• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.425-426
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• 2006

Overdriving schemes are used to improve the response time of liquid crystal display. Typically they are implemented by using LUTs (look-up table) within an image processor. However, the size of LUT is limited by the physical memory size and system cost. In this paper, we present an improved method for LUT implementation using linear interpolation and piecewise least-square polynomial regression. Using the proposed method, the performance of LUT can be improved and memory size of that can be reduced.

• Computational Structural Engineering
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• v.2 no.2
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• pp.113-119
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• 1989

Methods for identification of modal properties of linear structures are presented. The extended Kalman filtering technique is employed. The state equation is formulated by two different ways, namely by the time domain and frequency domain approaches. Verifications are carried out by using the simulated records of ground acceleration and structural response. Then the techniques are applied to the estimation of modal parameters of a scaled model for a 3-story building which is installed on a shaking table.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.211-217
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• 1995

Conventional linear control fails to provide precise positioning of a control object under the influence of friction, deadzone, saturation, etc. This paper proposes a high-precision control scheme for a precise point-to-point positioning system, called an X-Y table, even under the same influences above. The proposed scheme is composed of a fuzzy precompensator and a PD controller. The fuzzy precompensator is employed to improve the performance of the PD controller. Its fuzzy rules are obtained from experimental evolutionary programming (EP), not from an expert. The effectiveness of the scheme is demonstrated by experiments on the X-Y table. with a positioning error of within 1$\mu\textrm{m}$.

• Journal of the Korean Home Economics Association
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• v.20 no.4
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• pp.45-52
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• 1982

This research is aimed at establishing nominal sizes for the clothes manufacturers by using the results from a comprehensive study with 6~9 year-old girls. From the results of the data analysis, we found the following points: 1) The stature and the weight, which have strong correlations with each part of the body, are selected as the independent variables. 2) The frequency-distribution was calculated from the variable quantities(Table 1~5). 3) The nominal size for the jacket, blouse, skirt, and trousers was estimated by the frequency-distribution(Table 6~9). 4) A multiple linear regression model to estimate the 18 items was formulated.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1159-1161
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• 2005

This study uses a design of experiments to explain correlations between the objective function and design variables. Analysis of means, analysis of variance and table of orthogonal array were carried out. The change of shape design variable for TFLM based on the table of orthogonal array is made. Therefore this study carried to decide design variables for maximizing thrust force of TFLM. we showed improved design variables.

• Nuclear Engineering and Technology
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• v.35 no.4
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• pp.286-298
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• 2003

A steam explosion module, STX, has been developed using the mechanistic steam explosion analysis code, TEXAS-V, in order to estimate the dynamic load with steam explosion by implementing the module to the integrated safety analysis code, MELCOR. One of the difficulties in using mechanistic steam explosion codes is that they do not have any obvious criteria for defining some uncertain parameters such as triggering timing, triggering magnitude, mesh axial length and mesh cross-sectional area. These parameters have been user decision parts in the past. Steam explosion sample calculations and sensitivity studies on uncertain parameters were conducted to investigate those uncertain parameters. The TEXAS-V simulations were summarized in the format of a look-up table and a linear interpolation technique was adopted to calculate the steam explosion load between the data points in the table. The STX-module merged with MELCOR showed the same results as the original MELCOR and additionally it could estimate the steam explosion load in the reactor cavity.

• Journal of the Korean Society of Mechanical Technology
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• v.20 no.6
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• pp.872-878
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• 2018

Steam tables including superheated, saturated and compressed region were simultaneously modeled using the neural networks. Pressure and temperature were used as two inputs for superheated and compressed region. On the other hand Pressure and dryness fraction were two inputs for saturated region. The outputs were specific volume, specific enthalpy and specific entropy. The neural network model were compared with the linear interpolation model in terms of the percentage relative errors. The criterion of judgement was selected with the percentage relative error of 1%. In conclusion the neural networks showed better results than the interpolation method for all data of superheated and compressed region and specific volume of saturated region, but similar for specific enthalpy and entropy of saturated region.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.1
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• pp.79-83
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• 2000

Although it is well known that fuzzy learning controller is powerful for nonlinear systems, it is very difficult to apply a learning method if they are unstable. An unstable system diverges for impulse input. This divergence makes it difficult to learn the rules unless we can find the initial rules to make the system table prior to learning. Therefore, we introduced LQR(Linear Quadratic Regulator) technique to stabilize the system. It is a state feedback control to move unstable poles of a linear system to stable ones. But, if the system is nonlinear or complicated to get a liner model, we cannot expect good results with only LQR. In this paper, we propose that the LQR law is derived from a roughly approximated linear model, and next the fuzzy controller is tuned by the adaptive on-line learning with the real nonlinear plant. This hybrid controller of LQR and fuzzy learning was superior to the LQR of a linearized model in unstable nonlinear systems.

• The Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.337-346
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• 2004

The Pearson chi-square goodness-of-fit test and the likelihood ratio tests are usually used for testing independence in two-way contingency tables under random sampling. But both of these tests may provide false results for the contingency table with clustered observations. In this case we consider the generalized linear mixed model which includes random effects of clustering in addition to the fixed effects of covariates. Both the heterogeneity between clusters and the dependency within a cluster can be explained via generalized linear mixed model. In this paper we introduce several types of generalized linear mixed model for testing independence in contingency tables with clustered observations. We also discuss the fitting of these models through a real dataset.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.4 s.109
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• pp.394-403
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• 2006

A new equivalent linearization technique is proposed for a friction damper-brace system (FDBS) idealized as a elastoplastic system. The equivalent linearization technique utilizes secant stiffness and dissipated energy defined by the probability distribution of the extremal displacement of the FDBS. In addition, a conversion scheme is proposed so that an equivalent linear system is designed first and converted to the FDBS. For comparative study, an existing model update technique based on system identification is modified in a form appropriate to update single element. For the purpose of verification, shaking table tests of a small scale three-story shear building model, in which a rotational FDBS is installed, are conducted and equivalent linear systems are obtained using the proposed technique and the model update technique. Complex eigenvalue analysis is conducted for those equivalent linear systems, and the natural frequencies and modal damping ratios are compared with those obtained from system identification. Additionally, RMS and peak responses obtained from time history analysis of the equivalent linear systems are compared with measured ones.