Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Yunpeng Chai"'
Publikováno v:
大数据, Vol 9, Pp 3-15 (2023)
With the exponential growth of data and the company's cross-domain disaster recovery requirements, companies increasingly need to manage data across spatial domains.Cross-domain data management requires a distributed consensus algorithm to make the d
Externí odkaz:
https://doaj.org/article/1f6b4a0408ec40a8be1c515e9d484a7b
Publikováno v:
Crystals, Vol 14, Iss 5, p 424 (2024)
In this study, hot compression experiments were conducted on cast TC21 titanium alloy using a Gleeble-1500D thermal simulation compression tester, and the hot-compressed specimens were heat-treated. The data obtained after analyzing the thermal compr
Externí odkaz:
https://doaj.org/article/2d3236f7679a4f7db68e66249d771ade
Autor:
Hong MEI, Xiaoyong DU, Hai JIN, Xueqi CHENG, Yunpeng CHAI, Xuanhua SHI, Xiaolong JIN, Yasha WANG, Chi LIU
Publikováno v:
大数据, Vol 9, Pp 1-20 (2023)
Major countries in the world attach great importance to the development of big data technology.China also puts big data as a national strategy, of great significance to develop in the long run.Big data technologies include data collection, transmissi
Externí odkaz:
https://doaj.org/article/89229e8048764b6085300339d23af4bf
Publikováno v:
Data Science and Engineering, Vol 5, Iss 1, Pp 65-79 (2019)
Abstract Intra-query fault tolerance has increasingly been a concern for online analytical processing, as more and more enterprises migrate data analytical systems from mainframes to commodity computers. Most massive parallel processing (MPP) databas
Externí odkaz:
https://doaj.org/article/4d92ef30b3dc439d99fb2a58e5aad84a
Publikováno v:
Data Science and Engineering, Vol 4, Iss 1, Pp 24-43 (2019)
Abstract With the popularity of knowledge graphs growing rapidly, large amounts of RDF graphs have been released, which raises the need for addressing the challenge of distributed subgraph matching queries. In this paper, we propose an efficient dist
Externí odkaz:
https://doaj.org/article/9364b1f7b65e4d44a1fe21678567998e
Publikováno v:
大数据, Vol 4, p 2018057 (2018)
To adapt to data science and big data talent cultivation requirements of the new era,School of Information,Renmin University of China has reformed its course system in recent years.Three course groups as problem solving,computer system,and data scien
Externí odkaz:
https://doaj.org/article/18d2291071d44d5dbd69369776b93c76
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. :1-14
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e350b66b40509e4b6f3017830b936086
https://doi.org/10.1109/tkde.2023.3235399
https://doi.org/10.1109/tkde.2023.3235399
Autor:
Qiang Yin, Jianhua Wang, Sheng Du, Jianquan Leng, Jintao Li, Yinhao Hong, Feng Zhang, Yunpeng Chai, Xiao Zhang, Xiaonan Zhao, Mengyu Li, Song Xiao, Wei Lu
Publikováno v:
Data Science and Engineering. 7:328-338
With the diverse applications to industry and domain-specific context, multi-source information extraction on semi-structured and unstructured data, as well as across data models, is becoming more common. However, multi-model information extraction o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::418a709786640ba8a425a670b6827d6c
https://doi.org/10.1007/s41019-022-00196-2
https://doi.org/10.1007/s41019-022-00196-2
Publikováno v:
ACM Transactions on Storage.
To satisfy the enormous storage capacities required for big data, data centers have been adopting high-density shingled magnetic recording (SMR) disks. However, the weak fine-grained random write performance of SMR disks caused by their inherent writ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::63f79969f0e4db1d5940dfe750d602ab
https://doi.org/10.1145/3588442
https://doi.org/10.1145/3588442
Publikováno v:
Communications in Computer and Information Science ISBN: 9789819913534
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1df191a8f732e5fd562818be25f4750
https://doi.org/10.1007/978-981-99-1354-1_3
https://doi.org/10.1007/978-981-99-1354-1_3
