• Korean journal of food and cookery science
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• v.23 no.1 s.97
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• pp.1-8
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• 2007

Extraction conditions were optimized using response surface methodology for preparing high-quality, hot water extracts from cultivated Chrysanthemum indicum L. petals. A fractional factorial design was applied to investigate the effects of added sample ratio ($X_1$), extraction temperature ($X_2$) and extraction time ($X_3$) variables on extract properties, such as, soluble solid contents ($Y_1$), sugar content ($Y_2$), ?E ($Y_3$), turbidity ($Y_4$), total phenol ($Y_5$) and DPPH ($Y_6$). Second-order models were employed to generate a 3-dimensional response surface for dependent variables and their coefficients of determination ($R^2$) ranged from 0.8408${\sim}$0.9914. The range of optimum conditions at $80^{\circ}C$ extraction for maximize characteristics of hot water extracts was 2.3${\sim}$2.7 g and 9.2${\sim}$11.2 hr.

• Integrative Medicine Research
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• v.6 no.4
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• pp.388-394
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• 2017

Background: The present study optimized ultrasound-assisted extraction conditions to maximize extraction yields of glycyrrhizic acid from licorice. Methods: The optimal extraction temperature ($X_1$), extraction time ($X_2$), and methanol concentration ($X_3$) were identified using response surface methodology (RSM). A central composite design (CCD) was used for experimental design and analysis of the results to obtain the optimal processing parameters. Results: Statistical analyses revealed that three variables and the quadratic of $X_1$, $X_2$, and $X_3$ had significant effects on the yields and were followed by significant interaction effects between the variables of $X_2$ and $X_3$ (p<0.01). A 3D response surface plot and contour plots derived from the mathematical models were applied to determine the optimal conditions. The optimum ultrasound-assisted extraction conditions were as follows: extraction temperature, $69^{\circ}C$; extraction time, 34?min; and methanol concentration, 57%. Under these conditions, the experimental yield of glycyrrhizic acid was 3.414%, which agreed closely with the predicted value (3.406%). Conclusion: The experimental values agreed with those predicted by RSM models, thus indicating the suitability of the model employed and the success of RSM in optimizing the extraction conditions.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.275-282
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• 2006

System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolernce of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or etimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte Carlo simulation and got the probabilistic sensitivity. The sensitivity of structural response with respect to in constant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.

• Journal of the Korean Wood Science and Technology
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• v.39 no.1
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• pp.75-85
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• 2011

The main purpose of this study is to evaluate the potential of producing bioethanol from yellow poplar ($Liriodendron$ $tulipifera$) wood chips by oxalic acid pretreatment and to examine the pretreatment conditions by response surface methodology (RSM). Based on $2^3$ factorial design, adjusted variables were reaction temperature ($^{\circ}C$), residence time (min), and acid loading (g/g), and a series of distinct 15 experimental conditions was organized with duplication at central point (total 16 performances). After pretreatment, simultaneous saccharification and fermentation (SSF) was subjected on solid fraction with yeast strain $Pichia$ $stipitis$. Maximum ethanol yields of the most samples were measured at 72 hours and applied to RSM as a dependent variable. 9.7 g/${\ell}$ of ethanol was produced from the solid pretreated at $180^{\circ}C$ for 40 min with 0.013 g/g of oxalic acid loading. According to the response surface methodology, it was determined that the temperature is the most governing factor via statistic analysis.

• Journal of the Korean Statistical Society
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• v.36 no.4
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• pp.557-578
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• 2007

In Response Surface Methodology (RSM), rotatability is a natural and highly desirable property. For second order general correlated regression model, the concept of robust rotatability was introduced by Das (1997). In this paper a new measure of robust rotatability for second order response surface designs with correlated errors is developed and illustrated with an example. A comparison is made between the newly developed measure with the previously suggested measure by Das (1999).

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.03b
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• pp.143-148
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• 1999

Design optimization is performed to calculated the draw-bead force for satisfying the design re-quirements. For an analysis tool a rigid-plastic finite element method with modified membrane element is adopted. response surface methodology is utilized for constructing the approximation surface for the optimum searching of draw bead force in sheet metal forming process. the algorithm developed is ap-plied to a design of the draw bead forces in a deep drawing process. The results show that the design of process parameters is applicable in complex metal forming analysis. It is also noted that the present algo-rithm enhances the stable optimum solution with small times of optimization iteration.

• Journal of Korean Society for Quality Management
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• v.40 no.1
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• pp.49-59
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• 2012

In computer simulation models the output from the computer code is often deterministic, i.e., running the code twice with the same values for the input variables would give the same output. It is discussed why the response surface method with polynomial approximation for the true response function is a good approximation to the computer experiments model. A sequential strategy to find the proper reduced quadratic polynomial model is illustrated with a case study in the military war game computer simulation model.

• Journal of Korean Society for Quality Management
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• v.7 no.2
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• pp.22-28
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• 1979

The problem considered in this paper is to select the vital factor effect to the product quality through the experimental design and analysis of response surface, so as to control the quality improvement of industrial product. In this time, even through the mathematical model is unknown it could be applicable to control the quality of industrial products and to determine optimum operating condition for many technical fields, particulary, for industrial manufacturing process. When a set of data is available from an experimental design, it is often of interest 1:0 fit polynominal repression model in independent variables (eg, time, temperature, pressure, etc) the optimize the response variable (eg. yield, strength etc). This paper proposes a method known to obtain the optimum operating condition, and how to find the condition by using table of orthogonal array experiments, and optimization methodology of statistical model. A criterion can be applied determining to optimum operating conditions in manufacturing industry and improving the fit of response surface which may be used for prediction of responses and quality control of industrial products.

• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.413-424
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• 2010

Mixture experiments involve combining ingredients or components of a mixture and the response is a function of the proportions of ingredients which is independent of the total amount of a mixture. The purpose of the mixture experiments is to find the optimum blending at which responses such as the flavor and acceptability are maximized. We assume the quadratic or special cubic canonical polynomial model over the experimental region for a mixture since the current mixture is assumed to be located in the neighborhood of the optimal mixture. The cost of the mixture is proportional to the cost of the ingredients of the mixture and is the linear function of the proportions of the ingredients. In this paper, we propose mixture response surface methods to develop a mixture such that the cost is down more than ten percent as well as mean responses are as good as those from the current mixture. The proposed methods are illustrated with the well known the flare experimental data described by McLean and Anderson(1966).

• Clean Technology
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• v.23 no.4
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• pp.413-420
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• 2017

The batch experiments and response surface methodology (RSM) have been applied to the investigation of the Cs adsorption with zeolite X synthesized using coal fly ash generated from the thermal power plant. Regression equation formulated for Cs adsorption was represented as a function of response variables. The model was highly relevant because the decision coefficient ($r^2$) was 0.9630. It was confirmed from the statistical results that the removal efficiency of Cs was affected by the order of experimental factors as pH > Cs concentration > temperature. The adsorption kinetics were more accurately represented by a pseudo second-order model. The maximum adsorption capacity calculated from the Langmuir isotherm model was $151.52mg\;g^{-1}$ at 293 K. Also, according to the thermodynamic parameters calculated from Vant Hoff equation, it could be confirmed that the adsorption reaction was an endothermic reaction and a spontaneous process.