• Journal of the Korean Statistical Society
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• v.28 no.4
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• pp.415-433
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• 1999

This paper considers the design of step-stress accelerated life tests for the Weibull distribution with a nonconstant shape parameter under Type I censoring. It is assumed that scale and shape parameters are log-linear functions of (possibly transformed) stress and that a cumulative exposure model holds for the effect of changing stress. The asymptotic variance of the maximum likelihood estimator of a stated quantile at design stress is used as an optimality criterion. The optimum three step-stress plans are presented for selected values of design parameters and the effects of errors in pre- estimates of the design parameters are investigated.

• Magazine of the Korean Society of Agricultural Engineers
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• v.14 no.2
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• pp.2649-2653
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• 1972

Many empirical research surveys have supported that Organizational Citizenship Behavior (OCB) is influnced by or closely related with leadership styles. The first purpose of this study is to review the relationship between 2 leadership styles(employee-centered style, job-centered style) and 2 OCB factors(altruism, conscientiousness) as a criterion variable, and the second and primary purpose is to test the moderating effects of structural factors(formalization, centralization) and personal factors(growth needs, sex, age, tenure, rank, occupation, school career) between 2 leadership styles and 2 OCB factors. For the analytical purpose of this article, Fisher's Z-transformation and SGC(split groups correlations) methods were introduced. Generally 2 leadership styles are found to influence on altruism and conscientiousness respectively. Out of 36 cases, only 2 cases were significant in moderating effects. Based on empirical results, there is no moderating effects in conscientiousness. But altruism is found to more closely related with employee-centered leadership in low centralized group than on high centralized group, and more closely related with job-centered leadership in low growth-needs group than in high growth-needs group.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.671-674
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• 1997

The objective of this paper is to present a new feature-vector extraction method for the automatic detection and classification of power quality(PQ) disturbances, where FIT, DWT(Discrete Wavelet Transform), and Fisher's criterion are utilized to extract an appropriate feature vector. In particular, the proposed classifier consists of three parts: i.e., (i) automatic detection of PQ disturbances, where the wavelet transform and signal power estimation method are utilized to detect each disturbance, (ii) feature vector extraction from the detected disturbance, and (iii) automatic classification, where Multi-Layer Perceptron(MLP) is used to classify each disturbance from the corresponding extracted feature vector. To demonstrate the performance and applicability of the proposed classification algorithm, some test results obtained by analyzing 10-class power quality disturbances are also provided.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.47
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• pp.11-23
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• 1998

Many empirical research surveys have supported that Organizational Citizenship Behavior (OCB) is influnced by or closely related with leadership styles. The first purpose of this study is to review the relationship between 2 leadership styles(employee-centered style, job-centered style) and 2 OCB factors(altruism, conscientiousness) as a criterion variable, and the second and primary purpose is to test the moderating effects of structural factors(formalization, centralization) and personal factors(growth needs, sex, age, tenure, rank, occupation, school career) between 2 leadership styles and 2 OCB factors. For the analytical purpose of this article, Fisher's Z-transformation and SGC(split groups correlations) methods were introduced. Generally 2 leadership styles are found to influence on altruism and conscientiousness respectively. Out of 36 cases, only 2 cases were significant in moderating effects. Based on empirical results, there is no moderating effects in conscientiousness. But altruism is found to more closely related with employee-centered leadership in low centralized group than on high centralized group, and more closely related with job-centered leadership in low growth-needs group than in high growth-needs group.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1030-1032
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• 1998

In this paper, an efficient feature vector extraction method and MLP neural network are utilized to automatically detect and classify power quality disturbances, where the proposed classification procedure consists of the following three parts: i.e., (i) PQ disturbance detection using discrete wavelet transform. (ii) feature vector extraction from the detected disturbance. using several methods, such as FFT, DWT, Fisher's criterion. etc.. and (iii) classification of the corresponding type of each PQ disturbance by recognizing the pattern of the extracted feature vector. To demonstrate the performance and, applicability of the proposed classification algorithm. some test results obtained by analyzing 10-class PQ disturbances are also provided.

• Journal of KIISE:Software and Applications
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• v.37 no.1
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• pp.1-8
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• 2010

Recently lots of attention has been paid to gene set analysis for identifying differentially expressed gene-sets between two sample groups. Unlike earlier approaches, the gene set analysis enables us to find significant gene-sets along with their functional characteristics. For this reason, various novel approaches have been suggested lately for gene set analysis. As one of such, PAGE is a parametric approach that employs average difference (AD) as an expression metric to quantify expression differences between two sample groups and assumes that the distribution of gene scores is normal. This approach is preferred to non-parametric approach because of more effective performance. However, the metric AD does not reflect either gene expression intensities or variances over samples in calculating gene scores. Thus, in this paper, we investigate the usefulness of several other expression metrics for parametric gene-set analysis, which consider actual expression intensities of genes or their expression variances over samples. For this purpose, we examined three expression metrics, WAD (weighted average difference), FC (Fisher's criterion), and Abs_SNR (Absolute value of signal-to-noise ratio) for parametric gene set analysis and evaluated their experimental results.

• Smart Structures and Systems
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• v.13 no.3
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• pp.389-406
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• 2014

Optimal sensor placement techniques play a significant role in enhancing the quality of modal data during the vibration based health monitoring of civil structures, where many degrees of freedom are available despite a limited number of sensors. The literature has shown a shift in the trends for solving such problems, from expansion or elimination approach to the employment of heuristic algorithms. Although these heuristic algorithms are capable of providing a global optimal solution, their greatest drawback is the requirement of high computational effort. Because a highly efficient optimisation method is crucial for better accuracy and wider use, this paper presents an improved simulated annealing (SA) algorithm to solve the sensor placement problem. The algorithm is developed based on the sensor locations' coordinate system to allow for the searching in additional dimensions and to increase SA's random search performance while minimising the computation efforts. The proposed method is tested on a numerical slab model that consists of two hundred sensor location candidates using three types of objective functions; the determinant of the Fisher information matrix (FIM), modal assurance criterion (MAC), and mean square error (MSE) of mode shapes. Detailed study on the effects of the sensor numbers and cooling factors on the performance of the algorithm are also investigated. The results indicate that the proposed method outperforms conventional SA and Genetic Algorithm (GA) in the search for optimal sensor placement.

• Journal of Trauma and Injury
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• v.24 no.2
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• pp.89-94
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• 2011

Purpose: A few studies have assessed the factors affecting the prognoses for major trauma patients and those improving the circumstances when dealing with the trauma system. In that light, we analyzed factors, such as pre-hospital factors, the time to admission, the length of stay in the emergency department (ED) and emergency operation, influencing the outcomes for trauma patients. Methods: The patients who visited our emergency department from April 1, 2009, to February 29, 2011, due to major trauma were enrolled in the study. The inclusion criterion was a revised trauma score (RTS) < 7 or injury severity score (ISS) ${\geq}$ 16. We used reviews of medical records, to analyze each step of emergency medical care with respect to patients' sex, age, visit time and visit date. Continuous variables were described as a median with an interquartile range, and we compared the variables between the survival and the mortality groups by using the Mann-Whitney U test. Fisher's exact test was used for nominal variables. Using the variables that showed statistical significance in univariate comparisons, we performed a logistic regression analysis, and we tested the model's adequacy by the using the Hosmer-Lemeshow method. Results: A total of 261 patients with major trauma satisfied either the RTS score criterion or the ISS score criterion. Excluding 12 patients with missing data, 249 patients were included in this study. The overall mortality rate was 16.9%. Time to ED arrival, time to admission, time of ED stay, RTS, ISS, and visit date being a holiday showed statistically significant differences between the survival and the mortality groups in the univariate analysis. RTS, ISS, length of ED stay, and visit date being a holiday showed statistical significance in the multivariate analysis. Conclusion: The mortality rate did not show a significant relationship with the time to ED arrival, use of 119, on time to admission. Rather, it elicited a quite significant correlation with the trauma scoring system (RTS and ISS), the time of ED stay, and the visit date being a holiday.

• Korean Journal of Biological Psychiatry
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• v.11 no.2
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• pp.165-172
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• 2004

Objective:Although polymorphism of dopamine transporter gene(DAT1) has been considered to be implicated in the pathogenesis of social phobia, previous investigations have been inconsistent and controversial. The authors investigated the relationship between DAT1 polymorphism and social phobia in Koreans. Methods:DAT1 and alleles of fifty subjects who met DSM-IV criterion of social phobia, and those of age- & sex- matched fifty normal controls in Korea were compared. Additionally, patients were grouped into generalized(33) and nongeneralized(17) types and DAT1 polymorphism was compared with that of age- & sex- matched controls. DAT1 with variable number of tandem repeats(VNTR) were determined by using polymerase chain reaction. To compare the distribution of the DAT1 polymorphism between different groups, Fisher's exact test was used. Results:There were no significant differences in either genotypic(p=0.451) or allelic(p=0.452) distributions between the social phobia patients and the controls. There also were no differences in genotypic distribution between subtypes of social phobia patients and the controls. Conclusion:We couldn't find any association between DAT1 polymorphism and social phobia. Further studies including larger number of samples and diverse clinical variables should be conducted to elucidate the present findings.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.4 s.304
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• pp.33-42
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• 2005

This paper proposes a classification method for gene expression data, using membership function and neural network. The gene expression is a process to produce mRNA and protains which generate a living body, and the gene expression data is important to find out the functions and correlations of genes. Such gene expression data can be obtained from DNA 칩 massively and quickly. However, thousands of gene expression data may not be useful until it is well organized. Therefore a classification method is necessary to find the characteristics of gene data acquired from the gene expression. In the proposed method, a set of gene data is extracted according to the fisher's criterion, because we assume that selected gene data is the well-classified data sample. However, the selected gene data does not guarantee well-classified data sample and we calculate feature values using membership function to reduce the influence of outliers in gene data. Feature vectors estimated from the selected feature values are used to train back propagation neural network. The experimental results show that the clustering performance of the proposed method has been improved compared to other existing methods in various gene expression data.