• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.277-286
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• 2010

In this paper amplitude and phase distortion of the received signal through a fading channel results in a severe performance degradation of the communication system, Therefore we consider the variance of the maximum a posteriori phase estimate of sinusoidal signal by the Cramer-Rao bound in wireless fading channel. To find the Cramer-Rao lower bound for the variance of the phase, We use the derived probability density function(pdf) of the phase in Nakagami fading channel. We analyze the error performance of modulation signals using order statistics on generalized combining reception and find adequate diversity branch number.

• The Journal of Asian Finance, Economics and Business
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• v.1 no.3
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• pp.5-16
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• 2014

This study aims to examine the dynamics of price changes and trading volume of Kuala Lumpur Options and Financial Futures Exchange (KLOFFE) from 2000 to 2008. With augmented analysis, our results support two hypotheses. First, under information spillover, our findings support noise traders' hypothesis as the time span for variance of past trading volume to cause variance of current return is found to be asymmetric under bull and bear markets. Second, looking at the dynamic relation between volume and volatility of price changes, our findings support Liquidity-Driven Trade hypothesis as past trading volume and subsequent volatility of return exhibit positive correlation. In terms of investors' behavior in response to the news, we find that investors are more risk taking in bull market and more risk reverse in bear market. Our study suggests that investors should adjust their strategy in the futures market in a dynamic manner as the time span of new information arrival is not consistent. Also, uninformed investors with information asymmetry should expect noninformational trading from informed investors to establish their desired positions for better liquid position.

• Clinics in Shoulder and Elbow
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• v.25 no.3
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• pp.173-181
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• 2022

Background: Healing of the tendon itself is not always related to successful clinical outcomes after rotator cuff repair. It was hypothesized that certain radiologic factors affecting clinical outcomes could exist in case of the retear after arthroscopic rotator cuff repair (ARCR) and the radiologic factors could help predict clinical process. The purpose of this study was to identify the radiologic factors associated with clinical outcomes of the retear after ARCR. Methods: Between January 2012 and December 2019, among patients with sufficient footprint coverage for ARCR, 96 patients with Sugaya classification 4 or higher retear on follow-up magnetic resonance imaging were included. The association between clinical outcomes such as American Shoulder and Elbow Surgeons (ASES) score, Constant score and range of motion and radiologic variables such as initial tear dimension, retear dimension, variance of tear dimension, critical shoulder angle, acromial index, and acromiohumeral distance was analyzed. Results: Preoperatively, the ASES and Constant scores were 59.81±17.02 and 64.30±15.27, respectively. And at the last follow-up, they improved to 81.56±16.29 and 78.62±14.16, respectively (p<0.01 and p<0.01). In multiple linear regression analysis, the variance of the mediolateral dimension of tear had statistically significant association with the ASES and Constant scores (p<0.01 and p=0.01). Conclusions: In patients with the retear after ARCR, the variance in the mediolateral dimension of tear had significantly negative association with the clinical outcomes. This could be considered to be reference as relative criteria and needed more sample and mechanical study.

• Interdisciplinary Bio Central
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• v.2 no.2
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• pp.4.1-4.6
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• 2010

The most common type of microarray experiment has a simple design using microarray data obtained from two different groups or conditions. A typical method to identify differentially expressed genes (DEGs) between two conditions is the conventional Student's t-test. The t-test is based on the simple estimation of the population variance for a gene using the sample variance of its expression levels. Although empirical Bayes approach improves on the t-statistic by not giving a high rank to genes only because they have a small sample variance, the basic assumption for this is same as the ordinary t-test which is the equality of variances across experimental groups. The t-test and empirical Bayes approach suffer from low statistical power because of the assumption of normal and unimodal distributions for the microarray data analysis. We propose a method to address these problems that is robust to outliers or skewed data, while maintaining the advantages of the classical t-test or modified t-statistics. The resulting data transformation to fit the normality assumption increases the statistical power for identifying DEGs using these statistics.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2009.11a
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• pp.517-521
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• 2009

A unsteady internal ballistic analysis model was proposed to take account for the variance of local variance of pressure and velocity along the grain surface of a hybrid rocket combustor. The model of concern in the study was fairly comparable with the test result. The local variation of the oxidizer mass flow rate along grain surface results in chamber pressure, regression rate, and gas velocity change along its flow direction.

• Journal of The Korean Association For Science Education
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• v.16 no.3
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• pp.278-285
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• 1996

High school students' achievements in algorithmic problems, and figure-formatted and textual-formatted conceptual problems concerning stoichiometry, gaseous state, and solution, were measured by the Chemistry Problem Solving Ability Test. The relationships among the achievement scores in the three types of problems and cognitive variables such as logical thinking ability, mental capacity, and field dependence/field independence were examined. The portion of variance of explanation for each achievement score was also studied by a multiple regression analysis. The results showed that logical thinking ability was significantly correlated with the achievement score in the algorithmic problems, and accounted for the significant portion of the variance of the score. Mental capacity accounted for the significant portion of the variance of the score in the figure-formatted conceptual problems. Although field dependence/field independence was significantly correlated with all the achievement scores, it did not significantly account for any scores in multiple regression analyses. However, the magnitudes of correlation coefficients among the achievement scores were higher than those between the achievement scores and cognitive variables. The best predictor for each score was also found to be one of the other achievement scores. Educational implications are discussed.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.703-708
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• 2022

K-means clustering is a representative clustering technique. However, there is a limitation in not being able to integrate the performance evaluation scale and the method of determining the minimum number of clusters. In this paper, a method for numerically determining the minimum number of clusters is introduced. The explained variance is presented as an integrated measure. We propose that the k-means clustering method should be performed in the subspace of the PCA in order to simultaneously satisfy the minimum number of clusters and the threshold of the explained variance. It aims to present an explanation in principle why principal component analysis and k-means clustering are sequentially performed in pattern recognition and machine learning.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.287-295
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• 2020

Group method of data handling (GMDH) is considered one of the earliest deep learning methods. Deep learning gained additional interest in today's applications due to its capability to handle complex and high dimensional problems. In this study, multi-layer GMDH networks are used to perform uncertainty quantification (UQ) and sensitivity analysis (SA) of nuclear reactor simulations. GMDH is utilized as a surrogate/metamodel to replace high fidelity computer models with cheap-to-evaluate surrogate models, which facilitate UQ and SA tasks (e.g. variance decomposition, uncertainty propagation, etc.). GMDH performance is validated through two UQ applications in reactor simulations: (1) low dimensional input space (two-phase flow in a reactor channel), and (2) high dimensional space (8-group homogenized cross-sections). In both applications, GMDH networks show very good performance with small mean absolute and squared errors as well as high accuracy in capturing the target variance. GMDH is utilized afterward to perform UQ tasks such as variance decomposition through Sobol indices, and GMDH-based uncertainty propagation with large number of samples. GMDH performance is also compared to other surrogates including Gaussian processes and polynomial chaos expansions. The comparison shows that GMDH has competitive performance with the other methods for the low dimensional problem, and reliable performance for the high dimensional problem.

• Journal of Fashion Business
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• v.10 no.2
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• pp.181-193
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• 2006

The purpose of this study was to examine which factors among addiction buying behavior had been affected by body image. 235 female college students were surveyed for this study. For data analysis, descriptive statistics, $x^2$-test, multiple regression were used. As the results, generally there were significantly correlated among body image, diet addiction, binge eating, cosmetic surgery addiction, compulsive behavior and shoplift tendencies. Multiple regression results revealed that diet addiction, cosmetic surgery addiction, binge eating accounted for 34.8% of the explained variance in weight obsession. Also, regression results indicated that cosmetic surgery addiction, self-esteem, and diet addiction, and cosmetic surgery obession accounted for 20.4% of the explained variance in appearance orientation. Finally, regression results pointed out that self-esteem and diet obession accounted 22.3% of the explained variance in appearance evaluation. Based on these results, fashion marketing strategies would be suggested.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.437-449
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• 2014

In this study, we analyzed an effect of area-environmental factor on breast cancer screening rates using multi-level analysis. It was intended for the KNHANES-IV. Total subjects were 14338. Among them, 4143 subjects met the inclusion criteria. When we applied only empty Model, a variance of breast cancer screening rates was 0.061 in each region. When we applied Model with individual level variables, the variance was 0.034. However, when we applied both Model with individual level variables and Model with area level variables, the variance was 0.023. We drew applied only individual level variables parallel applied 3 regional variances which could explain variance of inspection of breast cancer up to 18.04% compared with applied only individual level variables. Area level variables could reduce a variance of region. This means besides individual level variables. The group can share a same thing and can effect to breast cancer screening rates. We need to discover factors which area level variables and suggest that make a standard for inspection of breast cancer.