• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.2
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• pp.71-76
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• 2008

Micro end-milling is one of effective technology that is able to do ultra-precision machining while increasing the productivity and has wide application field. But selection of machining condition is very difficult because of complicated machining mechanism. Therefore this study was carried out to select working factors to get the optimum surface roughness. Machining condition are depth of cut, feed rate and spindle revolution. The result of this study showed that Surface roughness was affected, in the other of depth of cut, spindle revolution, feed rate. And this study provided an regression equation relating surface roughness to working factors through Regression Analysis and determination coefficient of regression equation had a satisfactory reliability of 79%.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.163-170
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• 2007

In this paper, We propose a new technique for extraction of moving objects included in compressed video signal. Moving object extraction is used in several fields such as contents based retrieval and target tracking. In this paper, in order to extract moving object blocks, motion vectors and DCT coefficients are used selectively. The proposed algorithm has a merit that it is no need of perfect decoding, because it uses only coefficients on the DCT transform domain. We used three test video sequences in the computer simulation, and obtained satisfactory results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.195-202
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• 1995

This paper presents the calculating method of optimum correction mass within permissible vibration limits for rotating machinery in two-plane field balancing. Basic technique of this method based on influence coefficient method, is graphic vector composition that the resultant of two influence vectors obtained by trial mass have to be equilibrium with initial vibration vector in the each correction plane. Genetic algorithm which is a search algorithm based on the mechanics of natural selection and natural genetics is used for vector composition, and SUMT method is used to objective function which seeks optimum correction mass for balancing a rotor.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.7
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• pp.306-312
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• 2006

Support Vector Machine(SVM), of which the foundations have been developed by Vapnik (1995), is gaining popularity thanks to many attractive features and promising empirical performance. In this paper, we propose a new short-term load forecasting technique based on SVM. We discuss the input vector selection of SVM for load forecasting and analyze the prediction performance for various SVM parameters such as kernel function, cost coefficient C, and $\varepsilon$ (the width of 8 $\varepsilon-tube$). The computer simulation shows that the prediction performance of the proposed method is superior to that of the conventional neural networks.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.48 no.5
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• pp.369-371
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• 2003

Cyanidin 3-glucoside (C3G) content contained in the grains of blackish purple rice varieties, Heugjinjubyeo, Kilimheugmi, Heugnambyeo, Sanghaehy-anghyeolla, and the progenies derived from their crosses was evaluated by HPLC and UV-Vis spectroscopy. C3G content was higher in the range of 10-30% by using UV-Vis method compared to HPLC method. A significant linear relationship was, however, observed between two analytical methods. The correlation coefficient was 0.98. Thus, this results suggested that it would be able to use UV-Vis spectroscopy to determine C3G content which does not demanded precise value like selection.

• Advances in environmental research
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• v.3 no.2
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• pp.131-149
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• 2014

Two different model selection indices, the Akaike information criterion (AIC) and the coefficient of determination ($R^2$), are used to discriminate competing isotherm equations for aqueous pollutant removal systems. The former takes into account model accuracy and complexity while the latter considers model accuracy only. The five types of isotherm shape in the Brunauer-Deming-Deming-Teller (BDDT) classification are considered. Sorption equilibrium data taken from the literature were correlated using isotherm equations with fitting parameters ranging from two to five. For the isotherm shapes of types I (favorable) and III (unfavorable), the AIC favors two-parameter equations which can easily track these simple isotherm shapes with high accuracy. The $R^2$ indicator by contrast recommends isotherm equations with more than two parameters which can provide marginally better fits than two-parameter equations. To correlate the more intricate shapes of types II (multilayer), IV (two-plateau) and V (S-shaped) isotherms, both indices favor isotherm equations with more than two parameters.

• Korean Journal of Organic Agriculture
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• v.28 no.4
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• pp.459-475
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• 2020

This study analyzes weather derivatives as an alternative risk management tool to stabilize farm revenue to complement the existing crop insurance program which suffers from asymmetric information problems such as adverse selection, moral hazard, and verifiability. We estimated apple yield functions to observe the relationship between yields and weather indices such as temperature and precipitation. Based on the estimated yield functions we designed weather futures and options products underlying temperature and precipitation, and calculated the prices of futures and options by two different approaches, historical distribution and Monte Carlo simulation. We found that weather futures and options stabilize farm revenue based on the estimated four risk indicators: Coefficient of Variation, Value at Risk, Certainty Equivalence, and Risk Premium. As a result, weather derivatives could be considered as a potential farm risk management tool through studying more in legal and institutional strategies and developing various derivatives products.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.146-150
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• 2021

Plasma information based virtual metrology (PI-VM) that predicts wafer-to-wafer etch rate variation after wet cleaning of plasma facing parts was developed. As input parameters, plasma information (PI) variables such as electron temperature, fluorine density and hydrogen density were extracted from optical emission spectroscopy (OES) data for etch plasma. The PI-VM model was trained by stepwise variable selection method and multi-linear regression method. The expected etch rate by PI-VM showed high correlation coefficient with measured etch rate from SEM image analysis. The PI-VM model revealed that the root cause of etch rate variation after the wet cleaning was desorption of hydrogen from the cleaned parts as hydrogen combined with fluorine and decreased etchant density and etch rate.

• Journal of Korea Multimedia Society
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• v.24 no.12
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• pp.1614-1623
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• 2021

In this paper, the purpose is evaluation of the effect of using fractal feature in machine learning based pancreatic tumor classification. We used the data that Pancreas CT series 469 case including 1995 slice of benign and 1772 slice of malignant. Feature selection is implemented from 109 feature to 7 feature by Lasso regularization. In Fractal feature, fractal dimension is obtained by box-counting method, and hurst coefficient is calculated range data of pixel value in ROI. As a result, there were significant differences in both benign and malignancies tumor. Additionally, we compared the classification performance between model without fractal feature and model with fractal feature by using support vector machine. The train model with fractal feature showed statistically significant performance in comparison with train model without fractal feature.

• Journal of Bio-Environment Control
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• v.27 no.4
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• pp.277-284
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• 2018

For the main variables to be selected by the designer for the heating and cooling load calculation in greenhouses, in order to evaluate the effect of these design values on the heating and cooling load, the simulations were carried out by varying the respective design values. Based on these results, we proposed the design values which should pay special attention to selection. The design values which have the greatest effect on the heating load were the overall heat transfer coefficient of the covering material and the design outdoor temperature was next. The effect of the design values according to the number of spans showed little difference. In the case of the single-span greenhouse, the effect of the design values related to the underground heat transfer can not be ignored. However, in the case of the multi-span greenhouse, the effect of the design values related to the underground heat transfer and the infiltration rate were insignificant. The design values which have the greatest effect on the cooling load were the solar radiation into the greenhouse and the evapotranspiration coefficient, followed by the indoor and outdoor temperature difference and the ventilation rate. The effect of the design values showed a great difference between the single-span greenhouse and the multi-span greenhouse, but there was almost no difference according to the number of spans. The effect of the overall heat transfer coefficient of the covering material was negligible in both the single-span greenhouse and the multi-span greenhouse. However, the effect of the indoor and outdoor temperature difference and the ventilation rate on the cooling load was not negligible. Especially, it is considered that the effect is larger in multi-span greenhouse.