• Korean Journal of Computational Design and Engineering
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• v.14 no.1
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• pp.10-17
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• 2009

Surface detection and parameter estimation in point cloud is a relevant subject in CAD/CAM, reverse engineering, computer vision, coordinate metrology and digital factory. In this paper we present a software for a fully automatic surface detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting, which work interactively. Our newly developed algorithms for orthogonal distance fitting(ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. We demonstrate the performance of the software on a variety of point clouds generated by laser radar, computer tomography, and stripe-projection method.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.3
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• pp.399-406
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• 1996

This paper presents a method of hierarchical state estimation of the time-varying linear systems via Block-pulse function(BPF). When we estimate the state of the systems where noise is considered, it is very difficult to obtain the solutions because minimum error variance matrix having a form of matrix nonlinear differential equations is included in the filter gain calculation. Therefore, hierarchical approach is adapted to transpose matrix nonlinear differential equations to a sum of low order state space equation from and Block-pulse functions are used for solving each low order state space equation in the form of simple and recursive algebraic equation. We believe that presented methods are very attractive nd proper for state estimation of time-varying linear systems on account of its simplicity and computational convenience. (author). 13 refs., 10 figs.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1516-1521
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• 2004

An inverse boundary analysis of surface radiation in an axisymmetric cylindrical enclosure has been conducted in this study. Net energy exchange method was used to calculate the radiative heat flux on each surface, and a hybrid genetic algorithm was adopted to minimize an objective function, which is expressed by sum of square errors between estimated and measured heat fluxes on the design surface. We have examined the effects of the measurement error as well as the number of measurement points on the estimation accuracy.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.5
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• pp.1273-1279
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• 2016

Flow boiling pressure drop in multi channels was experimently investigated. The multi channel has a width and depth of 0.45 and 0.2mm respectively, and comprises 15 parallel channels. The measured total pressure drop is expressed by the sum of the frictional pressure drop and acceleration pressure drop. In order to predict the total pressure drop, it is required to obtain the correct frictional pressure drop. The existing correlations to predict the frictional pressure were compared with measured frictional pressure drop. The new correlation was developed in the form of the Chisholm correlation. It was related to Chisholm Constant B as a function of Martinelli parameter. The new correlation predicted the experimental data within a mean absolute error of 5.5%.

• ETRI Journal
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• v.35 no.4
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• pp.714-717
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• 2013

Peak power reduction techniques in orthogonal frequency division multiplexing (OFDM) has been an important subject for many researchers for over 20 years. In this letter, we propose a side-information-free technique that is based on the concept of random variable (RV) transformation. The suggested method transforms RVs into other RVs, aiming to reshape the constellation that will consequently produce OFDM symbols with a reduced peak-to-average power ratio. The proposed method has no limitation on the mapping type or the mapping order and has no significant effect on the bit error rate performance compared to other methods presented in the literature. Additionally, the computational complexity does not increase.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.317-318
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• 2007

In this paper, we propose an efficient timing closure methodology during physical implementation. Many types of slacks and closure solutions were introduced case-by-case. The major part of violations was managed by specified tools, but the exceptionally generated minor violation which was occurred through correlation error between tools was manually corrected by ASIC engineer. From the proposed method, we identified that the best effective method is to decrease the sum of intrinsic delay in case of setup time violation.

• Journal of the Optical Society of Korea
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• v.20 no.6
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• pp.762-769
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• 2016

The dynamic modulation transfer function (MTF) for image degradation caused by sinusoidal vibration is formulated based on a Bessel function of the first kind. The presented method makes it possible to obtain an analytical MTF expression derived for arbitrary frequency sinusoidal vibration. The error obtained by the use of finite order sum approximations instead of infinite sums is investigated in detail. Dynamic MTF exhibits a stronger random behavior for low frequency vibration than high frequency vibration. The calculated MTFs agree well with the measured MTFs with the slant edge method in imaging experiments. With the proposed formula, allowable amplitudes of any frequency vibration are easily calculated. This is practical for the analysis and design of the line-of-sight stabilization system in the remote sensing camera.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1796-1801
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• 2009

This paper is concerned with the problem of delay-dependent robust $H_{\infty}$ filtering for uncertain descriptor systems with time-varying delay. The considering uncertainty is convex compact set of polytoic type. The purpose is the design of a linear filter such that the resulting filtering error descriptor system is regular, impulse-free, and asymptotically stable with $H_{\infty}$ norm bound. By establishing a finite sum inequality based on quadratic terms, a new delay-dependent bounded real lemma (BRL) for delayed descriptor systems is derived. Based on the derived BRL, a robust $H_{\infty}$ filter is designed in terms of linear matrix inequaltity (LMI). Numerical examples are given to illustrate the effectiveness of the proposed method.

• Journal of Sensor Science and Technology
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• v.25 no.6
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• pp.418-422
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• 2016

A filtering algorithm based on the decentralized moving average Kalman filter with uncertainties is proposed in this paper. The proposed filtering algorithm presented combines the Kalman filter with the moving average strategy. A decentralized fusion algorithm with the weighted sum structure is applied to the local moving average Kalman filters (LMAKFs) of different window lengths. The proposed algorithm has a parallel structure and allows parallel processing of observations. Hence, it is more reliable than the centralized algorithm when some sensors become faulty. Moreover, the choice of the moving average strategy makes the proposed algorithm robust against linear discrete-time dynamic model uncertainties. The derivation of the error cross-covariances between the LMAKFs is the key idea of studied. The application of the proposed decentralized fusion filter to dynamic systems within a multisensor environment demonstrates its high accuracy and computational efficiency.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.195-202
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• 2017

We can sometimes find instability against numerical solutions in nonlinear regression. All iterative procedures in nonlinear regression require initial parameter values to be selected. Poor starting values may result in convergence to an unwanted stationary point of the error sum of squares surface. Starting values can sometimes cause the chaos effect in the nonlinear regression model. We can find the chaos phenomena with the convergence plot of starting values in the parameter space.