The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

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

Purpose Heavy metals are toxic pollutants released into the environment as a result of different industrial activities. Biosorption of heavy metals from aqueous solutions is a new technology for the treatment of industrial wastewater. The aim of the present research is to highlight the basic biosorption theory to heavy metal removal. Materials and methods Heterogeneous cultures mostly dried anaerobic bacteria, yeast (fungi), and protozoa were used as low-cost material to remove metallic cations Pb(II), Cr(III), and Cd(II) from synthetic wastewater. Competitive biosorption of these metals was studied. Results The main biosorption mechanisms were complexation and physical adsorption onto natural active functional groups. It is observed that

This work presents a computer studying to simulate the charging process of a dust grain immersed in plasma with negative ions. The study based on the discrete charging model. The model was developed to take into account the effect of negative ions on charging process of dust grain.
The model was translated to a numerical calculation by using computer programs. The program of model has been written with FORTRAN programming language to calculate the charging process for a dust particle in plasma with negative ion, the time distribution of a dust charge, number charge equilibrium and charging time for different value of ηe (ratio of number density of electron to number density of positive ion).

Coupling reaction of 2-amino benzoic acid with the 8-hydroxy quinoline gave the azo ligand (H2L): 5-(2-benzoic acid azo )-8-hydroxy quinoline.Treatment of this ligand with some metal ions (CoII, NiII and CuII ) in ethanolic medium with a (1:2) (M:L) ratio yielded a series of neutral complexes with general Formula[M(HL)2],where: M=Co(II), Ni(II) and Cu(II), HL=anion azo ligand (-1).The prepared complexes were characterized using flame atomic absorption,FT-IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements.

The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o