Incremental forming is a flexible sheet metal forming process which is performed by utilizing simple tools to locally deform a sheet of metal along a predefined tool path without using of dies. This work presents the single point incremental forming process for producing pyramid geometry and studies the effect of tool geometry, tool diameter, and spindle speed on the residual stresses. The residual stresses were measured by ORIONRKS 6000 test measuring instrument. This instrument was used with four angles of (0º,15º,30º, and 45º) and the average value of residual stresses was determined, the value of the residual stress in the original blanks was (10.626 MPa). The X-ray diffraction technology was used to measure the residual stresses

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

A cost-effective and efficient detector was created to conduct thorough turbidimetric measurements by reaction of Co (II) ion with calcium ferro cyanide to form bright green particulate, using the method of continuous flow injection analysis, the use of NAG-5SX1-1D-SSP Analyzer in determining cobalt (II) ion in a test for the validity of the new design. The NAG-5SX1-1D-SSP Analyzer is composed of five irradiation sources of white snow leds having the diameter of 10 mm with one solar cell of 55 mm length, 13.5 mm width. Using a selector switch to select the optimum voltage to be used which was 2.7 VDC. Under conditions of optimization, cobalt (II) ion was determined at 0.005–20 mmol. L–1(n = 23) while linearity dynamic range 0.005–7 mm

Pharmaceuticals are widely distributed in different applications and also released into the environment. Adsorption of Ciprofloxacin HCl (CIPH) on Porcelinaite was studied at ambient conditions. The adsorption isotherms can be well described using the Freundlich and Temkin equations. The pH of the solution influences significantly the adsorption capacity of Porcelinaite, the adsorption of CIPH increased from the initial pH 1.3 and then decreased over the pH rang of 3.8-9. The adsorption is sensitive to the change in ionic Strength, which indicate that electrostatic attraction is a significant mechanism for sorption process. The enthalpy change (ΔH) for the adsorption of CIPH onto Porcelinaite signifies an endothermic adsorption. The ΔG va

Pharmaceuticals are widely distributed in different applications and also released into the environment. Adsorption of Ciprofloxacin HCl (CIPH) on Porcelinaite was studied at ambient conditions. The adsorption isotherms can be well described using the Freundlich and Temkin equations. The pH of the solution influences significantly the adsorption capacity of Porcelinaite, the adsorption of CIPH increased from the initial pH 1.3 and then decreased over the pH rang of 3.8-9. The adsorption is sensitive to the change in ionic Strength, which indicate that electrostatic attraction is a significant mechanism for sorption process. The enthalpy change (∆H) for the adsorption of CIPH onto Porcelinaite signifies an endothermic adsorption. The ∆G