• 대한기계학회논문집A
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• 제29권6호
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• pp.795-803
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• 2005

This paper studies the observability of calibration system with a measurement operator. The calibration system needs a simple digital indicator to measure the mobile table movements with respect to the MC coordinate. However, it yields the concern about the poor parameter observability due to measuring only a part of the movements. We uses the QR-decomposition to find the optimal calibration configurations maximizing the linear independence of rows of an observation matrix. The number of identifiable parameter is examined by the rank of the observation matrix, which represents the parameter observability. The method is applied to a 6-axis MC with parallel tilting table and the calibration results are presented. These results verify that all necessary kinematic parameters are observable and the calibration system has robustness to the noise using optimal calibration configurations.

• 대한기계학회논문집A
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• 제27권4호
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• pp.647-655
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• 2003

This paper studies the observability of calibration system with a constraint movement by a constraint operator. The calibration system with the constraint movement need only simple sensing device to check whether the constraint movements are completed within an established range. However, it yields the concern about the poor parameter observability due to the constraint movements. This paper uses the QR-decomposition to find the optimal calibration configurations maximizing the linear independence of rows of a observation matrix. The number of identifiable parameters are examined by the rank of the observation matrix, which represents the parameter observability. The method is applied to a parallel typed machining center and the calibration results are presented. These results verify that the calibration system with low-cost indicators and simple planar table is accurate as well as reliable.

• 음성과학
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• 제14권2호
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• pp.105-114
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• 2007

The performance of speaker identifier is severely degraded in noisy environments. A study suggested the concept of observation membership for enhancing performances of speaker identifier with noisy speech [1]. The method scaled observation probabilities of input speech by observation identification values decided by SNR. In the paper [1], the authors suggested heuristic parameter values for membership function. In this paper we attempt to apply particle swarm optimization (PSO) for obtaining the optimal parameters for speaker identification in noisy environments. With the speaker identification experiments using the ETRI database we prove that the optimization approach can yield better performance than using only the original membership function.

• 천문학회보
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• 제38권2호
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• pp.35.2-35.2
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• 2013

I will present a new approach to constrain galaxy physical parameters from the combined interpretation of stellar and nebular emission in wide ranges of observations. This approach relies on a comprehensive library of synthetic spectra, assembled using state-of-the-art models of star formation and chemical enrichment histories, stellar population synthesis, nebular emission and attenuation by dust. We focus on the constraints set by 5-band photometry and low- and medium-resolution spectroscopy at optical rest wavelengths on a few physical parameters characterizing the stars and interstellar medium. Since these parameters cannot be known a priori for any galaxy sample, we assess the accuracy to which they can be retrieved by simulating 'pseudo-observations' using models with known parameters. We find that the combined analysis of stellar and nebular emission in low-resolution (50A FWHM) galaxy spectra provides valuable constraints on all physical parameters. The approach can be extended to the analysis of any type of observation and during this talk i will present some applications to observed galaxies up to redshift 1.5.

• International Journal of Control, Automation, and Systems
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• 제6권1호
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• pp.109-118
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• 2008

We present two estimators for discrete non-Gaussian and nonstationary probability density estimation based on a dynamic Bayesian network (DBN). The first estimator is for off line computation and consists of a DBN whose transition distribution is represented in terms of kernel functions. The estimator parameters are the weights and shifts of the kernel functions. The parameters are determined through a recursive learning algorithm using maximum likelihood (ML) estimation. The second estimator is a DBN whose parameters form the transition probabilities. We use an asymptotically convergent, recursive, on-line algorithm to update the parameters using observation data. The DBN calculates the state probabilities using the estimated parameters. We provide examples that demonstrate the usefulness and simplicity of the two proposed estimators.

• 한국국방경영분석학회지
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• 제11권2호
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• pp.69-82
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• 1985

In this study, we consider the simultaneous estimation of the parameters of the distribution of p independent Poisson random variables using the weighted loss function. The relation between the estimation under the weighted loss function and the case when more than one observation is taken from some population is studied. We derive an estimator which dominates Tsui and Press's estimator when certain conditions hold. We also derive an estimator which dominates the maximum likelihood estimator(MLE) under the various loss function. The risk performances of proposed estimators are compared to that of MLE by computer simulation.

• Communications for Statistical Applications and Methods
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• 제3권1호
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• pp.235-242
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• 1996

When the linear growth birth and death process observed at a set of equidistant time points, McNeil and Weiss (1997) present a method for simultaneously estimating the Malthusian parameter and the sum of the two parameters under wery restricted assumptions using a diffusion approximation. This article suggests a method, which does not require the restrictions given by Weiss, for estimating simultaneously the Malthusian parameter and the sum of the two parameters.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2003년도 추계학술발표회 논문집
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• pp.373-378
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• 2003

This study deals with development of transformation tool for transformation of digital map coordinates systems using by the best fit transformation parameters which are determined between the local geodetic datum and geocentric datum (ITRF2000) in Korea and distortion modelling derived from collocation method. We used 107 control points as a common points. For analyzing the derived parameters, another 83 common points are tested. Finally, the best fit parameters are determined from Molodensky-Badekas model after considering the RMSE, maximum value, minimum values, and 95% confidence interval of residuals. after transformation of best fit parameters and distortion modelling, we could develop transformation tools with advenced accuracy. so it is possible to perform on transformation of digital map with scale 1:5,000. and we tested accuracy eveluation through analysis between transformation results and field results of GPS observation.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2009년도 추계학술대회 논문집
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• pp.375-378
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• 2009

Hot press forming is a new forming process which also names as hot stamping. It can greatly enhance the formability of forming parts. This paper researches the formability of boron steel sheet in hot bending process which is a kind of hot press forming. In the text, the influence of hot press forming processing parameters, such as the heating temperature, blank holding force, punch speed and punch and die radius, on the mechanics properties and microstructure of the hot bending parts was analyzed by tension test and the metallographic observation on the parts with various processing parameters. The relationship between blank holding force and punch load was also presented.

• 전기학회논문지
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• 제63권3호
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• pp.383-388
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• 2014

This paper describes a wave modeling method using low-cost sensors. Wave modeling is applied to the wave monitoring system for accurate measurement of ocean wave parameters. The observation of ocean wave parameters is necessary to improve the accuracy of forecast of ocean wave condition. However, the ocean wave parameters measured by a low-cost wave monitoring system suffer from several errors. Therefore we introduce a wave modeling method to compensate the ocean wave parameters corrupted by errors. The proposed method is analyzed using experiments within controlled environment. It is verified that the accuracy of low-cost wave monitoring system can be increased by the proposed method.