A two-dimensional computational study had been performed regarding aerodynamic forces and pressures affecting a cambered inverted airfoil, CLARK-Y smoothed with ground effects by solving the Reynolds-averaged Navier-Stokes equations, using the commercial software COMSOL Multiphysics 5.0 solver. Turbulence effects are modeled using the Menter shear-stress transport (SST) two-equation model. The negative lift (down-force), drag forces and pressures surface were predicted through the simulation of wings over inverted wings in different parameters namely; varying incidences i.e. angles of attack of the airfoils, varying the ride hide from the ground covering various force regions, two-dimensional cross-section of the inverted front wings to be

Nanostructured Al2O3has been applied as a protective coating against corrosion of the carbon steel (C.S) in seawater environment (3.5% NaCl) at temperatures range (298-328)K. Aluminananoparticles were deposited on carbon steel substrates by cathodic electrophoretic deposition (EPD) with ethanol as suspension medium and poly(acrylic acid) (PAA) as polymeric charging agent. Meanwhile, thesurface morphology was examined using Atomic-force microscopy (AFM). The cross-section AFM showed that the particles sizes for the Al2O3 NPs is around 60-80 nm. The anticorrosion behaviour of coated C.S was investigated in 3.5% NaCl at temperature range 298-328 K by potentiodynamic polarization measurements. Results show that using PAA in suspension coat incr

The adsorption behavior of congo red dye from its aqueous solutions was investigated onto natural and modified bauxite clays. Both bauxite and modified bauxite are primarily characterized by using, FTIR, SEM, AFM, and XRD. Several variables are studied as a function of adsorption including contact time, adsorbent weight, pH, ionic strength, particle size and temperature under batch adsorption technique. The absorbance of the solution before and after adsorption was measured spectrophotometrically. The equilibrium data fit with Langmuir model of adsorption and the linear regression coefficient R2 is found to be 0.9832 and 0.9630 for natural and modified bauxite respectively at 37.5°C which elucidate the best fitting isotherm model. The gene

The adsorption of Cr (VI) from aqueous solution by spent tea leaves (STL) was studied at different initial Cr (VI) concentrations, adsorbent dose, pH and contact time under batch isotherm experiments The adsorption experiments were carried out at 30°C and the effects of the four parameters on chromium uptake to establish a mathematical model description percentage removal of Cr (VI). The
analysis results showed that the experimental data were adequately fitted to second order polynomial model with correlation coefficients for this model was (R2 = 0.9891). The optimum operating parameters of initial Cr (VI) concentrations, adsorbent dose, pH and contact time were 50 mg/l, 0.7625 g, 3 and 100 min, respectively. At these conditions, th

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col