Zobrazeno 1 - 10
of 249
pro vyhledávání: '"Sungil, Kim"'
Publikováno v:
Electronic Research Archive, Vol 31, Iss 2, Pp 691-707 (2023)
The accurate estimation of time delays is crucial in traffic congestion analysis, as this information can be used to address fundamental questions regarding the origin and propagation of traffic congestion. However, the exact measurement of time dela
Externí odkaz:
https://doaj.org/article/b33d474123eb426fb2a459cdabfaf30d
Publikováno v:
Case Studies in Thermal Engineering, Vol 49, Iss , Pp 103218- (2023)
Spray drying process, widely used in industrial applications, is highly energy-consuming. To reduce the energy consumption under the secured yield, optimizing the operating conditions of drying process or utilizing heat from the exhaust air of dryers
Externí odkaz:
https://doaj.org/article/fecb0b94f2f44d35bd5896f37e40ba52
Publikováno v:
Micromachines, Vol 14, Iss 9, p 1766 (2023)
Selective laser etching is a promising candidate for the mass production of glass interposers. It comprises two steps: local modification by an ultrashort-pulsed laser and chemical etching of the modified volume. According to previous studies, when a
Externí odkaz:
https://doaj.org/article/0467074fd6404cce82d9552d683bcbb1
Publikováno v:
ETRI Journal, Vol 43, Iss 5, Pp 916-922 (2021)
AbstractWe calculated the correlation between the doping concentration of the charge layer and the multiplication layer for separate absorption, grading, charge, and multiplication InGaAs/InAlAs avalanche photodiodes (APDs). For this purpose, a predi
Externí odkaz:
https://doaj.org/article/0c3dc35fd7f849b4a9b1dbcea9250191
Autor:
Kushal K. Dey, Bryce van de Geijn, Samuel Sungil Kim, Farhad Hormozdiari, David R. Kelley, Alkes L. Price
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
Deep learning models have shown great promise in predicting regulatory effects from DNA sequence. Here the authors evaluate sequence-based epigenomic deep learning models and conclude that these models are not yet ready to inform our knowledge of hum
Externí odkaz:
https://doaj.org/article/e966c41c45b24c86a35cad7f34f42b80
Publikováno v:
Micro and Nano Systems Letters, Vol 7, Iss 1, Pp 1-7 (2019)
Abstract We present the selective laser-induced etching (SLE) process and design guidelines for the fabrication of three-dimensional (3D) microfluidic channels in a glass. The SLE process consisting of laser direct patterning and wet chemical etching
Externí odkaz:
https://doaj.org/article/a0c7df1e2d3847c2bd3a50e0cb28a790
Autor:
Hong En Fu, Thomas Myeongseok Koo, Myeong Soo Kim, Min Jun Ko, Bum Chul Park, Kyuha Oh, Younhyung Cho, Jae-Wan Jung, Sungil Kim, Woong Sik Jang, Chae Seung Lim, Young Keun Kim
Publikováno v:
ACS Applied Nano Materials. 6:5789-5798
Publikováno v:
Micromachines, Vol 13, Iss 8, p 1331 (2022)
A miniaturized pump to manipulate liquid flow in microchannels is the key component of microfluidic devices. Many researchers have demonstrated active microfluidic pumps, but most of them still required additional large peripherals to operate their m
Externí odkaz:
https://doaj.org/article/22be30d1212943ddad4521e7e17eee2d
Publikováno v:
Applied Sciences, Vol 12, Iss 17, p 8775 (2022)
This study proposes a deep-learning-based model to generate synthetic compressional wave velocity (Vp) from well-logging data with application to the Ulleung Basin Gas Hydrate (UBGH) in the East Sea, Republic of Korea. Because a bottom-simulating ref
Externí odkaz:
https://doaj.org/article/5b6fa9debf284051838e2529a39c8548
Autor:
Jong Kwan Lee, Sujin Kim, Wonsik Kim, Sungil Kim, Seungwoo Cha, Hankyeol Moon, Dong Hoon Hur, Seon-Young Kim, Jeong-Geol Na, Jin Won Lee, Eun Yeol Lee, Ji-Sook Hahn
Publikováno v:
Biotechnology for Biofuels, Vol 12, Iss 1, Pp 1-11 (2019)
Abstract Background Methane, a main component of natural gas and biogas, has gained much attention as an abundant and low-cost carbon source. Methanotrophs, which can use methane as a sole carbon and energy source, are promising hosts to produce valu
Externí odkaz:
https://doaj.org/article/f6f538bf1fd7463a9b633a8305bbf14e