• Korean Journal of Food Science and Technology
• /
• v.38 no.6
• /
• pp.725-729
• /
• 2006

A method was developed for the determination of fructooligosaccharides and raffinose contents in infant formula. The samples were extracted and analyzed by liquid chromatography equipped with carbohydrate column and evaporative light scattering detector. The mobile phase used for the gradient mode was water-acetonitrile, at a flow rate of 1.0mL/min. The method showed a mean recovery of 95-99%, the relative standard deviation obtained in the precision study was 0.774-8.982%, the quantification and detection limits were 25-50mg/L.

• The Journal of the Korea Contents Association
• /
• v.10 no.7
• /
• pp.107-114
• /
• 2010

Color is a sense signal for human to perceive being through light, and the color is divided into chromatic color and achromatic color. Chromatic color has hue, intensity, and saturation, but achromatic color has only intensity among the properties of chromatic color and doesn't have hue and saturation. Therefore it is important to split colors of image into area for human to perceive colors and not to perceive ones based on vision of human being. In this paper, we find a function to split colors of image into chromatic region of chromatic color region and achromatic region of achromatic color region. First, the input image of RGB color space is converted into the image of HSI color space in consideration of human vision and get a binary image from the converted image. After then, a function to split colors into ROC(ROC: Region of chromatic.) and ROA(ROA:Region of achromatic) is yield. It is difficult to split color of a general image into ROC and ROA. Therefore, to get the chromatic area and achromatic area, we make gradient images to have all range of intensity and range of saturation and to have a little range of hue and yield the function. The evaluation is tested using subjective-quality by 50 non-experts for result images of test images and general images. The results of the proposed method get better 27.5~32.96% than these of the conventional method

• Progress in Medical Physics
• /
• v.9 no.3
• /
• pp.185-192
• /
• 1998

It is necessarily to evaluate the energy of X-ray emitted from linear accelerator in order to determine the accurate absorbed dose. The method of direct measurement for x-ray energy is very difficult and impractical. Therefore the method of using beam quality index is generally used. Several dosimetry protocols recommend the use of quality indices such as depth of dose maximum at radiation central axis, dose gradient, and dose level. The linear accelerator manufactures follow the recommendation as dosimetry protocols. The study was performed for us to select the most suitable parameter among the Quality indices as described above. For photon beams of 4, 6, 10, 15, and 21 MV nominal energies produced by four kinds of accelerators(Mitsubishi, Scanditronix, Siemens, Varian) in eleven institutions, We evaluated the x-ray energies obtained by the Quality indices as recommended by several dosimetry protocols and manufactures. Results showed that there were energy spreads according to the same accelerators and Quality indices even though nominal energies were same. It appeared that the percent depth dose at 10 cm (D$_{10}$(%)) gave the smallest deviation and spread of energies. As energies increased, the energy deviation increased for all the quality indices. It is desirable for the use of unified quality index to compare the evaluation of beam quality at different institutions.

• Journal of Food Hygiene and Safety
• /
• v.22 no.4
• /
• pp.370-374
• /
• 2007

An analytical method for the simultaneous determination of four tetracycline (oxytetracycline, tetracycline, chlortetracycline, doxycycline) in egg samples was developed and validated using liquid chromatography with ultraviolet detection. Egg samples were extracted by the liquid-liquid extraction based on acetonitrile. The chromatographic separation was achieved on a reverse phase C8 column with gradient elution using a mobile phase of 20 mM oxalic acid (pH 1.5)/acetonitrile. The procedure was validated according to the Food Drugs Administration guideline determining accuracy, precision, and limit of detection. Mean recovery of tetracyclines from spiked egg samples (50, 100, 200, 400, and $800{\mu}g/kg$) were 78.8-109.3%. Linearity in concentration range of $50-800{\mu}g/kg$ was obtained with the correlation coefficient $(r^2)$ of 0.994-0.999. The intra- and inter-day precision (relative standard deviation; RSD) was between 0.3-12.8 and 0.2-11.7%, respectively. Limit of detection (LOD) and limit of quantification (LOQ) for the investigated tetracyclines were 30 and $50{\mu}g/kg$ depending on egg samples, respectively. This method was reliable, sensitive, economical and suitable for routine monitoring of tetracycline residues in dairy egg.

• Journal of KIISE:Software and Applications
• /
• v.30 no.3_4
• /
• pp.326-338
• /
• 2003

The objective of a neural network design and model selection is to construct an optimal network with a good generalization performance. However, training data include noises, and the number of training data is not sufficient, which results in the difference between the true probability distribution and the empirical one. The difference makes the teaming parameters to over-fit only to training data and to deviate from the true distribution of data, which is called the overfitting phenomenon. The overfilled neural network shows good approximations for the training data, but gives bad predictions to untrained new data. As the complexity of the neural network increases, this overfitting phenomenon also becomes more severe. In this paper, by taking statistical viewpoint, we proposed an integrative process for neural network design and model selection method in order to improve generalization performance. At first, by using the natural gradient learning with adaptive regularization, we try to obtain optimal parameters that are not overfilled to training data with fast convergence. By adopting the natural pruning to the obtained optimal parameters, we generate several candidates of network model with different sizes. Finally, we select an optimal model among candidate models based on the Bayesian Information Criteria. Through the computer simulation on benchmark problems, we confirm the generalization and structure optimization performance of the proposed integrative process of teaming and model selection.

• Journal of Intelligence and Information Systems
• /
• v.10 no.1
• /
• pp.109-123
• /
• 2004

Corporate financial distress and bankruptcy prediction is one of the major application areas of artificial neural networks (ANNs) in finance and management. ANNs have showed high prediction performance in this area, but sometimes are confronted with inconsistent and unpredictable performance for noisy data. In addition, it may not be possible to train ANN or the training task cannot be effectively carried out without data reduction when the amount of data is so large because training the large data set needs much processing time and additional costs of collecting data. Instance selection is one of popular methods for dimensionality reduction and is directly related to data reduction. Although some researchers have addressed the need for instance selection in instance-based learning algorithms, there is little research on instance selection for ANN. This study proposes a genetic algorithm (GA) approach to instance selection in ANN for bankruptcy prediction. In this study, we use ANN supported by the GA to optimize the connection weights between layers and select relevant instances. It is expected that the globally evolved weights mitigate the well-known limitations of gradient descent algorithm of backpropagation algorithm. In addition, genetically selected instances will shorten the learning time and enhance prediction performance. This study will compare the proposed model with other major data mining techniques. Experimental results show that the GA approach is a promising method for instance selection in ANN.

• Journal of Korea Multimedia Society
• /
• v.8 no.11
• /
• pp.1496-1509
• /
• 2005

In this paper, an adaptive license plate recognition system which detects and recognizes license plate at real-time by using projected plane convolution and Decision Tree Classifier is proposed. And it was tested in circumstances which presence of complex background. Generally, in expressway tollgate or gateway of parking lots, it is very difficult to detect and segment license plate because of size, entry angle and noisy problem of vehicles due to CCD camera and road environment. In the proposed algorithm, we suggested to extract license plate candidate region after going through image acquisition process with inputted real-time image, and then to compensate license size as well as gradient of vehicle with change of vehicle entry position. The proposed algorithm can exactly detect license plate using accumulated edge, projected convolution and chain code labeling method. And it also segments letter of license plate using adaptive binary method. And then, it recognizes license plate letter by applying hybrid pattern vector method. Experimental results show that the proposed algorithm can recognize the front and rear direction license plate at real-time in the presence of complex background environments. Accordingly license plate detection rate displayed $98.8\%$ and $96.5\%$ successive rate respectively. And also, from the segmented letters, it shows $97.3\%$ and $96\%$ successive recognition rate respectively.

• Investigative Magnetic Resonance Imaging
• /
• v.5 no.2
• /
• pp.116-122
• /
• 2001

Purpose : To find sensitivity of MRI imaging methods to slow flow phantom study was performed with conventional Spin-Echo, gradient echo based Phase Contrast, fast GRASS, and heavily T2-weighted Fast Spin Echo pulse sequences. Materials and Methods : A siphon driven flow phantom was constructed with a ventriculo-peritoneal shunt catheter and a GE phantom to achieve continuous variable flow. Four different pulse sequences including Spin-Echo, Phase Contrast, GRASS and Heavily T2-weighted Fast Spin Echo were evaluated to depict slow flow in the range from 0.08 ml/min to 1.7 ml/min and to compare signal intensities between static fluid and flowing fluid. Results : In the slow flow above 0.17 ml/min conventional Spin-Echo showed superior apparent contrast between static and flowing fluid while GRASS was more sensitive to the very slow flow below 0.17 ml/mim. It was not accurate to calculate flow and velocity below 0.1 ml/min with a modified PC imaging. Conclusion : Four different MR pulse sequences demonstrated different sensitivity to the range of slow flow from 0.08 ml/min to 1.7 ml/min. This finding may be clinically useful to measure CSF shunt flow or detecting CSF collection and thrombosis.

• Journal of the Korean Chemical Society
• /
• v.58 no.6
• /
• pp.535-542
• /
• 2014

A simple and efficient preconcentration method was developed using three-phase liquid phase microextraction prior to HPLC-UV for simultaneous extraction and determination of tetracycline antibiotics (tetracycline, oxytetracycline, and chlortetracycline). The tetracycline antibiotics were separated simultaneously on a column ($C_8$, $3.0{\times}150mm$, $3{\mu}m$) with high selectivity and sensitivity using gradient elution. Under optimized conditions (extraction solvent, heptanal; pH of donor, 9.0; pH of acceptor, 1.0; stirring speed, 700 rpm; NaCl salt, 0%; and extraction time, 60 min), enrichment factors (EF) were between 5.6 and 22.3. The limit of detection (LOD) and limit of quantitation (LOQ) in the spiked urine matrix were in the concentration range of $0.08{\sim}0.8{\mu}g/mL$ and $0.4{\sim}1.6{\mu}g/mL$, respectively. The calibration curves were linear within the range of $0.1{\sim}32{\mu}g/mL$ with the square of the correlation coefficient being more than 0.995. The precision (as a relative standard deviation, RSD) and accuracy (as a relative recovery) within working range were 1.3~9.1% and 84~118%, respectively.

• Korean Journal of Food Science and Technology
• /
• v.52 no.1
• /
• pp.26-30
• /
• 2020

This study was undertaken to determine the characteristics of xanthoangelol, the major chalcone constituent derived from the extracts of different parts of Lespedeza bicolor. Xanthoangelol was isolated from the root extract using column chromatography and used as a standard for quantitative analysis. The structure of the isolated compound was established based on spectroscopic evidence. The HPLC-DAD method was validated for specificity, linearity, precision, accuracy, limit of detection, and limit of quantitation. The calibration curve of xanthoangelol had significant linearity (R²>0.9999). Limit of detection and limit of quantitation 0.018 and 0.059 ㎍/mL, respectively. The relative standard deviation values of precision test, and intra- and inter-day tests were less than 0.22 and 0.40%, respectively. In the recovery test, the accuracy ranged from 98.98-102.78% with RSD values less than 0.13%. The method validation parameters indicate the applicability of the HPLC method for quality control of food or drug formulations containing L. bicolor.