Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Taeyong Sim"'
Autor:
Hakje Yoo, Taeyong Sim
Publikováno v:
IEEE Access, Vol 10, Pp 115884-115894 (2022)
Coarse registration is the first step in determining the accuracy of surgical navigation. The purpose of this study was to present an automated coarse registration (ACR) methodology to improve the convenience and accuracy. For this purpose, a deep le
Externí odkaz:
https://doaj.org/article/007c71315f324727abb8b44aa68d04fa
Publikováno v:
Machines, Vol 11, Iss 7, p 674 (2023)
The performance of the electrohydraulic proportional control valve (EHPV) employed in a tractor’s automatic steering system directly influences the steering performance. To develop a highly reliable EHPV, it is essential to analyze the hydraulic ch
Externí odkaz:
https://doaj.org/article/9c4ba88f02e149b2a5efe57b58cf984c
Autor:
Seung-Min Baek, Seung-Yun Baek, Hyeon-Ho Jeon, Wan-Soo Kim, Yeon-Soo Kim, Nam-Hyeok Kim, Taeyong Sim, Hyunggun Kim, Yong-Joo Kim
Publikováno v:
Agriculture, Vol 12, Iss 2, p 123 (2022)
This study was conducted to ensure gear durability and design optimal transmission of agricultural tractors. A field test was conducted using an 86 kW agricultural tractor for plow and rotary tillage, which are typical agricultural operations. The fi
Externí odkaz:
https://doaj.org/article/f58767b5d0af4071a33fac1c7c2a2c97
Autor:
Taeyong Sim, Hakje Yoo, Dongjun Lee, Seung-Woo Suh, Jae Hyuk Yang, Hyunggun Kim, Joung Hwan Mun
Publikováno v:
Journal of NeuroEngineering and Rehabilitation, Vol 15, Iss 1, Pp 1-11 (2018)
Abstract Background The aim of this study was to quantitatively analyze quite standing postural stability of adolescent idiopathic scoliosis (AIS) patients in respect to three sensory systems (visual, vestibular, and somatosensory). Method In this st
Externí odkaz:
https://doaj.org/article/b28a283fc80d48979045a5b606af821a
Publikováno v:
Sensors, Vol 21, Iss 14, p 4801 (2021)
Machine vision with deep learning is a promising type of automatic visual perception for detecting and segmenting an object effectively; however, the scarcity of labelled datasets in agricultural fields prevents the application of deep learning to ag
Externí odkaz:
https://doaj.org/article/e5d01f4cc67e4313aac704347b781726
Publikováno v:
Sensors, Vol 18, Iss 4, p 1227 (2018)
In order to overcome the current limitations in current threshold-based and machine learning-based fall detectors, an insole system and novel fall classification model were created. Because high-acceleration activities have a high risk for falls, and
Externí odkaz:
https://doaj.org/article/e6c74b29f2504beca5061b543ee06ed8
Publikováno v:
Machines; Volume 11; Issue 7; Pages: 674
The performance of the electrohydraulic proportional control valve (EHPV) employed in a tractor’s automatic steering system directly influences the steering performance. To develop a highly reliable EHPV, it is essential to analyze the hydraulic ch
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::c8971f676adbbcd27bab6efb233cf8e4
Autor:
Yong-Han Kim, Seong-Bo Kim, Se-Hui Choi, Thi-Thao-Linh Nguyen, Sung-Hoon Ahn, Kyung-Sun Moon, Kwan Hyung Cho, Taeyong Sim, Eun-Ji Heo, Sungtae Kim, Han-Gon Choi, Dong-Jin Jang
The purpose of this study is to develop and evaluate a self-microemulsifying drug delivery system (SMEDDS) to improve the oral absorption of poorly water-soluble Olaparib. Through the solubility test of Olaparib in various oils, surfactants and co-su
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::290d34f8f5769e8acecbb0e0868e5176
https://doi.org/10.20944/preprints202304.0569.v1
https://doi.org/10.20944/preprints202304.0569.v1
Autor:
Hakje, Yoo, Taeyong, Sim
Publikováno v:
Medical Physics. 49:4845-4860
Although the surface registration technique has the advantage of being relatively safe and the operation time is short, it generally has the disadvantage of low accuracy.This research proposes automated machine learning (AutoML)-based surface registr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::310dc67f93b6ab8e1c36b0ee4cc46c9b
https://doi.org/10.1002/mp.15696
https://doi.org/10.1002/mp.15696
Autor:
Taeyong Sim, Seonbin Choi, Yunjae Kim, Su Hyun Youn, Dong-Jin Jang, Sujin Lee, Chang-Jae Chun
Publikováno v:
Electronics; Volume 11; Issue 18; Pages: 2947
This research proposes a methodology for the selection of input variables based on eXplainable AI (XAI) for energy consumption prediction. For this purpose, the energy consumption prediction model (R2 = 0.871; MAE = 2.176; MSE = 9.870) was selected b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27fd59dbb43f4031e761c67f72fb5186