• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.268-272
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• 1996

Error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The camera calibration is a necessary procedure for stereo vision-based depth computation. Intra and extra parameters should be obtain to determine the relation between image and world coordination through experiment. One difficulty is in camera alignment for parallel installation: placing two CCD arrays in a plane. No effective methods for such alignment have been presented before. Some amount of depth error caused from such non-parallel installation of cameras is inevitable. If the pixel distance parameter which is one of intra parameter is calibrated with known points, such error can be compensated in some amount. Such error compensation effect with the calibrated pixel distance parameter is demonstrated with some experimental results.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1004-1011
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• 2016

The inaccurate model parameters in the predictive current control of surface-mounted permanent magnet synchronous motor (SMPMSM) affect the current dynamic response and steady-state error. This paper presents a model parameter correction algorithm based on the relationship between the errors of model parameters and the static errors of dq-axis current. In this correction algorithm, the errors of inductance and flux are corrected in two steps. Resistance is ignored. First, the proportional relations between inductance and d-axis static current errors are utilized to correct the error of model inductance. Second, the flux is corrected by utilizing the proportional relations between flux and q-axis static current errors under the condition that inductance is corrected. An experimental study with a 100 W SMPMSM is performed to validate the proposed algorithm.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1212-1214
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• 2003

The usual technique of correction and positioning of film image of RS require enough control points to provide the geographic coordinate. Some distortion and error caused by earth curvature and terrain and photograph tilt can't be eliminated by these ways. In this paper a set of technique of systemic correction and positioning of remote sensing image base on orbit parameter is described, some questions in its realization and their solvent also included.

• Economic and Environmental Geology
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• v.44 no.6
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• pp.475-483
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• 2011

Quantitative estimate of manganese nodules based on the operation of a free fall grab (FFG) needs to be corrected because of its less retrieval ability. Previously, the correction parameter of the nodule abundance collected by FFG was calculated based on the image analysis of the photos of bottom sediment in the northern sector of the nodule exploration area of Korea in the NE equatorial Pacific. However, nodules in the southern sector are commonly covered by sediment, which may prevent the use of the correction parameter estimated by photographic techniques. In this study, we attempted dual nodule sampling at the same location by different equipments (i.e. box corer (BC) and FFG) to examine the previous correction parameter of nodule abundance for FFG operation. During the exploration cruises in 2007 to 2009, Mn-nodules were collected from 40 stations both by BC and FFG in the southern sector. The correlation analysis between BC and FFG operations revealed that the BC collected nodules 1.43 times larger than FFG. Our result suggests that the correction parameter of 1.43 can be applied for collection of FFG data to estimate Mn-nodule distribution in the southern sector. The obtained parameter is similar to the previous parameter (1.42~1.45) calculated by the image analysis method, indicating an usefulness of new correction parameter suggested by this study.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.124-131
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• 2016

Baseline correction is very important due to influence on performance of spectral analysis in application of spectroscopy. Baseline is often estimated by parameter selection using visual inspection on analyte spectrum. It is a highly subjective procedure and can be tedious work especially with a large number of data. For these reasons, it is an objective and automatic procedure is necessary to select optimal parameter value for baseline correction. Asymmetrically reweighted penalized least squares (arPLS) based on penalized least squares was proposed for baseline correction in our previous study. The method uses a new weighting scheme based on the generalized logistic function. In this study, we present an automatic selection of optimal parameter for baseline correction using arPLS. The method computes fitness and smoothness values of fitted baseline within available range of parameters and then selects optimal parameter when the sum of normalized fitness and smoothness gets minimum. According to the experimental results using simulated data with varying baselines, sloping, curved and doubly curved baseline, and real Raman spectra, we confirmed that the proposed method can be effectively applied to optimal parameter selection for baseline correction using arPLS.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1147-1155
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• 2018

This paper presents an improved method to determine the internal parameters for improving accuracy of a lithium ion battery equivalent circuit model. Conventional methods for the parameter estimation directly using the curve fitting results generate the phenomenon to be incorrect due to the influence of the internal capacitive impedance. To solve this phenomenon, simple correction procedure with transient state analysis is proposed and added to the parameter estimation method. Furthermore, conventional dynamic equation for correction is enhanced with advanced RC impedance dynamic equation so that the proposed modeling results describe the battery dynamic characteristics more exactly. The improved accuracy of the battery model by the proposed modeling method is verified by single cell experiments compared to the other type of models.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.605-606
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• 2005

Depth error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. Intra and extra parameters should be obtain to determine the relation between image and world coordination through experiment. One difficulty is in camera alignment for parallel installation: placing two CCD arrays in a plane. If the pixel distance parameter which is one of intra parameter is calibrated with known points, such error can be compensated in some amount. Such error compensation effect with the calibrated pixel distance parameter is demonstrated with various experimental results.

• Magazine of the Korean Society of Agricultural Engineers
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• v.42 no.6
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• pp.106-114
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• 2000

In order to evaluate the shear characteristics of undisturbed weathered granite soil which is a typical residual soil in Korea, the mechanical properties are first investigated and discussed by carrying out a series of direct shear test and then dilatancy correction is performed by using Taylor’s correction equation. In this study, specimens are sampled at Pungam(-3, -8, -13m below ground surface), Kwangju and Iksan(-5m below ground surface), Jeonbuk. The test results are summarized as follows: 1) Mohr-Coulomb failure criterion is not linear under the low confining pressure. 2) The value of cohesion is smaller than usually determined value in low pressure region. 3) The value of strength parameter c and ø which are corrected by Taylor’s correction equation is a little bit small.

• Quantitative Bio-Science
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• v.37 no.2
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• pp.133-141
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• 2018

Graphical lasso is one of the most popular methods to estimate a sparse precision matrix, which is an inverse of a covariance matrix. The objective function of graphical lasso imposes an ${\ell}_1$-penalty on the (vectorized) precision matrix, where a tuning parameter controls the strength of the penalization. The selection of the tuning parameter is practically and theoretically important since the performance of the estimation depends on an appropriate choice of tuning parameter. While information criteria (e.g. AIC, BIC, or extended BIC) have been widely used, they require an asymptotically unbiased estimator to select optimal tuning parameter. Thus, the biasedness of the ${\ell}_1$-regularized estimate in the graphical lasso may lead to a suboptimal tuning. In this paper, we propose a two-staged bias-correction procedure for the graphical lasso, where the first stage runs the usual graphical lasso and the second stage reruns the procedure with an additional constraint that zero estimates at the first stage remain zero. Our simulation and real data example show that the proposed bias correction improved on both edge recovery and estimation error compared to the single-staged graphical lasso.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.500-506
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• 2019

In this study, we present a decision function of optimal smoothing parameter for baseline correction using Asymmetrically reweighted penalized least squares (arPLS). Baseline correction is very important due to influence on performance of spectral analysis in application of spectroscopy. Baseline is often estimated by parameter selection using visual inspection on analyte spectrum. It is a highly subjective procedure and can be tedious work especially with a large number of data. For these reasons, an objective procedure is necessary to determine optimal parameter value for baseline correction. The proposed function is defined by modeling the median value of possible parameter range as the length and order of the background signal. The median value increases as the length of the signal increases and decreases as the degree of the signal increases. The simulated data produced a total of 112 signals combined for the 7 lengths of the signal, adding analytic signals and linear and quadratic, cubic and 4th order curve baseline respectively. According to the experimental results using simulated data with linear, quadratic, cubic and 4th order curved baseline, and real Raman spectra, we confirmed that the proposed function can be effectively applied to optimal parameter selection for baseline correction using arPLS.