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Titlebook: Computational Data and Social Networks; 9th International Co Sriram Chellappan,Kim-Kwang Raymond Choo,NhatHai P Conference proceedings 2020

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發(fā)表于 2025-3-28 16:57:40 | 只看該作者
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發(fā)表于 2025-3-28 20:52:17 | 只看該作者
Diastereoselectivity in Organic Reactions,on to compare the performance of our flexible interval IJ with the existing IJ scheme. The results show that our strategy is nearly saving 10% energy and guarantees the same security level as IJ can provide.
43#
發(fā)表于 2025-3-29 02:11:15 | 只看該作者
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發(fā)表于 2025-3-29 03:58:14 | 只看該作者
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發(fā)表于 2025-3-29 09:57:23 | 只看該作者
Network Based Comparison of Indian Railways and Airwayshe need for such type of network arises as the order of both networks are different. This newly formed network can be used in identifying new routes and adding more flights on some of the popular routes in India.
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發(fā)表于 2025-3-29 13:16:57 | 只看該作者
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發(fā)表于 2025-3-29 17:13:38 | 只看該作者
0302-9743 tional Methods for Social Good Applications; NLP and Affective Computing; Privacy and Security; Blockchain; Fact-Checking, Fake News and Malware Detection in Online Social Networks; and Information Spread in Social and Data Networks..978-3-030-66045-1978-3-030-66046-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
48#
發(fā)表于 2025-3-29 21:27:55 | 只看該作者
Conference proceedings 2020llas, TX, USA, in December 2020...The 20 full papers were carefully reviewed and selected from 83 submissions. Additionally the book includes 22 special track papers and 3 extended abstracts. The selected papers are devoted to topics such as Combinatorial Optimization and Learning; Computational Met
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發(fā)表于 2025-3-30 01:07:55 | 只看該作者
0302-9743 held in Dallas, TX, USA, in December 2020...The 20 full papers were carefully reviewed and selected from 83 submissions. Additionally the book includes 22 special track papers and 3 extended abstracts. The selected papers are devoted to topics such as Combinatorial Optimization and Learning; Computa
50#
發(fā)表于 2025-3-30 06:43:28 | 只看該作者
https://doi.org/10.1007/978-3-642-48316-5e case with original data were compared on 10 classification tasks. C5.0 acted as the classifiers to access the efficiency of these algorithms. As revealed from the results, the FMF shortened the processing time at least twelve times by three baselines, and it achieved the highest accuracy in most cases.
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