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

As one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord

The Cu(II) was found using a quick and uncomplicated procedure that involved reacting it with a freshly synthesized ligand to create an orange complex that had an absorbance peak of 481.5 nm in an acidic solution. The best conditions for the formation of the complex were studied from the concentration of the ligand, medium, the eff ect of the addition sequence, the eff ect of temperature, and the time of complex formation. The results obtained are scatter plot extending from 0.1–9 ppm and a linear range from 0.1–7 ppm. Relative standard deviation (RSD%) for n = 8 is less than 0.5, recovery % (R%) within acceptable values, correlation coeffi cient (r) equal 0.9986, coeffi cient of determination (r2) equal to 0.9973, and percentage capita

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

The accuracy of the skillful performance of the front and back dimensions of badminton in volleyball, occurs through the investment of complex exercises (physical skills) in a single performance and its characteristics that give the correct movement behavior and speed to the accuracy of the performance of the strokes as well as the identification of changes in some physiological indicators of By using these compound exercises. The research problem lies: I found a weakness in the accuracy of the performance of the front and back dimensions strike and diagnosed this through the tests that it conducted on the players to identify and know the problem, and attributed this weakness to a weakness in the necessary physical and skill abilities and t

     Pregnancy and delivery are physiological conditions that are marked by abrupt alterations to hormones, immunological and molecular characters. The current study aimed to evaluate oxytocin (OT), prolactin (PRL), cortisol and insulin growth factor-2 (IGF-2) levels as physiological biomarkers; programmed cell death protein-1 (PD-1), programmed cell death ligand-1 (PD-L1),interleukin-6 (IL-6) as immunological biomarkers, and single nucleotide polymorphisms (SNPs; rs53576 and rs2254298) of oxytocin receptor gene OXTR as molecular factors in samples of Iraqi women undergoing caesarean section (CS) and normal delivery (ND). Blood samples were collected from 96 pregnant women at term with ages ranging between 16-43 years. Regarding

In this research work a composite material was prepared contains a matrix which is unsaturated polyester resin (UPE) reinforced with carbon nanotube the percentage weight (0.1, 0.2, 0.4.0.5) %, and Zn particle the percentage weight (0.1, 0.2,0.4,0.5)%.
All sample were prepared by hand lay-up, process the mechanical tests contains hardness test, wear rate test, and the coefficient of thermal conductivity. The results showed a significant improvement in the properties of overlapping, Article containing carbon nano-tubes and maicroparticles of zinc because of its articles of this characteristics of high quality properties led to an, an increase in the coefficient of the rmalconductivity, and increase the hardness values with increased pe