• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.05c
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• pp.43-46
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• 2004

This paper describes the information for quantitative simulation of weal이y ionized plasma. We must grasp the meaning of the plasma state condition to utilize engineering application and to understand materials of plasma state. Using quantitative simulations of weakly ionized plasma, we can analyze gas characteristic. In this paper, the electron transport characteristic in $CH_4$ has been analysed over the E/N range 0.1~300[Td], at the $300[_{\circ}K]$ by the two tenn approximation Boltzmann equation method and Monte Carlo Simulation. Boltzmann equation method has also been used to predict swarm parameter using the same cross sections as input. The behavior of electron has been calculated to give swarm parameter for the electron energy distribution function has been analysed in $CH_4$ at E/N=10, 100 for a case of the equilibrium region in the mean energy. The result of Boltzmann equation and Monte Carlo Simulation has been compared with experimental data by Ohmori, Lucas and Carter. The swarm parameter from the swarm study are expected to sever as a critical test of current theories of low energy scattering by atoms and molecules.

• Bulletin of the Korean Chemical Society
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• v.26 no.1
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• pp.139-145
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• 2005

Artificial neural networks (ANNs), for a first time, were successfully developed for the modeling and prediction of solvent effects on rate constant of [2+2] cycloaddition reaction of diethyl azodicarboxylate with ethyl vinyl ether in various solvents with diverse chemical structures using quantitative structure-activity relationship. The most positive charge of hydrogen atom (q$^+$), dipole moment ($\mu$), the Hildebrand solubility parameter (${\delta}_H^2$) and total charges in molecule (q$_t$) are inputs and output of ANN is log k$_2$ . For evaluation of the predictive power of the generated ANN, the optimized network with 68 various solvents as training set was used to predict log k$_2$ of the reaction in 16 solvents in the prediction set. The results obtained using ANN was compared with the experimental values as well as with those obtained using multi-parameter linear regression (MLR) model and showed superiority of the ANN model over the regression model. Mean square error (MSE) of 0.0806 for the prediction set by MLR model should be compared with the value of 0.0275 for ANN model. These improvements are due to the fact that the reaction rate constant shows non-linear correlations with the descriptors.

• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.903-911
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• 2008

Association rule mining searches for interesting relationships among items in a given large database. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. Many data is most quantitative data. There is a need for partitioning techniques to quantitative data. The partitioning process is referred to as binning. We introduce several binning methods ; parameter mean binning, equi-width binning, equi-depth binning, clustering-based binning. So we apply these binning methods to several distribution types of quantitative data and present the best binning method for association rule discovery.

• International Journal of Industrial Entomology and Biomaterials
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• v.2 no.1
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• pp.79-81
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• 2001

A study was conducted to establish the degree of genetic divergence between different hybrid forms and rearing conditions through estimation of the minimum number of genes (allelic pairs) differentiating parents in terms of specific quantitative traits. It was established that the minimum gene numbers differentiating parental lines in the inheritance of cocoon was 1, of cocoon shell weight- between 1 and 2, and of silk filament length- between 2 and 3. The variability in the specific genetic parameter could be explained by the reliability of the statistical-and-genetic method used and the expression of genes affecting the formation of each of the characters tested. Gene expression, in its turns is conditioned both by the gene interaction within the genotypes and the different genotype response to environmental change. To go deep in the problem, experiments should be conducted under strictly controlled conditions, reducing the mathematical-and-genetic analysis to a physiological levels and hence to analyse the genetic nature of the specific quantitative character formation and its genetic control.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.454-456
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• 1998

Traditional adaptive control algorithms are not robust to dynamic uncertainties. The adaptive control algorithms developed previously to deal with dynamic uncertainties do not facilitate quantitative design. We proposed a new robust adaptive control algorithms consists of an $H^{\infty}$ suboptimal control law and a robust parameter estimator. Numerical examples showing the effectiveness of the $H^{\infty}$ adaptive scheme are provided.

• Fire Science and Engineering
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• v.7 no.2
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• pp.3-12
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• 1993

The closed type sprinkler head is a component of sprinkler system for fire protection. The purpose of this study is to inverstigate the influence factors of the responsiveness of the head by heated wind tunnel experiment. As the result of this study, it was found that response time index and conduction parameter showed the same characteristic quantitative changes to head types and test methods.

• Bulletin of the Korean Chemical Society
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• v.15 no.11
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• pp.976-980
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• 1994

The sensitivity factors and the error propagation factors are defined for the three-parameter ellipsometry (TPE). The sensitivity factor is useful for understanding the nature of the TPE measurements in connection with determination of the optical properties and the thickness of a film. On the other hand, the error propagation factors provide a quantitative tool for predicting the optimum condition for TPE experiments. Their usefulness is demonstrated for the passive film formed on nickel in aqueous solution.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.199-199
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• 2000

Most of linear time-varying(LTV) systems except special cases have no general solution for the dynamic equations. Thus, it is difficult to design time-varying controllers in analytic ways, and other control design approaches such as robust control have been applied to control design for uncertain LTI systems which are the approximation of LTV systems have been generally used instead. A robust control method such as quantitative feedback theory(QFT) has an advantage of guaranteeing the stability and the performance specification against plant parameter uncertainties in frozen time sense. However, if these methods are applied to the approximated linear time-invariant(LTI) plants which have large uncertainty, the designed control will be constructed in complicated forms and usually not suitable for fast dynamic performance. In this paper, as a method to enhance the fast dynamic performance, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks for LTV systems with bounded time-varying parameters.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.2
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• pp.107-114
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• 2014

This paper proposes a common rail pressure control algorithm for passenger car diesel engines. For handling the parameter-varying characteristics of common rail systems, the quantitative feedback theory (QFT) is applied to the design of a robust rail pressure control algorithm. The driving current of the pressure control valve and the common rail pressure are used as the input/output variables for the common rail system model. The model parameter uncertainty ranges are identified through experiments. Rail pressure controller requirements in terms of tracking performance, robust stability, and disturbance rejection are defined on a Nichols chart, and these requirements are fulfilled by designing a compensator and a prefilter in the QFT framework. The proposed common rail pressure control algorithm is validated through engine experiments. The experimental results show that the proposed rail pressure controller has a good degree of consistency under various operating conditions, and it successfully satisfies the requirements for reference tracking and disturbance rejection.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.2
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• pp.52-60
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• 2002

Axiomatic Design is the one of many useful methods for making a good design. In this method, the independency of Functional Requirements (FRs) is an important property to determine whether the design is good or not. Until now so many designers have decided the independency between FRs by their own decisions. The way depending on inspiration is simple and fast, but it can not be considered as a precise conclusion. Also there are not exact rule that evaluate the quantitative independence between FRs. This paper will show the way to evaluate the quantitative independence of FRs from the comparison between FRs of lower levels, and develop more efficient and objective tool in Axiomatic Design.