• Korean Journal of Food Science and Technology
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• v.29 no.3
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• pp.509-515
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• 1997

Crude papain was extracted from papaya latex under various conditions. Extraction conditions of crude papain were optimized by the response surface methodology (RSM). Extraction yield of papain was affected by concentration of $NaHSO_3$, extraction time and pH. Three independent factors were chosen to determine their effects on the various responses and the function was expressed in terms of a quadratic polynomial equation, which measures the linear, quadratic and interaction effects. According to the results of RSM, the stationary point for quantitatively dependent variable was found to be the maximum point for extraction yield. Optimum conditions of papain extraction were 4% of $NaHSO_3$, 120 min of extraction time and pH 7.6. Under these conditions, 793.16 mg of papain per g latex was extracted from papaya latex.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.4
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• pp.321-327
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• 2017

In this study, to investigate the shape of the back bead as a weld quality parameter and to select the optimal condition of the root-pass TIG welding of a horizontal butt-joint, an experimental design and the response surface method (RSM) have been employed. Three parameters are used as input variables, which include the base current, peak current, and welding speed. The back bead width is selected as an output variable representing the weld quality, the target value of the width is 5.4 mm. Conducting the experiments according to the Box-Behnken experimental design, a $2^{nd}$ regression model for the back bead width was made, and the validation of the model was confirmed by using the F-test. The desirability function was designed through the nominal-the-best formula for the appropriate back bead width. Finally, the following optimal condition for welding was selected using the RSM: base current of 0.9204, peak current of 0.8676, and welding speed of 0.3776 in coded values. For verification, a test welding process under the optimal condition was executed and the result showed the back bead width of 5.38 mm that matched the target value well.

• Korean Chemical Engineering Research
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• v.50 no.3
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• pp.545-550
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• 2012

A 17-run Box-Behnken design (BBD) was used to optimize the extraction conditions of astaxanthin from shrimp waste. Three factors such as ratio of ethanol to raw material, extraction temperature ($^{\circ}C$) and extraction time (min) were investigated. The adjusted coefficient of determination ($R^2{_{adj}}$) for the model was 0.9218, and the probability value (p=0.0003) demonstrated a high significance for the regression model. The optimum extraction conditions were found to be: optimized ratio of ethanol to raw material 29.7, extraction temperature $49.5^{\circ}C$ and extraction time 59.9 min. Under these conditions, the mean extraction yield of astaxanthin was $17.80{\mu}g/g$, which was in good agreement with the predicted model value. Under these conditions, validation experiments were done and the mean extraction yield of astaxanthin was $17.77{\mu}g/g$, which is in good agreement with the predicted model value.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.2
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• pp.66-73
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• 2017

This study was to evaluate the influential parameters such as intial Cs concentration, reaction temperature, contact time and pH variation of solution on Cs adsorption. Using the experimental data, adsorption kinetics, isotherms and thermodynamic properties were analyzed. The Cs ion adsorption of the zeolite X was effective in the range from pH 5 to 10 and reached equilibrium after 60 minutes. The adsorption kinetics and isotherms of Cs ion with the zeolite X was described well by the pseudo-second-order kinetic and Langmuir isotherm model. The maximum adsorption capacities of Cs ion calculated from Langmuir isotherm model at 293~333 K were from 303.03 mg/g to 333.33 mg/g. It was found that thermodynamic property of Cs ion absorption on the zeolite X was spontaneous and endothermic reaction. The experimental data were fitted a second-order polynomial equation by the multiple regression analysis. The values of the dependent variable calculated by this best fitted model equation were in very good agreement with the experimentally obtained values.

• Applied Chemistry for Engineering
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• v.30 no.5
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• pp.615-619
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• 2019

Statistical design of experiments was performed to optimize MOF-235 synthesis process. Concentrations of terephthalic acid (TPA), iron (III) chloride hexahydrate, N,N-dimethylformamide (DMF) and ethanol were important factors to develop the crystal structure of MOF-235. MOF-235 was synthesized with various concentrations of the listed chemicals above and the crystallinity was measured by XRD. The effect of the composition on the synthesis of MOF-235 was evaluated using a statistical analysis. For the variance analysis using F-test, the concentration of ethanol showed the greatest effect on the crystallinity and TPA the least influential. A regression model for predicting the crystallinity of MOF-235 was derived and the prediction results for two synthetic variables were presented using contour plots. Finally, the crystallinity was predicted by a mixture method with $FeCl_3$, ethanol and DMF.

• Applied Chemistry for Engineering
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• v.35 no.4
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• pp.329-334
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• 2024

To improve the UV absorbance and emulsion stability of sunscreen creams prepared using refined seabuckton oil, experimental conditions were designed utilizing the central composite design model-response surface methodology (CCD-RSM). The amount of surfactant, emulsification time, and thickener amount were chosen as independent variables, and the experiment was carried out after the reaction values of ESI, MDS, and UV absorbance at 290 nm were determined. The main effect and interaction effect, which have the most influence on the response value, were analyzed through the F-value and P-value of the regression equation coefficient calculated through RSM, and the statistical significance of the coefficient was evaluated through the P-value. The optimal emulsification conditions using RSM were calculated as follows: amount of surfactant (4.39 wt%), emulsification time (25.42 min), and amount of thickener (1.24 wt%). At these conditions, the reaction value was calculated as ESI (98.5%), MDS (32.9 nm), and UV absorbance (2.73). As a result of conducting an actual experiment under the calculated optimal conditions, the average error rate was measured as ± 2.7%

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.3
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• pp.15-23
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• 2013

Weight reduction of a automobile has been steadily tried in automotive industry to improve fuel efficiency, driving performance and the production profits. Since the weight of BIW takes up a large portion of the total weight of the automobile, reducing the weight of BIW greatly contributes to reducing the total weight of the vehicle. To reduce weight, vehicle manufacturers have tried to apply lightweight materials, such as aluminum and high-strength steel, to the components of BIW instead of conventional steel. In this research, material arrangement of an automotive BIW was optimized by formulating a design problem to minimize weight of the BIW while satisfying design requirements about bending and torsional stiffness and perform a metamodel-based design optimization strategy. As a result of the design optimization, weight of the BIW is reduced by 45.7% while satisfying all design requirements.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.117-125
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• 2023

In the development of clothing design through virtual simulation, it is essential to minimize the differences between the virtual and the real world as much as possible. The most critical task to enhance the similarity between virtual and real garments is to find simulation parameters that can closely emulate the physical properties of the actual fabric in use. The simulation parameter optimization process requires manual tuning by experts, demanding high expertise and a significant amount of time. Especially, considerable time is consumed in repeatedly running simulations to check the results of applying the tuned simulation parameters. Recently, to tackle this issue, artificial neural network learning models have been proposed that swiftly estimate the results of drape test simulations, which are predominantly used for parameter tuning. In these earlier studies, relatively simple linear stiffness models were used, and instead of estimating the entirety of the drape mesh, they estimated only a portion of the mesh and interpolated the rest. However, there is still a scarcity of research on non-linear stiffness models, which are commonly used in actual garment design. In this paper, we propose a learning model for estimating the results of drape simulations for non-linear stiffness models. Our learning model estimates the full high-resolution mesh model of drape. To validate the performance of the proposed method, experiments were conducted using three different drape test methods, demonstrating high accuracy in estimation.

• Korean Journal of Food Science and Technology
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• v.45 no.2
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• pp.180-190
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• 2013

The purpose of this study was to determine the optimal amount of 2 ingredients, i.e., black barley flour ($X_1$), and olive oil ($X_2$), for the production of white pan bread from black barley flour. The experiment was designed according to the central composite design of response surface methodology, which showed 10 experimental points, including 2 replicates for black barley flour and olive oil. Significant differences were found in the results of the physical and mechanical properties analysis of each sample, including weight (p<0.05), volume (p<0.01), specific loaf volume (p<0.01), color L (p<0.01), color a (p<0.001), color b (p<0.05), hardness (p<0.001), springiness (p<0.01), cohesiveness (p<0.01), gumminess (p<0.001) and chewiness (p<0.05). Significant differences in the sensory measurements were observed in color (p<0.01), appearance (p<0.01), texture (p<0.05), taste (p<0.05) and overall quality (p<0.05). The optimum formulation, which was calculated using the numerical and graphical methods, was determined to be 18.00% black barley flour and 1.80% olive oil.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.36-51
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• 2012

The demand for a climatological dataset with a regular spaced grid is increasing in diverse fields such as ecological and hydrological modeling as well as regional climate impact studies. PRISM(Precipitation-Elevation Regressions on Independent Slopes Model) is a useful method to estimate high-altitude precipitation. However, it is not well discussed over the optimization of PRISM parameters and DEM(Digital Elevation Model) resolution in South Korea. This study developed the PRISM and then optimized parameters of the model and DEM resolution for producing a gridded annual average precipitation data of South Korea with 1km spatial resolution during the period 2000-2005. SCE-UA (Shuffled Complex Evolution-University of Arizona) method employed for the optimization. In addition, sensitivity analysis investigates the change in the model output with respect to the parameter and the DEM spatial resolution variations. The study result shows that maximum radius within which station search will be conducted is 67km. Minimum radius within which all stations are included is 31km. Minimum number of stations required for cell precipitation and elevation regression calculation is four. Optimizing DEM resolution is $1{\times}1km$. This study also shows that the PRISM output very sensitive to DEM spatial resolution variations. This study contributes to improving the accuracy of PRISM technique as it applies to South Korea.