Given the rise of artificial intelligence,big data analytics has emerged as an important tool for processing and assimilating the enormous volume of data available on social media.It is of great theoretical and practi...Given the rise of artificial intelligence,big data analytics has emerged as an important tool for processing and assimilating the enormous volume of data available on social media.It is of great theoretical and practical significance to explore the public opinion diffusion process and characteristics,and users’emotions of mega sports events based on big data statistics in the social media environment.This paper takes the Jakarta Asian Games,Russian World Cup and PyeongChang Winter Olympics held in 2018 as cases,uses text mining and social network analysis methods to analyze the dissemination process of social media users’data,presents the semantic words disseminated in sports events through high-frequency word cloud diagrams,and summarizes the general rules of public opinion dissemination.The results show that the more users’participation,the greater diffusion volume,and the diffusion process shows fast increasing,short duration,scattered topics,diversified contents,and strong guidance and weak continuity of attention.The high-frequency words,except for the names of the events,such as“cheer”,“win the game”and“must win”,have obvious concentration of emotional words.展开更多
The founding conference of the Big Data Statistics Branch (BDSB) of the Chinese Association forApplied Statistics (CAAS) was held on 8 December 2018, at East China Normal University (ECNU),Shanghai, China. More than 6...The founding conference of the Big Data Statistics Branch (BDSB) of the Chinese Association forApplied Statistics (CAAS) was held on 8 December 2018, at East China Normal University (ECNU),Shanghai, China. More than 600 experts and scholars attended the conference. Professor ZhangRiquan was elected as the chairman of the first Board of Directors of the BDSB. Fang Xiangzhong,Chairman of the CAAS, delivered a speech. Professor Wang Zhaojun and Dr Liu Zhong delivered,respectively, keynote reports on the development of Big Data researches and practices, at theconference. The BDSB will be dedicated to building a high-level big data statistics exchange platform for experts and scholars in universities, governments, enterprises, and other fields to betterserve the society and serve the country’s major strategies.展开更多
As an innovative development of single-atom catalysts(SACs),single-cluster catalysts(SCCs)such as dualatom catalysts have attracted considerable interest due to their excellent performance in catalysis.As one of the m...As an innovative development of single-atom catalysts(SACs),single-cluster catalysts(SCCs)such as dualatom catalysts have attracted considerable interest due to their excellent performance in catalysis.As one of the most powerful and visualizable tools,scanning transmission electron microscopy(STEM)has been widely applied in the characterization of SCCs.Herein,the nitrogen-doped carbonsupported FeFe and CoFe,two representative examples of homonuclear and heteronuclear SCCs,are characterized by STEM.Furthermore,an image processing program is developed to analyze the STEM images and to obtain the locations of atoms,as well as the projected distances between atoms in possible dual-atom pairs.The dimer distances of both CoFe and FeFe catalysts exhibit a trimodal distribution,which can correspond to the energy-favorable atomic structures of the theoretical simulations.Our work offers an avenue for directly revealing the possible atomic configurations of dual-atom sites in SCCs via big data statistics of STEM images and strong theoretical simulations.展开更多
基金Supported by National Natural Science Foundation of China(72302230)Shandong Provincial Natural Science Foundation Youth Project(ZR2023QG068)。
文摘Given the rise of artificial intelligence,big data analytics has emerged as an important tool for processing and assimilating the enormous volume of data available on social media.It is of great theoretical and practical significance to explore the public opinion diffusion process and characteristics,and users’emotions of mega sports events based on big data statistics in the social media environment.This paper takes the Jakarta Asian Games,Russian World Cup and PyeongChang Winter Olympics held in 2018 as cases,uses text mining and social network analysis methods to analyze the dissemination process of social media users’data,presents the semantic words disseminated in sports events through high-frequency word cloud diagrams,and summarizes the general rules of public opinion dissemination.The results show that the more users’participation,the greater diffusion volume,and the diffusion process shows fast increasing,short duration,scattered topics,diversified contents,and strong guidance and weak continuity of attention.The high-frequency words,except for the names of the events,such as“cheer”,“win the game”and“must win”,have obvious concentration of emotional words.
文摘The founding conference of the Big Data Statistics Branch (BDSB) of the Chinese Association forApplied Statistics (CAAS) was held on 8 December 2018, at East China Normal University (ECNU),Shanghai, China. More than 600 experts and scholars attended the conference. Professor ZhangRiquan was elected as the chairman of the first Board of Directors of the BDSB. Fang Xiangzhong,Chairman of the CAAS, delivered a speech. Professor Wang Zhaojun and Dr Liu Zhong delivered,respectively, keynote reports on the development of Big Data researches and practices, at theconference. The BDSB will be dedicated to building a high-level big data statistics exchange platform for experts and scholars in universities, governments, enterprises, and other fields to betterserve the society and serve the country’s major strategies.
基金supported by the National Key Research and Development Project(2022YFA1503900,2022YFA1503000,and 2022YFA1203400)Shenzhen Fundamental Research Funding(JCYJ20210324115809026,JCYJ20220818100212027,and JCYJ20200109141216566)+7 种基金Shenzhen Science and Technology Program(KQTD20190929173815000)Guangdong scientific program with contract no.2019QN01L057Guangdong Innovative and Entrepreneurial Research Team Program(2019ZT08C044)to Gu Msupported by the National Natural Science Foundation of China(22033005)to Li Jpartially sponsored by Guangdong Provincial Key Laboratory of Catalysis(2020B121201002).support from Presidential fund and Development and Reform Commission of Shenzhen Municipalitysupported by the Center for Computational Science and Engineering at SUSTechthe CHEM high-performance supercomputer cluster(CHEMHPC)located at the Department of Chemistry,SUSTech。
文摘As an innovative development of single-atom catalysts(SACs),single-cluster catalysts(SCCs)such as dualatom catalysts have attracted considerable interest due to their excellent performance in catalysis.As one of the most powerful and visualizable tools,scanning transmission electron microscopy(STEM)has been widely applied in the characterization of SCCs.Herein,the nitrogen-doped carbonsupported FeFe and CoFe,two representative examples of homonuclear and heteronuclear SCCs,are characterized by STEM.Furthermore,an image processing program is developed to analyze the STEM images and to obtain the locations of atoms,as well as the projected distances between atoms in possible dual-atom pairs.The dimer distances of both CoFe and FeFe catalysts exhibit a trimodal distribution,which can correspond to the energy-favorable atomic structures of the theoretical simulations.Our work offers an avenue for directly revealing the possible atomic configurations of dual-atom sites in SCCs via big data statistics of STEM images and strong theoretical simulations.
