• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.182-184
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• 2005

In this study, we propose a chi-squared test of spherical symmetry. The advantage of this test is that the test statistic and its asymptotic p-value are easy to compute. A simulation study is conducted to study the accuracy, in finite samples, of the limiting distribution of the test statistic under spherical symmetry. The power of our test is compared with those of other tests for spherical symmetry in various alternative distributions via simulation.

• PNF and Movement
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• v.16 no.3
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• pp.405-414
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• 2018

Purpose: The purpose of this study was to examine test-retest reliability and criterion-related validity of a trunk stability robot when measuring the weight-bearing symmetry static sitting and standing in stroke patients. Methods: For 27 stroke patients, weight-bearing symmetry was assessed twice, 7 days apart. The intraclass correlation coefficient (ICC2,1) and minimal detectable change (MDC) were used to examine the level of agreement between test and retest. The criterion-related validity of weight -bearing symmetry was demonstrated by Spearman correlation of modified Barthel index (MBI), the sit to stand test (STS), the timed up & go Test (TUG), and the function in sitting test (FIST). Results: the test-retest agreements were excellent for the weight-bearing symmetry of static sitting (ICC2,1: 0.90) and standing (ICC2,1: 0.89). It all showed that the acceptable MDC for the weight-bearing symmetry of static sitting and standing was 0.11 and 0.16, respectively (highest possible score<20 %), indicating that the measures had a small and acceptable degree of measurement error. The weight-bearing symmetry of static sitting was significantly correlated with the TUG(r=-0.45) and FIST(r=0.46)(p<0.05); the weight-bearing symmetry of static standing was also significantly correlated with MBI (r=0.65), TUG (r=-0.67), FIST (r=0.61)(p<0.01), and STS (r=-0.47)(p<0.05). Conclusion: The weight-bearing symmetry of static sitting and standing assessed by the trunk stability robot showed highly sufficient test-retest agreement and mild-to-moderate validity. It could also be useful for clinicians and researchers to evaluate balance performance and monitor functional change in stroke patients.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1367-1370
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• 1997

This paper presents a vision algorithm for finding the centers of steam generator tubes using the generalized symmetry transform, which is used for ECT(Eddy Current Test) of steam generator tubes in nuclear power plants. The geometrical properties of the image representing steam generator tubes shows that they have amost circular or somewhat elliptic appearances and each tube has strong symmetry about its center. So we apply the generalized symmetry transform to finding centers of steam geneator tubes. But applying the generalized symmetry transform itself without any modification gives difficulties in obtaining the exact centers of steam generator tubes. But applying the generalized symmetry transform itself without any modification gives difficulties in obtaining the exact centers of tubes due to the shadow effect generated by the local light installed inside steam generator. Therefore we make the generalized symmetry transform modified, which uses a modified phase weight function in getting the symmetry magnitude in order to overcome the misleading effect by the local light. The experimental results indicate that the proposed vision algorithm efficiently recongnizes centers of steam generator tubes.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.99-113
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• 2005

In this article, we propose a chi-squared test of spherical symmetry. The advantage of this test is that the test statistic and its asymptotic p-value are easy to compute. The limiting distribution of the test statistic is derived under spherical symmetry and its accuracy, in finite samples, is studied via simulation. Also, a simulation study is conducted in which the power of our test is compared with those of other tests for spherical symmetry in various alternative distributions. Finally, an illustrative example of application to a real data is provided.

• Journal of the Korea Society of Computer and Information
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• v.21 no.4
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• pp.9-15
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• 2016

Symmetry is everywhere in the world around us from galaxy to microbes. From ancient times symmetry is considered to be a reflection of the harmony of universe. Symmetry is not only a significant clue for human cognitive process, but also useful information for computer vision such as image understanding system. Application areas include face detection and recognition, indexing of image database, image segmentation and detection, analysis of medical images, and so on. The technique used in this paper extracts edges, and the perpendicular bisector of any two edge points is considered to be a candidate axis of symmetry. The coefficients of candidate axis are accumulated in the coefficient space. Then the axis of symmetry is determined to be the line for which the coefficient histogram has maximum value. In this paper, an improved method is proposed that utilizes the directional information of edges, which is a byproduct of the edge detection process. Experiment on 20 test images shows that the proposed method performs 22.7 times faster than the original method. In another test on 5 images with 4% salt-and-pepper noise, the proposed method detects the symmetry successfully, while the original method fails. This result reveals that the proposed method enhances the speed and accuracy of detection process at the same time.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.63-68
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• 2003

One of the widely accepted assumptions in many statistical problem is that the underlying distribution is symmetric. Though a large number of nonparametric test are available in the literature for this problem, very few procedures focuses on the distributional structure when the symmetry assumption is rejected. Yanagimoto and Sibuya (1972) provided the various types of asymmetric distributional structure, positive biasedness, namely. In this paper we consider the test of symmetry against several new positive biasedness restrictions which are stronger than Yanagimoto and Sibuya's type II bias but weaker than type IV (III) bias.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1191-1200
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• 2006

A chi-squared test of multivariate normality is suggested which is mainly focused on detecting deviations from elliptical symmetry. This test uses Mahalanobis distances of observations to have some power for deviations from multivariate normality. We derive the limiting distribution of the test statistic by a conditional limit theorem. A simulation study is conducted to study the accuracy of the limiting distribution in finite samples. Finally, we compare the power of our method with those of other popular tests of multivariate normality under two non-normal distributions.

• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.203-212
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• 2006

A chi-squared test of multivariate normality is suggested which is mainly focused on detecting deviations from elliptical symmetry. This test uses Mahalanobis distances of observations to have some power for deviations from multivariate normality. We derive the limiting distribution of the test statistic by a conditional limit theorem. A simulation study is conducted to study the accuracy of the limiting distribution in finite samples. Finally, we compare the power of our method with those of other popular tests of multivariate normality under two non-normal distributions.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.221-231
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• 2006

A chi-squared test of multivariate normality is suggested which is oriented for detecting deviations from elliptical symmetry. We derive the limiting distribution of the test statistic via a central limit theorem on empirical processes. A simulation study is conducted to study the accuracy of the limiting distribution in finite samples. Finally, we compare the power of our method with those of other popular tests of multivariate normality under a non-normal distribution.

• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.459-468
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• 2002

A class of asymmetric beta-ARCH processes is proposed and connections to traditional ARCH models are explained. Geometric ergodicity of the model is discussed. Conditional least squares as well as maximum likelihood estimators of parameters and their limit results are also presented. A test for symmetry of the model is studied with limiting power of test statistic given.