• Journal of Korean Society of Environmental Engineers
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• v.33 no.3
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• pp.149-156
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• 2011

This experimental design and response surface methodology (RSM) have been applied to the investigation of the electro-UV-ultrasonic complex process for the disinfection of E. coli in the water. The disinfection reactions of electro-UV-ultrasonic process were mathematically described as a function of parameters power of electrolysis ($X_1$), UV ($X_2$), and ultrasonic process ($X_3$) being modeled by use of the Box-Behnken technique, which was used for fitting 2nd order response surface model. The application of RSM yielded the following regression equation, which is empirical relationship between the residual E. coli number (Ln CFU) in water and test variables in coded unit: residual E. coli number (Ln CFU) = 23.69 - 3.75 Electrolysis - 0.67 UV - 0.26 Ultrasonic - 0.16 Electrolysis UV + 0.05 Electrolysis Ultrasonic + 0.27 $Electrolysis^2$ + 0.14 $UV^2$ - 0.01 $Ultrasonic^2$). The model predictions agreed well with the experimentally observed result ($R^2$ = 0.983). Graphical 2D contour and 3D response surface plots were used to locate the optimum range. The estimated ridge of maximum response and optimal conditions for residual E. coli number (Ln CFU) using 'numerical optimization' of Design-Expert software were 1.47 Ln CFU/L and 6.94 W of electrolysis, 6.72 W of UV and 14.23 W of ultrasonic process. This study clearly showed that response surface methodology was one of the suitable methods to optimize the operating conditions and minimize the residual E. coli number of the complex disinfection.

• Journal of Digital Convergence
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• v.16 no.4
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• pp.95-105
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• 2018

This study empirically test the roles of network closure and structural hole on radical innovation in technological knowledge exchange network in Gumi cluster. In doing so, we build 2,550 firm network, transforming association*firm(2-mode) to firm*firm(1-mode) network data. In addition, in order to investigate firms' attributes, we conduct survey for 101 firms in Gumi cluster using random sampling, and finally collect 86 firm samples. For analysis, we use ridge regression since network density and efficiency, indices of network closure and structural hole respectively, has a high level of multicollinearity. The findings show that structural hole has a significant and positive impact on radical innovation, but network closure has a significant and negative impact on radical innovation. This study contributes to present an empirical evidence of debate on network closure and structural hole based on past conceptual discussions and literature review and further goes a long way towards strategy formulation to establish social capital in accomplishing radical innovation. Further research is required that pays closer attention to features of technological knowledge, innovation types and interaction between network closure and structural hole, directing efforts to structural characteristics of various networks.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.12
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• pp.1684-1688
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• 2017

Objective: From a review of published information on genetic association studies, a meta-analysis was conducted to determine the influence of the genes ${\kappa}-casein$ (CSN3) and ${\beta}-lactoglobulin$ (LGB) on milk yield traits in Holstein, Jersey, Brown Swiss, and Fleckvieh. Methods: The GLIMMIX procedure was used to analyze milk production and percentage of protein and fat in milk. Models included the main effects and all their possible two-way interactions; not estimable effects and non-significant (p>0.05) two-way interactions were dropped from the models. The three traits analyzed used Poisson distribution and a log link function and were determined with the Interactive Data Analysis of SAS software. Least square means and multiple mean comparisons were obtained and performed for significant main effects and their interactions (p<0.0255). Results: Interaction of breed by gene showed that Holstein and Fleckvieh were the breeds on which CSN3 ($6.01%{\pm}0.19%$ and $5.98%{\pm}0.22%$), and LGB ($6.02%{\pm}0.19%$ and $5.70%{\pm}0.22%$) have the greatest influence. Interaction of breed by genotype nested in the analyzed gene indicated that Holstein and Jersey showed greater influence of the CSN3 AA genotype, $6.04%{\pm}0.22%$ and $5.59%{\pm}0.31%$ than the other genotypes, while LGB AA genotype had the largest influence on the traits analyzed, $6.05%{\pm}0.20%$ and $5.60%{\pm}0.19%$, respectively. Furthermore, interaction of type of statistical model by genotype nested in the analyzed gene indicated that CSN3 and LGB genes had similar behavior, maintaining a difference of more than 7% across analyzed genotypes. These results could indicate that both Holstein and Jersey have had lower substitution allele effect in selection programs that include CSN3 and LGB genes than Brown Swiss and Fleckvieh. Conclusion: Breed determined which genotypes had the greatest association with analyzed traits. The mixed model based in Bayesian or Ridge Regression was the best alternative to analyze CSN3 and LGB gene effects on milk yield and protein and fat percentages.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.59-66
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• 2018

This study examined the correlation among topography, forest type, soil and geology in Inje area where landslides occurred during heavy rainfall from July 11 to July 18, 2006 to assess the landslide susceptibility. In order to assess the susceptibility of future landslides, landslides occurred in Inje area were classified into slide type and flow type, and slope angle, aspect, curvature, ridge and valley were extracted from the area. The landslide susceptibility was assessed by applying diameter class, age class, density, and forest type to Bayesianbased LR (Logistic Regression) model and WOE (Weight of Evidence) model, and the fitness of modeling was verified by predict rate curve. As the results of susceptibility assessment, using all landslides without no distintion, it was found that 75% of the LR model and 73% of the WOE model were fit in terms of the top 20% of the landslides. According to slide type and flow type in the top 20% of the landslides, it was found that 71% of the LR model and 69% of the WOE model were fit in terms of the slide type. Whereas, it was found that 86% of the LR model and 82% of the WOE model were fit in terms of the flow type. That is, the results of the LR model showed higher fitness than the results of the WOE model, and the fitness of the flow type was higher than that of the slide type. Consequently, it suggests that it is reasonable to assess and verify the landslide susceptibility according to the types of landslides.

• The Journal of Bigdata
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• v.6 no.1
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• pp.51-62
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• 2021

In the field of medical artificial intelligence, there have been a lot of researches on disease prediction and classification algorithms that can help doctors judge, but relatively less interested in artificial intelligence that can help medical consumers acquire and judge information. The fact that more than 150,000 questions have been asked about which hospital to go over the past year in NAVER portal will be a testament to the need to provide medical information suitable for medical consumers. Therefore, in this study, we wanted to establish a classification model that classifies 8 medical subjects for symptom text directly described by patients which was collected from NAVER portal to help consumers choose appropriate medical subjects for their symptoms. In order to ensure the validity of the data involving patients' subject matter, we conducted similarity measurements between objective symptom text (typical symptoms by medical subjects organized by the Seoul Emergency Medical Information Center) and subjective symptoms (NAVER data). Similarity measurements demonstrated that if the two texts were symptoms of the same medical subject, they had relatively higher similarity than symptomatic texts from different medical subjects. Following the above procedure, the classification model was constructed using a ridge regression model for subjective symptom text that obtained validity, resulting in an accuracy of 0.73.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.6
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• pp.642-652
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• 2008

The aim of our research was to apply experimental design methodology in the optimization condition of Photo-Fenton oxidation of the residual livestock wastewater after the coagulation process. The reactions of Photo-Fenton oxidation were mathematically described as a function of parameters amount of Fe(II)($x_1$), $H_2O_2(x_2)$ and pH($x_3$) being modeled by the use of the Box-Behnken method, which was used for fitting 2nd order response surface models and was alternative to central composite designs. The application of RSM using the Box-Behnken method yielded the following regression equation, which is an empirical relationship between the removal(%) of livestock wastewater and test variables in coded unit: Y = 79.3 + 15.61x$_1$ - 7.31x$_2$ - 4.26x$_3$ - 18x$_1{^2}$ - 10x$_2{^2}$ - 11.9x$_3{^2}$ + 2.49x$_1$x$_2$ - 4.4x$_2$x$_3$ - 1.65x$_1$x$_3$. The model predicted also agreed with the experimentally observed result(R$^2$ = 0.96) The results show that the response of treatment removal(%) in Photo-Fenton oxidation of livestock wastewater were significantly affected by the synergistic effect of linear terms(Fe(II)($x_1$), $H_2O_2(x_2)$, pH(x$_3$)), whereas Fe(II) $\times$ Fe(II)(x$_1{^2}$), $H_2O_2$ $\times$ $H_2O_2$(x$_2{^2}$) and pH $\times$ pH(x$_3{^2}$) on the quadratic terms were significantly affected by the antagonistic effect. $H_2O_2$ $\times$ pH(x$_2$x$_3$) had also a antagonistic effect in the cross-product term. The estimated ridge of the expected maximum response and optimal conditions for Y using canonical analysis were 84 $\pm$ 0.95% and (Fe(II)(X$_1$) = 0.0146 mM, $H_2O_2$(X$_2$) = 0.0867 mM and pH(X$_3$) = 4.704, respectively. The optimal ratio of Fe/H$_2O_2$ was also 0.17 at the pH 4.7.

• Korean Journal of Food Science and Technology
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• v.32 no.4
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• pp.843-850
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• 2000

We have produced the microcapsule composed of ${\alpha}-tocopherol$ as a core material (Cm) and the gelatinized polysaccharide as a wall material (Wm). Firstly, we have developed a simple, sensitive, and quantitative analysis method of the microencapsulation product using 5% cupric acetate pyridine solution. We could then optimize all the conditions for the microencapsulation process such as the ratio of [Cm] to [Wm], the temperature of dispersion fluid, and the emulsifier concentration using response surface methodology (RSM). As for the microencapsulation of ${\alpha}-tocopherol$, the regression model equation for the yield of microencapsulation (YM, %) to the change of an independent variable could be predicted as follows : YM=99.77-1.76([Cm]:[Wm])-1.72$([Cm]\;:\;[Wm])^2$. From the ridge of maximum response, the optimum conditions for the microencapsulation of ${\alpha}-tocopherol$ were able to be determined as the ratio of [Cm] to [Wm] of 4.6:5.4(w/w), the emulsifier concentration of 0.49%, and dispersion fluid temperature of $25.5^{\circ}C$, respectively. Finally, the microcapsules produced under the optimal conditions were applied for the analysis of storage stability. The optimal conditions for the storage were found to be the values of pH 9.0 and $25{\sim}35^{\circ}C$. And the storage stability of the microcapsules containing ${\alpha}-tocopherol$ were higher than 99% for a week at pH 9.0 and $25^{\circ}C$.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.1
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• pp.44-54
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• 2001

This study was conducted to estimate microclimate of natural deciduous forest in national forest of Pyungchang, Kangwon province and to investigate the effects of the microclimatic conditions on the periodic annual increment of diameter by site types. In this study, site was first classified by nine types considering both elevation (higher than 1,000 m, 700∼1,000 m, and lower than 700 m) and topographical conditions (ridge, slope and valley). For each of site types, diameter growth was measured by using increment borer and periodic annual increment of diameter was then analyzed. A topoclimatological technique, for estimating microclimatic conditions, which make use of empirical relationships between the topographical factor and the climatic normals in the study area was applied to produce monthly mean, maximum and minimum temperatures, relative humidity, precipitation and hours of sunshine. From these monthly estimtes, 17 weather variables such as warmth index, coldness index, index of aridity etc. which affect the diameter growth were computed for each of site types. The periodic annual increment of diameter was then correlated with and regressed on the 17 weather variables to examine effects of microclimatic conditions on the diameter growth by site types. From the correlation analysis, it was found that the diameter growth by site types was positively correlated with all of 17 weather variables except the warmth index. Especially, the conditions such as high relative humidity and large amount of sunshine hours provide favorable environment for the growth of diameter. On the other hand, it was also found that diameter growth was negatively iufluenced by warmth index. According to the regression analysis, the periodic annual increment of diameter could be well predicted by index of aridity and mean relative humidity for the growing season.