• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2004년도 추계학술발표회 발표논문집
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• pp.583-584
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• 2004

• 한국초전도학회:학술대회논문집
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• 한국초전도학회 2004년도 High Temperature Superconductivity Vol.XIV
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• pp.33-33
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• 2004

• Journal of Microbiology and Biotechnology
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• 제14권6호
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• pp.1163-1169
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• 2004

An unstructured mathematical model is presented for lactic acid fermentation based on the energy balance. The proposed model reflects the energy metabolic state and then predicts the cell growth, lactic acid production, and glucose consumption rates by relating the above rates with the energy metabolic rate. Fermentation experiments were conducted under various initial lactic acid concentrations of 0, 30, 50, 70, and 90 g/l. Also, a genetic algorithm was used for further optimization of the model parameters and included the operations of coding, initialization, hybridization, mutation, decoding, fitness calculation, selection, and reproduction exerted on individuals (or chromosomes) in a population. The simulation results showed a good fit between the model prediction and the experimental data. The genetic algorithm proved to be useful for model parameter optimization, suggesting wider applications in the field of biological engineering.

• International Journal of Aeronautical and Space Sciences
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• 제14권1호
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• pp.58-66
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• 2013

This paper addresses the performance of three different types of attitude control systems for the Quad-rotor UAV to perform the flip maneuver. For this purpose, Quad-rotor UAV's 6-DOF dynamic model is derived, and it was used for designing an attitude controller of the Quad-rotor UAV. Attitude controllers are designed by three different methods. One is the open-loop control system design, another is the PD control system design, and the last method is the sliding mode control system design. Performances of all controllers are tested by 6-DOF simulation. In case of the open-loop control system, control inputs are calculated by the quad-rotor dynamic model and thrust system model that are identified by the thrust test. The 6-DOF realtime simulation environment was constructed in order to verify the performances of attitude controllers.

• International Journal of Internet, Broadcasting and Communication
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• 제12권3호
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• pp.149-155
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• 2020

Air pollution is a problem of environmental health risk in big cities. Recently, researchers have proposed using various artificial intelligence technologies to predict air pollution. The proposed model is Cooperative of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS), to predict air pollution of Korean cities using Python. Data air pollutant variables were collected and the Air Korean Web site air quality index was downloaded. This paper's aim was to predict on the health risks and the very unhealthy values of air pollution. We have predicted the air pollution of the environment based on the air quality index. According to the results of the experiment, our model was able to predict a very unhealthy value.

• 한국산업경영시스템학회:학술대회논문집
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• 한국산업경영시스템학회 2002년도 춘계학술대회
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• pp.25-30
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• 2002

The problem of qualitative reliability system is very important issue in the digitalized nuclear power plant, because the failure of its system brings about extravagant economic loss, extensive environment destruction, and fatal damage of human. Therefore this study is to develop the reliability evaluation model through the normalized scoring model by the quantitative and qualitative factors considering the advanced safety factors In the Advanced Pressurized water Reactor 1400MWe(APR 1400) under uncertainty Especially, the qualitative factors considering the information and human factors for the systematic and rational justification have been closely analyzed. The reliability evaluation model can be simply applied in real fields in order to minimize the industrial accident and human error in the digitalized nuclear power plant.

• 전기학회논문지
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• 제56권9호
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• pp.1589-1595
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• 2007

This paper suggests the advanced reliability assessment tool for railway signaling Hot-Standby sparing system. Existing reliability assessment for Hot-Standby sparing system controller is done by using single module mean failure rate based on approximated Hot standby sparing system function. Although approximated Hot standby sparing system function can be applied to various Hot standby sparing system, however, it is not able to reflect the exact system structure. In this paper, we suggest the advanced reliability function by identifying changeover-related failure factors and common failure mode which is not considered in existing approximated Hot standby sparing system reliability function via developing Hot standby sparing system model for railway signaling and applying FMECA to this model. Also. we compare reliability assessment results for model system to reliability assessment for existing system.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2008년도 춘계학술대회 논문집 센서 박막재료연구회 및 광주 전남지부
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• pp.22-26
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• 2008

In this paper, we developed a hybrid simulation model of carbon laser ablation under the Ar plasmas consisted of fluid and particle methods. Three kinds of carbon particles, which are carbon atom, ion and electron emitted by laser ablation, are considered in the computation. In the present simulation, we adopt capacitively coupled plasma with asymmetrical electrodes. As a result, in Ar plasmas, carbon ion motions were suppressed by a strong electric field and were captured in Ar plasmas. Therefore, a low number density of carbon ions were deposited upon substrate. In addition, the plume motions in Ar gas atmosphere was also discussed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.322-324
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• 2005

In this paper, we introduce the advanced Self-Organizing Fuzzy Polynomial Neural Network based on optimized FPN by evolutionary algorithm and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially genetic algorithms (GAs). The proposed model gives rise to a structurally and parametrically optimized network through an optimal parameters design available within Fuzzy Polynomial Neuron(FPN) by means of GA. Through the consecutive process of such structural and parametric optimization, an optimized and flexible the proposed model is generated in a dynamic fashion. The performance of the proposed model is quantified through experimentation that exploits standard data already used in fuzzy modeling. These results reveal superiority of the proposed networks over the existing fuzzy and neural models.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1996년도 춘계학술발표회논문집(2)
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• pp.349-355
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• 1996

In this study, the mechanistic critical heat flux (CHF) model and correlation for water are derived based on flow excursion (or Ledinegg instability) criterion and the simplified two-phase homogeneous model. The relationship between CHF for the water and the principal parameters such as mass flux heat of vaporization, heated length-to-diameter ratio, vapor-liquid density ratio and inlet subcooling is derived on the developed correlation. The developed CHF correlation predicts very well at the applicable ranges, 1 < P < 40 bar, 1, 300 < G 27, 00 kg/$m^2$s and inlet quality is less than -0.1. The overall mean ratio of predicted to experimental CHF value is 0.988 with standard deviation of 0.046.