5 Simple Techniques For Jiahao Shen KCL

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The next content are merged in Scholar. Their blended citations are counted only for the main report.

This "Cited by" count includes citations to the subsequent content articles in Scholar. Those marked * can be distinct from the article from 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 financial system is encountering the most demanding era of local climate modify beyond precisely what is obvious while in the pre-industrial age. Even though Africa's share of worldwide greenhouse gas (GHG) is small, the…

The following articles are merged in Scholar. Their merged citations are counted only for the 1st write-up.

Towards attack-resistant route mutation for VANETs: an on the web and adaptive Jiahao Shen Islam multiagent reinforcement Studying strategy

A not-for-revenue Group, IEEE is the whole world's most significant technical Qualified organization committed to advancing technology for the advantage of humanity.

A QoE-driven multicast approach with phase routing—A novel multimedia site visitors engineering paradigm

The existing era is experiencing a Predicament regarding engaging the essentialities of Electricity sources to achieve financial prosperity on account of the ensuing environmental troubles. As a result, sectors…

An optimized quantum minimum amount exploring algorithm with positive-results probability and its experiment simulation with Cirq

Tracking environmental sustainability pathways in Africa: Do purely natural resource dependence, renewable Strength, and technological improvements amplify or reduce the pollution noises?

Scanning radar ahead-looking superresolution imaging depending on the Weibull distribution for your sea-area goal

This "Cited by" rely includes citations to the following content in Scholar. Those marked * could be unique from the write-up from 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 shifting focus on protection technique dependant on deep reinforcement Discovering

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