• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 2000.04a
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• pp.281-286
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• 2000

• The monthly packaging world
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• s.83
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• pp.136-151
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• 2000

• Proceedings of the Zoological Society Korea Conference
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• 2000.10a
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• pp.126.2-127
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• 2000

No Abstract, See Full Text

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2000.04a
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• pp.113-119
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• 2000

• Proceedings of the PSK Conference
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• 2000.04a
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• pp.101.1-101.1
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• 2000

• Proceedings of the Korean Magnestics Society Conference
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• 2000.09a
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• pp.480-481
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• 2000

• Journal of Acupuncture Research
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• v.21 no.3
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• pp.215-229
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• 2004

Objective : We had a clinical report in headache but didn't in migraine. We have planned this study in order to get the basic data of migraine in oriental medicine. Methods : The patient of 36 in migraine checked sex, age, onset, family history, severity of pain, influences of life, induced cause, clinical pain characteristics, associated symptom, treatment style, and prescription, frequency, using period of analgesics by a questionnaire and differentiated syndromes in migraine and evaluated autonomic bioelectric response recorder(ABR-2000). Results : There are 23.4% in prevalence rate of migraine. The ratio of sex is M:F=1:17. The age of an attack is the highest in thirties. The patient are the most in forties. The mean duration of illness is $12.0{\pm}9.9$ years. 83.4% had a family history. 61.1% had a moderate grade in severity of pain. 77.8% selected fatigue in induced cause of migraine. 69.4% had tingling sense, nausea and vomiting in the associated symptoms. 91.7% used analgesics for treatment and 51.5% of them used analgesics voluntarily. 61.9% of them take analgesics less than once in a week. 33.6% had the phlegm syncope headache in differentiation of syndrome. In ABR-2000 results, item of graph showed low tendency mostly. Conclusions : We expected that this report of clinical progress, differentiation of syndromes and ABR-2000 results in migraine would be used basic data by oriental medicine to treat migraine.

• Journal of the Ergonomics Society of Korea
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• v.19 no.1
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• pp.11-22
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• 2000

In this research report, we are presenting several optimization models for cognitive systems by using stimulus-response matrix (S-R Matrix). Stimulus-response matrices are widely used for tabulating results from various experiments and cognition systems design in which the recognition and confusability of stimuli. This paper is relevant to analyze the optimization/mathematical programming models. The weakness and restrictions of the existing models are resolved by generalization considering average confusion of each subset of stimuli. Also, clustering strategies are used in the extended model to obtain centers of cluster in terms of minimal confusion as well as the character of each cluster.

• Journal of Power System Engineering
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• v.4 no.2
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• pp.71-76
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• 2000

It is well known that finite element analysis often has the inaccuracy when they are in conflict with test results. Model updating is concerned with the correction of analytical model by processing records of response from test results. This paper introduce a model updating technique using the frequency response function data. The measurement data is able to be used directly in the FRF sensitivity method because it is not necessary to identify. When a damping model is updated, it is necessary for the sensitivity matrix to be divided Into the complex part and real part. As an applying model, a cantilever and a rotor system are used. Specially the machined clearance($C_p$) of the journal bearing is updated.

• Journal of the Korean Statistical Society
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• v.29 no.4
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• pp.407-422
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• 2000

This article is concerned with the selecting predictor variables to be included in building a class of binary response t-link regression models where both probit and logistic regression models can e approximately taken as members of the class. It is based on a modification of the stochastic search variable selection method(SSVS), intended to propose and develop a Bayesian procedure that used probabilistic considerations for selecting promising subsets of predictor variables. The procedure reformulates the binary response t-link regression setup in a hierarchical truncated normal mixture model by introducing a set of hyperparameters that will be used to identify subset choices. In this setup, the most promising subset of predictors can be identified as that with highest posterior probability in the marginal posterior distribution of the hyperparameters. To highlight the merit of the procedure, an illustrative numerical example is given.