• Genomics & Informatics
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• 제17권4호
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• pp.47.1-47.12
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• 2019

The achievements of genome-wide association studies have suggested ways to predict diseases, such as type 2 diabetes (T2D), using single-nucleotide polymorphisms (SNPs). Most T2D risk prediction models have used SNPs in combination with demographic variables. However, it is difficult to evaluate the pure additive contribution of genetic variants to classically used demographic models. Since prediction models include some heritable traits, such as body mass index, the contribution of SNPs using unmatched case-control samples may be underestimated. In this article, we propose a method that uses propensity score matching to avoid underestimation by matching case and control samples, thereby determining the pure additive contribution of SNPs. To illustrate the proposed propensity score matching method, we used SNP data from the Korea Association Resources project and reported SNPs from the genome-wide association study catalog. We selected various SNP sets via stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and the elastic-net (EN) algorithm. Using these SNP sets, we made predictions using SLR, LASSO, and EN as logistic regression modeling techniques. The accuracy of the predictions was compared in terms of area under the receiver operating characteristic curve (AUC). The contribution of SNPs to T2D was evaluated by the difference in the AUC between models using only demographic variables and models that included the SNPs. The largest difference among our models showed that the AUC of the model using genetic variants with demographic variables could be 0.107 higher than that of the corresponding model using only demographic variables.

• 전자공학회논문지C
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• 제36C권4호
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• pp.54-64
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• 1999

본 논문에서는 실제 응용분야에서 사용될 수 있는 효율적인 필기 영어 단어 인식 방법을 제안한다. 필기 단어인식과 관련된 대부분의 응용분야에서 제공되는 사전의 활용을 극대화하기 위해 사전단어들을 인식의 초기 단계에서부터 사용한다. 초과 분할된 단어의 세크먼트들과 사전단어들 사이의 정합을 위해 동적 프로그래밍을 사용하며, 정합구간을 가변적으로 조정할 수 있도록 학습단계에서 추출한 문자 분할과 관련된 통계를 활용한다. 또한, 사전단어의 각 문자와 세그먼트들 사이의 정합 결과를 저장하여 반복되는 계산을 피한다. 제안하는 방법의 효용성을 입증하기 위해 다양한 서체를 갖는 실험용 필기 단어영상을 사용하여 실험을 수행한 결과, 사전에 기반한 단어 인식 과정을 최대로 활용하기 위한 가변정합구간 개념 및 문자단위 정합결과 저장 방법이 동적 프로그래밍과 함께 인식 속도 및 정확도 향상에 모두 크게 기여함을 확인하였다.

• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 1995년도 Language, Information and Computation = Proceedings of the 10th Pacific Asia Conference, Hong Kong
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• pp.121-126
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• 1995

A new method for Chinese word segmentation named Conditional F'||'&'||'BMM (Forward and Backward Maximal Matching) which incorporates both bigram statistics (ie., mutual infonllation and difference of t-test between Chinese characters) and linguistic rules for ambiguity resolution is proposed in this paper The key characteristics of this model are the use of: (i) statistics which can be automatically derived from any raw corpus, (ii) a rule base for disambiguation with consistency and controlled size to be built up in a systematic way.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2004년도 춘계학술대회
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• pp.15-23
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• 2004

When X and Y have independent two parameter exponential distributions, we develop a Bayesian testing procedures for the equality of two location parameters. Under the noninformative prior, we propose a Bayesian test procedures for the equality of two location parameters using fractional Bayes factor and intrinsic Bayes factor. Simulation study and some real data examples are provided.

• Journal of the Korean Statistical Society
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• 제31권1호
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• pp.17-31
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• 2002

This paper considers noninformative priors for the power law process under failure truncation. Jeffreys'priors as well as reference priors are found when one or both parameters are of interest. These priors are compared in the light of how accurately the coverage probabilities of Bayesian credible intervals match the corresponding frequentist coverage probabilities. It is found that the reference priors have a definite edge over Jeffreys'prior in this respect.

• Journal of the Korean Data and Information Science Society
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• 제24권3호
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• pp.643-650
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• 2013

We develop noninformative priors for a ratio of parameters of two Maxwell distributions which is used to check the equality of two Maxwell distributions. Specially, we focus on developing probability matching priors and Je reys' prior for objectiv Bayesian inferences. The probability matching priors, under which the probability of the Bayesian credible interval matches the frequentist probability asymptotically, are developed. The posterior propriety under the developed priors will be shown. Some simulations are performed for identifying the usefulness of proposed priors in objective Bayesian inference.

• Journal of the Korean Data and Information Science Society
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• 제27권4호
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• pp.1091-1100
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• 2016

This paper considers the noninformative priors for the linear function of parameters in the lognormal distribution. The lognormal distribution is applied in the various areas, such as occupational health research, environmental science, monetary units, etc. The linear function of parameters in the lognormal distribution includes the expectation, median and mode of the lognormal distribution. Thus we derive the probability matching priors and the reference priors for the linear function of parameters. Then we reveal that the derived reference priors do not satisfy a first order matching criterion. Under the general priors including the derived noninformative priors, we check the proper condition of the posterior distribution. Some numerical study under the developed priors is performed and real examples are illustrated.

• 한국조사연구학회:학술대회논문집
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• 한국조사연구학회 2006년도 추계학술대회 발표논문집
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• pp.67-83
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• 2006

In successive sampling on two occasions the problem of estimating a finite population quantile has been considered. The theory developed aims at providing the optimum estimates by combining (i) three double sampling estimators viz. ratio-type, product-type and regression-type, from the matched portion of the sample and (ii) a simple quantile based on a random sample from the unmatched portion of the sample on the second occasion. The approximate variance formulae of the suggested estimators have been obtained. Optimal matching fraction is discussed. A simulation study is carried out in order to compare the three estimators and direct estimator. It is found that the performance of the regression-type estimator is the best among all the estimators discussed here.

• Journal of the Korean Statistical Society
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• 제36권4호
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• pp.543-556
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• 2007

In successive sampling on two occasions the problem of estimating a finite population quantile has been considered. The theory developed aims at providing the optimum estimates by combining (i) three double sampling estimators viz. ratio-type, product-type and regression-type, from the matched portion of the sample and (ii) a simple quantile based on a random sample from the unmatched portion of the sample on the second occasion. The approximate variance formulae of the suggested estimators have been obtained. Optimal matching fraction is discussed. A simulation study is carried out in order to compare the three estimators and direct estimator. It is found that the performance of the regression-type estimator is the best among all the estimators discussed here.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 춘계종합학술대회 A
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• pp.894-897
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• 2008

스트레스는 현대 인간 문명사회에서의 피할 수 없는 결과이며 복잡한 현상이다. 또한 이의 통제 유무에 따라 인간의 활동능력은 심각한 변화를 받을 수 있다. 스트레스는 자극 호르몬인 아드레날린이나 다른 스트레스 호르몬이 혈중 내로 분비되어 우리 몸을 보호하려고 하는 반응으로 위험으로부터 싸우거나 멀리 피해버리는 힘과 에너지를 제공한다. 이러한 변화는 근유, 뇌, 심장에 더 많은 피를 보낼 수 있도록 맥박과 혈압을 증가시키고 더 많은 산소를 얻기 위해 호흡이 빨라지는 현상이 나타난다. 이에 본 논문에서는 스트레스를 통해 증가된 맥박과 혈압, 호흡수를 측정한 후 스트레스를 완화시키기 위한 방편으로 음악을 이용한 감성 기반 매칭 시스템을 설계한다. 음악에 따른 HRV와 APG의 변화율을 살펴보고 Zigbee를 이용하여 맥박, 혈압, 호흡수를 측정한 후 감성 음악을 기반으로 하여 스트레스를 완화시킬 수 있는 시스템을 제안한다.