About Jiahao Shen Islam

The existing era is experiencing a dilemma referring to partaking the essentialities of Electricity sources to achieve economic prosperity because of the following environmental troubles. Therefore, sectors…

The worldwide financial system is going through probably the most challenging period of weather adjust further than exactly what is apparent within the pre-industrial age. Although Africa's share of worldwide greenhouse fuel (GHG) is negligible, the…

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A not-for-gain Firm, IEEE is the world's greatest technological Specialist Business devoted to advancing technological innovation for the good thing about humanity.

A not-for-earnings organization, IEEE is the whole world's premier technical Experienced Firm dedicated to advancing technological innovation for the advantage of humanity.

A QoE-driven multicast method with section routing—A novel multimedia traffic engineering paradigm

Tracking environmental sustainability pathways in Africa: Do pure source dependence, renewable energy, and technological innovations amplify or decrease the air pollution noises?

Towards assault-resistant route mutation for VANETs: an on the web and adaptive multiagent reinforcement Finding out approach

An Jiahao Shen optimized quantum bare minimum hunting algorithm with sure-achievement likelihood and its experiment simulation with Cirq

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Scanning radar forward-hunting superresolution imaging based upon the Weibull distribution for your sea-surface area focus on

To handle scanning radar ahead-on the lookout sea imaging, this paper proposed a brilliant-resolution process determined by Weibull distribution. The proposed system inside our work introduced the generalized Gaussian…

The following articles are merged in Scholar. Their combined citations are counted just for the main posting.

This "Cited by" count features citations to the subsequent article content in Scholar. Those marked * may very well be distinctive within the report while in the profile.

The best way to disturb community reconnaissance: a shifting goal defense approach dependant on deep reinforcement learning

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