A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

This research is devoted to investigating the thermal buckling analysis behaviour of laminated composite plates subjected to uniform and non-uniform temperature fields by applying an analytical model based on a refined plate theory (RPT) with five unknown independent variables. The theory accounts for the parabolic distribution of the transverse shear strains through the plate thickness and satisfies the zero-traction boundary condition on the surface without using shear correction factors; hence a shear correction factor is not required. The governing differential equations and associated boundary conditions are derived by using the virtual work principle and solved via Navier-type analytical procedure to obtain critica

Background: The COVID-19 virus outbreak had a massive effect on many parts of people's lives, as they were advised to quarantine and lockdown to prevent the virus from spreading, which had a big impact on people's mental health, anxiety, and stress. Many internal and external factors lead to stress. This negatively influences the body's homeostasis. As a result, stress may affect the body's capacity to use energy to defend against pathogens. Many recent investigations have found substantial links between human mental stress and the production of hormones, prohormones, and/or immunological chemicals. some of these researches have verified the link between stress and salivary cortisol levels. The aim of this study is to measure salivary corti

It is important to note that Posaconazole (POCZ) is a newly developed extended-spectrum triazole that belongs to BCS class II and has a solubility of less than 1µg/ml. In patients with a weakened immune system, POCZ has been shown to be effective as an antifungal treatment for invasive infections caused by candida and aspergillus species. The nano-micelles technique can be used to increase POCZ solubility. In order to increase their apparent solubility in water, nano-micelles are made by combining macromolecules that self-assemble into ordered structures capable of entrapping hydrophobic drug molecules in the interior domain. Dispersed colloidal systems, of which nano-micelles are a subset, are a large and diverse group. Composed of a p

In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

In this study, the effect of design parameters such as pipe diameter, pipe wall thickness, pipe material and the effect of fluid velocity on the natural frequency of fluid-structure interaction in straight pipe conveying fully developed turbulent flow were investigate numerically,analytically and experimentally. Also the effect of support conditions, simply-simply and clamped-clamped was investigated. Experimentally, pipe vibrations were characterized by accelerometer mounted on the pipe wall. The natural frequencies of vibration were analyzed by using Fast Fourier Transformer (FFT). Five test sections of two different pipe diameters of 76.2
mm and 50.8 mm with two pipe thicknesses of 3.7 mm and 2.4 mm and two pipe materials,stainles