The use of composite materials has vastly increased in recent years. Great interest is therefore developed in the damage detection of composites using non- destructive test methods. Several approaches have been applied to obtain information about the existence and location of the faults. This paper used the vibration response of a composite plate to detect and localize delamination defect based on the modal analysis. Experiments are conducted to validate the developed model. A two-dimensional finite element model for multi-layered composites with internal delamination is established. FEM program are built for plates under different boundary conditions. Natural frequencies and modal displacements of the intact and damaged

Purpose The purpose of this study was to evaluate the complications associated with the use of reconstruction plates with or without non-vascularized bone graft in reconstruction of mandibular segmental defects caused by trauma and tumor resection and to analyze various factors that are associated with the development of complications. Methods A retrospective observational study was conducted, and the investigated variables included the age and gender of the patients, etiology of the defect, the site of the defect, the size of the defect, whether bone graft was used or not, type of plate used, and whether the reconstruction was immediate or delayed. The outcome variables were the postoperative complications and the success rate. Results Fif

This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

     Automated medical diagnosis is an important topic, especially in detection and classification of diseases. Malaria is one of the most widespread diseases, with more than 200 million cases, according to the 2016 WHO report. Malaria is usually diagnosed using thin and thick blood smears under a microscope. However, proper diagnosis is difficult, especially in poor countries where the disease is most widespread. Therefore, automatic diagnostics helps in identifying the disease through images of red blood cells, with the use of machine learning techniques and digital image processing. This paper presents an accurate model using a Deep Convolutional Neural Network build from scratch. The paper also proposed three CNN

Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar

Background: obesity is nowadays a pandemic condition. Obese subjects are commonly characterized by musculoskeletal disorders and particularly by non-specific low back pain (LBP). However, the relationship between obesity and LBP remain to date unsupported by an objective measurement of the mechanical behavior of spine and it is morphology in obese subjects. . Objectives: To identify the relationship between obesity and LBP regarding (height, weight, sleeping, chronic diseases, smoking, and steroid). Method: A cross-sectional study was conducted from the first of January 2016 to January 2018 in obe

Composite materials are widely used in the engineered assets as aerospace structures, marine and air navigation owing to their high strength/weight ratios. Detection and identification of damage in the composite structures are considered as an important part of monitoring and repairing of structural systems during the service to avoid instantaneous failure. Effective cost and reliability are essential during the process of detecting. The Lamb wave method is an effective and sensitive technique to tiny damage and can be applied for structural health monitoring using low energy sensors; it can provide good information about the condition of the structure during its operation by analyzing the propagation of the wave in the