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MUHAMMAD WASEEM on Muck Rack

MUHAMMAD WASEEM

Saudi Arabia
As seen in: Nature, Reuters, arXiv, Taylor & Francis Online, U.S. News and World Report, The Japan Times, Yahoo Sports, Yahoo Sports Canada, The Star (Malaysia), Geo News English and
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Articles

Finite element method based algorithm with intelligent computing for studying MHD heat and mass transfer in nanofluid flow over 2-D boundary layers in a porous medium

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By Farooq Shah, MUHAMMAD WASEEM, Tayyab Zameer
| Taylor & Francis Online
ABSTRACT Inspired by practical applications, this study investigates MHD heat and mass transfer in nanofluid flow over a two-dimensional boundary layer in a porous medium, considering radiation, viscous dissipation, Brownian motion, and thermophoresis effects. Suitable transformations reduce the governing nonlinear partial differential equations to ordinary differential equations (ODEs). The resulting boundary-layer equations are solved using the Finite Element Method (FEM).
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Computer Science > Software Engineering

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By MUHAMMAD WASEEM, Toufique Hasan, Jussi Rasku
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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Integrating machine learning and artificial neural networks for dynamic analysis of a fractional order smoking-induced lungs cancer model

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By Muhammad Talha, MUHAMMAD WASEEM, Fikadu Tesgera Tolasa
| Nature Verified
Abstract This study introduces a fractional-order framework for modeling the progression of smoking behavior and its relationship to cancer onset. The population is stratified into seven compartments: susceptible, exposed, chronic carriers, active smokers without intervention, smokers under treatment, cancer-diagnosed and recovered individuals.
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