• Fisheries and Aquatic Sciences
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• v.17 no.1
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• pp.47-57
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• 2014

Thai Jasmine rice (Oryza sativa, long grain Indica var.) is popular in southeastern Asia and China due to its non-glutinous, fluffy texture and fragrant smell. However it has a high starch digestibility, which leads to an increased glycemic index (GI). Therefore it may require modified cooking methods for diabetes patients. The objectives of this study were to optimize the ratio of Thai Jasmine rice, sea tangle, and olive oil (CLTR) based on consumers' acceptance. The GI of plain cooked Thai Jasmine rice (CLR) was measured as a control. Sensory evaluation and response surface methodology were used to determine the optimal ratio. Texture analysis and nutritional evaluation were also performed on the optimal recipe of cooked Jasmine rice with sea tangle. A multiple regression equation was developed in quadratic canonical polynomial models. We used 26 trained Chinese panelists in their forties to rate color, flavor, adhesiveness, and glossiness, which we determined were highly correlated with overall acceptability. The optimal CLTR formula was 34.8% rice, 2.8% sea tangle, 61.9% water, and 0.5% olive oil. Compared to CLR, CLTR had a lower hardness, but a higher springiness and cohesiveness. However, CLR and CLTR had the same adhesiveness and chewiness. The addition of sea tangle and olive oil delayed retro-gradation of starch in CLTR and increased total dietary fiber, and protein and ash contents. The degree of gelatinization, and in vitro protein and starch digestibility of CLTR were lower than those of CLR. Based on Wolver' method, the GI of CLTR (52.9, incremental area under the glycemic-response curve, ignoring the area below fasting, as used for calculating the GI [Inc]) was lower compared with that of CLR (70.94, Inc), which indicates that CLTR is effective in decreasing and stabilizing blood glucose level, owing to its lower degree of gelatinization and starch digestibility. Our results show that CLTR can contribute to the development of a healthier meal for families and the fast food industry.

• Korean Journal of Food Science and Technology
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• v.22 no.5
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• pp.497-502
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• 1990

The effect of sugar concentration, immersion time and temperature on water loss, solid gain or loss, and sugar molality of potatoes during osmotic concentration was analyzed by a response surface methodology (RSM), and those values were predicted by using a second degree polynomial regression model. Effect of osmotic concentration and blanching on vitamin C retention of air dried potatoes (6% MC: wet basis) was also evaluated. The most significant factor was sugar concentration for water loss, solid gain or loss, sugar molality, rate parameter and retention of vitamin C. Second and third factors were immersion time and temperature respectively. Water loss and solid gain were rapid in the first 10 min and then levelled off. A 44.6% of water loss was observed during osmotic concentration using a sugar solution $(60\;Brix,\;80^{\circ}C$) with 20 min of immersion time. Dried potatoes after osmotic concentration had higher vitamin C content than dried potatoes after blanching. Optimum regions for osmotic concentration process of potatoes were $60-70^{\circ}C$ of immersion temperature, 60 Brix of sugar solution and 16-20 min of immersion time based on above 30% of water loss and 50% of vitamin C retention.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.1-8
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• 2007

In this paper, research on joint optimization of the image spatial registration and the exposure compensation is conducted. The exposure compensation is performed in a frame work of the intensity compensation based on the polynomial approximation of the relationship between images. This compensation is jointly combined with the registration problem employing the Gauss-Newton nonlinear optimization method. In this paper, to perform for a simple and stable optimization, the block-coordinate method is combined with the Gauss-Newton optimization and extensively compared with the traditional approaches. Furthermore, regression analysis is considered in the compensation part for a better stable performance. By combining the block-coordinate method with the Gauss-Newton optimization, we can obtain a compatible performance reducing the computational complexity and stabilizing the performance. In the numerical result for a particular image, we obtain a satisfactory result for 10 repeats of the iteration, which implies a 50% reduction of the computational complexity. The error is also further reduced by 1.5dB compared to the ordinary method.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.188-194
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• 2013

In this paper, we proposed a new method for pulmonary vessels image segmentation and refinement from pulmonary image. Proposed method consist of following five steps. First, threshold estimation is performed by polynomial regression analysis of histogram variation rate of the pulmonary image. Second, segmentation of pulmonary vessels object is performed by density-based segmentation method based on estimated threshold in first step. Third, 2D connected component labeling method is applied to segmented pulmonary vessels. The seed point of both side diaphragms is determined by eccentricity and size of component. Fourth step is diaphragm extraction by 3D region growing method at the determined seed point. Finally, noise cancelation of pulmonary vessels image is performed by 3D connected component labeling method. The experimental result is showed accurately pulmonary vessels image segmentation, the diaphragm extraction and the noise cancelation of the pulmonary vessels image.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.501-506
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• 2001

Computer modeling is essential to evaluate possible design of suspension for a railway vehicles. By creating a simulation, the engineers are able to assess the feasibility of a given design and change the design factors to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have turned to surrogate modeling. A surrogate model is essentially a regression performed on a data sampling of the simulation. In the most general sense, metamodels(surrogate model) take the form $y(x)=f(x)+{\varepsilon}$, where y(x) is the true simulation output, f(x) is the metamodel output, and $\varepsilon$ is the error between the two. In this paper, a second order polynomial equation is partially used as a metamodel to represent the forty-six dynamic performances for high speed train. The number of factors as design variables of the metamodel is twenty-nine, which are composed the dynamic characteristics of suspension. This metamodel is used to search the optimum values of suspension characteristics which minimize the dynamic responses for high speed train. This optimization is a multi-objective problem which have many design variables. This paper shows that the response surface model which is made through the design of analysis of computer experiments method is very efficient to solve this complex optimization problem.

• Food Science and Preservation
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• v.10 no.3
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• pp.314-319
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• 2003

This study was conducted to the optimize salting process of eggplant for development new product and enhancement quality for export. Three variables by five level central composite design and response surface methodology were used to determine optimum conditions for salting time, temperature and salt concentration. Optimization of the process was conducted using the combination of the moisture content, salinity and color of surface and inside of salted eggplant. The regression polynomial model was suitable (P>0.05) by Lack-of-Fit analysis with highly significant. To optimize the process, based on surface response and contour plots, the individual contour plots of the response variables were superimposed. The optimum conditions for this process were 6 days and 15$^{\circ}C$ at 30％ concentration under the optimum of restricted variables as moisture content was below 84％, salinity was below 14％, L and b value of surface were 10 to 20 and below 0, L value and b value of inside were 70 to 75 and 16 to 18.

• Food Science and Preservation
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• v.10 no.3
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• pp.320-325
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• 2003

This study was conducted to optimize sugaring process of yam for development of new snack product and enhancement acceptability. Three variables by five level central composite design and response surface methodology were used to determine optimum conditions for sugaring time, temperature and concentration. Optimization of the process was conducted using the combination of the moisture content, solid content, color and rehydration ratio. The regression polynomial model was suitable (P>0.05) model by Lack-of-Fit analysis with highly significant. To optimize the process, based on surface response and contour plots, superimposing the individual contour plots for the response variables. The optimum conditions for this process were 5.5 hours and 58％ at 40$^{\circ}C$ under the optimum of restricted variables as moisture content was 66 to 70, solid content was 25 to 30％, L value was above 75, a value was -2.1 to -2.4, b value was above 5 and rehydration ratio was 200 to 250.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.153-158
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• 2020

The present study identify the predictive power of confrontational naming and generative naming as screening tests for normal and early cognitive impairment. The subjects were analyzed for 203 healthy elderly, 106 mild cognitive impairment (MCI), 31 mild dementia. The confrontational naming was measured by the short-term Korean Boston Name Waiting Test, and the generative naming was measured by the Control Associative Word Test. As a result of polynomial logistic regression, both confrontational naming and generative naming had a significant effect on discriminating cognitive impairment (MCI, mild dementia) in general elderly (p<0.05). On the other hand, when distinguishing mild dementia from mild cognitive impairment, the generative naming-phonetic test had no significant odds ratio. The results of this study suggest that when discriminating mild dementia in mild cognitive impairment group, it is not meaningful to look only at the total score of generative naming test.

• 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.

• Journal of Korean Society of Forest Science
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• v.101 no.1
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• pp.53-61
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• 2012

This study developed a growth model for Larix leptolepis based on the WLS model to examine the effects of climate change on them. The site index was chosen as the dependent variable and location, weather, and edaphic factor were chosen as independent variables. Simulations were performed under three A1B climate change scenarios with the temperature ranging from $-3.3^{\circ}C$ to $+3.3^{\circ}C$. The simulation results showed that the site index decreased with peak at $-0.8^{\circ}C$. The decrease level of the site index by region was also analyzed. Each scenario, site index has decreased mostly but some region was increased. When the temperature increased up to $3^{\circ}C$, site index was decreased to everywhere.