| 2008 | M-3(PO4)(2)-nanoparticle-coated LiCoO2 vs LiCo0.96M0.04O2 (M = Mg and Zn) on electrochemical and storage characteristics | Eom, Junho; Cho, Jaephil | ARTICLE | 902 |
| 2006-01 | M-Doped TiO₂ (M=Co, Cr, Fe)의 제조 : 전자 밴드구조-(1) | Bae, Sang Won; Kim, Hyun Gyu; Ji, Sang Min; Jang, Jum Suk; Jeong, Euh Duck; Hong, Suk Joon; Lee, Jae Sung | ARTICLE | 691 |
| 2019-05-22 | M-N-C 계 전극촉매 및 그 제조방법과 FE-N-C 계 전극촉매를 포함하는 연료전지 | 주상훈; 사영진; 우진우; 울산과학기술원 | Patent | 173 |
| 2014-01 | M2M Service Platforms: Survey, Issues, and Enabling Technologies | Kim, Jaewoo; Lee, Jaiyong; Kim, Jaeho; Yun, Jaeseok | ARTICLE | 86 |
| 2013-07 | M2M/IoT 서비스를 위한 무선 통신망 기술 : 지속적 WSN망과 Cellular 접근망 | 김종헌; 김재우; 유석; 이재용 | ARTICLE | 81 |
| 2001-10-11 | M3 Muscarinic Receptor-mediated Phospholipase D1 Activation Is Involved in the Up-Regulation of Phospholipase C Activity | Suh, Pann-Ghill; None; None; None; None; None | CONFERENCE | 27 |
| 2001-07-28 | M3 muscrinic receptor-mediated phospholipase D1 activation is involved in the up-regulation of phospholipase C activity | Suh, Pann-Ghill; None; None; None; None; None | CONFERENCE | 24 |
| 2019-08 | MACHINE LEARNING - BASED EXCITED STATE MOLECULAR DYNAMICS | Min, Seung Kyu; Kim, Kicheol | Master's thesis | 259 |
| 2016-12-16 | Machine Learning and Data Visualization in Manufacturing | Lee, Seungchul | CONFERENCE | 36 |
| 2018-03-05 | Machine learning and digital image processing for non-contact modal parameters identification of structures | Torbol, Marco; Park, KT | CONFERENCE | 36 |
| 2018-12-11 | Machine learning apporaches to wildfire detection using geostationary satellite data | Kang, Yoojin; Im, Jungho; Jang, Kunna | CONFERENCE | 45 |
| 2018-05-11 | Machine learning apporaches to wildfire detection using geostationary satellite data | Kang, Yoojin; Jang, Kunna; Im, Jungho | CONFERENCE | 44 |
| 2019-08-20 | Machine Learning Approach for the Prediction of Mechanical Properties Based on the Steel Microstructure Volume Fraction Ratio | Jung, Im Doo; Sung, Hyo kyung; Moon, Seung Ki | CONFERENCE | 56 |
| 2019-10-30 | Machine Learning Approach for the Prediction of Mechanical Properties with Microstructural Parameters in API Pipeline Steels | Jung, Im Doo; Sung. H. K.; Park, S. J.; Yu , J. H. | CONFERENCE | 30 |
| 2019-05 | Machine learning approaches for detecting tropical cyclone formation using satellite data | Kim, Minsang; Park, Myung-Sook; Im, Jungho; Park, S; Lee, Myong-In | ARTICLE | 396 |
| 2015-07-28 | Machine learning approaches for down scaling AMSR-E soil moisture over south Korea | Im, Jungho; Park, Sunyoung; Baek, JongJin; Choi, MinHa; Lee, Jinyoung | CONFERENCE | 48 |
| 2018-05 | Machine Learning Approaches for Estimating Forest Stand Height Using Plot-Based Observations and Airborne LiDAR Data | Lee, Junghee; Im, Jungho; Kim, Kyungmin; Quackenbush, Lindi J. | ARTICLE | 487 |
| 2012 | Machine Learning Approaches for Forest Carbon Stock Estimation Using Remotely Sensed Data | Im, Jungho | CONFERENCE | 25 |
| 2013-08 | Machine learning approaches for forest classification and change analysis using multi-temporal Landsat TM images over Huntington Wildlife Forest | Li, Manqi; Im, Jungho; Beier, Colin | ARTICLE | 779 |
| 2011-04-16 | Machine learning approaches for forest classification using multi-temporal Landsat TM images | Im, Jungho; None | CONFERENCE | 5 |
