The search included a comparison between two etchands for etch CR-39 nuclear track detector, by the calculation of bulk etch rate (Vb) which is one of the track etching parameters, by two measuring methods (thichness and change mass). The first type, is the solution prepared  from solving NaOH in Ethanol (NaOH/Ethanol) by varied normalities  under temperature(55ËšC)and etching time (30 min) then comparated with the second type the solution prepared from solving NaOH in water (NaOH/Water) by varied normalities with (70ËšC) and etching time (60 min) . All detectors were irradiated with (5.48 Mev) α-Particles from an 241Am source in during (10 min). The results that Vb would increase with the increase of

The degradation of Toluidine Blue dye in aqueous solution under UV irradiation is investigated by using photo-Fenton oxidation (UV/H2O2/Fe+). The effect of initial dye concentration, initial ferrous ion concentration, pH, initial hydrogen peroxide dosage, and irradiation time are studied. It is found put that the removal rate increases as the initial concentration of H2O2 and ferrous ion increase to optimum value ,where in we get more than 99% removal efficiency of dye at pH = 4 when the [H2O2] = 500mg / L, [Fe + 2 = 150mg / L]. Complete degradation was achieved in the relatively short time of 75 minutes. Faster decolonization is achieved at low pH, with the optimal value at pH 4 .The concentrations of degradation dye are detected by spectr

Double-layer micro-perforated panels (MPPs) have been studied extensively as sound absorption systems to increase the absorption performance of single-layer MPPs. However, existing proposed models indicate that there is still room for improvement regarding the frequency bands of absorption for the double-layer MPP. This study presents a double-layer MPP formed with two single MPPs with inhomogeneous perforation backed by multiple cavities of varying depths. The theoretical formulation is developed using the electrical equivalent circuit method to calculate the absorption coefficient under a normal incident sound. The simulation results show that the proposed model can produce absorption coefficient with wider absorption bandwidth compared w

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

In this paper, Bayes estimators of Poisson distribution have been derived by using two loss functions: the squared error loss function and the proposed exponential loss function in this study, based on different priors classified as the two different informative prior distributions represented by erlang and inverse levy prior distributions and non-informative prior for the shape parameter of Poisson distribution. The maximum likelihood estimator (MLE) of the Poisson distribution has also been derived. A simulation study has been fulfilled to compare the accuracy of the Bayes estimates with the corresponding maximum likelihood estimate (MLE) of the Poisson distribution based on the root mean squared error (RMSE) for different cases of the