The electrochemical behavior of Al-17%Si alloy is investigated in 3.5wt% NaCl solution. Many alloys with addition of the different wt% magnesium metal of  1wt%, 2%, 3wt% ,4.5wt% ,and 9wt% were prepared by gravity die casting . The microstructures of prepared alloys were examined by optical and SEM microscopes. Corrosion behavior was investigated by using potentiostat instrument under static potentials test and corrosion current was recorded to determine corrosion resistance of all prepared samples. It was found that the addition of Mg metal improves the corrosion resistance of Al-17%Si alloy in 3.5%NaCl solution. The alloy containing 1%Mg shows less corrosion rate than the others while the alloys containing 4.5%Mg, 9%Mg content have

 Additive aluminum powder to the polystyrene to prepare the composites Polystyrene– Aluminum.The samples were prepared by using mechanical  compressed method at low pressure and a temperature 120°C.         Measurements  of absorbance and reflectance spectra were carried out by UV-Visible  spectrophotometer , the effect of additive aluminum  on the optical band  gap Eop and  optical constants ( refractive index n, extinction coefficient k ,dielectric constant ε and optical conductivity σop)  were studied for the prepared composites .         Results showed a decrease in the Eop with increasing  perc

The main aim of image compression is to reduce the its size to be able for transforming and storage, therefore many methods appeared to compress the image, one of these methods is "Multilayer Perceptron ". Multilayer Perceptron (MLP) method which is artificial neural network based on the Back-Propagation algorithm for compressing the image. In case this algorithm depends upon the number of neurons in the hidden layer only the above mentioned will not be quite enough to reach the desired results, then we have to take into consideration the standards which the compression process depend on to get the best results. We have trained a group of TIFF images with the size of (256*256)  in our research, compressed them by using MLP for each

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

    The discharge of dyes into the water is a significant source of pollution, which is especially concerning given that textile mills are the primary contributor. Nanomaterial-based solutions to this issue have required extensive research and investigation due to their complex nature. In this research, novel nanoparticle were successfully synthesized using the leaves of the Eruca sativa plant. The nano was analyzed using scanning and transmission electron microscopy (SEM and TEM) measurements, and their crystal structure was determined using the X-ray diffraction technique (XRD). The incorporation of NPs resulted in an increase in the uptake of the Cibacron red dye. At a contact time of 30 minutes, observed a faster adsor

The studies on unbonded post-tensioned concrete members strengthened with Carbon Fiber Reinforced Polymers (CFRPs) are limited and the effect of strengthening on the strain of unbonded pre-stressed steel is not well characterized. Estimating the flexural capacity of unbound post-tensioned members using the design methodology specified in the design guidelines for FRP strengthening techniques of bonded post-tensioned members does not provide a reliable evaluation. This study investigates the behavior of unbonded post-tensioned concrete members with partial strand damage (14.3% and 28.6% damage) and strengthened with CFRP laminates using a near-surface mounted technique with and without U-wrap anchorages. The experimental results show

Background: Separation and deboning of artificial teeth from denture bases present a major clinical and labortory problem which affect both the patient and the dentist. The optimal bond strength of artificial teeth with denture base reinforced with nanofillers and flexible denture bases and the effect of thermo cycling should be evaluated. This study was conducted to evaluate and compare the shear bond strength of artificial teeth (acrylic and porcelain) with denture bases reinforced by 5% Zirconium oxide nanofillers and flexible bases under the effect of different surface treatments and thermo cycling and comparing the results with conventional water bath cured denture bases. Material and methods: Two types of artificial teeth; acrylic and

Background: White spot lesion is the first visible sign of dental caries that is characterized by demineralized lesion underneath an intact surface. Several studies demonstrated that they could be treated using noninvasive techniques like the use of fluoride or casein phospho-peptide and amorphous calcium phosphate. Improvement in aesthetic outcomes by covering the demineralized enamel is one of the advantages of the use of resin infiltration and opal-ustre microabrasion, which are two new techniques that had been used for treatment of white spot lesion. The purpose of this study was to evaluate the impact of resin infiltration and microabrasion in the microhardness of the artificial white spot lesions at various depths. Material and method

    Artificial Neural Network (ANN) is widely used in many complex applications. Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.  The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model  and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Je