• International Journal of Precision Engineering and Manufacturing
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• 제3권3호
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• pp.5-11
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• 2002

This paper describes the methods for calibration and evaluation of the relative expanded uncertainty of a multi-axis force/moment sensor. In order to use the sensor in the industry, it should be calibrated and its relative expanded uncertainty should be also evaluated. At present, the confidence of the sensor is shown with only interference error. However, it is not accurate, because the calibrated multi-axis force/moment sensor has an interference error as well as a reproducibility error of the sensor, etc. In this paper, the methods fur calibration and for evaluation of the relative expanded uncertainty of a multi-axis force/moment sensor are newly proposed. Also, a six-axis force/moment sensor is calibrated with the proposed calibration method and the relative expanded uncertainty is evaluated using the proposed uncertainty evaluation method and the calibration results. It is thought that the methods fur calibration and evaluation of the uncertainty can be usually used for calibration and evaluation of the uncertainty of the multi-axis force/moment sensor.

• 대한물리치료과학회지
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• 제10권2호
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• pp.53-61
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• 2003

The purposes of this study were to describe and compare pint moments according to 6 types of gait methods during free speed. 15 volunteers(7 male, 8 female: mean age = 23.33 yrs.) participated and performed 6 types of gait methods. From the 3 types of pint moments of lower extremities(hip, knee, ankle and foot), the following results were made: 1. In left hip pint, the flexion-extension moment was not significantly different, but the adduction-abduction moment and rotation moment were showed different curves during stance phase. 2. In left knee pint, the flexion-extension moment was not significantly different, but the varus-valgus moment and rotation moment were showed different curves during stance phase. 3. In left ankle and foot the dorsiflexion-plantarflexion moment was not significantly different but the varus-valgus moment and rotation moment were showed different curves during stance phase. In conclusion, because weight loading gait with 10-20% of body weight were normal gait patterns, It was inferred that all weight loading gaits did not indicate noxious reactions of human body.

• 대한화학회지
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• 제22권4호
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• pp.229-238
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• 1978

Spherical harmonic의 전개방법과 쌍극자모멘트의 행렬요소를 Mulliken의 overlap integral로 전환시키는 방법을 사용하여 쌍극자모멘트의 행렬요소를 계산하는 두가지 방법을 발전시켰다. 이 두 방법에 의하여 계산한 쌍극자모멘트행렬요소의 값은 서로 일치하였다.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.285-294
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• 2005

This paper deals with the comparison of parameter estimation methods in a 3-parameter Kappa distribution which is sometimes used in flood frequency analysis. Method of moment estimation(MME), L-moment estimation(L-ME), and maximum likelihood estimation(MLE) are applied to estimate three parameters. The performance of these methods are compared by Monte-carlo simulations. Especially for computing MME and L-ME, three dimensional nonlinear equations are simplified to one dimensional equation which is calculated by the Newton-Raphson iteration under constraint. Based on the criterion of the mean squared error, L-ME (or MME) is recommended to use for small sample size( n$\le$100) while MLE is good for large sample size.

• Communications for Statistical Applications and Methods
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• 제16권1호
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• pp.137-141
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• 2009

We study on selecting the kernel weighting function in smoothing moment conditions for dependent processes. For hypothesis testing in Generalized Method of Moments or Generalized Empirical Likelihood context, we find that smoothing moment conditions by Bartlett kernel delivers smallest size distortions based on empirical Edgeworth expansions of the long-run variance estimator.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.800-808
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• 2008

A fingerprint verification system based on a set of invariant moment features and a nonlinear Back Propagation Neural Network(BPNN) verifier is proposed. An image-based method with invariant moment features for fingerprint verification is used to overcome the demerits of traditional minutiae-based methods and other image-based methods. The proposed system contains two stages: an off-line stage for template processing and an on-line stage for testing with input fingerprints. The system preprocesses fingerprints and reliably detects a unique reference point to determine a Region-of-Interest(ROI). A total of four sets of seven invariant moment features are extracted from four partitioned sub-images of an ROI. Matching between the feature vectors of a test fingerprint and those of a template fingerprint in the database is evaluated by a nonlinear BPNN and its performance is compared with other methods in terms of absolute distance as a similarity measure. The experimental results show that the proposed method with BPNN matching has a higher matching accuracy, while the method with absolute distance has a faster matching speed. Comparison results with other famous methods also show that the proposed method outperforms them in verification accuracy.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.97-108
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• 2020

This paper compares several methods for estimating parameters of normal inverse Gaussian distribution. Ordinary maximum likelihood estimation and the method of moment estimation often do not work properly due to restrictions on parameters. We examine the performance of adjusted estimation methods along with the ordinary maximum likelihood estimation and the method of moment estimation by simulation and real data application. We also see the effect of the initial value in estimation methods. The simulation results show that the ordinary maximum likelihood estimator is significantly affected by the initial value; in addition, the adjusted estimators have smaller root mean square error than ordinary estimators as well as less impact on the initial value. With real datasets, we obtain similar results to what we see in simulation studies. Based on the results of simulation and real data application, we suggest using adjusted maximum likelihood estimates with adjusted method of moment estimates as initial values to estimate the parameters of normal inverse Gaussian distribution.

• Communications for Statistical Applications and Methods
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• 제27권3호
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• pp.377-383
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• 2020

The likelihood-based inference in a nonlinear generalized mixed model often requires computing moments of truncated multivariate normal random variables. Many methods have been proposed for the computation using a recurrence relation or the moment generating function; however, these methods rely on high dimensional numerical integrations. The numerical method is known to be inefficient for high dimensional integral in accuracy. Besides the accuracy, the methods demand too much computing time to use them in practical analyses. In this note, a moment calculation method is proposed under an assumption of a certain covariance structure that occurred mostly in generalized mixed models. The method needs only low dimensional numerical integrations.

• Communications for Statistical Applications and Methods
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• 제23권6호
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• pp.479-496
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• 2016

In this survey, we present a modified inverse moment estimation of parameters and its applications. We use a specific model to demonstrate its principle and how to apply this method in practice. The estimation of unknown parameters is considered. A necessary and sufficient condition for the existence and uniqueness of maximum-likelihood estimates of the parameters is obtained for the classical maximum likelihood estimation. Inverse moment and modified inverse moment estimators are proposed and their properties are studied. Monte Carlo simulations are conducted to compare the performances of these estimators. As far as the biases and mean squared errors are concerned, modified inverse moment estimator works the best in all cases considered for estimating the unknown parameters. Its performance is followed by inverse moment estimator and maximum likelihood estimator, especially for small sample sizes.

• 한국전산유체공학회지
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• 제17권2호
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• pp.28-34
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• 2012

In this study, the reliability-based design optimization of the airfoil was performed. PARSEC function was used to consider the uncertainty of the aerodynamic shape for the reliability-based shape optimization of airfoils. Among various reliability analysis methods, the moment method was used to compute the probability of failure of the aerodynamic performance. The accuracy of the reliability analysis was compared with other methods and it was found that the moment method predicts the probability of failure accurately. Deterministic and reliability-based optimizations were performed for the shape of the airfoil and it was demonstrated that reliability-based optimum assures the aerodynamic performances under uncertainties of the shape of the airfoil.