During treatment of inflammatory diseases, many conventional therapies (non-steroidal anti-inflammatory drugs) used to relief pain and inflammation. Chronic use of  the intended drugs is frequently associated with serious side effect, which may lead to discontinuation of treatment . The efficacy and dose- response effect of ammi majus extraxt  (2 , 4, 8 , 16, and 32 mg/rat) were assessed using  formalin to induce paw edema in rats as a model of chronic inflammation respectively. In this study,  42 rats were used and allocated into 7  groups each containing 6 rats, representing control (Distilled  water) , standard (piroxicam ) and test extract ( 2 , 4 , 8 , 16 and 32 mg/rat of Ammi majus alcoholic e

The current research deals with the specificity of the interior design of the classes of art education in the schools of excellence for the province of Muthanna and its center of the city of Samawah. In the first chapter، the problem of research was determined by the lack of internal spaces of the classes of art education to designs that meet the requirements and needs of students in these educational stages.  The importance of the research in being an addition to knowledge in the field of interior design and engineering department of the general directorates of the Ministry of Education. The objectives of the research were determined through.

1. Identifying the reality of the halls of art education for sch

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 cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere

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

Abstract. In this paper, a high order extended state observer (HOESO) based a sliding mode control (SMC) is proposed for a flexible joint robot (FJR) system in the presence of time varying external disturbance. A composite controller is integrated the merits of both HOESO and SMC to enhance the tracking performance of FJR system under the time varying and fast lumped disturbance. First, the HOESO estimator is constructed based on only one measured state to precisely estimate unknown system states and lumped disturbance with its high order derivatives in the FJR system. Second, the SMC scheme is designed based on such accurate estimations to govern the nominal FJR system by well compensating the estimation errors in the states and the lumped

This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH₂) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

Renewal is generally considered an urgent requirement of life, and a section of its continuation, because renewal means that life exists and continues, and just as renewal is in life, renewal is in science, and in this research the issue of renewal in the science of interpretation, and showed through research that renewal in This science was an urgent demand throughout the Islamic ages, as the research showed the necessity of renewal in the material of interpretation, its method and methods, and the researcher presented the opinions of schools about renewal in the interpretation of the Noble Qur’an inferred by living models that refer to their owners.