• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.132-134
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• 2009

Hemorrhagic shock is a common cause of death in emergency rooms. Since the symptoms of hemorrhagic shock occur after shock has considerably progressed, it is difficult to diagnose shock early. The purpose of this study was to improve early diagnosis of hemorrhagic shock using a survival prediction model in rats. We measured ECG, blood pressure, respiration and temperature in 45 Sprague-Dawley rats, and then obtained a logistic regression equation predicting survival rates. Area under the ROC curves was 0.99. The Hosmer-Lemeshow goodness-of-fit chi-square was 0.86(degree of freedom=8, p=0.999). Applying the determined optimal boundary value of 0.25, the accuracy of survival prediction was 94.7%

• Proceedings of the KSME Conference
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• 2000.11b
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• pp.514-519
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• 2000

Predicting a pressure drop between inlet and outlet of the filter system is essential in designing the optimum filter system. This experiment has been carried out to investigate several design parameters which influence in a pressure drop, such as different tube length and metal fiber filter mesh size. A 1/50 scale filter system was made to simulate a real filter system. Results are compared with Darcy equation for a porous media.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1487-1490
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• 2003

In this paper, the application of object-oriented Data Model to develop a multibody dynamic system, called O-DYN, is introduced. Mechanical components, such as bodies, joints, forces are modeled as objects which have data and method by using object-oriented modeling methodology. O-DYN, a dynamic analysis system, based on the object-oriented modeling concept is made in C++. One example is analyzed through the O-DYN, It is expected that the analysis program or individual module constructed in this paper would be useful for mechanical engineers in predicting the dynamic responses of multibody systems and developing an analysis program

• 한국전산유체공학회:학술대회논문집
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• 1998.05a
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• pp.156-161
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• 1998

This describes a numerical method for predicting the incompressible unsteady laminar three-dimensional flows of fluid behaviour with free-surface. The elliptic differential equations governing the flows have been linearized by means of finite-difference approximations, and the resulting equations have been solved via a fully-implicit iterative method. The free-surface is defined by the motion of a set of marker particles and interface behaviour was investigated by way of a 'Lagrangian' technique. Using the GALA concept of Spalding, the conventional mass continuity equation is modified to form a volumetric or bulk-continuity equation. The use of this bulk-continuity relation allows the hydrodynamic variables to be computed over the entire flow domain including both liquid and gas regions. Thus, the free-surface boundary conditions are imposed implicitly and the problem formulation is greatly simplified. The numerical procedure is validated by comparing the predicted results of a periodic standing waves problems with analytic solutions or experimental results from the literature. The results show that this numerical method produces accurate and physically realistic predictions of three-dimensional free-surface flows.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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• pp.168-175
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• 1999

In this paper, a modified RBF(Radial Basis Function) network structure is suggested for the prediction of a time-series with non-linear, non-stationary characteristics. Coventional RBF network predicting time series by using past outputs sense the trajectory of the time series and react when there exists strong relation between input and hidden activation function's RBF center. But this response is highly sensitive to level and trend of time serieses. In order to overcome such dependencies, hidden activation functions are modified to react to the increments of input variable and multiplied by increment(or dectement) for prediction. When the suggested structure is applied to prediction of Macyey-Glass chaotic time series, Lorenz equation, and Rossler equation, improved performances are obtained.

• Transactions of Materials Processing
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• v.13 no.2
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• pp.168-173
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• 2004

Microforming can be a good application for bulk metallic glasses. It is important to simulate the deformation behaviour of the bulk metallic glasses in a supercooled liquid region for manufacturing micromachine parts. For these purposes, a correct constitutive model which can reproduce viscosity results is essential for good predicting capability. In this paper, we studied deformation behaviour of the bulk metallic glasses using the finite element method in conjunction with the fictive stress constitutive model which can describe non-Newtonian as well as Newtonian behaviour. A combination of kinetic equation which describes the mechanical response of the bulk metallic glasses at a given temperature and evolution equations fur internal variables provide the constitutive equation of the fictive stress model. The internal variables are associated with fictive stress and relation time. The model has a modular structure and can be adjusted to describe a particular type of microforming process. Implementation of the model into the MARC software has shown its versatility and good predictive capability.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.13 no.1
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• pp.46-55
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• 2001

An approach using the nonlinear wave model in predicting wave-induced currents is presented. The model results were compared with those of the conventional model using phase-averaged radiation stress, and in addition with experimental data captured by a PIV system. As a result of comparison of wave-induced currents generated behind the surface-piercing breakwater and submerged breakwater, eddy patterns appeared to be similar each other but in general numerical solutions of both models were underestimated.

• ETRI Journal
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• v.28 no.2
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• pp.231-234
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• 2006

The cancellation performance of a linearization loop is limited by the degree of an amplitude imbalance and a phase imbalance. A delay mismatch causes a phase variation as a function of frequency. Therefore, the cancellation performance and linearization bandwidth are limited by a delay mismatch. The expression for the effects of an amplitude imbalance, a phase imbalance, and a delay mismatch on the characteristics of a linearization loop is derived and analyzed. The simulation results are compared with the results obtained by means of using a commercial simulation tool and the exact agreement is reported. The derived equation could be used in designing a linearization loop and predicting the cancellation performance of the linearization loop usefully. Some useful characteristics, known from the simulation results obtained by using the derived equation, of a linearization loop for designing and implementing feedforward amplifiers are described in detail.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.7
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• pp.1276-1281
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• 2010

To analyze the gas discharge phenomena in parallel-plane electrodes, the fully coupled finite element method (FEM) considering secondary electron emission effects in discharge column was adopted in this paper. Two coupled equations of the hydrodynamic diffusion-drift equations for three carriers and the Poisson's equation for electric scalar potential should be solved as a system equation. The proposed method including two secondary electron processes of the photoemission and background ionization has been successfully applied to evaluating the breakdown voltage in parallel-plane electrodes and is verified by comparing its numerical results with the experimental ones. From the obtained results, it is inferred that the proposed numerical scheme will be useful for predicting and understanding streamer transient phenomena.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2299-2301
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• 1998

In this paper, a modified RBF (Radial Basis Function) neural network structure is suggested for the prediction of time series with non-linear, non-stationary characteristics. Conventional RBF neural network predicting time series by using past outputs is for sensing the trajectory of the time series and for reacting when there exists strong relation between input and hidden neuron's RBF center. But this response is highly sensitive to level and trend of time serieses. In order to overcome such dependencies, hidden neurons are modified to react to the increments of input variable and multiplied by increments(or decrements) of out puts for prediction. When the suggested structure is applied to prediction of Lorenz equation, and Rossler equation, improved performances are obtainable.