• The Journal of Korea Robotics Society
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• v.8 no.2
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• pp.104-115
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• 2013

For natural human-robot interaction, we need to know location and shape of facial feature in real environment. In order to track facial feature robustly, we can use the method combining particle filter and active appearance model. However, processing speed of this method is too slow. In this paper, we propose two ideas to improve efficiency of this method. The first idea is changing the number of particles situationally. And the second idea is switching the prediction model situationally. Experimental results is presented to show that the proposed method is about three times faster than the method combining particle filter and active appearance model, whereas the performance of the proposed method is maintained.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.1
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• pp.64-76
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• 2015

This paper suggests applying pseudospectral model predictive method for exo-atmospheric guidance. The method is a fusion of pseudospectral law and model predictive control, in which a two point boundary value problem is formulated using model predictive approach and solved by applying pseudospectral law. In this work, the method is applied to exo-atmospheric guidance with specific target requirement. The existing exo-atmospheric guidance methods suffice general requirements for guidance, but cannot ensure specific target constraints; whereas, the presented method is able to do so. The proposed guidance law is assessed through simulation of perturbed cases, and the tests suggest that the method is able to operate semi-autonomously under control and thrust vector perturbations.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.3
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• pp.264-270
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• 2011

A new method for creating a logical data model is proposed. The logical data model developed by the method defines table, primary key, foreign key, and fields. The framework of the logical data model is constructed by modeling the relationships between events and their related entity types. The proposed method consists of a series of objective and quantitative decisions such as maximum cardinality of relationships and functional dependency between the primary key and attributes. Even beginners to database design can use the methology as long as they understand such basic concepts about relational databases as primary key, foreign key, relationship cardinality, parent-child relationship, and functional dependency. The simple and systematic approach minimizes decision errors made by a database designer. In practial database design the method creates a logical data model in Boyce-Codd normal form unless the user of the method makes a critical decision error, which is very unlikely.

• International Journal of Naval Architecture and Ocean Engineering
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• v.2 no.1
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• pp.14-23
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• 2010

A numerical model was developed for simulating a three-dimensional multilayer hydrodynamic and thermodynamic model in domains with irregular bottom topography. The model was designed for examining the interactions between flow and topography. The model was based on the three-dimensional Navier-Stokes equations and was solved using the fractional step method, which combines the finite difference method in the horizontal plane and the finite element method in the vertical plane. The numerical techniques were described and the model test and application were presented. For the model application to the northern part of Ariake Sea, the hydrodynamic and thermodynamic results were predicted. The numerically predicted amplitudes and phase angles were well consistent with the field observations.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.12
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• pp.209-219
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• 1995

As a new algorithm for RC tree delay estimation, we propose a $\tau$-model of the driver and a moment propagation method. The $\tau$-model represents the driver as a Thevenin equivalent circuit which has a one-time-constant voltage source and a linear resistor. The new driver model estimates the input voltage waveform applied to the RC more accurately than the k-factor model or the 2-piece waveform model. Compared with Elmore method, which is a lst-order approximation, the moment propagation method, which uses $\pi$-model loads to calculate the moments of the voltage waveform on each node of RC trees, gives more accurate results by performing higher-order approximations with the same simple tree walking algorithm. In addition, for the instability problem which is common to all the approximation methods using the moment matching technique, we propose a heuristic method which guarantees a stable and accureate 2nd order approximation. The proposed driver model and the moment propagation method give an accureacy close to SPICE results and more than 1000 times speedup over circuit level simulations for RC trees and FPGA interconnects in which the interconnect delay is dominant.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.4
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• pp.249-253
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• 2012

This paper suggests a numerical method for valuation of American options under the Kou model (double exponential jump diffusion model). The method is based on approximation of underlying asset price using a finite-state, time-homogeneous Markov chain. We examine the effectiveness of the proposed method with simulation results, which are compared with those from the conventional numerical method, the finite difference method for PIDE (partial integro-differential equation).

• Management Science and Financial Engineering
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• v.19 no.2
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• pp.37-42
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• 2013

This paper suggests a numerical method for valuation of European and American options under the two L$\acute{e}$vy Processes, Normal Inverse Gaussian Model and the Variance Gamma model. The method is based on approximation of underlying asset price using a finite-state, time-homogeneous Markov chain. We examine the effectiveness of the proposed method with simulation results, which are compared with those from the existing numerical method, the lattice-based method.

• Structural Engineering and Mechanics
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• v.52 no.2
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• pp.261-274
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• 2014

An accurate finite element (FE) model of a structure is essential for predicting reliably its dynamic characteristics. Such a model is used to predict the effects of structural modifications for dynamic design of the structure. These modifications may be imposed by design alterations for operating reasons. Most of the model updating techniques neglect damping and so these updated models can't be used for accurate prediction of vibration amplitudes. This paper deals with the basic formulation of damped finite element model updating method and its use for structural dynamic modifications. In this damped damped finite element model updating method, damping matrices are updated along with mass and stiffness matrices. The damping matrices are updated by updating the damping coefficients. A case involving actual measured data for the case of F-shaped test structure, which resembles the skeleton of a drilling machine is used to evaluate the effectiveness of damped FE model updating method for accurate prediction of the vibration levels and thus its use for structural dynamic modifications. It can be concluded from the study that damped updated FE model updating can be used for structural dynamic modifications with confidence.

• Journal of the Korean Statistical Society
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• v.28 no.3
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• pp.311-324
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• 1999

The problem of 'outliers', observations which look suspicious in some way, has long been one of the most concern in the statistical structure to experimenters and data analysts. We propose a model for an outlier problem and also analyze it in linear regression model using a Bayesian approach. Then we use the mean-shift model and SSVS(George and McCulloch, 1993)'s idea which is based on the data augmentation method. The advantage of proposed method is to find a subset of data which is most suspicious in the given model by the posterior probability. The MCMC method(Gibbs sampler) can be used to overcome the complicated Bayesian computation. Finally, a proposed method is applied to a simulated data and a real data.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.11
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• pp.619-625
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• 2003

We proposed an optimum PID controller design method of the Smith Predictor It can be applied to various processes. The real process is approximated via the second order plus time delay model (SOPTD) whose parameters are specified through a model reduction algorithm. We already proposed a new model reduction method that considered four point in the Nyquist curve to reduced the steady state error between the real process model and the reduced model using the gradient decent method and the genetic algorithms. In addition, the Smith predictor is used to compensate time delay of the real process model. In this paper, the new optimum parameter tuning algorithm for PID controller of the Smith Predictor is proposed through ITAE as performance index. The Simulation results show the validity and improvement of performance for various processes.