Browse by Title 

Showing results 156861 to 156880 of 275281

156861
Predicting BVI Loadings and Wake Structure of the HART II Rotor Using Adaptive Unstructured Meshes

Yu, D. O; Jung, M. S; Kwon, Oh Joon; Yu, Y. H, Presented at the 2nd International Forum on Rotorcraft Multidisciplinary Technology, 2009-10-19

156862
Predicting clinical benefit of immunotherapy by antigenic or functional mutations affecting tumour immunogenicity

Kim, Kwoneel; Kim, Hong Sook; Kim, Jeong Yeon; Jung, Hyunchul; Sun, Jong-Mu; Ahn, Jin Seok; Ahn, Myung-Ju; et al, NATURE COMMUNICATIONS, v.11, no.1, 2020-02

156863
Predicting clinical responses to checkpoint immunotherapy based on genetic and epigenetic alterations in cancer = 유전적 및 후성유전적 변이에 기반한 항암면역치료 반응성 예측link

Kim, Kyeong Hui; Choi, Jung Kyoon; et al, 한국과학기술원, 2022

156864
Predicting complexity of refactoring within refactoring application contexts = 적용 상황에서의 코드 리팩토링의 복잡도 예측link

Gim, Jong-Gun; 김종근; et al, 한국정보통신대학교, 2006

156865
Predicting computer task performance: Personal goal and self-efficacy

Yi, Mun Yong; Im, K.S., JOURNAL OF ORGANIZATIONAL AND END USER COMPUTING, v.16, no.2, pp.20 - 37, 2004-04

156866
Predicting corporate defaults using machine learning with geometric-lag variables

Kim, Hyeongjun; Cho, Hoon; Ryu, Doojin, INVESTMENT ANALYSTS JOURNAL, v.50, no.3, pp.161 - 175, 2021-07

156867
Predicting critical transitions in complex systems = 복잡계 시스템의 임계전이 예측에 관한 연구link

Chu, Hyunho; 추현호; et al, 한국과학기술원, 2016

156868
Predicting Detectability and Annoyance of EV Warning Sounds using Partial Loudness

Jacobsen, Gustav N; Ih, Jeong Guon; Song, Wookeun; Macdonald, Ewen N, Inter-Noise 2016, InterNoise, 2016-08-22

156869
Predicting disease phenotypes based on the molecular networks with Condition-Responsive Correlation

Lee, Se-Joon; Lee, Eun-Jung; Lee, Kwang-Hyung; Lee, Do-Heon, INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS, v.5, no.2, pp.131 - 142, 2011-03

156870
Predicting double-blade vertical axis wind turbine performance by a quadruple-multiple streamtube model

Hara, Y.; Kawamura, T.; Akimoto, Hiromichi; Tanaka, K.; Nakamura, T.; Mizumukai, K., International Journal of Fluid Machinery and Systems, v.7, no.1, pp.16 - 27, 2014-03

156871
Predicting drug interactions from molecular structures using machine learning

Kim, Hyun Uk, Artificial Intelligence for Natural Product Drug Discovery, Lorentz Center, 2021-09-27

156872
Predicting drug response using biological networks = 생물학적 네트워크를 활용한 약물 반응 예측link

Hwang, Woochang; 황우창; et al, 한국과학기술원, 2016

156873
Predicting drug-target interaction using 3D structure-embedded graph representations from graph neural networks

Lim, Jaechang; Ryu, Seongok; Park, Kyubyong; Choe, Yo Joong; Ham, Jiyeon; Kim, Woo Youn, The 5 th International Conference on Molecular Simulation, The Korean Institute of Metals and Materials, The Korea Institute of Science and Technology, Korea Advanced Institute of Science and Technology - ACE Team, Seoul National University, 2019-11-05

156874
Predicting Drug-Target Interaction Using a Novel Graph Neural Network with 3D Structure-Embedded Graph Representation

Lim, Jaechang; Ryu, Seongok; Park, Kyubyong; Choe, Yo Joong; Ham, Jiyeon; Kim, Woo Youn, JOURNAL OF CHEMICAL INFORMATION AND MODELING, v.59, no.9, pp.3981 - 3988, 2019-09

156875
Predicting drug-target interaction using a novel graph neural network with 3D structure-embedded graph representation

임재창; 류성옥; 박규병; 최요중; 함지연; 김우연, 제130차 대한화학회 물리화학분과회 하계 심포지엄, 대한화학회 물리화학분과회, 2019-07-08

156876
Predicting drug-target interactions with deep neural networks in semi-supervised learning manner = 준지도 학습 방식의 심층 신경망을 이용한 약물-타겟 단백질의 상호작용 예측link

Jeong, Chungsun; Lee, Do Heon; et al, 한국과학기술원, 2019

156877
Predicting Dynamic Clinical Outcomes of the Chemotherapy for Canine Lymphoma Patients Using a Machine Learning Model

Koo, Jamin; Choi, Kyucheol; Lee, Peter; Polley, Amanda; Pudupakam, Raghavendra Sumanth; Tsang, Josephine; Fernandez, Elmer; et al, VETERINARY SCIENCES, v.8, no.12, pp.8120301, 2021-12

156878
Predicting electron density using convolutional neural networks

이룡규; 김용훈, 제18회 고등과학원 전자구조계산학회, 한국고등과학원, 2022-07-07

156879
Predicting electron density using convolutional neural networks

이룡규; 김용훈, 2022 Workshop on Computational Nanotechnology, 카이스트 전기 및 전자공학부 계산나노공학 연구실, 2022-07-22

156880
Predicting Electronic Density of States of Nanoparticles by Principal Component Analysis and Crystal Graph Convolutional Neural Network

Bang, Kihoon; Yeo, Byung Chul; Hong, Doosun; Kim, Donghun; Han, Sang Soo; Lee, Hyuck-Mo, TMS 2020 Annual Meeting & Exhibition, The Minerals, Metals & Materials Society, 2020-02-24

rss_1.0 rss_2.0 atom_1.0