• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.5
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• pp.623-628
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• 2007

The accurate peak response estimation of a seismically excited structure with frictional damping system(FDS) is very difficult since the structure with FDS shows nonlinear behavior dependent on the structural period, loading characteristics, and relative magnitude between the frictional force and the excitation load. Previous studies have estimated that by replacing a nonlinear system with an equivalent linear one or by employing the response spectrum obtained based on nonlinear time history and statistical analysis. In the case that an earthquake load is defined with probabilistic characteristics, the corresponding response of the structure with FDS has probabilistic distribution. In this study, nonlinear time history analyses were performed for the structure with FDS subjected to artificial earthquake loads generated using Kanai-Tajimi filter. An equation for the probability density function (PDF) of the displacement response is proposed by adapting the PDF of the normal distribution. Finally, coefficients of the proposed PDF are obtained by regression analysis of the statistical distribution of the time history responses. Finally the correlation between PDFs and statistical response distribution is presented.

• Preventive Nutrition and Food Science
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• v.22 no.1
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• pp.37-44
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• 2017

Sulfur-containing amino acids play important roles in good flavor generation in Maillard reaction of non-enzymatic browning, so aqueous model systems of glucosamine and cysteine were studied to investigate the effects of reaction temperature, initial pH, reaction time, and concentration ratio of glucosamine and cysteine. Response surface methodology was applied to optimize the independent reaction parameters of cysteine and glucosamine in Maillard reaction. Box-Behnken factorial design was used with 30 runs of 16 factorial levels, 8 axial levels and 6 central levels. The degree of Maillard reaction was determined by reading absorption at 425 nm in a spectrophotometer and Hunter's L, a, and b values. ${\Delta}E$ was consequently set as the fifth response factor. In the statistical analyses, determination coefficients ($R^2$) for their absorbance, Hunter's L, a, b values, and ${\Delta}E$ were 0.94, 0.79, 0.73, 0.96, and 0.79, respectively, showing that the absorbance and Hunter's b value were good dependent variables for this model system. The optimum processing parameters were determined to yield glucosamine-cysteine Maillard reaction product with higher absorbance and higher colour change. The optimum estimated absorbance was achieved at the condition of initial pH 8.0, $111^{\circ}C$ reaction temperature, 2.47 h reaction time, and 1.30 concentration ratio. The optimum condition for colour change measured by Hunter's b value was 2.41 h reaction time, $114^{\circ}C$ reaction temperature, initial pH 8.3, and 1.26 concentration ratio. These results can provide the basic information for Maillard reaction of aqueous model system between glucosamine and cysteine.

• Food Science and Preservation
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• v.12 no.6
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• pp.617-623
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• 2005

Response surface methodology (RSM) was applied to microwave-assisted process (MAP) extraction for effective components from Mosla dianthera M. Microwave power (2,450 MHz, 0-160 W) and extraction time (1-5 min) were used as independent variables ($X_i$) for central composite design to yield 10 different extraction conditions. Optimum conditions were predicted for dependent variables of $75\%$ ethanol extracts, such as total yield($Y_1$), total phenolics($Y_2$), total flavonoids($Y_3$), and electron donation ability($Y_4$, EDA). Determination coefficients ($R^2$) of regression equations for dependent variables ranged from 0.8397 to 0.9801, and microwave power was observed to be more influential than extraction time in MAP. The maximal values of each dependent variable predicted at different extraction conditions of microwave power (W) and extraction time (min) were as follows; $6.76\%$ of total yield at 142.00 W and 4.36 min, 78.68 mg/g of total phenolics at 136.78 W and 4.40 min, 6.75 mg/g of total flavonoids at 159,69 W and 3.17 min, and $49.81\%$ of EDA at 133.87 W and 4.47 min, respectively. The superimposed contour maps for maximizing dependent variables illustrated the MAP conditions of 79 to 113 W in power and of 2.73 to 3.84 min in extraction time.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.3
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• pp.464-469
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• 2015

Response surface methodology (RSM) was used to monitor extraction characteristics of extracts from Sarcodon aspratus. Based on a central composite design, independent variables were microwave power (30~150 W), ethanol concentration (0~100%), and extraction time (1~9 min). Dependent variables were yield, electron-donating ability, total phenol contents, and SOD-like activity. Coefficients of determination ($R^2$) for dependent variables ranged from 0.80 at 0.97. The maximum extraction yield was 50.28% under conditions of 125.1 W microwave power, 18.67% ethanolic concentration, and 7.06 min extraction time. The maximum extraction electron-donating ability was 22.14% under conditions of 31.09 W, 45.76%, and 4.32 min. The maximum extraction total polyphenol content was 30.54 mg tannic acid equivalent/g at 122.54 W, 48.05%, and 8.36 min. The maximum extraction SOD-like activity was 33.44% at 121.17 W, 47.42%, and 8.41 min. Based on superimposition of four dimensional RSM with respect to extraction yield, electron-donating ability, total polyphenol content, and SOD-like activity obtained under various extraction conditions, optimum ranges of extraction conditions were found to be microwave power of 78~88 W, ethanol concentration of 39~57%, and extraction time of 3.5~9 min.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.46-56
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• 2018

This paper aimed to identify main factors of community characters, which have an effect on the land surface temperature(LST) change and estimate the impacting coefficient(ratio) of factors in a significant level of statistics. Chungcheongbuk-do province was selected and then partitioned into city and county areas for the sake of convenience of modeling. LST time series data and the community character data were developed based on Terra Satellite MODIS data and collected from the National Statistical Office, respectively. By the cause and effect relationship between community characters and LST, regression coefficients were estimated using a penal model. In a panel modeling, LST and community characters were used as a dependent variable and explanatory variables, respectively. Panel modeling analysis was carried out using statistical package STATA14 and one-way fixed effect model was selected as the most suitable model to evaluate the regression coefficients in the study area. The impacting ratio of LST change by any explanatory variable derived from the regression coefficients of the panel model fixed. Impacting ratios for industrial areas, elevation ${\times}$ building, energy usage, average window speed, non-urban management area, agricultural, nature and environmental conservation, average precipitation were 3.746, 2.856, 2.742, 0.553, 0.102, 0.071 and 0.003, respectively.

• Journal of Environmental Impact Assessment
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• v.20 no.5
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• pp.705-716
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• 2011

For the efficient discovery of knowledge and information from the observed systems, data mining techniques can be an useful tool for the prediction of water quality at intake station in rivers. Deterioration of water quality can be caused at intake station in dry season due to insufficient flow. This demands additional outflow from dam since some extent of deterioration can be attenuated by dam reservoir operation to control outflow considering predicted water quality. A seasonal occurrence of high ammonia nitrogen ($NH_3$-N) concentrations has hampered chemical treatment processes of a water plant in Geum river. Monthly flow allocation from upstream dam is important for downstream $NH_3$-N control. In this study, prediction models of water quality based on multiple regression (MR), artificial neural network and data mining methods were developed to understand water quality variation and to support dam operations through providing predicted $NH_3$-N concentrations at intake station. The models were calibrated with eight years of monthly data and verified with another two years of independent data. In those models, the $NH_3$-N concentration for next time step is dependent on dam outflow, river water quality such as alkalinity, temperature, and $NH_3$-N of previous time step. The model performances are compared and evaluated by error analysis and statistical characteristics like correlation and determination coefficients between the observed and the predicted water quality. It is expected that these data mining techniques can present more efficient data-driven tools in modelling stage and it is found that those models can be applied well to predict water quality in stream river systems.

• Advances in nano research
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• v.17 no.1
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• pp.33-49
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• 2024

Using the mechanical treatments for mechanical properties improvement was rarely in the development scope before. This research approves through analytical ways that surface impacts can improve the quality of the surface significantly. This fact is approved for deposited titanium on silicone substrate. The new algorithm called minimum resultant error method (MREM) which is a direct combination of nanoindentation, FEM and dimensional analysis through a reverse method is utilized to extract the mechanical characteristics of the coating surface before and after impact. This method is extended to the time dependent behavior of the material to obtain strain rate coefficient. To implement this new approach, a new analysis technic is developed to define the residual stress field caused by surface impact as initial condition for nanoindentation. Analyzing the model in micro and macro scale at the same time was one of the main resolved challenges in this study. The result was obtaining of the constants of Johnson-Cook constitutive equation. Comparing the characteristics of the coating surface before and after impact shows high improvement in yield stress (34%), Elastic modulus (7.75%) and strain hardening coefficient (2.8%). The main achievement is that the strength improvement in titanium thin layer is much higher than bulk titanium. The yield strength shows 41.7% improvement for coated titanium comparing with 24% for bulk material. The rate of enhancement is about 6 times when it comes to the Young's modulus.

• Food Science and Preservation
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• v.18 no.4
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• pp.546-551
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• 2011

Response surface methodology (RSM) was used for the microwave-assisted extraction (MAE) of the effective components of grape seed, such as its antioxidative and nitrite-scavenging abilities. Microwave power (2,450 MHz, 0-160W), ethanol concentration (0-100%), and MAE time (1-5 min) were used as independent variables (Xi) for the central composite design to yield 16 different MAE conditions. The optimum MAE conditions were predicted for the dependent variables of the extracts, such as the total phenolic content ($Y_1$) antioxidative ability ($Y_2$), and nitrite-scavenging ability ($Y_3$), depending on different microwave powers, ethanol concentrations, and MAE times. The determination coefficients ($R^2$) of the regression equations for the dependent variables ranged from 0.8024 to 0.9498. The maximal values of each dependent variable were predicted at different MAE conditions, as follows: 3.19% total phenolic content at 142.32W, 44.30% ethanol, and 4.36 min, and 1.22 antioxidative ability at 84.44W, 56.60% ethanol, and 3.28 min. More than 99.5% nitrite-scavenging ability was predicted at pH 1.2-3.0, 30.80-106.58W, 49.32-55.18% ethanol, and 3.72-4.58min, respectively. The results indicated that the total phenolic content and anti oxidative ability showed a higher correlation with each other in that they were more influenced by microwave power than by the other variables, while the nitrite-scavenging ability was largely influenced by the ethanol concentration.

• Journal of the Korean Society of Food Science and Nutrition
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• v.35 no.6
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• pp.780-785
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• 2006

The composition analysis of various radish (Rapharnus sativus L.) leaves and the effects of drying condition on the quality characteristics of hot-air dried radish leaves were carried out by a response surface methodology. Independent variables put in drying temperature $(X_1)$ and drying time $(X_2)$, dependent variables put in color, calcium, iron, vitamin, etc. In the proximate composition of radish leaves by varieties, there were no significant differences in the ash, protein, lipid, calcium and iron content of samples, but there were significant differences in the vitamins, chlorophyll and color value of samples. The quality characteristics on dried radish leaves by central composite design, it was significant value on the moisture content, chlorophyll and color value according to drying temperature and drying times. But there were no significant differences in the contents of calcium $(31.41{\sim}35.80\;mg/g,\;dry\;base)$ and iron $(0.21{\sim}0.29\;mg/g\;dry\;base)$. The multiplex regression coefficients analysis were calculated with independent variables $(X_1,\;X_2)$ and dependent variables (moisture, chlorophyll, color value). The calculated coefficient correlations for the each samples were $R^2>0.97$. The effects of drying temperature were greater than drying time in the total chlorophyll content changes of radish leaves. Based on the present study, the optimum drying condition for the lowest color changes and effective reduction of moisture of radish leaves were expected to be $5{\sim}6$ hours at $70^{\circ}C$.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.48 no.3
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• pp.255-264
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• 2022

The active ingredients of Napttegi Kong(GML, Glycine max landrace), a type of native rare soybeans, were identified, and an ultrasonic extraction method was introduced as an eco-friendly extraction method. Through the component analysis of the Napttegi Kong extract, the epicatechin, which was not found in conventional soybeans, was identified. For effective extraction using ultrasonic, the main extraction conditions were optimized using the response surface analysis method. Through the Box-Behnken design process, 15 experiments were conducted with the extraction temperature, the ratio of extraction solvent/solution, and extraction time as key independent variables. A quadratic regression equation for the two dependent variables, epicatechin content and total isoflavone content, was derived, and the coefficients of determination were found to be high as R² = 0.9939 and R² = 0.9844, respectively, confirming that the correlation showed high significance. The extraction conditions satisfying the maximum expectations of these two dependent variables were predicted. to be 40.4℃ of extraction temperature, 19.3 times of extraction solvent/solution, and 91 sec of extraction time. The expected value and the actual experimental value of the epikatechin content and the total isoflavone content were similar, so it was confirmed that this experimental method is a highly reliable optimization model.