This study includes using green or biosynthesis-friendly technology, which is effective in terms of low cost and low time and energy to prepare V₂O₅NPs nanoparticles from vanadium sulfate VSO₄.H₂O using aqueous extract of Punica Granatum at a concentration of 0.1M and with a basic medium PH= 8-12. The V₂O₅NPs nanoparticles were diagnosed using several techniques, such as FT-IR, UV-visible with energy gap Eg = 3.734eV, and the X-Ray diffraction XRD was calculated using the Debye Scherrer equation. It was discovered to be 34.39nm, Scanning Electron Microscope (SEM), Transmission Electron Microscopy TEM. The size, structure, and composition of synthetic V₂O₅

The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

Abstract

In the field of construction materials the glass reinforced mortar and Styrene Butadiene mortar are modern composite materials. This study experimentally investigated the effect of addition of randomly dispersed glass fibers and layered glass fibers on density and compressive strength of mortar with and without the presence of Styrene Butadiene Rubber (SBR). Mixtures of 1:2 cement/sand ratio and 0.5 water/cement ratio were prepared for making mortar. The glass fibers were added by two manners, layers and random with weight percentages of (0.54, 0.76, 1.1 and 1.42). The specimens were divided into two series: glass-fiber reinforced mortar without SBR and glass-fiber reinforced mortar with 7% SBR of mixture water. All s

Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model  in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling  the Symmetric gray scale texture image and estimating by using

Abstract

The Classical Normal Linear Regression Model Based on Several hypotheses, one of them is Heteroscedasticity as it is known that the wing of least squares method (OLS), under the existence of these two problems make the estimators, lose their desirable properties, in addition the statistical inference becomes unaccepted table. According that we put tow alternative,  the first one is  (Generalized Least Square) Which is denoted by (GLS), and the second alternative is to (Robust covariance matrix estimation) the estimated parameters method(OLS), and that the way (GLS) method neat and certified, if the capabilities (Efficient) and the statistical inference Thread on the basis of an acceptable

In this work we study the influence of the laser pulse energy and ablation time on the aluminum nanoparticles productivity during nanosecond laser ablation of bulk aluminum immersed in liquid.
Aluminum nanoparticles were synthesized by pulsed laser ablation of Al targets in ethanol for 3-8 minutes using the 1064 nm wavelength of a Nd:YAG laser with energies of 300-500 mJ per pulse.The laser energy was varied between 300 and 500 mJ/pulse, whereas the ablation time was set to 5 minutes. UV-Visible absorption spectra was used for the characterization and comparison of products.

Design of experiments (DOE) was made by Minitab software for the study of three factors used in the precipitation process of the Sodium Aluminate solution prepared from digestion of α-Al₂O₃  to determine the optimum conditions to a produce Boehmite which is used in production of ɤ-Al₂O₃ during drying and calcination processes, the factors are; the temperature of the sodium aluminate solution, concentration of HCl acid added for the precipitation and the pH of the solution at which the precipitation was ended. The design of the experiments leads to 18 experiments.

   The results show that the optimum conditions for the precipitation of the sodium aluminate solution which

In this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate k_p (10^-12g².cm^-4.s^-1) in Incoloy 800H at 900^oC . ANN was used for estimating the predicted values of hot corrosion rate k_p (10^-12g².cm^-4.s^-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic alg