• Journal of Korea Water Resources Association
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• v.33 no.3
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• pp.365-374
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• 2000

This paper is to present the determination of the optimal Joss rate parameters and urnt bydrographs from the observed single rainfall-runoff event using optimization models coupled with a stochastic technique for the global solution. Two kinds of the linear program models are formulated to derive the optimal unit hydrographs and loss rate parameters for gaged basins; one mimmizes the summation of the absolute residual between predlCted and observed runoff ordinates and the other, the maximum absolute residuaL Multistart algorithm which is one or stochastic techniques for the global optimum is adopted to perturb the parameters of the loss rate equations. Multistart efficiently searches the feasIble region to identify the global optimlUll for loss rate parameters, which yields the optimal loss rate parameters and unit hydrograph for Kostiakov's, Plulip's, and Horton's equation. The unique unit hydrograph ordinates for a gIven rainfall-runoff event iS exclusrvely obtained WIth $\Phi$ index, but unit hydrograph ordinates depend upon the parameters [or each loss rate equations. The parameters of Green-Ampt's are determined through a trial and error method. In this paper the single rainfall-nmoff event observed from a watershed is considered to test the proposed method. The optimal unit hydrograph herein found has smaller deviations than the ones reported previously by other researchers.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.7-13
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• 2018

In the current study, we proposed an optimized brain-computer interface (BCI) which employed blind source separation (BBS) approach to remove noises. Thus motor imagery (MI) signal and steady state visual evoked potential (SSVEP) signal were easily to be detected due to enhancement in signal-to-noise ratio (SNR). Moreover, a combination between MI and SSVEP which is typically can increase the number of commands being generated in the current BCI. To reduce the computational time as well as to bring the BCI closer to real-world applications, the current system utilizes a single-channel EEG signal. In addition, a convolutional neural network (CNN) was used as the multi-class classification model. We evaluated the performance in term of accuracy between a non-BBS+BCI and BBS+BCI. Results show that the accuracy of the BBS+BCI is achieved $16.15{\pm}5.12%$ higher than that in the non-BBS+BCI by using BBS than non-used on. Overall, the proposed BCI system demonstrate a feasibility to be applied for multi-dimensional control applications with a comparable accuracy.

• Korean Journal of Food Science and Technology
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• v.32 no.3
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• pp.646-653
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• 2000

Using agar and waxy com starch as the wall material, we could encapsulate the purified fish oil. Firstly, we have developed a simple and sensitive method for the quantitative analysis of the microencapsulation yield using 5% cupric acetate pyridine solution. Then, the optimum conditions such as the ratio of [core material] to [wall material]$(X_1)$, the temperature of dispersion fluid$(X_2)$, and the emulsifier concentration$(X_3)$ for the microencapsulation process were determined by using response surface methodology(RSM). The regression model equation for the yield of microencapsulation(Y, %) of purified fish oil upon three kinds of independent variables could be predicted as follows; Y = 100.138621-0.735000$(X_1)$+0.840000$(X_1)(X_2)$+0.817500$(X_1)(X_3)$-0.852500$(X_2)(X_3)$. And the optimum conditions for the microencapsulation of the purified fish oil were the ratio of [core material] to [wall material] of 4.9 : 5.1(w/w), the emulsifier concentration of 0.48%, and dispersion fluid temperature of $19.4^{\circ}C$. The microcapsules containing the purified fish oil showed the highest storage stability at pH 7.0 and $20{\sim}25^{\circ}C$.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.46 no.2
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• pp.185-194
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• 2020

This study was conducted to find out the optimal extraction conditions to obtain extracts with a high content of ginsenosides and antioxidant activity using the ginseng berry. After extraction by stirring, ultrasound and microwave method using 70% ethanol and distilled water as solvents, the results of considering the content of ginsenoside Re and Rb1, total polyphenol content, antioxidant activity, and whether it is an environmentally friendly manufacturing method, it was confirmed that the microwave method using distilled water is good method of extraction. The optimization of extraction conditions for microwave method were made by response surface methodology (RSM). Microwave power (50 ~ 200 W, X1), solvent and ginseng berry ratio (5 ~ 20 times, X2) and the extraction time (30 ~ 120 s, X3) were used as independent variables. The model showed a good fit having a determination coefficient of the regression equation of 0.9 or more and a p-value less than 0.05. Estimated conditions for the maximized extraction of ginsenoside contents and total polyphenols were 200 w in microwave power, 20 times in solvent and ginseng berry ratio, and 90 s in extraction time. Predicted values at the optimum conditions were total polyphenols of 6.23 mg GAE/g, ginsenoside Re of 17.69 mg/g, and ginsenoside Rb1 of 16.01 mg/g. In the verification of the actual measurement the obtained values showed 6.33 mg GAE/g, 17.79 mg/g, and 15.59 mg/g, respectively, in good agreement with predicted values.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.141-141
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• 2013

We have generated the needle-typed nonthermal plasma jet by using an Ar gas flow at atmospheric pressure. Diagnostics of electron temperature anddensity is critical factors in optimization of the atmospheric plasma jet source in accordance with the gas flow rate. We have investigated the electron temperature and density of plasma jet by selecting the four metastable Ar emission lines based on the atmospheric collisional radiative model and radial profile characteristics of current density, respectively. The averaged electron temperature and electron density for this plasma jet are found to be ~1.6 eV and ~$3.2{\times}10^{12}cm^{-3}$, respectively, in this experiment. The densities of OH radical species inside the various bio-solutions are found to be higher by about 4~9 times than those on the surface when the argon bioplasma jet has been bombarded onto the bio-solution surface. The densities of the OH radicalspecies inside the DI water, DMEM, and PBS are measured to be about $4.3{\times}10^{16}cm^{-3}$, $2.2{\times}10^{16}cm^{-3}$, and $2.1{\times}10^{16}cm^{-3}$, respectively, at 2 mm downstream from the surface under optimized Ar gas flow 250 sccm.

• Applied Biological Chemistry
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• v.42 no.1
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• pp.58-62
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• 1999

Method to access qualities of brown sauce and optimize its cooking conditions was studied by sensory evaluation and response surface methodology. Cooks of an hotel, sauce experts, were selected as sensory panelists, and the brown sauce cooking conditions practically used in an hotel were adopted to prepare sauce samples for the sensory test. The cooking conditions were designed with two factors, i.e., one factor of roux contents with three levels and the other factor of cooking times with three levels, which were known as most important in sauce cooking. Sensory acceptance evaluation with intensity 7 grades was applied for several sauce attributes such as color, flavour, viscosity, taste and overall. Ability of each panel to perceive the differences between the brown sauces prepared under different cooking conditions was judged, and only data of the 9 panelists proved as reliable among the 12 panelists were reflected. The acceptances by different cooking conditions were found to be in the order of 11 > 9 > 13% roux contents and 8 > 9 > 7 hr cooking times. Response surface methodology was treated with second-order model on the sensory data and the optimum cooking conditions with the highest acceptances were $10.3{\sim}10.8%$ roux content and 8 hr cooking time.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.1
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• pp.1-11
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• 2005

Several Solid Freeform Fabrication Systems(SFFS) are commercialized in a few companies for rapid prototyping. However, they have many technical problems including the limitation of applicable materials. A new method of agile prototyping is required for the recent manufacturing environments of multi-item and small quantity production. The objectives of this paper include the development of a novel method of SFFS, the CAFL/sup VM/(Computer Aided Fabrication of Lamination for Various Material), and the manufacture of the various material samples for the certification of the proposed system and the creation of new application areas. For these objectives, the technologies for a highly accurate robot path control, the optimization of support structure, CAD modeling, adaptive slicing was implemented. However, there is an important problem with the conventional 2D lamination method. That is the inaccuracy of 3D model surface, which is caused by the stair-type surface generated in virtue of vertical 2D cutting. In this paper, We design the new control algorithm that guarantees the constant speed, precise positioning and tangential cutting on the 5DOF SFFS. We develop the tangential cutting algorithm to be controlled with constant speed and successfully implemented in the 5DOF CAFL/sup VM/ system developed in this paper. Finally, this paper confirms its high-performance through the experimental results from the application into CAFL/sup VM/ system.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.52-64
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• 1995

Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• Korean Journal of Construction Engineering and Management
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• v.10 no.5
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• pp.113-122
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• 2009

The domestic construction market started to expand steadily since 1970s. The building market which utilizes a sandwich panel with advantages of economical construction expenses and convenient construction has grown rapidly in recent years. However, the companies which specialize in constructing sandwich panels are relatively small or medium size, compared with other construction companies. As a result, studies on the improvement of productivity have not been conducted sufficiently. In this study, the construction sites of sandwich panel are investigated, and the work processes by each team are analyzed. Additionally, the productivity and the construction cost of each work group are analyzed by constructing a model using the Web-Cyclone. It analyzed sensitivities about change of productivity and work costs following in processing place of the panel which is one of the productivity effect factors, so it assayed the optimized productivity by each work group and work costs. Analysis showed that 30% of productivity has improved compared with the factory processing work group, and analysis of work costs showed that about 15% of work costs was increased. Also sensitivity analysis of opening ratio showed that the work costs optimization will be accomplished when about 20% of opening was processed from the factory.

• Journal of the Korean GEO-environmental Society
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• v.8 no.4
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• pp.19-25
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• 2007

Process analysis with ASM3 (Activated Sludge Model3) was performed to offer basic data for the optimization of aerated biofilter (ABF) process design and operation. This study was focused on the simulation of the nitrification reaction in ABF which was a part of the advanced nutrient treatment process using bio-adsorption. The ABF process has been developed for the removal of suspended solids and nitrification reaction in sewage. A GPS-X (General Purpose Simualtor-X) was used for the sensitivity analysis and operation assessment. Sensitivity of ASM3 parameters on ABF was analysed and 4 major parameters ($Y_A$, $k_{sto}$, ${\mu}_A$, $K_{A,HN}$) were determined by dynamic simulation using 70 days data from pilot plant operation. The optimized values were 0.14 for $Y_A$, 3.5/d for $k_{sto}$, 2.7/d for ${\mu}_A$ and 1.1 mg/L for $K_{A,HN}$, respectively. Simulation with optimized parameter values were conducted and TN, $NH_4{^+}-N$ and $NO_3{^-}-N$ concentrations were estimated and compared with measured data at the range of 10 min to 4 hrs of hydraulic retention time (HRT). The simulated results showed that optimized parameter values could represent the characteristics of ABF process. Especially, the ABF showed relatively high nitrification rate (60%) under very short HRT of 10 min. As a consequence, the ABF was thought to be successfully used in the site which having high variation of influent loading rate.