Zobrazeno 1 - 10
of 43
pro vyhledávání: '"XIANGPING ZHENG"'
Publikováno v:
PLoS ONE, Vol 18, Iss 5, p e0286321 (2023)
BackgroundCOVID-19 caused severe effects on the psychological well-being of Chinese students overseas (COS). Physical activity (PA) is critical to strengthen immunity, prevent infection, and reduce the psychological burden caused by COVID-19. However
Externí odkaz:
https://doaj.org/article/eedb2a646cc54d239ede06a5cc38d125
Autor:
Dongqing Lin, Ying Wei, Aizhong Peng, He Zhang, Chunxiao Zhong, Dan Lu, Hao Zhang, Xiangping Zheng, Lei Yang, Quanyou Feng, Linghai Xie, Wei Huang
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-11 (2020)
Gridarenes with well-defined edges and vertices represent versatile nanoscale building blocks for installating frameworks but suffer from lack of stereoselective control during their synthesis. Here, the authors report a diastereoselective gridizatio
Externí odkaz:
https://doaj.org/article/0f1f4a0c408b4c9280789b973052f223
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 17:1-19
Recently, with the development of temporal knowledge graph technology, more and more Temporal Knowledge Graph Embedded (TKGE) models have been developed. The effectiveness of TKGE largely depends on the ability to model intrinsic relation patterns an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b67fabd31270d2f8b1af1b08b64d497b
https://doi.org/10.1145/3589644
https://doi.org/10.1145/3589644
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 17:1-19
Weakly Supervised Semantic Segmentation with image-level annotation uses localization maps from the classifier to generate pseudo labels. However, such localization maps focus only on sparse salient object regions, it is difficult to generate high-qu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a18fe2eeb82e6fcff8896cd415103fb4
https://doi.org/10.1145/3589343
https://doi.org/10.1145/3589343
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 17:1-25
As the scope of receptive field and the depth of Graph Neural Networks (GNNs) are two completely orthogonal aspects for graph learning, existing GNNs often have shallow layers with truncated-receptive field and far from achieving satisfactory perform
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d96feaf2c1d626b940bbc181fe6f3be8
https://doi.org/10.1145/3572781
https://doi.org/10.1145/3572781
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5a8c79a65726e7dcb481e58eeb89914
https://doi.org/10.1109/icassp49357.2023.10095978
https://doi.org/10.1109/icassp49357.2023.10095978
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8aeede8a995415766095c0452350aea3
https://doi.org/10.1109/icassp49357.2023.10095087
https://doi.org/10.1109/icassp49357.2023.10095087
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b75ac12d8781374dd63c7913330a7e2f
https://doi.org/10.1109/icassp49357.2023.10095586
https://doi.org/10.1109/icassp49357.2023.10095586
ESTRATEGIAS DE ENTRENAMIENTO DE RESISTENCIA CARDIOPULMONAR Y APTITUD FÍSICA PARA ADOLESCENTES OBESOS
Autor:
Xue Zhang, Xiangping Zheng
Publikováno v:
Revista Brasileira de Medicina do Esporte, Volume: 29, Article number: e2022_0744, Published: 27 FEB 2023
Introduction: Reducing the risk of obesity and maintaining healthy lifestyle habits and physical exercise is very important for adolescents in a crucial period of their development. Objective: Study the effect of physical training on cardiopulmonary
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d3400f7fe7bc0396e50b16adc69d66b
https://doi.org/10.1590/1517-8692202329012022_0744
https://doi.org/10.1590/1517-8692202329012022_0744
Publikováno v:
Proceedings of the 2023 SIAM International Conference on Data Mining (SDM) ISBN: 9781611977653
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b007273abe7139bf6829a821104448e5
https://doi.org/10.1137/1.9781611977653.ch57
https://doi.org/10.1137/1.9781611977653.ch57
