• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.4
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• pp.326-333
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• 2015

A turbo fan engine performance analysis program combined with a particle swarm optimization(PSO) has been developed to optimize the major design parameters of the combat aircraft gas turbine engine. The optimized parameters includes bypass ratio, fan pressure ratio, high pressure compression ratio and burner exit temperature. The objective parameters have been determined using a multi-objective function consisting of the net thrust and specific fuel consumption along a weight function. The basic model for the combat aircraft gas turbine engine has been selected as the F404 turbofan engine which is widely used in the combat aircraft, F-18 and Korean high level training aircraft, T-50. The optimal conditions of four parameters have been obtained for various design conditions.

• Korean Journal of Optics and Photonics
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• v.8 no.2
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• pp.81-87
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• 1997

This paper presents the optimum initial design containing the first and third order properties of the four-group video camera zoom system using lens modules, and its real lens design. The optimum initial design with focal length range of 6.1693 to 58.4065 mm is derived by assigning appropriate first order quantities and third order aberrations to each module along with the specific constraints required for optimization. By scaling the focal length of each lens group, an initial real lens selected for each group has been designed to match its focal length into that of the each lens module, and then combined to establish an actual zoom system by adjusting the air space between the groups at all zoom positions. The combination of the separately designed groups results in a system which satisfies the first order properties of the zoom system consisting of original lens modules. As a result, by residual aberration correction, we could obtain a zoom system useful in video zoom camera employing the rear focus method.

• Food Science and Preservation
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• v.13 no.3
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• pp.357-362
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• 2006

In other to produce vinegar min citron (Citrusu junos), acetic acid bacteria were selected from several conventional vinegars, and total 25 acetic acid producing bacterial strains were isolated. Among the isolated strains, a strain was selected from the medium which showed the highest productivity of acetic acid. The strain was identified as Acetobacter sp V-16 and it cultural characteristics were also investigated in the medium with citron juice. Optimum temperature for the growth of Acetobacter sp. V-16 was $30^{\circ}\C$. The medium containing 2% acetic acid, 5% ethanol, and 30% citron juice was suitable for acetic acid production with Acetobacter sp. V-16. The acidity of culture medium was reached to 6.8% after 10 days shaking cultivation at $30^{\circ}\C$.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.11
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• pp.963-971
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• 2012

In this paper, development of optimal design tools for wing structure is described including multi load spectra condition and fatigue analysis. Two dimensional CFD result are used for calculating aerodynamic force. Design variables are composed of a number of rib and spar, positions, and thickness of each structural member. The mission profile for fatigue analysis is composed based upon the results of CFD analysis, the flight-by-flight spectra method, the excessive curves for gust loads. Minor's rule was used to deal with multi-load condition. Stress analysis and fatigue analysis are performed to calculate objective functions. Particle Swarm Optimization(PSO) algorithm was used to apply to problems which have dozens of design variables.

• Journal of the Korean Society of Propulsion Engineers
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• v.3 no.1
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• pp.24-33
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• 1999

For performance prediction and diagnostics of gas turbine engines, linear and non-linear gas path analysis are applied. In order to find optimal instrument parameters to detect the physical faults such as (outing, erosion and corrosion, non-linear gas path analysis is used. A typical industrial gas turbine engine, TB5000, is used to study the effect of physical faults on engine performance. Through comparison of RMS error between linear and non-linear gas path analysis, the optimal instrument parameters can be defined. As a result, it is found that the linear GPA has the level of error introduced by the assumption of the linear mode: can be of the same order of magnitude as the fault being soughtwhile the non-linear GPA can be solved the non-linear relationships between dependent and independent parameters using an iterative method such as the Newton-Raphson method with sufficient accuracy.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.5
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• pp.13-26
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• 1999

This paper presents a metric that can guide to optimal circuit models for interconnects among various models, given interconnect parameters and operating environment. To get this goal, we categorize interconnects into RC~c1ass and RLC-c1ass model domains based on the quantitative modeling error analysis using total resistance, inductance and capacitance of interconnects as well as operating frequency. RC~c1ass circuit models, which include most on~chip interconnects, can be efficiently analyzed by using the model~order reduction techniques. RLC-c1ass circuit models are constructed using one of three candidates, ILC(Iterative Ladder Circuit) macromodels, MC(Method of Characteristics) macromodels, and state-based convolution method, the selection process of which is based upon the allowable modeling error and electrical parameters of interconnects. We propose the model domain diagram leading to optimal circuit models and the division of model domains has been achieved considering the simulation cost of macromodels under the environmental assumption of the general purpose circuit simulator such as SPICE. The macromodeling method presented in this paper keeps the passivity of the original interconnects and accordingly guarantees the unconditional stability of circuit models.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.402-410
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• 2004

In this paper, an optimal design method of clonal selection based Fuzzy-Neural Networks (FNN) model for complex and nonlinear systems is presented. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. Also Advanced Clonal Selection (ACS) is proposed to find the parameters such as parameters of membership functions, learning rates and momentum coefficients. The proposed method is based on an Immune Algorithm (IA) using biological Immune System and The performance is improved by control of differentiation rate. Through that procedure, the antibodies are producted variously and the parameter of FNN are optimized by selecting method of antibody with the best affinity against antigens such as object function and limitation condition. To evaluate the performance of the proposed method, we use the time series data for gas furnace and traffic route choice process.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.11
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• pp.99-107
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• 2009

Since a long work piece influences the natural frequency of the entire system with a miniature high speed spindle, a bar-feeder is used for a long work piece to improve the vibration characteristics of a spindle system. Therefore, it is very important to design optimally support positions between a bar-feeder and a long work piece for a miniature high speed spindle system. The goal of the current paper is to present an optimization method for the design of support positions between a bar-feeder and a long work piece. This optimization method is effectively composed of the method of design of experiment (DOE), the artificial neural network (ANN) and the genetic algorithm (GA). First, finite element models which include a high speed spindle, a long work piece and the support conditions of a bar-feeder were generated from the orthogonal array of the DOE method, and then the results of natural vibration analysis using FEM were provided for the learning inputs of the neural network. Finally, the design of bar-feeder support positions was optimized by the genetic algorithm method using the neural network approximations.

• The Korean Journal of Food And Nutrition
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• v.22 no.1
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• pp.103-109
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• 2009

In order to isolate antibiotic producing microorganisms, several actinomycetes were isolated from soil samples. The aerial hyphae of Y-88 strain were gray in color with tree types. Under the microscopic examination, the Y-88 isolate formed a spiral aerial spore mass with a smooth surface and a rectiflexibilis type of spore chain. Y-88 utilized glucose, fructose, arabinose, and sucrose, but not rhamnose, raffinose, mannitol, or inositol. In addition, Y-88 produced melanin on the tyrosine agar and the strain could utilize L-valine, L-phenylalanine, and L-hydroxyproline. Based on these results and the cultural and physiological characteristics described in the Bergey's Manual, the Actinomycetes, Y-88, was identificated as a Streptomyces species. The optimum medium conditions for this antibiotic producing Streptomyces sp. Y-88 was 1.6% soluble starch, 0.6% glucose, 0.6% beef extract, 0.01% $K_2HPO_4$, 0.01% $MgSO_4$ $7H_2O$, and 0.01% $ZnSO_4$ $7H_2O$ at an initial pH of 4.0, and 25$^{\circ}C$.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.125-133
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• 2010

A policy based resource management framework is proposed, that supports the optimal QoS by applying resources management function which is changed according to the status of mobile terminal and heterogeneous connections to hand-over process of mobile terminals based on heterogeneous network. To assess the performance of policy based resource management framework proposed in this thesis, in case of applying weighted policy for selecting optimal cell in hand-over occurring among duplicated heterogeneous connections, the transmission delay was remarkably enhanced as the number of multimedia sessions increased. This means, in case of QoS deterioration of multimedia session occurring in service connection, hand-over was executed with the optimal connection.