Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Jinglong Yu"'
Autor:
Peng Jiang, Hengqian Gan, Rui Yao, Jinghai Sun, Jiguang Lu, Dongjun Yu, Hui Li, Jinglong Yu, Bin Dong, Xiaoming Chai, Jianing Yin
Publikováno v:
Engineering, Vol 28, Iss , Pp 21-25 (2023)
Externí odkaz:
https://doaj.org/article/f9c4e5b5e1144149b7ed5931b02a37ae
Autor:
Ning Zhang, Man Gao, Jinglong Yu, Qiang Zhang, Weiguang Wang, Congxiao Zhou, Lingjia Liu, Ting Sun, Xing Liao, Junhong Wang
Publikováno v:
Brain and Behavior, Vol 12, Iss 10, Pp n/a-n/a (2022)
Abstract Objectives Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in childhood, which may be related to adverse childhood experiences (ACEs). Our study aims to explore the association between ACEs and subsequ
Externí odkaz:
https://doaj.org/article/fa328c12c4be4f2bb95bd66bfccb39e1
Publikováno v:
Frontiers in Psychology, Vol 13 (2022)
BackgroundWith the popularity of computers, the internet, and the global spread of COVID-19, more and more attention deficit hyperactivity disorder (ADHD) patients need timely interventions through the internet. At present, there are many online inte
Externí odkaz:
https://doaj.org/article/ea05b38a916f4551b970bb19f3aafdef
Publikováno v:
Frontiers in Psychology, Vol 12 (2022)
Objective: Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by developmentally inappropriate inattention, hyperactivity, and impulsivity. Multiple cognitive training appeared to be more effective than wor
Externí odkaz:
https://doaj.org/article/ccc4a5a5aa4f4733a928f7d50c093282
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9789819913640
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9fb7708d30d6b279d7c2326a8c0da0d1
https://doi.org/10.1007/978-981-99-1365-7_77
https://doi.org/10.1007/978-981-99-1365-7_77
Autor:
null Ning Zhang, null Man Gao, null Jinglong Yu, null Qiang Zhang, null Weiguang Wang, null Congxiao Zhou, null Lingjia Liu, null Ting Sun, null Xing Liao, null Junhong Wang
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ddf604e27207e485b281397a4f7cb682
https://doi.org/10.1002/brb3.2748/v2/response1
https://doi.org/10.1002/brb3.2748/v2/response1
Publikováno v:
Journal of Physics: Conference Series. 2218:012062
Aiming at the low efficiency of wind turbines in service, this paper proposes a statistical method of low efficiency turbines based on wind power curve generated from operating data. According to the data distribution characteristics of the wind-powe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e1e381244af135f48451db6ea4afb82
https://doi.org/10.1088/1742-6596/2218/1/012062
https://doi.org/10.1088/1742-6596/2218/1/012062
Autor:
Andrew Cameron, L. M. Song, Jun Yan, Lei Zhang, Mao Yuan, Hui Qian, Ningyu Tang, Wenbai Zhu, Xuedong Gu, Caihong Sun, Xiang-Wei Shi, M. Huang, Aiying Zhou, Dai Shi, Lichun Zhu, Zhang Xinxin, Hui Li, Jinyuo Song, Zhichen Pan, Haiyan Zhang, Heng-Qian Gan, S. Yang, Pei Wang, Jinghai Sun, Rui Luo, Peng Jiang, Boqin Zhu, Rui Yao, Hongfei Liu, Ming-Lei Guo, Di Li, Xiaoyao Xie, Qiaoli Hao, Shuyun Cao, Li Yang, Jun Han, Shuxin Zhang, Hongfeng Wang, Ran Duan, Jinglong Yu, M. Cruces, Dongjun Yu, X. Z. Zheng, George Hobbs, Hong Wang, Duncan R. Lorimer, Yi Feng, Ming Zhu, Lei Qian, David Champion, Michael Kramer, Laura Spitler, Lin Huang, Yan Zhu, Weiwei Zhu, Cheng-Min Zhang, Wang Qiming, Youling Yue, Bing Zhang, Li Feng, Chenhui Niu, Qi Li, Chengjin Jin, Bo Peng, Jiarui Niu, Yi Wang, Qisheng Li, Gaofeng Pan, Chenchen Miao, Long Gao
We report the discovery of a highly dispersed fast radio burst, FRB~181123, from an analysis of $\sim$1500~hr of drift-scan survey data taken using the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The pulse has three distinct emissio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11d5bb2f3d973c440c3f34cddae9743b
Publikováno v:
Journal of Physics: Conference Series. 2179:012041
This paper adopts deep learning self-encoding algorithm, using JAVA, C++ and python language mixed programming computing technology to realize wind turbine parameter monitoring and early warning and software system design and development. This paper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5e390c0add4b7ee6f3ea85ea4d12027
https://doi.org/10.1088/1742-6596/2179/1/012041
https://doi.org/10.1088/1742-6596/2179/1/012041