• Journal of the Korean Statistical Society
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• v.19 no.2
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• pp.145-150
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• 1990

In this article we develop the marginal posterior density of the model parameters in the multiresponse regression models when missing values exist only in one response. The resulting density resolves a couple of problems in the estimation approach proposed by Box, Draper, and Hunter (1970) and provides a general interpretation for relationship between the estimates of the missing values and the parameters.

• Journal of Biosystems Engineering
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• v.16 no.2
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• pp.111-117
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• 1991

An empirical model for diesel engine control was obtained using a system identification method. A pseudo-random binary sequence was used as an input signal. Spectral anaylsis was used to find the frequency response of system. Model parameters of transfer functions were obtained using nonlinear regression.

• Journal of Korean Society for Quality Management
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• v.27 no.1
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• pp.59-79
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• 1999

The fitting of a response surface model and the subsequent exploration of the response surface are usually based on the assumption that the experimental runs are carried out under homogeneous conditions. This, however, may be quite often difficult to achieve in many experiments. To control such an extraneous source of variation, the response surface design should be arranged in several blocks within which homogeneity of conditions can be maintained. In this case, when fitting a response surface model, the least squares estimates of the model's parameters and the prediction variance will generally depend on how the response surface design is blocked. That is, the choice of a blocking arrangement for a response surface design can have a considerable effect on estimating the mean response and on the size of the prediction variance. In this paper, we propose a measure for evaluating the effect of blocking of response surface designs using cuboidal regions.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.2
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• pp.193-200
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• 2002

Simple spring-damper-mass models have been widely used to investigate whole-body vortical biodynamic response characteristics of the seated vehicle driver. Most previous models have not considered the effect of wobbling masses; i.e. heart, lungs, liver, intestine, etc. In this study, 4 -DOF seated driver model including one non-rigid mass representing wobbling visceral mass, 5-DOF model including intestine, and 10-DOF model including five lumbar vertebral masses were proposed. The model parameters were identified by a combinatorial optimization technique. simulated annealing method. The objective function was chosen as the sum of error between model response of seat-to-head transmissibility and driving point mechanical impedance and those of experimental data for subjects seated erect without backrest support. The model response showed a good agreement with the experimental response characteristics. Using a 10-DOF model, calculated resonance frequency of lumbar spine at 4Hz was matched well with experimental results of Panjabi et al.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1257-1260
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• 2005

Grinding process has unique characteristics compared with other machining processes. The cutting edges of the grinding wheel don't have uniformity and act differently on the workpiece at each grinding. The response surface analysis is one of various methods for optimizing and evaluating the process parameters to achieve the desired output. In this study, the effect of the grinding parameters on outcomes of the surface grinding was analyzed experimently. To predict the grinding outcomes and to select the grinding conditions before grinding, the second-order response surface models for the grinding force and the surface roughness were developed.

• Journal of KSNVE
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• v.2 no.3
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• pp.193-202
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• 1992

The unbalance response analysis is one of the essential area in the forced vibration analysis of rotor bearing systems because of it usefulness in balancing and diagnosis as well as identification of parameters involved in rotor bearing systems. However some unbalance responses are not measurable due to the fact that rotor bearing systems are often encapsulated by fixtures or safety protectors. In the present paper, an efficent estimation scheme for unmeasured unbalance responses in rotor bearing systems is developed. The fundamental fearture of the proposed method is characterized by the linear formulae to estimate the unbalance responses from the measured unbalance responses and the finite element auxilliary model equation which is constructed to be identical to the prototype excluding the uncertain parameters such as bearing coefficients. The identification formulae for bearing parameters are also derived by using the unbalance response and the finite elements auxiliary model. Simulation is provided to verify the effectiveness of the proposed method.

• Journal of the military operations research society of Korea
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• v.25 no.2
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• pp.158-169
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• 1999

This paper is concerned with the application of generalized linear interactive modelling(GLIM) to the binary categorical data. To analyze the categorical data given by a contingency table, finding a good-fitting loglinear model is commonly adopted. In the case of a contingency table with a response variable, we can fit a logit model to find a good-fitting loglinear model. For a given $2^4$ contingency table with a binary response variable, we show the process of fitting a loglinear model by fitting a logit model using GLIM and SAS and then we estimate parameters to interpret the nature of associations implied by the model.

• Structural Engineering and Mechanics
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• v.75 no.3
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• pp.327-337
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• 2020

The stability and dynamic performance of a flapper-nozzle servo valve depend on several factors, such as the motion of the armature component and the deformation of the spring tube. As the only connection between the armature component and the fixed end, the spring tube plays a decisive role in the dynamic response of the entire system. Aiming at predicting the vibration characteristics of the servo valves to combine them with the control algorithm, an innovative dynamic stiffness based on a distributed parameter model (DPM) is proposed that can reflect the dynamic deformation of the spring tube and a suitable discrete method is applied according to the working condition of the spring tube. With the motion equation derived by DPM, which includes the impact of inertia, damping, and stiffness force, the mathematical model of the spring tube dynamic stiffness is established. Subsequently, a suitable program for this model is confirmed that guarantees the simulation accuracy while controlling the time consumption. Ultimately, the transient response of the spring tube is also evaluated by a finite element method (FEM). The agreement between the simulation results of the two methods shows that dynamic stiffness based on DPM is suitable for predicting the transient response of the spring tube.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.2
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• pp.458-466
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• 1998

In this work, a frequency domain method is tested numerically and experimentally to improve nonlinear model parameters using the frequency response function at the nonlinear element connected point of structure. This method extends the force-state mapping technique, which fits the nonlinear element forces with time domain response data, into frequency domain manipulations. The force-state mapping method in the time domain has limitations when applying to complex real structures because it needd a time domain lumped parameter model. On the other hand, the frequency domain method is relatively easily applicable to a complex real structure having nonlinear elements since it uses the frequency response function of each substurcture. Since this mehtod is performed in frequency domain, the number of equations required to identify the unknown parameters can be easily increased as many as it needed, just by not only varying excitation amplitude bot also selecting excitation frequency domain method has some advantages over the classical force-state mapping technique in the number of data points needed in curve fit and the sensitivity to response noise.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.344-347
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• 2005

Helper T(Th) cells regulate immune response by producing various kinds of cytokines in response to antigen stimulation. The regulatory functions of Th cells are promoted by their differentiation into two distinct subsets, Th1 and Th2 cells. Th1 cells are involved in inducing cellular immune response by activating cytotoxic T cells. Th2 cells trigger B cells to produce antibodies, protective proteins used by the immune system to identify and neutralize foreign substances. Because cellular and humoral immune responses have quite different roles in protecting the host from foreign substances, Th cell differentiation is a crucial event in the immune response. The destiny of a naive Th cell is mainly controlled by cytokines such as IL-4, IL-12, and IFN-${\gamma}$. To understand the mechanism of Th cell differentiation, many mathematical models have been proposed. One of the most difficult problems in mathematical modeling is to find appropriate kinetic parameters needed to complete a model. However, it is relatively easy to get qualitative or linguistic knowledge of a model dynamics. To incorporate such knowledge into a model, we propose a novel approach, fuzzy continuous Petri nets extending traditional continuous Petri net by adding new types of places and transitions called fuzzy places and fuzzy transitions. This extension makes it possible to perform fuzzy inference with fuzzy places and fuzzy transitions acting as kinetic parameters and fuzzy inference systems between input and output places, respectively.