Výsledky vyhledávání - "Yeongjin Cho"

Akademický článek

A Study on the Anomaly Detection of Engine Clutch Engagement/Disengagement Using Machine Learning for Transmission Mounted Electric Drive Type Hybrid Electric Vehicles

Autor: Yonghyeok Ji, Seongyong Jeong, Yeongjin Cho, Howon Seo, Jaesung Bang, Jihwan Kim, Hyeongcheol Lee

Publikováno v: Applied Sciences, Vol 11, Iss 21, p 10187 (2021)

Transmission mounted electric drive type hybrid electric vehicles (HEVs) engage/disengage an engine clutch when EV↔HEV mode transitions occur. If this engine clutch is not adequately engaged or disengaged, driving power is not transmitted correctly

Externí odkaz: https://doaj.org/article/70700a112af74cde9732947e86560643

Zobrazit plný text záznamu

A Study on the Anomaly Detection of Engine Clutch Engagement/Disengagement Using Machine Learning for Transmission Mounted Electric Drive Type Hybrid Electric Vehicles

Autor: Jihwan Kim, Yonghyeok Ji, Yeongjin Cho, Jaesung Bang, Hyeongcheol Lee, Howon Seo, Seongyong Jeong

Publikováno v: Applied Sciences, Vol 11, Iss 10187, p 10187 (2021)
Applied Sciences
Volume 11
Issue 21

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9138407187923408bbae7ae1eabf303a
https://doi.org/10.3390/app112110187

Zobrazit plný text záznamu

Absorption Study of Genistein Using Solid Lipid Microparticles and Nanoparticles: Control of Oral Bioavailability by Particle Sizes

Autor: Hyojin Jeon, Sangwon Gil, Sonia Barua, Yeongjin Cho, Seung-Yup Yoo, Seong-Chul Hong, Jaehwi Lee, Hyeongmin Kim, Jeong Tae Kim, Kyungsoo Oh

Publikováno v: Biomolecules & Therapeutics

In this study, the effect of particle size of genistein-loaded solid lipid particulate systems on drug dissolution behavior and oral bioavailability was investigated. Genistein-loaded solid lipid microparticles and nanoparticles were prepared with gl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7761e7a98917ca5e654a00644b32cdeb
http://europepmc.org/articles/PMC5499625

Zobrazit plný text záznamu

Akademický článek

Development and Validation of a Prediction Model for Differentiation of Benign and Malignant Fat-Poor Renal Tumors Using CT Radiomics

Autor: Seokhwan Bang, Hee-Hwan Wang, Hokun Kim, Moon Hyung Choi, Jiook Cha, Yeongjin Choi, Sung-Hoo Hong

Publikováno v: Applied Sciences, Vol 13, Iss 20, p 11345 (2023)

Objectives: To develop and validate a machine learning-based CT radiomics classification model for distinguishing benign renal tumors from malignant renal tumors. Methods: We reviewed 499 patients who underwent nephrectomy for solid renal tumors at o

Externí odkaz: https://doaj.org/article/2dfbc0c7bba84d1bb86daccb07a3847b

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání