• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.260-263
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• 2016

Recently high dynamic range imaging technique is hot issue in computer graphic area. We present a progressive tone mapping algorithm, which is based on weighted least squares optimization framework. Our approach combines weighted leastsquaresfiltering with iCAM06, for showing more perceptual high dynamic range images in conventional display, while avoiding visual halo artifacts. We decompose high dynamic range image into base layer and detail layer. The base layer has large scale variation, it is obtained by using weighted least squares filtering, and then the base layer incorporates iCAM06 model. Then, adaptive compression on the base layer according to human visual system. Only the base layer reduces contrast, and preserving detail. The resultshows more perceptual color appearance and preserve fine detail, while avoiding common artifacts.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.321-327
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• 1993

In order to maintain the cutting force at a desired level during peripheral end milling processes in spite of variation of the depth of cut and other machining conditions, a feedrate override. Apaptive Control Constraint (ACC) system are developed. Feedrate override was accomplished by a developed MMC board and PMC interface techniques. Nonlinear model of the cutting process was linearized as an adaptive model with time varying paramrters. Integral type estimators were introduced for on-line identification of cutting and control parameters in peripheral and milling processes. Zero Order Jold (ZOH) type degital control methodology which uses pole-placement concepts was applied for the ACC system. Performance of the developed ACC system was confirmed on the vertical machining center equipped with FANUC OMC for a large amount of experiment

• Journal of the Korean Society for Precision Engineering
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• v.21 no.2
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• pp.74-82
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• 2004

In this paper, a disturbance feedforward compensator design technique is proposed for an active magnetic bearing system subject to base motion for attenuating disturbance responses. In the consideration of the requirements on the model accuracy in the model based compensator designs, an experimental feedforward compensator design based on adaptive estimation by means of the Multiple Filtered-x least mean square(MFXLMS) algorithm is proposed. The performance and the effectiveness of the proposed technique will be presented in the succeeding paper in which the proposed technique is applied to a 2-DOF active magnetic bearing system subject to base motion.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.713-727
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• 2005

Among different regression approaches, nonparametric procedures perform well under different conditions. In practice it is very hard to identify which is the best procedure for the data at hand, thus model combination is of practical importance. In this paper, we focus on one dimensional regression with fixed design. Polynomial regression, local regression, and smoothing spline are considered. The data are split into two parts, one part is used for estimation and the other part is used for prediction. Prediction performances are used to assign weights to different regression procedures. Simulation results show that the combined estimator performs better or similarly compared with the estimator chosen by cross validation. The combined estimator generates a similar risk to the best candidate procedure for the data.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.1062-1067
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• 2005

This paper discusses a skeleton feature extraction method for ubiquitous robot system. The skeleton features are used to analyze human motion and pose estimation. In different conventional feature extraction environment, the ubiquitous robot system requires more robust feature extraction method because it has internal vibration and low image quality. The new hybrid silhouette extraction method and adaptive skeleton model are proposed to overcome this constrained environment. The skin color is used to extract more sophisticated feature points. Finally, the experimental results show the superiority of the proposed method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.441-445
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• 2004

In this paper, we deal with an inventory model of a multi-stage, serial supply chain system where a single product type and nonstationary customer demand pattern are considered. The retailer and suppliers place their orders according to an echelon-stock based replenishment control policy. We assume that the suppliers can access online information on the demand history and use this information when making their replenishment decisions. Using a reinforcement learning technique, the inventory control parameters are designed to adaptively change as the customer demand pattern is altered, in order to maintain a given target service level. Through a simulation based experiment, we verified that our approach is good for maintaining the target service level.

• Journal of Electrical Engineering and Technology
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• v.2 no.3
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• pp.353-357
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• 2007

The bearing diagnostics method is presented in this paper using fuzzy inference based on vibration data. Both time-domain and frequency-domain features are used as input data for bearing fault detection. The Adaptive Network based Fuzzy Inference System (ANFIS) and Genetic Algorithm (GA) have been proposed to select the fuzzy model input and output parameters. Training results give the optimized fuzzy inference system for bearing diagnosis based on measured vibration data. The result is also tested with other sets of bearing data to illustrate the reliability of the chosen model.

• BMB Reports
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• v.30 no.1
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• pp.7-12
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• 1997

The kinetics of the interesterification of triolein and stearic acid catalyzed by immobilized Rhizopus delemar lipase were studied in a batch operation. In order to clarify the mechanisms of this reaction, three models are discussed under various conditions in terms of the ratio of triolein and stearic acid. The rate constants involved in the proposed model were determined by combining the numerical Gauss-elemination method, and the trial-and-error method so as to fit the calculated results with the experimental data. The accuracy of the obtained rate constants was confirmed after they were substituted for simultaneous differential equations and the equations simulated using an adaptive step-size Runge-Kutta method. Finally, the model which agrees with the calculated results and the experimental data was selected.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.812-814
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• 1999

In this paper, we propose a new control algorithm based on the neural network(NN) feedback compensation with a desired trajectory modification. The proposed algorithm decreases trajectory errors by a feed-forward desired torque combined with a neural network feedback torque component. And, to robustly control the tracking error, we modified the desired trajectory by variable structure concept smoothed by a fuzzy logic. For the numerical simulation, a 2-link robot manipulator model was assumed. To simulate the disturbance due to the modelling uncertainty. As a result of this simulation, the proposed method shows better trajectory tracking performance compared with the CTM and decreases the chattering in control inputs.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.780-785
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• 2007

Accurate and fast haptic simulations of deformable objects are desired in many applications such as medical virtual reality. In haptic interactions with a coarse model, the number of nodes near the haptic interaction region is too few to generate detailed deformation. Thus, local refinement techniques need to be developed. Many approaches have employed purely geometric subdivision schemes, but they are not proper in describing the deformation behavior of deformable objects. This paper presents a continuum mechanics-based finite element adaptive method to perform haptic interaction with a deformable object. This method superimposes a local fine mesh upon a global coarse model, which consists of the entire deformable object. The local mesh and the global mesh are coupled by the s-version finite element method (s-FEM), which is generally used to enhance accurate solutions near the target points even more. The s-FEM can demonstrate a reliable deformation to users in real-time.