Abstract

     Machining residual stresses correlate very closely with the cutting parameters and the tool geometries. This research work aims to investigate the effect of cutting speed, feed rate and depth of cut on the surface residual stress of steel AISI 1045 after face milling operation. After each milling test, the residual stress on the surface of the workpiece was measured by using X-ray diffraction technique. Design of Experiment (DOE) software was employed using the response surface methodology (RSM) technique with a central composite rotatable design to build a mathematical model to determine the relationship between the input variables and the response. The results showed that both

      Many neuroscience applications, including understanding the evolution of the brain, rely on neural cell instance segmentation, which seeks to integrate the identification and segmentation of neuronal cells in microscopic imagery. However, the task is complicated by cell adhesion, deformation, vague cell outlines, low-contrast cell protrusion structures, and background imperfections. On the other hand, existing segmentation approaches frequently produce inaccurate findings. As a result, an effective strategy for using the residual network with attention to segment cells is suggested in this paper. The segmentation mask of neural cells may be accurately predicted. This method is built on U-net, with EfficientNet serving as the e

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

Face recognition is a type of biometric software application that can identify a specific
individual in a digital image by analyzing and comparing patterns. It is the process of
identifying an individual using their facial features and expressions.
In this paper we proposed a face recognition system using Stationary Wavelet Transform
(SWT) with Neural Network, the SWT are applied into five levels for feature facial
extraction with probabilistic Neural Network (PNN) , the system produced good results
and then we improved the system by using two manner in Neural Network (PNN) and
Support Vector Machine(SVM) so we find that the system performance is more better
after using SVM where the result shows the performance o

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

This paper develops a nonlinear transient three-dimensional heat transfer finite element model and a rate independent three-dimensional deformation model, developed for the CO₂ laser welding simulations in Al-6061-T6 alloy. Simulations are performed using an indirect coupled thermal-structural method for the process of welding. Temperature-dependent thermal properties of Al-6061-T6, effect of latent heat of fusion, and the convective and radiative boundary conditions are included in the model. The heat input to the model is assumed to be a Gaussian heat source. The finite element code ANSYS12, along with a few FORTRAN subroutines, are employed to obtain the numerical results. The benefit of the proposed methodology is that it

Incremental Sheet Metal Forming (ISMF) is a modern sheet metal forming technology which offers the possibility of manufacturing 3D complex parts of thin sheet metals using the CNC milling machine. The surface quality is a very important aspect in any manufacturing process. Therefore, this study focuses on the resultant residual stresses by forming parameters, namely; (tool shape, step over, feed rate, and slope angle) using Taguchi method for the products formed by single point incremental forming process (SPIF). For evaluating the surface quality, practical experiments to produce pyramid like shape have been implemented on aluminum sheets (AA1050) for thickness (0.9) mm. Three types of tool shape used in this work, the spherical tool ga

     Face detection is one of the important applications of biometric technology and image processing. Convolutional neural networks (CNN) have been successfully used with great results in the areas of image processing as well as pattern recognition. In the recent years, deep learning techniques specifically CNN techniques have achieved marvellous accuracy rates on face detection field. Therefore, this study provides a comprehensive analysis of face detection research and applications that use various CNN methods and algorithms. This paper presents ten of the most recent studies and illustrate the achieved performance of each method.