Zobrazeno 1 - 10 of 25 pro vyhledávání: '"Jihyuk Kim"'
1
Heat Transfer on Fuel Injector Surface With Backward Facing Stepped Scramjet Flame Holder
Autor: Hyung Mo Bae, Jihyuk Kim, Juyeong Nam, Injoong Chang, Hee Koo Moon, Hyung Hee Cho
Publikováno v: ASME 2022 Heat Transfer Summer Conference.
The scramjet engine burns fuel under supersonic flow condition in a combustion chamber while minimizing total pressure such that it can operate under both supersonic and hypersonic flows. For combustion under supersonic flow field, a flame holder is
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::381685e7167bac54da17dd013175e08e
https://doi.org/10.1115/ht2022-83853
Zobrazit plný text záznamu
2
Oxygen isotope record of magmatic evolution of alkaline volcanic rocks at The Pleiades, northern Victoria Land, Antarctica
Autor: Nak Kyu Kim, Jihyuk Kim, Jong Ik Lee, Mi Jung Lee
Publikováno v: Geosciences Journal. 25:787-797
Oxygen isotopes are used to examine the well-documented magmatic evolution of alkaline volcanic rocks at The Pleiades in northern Victoria Land (NVL), Antarctica. Oxygen isotopes were measured in olivine, clinopyroxene, and plagioclase phenocrysts to
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b7a0398a0f62e631fad466dae148acd8
https://doi.org/10.1007/s12303-021-0002-x
Zobrazit plný text záznamu
3
Collective Relevance Labeling for Passage Retrieval
Autor: Jihyuk Kim, Minsoo Kim, Seung-won Hwang
Deep learning for Information Retrieval (IR) requires a large amount of high-quality query-document relevance labels, but such labels are inherently sparse. Label smoothing redistributes some observed probability mass over unobserved instances, often
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb85e61aaecc21bfa1d8c2188e16a346
http://arxiv.org/abs/2205.03273
Zobrazit plný text záznamu
5
Web Document Encoding for Structure-Aware Keyphrase Extraction
Autor: Seung-won Hwang, Young-In Song, Jihyuk Kim
Publikováno v: SIGIR
We study keyphrase extraction (KPE) from Web documents. Our key contribution is encoding Web documents to leverage structure, such as title or anchors, by building a graph of words representing both (a) position-based proximity and (b) structural rel
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bb5bb90b50de6bfaeaaa37d6645bcdb3
https://doi.org/10.1145/3404835.3463067
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje