Výsledky vyhledávání - "Youngseuk Cho"

Akademický článek

A decision tree to identify the combinations of non-communicable diseases that constitute the highest risk for dental caries experience: A hospital records-based study.

Autor: Hyun-Joo Kim, Youngseuk Cho, Yunhwan Noh, Ji-Young Joo, Hae Ryoun Park

Publikováno v: PLoS ONE, Vol 16, Iss 10, p e0257079 (2021)

To investigate whether dental status, represented by the DMFT score, was affected by the presence of NCDs and determined the NCDs that had a greater impact on the DMFT score. This retrospective cross-sectional study included a total of 10,017 individ

Externí odkaz: https://doaj.org/article/f5259c7fc1af43028c3b0ad6bf566bf2

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Akademický článek

Exact Inference for an Exponential Parameter under Generalized Adaptive Progressive Hybrid Censored Competing Risks Data

Autor: Youngseuk Cho, Kyeongjun Lee

Publikováno v: Symmetry, Vol 12, Iss 12, p 2005 (2020)

It is known that the lifetimes of items may not be recorded exactly. In addition, it is known that more than one risk factor (RisF) may be present at the same time. In this paper, we discuss exact likelihood inference for competing risk model (CoRiM)

Externí odkaz: https://doaj.org/article/35ddc54311214ee5868da1a7cdf14706

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Akademický článek

Estimating the Entropy of a Weibull Distribution under Generalized Progressive Hybrid Censoring

Autor: Youngseuk Cho, Hokeun Sun, Kyeongjun Lee

Publikováno v: Entropy, Vol 17, Iss 1, Pp 102-122 (2015)

Recently, progressive hybrid censoring schemes have become quite popular in a life-testing problem and reliability analysis. However, the limitation of the progressive hybrid censoring scheme is that it cannot be applied when few failures occur befor

Externí odkaz: https://doaj.org/article/f6a24c1ea8374a92bd21e42d87e8526c

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Akademický článek

An Estimation of the Entropy for a Rayleigh Distribution Based on Doubly-Generalized Type-II Hybrid Censored Samples

Autor: Youngseuk Cho, Hokeun Sun, Kyeongjun Lee

Publikováno v: Entropy, Vol 16, Iss 7, Pp 3655-3669 (2014)

In this paper, based on a doubly generalized Type II censored sample, the maximum likelihood estimators (MLEs), the approximate MLE and the Bayes estimator for the entropy of the Rayleigh distribution are derived. We compare the entropy estimators’

Externí odkaz: https://doaj.org/article/37aa52eb94244f84842a8a4ee900b80c

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Diagnosis of Early Glottic Cancer Using Laryngeal Image and Voice Based on Ensemble Learning of Convolutional Neural Network Classifiers

Autor: Ickhwan Kwon, Soo-Geun Wang, Sung-Chan Shin, Yong-Il Cheon, Byung-Joo Lee, Jin-Choon Lee, Dong-Won Lim, Cheolwoo Jo, Youngseuk Cho, Bum-Joo Shin

Publikováno v: Journal of Voice.

The purpose of study is to improve the classification accuracy by comparing the results obtained by applying decision tree ensemble learning, which is one of the methods to increase the classification accuracy for a relatively small dataset, with the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c130bc0fd42f1d2de24395bdbee62057
https://doi.org/10.1016/j.jvoice.2022.07.007

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