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

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

Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this

protein oxidation through oxidative stress, which represents the overall status of the protein in the cell/tissue. Due to their increased levels of AOPPs were reported during T2DM. The aim of this study was to assess AOPP level in T2DM subjects with foot ulcer (DFU) and explore its correlation with infection. Type 2 diabetic patients (n=108) and healthy subjects (n=25) were enrolled in this study. The T2DM group was subdivided to diabetic patients without complications (n=25) and eighty-three (83) of them have diabetic foot. They were sub- grouped into two groups according to presence Osteomyelitis and abscess, and in reliance on medical analysis of WBC count and CRP. Group of diabetic without superficial or deep ulcer and no osteomyelitis

After the democratic transformation in 2003 in Iraq, young people waited a lot to take their real opportunity to participate in politics, but most of the laws regulating political and electoral work have been unfair to young people, despite developments in laws and legislation, but opportunities did not allow young people to participate in politics, which was reflected It negatively affected their participation in voting and nomination, and even their assumption of public office and positions, which is why they complained about the ruling class and the political system through protests, or when they refused to vote, and this is reflected in the recent parliamentary elections and low participation rates

Human cytomegalovirus (HCMV) infection is ubiquitous and successfully reactivated in patients with immune dysfunction as in patient with multiple myeloma (MM), causing a wide range of life-threatening diseases. Early detection of HCMV and significant advances in MM management has amended patient outcomes and prolonged survival rates.

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe