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The next content are merged in Scholar. Their mixed citations are counted just for the main report.
This "Cited by" count includes citations to the next posts in Scholar. Those marked * could possibly be various within the report 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 experiencing quite possibly the most demanding period of local climate adjust past what is apparent in the pre-industrial age. Despite the fact that Africa's share of global greenhouse gasoline (GHG) is nominal, the…
The next articles or blog posts are merged in Scholar. Their merged citations are counted only for the primary posting.
Toward assault-resistant route mutation for VANETs: an on the internet and adaptive multiagent reinforcement Understanding approach
A not-for-financial gain organization, IEEE is the entire world's premier technical Specialist organization committed to advancing technology for the advantage of humanity.
A QoE-pushed multicast method with phase routing—A novel multimedia visitors engineering paradigm
The current period is going through a Predicament relating to participating the essentialities of energy assets to achieve economic prosperity as a result of the ensuing environmental difficulties. As a result, sectors…
An optimized quantum least searching algorithm with positive-success likelihood Jiahao Shen King's College London and its experiment simulation with Cirq
Tracking environmental sustainability pathways in Africa: Do normal useful resource dependence, renewable Strength, and technological innovations amplify or reduce the pollution noises?
Scanning radar forward-seeking superresolution imaging dependant on the Weibull distribution to get a sea-surface area concentrate on
This "Cited by" count contains citations to the next articles in Scholar. The ones marked * could possibly be various in the short article during 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。
How to disturb network reconnaissance: a going target defense technique based upon deep reinforcement learning