.2% ethanolic sodium lauryl sulfate solution and with the aid of small nitrogen gas bubbles. And this solvent sublation method was applied to the analysis of real water samples and good results of more than 85% recoveries were obtained in spiked samples.

• Journal of the East Asian Society of Dietary Life
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• v.23 no.6
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• pp.789-798
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• 2013

In the present study, optimization on ${\beta}$-glucanase-assisted extraction was made in order to isolate waxy barley starch from domestic cultivar using the D-optimal design suitable for response surface methodology (RSM). The results demonstrated that the amount of enzyme was found to be a major influencing factor on the extraction yield, which was substantially increased by increasing the amount of enzyme. It was also influenced by the reaction time and amount of water addition; however, the two factors were less influential than the amount of enzyme. The optimized condition by RSM for the reaction time was found to be 2.63 hours and amount of enzyme 1.7%, and amount of water addition 4.38 times the weight of raw material. With the enzyme treatment, the starch content in residues (R), particularly in R1 and R5, was reduced considerably, resulting in an increase in the extraction yield and therefore primarily and effectively releasing B-type starch small granule confirmed by scanning electronic microscopy. In addition, the study determined the physicochemical properties of isolated waxy starch (i.e., purity, water adsorption capacity, thermal properties, rheology and starch morphology) and compared them with those from the enzyme-not treated sample. It was found that they were almost similar to each other, except for the purity of starch, which was lower in the enzyme-treated sample than in the enzyme-not treated one.

• Analytical Science and Technology
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• v.29 no.5
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• pp.219-224
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• 2016

불산 중 극미량 음이온의 고상추출과 이온크로마토그래프를 이용한 고감도 분석법이 개발되었다. 불산 중 불소이온이 고상에 의해 제거하였고 이어서 음이온 (F⁻, CH₃COO⁻, Cl⁻, Br⁻, NO₃⁻, PO₄³⁻, SO₄²⁻)들이 이온크로마토그래프를 이용하여 연속적으로 분리하였다. 고상 추출법에 영향을 주는 각 인자들 (흡착제의 선택, 시료의 부피 및 pH, 용출 용액과 용출용액의 부피)을 결정하였으며 그 결과 흡착제로서 Oasis WAX 컬럼이 가장 우수하였고 1.0 mL의 시료부피, 용출용액으로 50 mM 초산암모늄염 5 mL가 분리능에서 가장 우수하였다. 개발한 방법에 의한 음이온 (Cl⁻, Br⁻, NO₃⁻, PO₄³⁻, SO₄²⁻)들의 방법검출한계는 25 % 불산용액 (w/w) 중에 0.04~0.30 µg/L의 범위를 보였고 정밀도는 20.0와 40.0 µg/L의 농도에서 5 % 이내를 보였다. 한 제조회사에 의한 25 % 불산 중 음이온의 4.2에서 47.5 µg/L의 범위로 모두 검출되었다. 이 방법은 시험절차가 간단하고, 재현성 및 감도가 좋아서 반도체회사에서 불산 중 음이온 불순물을 정도 관리하는데 매우 유용한 방법이 될 것으로 판단된다.

• Korean Journal of Food Science and Technology
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• v.35 no.4
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• pp.591-597
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• 2003

To compare the quality of genomic DNA extracted from potato for PCR detection, four different methods, such as silica-based membrane method, silica-coated bead method, STE solution treatment, and CTAB-phenol/chloroform method, were evaluated. Also, to remove an excessive carbohydrate from the potato, ${\alpha}$- and ${\beta}$-amylase were used individually and in combination. When used both silica-based membrane method and silica-coated bead method combined with enzymes, the genomic DNAs were extracted from the raw potato with high purity for PCR. However, the silica-coated head method combined with enzyme treatment was the most efficient for extraction of the genomic DNA from the frozen fried potatoes. When applied with STE solution, the highly purified DNA was extracted from the raw potatoes without enzyme treatment in adequate yield for PCR. In cases of processed potatoes, such as frozen-fried potato and fabricated potato chips, CTAB-phenol/chloroform method is mostly feasible for DNA extraction and PCR efficacy at high sensitivity. As the results of PCR amplification, 216bp of PCR product was detected on 2% agarose gel electrophoresis, but any amplicons derived from New leaf and New leaf Y gene was not detected in any sample.

• Applied Biological Chemistry
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• v.51 no.1
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• pp.11-16
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• 2008

The extraction conditions for resveratrol production from grape fruit stem, which is a by-product of grape processing, were optimized to develop high-functional grape-based products. Additionally, the bioefficacy of grape fruit stem extract (GFSE) as an antioxidant agent was evaluated. Resveratrol was extracted using various experimental conditions such as extractant type, extractant concentration, raw material-extractant ratio, extraction time and temperature, and the results were analyzed using a statistical program (SPSS). The resveratrol yield was the highest when 80% ethanol with a raw-material-extractant ratio of 1:10 (w/v) was used. In addition, the optimal temperature and time were selected as $60^{\circ}C$ and 90 min, respectively. When the antioxidant activity was analyzed and expressed as DPPH radical scavenging activity and SOD-like activity, the antioxidant activity of GFSE was higher than that of BHT, BHA and L-ascorbic acid. Finally, it was found that GFSE could be used as a raw material for the production of high antioxidant agents.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.221-221
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• 2013

Vertical LED (VLED) has been recognized as a way to obtain the high-power LED due to their advantages [1]. However, approximately 4% of the light generated from the active region is extracted, if the light extraction from side walls and back side is neglected because of Fresnel reflection (FR) and total internal reflection (TIR) [2,3]. In this study, the optical simulation of the VLED with the various microstructures was performed. Among them, the microlens having the diameter of 3 ${\mu}m$ and the height of 1.5 ${\mu}m$ shown the best result was chosen, and then, optimized microlens was formed on a GaN template using conventional semiconductor process. Various microstructures were proposed to improve the light extraction efficiency (LEE) of the VLED for the simulation. The LEE was simulated using LightTools based on a Monte Carlo ray tracing. The microstructures with hemisphere, cone, truncated and cylinder pattern having diameter of 3 ${\mu}m$ were employed on the top layer of the VLED respectively. The improvement of the LEE by using the microstructure is 87% for the hemisphere, 77% for the cone, 53% for the truncated, 21% for the cylinder, compared with the LEE of the flat surface at the reflectance of 85%. The LEE was increased by 88% at the height of 1.5 ${\mu}m$, compared with the LEE of the flat surface. We found that the microlens on the top layer is the most suitable for increasing the LEE. In order to apply the proposed microlens on n-GaN surface, we fabricated microlens on a GaN template. A photoresist array having hexagonal-closed packed microlens was fabricated on the GaN template. Then, optimization of etching the GaN template was performed using a dry etching process with ICP-RIE. The dry etching carried out using a gas mixture of Cl2 and Ar, each having a flow rate of 16 sccm and 10 sccm, respectively with RF power of 50 W, ICP power of 900 W and chamber pressure of 2 mTorr was the optimum etching condition as shown in Fig. 2(a).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.128-135
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• 2015

In this study, we develop the very short-term precipitation forecasting model as well as classifier based on polynomial radial basis function neural networks by using AWS(Automatic Weather Station) and KLAPS(Korea Local Analysis and Prediction System) meteorological data. The polynomial-based radial basis function neural networks is designed to realize precipitation forecasting model as well as classifier. The structure of the proposed RBFNNs consists of three modules such as condition, conclusion, and inference phase. The input space of the condition phase is divided by using Fuzzy C-means(FCM) and the local area of the conclusion phase is represented as four types of polynomial functions. The coefficients of connection weights are estimated by weighted least square estimation(WLSE) for modeling as well as least square estimation(LSE) method for classifier. The final output of the inference phase is obtained through fuzzy inference method. The essential parameters of the proposed model and classifier such ad input variable, polynomial order type, the number of rules, and fuzzification coefficient are optimized by means of Particle Swarm Optimization(PSO) and Differential Evolution(DE). The performance of the proposed precipitation forecasting system is evaluated by using KLAPS meteorological data.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.143-151
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• 2010

Fingerprint classification is a step to increase the efficiency of an 1:N fingerprint recognition system and plays a role to reduce the matching time of fingerprint and to increase accuracy of recognition. It is difficult to classify fingerprints, because the ridge pattern of each fingerprint class has an overlapping characteristic with more than one class, fingerprint images may include a lot of noise and an input condition is an exceptional case. In this paper, we propose a novel approach to design a stochastic model and to accomplish fingerprint classification using a directional characteristic of fingerprints for an effective classification of various qualities. We compute the directional value by searching a fingerprint ridge pixel by pixel and extract a directional characteristic by merging a computed directional value by fixed pixels unit. The modified Markov model of each fingerprint class is generated using Markov model which is a stochastic information extraction and a recognition method by extracted directional characteristic. The weight list of classification model of each class is decided by analyzing the state transition matrixes of the generated Markov model of each class and the optimized value which improves the performance of fingerprint classification using GA (Genetic Algorithm) is estimated. The performance of the optimized classification model by GA is superior to the model before the optimization by the experiment result of applying the fingerprint database of various qualities to the optimized model by GA. And the proposed method effectively achieved fingerprint classification to exceptional input conditions because this approach is independent of the existence and nonexistence of singular points by the result of analyzing the fingerprint database which is used to the experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1150-1158
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• 2010

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.41 no.4
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• pp.361-373
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• 2015

This study was carried out to evaluate the antioxidant and antibacterial activities of Glycyrriza uralensis Fisher (Jecheon, Korea) extracts obtained by various extraction conditions (85% ethanol, heating temperatures and times), and to establish the optimal extraction condition of G. uralensis for the application as cosmetic ingredients. The extracts obtained under different conditions were concentrated and made in the powdered (sample-1) and were the crude extract solutions without concentration (sample-2). The antioxidant effects were determined by free radical scavenging activity ($FSC_{50}$), ROS scavenging activity ($OSC_{50}$), and cellular protective effects. Antibacterial activity was determined by minimum inhibitory concentration (MIC) on human skin flora. DPPH free radical scavenging activity of sample-1 ($100{\mu}g/mL$) was 10% higher in group extracted for 6 h than 12 h, but sample-2 didn't show any significant differences. The extraction yield extracted with same temperature for 12 h was 2.6 times higher than 6 h, but total flavonoid content was 1.1 times higher. These results indicated that total flavonoid content hardly increased with increasing extraction time. Free radical scavenging activity, ROS scavenging activity and cellular protective effects were not dependent on the yield of extraction, but total flavonoid content of extraction. Antibacterial activity on three skin flora (S. aureus, B. subtilis, P. acnes)of sample-1 in different extraction conditions were evaluated on same concentration, and the group extracted at 25 and $40^{\circ}C$ showed 16 times higher than methyl paraben ($2,500{\mu}g/mL$). In conclusion, 85% ethanol extracts of G. uralensis extracted at $40^{\circ}C$ for 6 h showed the highest antioxidant and antibacterial activity. These results indicate that the extraction condition is important to be optimized by comprehensive evaluation of extraction yield with various conditions, yield of active component, and activity test with concentrations, and activity of 100% extract, for manufacturing process of products.