• Asian-Australasian Journal of Animal Sciences
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• v.27 no.4
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• pp.574-579
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• 2014

A lysozyme gene from breast of Tibetan sheep was successfully expressed by secretion using a-factor signal sequence in the methylotrophic yeast, Pichia pastoris GS115. An expression yield and specific activity greater than 500 mg/L and 4,000 U/mg was obtained. Results at optimal pH and temperature showed recombinant lysozyme has higher lytic activity at pH 6.5 and $45^{\circ}C$. This study demonstrates the successful expression of recombinant lysozyme using the eukaryotic host organism P. pastoris paving the way for protein engineering. Additionally, this study shows the feasibility of subsequent industrial manufacture of the enzyme with this expression system together with a high purity scheme for easy high-yield purification.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.32-38
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• 1999

An autonomous mobile vehicle for transport system must plan optimal path in work envimnrent without human supervision and obstacle collision. This is to reach a destination without getting lost. In this paper, a genetic algorithm for globaI and local path planning and collision avoidance is proposed. The genetic algorithm searches for a path in the entire and continuous free space and unifies global path planning and local path planning. The sinmulation shows the proposed method is an efficient and effective method when compared with the traditional collision avoidance algorithms.rithms.

• Journal of Power System Engineering
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• v.3 no.4
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• pp.63-68
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• 1999

The determination of the optimal machining parameters in metal cutting, such as cutting speed, feed rate, and depth of cut, is an important aspect in an economic manufacturing process. The main objective in general is either to minimize the production cost or to maximize the production rate. Also there are constraints on all the machining operations which put restrictions on the choice of the machining parameters. In this paper as an objective function the production cost is considered with two constraints, surface finish and cutting power. Genetic Algorithm is applied to determine the optimum machining parameters, and the effectiveness of the applied algorithm is demonstrated by means of an example, turning operation.

• Journal of Sericultural and Entomological Science
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• v.43 no.1
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• pp.29-32
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• 2001

At present, more than 300 races of the Silkworm are conserved and used as valuable genetic resources. But because of the uneffectiveness of manual data management, faster and systematic data base construction is needed. So, development of silkworm genetic resources management program has been begun and the result can be practically used. When developing the program, Visual basic was used for data input system construction, and MS Access for database. IIS(Internet Information System) and ASP(Active Server Page) was also used for searching data and information with Internet Web Server and Web Browser which is comfortable for constructing database and providing information. Data input item consists of 46 practical characteristics such as race name, moltinism, larval period and pupation percentage etc.. And these characteristics are classified with qualitative and quantitative character. Photographs of silkworm, cocoon and other related items were scanned and the image data was recorded on the database.

• Journal of Electrical Engineering and Technology
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• v.2 no.3
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• pp.353-357
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• 2007

The bearing diagnostics method is presented in this paper using fuzzy inference based on vibration data. Both time-domain and frequency-domain features are used as input data for bearing fault detection. The Adaptive Network based Fuzzy Inference System (ANFIS) and Genetic Algorithm (GA) have been proposed to select the fuzzy model input and output parameters. Training results give the optimized fuzzy inference system for bearing diagnosis based on measured vibration data. The result is also tested with other sets of bearing data to illustrate the reliability of the chosen model.

• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.182-191
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• 2011

Genetic algorithms (GA) and particle swarm optimization (PSO) are the most famous optimization techniques among various modern heuristic optimization techniques. These two approaches identify the solution to a given objective function, but they employ different strategies and computational effort; therefore, a comparison of their performance is needed. This paper presents the application and performance comparison of the PSO and GA optimization techniques for a static synchronous series compensator-based controller design. The design objective is to enhance power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem, and both PSO and GA optimization techniques are employed to search for the optimal controller parameters.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.4
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• pp.396-407
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• 2015

The literature about intelligence assets allocation focused on mainly single or partial assets such as TOD and GSR. Thus, it is limited in application to the actual environment of operating various assets. In addition, field units have generally vulnerabilities because of depending on qualitative analysis. Therefore, we need a methodology to ensure the validity and reliability of intelligence asset allocation. In this study, detection probability was generated using digital geospatial data in MGIS (Military Geographic Information System) and simulation logic of BCTP (Battle Commander Training Programs) in the R.O.K army. Then, the optimal allocation mathematical model applied concept of simultaneous integrated management, which was developed based on the partial set covering model. Also, the proposed GA (Genetic Algorithm) provided superior results compared to the mathematical model. Consequently, this study will support effectively decision making by the commander by offering the best alternatives for optimal allocation within a reasonable time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.203-206
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• 2001

Finding the optimal solution in the river water quality management system is very hard with the non-linearity of the water quality model. Many suggested methods for that using the linear programming, non-linear programming and dynamic programming, are failed to give an optimal solution of sufficient accuracy and satisfaction. We studied a method to find a solution optimizing the river water quality management in the aspect of the efficiency and the cost of the waste water treatment facilities satisfying the water Quality goals. In the suggested method, we use the QUAL2E water quality model and the genetic algorithm. A brief result of the project to optimize the water quality management in the Youngsan river is presented.

• Journal of Microbiology and Biotechnology
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• v.10 no.1
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• pp.115-118
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• 2000

Recombinant plasmids harboring a heterologous gene coding for the enhanced green fluorescent protein (EGFP) were transfected and expressed in Drosophila melanogaster S2 cells. A stable transformation of polyclonal cell populations expressing EGFP were isolated after 4 weeks of selection with hygromycin B. The recombinant EFGP expressed in transformed S2 cells consisted of a molecular weight of 27 kDa. EGFP expression was also confirmed by fluorometric measurement. The maximum EGFP concentration was about 9.3 mg/I. The present findings demonstrate not only the successful stable expression of EGFP in Drosophuila was about 9.3 mgI. The present findings demonstrate not only the successful stable expression of EGFP in Drosophila S2 cells, but also the use of EGFP as a reporter to analyze gene expression, with its potential of a Drosophila cell expression system for recombinant protein production being an alternative to a baculovirus-insect cell expression system.

• Journal of Korean Society of Water and Wastewater
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• v.32 no.2
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• pp.115-122
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• 2018

Direct spring loaded pressure relief valve(DSLPRV) is a safety valve to relax surge pressure of the pipeline system. DSLPRV is one of widely used safety valves for its simplicity and efficiency. However, instability of the DSLPRV can caused by various reasons such as insufficient valve volume, natural vibration of the spring, etc. In order to improve reliability of DSLPRV, proper selection of design factors of DSLPRV is important. In this study, methodology for selecting design factors for DSLPRV was proposed. Dynamics of the DSLPRV disk was integrated into conventional 1D surge pressure analysis. Multi-objective genetic algorithm was also used to search optimum design factors for DSLPRV.