• Journal of the Korea Society for Simulation
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• v.5 no.1
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• pp.91-106
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• 1996

Control Variate (CV) is very useful technique for variance reduction in a wide class of queueing network simulations. However, the loss in variance reduction caused by the estimation of the optimum control coefficients is an increasing function of the number of control variables. Therefore, in some situations, it is required to select an optimal set of control variables to maximize the variance reduction . In this paper, we develop the Adaptive Control Variates (ACV) method which selects an optimal set of control variates during the simulation adatively. ACV is useful to maximize the simulation efficiency when we need iterated simulations to find an optimal solution. One such an example is the Simulated Annealing (SA) because, in SA algorithm, we have to repeat in calculating the objective function values at each temperature, The ACV can also be applied to the queueing network optimization problems to find an optimal input parameters (such as service rates) to maximize the throughput rate with a certain cost constraint.

• Journal of Korean Society on Water Environment
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• v.25 no.1
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• pp.96-101
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• 2009

The aim of this research was to apply experimental design methodology to optimizetion the photolytic degradation of N-nitrosodimethylamine (NDMA). Reactions were mathematically described as a function of parameters such as pH, initial NDMA concentration, and UV intensity using the Box-Behnken method. The results showed that the responses of NDMA removal (%) in photolysis were significantly affected by the synergistic effect of linear term of pH, initial NDMA concentration and UV intensity. The application of Response Surfase Methodology (RSM) using the Box-Behnken method yielded the following regression equation, which is an empirical relationship between the removal (%) of NDMA and test variables in coded unit: Y = 50.929 + 16.073(UV) - 7.909(NDMA) - 27.432(pH) - 11.385(UV)(NDMA) - 7.363(UV)(pH) +13.811(NDMA)(pH). The model predictions agreed well with the experimentally observed result ($R_2(ad.)=89%$).

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.960-963
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• 1996

In this paper, the optimization of a fuzzy controller using genetic algorithm is studied. The fuzzy controller has been widely applied to industries because it is highly flexible, robust easy to implement and suitable for complex systems. Generally, the design of fuzzy controller has difficulties in determining the structure of the rules and the membership functions. To solve these problems, the proposed method optimizes the structure of fuzzy rules and the parameters of membership functions simultaneously in an off-line method. The proposed method is evaluated through computer simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.8
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• pp.649-654
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• 2002

The essential philosophy of the QFT(Quantitative Feedback Theory) is that a suitable controller can be found by loop shaping a nominal loop transfer function such that the frequency response of this function does not violate the QFT bounds. The loop shaping synthesis involves the identification of a structure and its specialization by means of the parameter optimization. This paper presents an optimization algorithm to estimate the controller parameters from the frequency transfer function synthesis using the TLS(Total Least Squares) in the QFT loop shaping procedure. The proposed method identifies the parameter vector of the robust controller from an overdetermined linear system developed from rearranging the two dimensional system matrices and output vectors obtained from the QFT bounds. The feasibility of the suggested algorithm is illustrated with an example.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1092-1097
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• 2005

In this paper, design approach of PID controller with rejection function against external disturbance in motor control system is proposed using bacterial foraging based optimal algorithm. Up to the present time, PID Controller has been used to operate for AC motor drive because of its implementational advantages in practice and simple structure. However, it is not easy to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error in the industrial system with disturbance. To design disturbance rejection tuning, disturbance rejection conditions based on $H_{\infty}$ are illustrated and the performance of response based on the bacterial foraging is computed for the designed PID controller as ITSE (Integral of time weighted squared error). Hence, parameters of PID controller are selected by bacterial foraging based optimal algorithm to obtain the required response

• Journal of electromagnetic engineering and science
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• v.7 no.3
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• pp.129-133
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• 2007

In this paper, we present the development of an antenna specialized for the maritime collision avoidance system. This antenna is configured as the dielectric rod partially embedded in the metal cavity to reduce the overall size, simultaneously assuring the mechanical sturdiness against the challenging oceanic weather conditions. More importantly, the design has been carefully done to meet the requirements on the radiation pattern(with the slope < 5 dB/deg in the elevation(E-plane), circular in the azimuth) suitable to receiving the reflected signals from the other objects on the sea. To find the optimal design parameters, the genetic algorithm has been used to meet the goals of the desired return loss and pattern. This design methodology is validated by the good agreement between the calculation and measurement.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.483-486
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• 2014

Although flip-chip interconnects have smaller parasitics than bonding wires, they should be carefully designed at 60 GHz. Insertion loss at a flip-chip transition may differ as much as 2 dB depending on design parameters. In this paper we present a comprehensive sensitivity analysis to optimize the flip-chip transition.

• Genomics & Informatics
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• v.9 no.3
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• pp.134-135
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• 2011

DNA chips are used for experiments on genes and provide useful information that could be further analyzed. Using the data extracted from the DNA chips to find useful patterns or information has become a very important issue. In this paper, we explain the application developed for classifying DNA chip data using a classification method based on the Particle Swarm Optimization (PSO) algorithm. Considering that DNA chip data is extremely large and has a fuzzy characteristic, an algorithm that imitates the ecosystem such as the PSO algorithm is suitable to be used for analyzing such data. The application enables researchers to customize the PSO algorithm parameters and see detail results of the classification rules.

• Journal of Communications and Networks
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• v.12 no.2
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• pp.150-157
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• 2010

Understanding and optimizing the energy consumption of wireless devices is critical to maximize the network lifetime and to provide guidelines for the design of new protocols and interfaces. In this work, we first provide an accurate analysis of the energy performance of an IEEE 802.11 WLAN, and then we derive the configuration to optimize it. We further analyze the impact of the energy configuration of the stations on the throughput performance, and we discuss under which circumstances throughput and energy efficiency can be both jointly maximized and where they constitute different challenges. Our findings are that, although an energy-optimized configuration typically yields gains in terms of throughput as compared against the default configuration, it comes with a reduction in performance as compared against the maximum-bandwidth configuration, a reduction that depends on the energy parameters of the wireless interface.

• Transactions of the Korean hydrogen and new energy society
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• v.24 no.4
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• pp.275-281
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• 2013

This study was conducted to increase the amount of bio-hydrogen production from microalgae(Chlorella vulgaris) in batch reactors by thermal pre-treatment. The optimization of thermal pre-treatment was conducted using statistic experimental design of response surface methodology. Two experimental parameters of temperature and reaction time were considered. The optimization condition was founded at the coded variables of <0.52, -0.07> corresponding to the experimental of heating temperature of $95.6^{\circ}C$ and reaction time of 57.9 min, respectively. Under the optimal condition, the maximum hydrogen production was predicted to 25.3mL $H_2/g$ dry cell weight (dcw), which was 9.1 times higher value of control(2.8mL $H_2/g$ dcw).