2022 연구성과별 연구자 정보 (83 / 2879)

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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
A Study on the N2O Reduction Rate According to Temperature and Residence Time in the Exhaust Gas Atmosphere Emitted on Combustion of Air and Oxygen Kim, Ji Yeop Kim, JY 2 Kyungpook Natl Univ, Sch Mech Engn, Daegu 41566, South Korea jghong70@knu.ac.kr;
A Study on the N2O Reduction Rate According to Temperature and Residence Time in the Exhaust Gas Atmosphere Emitted on Combustion of Air and Oxygen Lee, Han Min Lee, HM 3 Kyungpook Natl Univ, Sch Mech Engn, Daegu 41566, South Korea jghong70@knu.ac.kr;
A Study on the N2O Reduction Rate According to Temperature and Residence Time in the Exhaust Gas Atmosphere Emitted on Combustion of Air and Oxygen Baik, Gwang Yeol Baik, GY 4 Kyungpook Natl Univ, Sch Mech Engn, Daegu 41566, South Korea jghong70@knu.ac.kr;
A Study on the N2O Reduction Rate According to Temperature and Residence Time in the Exhaust Gas Atmosphere Emitted on Combustion of Air and Oxygen Jeon, Min Kyu Jeon, MK 5 Korea Inst Machinery & Mat, Dept Environm Machinery, Daejeon 34103, South Korea jghong70@knu.ac.kr;
A Study on the N2O Reduction Rate According to Temperature and Residence Time in the Exhaust Gas Atmosphere Emitted on Combustion of Air and Oxygen Yun, Jin Han Yun, JH 6 Korea Inst Machinery & Mat, Dept Environm Machinery, Daejeon 34103, South Korea jghong70@knu.ac.kr;
A Study on the N2O Reduction Rate According to Temperature and Residence Time in the Exhaust Gas Atmosphere Emitted on Combustion of Air and Oxygen Hong, Jung Goo Hong, JG 7 교신저자 Kyungpook Natl Univ, Sch Mech Engn, Daegu 41566, South Korea jghong70@knu.ac.kr;
A Study on the Optimal Deep Learning Model for Dam Inflow Prediction Kim, Beom-Jin Kim, BJ 1 Korea At Energy Res Inst, Adv Structures & Seism Safety Res Div, Daejeon 34057, South Korea bhkimc@knu.ac.kr;
A Study on the Optimal Deep Learning Model for Dam Inflow Prediction Lee, You-Tae Lee, YT 2 Korea Water Resources Corp, Anal Ctr, Natl Drought Informat, Daejeon 34350, South Korea bhkimc@knu.ac.kr;
A Study on the Optimal Deep Learning Model for Dam Inflow Prediction Kim, Byung-Hyun Kim, BH 3 교신저자 Kyungpook Natl Univ, Dept Civil Engn, Daegu 41566, South Korea 0000-0001-7455-1292 Kim, Byunghyun bhkimc@knu.ac.kr;
A Study on Verification of Equivalence and Effectiveness of Non-Pharmacologic Dementia Prevention and Early Detection Contents : Non-Randomly Equivalent Design Jeong, Hyun-Seok Jeong, HS 1 Kyungpook Natl Univ, Coll Social Sci, Dept Psychol, 80 Daehak Ro, Daegu 41566, South Korea 0000-0002-1613-5001 jeong, hyeonseog psykhg@yu.ac.kr;moonsun@knu.ac.kr;
A Study on Verification of Equivalence and Effectiveness of Non-Pharmacologic Dementia Prevention and Early Detection Contents : Non-Randomly Equivalent Design Kim, Oh-Lyong Kim, OL 2 Yeungnam Univ, Coll Med, Dept Neurosurg, Daegu, South Korea psykhg@yu.ac.kr;moonsun@knu.ac.kr;
A Study on Verification of Equivalence and Effectiveness of Non-Pharmacologic Dementia Prevention and Early Detection Contents : Non-Randomly Equivalent Design Koo, Bon-Hoon Koo, BH 3 Yeungnam Univ, Coll Med, Dept Psychiat, 170 Hyeonchung Ro, Daegu 42415, South Korea KOD-4275-2024 KOO, BON HOON 0000-0001-9633-3835 Koo, Bon Hoon psykhg@yu.ac.kr;moonsun@knu.ac.kr;
A Study on Verification of Equivalence and Effectiveness of Non-Pharmacologic Dementia Prevention and Early Detection Contents : Non-Randomly Equivalent Design Kim, Ki-Hyun Kim, KH 4 Corp Res Inst Clupea Inc, Daegu, South Korea 0000-0001-9717-6069 KIM, KIHYUN psykhg@yu.ac.kr;moonsun@knu.ac.kr;
A Study on Verification of Equivalence and Effectiveness of Non-Pharmacologic Dementia Prevention and Early Detection Contents : Non-Randomly Equivalent Design Kim, Gi-Hwan Kim, GH 5 Corp Res Inst Clupea Inc, Daegu, South Korea 0000-0001-5711-9350 Kim, Gihwan psykhg@yu.ac.kr;moonsun@knu.ac.kr;
A Study on Verification of Equivalence and Effectiveness of Non-Pharmacologic Dementia Prevention and Early Detection Contents : Non-Randomly Equivalent Design Bai, Dai-Seg Bai, DS 6 Yeungnam Univ, Coll Med, Dept Psychiat, 170 Hyeonchung Ro, Daegu 42415, South Korea psykhg@yu.ac.kr;moonsun@knu.ac.kr;
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