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2024 연구성과별 연구자 정보 (791 / 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
Enhancing Inter-Patient Performance for Arrhythmia Classification with Adversarial Learning Using Beat-Score Maps Shin, Miyoung Shin, M 3 교신저자 Kyungpook Natl Univ, Grad Sch Elect & Elect Engn, Biointelligence & Data Min Lab, Daegu 41566, South Korea yeji7102@naver.com;realjaewon94@gmail.com;shinmy@knu.ac.kr;
Enhancing landfill gas bio-desulfurization: operational insights and microbial dynamics from the Daegu Bangcheon-ri Sanitary Landfill Cho, Eunsue Cho, ES 1 Daesung Ecoenergy, Daegu, South Korea jwhong@knu.ac.kr;
Enhancing landfill gas bio-desulfurization: operational insights and microbial dynamics from the Daegu Bangcheon-ri Sanitary Landfill Cho, Eunsue Cho, ES 1 Kyungpook Natl Univ, Dept Hydrogen & Renewable Energy, Daegu, South Korea jwhong@knu.ac.kr;
Enhancing landfill gas bio-desulfurization: operational insights and microbial dynamics from the Daegu Bangcheon-ri Sanitary Landfill You, Young-Hyun You, YH 2 Natl Inst Biol Resources, Species Divers Res Div, Incheon, South Korea jwhong@knu.ac.kr;
Enhancing landfill gas bio-desulfurization: operational insights and microbial dynamics from the Daegu Bangcheon-ri Sanitary Landfill Back, Chang-Gi Back, CG 3 Dankook Univ, Dept Environm Hort & Landscape Architecture, Environm Hort, Cheonan, South Korea jwhong@knu.ac.kr;
Enhancing landfill gas bio-desulfurization: operational insights and microbial dynamics from the Daegu Bangcheon-ri Sanitary Landfill Hong, Ji Won Hong, JW 4 교신저자 Kyungpook Natl Univ, Dept Hydrogen & Renewable Energy, Daegu, South Korea jwhong@knu.ac.kr;
Enhancing landfill gas bio-desulfurization: operational insights and microbial dynamics from the Daegu Bangcheon-ri Sanitary Landfill Hong, Ji Won Hong, JW 4 교신저자 Kyungpook Natl Univ, Adv Bioresource Res Ctr, Daegu, South Korea jwhong@knu.ac.kr;
Enhancing machine learning models for total organic carbon prediction by integrating geospatial parameters in river watersheds Oh, Haeseong Oh, H 1 Sejong Univ, Dept Environm & Energy, 209 Neungdong Ro, Seoul 05006, South Korea 0000-0001-7599-9777 oh, haeseong jinhur@sejong.ac.kr;
Enhancing machine learning models for total organic carbon prediction by integrating geospatial parameters in river watersheds Park, Ho-Yeon Park, HY 2 Sejong Univ, Dept Environm & Energy, 209 Neungdong Ro, Seoul 05006, South Korea jinhur@sejong.ac.kr;
Enhancing machine learning models for total organic carbon prediction by integrating geospatial parameters in river watersheds Kim, Jae In Kim, JI 3 Kyungpook Natl Univ, Dept Ecol & Environm Syst, 2559 Gyeongsang daero, Sangju 37224, South Korea jinhur@sejong.ac.kr;
Enhancing machine learning models for total organic carbon prediction by integrating geospatial parameters in river watersheds Lee, Byung Joon Lee, BJ 4 Kyungpook Natl Univ, Dept Ecol & Environm Syst, 2559 Gyeongsang daero, Sangju 37224, South Korea jinhur@sejong.ac.kr;
Enhancing machine learning models for total organic carbon prediction by integrating geospatial parameters in river watersheds Choi, Jung Hyun Choi, JH 5 Ewha Womans Univ, Dept Environm Sci & Engn, 52 Ewhayeodae Gil, Seoul 03760, South Korea jinhur@sejong.ac.kr;
Enhancing machine learning models for total organic carbon prediction by integrating geospatial parameters in river watersheds Hur, Jin Hur, J 6 교신저자 Sejong Univ, Dept Environm & Energy, 209 Neungdong Ro, Seoul 05006, South Korea jinhur@sejong.ac.kr;
Enhancing Microcontroller Security Through Volatile Memory-Resident Encrypted Code Kim, Minjung Kim, M 1 Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu, South Korea boltanut@knu.ac.kr;
Enhancing Microcontroller Security Through Volatile Memory-Resident Encrypted Code Park, Daejin Park, D 2 교신저자 Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu, South Korea boltanut@knu.ac.kr;
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