• Mycobiology
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• v.47 no.4
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• pp.512-520
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• 2019

Statistical experimental methods were used to optimize the medium for mass production of a novel laccase3 (Lac3) by recombinant Saccharomyces cerevisiae TYEGLAC3-1. The basic medium was composed of glucose, casamino acids, yeast nitrogen base without amino acids (YNB w/o AA), tryptophan, and adenine. A one-factor-at-a-time approach followed by the fractional factorial design identified galactose, glutamic acid, and ammonium sulfate, as significant carbon, nitrogen, and mineral sources, respectively. The steepest ascent method and response surface methodology (RSM) determined that the optimal medium was (g/L): galactose, 19.16; glutamic acid, 5.0; and YNB w/o AA, 10.46. In this medium, the Lac3 activity (277.04 mU/mL) was 13.5 times higher than that of the basic medium (20.50 mU/mL). The effect of temperature, pH, agitation (rpm), and aeration (vvm) was further examined in a batch fermenter. The best Lac3 activity was 1176.04 mU/mL at 25 ℃, pH 3.5, 100 rpm, and 1 vvm in batch culture.

• Microbiology and Biotechnology Letters
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• v.32 no.4
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• pp.317-321
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• 2004

We selected a solvent for producing antioxidants from sporophyll of Undaria pinnatOptimum extraction condition for antioxidant ability(Y) of sporophyll of U. pinnatifida was investigated using response surface methodology(RSM). A compound central design was used with variables ($X_1$)temperature($^{\circ}C$) (3.4; 20; 60; 100; 116.6); ($X_2$) pH(1.8; 3; 6; 9; 10.2) and ($X_3$) treatment time(min) (1.7; 10; 30; 50; 58.3). Antioxidant activities were increased with decreasing pH and increasing temperature. The optimal extraction conditions for antioxidant ability(Y) of sporophyll of U. pinnatifida were found to be temperature $51.55^{\circ}C$, pH 4.2 and treatment time 28.2 min. Among the variables tested, pH showed greater significant facin extraction of antioxidants from sporophyll of U. pinnatifida.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.375-381
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• 2005

Usually genetic algorithms are used to design optimal system. However the performance of the algorithm is determined by the fitness function and the system environment. It is expected that a co-evolutionary algorithm, two populations are constantly interact and co-evolve, is one of the solution to overcome these problems. In this paper we propose three types of co-evolutionary algorithm to solve GA-Hard problem. The first model is a competitive co-evolutionary algorithm that solution and environment are competitively co-evolve. This model can prevent the solution from falling in local optima because the environment are also evolve according to the evolution of the solution. The second algorithm is schema co-evolutionary algorithm that has host population and parasite (schema) population. Schema population supply good schema to host population in this algorithm. The third is game model-based co-evolutionary algorithm that two populations are co-evolve through game. Each algorithm is applied to visual servoing, robot navigation, and multi-objective optimization problem to verify the effectiveness of the proposed algorithms.

• Korean Journal of Agricultural Science
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• v.45 no.2
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• pp.283-289
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• 2018

Agricultural gear reducers are used in a variety of agricultural machinery designs such as in agricultural tractors and transport cars, and even greenhouses. For greenhouses, a gear reducer is used to control windows on the side and the roof. Gear reducers for agricultural applications are designed using the empirical method because of the lack of a standard for experimentation. Simulation is necessary for the optimal design of an agricultural gear reducer. There are many advantages to this optimization such as low-cost maintenance, reduced size, and weight. In this study, bending and contact safety factor simulation for the gear reducer of a greenhouse was conducted by decreasing the face widths of helical gear shaft 2 and shaft 3 from 30.8 and 30 mm, respectively, at an interval of 4 mm. The bending and contact safety factors were calculated using AGMA standard. Simulation results showed that bending and contact safety factors decreased rapidly when the face width of the helical gear on shaft 2 was 30 mm and the face width of helical gear on shaft 3 decreased from 30.8 mm to 26.8 mm, suggesting that it would be safe to reduce the face width of the helical gear on shaft 3 to 26.8 mm. The reduction of the face width also reduced the weight of the agricultural gear. This study suggests that the agricultural gear reducer safety factor decreases as the face width decreases.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.6
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• pp.341-348
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• 2019

The purpose of this study is to model and analyze retractable large spatial structures by applying parametric modeling techniques. The modeling of wind loads in the analysis of typical structures including curved surfaces can be error-prone, and the processing time increases dramatically when there are many types of variables. However, the method based on StrAuto that was developed in previous research, facilitates the efficacious assignment of wind loads to structures and the rapid arrival of conclusions. As a result, it is possible to compare alternatives with various loads, including wind loads, to determine an optimal alternative much faster than the existing process. Further, it is almost impossible to directly input the wind load by calculating the area of an irregularly curved surface. However, the proposed method automatically assigns the wind load, which allows for automatic optimization in a structural analysis system. The approach was applied and optimized using several models, and the results are presented.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.513-520
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• 2004

A steady-state/transient performance simulation model was newly developed for the propulsion system of the CRW (Canard Rotor Wing) type UAV (Unmanned Aerial Vehicle) during flight mode transition. The CRW type UAV has a new concept RPV (Remotely Piloted Vehicle) which can fly at two flight modes such as the take-off/landing and low speed forward flight mode using the rotary wing driven by engine bypass exhaust gas and the high speed forward flight mode using the stopped wing and main engine thrust. The propulsion system of the CRW type UAV consists of the main engine system and the duct system. The flight vehicle may generally select a proper type and specific engine with acceptable thrust level to meet the flight mission in the propulsion system design phase. In this study, a turbojet engine with one spool was selected by decision of the vehicle system designer, and the duct system is composed of main duct, rotor duct, master valve, rotor tip-jet nozzles, and variable area main nozzle. In order to establish the safe flight mode transition region of the propulsion system, steady-state and transient performance simulation should be needed. Using this simulation model, the optimal fuel flow schedules were obtained to keep the proper surge margin and the turbine inlet temperature limitation through steady-state and transient performance estimation. Furthermore, these analysis results will be used to the control optimization of the propulsion system, later. In the transient performance model, ICV (Inter-Component Volume) model was used. The performance analysis using the developed models was performed at various flight conditions and fuel flow schedules, and these results could set the safe flight mode transition region to satisfy the turbine inlet temperature overshoot limitation as well as the compressor surge margin. Because the engine performance simulation results without the duct system were well agreed with the engine manufacturer's data and the analysis results using a commercial program, it was confirmed that the validity of the proposed performance model was verified. However, the propulsion system performance model including the duct system will be compared with experimental measuring data, later.

• Korean Journal of Food Science and Technology
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• v.35 no.2
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• pp.222-228
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• 2003

Optimum extraction conditions for yield, browning color, electron-donating ability, nitrite-scavenging effect, total polyphenol content, and tyrosinase-inhibitory activity of Flammulina velutipes were determined using response surface methodology through central composite design. Yield of F. velutipes was affected by ethanol concentration, and browning color improved more with the increase of ethanol concentration than microwave power. Nitrite-scavenging effect was improved with increasing ethanol concentration and decreasing microwave power. Electron-donating ability and total polyphenol content were improved with increasing ethanol concentration and microwave power. Tyrosinase-inhibitory effect increased more with decrease in microwave power than with ethanol concentration. The optimal range of extraction conditions for effective component of F. velutipes were $47.21{\sim}76.05$ watt of microwave power, $10.25{\sim}43.56%$ of ethanol concentration, and 5.72 min of extraction time.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.2
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• pp.247-252
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• 2015

The majority of electric power in the domestic manned islands with off-grid power system is supplied by the diesel generators. However, in the case of off-grid islands the fuel cost is more expensive to inland areas and difficult to transport them to islands. So the development of renewable energy system using natural resource have been recently introduced. But renewable energy that depend on the natural environment, it is necessary to organized the hybrid system with existing diesel engine because the energy is difficult to maintain stable electric power. This paper presents the results of a feasibility study of hybrid system with energy storage system such as wind, solar, battery and diesel engine. The study included off-grid island as the Seogeochado islands located in Jeolanamdo Province. And, the paper proposed a optimal capacity of hybrid system configuration to maintain carbon free with minimum investment cost. the analysis of economic adaptability performed by HOMER program.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.433-440
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• 2014

In this study, a method for the low-carbon active distribution system (ADS) planning is proposed. It takes into account the impacts of both network capacity and demand correlation to the renewable energy accommodation, and incorporates demand response (DR) as an available resource in the ADS planning. The problem is formulated as a mixed integer nonlinear programming model, whereby the optimal allocation of renewable energy sources and the design of DR contract (i.e. payment incentives and default penalties) are determined simultaneously, in order to achieve the minimization of total cost and $CO_2$ emissions subjected to the system constraints. The uncertainties that involved are also considered by using the scenario synthesis method with the improved Taguchi's orthogonal array testing for reducing information redundancy. A novel cuckoo search (CS) is applied for the planning optimization. The case study results confirm the effectiveness and superiority of the proposed method.