Many researchers used different methods in their investigations to enhance the heat transfer coefficient, one of these methods is using porous medium. Heat transfer process inside closed and open cavities filled with a fluid-saturated porous media has a considerable importance in different engineering applications, such as compact heat exchangers, nuclear reactors and solar collectors. So, the present paper comprises a review on natural, forced, and combined convection heat transfer inside a porous cavity with and without driven lid. Most of the researchers on this specific subject studied the effect of many parameters on the heat transfer and fluid field inside a porous cavity, like the angle of inclination, the presence of vibration, magnetic fields, and heat generation. They used different thermal and hydrodynamic boundary conditions, different geometries of cavity, and different saturated-fluids. Results manifested that the fluid and thermal characteristics enhance greatly as porosity increases at a high value of Darcy number. Also, vibrational effects are a dominant factor in the heat transfer process only at high Darcy and Reynolds numbers.
Arabic text classification is a challenging task because of the complex morphology of the language, the existence of different writing forms and a multitude of dialects, which can result in sparser common text representations. While transformer models such as AraBERT have obtained superior results on many Arabic NLP tasks, their high computational requirements make them difficult to deploy in environments with limited hardware resources. In some cases this can also make the model less practical for researchers working with basic computer systems. This study focuses on a more practical issue: how much accuracy a simple classifier may lose when the amount of required computation is reduced. We use a combined TF-IDF representation based on bo
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