Zobrazeno 1 - 10
of 174
pro vyhledávání: '"Mohammad Umair"'
Publikováno v:
Adsorption Science & Technology, Vol 42 (2024)
A Scottish wood biochar sample was investigated for water remediation against persistent organic pollutants as a potential renewable material for adsorption processes. Textural characterisation gave a high surface area (588 m 2 /g) and a mix of micro
Externí odkaz:
https://doaj.org/article/925aa713000a4c7c9bb704dd834267a2
Publikováno v:
Emerging Science Journal, Vol 4, Iss 0, Pp 1-17 (2020)
In modern era, a wide range of smart industries is being focus on automation-based applications. Various technologies are rapidly implementing in Industrial Internet of Things (IIoT) for manufacturing sectors that helping to achieve advanced schedule
Externí odkaz:
https://doaj.org/article/1157d94e1d2648b9ac0d386c364874bb
This paper extends the paradigm of "mobile edge learning (MEL)" by designing an optimal task allocation scheme for training a machine learning model in an asynchronous manner across mutiple edge nodes or learners connected via a resource-constrained
Externí odkaz:
http://arxiv.org/abs/2012.00143
Machine learning (ML) and artificial intelligence (AI) have recently made a significant impact on improving the operations of wireless networks and establishing intelligence at the edge. In return, rare efforts were made to explore how adapting, opti
Externí odkaz:
http://arxiv.org/abs/2006.07453
This paper proposes to maximize the accuracy of a distributed machine learning (ML) model trained on learners connected via the resource-constrained wireless edge. We jointly optimize the number of local/global updates and the task size allocation to
Externí odkaz:
http://arxiv.org/abs/2006.07402
Autor:
Mohammad, Umair, Sorour, Sameh
This paper proposes a scheme to efficiently execute distributed learning tasks in an asynchronous manner while minimizing the gradient staleness on wireless edge nodes with heterogeneous computing and communication capacities. The approach considered
Externí odkaz:
http://arxiv.org/abs/1905.01656
Akademický článek
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Autor:
Mohammad, Umair, Sorour, Sameh
This paper aims to establish a new optimization paradigm for implementing realistic distributed learning algorithms, with performance guarantees, on wireless edge nodes with heterogeneous computing and communication capacities. We will refer to this
Externí odkaz:
http://arxiv.org/abs/1811.03748
Autor:
Jamal, Mohammad Umair1 (AUTHOR) umair.jamal@strath.ac.uk, Fletcher, Ashleigh1 (AUTHOR), Baby, Alan1 (AUTHOR), Maso, Isaac1 (AUTHOR), Šiller, Lidija2 (AUTHOR)
Publikováno v:
Adsorption Science & Technology. Jan-Dec2024, Vol. 42, p1-25. 25p.
Publikováno v:
In Injury October 2022 53(10):3361-3364