In the beta decay process, a neutron converts into a proton, or vice versa, so the atom in this process changes to a more stable isobar. Bethe-Weizsäcker used a quasi-experimental formula in the present study to find the most stable isobar for isobaric groups of mass nuclides (A=165-175). In a group of isobars, there are two methods of calculating the most stable isobar. The most stable isobar represents the lowest parabola value by calculating the binding energy value (B.E) for each nuclide in this family, and then drawing these binding energy values as a function of the atomic number (Z) in order to obtain the mass parabolas, the second method is by calculating the atomic number value of the most stable isobar (ZA). The results show that the mass parabolas of isobar elements with an even mass number (A=even) vary from the mass parabolas of isobar elements with an odd mass number (A=odd), In the case of single isobars, it has one parabola, meaning that it has one stable isobar, while we find that the pairs isobars appear to have two parabolas, meaning that it has more than one stable isobar. When we compared the two methods used in this study to determine the most stable isobars, we found that in two techniques for odd isobars, stable isobars are mostly the same nuclide, whereas in suitcases of even isobars with two stable isobars (only one of them are same stable isobars).
A novel technique for nanoparticles with a chemical method and impact for resistance bacteria methicillin-resistant Staphylococcus aureus (MRSA), UV-visible analysis confirmed the by Fourier transform infrared spectroscopy (FT-IR) and Energy dispersive X-Ray (EDX), Scanning electron microscope (SEM) and X-ray diffraction pattern estimation antimicrobial excellent antibacterial activity against MRSA (with zone of inhibition of 11 ± 02 mm , 9 ± 01 mm,8 ± 03 mm and 7.5 ± 02 mm and 6.5 ± 02 mm) at different concentrations (0.5 ,0.25, 0.125, 0.0625, 0.03125) mg/ml while good activity was 16 ± 03 mm at 17 ± 02 mm zone at 0.25, 0.125 mg/mL, respectively. The increase in microorganism resistance to antibiotics a couple of have caused
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In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients
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Abstract
Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia
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This research aims at identifying the communicative habits and content reflections on the communication process, especially the young audience which is one of the main group for whom the announcements are made. Because young people face life with passion and aspiration making them respond to each effect used by the media in the design of the advertising using all the effective techniques, attractive methods for young children like depending on drama, technical tricks, music and logos easily to be remembered and responded to the desires of the young in their entertainment. This research also aims at identifying the impact of the internet as a channel of commercial advertising on the purchasing behavior of young people at the universities
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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