A new imidazolidine 4-one derivative, of namly 2-[2-(4-Bromo-phenyl)-imidazo [1,2-a] pyridine-3-yl]-3-(4-nitro-phenyl)-imidazolidine-4-one (BPIPNP) was investigated as corrosion inhibitor for carbon steel in salty (3.5% NaCl) and acidic (0.5M HCl) solutions using potentiometric polarization measurements. The results revealed that the percentage inhibition efficiencies (%IE) in the salty solution (90.67%) are greater than that in the acidic solution (83.52%). Experimentally, the thermodynamic parameters obtained have supported a physical adsorption mechanism and which followed Langmuir adsorption isotherm. Density Functional Theory (DFT) of quantum mechanical method with B3LYP 6-311++G (2d, 2p) level was used to calculate geometrical stru

In this paper, the effect of wear in the fluid film journal bearings on the dynamic stability of rotor bearing system has been studied depending on the development of new analytical equations for motion, instability threshold speed and steady state harmonic response for rotor with offset disc supported by worn journal bearings. Finite element method had been used for modeling the rotor bearing system. The analytical model is verified by comparing its results with that obtained numerically for a rotor supported on the short bearings. The analytical and numerical results showed good agreement with about 8.5% percentage error in the value of critical speed and about 3.5% percentage error in the value of harmonic response. T

In this work we study gamma modules which are implying full stability or implying by full stability. A gamma module is fully stable if for each gamma submodule of and each homomorphism of into . Many properties and characterizations of these classes of gamma modules are considered. We extend some results from the module to the gamma module theories.

This search seeks to know the trends of academics in the field of Press and audio, video and read press about paper press compared with continued development and widespread deployment of web journalism. This research belongs to descriptive studies which depends on sample survey approach adopted by five-meter design measuring trends. It contains 28 items having applied honesty and reliability transaction and the scale form is distributed to the sample studied of about 110 professors and then the researcher collects them and then applying the appropriate statistical program to get the results. This search seeks to know the trends of academics in the field of Press and audio, video and read press about paper press compared with continu

Let  be an n-Banach space, M be a nonempty closed convex subset of , and S:M→M be a mapping that belongs to the class  mapping. The purpose of this paper is to study the stability and data dependence results of a Mann iteration scheme on n-Banach space

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

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

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