• Journal of Labour Economics
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• v.24 no.3
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• pp.1-12
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• 2001

Seoul/Kyungki-born workers have higher wages than other regions-born workers. In order to determine whether this difference is due to taste or statistical discrimination, an econometric model is suggested and a test is done with it. According to the test, the hypothesis that the difference is wholly due to taste discrimination is rejected: a part of the difference is due to statistical discrimination. Since statistical discrimination in this paper comes out in the process of a worker's wage being determined according to his productivity, it is no problem for the government to intervene in.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.567-576
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• 2006

In this paper, we applied the multiblock dimension reduction methods to the classification of tumor based on microarray gene expressions data. This procedure involves clustering selected genes, multiblock dimension reduction and classification using linear discrimination analysis and quadratic discrimination analysis.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.12
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• pp.119-125
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• 1999

This paper gives an overview of the various approaches to designing statistical pattern recognition scheme based on Bayes discrimination rule and the artificial neural networks for rotating machine condition classification. Concerning to Bayes discrimination rule, this paper contains the linear discrimination rule applied to classification into several multivariate normal distributions with common covariance matrices, the quadratic discrimination rule under different covariance matrices. Also we discribes k-nearest neighbor method to directly estimate a posterior probability of each class. Five features are extracted in time domain vibration signals. Employing these five features, statistical pattern classifier and neural networks have been established to detect defects on rotating machine. Four different cases of rotation machine were observed. The effects of k number and neural networks structures on monitoring performance have also been investigated. For the comparison of diagnosis performance of these two method, their recognition success rates are calculated form the test data. The result of experiment which classifies the rotating machine conditions using each method presents that the neural networks shows the highest recognition rate.

• Journal of the Korean Statistical Society
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• v.25 no.2
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• pp.289-301
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• 1996

This paper suggests a new diagnostic measure for detecting influential observations in two group linear discriminant analysis(LDA). It is developed from an information theoretic point of view using the minimum discrimination information(MDI) methodology. MDI estimator of symmetric divergence by Kullback(l967) is taken as a measure of the power of discrimination in LDA. It is shown that the effect of an observation over the power of discrimination is fully explained by the diagnostic measure. Asymptotic distribution of the proposed measure is derived as a function of independent chi-squared and standard normal variables. By means of the distributions, a couple of methods are suggested for detecting the influential observations in LDA. Performance of the suggested methods are examined through a simulation study.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.98-105
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• 2000

In this study, we developed rotating machine vibration condition monitoring system based upon Windows NT and DSP Board. Developed system includes signal analysis module, trend monitoring and simple diagnosis using threshold value. Trend analysis and report generation are offered with database management tool which was developed in MS-ACCESS environment. Post-processor, based upon Matlab, is developed for vibration signal analysis and fault detection using statistical pattern recognition scheme based upon Bayes discrimination rule and neural networks. Concerning to Bayes discrimination rule, the developed system contains the linear discrimination rule with common covariance matrices and the quadratic discrimination rule under different covariance matrices. Also the system contains k-nearest neighbor method to directly estimate a posterior probability of each class. The result of case studies with the data acquired from Pyung-tak LNG pump and experimental setup show that the system developed in this research is very effective and useful.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.221-222
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• 2005

In this paper, application of NN (Neural Network) as a method of pattern discrimination of PD(partial discharge) which occurs at the stator coil of traction motor was studied. For PD data acquisition, three defective models are manufactured such as internal discharge model, slot discharge model and surface discharge model. PD data for recognition were acquired from PD detector and DAQ board which is able to analysis the PD signal and perform the pattern discrimination. Statistical distributions and parameters are calculated to discriminate PD sources. And also these statistical distribution parameters are applied to classify PD sources by BP and has good recognition rate on the discharge sources.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.69
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• pp.36-49
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• 2001

Group level discriminations are observed in employment relations and other transactions in the form of residential occupational and production segregation and differential treatments. Recent developments in the rational theories of discrimination both on the market level and the non-market level are reviewed in terms of their relative strengths, weaknesses and complementarities. Taste discrimination could remain much suppressed in the market but could effect much chain reaction through various ways of statistical discrimination, price discrimination, human capital investment and segregation. Taste discrimination could also take the more structured form of co-workers' requiring compensation for reduced productivity due to increasing interactions with members of different language and culture in a non-segregative system. If could also be viewed in the framework of brand learning models. Non-market models of discrimination are seen to be an essential part to explain extended modes of discrimination.

• Korean Journal of Social Welfare
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• v.48
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• pp.333-358
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• 2002

The purpose of this study is to analyze empirically the causes of high unemployment among the people with disabilities, focused on productivity and discrimination. In order to pursue such goal this study adopts human capital theory, screening theory, job contest theory, taste theory and statistical discrimination theory as theoretical background. The major findings are: (1) Among the human capital variables Education degree and job training are not statistically significant on employment. Only degree of activity limit has significant effect. (2) Among the discrimination related variables only discrimination experiences variable has negative effect on employment. (3) Between degree of activity limit and discrimination experiences, both have similar effect on employment. But the degree of activity limit can be thought as discrimination related element. Because' not giving resonable accommodation' is regarded discrimination in ADA or DDA. These mean that it is important for society to compel the employment of the disabled and to put focus on eliminating prejudice rather than accomplishing education and job training programs to improve the employment of the disabled. In order to accomplish this it is necessary to increase the levy for disabled persons' employment promotion of the disabled persons' employment promotion act and to establish the disability discrimination act. Also, integrated education starting from infancy is necessary. Education system should be changed, and Job training must focused on industry which demand more labor force.

• Korean Journal of Food Science and Technology
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• v.44 no.5
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• pp.503-525
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• 2012

Consumers are increasingly concerned about the origin of foods, so the geographical origin of foods has been a major topic of debate and extensive research. Various instrumental methods (e.g. high performance liquid chromatography (HPLC), gas chromatography (GC), capillary electrophoresis (CE), electronic nose, near-infrared spectroscopy (NIRS), nuclear magnetic resonance spectroscopy (NMR), DNA analysis, multi-isotope analysis) in conjunction with statistical analysis, were developed and applied in attempt to provide reliable answers to their geographical origin. This study reviews current developments in the application of various methods for a clear geographical origin of foods. The limitation of discrimination analysis for geographical origin was also discussed.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.247-263
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• 2001

This paper concerns a problem of classification based on training dta. A framework of information geometry is given to elucidate the characteristics of discriminant functions including logistic discrimination and AdaBoost. We discuss a class of loss functions from a unified viewpoint.