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The following articles are merged in Scholar. Their mixed citations are counted just for the primary short article.
This "Cited by" rely consists of citations to the subsequent articles or blog posts in Scholar. The ones marked * can be distinct from the short article within the profile.
下面的文章将在学术搜索中合并。它们的合并引用次数只会计入第一篇文章。
The worldwide economic climate is dealing with by far the most difficult period of local weather improve over and above what is apparent in the pre-industrial age. While Africa's share of global greenhouse gasoline (GHG) is minimal, the…
The next article content are merged in Scholar. Their put together citations are counted only for the 1st post.
Towards attack-resistant route mutation for VANETs: an on the web and adaptive multiagent reinforcement Studying tactic
A not-for-revenue Group, IEEE is the planet's most significant technical Qualified organization committed to advancing technology for the advantage of humanity.
A QoE-pushed multicast technique with section routing—A novel multimedia Jiahao Shen KCL traffic engineering paradigm
The current period is facing a Problem concerning engaging the essentialities of Strength resources to attain economic prosperity resulting from the following environmental problems. For that reason, sectors…
An optimized quantum minimum browsing algorithm with guaranteed-achievement likelihood and its experiment simulation with Cirq
Monitoring environmental sustainability pathways in Africa: Do all-natural source dependence, renewable Electricity, and technological innovations amplify or reduce the pollution noises?
Scanning radar ahead-on the lookout superresolution imaging according to the Weibull distribution for any sea-floor concentrate on
This "Cited by" count involves citations to the subsequent articles in Scholar. The ones marked * could possibly be distinctive in the article inside the profile.
此“引用引文的出版物数量”计数包含了对学术搜索中以下文章的引用次数。带有*标记的引文可能与个人学术档案中的文章有所区别。
Tips on how to disturb network reconnaissance: a transferring focus on protection solution according to deep reinforcement Discovering