Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned above, which is a very

Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO₄), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned

Theoretical and experimental investigations of free convection through a cubic cavity with sinusoidal heat flux at bottom wall, the top wall is exposed to an outside ambient while the other walls are adiabatic saturated in porous medium had been approved in the present work. The range of Rayleigh number was and Darcy number values were . The theoretical part involved a numerical solution while the experimental part included a set of tests carried out to study the free convection heat transfer in a porous media (glass beads) for sinusoidal heat flux boundary condition. The investigation enclosed values of Rayleigh number (5845.6, 8801, 9456, 15034, 19188 and 22148) and angles of inclinations (0, 15, 30, 45 and 60 degree). The numerical an

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al