• Applied Chemistry for Engineering
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• v.34 no.4
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• pp.455-459
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• 2023

Three different optimization studies were conducted for the synthesis of MIL-100(Fe) and MIL-100(Fe)@COF using design of experiments. In the first study, the optimal concentration of precursors was determined using a mixture design method, and a modified molar ratio of 0.4155:0.2664:0.3182 was found to yield the highest crystallinity. In the second study, a central composite design was used to optimize the main factors of synthesis temperature and time with a synthesis temperature of 161℃ and a synthesis time of 12 hours. In the third study, a screening design method was used to determine the effect of five precursors on the formation of MIL-100(Fe)@COF, and the presence of characteristic peaks at 1552, 1483, and 1354 cm^-1 was found to be important for the existence of the COF structure. MIL-100(Fe)@COF synthesized with a modified molar ratio of 0.4831:0.4169:0.1 was predicted to exhibit optimal conditions.

• Korean Journal of Materials Research
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• v.33 no.4
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• pp.151-158
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• 2023

In this study, a new type of composite material combined with carbonyl iron, a relatively strong ferromagnetic material, was prepared to overcome the current application limitations of Prussian blue, which is effective in removing radioactive cesium. The surface of the prepared composite was analyzed using SEM and XRD, and it was confirmed that nano-sized Prussian Blue was synthesized on the particle surface. In order to evaluate the cesium removal ability, 0.2 g of the composite prepared for raw cesium aquatic solution at a concentration of 5 ㎍ was added and reacted, resulting in a cesium removal rate of 99.5 %. The complex follows Langmuir's adsorption model and has a maximum adsorption amount (q_e) of 79.3 mg/g. The Central Composite Design (CCD) of the Response Surface Method (RSM) was used to derive the optimal application conditions of the prepared composite. The optimal application conditions achieved using Response optimization appeared at a stirring speed of pH 7, 17.6 RPM. The composite manufactured through this research is a material that overcomes the Prussian Blue limit in powder form and is considered to be excellent economically and environmentally when applied to a cesium removal site.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.13 no.3
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• pp.22-33
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• 2005

Response Surface Method (RSM) constructs approximate response surfaces using sample data from experiments or simulations and finds optimum levels of process variables within the fitted response surfaces of the interest region. It will be necessary to get the most suitable response surface for the accuracy of the optimization. The application of RSM plan experimental designs. The RSM is used in the sequential optimization process. The first goal of this study is to improve the plan of central composite designs of experiments with various locations of axial points. The second is to increase the optimal efficiency applying a modified method to update interest regions.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.10a
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• pp.35-43
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• 2001

As the demands for lightweight construction and precision grow, there is an increasing interest on hydroforming technology. This paper deals with designing automobile subframe for applying welded blanks hydroforming. In applying welded blanks hydroforming to automobile subframe, it is a serious problem that blanks wrinkle in deformed shape. To suppress wrinklings in blanks, the sections of the die where blanks wrinkled is modified. In addition to this, it is intended that the sum of thickness variation about wrinkling regions be minimized. For this purpose, parameters for influencing formability are selected and evaluated using orthogonal array. Among these parameters, parameters having a major effect on formability are selected again. Using CCD(central composite design) with the selected parameters, response surface is build up and optimal design is performed.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.852-857
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• 2004

A new and efficient method for estimating the statistical moments of a system performance function has been developed. The method consists of two steps: (1) An approximate response surface is generated by a quadratic regression model, and (2) the statistical moments of the regression model are then calculated by experimental design techniques proposed by Seo and $Kwak^{(4)}$. In this approach, the size of experimental region affects the accuracy of the statistical moments. Therefore, the region size should be selected suitably. The D-optimal design and the central composite design are adopted over the selected experimental region for the regression model. Finally, the Pearson system is adopted to decide the distribution type of the system performance function and to analyze structural reliability.

• Journal of Microbiology and Biotechnology
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• v.15 no.1
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• pp.197-201
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• 2005

A novel chitinase-producing bacterial strain of Pantoea dispersa was isolated from the sea near Bhavnagar, India for efficient disposal of chitinous waste from the seafood processing industry. The medium components were optimized by using a cubic model in the central composite design for increasing chitinase production. The optimal concentrations for higher production of chitinase were (g l-1) chitin, 10.0; urea, 0.35; MgSO4 7H2O, 0.08, and CaCl2, 0.15. Here, peptone (0.05 g l-1) was used as a constant variant in all trials. Using a statistical optimization method, the chitinase production was found to increase from 108 to 486.4 units ml-1. Chitin was prepared from the crustacean waste, and Fourier Transform Infrared (FTIR) Spectroscopy was used to characterize the isolated chitin. Chitinous waste degradation was studied in terms of chitinase production.

• Biotechnology and Bioprocess Engineering:BBE
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• v.11 no.3
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• pp.251-257
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• 2006

The components of the media used to elicit the biosynthesis of $poly-{\gamma}-glutamic$ acid $({\gamma}-PGA)$ by Bacillus subtilis ZJU-7 were investigated, particularly the carbon and nitrogen sources Of the 7 carbon sources investigated, sucrose induced the highest rate of ${\gamma}-PGA$ productivity; among the nitrogen sources, tryptone had the best effect for ${\gamma}-PGA$ production. A $2^{6-2}$ fractional factorial design was used to screen factors that influence ${\gamma}-PGA$ production significantly, and a central composite design was finally adopted to formulate the optimal medium. ${\gamma}-PGA$ productivity improved approximately 2-fold when the optimal medium was used compared with the original nonoptimized medium, and volumetric productivity reached a maximum of 58.2 g/L after a 24-h cultivation period.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.3
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• pp.232-238
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• 2011

In the present study, Taguchi method is used to determine the rough region first, followed by RSM technique to determine the exact optimum value during milling on a machining center. A region reducing algorithm is applied to narrow down the region of the Taguchi method for RSM. The result from the Taguchi method is fed to train the artificial neural network (ANN), whose optimum value is used to drive the region reducing algorithm. The proposed algorithm is tested under different cutting condition and results show that the introduced algorithm works well during milling process. It is also shown that theoretically obtained optimal cutting condition is very close to experimentally obtained result.

• Journal of Microbiology and Biotechnology
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• v.22 no.1
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• pp.92-99
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• 2012

The optimal physical factors affecting enzyme production in an airlift fermenter have not been studied so far. Therefore, the physical parameters such as aeration rate, pH, and temperature affecting PLA-degrading enzyme production by Actinomadura keratinilytica strain T16-1 in a 3 l airlift fermenter were investigated. The response surface methodology (RSM) was used to optimize PLA-degrading enzyme production by implementing the central composite design. The optimal conditions for higher production of PLA-degrading enzyme were aeration rate of 0.43 vvm, pH of 6.85, and temperature at $46^{\circ}C$. Under these conditions, the model predicted a PLA-degrading activity of 254 U/ml. Verification of the optimization showed that PLA-degrading enzyme production of 257 U/ml was observed after 3 days cultivation under the optimal conditions in a 3 l airlift fermenter. The production under the optimized condition in the airlift fermenter was higher than un-optimized condition by 1.7 folds and 12 folds with un-optimized medium or condition in shake flasks. This is the first report on the optimization of environmental conditions for improvement of PLA-degrading enzyme production in a 3 l airlift fermenter by using a statistical analysis method. Moreover, the crude PLA-degrading enzyme could be adsorbed to the substrate and degraded PLA powder to produce lactic acid as degradation products. Therefore, this incident indicates that PLA-degrading enzyme produced by Actinomadura keratinilytica NBRC 104111 strain T16-1 has a potential to degrade PLA to lactic acid as a monomer and can be used for the recycle of PLA polymer.

• Journal of Dairy Science and Biotechnology
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• v.26 no.2
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• pp.51-56
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• 2008

Using central composite design, we have designed optimization of the manufacturing of processed butter. And response surface analysis by least-square regression was used Statistical Analysis System(SAS). Central composite design can be achieved by response surface techniques that allow flexibility in modeling and analysis. Response surface methodology(RSM) was used to optimize hardness(%) using as independent variables; the content of butter($X_1$), ranging from 50 to 90(%), the content of soybean oil($X_2$), from 0 to 20(%), and the hydrogenated soybean oil($X_3$) from 0 to 4(%). The results on the regression coefficients calculated for overrun by response surface by least-square regression(RSREG) were followed. It was considered that the linear regression was significant(p<0.01). As for the processed butter, the regression model equation for the hardness(Y, %) to the change of an independent variable could be predicted as follow: $Y=60.88-8.92X_2-{29.3X_2}^2$. The optimal for the manufacturing of processed butter were determined at the content of butter of 88.22%, soybean oil of 6.71% and hydrogenated soybean oil of 2.36%, respectively. Optimum compositions were resulted in hardness of 65.78 N. Finally the reference sample(Butter in the morning, Seoul Dairy Co-op.) and processed butter manufacturing under the optimal conditions were compared with spreadability test. The spreadability scores result from reference sample and butter under optimal conditions was not found a significant difference.