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2024 연구성과별 연구자 정보 (1190 / 2344)

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Document Title Author Full Name Author Short Name Index Corresponding Address ResearcherID ResearcherID Author Name ORCID ORCID Author Name Related Email
Improvement of volatile aromatic compound levels and sensory quality of distilled soju derived from Saccharomyces cerevisiae and Wickerhamomyces anomalus co-fermentation Kim, Yeong-Jun Kim, YJ 3 Kyungpook Natl Univ, Sch Food Sci & Biotechnol, Daegu 41566, South Korea lsbyuck@knu.ac.kr;
Improvement of volatile aromatic compound levels and sensory quality of distilled soju derived from Saccharomyces cerevisiae and Wickerhamomyces anomalus co-fermentation Choi, Jun-Su Choi, JS 4 Kyungpook Natl Univ, Sch Food Sci & Biotechnol, Daegu 41566, South Korea MVY-2121-2025 Choi, Jun-Su lsbyuck@knu.ac.kr;
Improvement of volatile aromatic compound levels and sensory quality of distilled soju derived from Saccharomyces cerevisiae and Wickerhamomyces anomalus co-fermentation Lee, Sae-Byuk Lee, SB 5 교신저자 Kyungpook Natl Univ, Sch Food Sci & Biotechnol, Daegu 41566, South Korea lsbyuck@knu.ac.kr;
Improvement of volatile aromatic compound levels and sensory quality of distilled soju derived from Saccharomyces cerevisiae and Wickerhamomyces anomalus co-fermentation Lee, Sae-Byuk Lee, SB 5 교신저자 Kyungpook Natl Univ, Inst Fermentat Biotechnol, Daegu 41566, South Korea lsbyuck@knu.ac.kr;
IMPROVING NOROVIRUS OUTBREAK PREDICTION THROUGH FEATURE SELECTION USING MACHINE LEARNING METHODS Cho, Giphil Cho, G 1 Kangwon Nat Univ, Dept Artificial Intelligence & Software, Kangwon, South Korea giphil@kangwon.ac.kr;jeonghwa_seo@knu.ac.kr;hjlee@knu.ac.kr;
IMPROVING NOROVIRUS OUTBREAK PREDICTION THROUGH FEATURE SELECTION USING MACHINE LEARNING METHODS Seo, Jeonghwa Seo, J 2 Kyungpook Natl Univ, Dept Stat, Kyungpook, South Korea giphil@kangwon.ac.kr;jeonghwa_seo@knu.ac.kr;hjlee@knu.ac.kr;
IMPROVING NOROVIRUS OUTBREAK PREDICTION THROUGH FEATURE SELECTION USING MACHINE LEARNING METHODS Lee, Hyojung Lee, H 3 교신저자 Kyungpook Natl Univ, Dept Stat, Kyungpook, South Korea giphil@kangwon.ac.kr;jeonghwa_seo@knu.ac.kr;hjlee@knu.ac.kr;
Improving rainfall-runoff modeling in the Mekong river basin using bias-corrected satellite precipitation products by convolutional neural networks Le, Xuan-Hien Le, XH 1 교신저자 Kyungpook Natl Univ, Dept Adv Sci & Technol Convergence, 2559 Gyeongsang, Sangju 37224, South Korea AAZ-9166-2021 Le, Xuan-Hien 0000-0002-0947-0805 Le, Xuan-Hien hienlx@knu.ac.kr;leegiha@knu.ac.kr;
Improving rainfall-runoff modeling in the Mekong river basin using bias-corrected satellite precipitation products by convolutional neural networks Le, Xuan-Hien Le, XH 1 교신저자 Thuyloi Univ, Fac Water Resources Engn, 175 Tay Son, Hanoi 10000, Vietnam AAZ-9166-2021 Le, Xuan-Hien 0000-0002-0947-0805 Le, Xuan-Hien hienlx@knu.ac.kr;leegiha@knu.ac.kr;
Improving rainfall-runoff modeling in the Mekong river basin using bias-corrected satellite precipitation products by convolutional neural networks Kim, Younghun Kim, Y 2 Kyungpook Natl Univ, Dept Adv Sci & Technol Convergence, 2559 Gyeongsang, Sangju 37224, South Korea hienlx@knu.ac.kr;leegiha@knu.ac.kr;
Improving rainfall-runoff modeling in the Mekong river basin using bias-corrected satellite precipitation products by convolutional neural networks Binh, Doan Van Binh, DV 3 Vietnamese German Univ, Fac Engn, Ben Cat Town 820000, Binh Duong, Vietnam AAY-3488-2020 Van Binh, Doan hienlx@knu.ac.kr;leegiha@knu.ac.kr;
Improving rainfall-runoff modeling in the Mekong river basin using bias-corrected satellite precipitation products by convolutional neural networks Jung, Sungho Jung, S 4 Kyungpook Natl Univ, Dept Adv Sci & Technol Convergence, 2559 Gyeongsang, Sangju 37224, South Korea hienlx@knu.ac.kr;leegiha@knu.ac.kr;
Improving rainfall-runoff modeling in the Mekong river basin using bias-corrected satellite precipitation products by convolutional neural networks Nguyen, Duc Hai Nguyen, DH 5 Univ Saskatchewan, Dept Civil Geol & Environm Engn, 57 Campus Dr, Saskatoon, SK S7N 5A9, Canada AAD-8210-2020 Nguyen, Hai hienlx@knu.ac.kr;leegiha@knu.ac.kr;
Improving rainfall-runoff modeling in the Mekong river basin using bias-corrected satellite precipitation products by convolutional neural networks Lee, Giha Lee, G 6 교신저자 Kyungpook Natl Univ, Dept Adv Sci & Technol Convergence, 2559 Gyeongsang, Sangju 37224, South Korea hienlx@knu.ac.kr;leegiha@knu.ac.kr;
Improving Systematic Generalization of Linear Transformer Using Normalization Layers and Orthogonality Loss Function Park, Taewon Park, T 1 Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu 41566, South Korea ptw4570@knu.ac.kr;hyunchul_kim@knu.ac.kr;
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