• Journal of the Korean Wood Science and Technology
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• v.44 no.1
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• pp.85-95
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• 2016

In this study, furfural, which is one of the value-added chemicals, was produced from the hydrolyzate of Quercus mongolica using dilute acid pretreatment, and the optimal pretreatment condition was determined by Response Surface Methodology (RSM) to obtain high yield of furfural. Based on Central Composite Design, the pretreatment experiment was designed with parameters such as reaction temperature ($X_1$), acid concentration ($X_2$), and reaction time ($X_3$) as independent variables, while dependent variable was furfural concentration (Y), and furfural yield (Z) was shown as percentage of Y per a dry weight basis. According to results of RSM, it was confirmed that reaction temperature ($X_1$) was the most influence factor and reaction temperature ($X_1$)-acid concentration ($X_2$) was the most significant interaction factor on furfural yield. Also, the optimal condition for the highest furfural yield was predicted at reaction temperature of $184^{\circ}C$, acid concentration of 1.17%, and reaction time of 5 min by RSM, and expected maximum yield of furfural was 6.37%. Experimentally, the maximum yield of furfural produced at above optimal condition was 6.21%, and it was considerably similar with the predicted value, and therefore the model for furfural production from the hydrolyzate of Quercus mongolica during dilute acid pretreatment could be built using RSM.

• Journal of the Korean GEO-environmental Society
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• v.14 no.5
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• pp.57-63
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• 2013

In this study, the characteristics of degradation and mineralization of diazinon using a statistical approach based on Box-Behnken design (BBD, one of response surface method) was investigated in an E-beam process, and also the main factors with diazinon concentration ($X_1$), irradiatin intensity ($X_2$) and pH ($X_3$) which consisted of 3 levels in each factor was set up to determine the effects of factors and optimization. At first, effects of pH and diazinon concentration were investigated to determine the proper range of application on response surface method(RSM). In statistical approach, the regression analysis and analysis of variance (ANOVA) were applied to evaluate the quantitative comparison of each factors in order to obtain the effects were irradiation intensity>diazinon concentration>pH. The regression model predicted the optimization point using the response optimizer to consider the effects of operation conditions were $Y_1=81.73-5.58X_1+23.69X_2-14.23X{_2}^2+4.22X{_3}^2(R^2=99.7%)$, $Y_2=35.23-3.01X_1+10.79X_2-7.58X_2{^2}(R^2=97.9%)$ and 95.7% of diazinon degradation, 41.8% of TOC reduction at 12.75mg/L and 4.26kGy, respectively. The pH condition was not significantly affects on E-beam process than other advanced oxidation processes (AOPs).

• Food Engineering Progress
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• v.14 no.2
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• pp.112-117
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• 2010

Black ginger, obtained from steaming and drying process, provides the various functional properties. This study was performed to investigate the optimum processing conditions for black ginger with high content of biologically active substance such as anti-oxidations. Optimum processing conditions such as temperature and time for black ginger was determined by response surface methodology (RSM) with manufacturing process and functionality. The optimum steaming condition was determined 6 hours at 93.2$^{\circ}C$, and 82.7 mg/L DPPH scavenging activities was obtained at this condition. The black ginger drink was made with black ginger extracts, Japanese apricot, and honey. Interaction effects of these ingredients were investigated by modified distance based on design and analyzed by linear, nonlinear regression model, and RSM. The optimization of mixture ratio was made by statistical modeling using DPPH scavenging activities and sensory properties which are the important target constraints in drink. Total flavonoids showed a linear canonical form, while preference and antiradical activity showed a nonlinear canonical form indicating the higher interaction among mixtures. The response trace plot revealed that antiradical activity, sensory properties and total flavonoids were quite sensitive to the drink blending. The optimum formulation of the drink was set at 14.2% of black ginger extracts, 5% of Japanese apricot, and 10.8% honey.

• Food Science of Animal Resources
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• v.32 no.6
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• pp.783-788
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• 2012

The aim of this study was to optimize the manufacturing condition of spreadable modified butter by RSM. Based on the central composite design, the degree of optimization was expressed as a SFC as a dependent variable (Y, %) determined by NMR with 23 experimental groups. Three independent variables were the contents of butter ($X_1$, 35-75%), the contents of grape seed oil ($X_2$, 15-35%), and the contents of hydrogenated soybean oil ($X_3$, 0-4%). As the result, SFC at $10^{\circ}C$ was ranged from 32.37 to 42.76%. In addition, the regression coefficients were calculated for SFC at $10^{\circ}C$ by RSREG. The regression model equation for the SFC was $Y=39.18-0.04X_1X_3$. Consequently, the optimal contents for manufacturing spreadable modified butter were determined as 55.18% for butter, 40.78% for grape seed oil, and 4.08% for hydrogenated soybean oil, respectively. The predicted response value for SFC at $10^{\circ}C$ was 30.20%, comparable to the actual experimental SFC value as 29.85%. Finally hardness and spreadability in reference butter and spreadable modified butter produced under the optimal conditions was measured. The hardness in spreadable modified butter was 31.80 N as compared to 69.92 N in reference butter. The spreadability in spreadable modified butter was 5.6 point as compared to reference butter. This difference may be due to the contents of solid fat by butter and hydrogenated soybean oil. This study showed that the SFC value at $10^{\circ}C$ could be a suitable indicator for the manufacturing spreadable modified butter to predict important attributes such as mouth feel, hardness and spreadability.

• Journal of Life Science
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• v.25 no.6
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• pp.680-685
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• 2015

Previously, cellulase and xylanase producing microorganism, Bacillus subtilis NC1, was isolated from soil. Based on the 16S rRNA gene sequence and API 50 CHL test the strain was identified as Bacillus subtilis, and named as B. subtilis NC1. We cloned and sequenced the genes for cellulase and xylanase. Plus, the deduced amino acid sequences from the genes of cellulase and xylanase were determined and were also identified as glycosyl hydrolases family (GH) 5 and 30, respectively. In this study to optimize the medium parameters for cellulase production by B. subtilis NC1 the RSM (response surface methodology) based on CCD (central composite design) model was performed. Three factors, tryptone, yeast extract, and NaCl, for N or C source were investigated. The cellulase activity was measured with a carboxylmethyl cellulose (CMC) plate and the 3,5-dinitrosalicylic acid (DNS) methods. The coefficient of determination (R²) for the model was 0.960, and the probability value (p=0.0001) of the regression model was highly significant. Based on the RSM, the optimum conditions for cellulase production by B. subtilis NC1 were predicted to be tryptone of 2.5%, yeast extract of 0.5%, and NaCl of 1.0%. Through the model verification, cellulase activity of Bacillus subtilis NC1 increased from 0.5 to 0.62 U/ml (24%) compared to the original medium.

• Smart Structures and Systems
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• v.14 no.5
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• pp.811-830
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• 2014

A numerical study has been carried out to simulate an innovative monitoring procedure to detect and localize damage in reinforced concrete beams retrofitted with carbon fiber reinforced polymer (CFRP) unidirectional laminates. The main novelty of the present simulation is its ability to conduct the electromechanical admittance monitoring technique by considerably compressing the amount of data required for damage detection and localization. A FEM simulation of electromechanical admittance-based sensing technique was employed by applying lead zirconate titanate (PZT) transducers to acquire impedance spectrum signatures. Response surface methodology (RSM) is finally adopted as a tool for solving inverse problems to estimate the location and size of damaged areas from the relationship between damage and electromechanical admittance changes computed at PZT transducer surfaces. This statistical metamodel technique allows polynomial models to be produced without requiring complicated modeling or numerous data sets after the generation of damage, leading to considerably lower cost of creating diagnostic database. Finally, a numerical example is carried out regarding a steel-reinforced concrete (RC) beam model monotonically loaded up to its failure which is also retrofitted by a CFRP laminate to verify the validity of the present metamodeling monitoring technique. The load-carrying capacity of concrete is predicted in the present paper by utilizing an Ottosen-type failure surface in order to better take into account the passive confinement behavior of retrofitted concrete material under the application of FRP laminate.

• Journal of the Korean Dietetic Association
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• v.26 no.1
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• pp.1-13
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• 2020

This study was undertaken to optimize preparation of sweet rice muffins using lotus (Nelumbo nucifera Gaertn) seed powder. The experimental conditions used in the preparation included lotus seed powder (X₁) and soybean oil (X₂). The muffin formulation was optimized using rheology. Lightness (P<0.01) displayed a quadratic model pattern, whereas yellowness (P<0.01) and redness (P<0.05) was presented a linear model. Texture properties significantly differed in cohesiveness (P<0.05). Evaluating the sensory characteristics of muffins, except for flavor and texture, the remaining properties of color (P<0.01), taste, overall quality, and appearance (P<0.05) were found to be significantly different. The overall quality was also affected by the proportion of lotus seed powder, rather than the amount of soybean oil. The optimal ratio for palatability of muffins was determined to be 47.80 g lotus seed powder and 95.28 g soybean oil. Taken together, our results indicate that sweet rice muffins prepared using lotus seed powder are sufficiently competitive in terms of function and quality.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.54-67
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• 2005

This paper provides an evaluation of an optimization-based, multiple-input double-output (MIDO) run-to-run (R2R) control scheme for general semiconductor manufacturing processes. The controller in this research, termed adaptive dual response optimizing controller (ADROC), can serve as a process optimizer as well as a recipe regulator between consecutive runs of wafer fabrication. In evaluation, it is assumed that the equipment model could be appropriately described by a pair of second-order polynomial functions in terms of a set of controllable variables. Of practical relevance is to consider a drifting effect in the equipment model since in common semiconductor practice the process tends to drift due to machine aging and tool wearing. We select a typical application of R2R control to chemical mechanical planarization (CMP) in semiconductor manufacturing in this evaluation, and there are five different CMP process scenarios demonstrated, including mean shift, variance increase, and IMA disturbances. For the controller, ADROC, an on-line estimation technique is implemented in a self-tuning (ST) control manner for the adaptation purpose. Subsequently, an ad hoc global optimization algorithm based on the dual response approach, arising from the response surface methodology (RSM) literature, is used to seek the optimum recipe within the acceptability region for the execution of next run. The main components of ADROC are described and its control performance is assessed. It reveals from the evaluation that ADROC can provide excellent control actions for the MIDO R2R situations even though the process exhibits complicated, nonlinear interaction effects between control variables, and the drifting disturbances.

• Korean Chemical Engineering Research
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• v.48 no.5
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• pp.589-597
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• 2010

Strengthening the regulation standard of biological nutrient in wastewater treatment plant(WWTP), the necessity of repair of WWTP which is operated in conventional activated sludge process to advanced nutrient removal treatment is increased. However, in full-scale wastewater treatment system, it is not easy to fine the optimized operational condition of the advanced nutrient removal treatment through experiment due to the complex response of various influent conditions and operational conditions. Therefore, in this study, an upgrading design of conventional activated sludge process to advanced nutrient removal process using the modeling and simulation method based on activated sludge model(ASMs) is executed. And a design optimization of advanced treatment process using the response surface method(RSM) is carried out for statistical and systematic approach. In addition, for the operational optimization of full-scale WWTP, a correct analysis about kinetic variables of wastewater treatment is necessary. In this study, through partial least square(PLS) analysis which is one of the multivariable statistical analysis methods, a correlation between the kinetic variables of wastewater treatment system is comprehended, and the most effective variables to the advanced treatment operation result is deducted. Through this study, the methodology for upgrading design and operational optimization of advanced treatment process is provided, and an efficient repair of WWTP to advanced treatment can be expected reducing the design time and costs.

• Clean Technology
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• v.28 no.3
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• pp.218-226
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• 2022

As a result of the recent social transformation towards a hydrogen economy and carbon-neutrality, the demands for hydrogen energy have been increasing rapidly worldwide. As such, eco-friendly hydrogen production technologies that do not produce carbon dioxide (CO₂) emissions are being focused on. Among them, ammonia (NH₃) is an economical hydrogen carrier that can easily produce hydrogen (H₂). In this study, Ru/Al₂O₃ catalyst coated onmetallic monolith for hydrogen production from ammonia was prepared by a dip-coating method using a catalyst slurry mixture composed of Ru/Al₂O₃ catalyst, inorganic binder (alumina sol) and organic binder (methyl cellulose). At the optimized 1:1:0.1 weight ratio of catalyst/inorganic binder/organic binder, the amount of catalyst coated on the metallic monolith after one cycle coating was about 61.6 g L^-1. The uniform thickness (about 42 ㎛) and crystal structure of the catalyst coated on the metallic monolith surface were confirmed through scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis. Also, a numerical optimization regression equation for NH3 conversion according to the independent variables of reaction temperature (400-600 ℃) and gas hourly space velocity (1,000-5,000 h^-1) was calculated by response surface methodology (RSM). This model indicated a determination coefficient (R²) of 0.991 and had statistically significant predictors. This regression model could contribute to the commercial process design of hydrogen production by ammonia decomposition.