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Nazrul Azlan Abdul Samat, Norfifah Bachok and Norihan Md Arifin
The present study aims to offer new numerical solutions and optimisation strategies for the fluid flow and heat transfer behaviour at a stagnation point through a nonlinear sheet that is expanding or contracting in water-based hybrid nanofluids. Most hyb...
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Wenbo Peng and Jinjie Huang
Current object detection methods typically focus on addressing the distribution discrepancies between source and target domains. However, solely concentrating on this aspect may lead to overlooking the inherent limitations of the samples themselves. This...
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Changhao Wu, Siyang He, Zengshan Yin and Chongbin Guo
Large-scale low Earth orbit (LEO) remote satellite constellations have become a brand new, massive source of space data. Federated learning (FL) is considered a promising distributed machine learning technology that can communicate optimally using these ...
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Jose Luis Vieira Sobrinho, Flavio Henrique Teles Vieira and Alisson Assis Cardoso
The high dimensionality of real-life datasets is one of the biggest challenges in the machine learning field. Due to the increased need for computational resources, the higher the dimension of the input data is, the more difficult the learning task will ...
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Konstantin Volkov
The opportunities provided by new information technologies, object-oriented programming tools, and modern operating systems for solving boundary value problems in CFD described by partial differential equations are discussed. An approach to organizing ve...
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