• Anxiety and mood
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• v.7 no.1
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• pp.16-21
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• 2011

Objective : Depressive symptoms often coexist with other anxiety disorder symptoms. Furthermore, an anxiety disorder that is comorbid with a depressive disorder results in more severe symptoms and a poorer outcome prognosis. To understand the construct of depressive symptoms in anxiety disorder, this study investigated the factor structure of the Beck Depression Inventory among outpatients with anxiety disorders. Methods : All data were from psychiatric department outpatients at a university-affiliated hospital. We conducted a principal component analysis using data from 194 outpatients with DSM-IV anxiety disorders and calculated goodness-of-fit-indices. Results : Exploratory factor analysis revealed a four factor structure--Cognitive-affective symptoms (Factor 1), Somatic symptoms (Factor 2), Self-reproach (Factor 3), and Hypochondriasis/indecisiveness (Factor 4)--and a 57% total variance. This four-factor model demonstrated an acceptable level of model fit, and it fit better than did a three-factor solution from the literature on depressive disorder. Conclusion : This study's results suggest a difference in the construct of self-reported depressive symptoms in anxiety disorders. These findings also support a dimensional approach to studying anxiety and depression. Further studies may benefit from including comorbid depressive disorder and its influence on anxiety disorders.

• Bulletin of the Korean Chemical Society
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• v.28 no.9
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• pp.1613-1614
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• 2007

• Bulletin of the Korean Chemical Society
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• v.29 no.9
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• pp.1860-1862
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• 2008

• Journal of the Korean Statistical Society
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• v.31 no.2
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• pp.163-175
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• 2002

An extended version of the minimax eccentricity factor estimation for multiple set case is proposed. In addition, two more simple methods for multiple set factor analysis exploiting the concept of generalized canonical correlation analysis is suggested. Finally, a certain connection between the generalized canonical correlation analysis and the multiple set factor analysis is derived which helps us clarify the relationship.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1123-1134
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• 2007

This article addresses the problem of testing whether the shape parameters in k independent Weibull populations are equal. We propose a Bayesian model selection procedure for equality of the shape parameters. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the objective Bayesian model selection procedure based on the fractional Bayes factor and the intrinsic Bayes factor under the reference prior. Simulation study and a real example are provided.

• Archives of Pharmacal Research
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• v.21 no.5
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• pp.549-554
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• 1998

Tissue factor (TF), a principal initiator of the veertebrate coagulation cascade, is expressed in organ tissues, cells and blood. TF is konwn to be induced in endothelial cells, monocytes and macrophages by inflammatory stimuli and in many pathologic conditions. By using the modified method for in vido TF activity assay, we found that turpentine oil injection as an inflamatory stimulus also induced the TF activity in lung and brain tissues of rats. And the age-related increase in Tf activity was observed in healthy rat brain tissue.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.64-69
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• 2013

For power system protection, the distance relay settings are important. Apparent factor is a necessary parameter in distance relay settings. Apparent factors have to be calculated when setting the distance relays and doing the resetting in case of configuration change in power system. The problem is that the current method to calculate apparent factor requires tools and plenty of time to do fault analysis and this method is complex especially in case of configuration change. Therefore this paper proposes a fast algorithm to calculate apparent factor without the fault analysis. Test results prove that this algorithm is simple and accurate by simulation.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.1125-1129
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• 1993

A piezoelectric ring type plate, which vibrates in flexural vibration mode, is used for the stator of ultrasonic motor. To design the stator adequately, the force factor of the stator should be estimated in advance. The theoretically calculated force factors for the flexural vibration mode are compared with the measured ones to obtain good agreement. In order to study how to control the force factor, the relation between the shape of the stator and force factor is also considered.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.933-942
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• 2013

Common factor analysis and principal component analysis represent two technically distinctive approaches to exploratory factor analysis. Much of the psychometric literature recommends the use of common factor analysis instead of principal component analysis. Nonetheless, factor analysts use principal component analysis more frequently because they believe that principal component analysis could yield (relatively) less accurate estimates of factor loadings compared to common factor analysis but most often produce similar pattern of factor loadings, leading to essentially the same factor interpretations. A simulation study is conducted to evaluate the relative performance of these two approaches in terms of factor pattern recovery under different experimental conditions of sample size, overdetermination, and communality.The results show that principal component analysis performs better in factor recovery with small sample sizes (below 200). It was further shown that this tendency is more prominent when there are a small number of variables per factor. The present results are of practical use for factor analysts in the field of marketing and the social sciences.

• Asian Journal of Atmospheric Environment
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• v.5 no.3
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• pp.189-195
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• 2011

Korea-specific GHG emissions should be estimated correctly in order to ensure effective measurement of climate change variables. The use of country-specific data that reflects fuel and technology characteristics is needed for accurate GHG emissions estimation. Oxidation factors are used to convert existing data into equivalent GHG emissions, and changes in these oxidation factors are directly related to changes in emissions. As such, the oxidation factor is one of the most important variables in using country-specific data to determine GHG emissions. In this study, the oxidation factor of bituminous coal in large scale boilers was estimated using 4,527 data points sampled from eight large-scale boilers that had been using bituminous coal for two years. The average oxidation factor was determined to be 0.997, which is lower than the oxidation factor of 1 that is recommended by the IPCC G/L for large scale boilers when estimating national GHG emissions. However, an oxidation factor less than 1 is assumed for fluidized bed boilers, internal combustion engines, and other small-scale boilers. Accordingly, studies on oxidation factor estimation should be continued to allow for accurate estimation of GHG emissions.