Search Results at the International Journal of Science and Research (IJSR)

This study examines the vibrations produced by hydropower operations to improve embankment dam safety. This study consists of two parts: In the first part, ANSYS-CFX was used to generate a three-dimensional (3-D) finite volume (FV) model to simulate a vertical Francis turbine unit in the Mosul hydropower plant. The pressure pattern result of the turbine model was transformed into the dam body to show how the turbine unit's operation affects the dam's stability. The upstream reservoir conditions, various flow rates, and fully open inlet gates were considered. In the second part of this study, a 3-D FE Mosul dam model was simulated using an ANSYS program. The operational turbine model's water pressure pattern is conveyed t

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

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

In present project, new Schiff base of 4, 4'- (((1E, 1'E)-1,4-.phenylenebis- (methane-ylylidene))-bis-(azane-ylylidene)) bis-(5-(4-chlorophenyl) -4H -1,2,4-triazole-3-thione) (L3) has been synthesized by condensation of 4-amino-5-(4-chlorophenyl)-2,4-dihydro-3H-1,2,4-triazole-3-thione with benzene-1,4-dicarboxaldehyde. The new asymmetrical Schiff base (L3) used as a ligand to synthesize a new complex with Co(II), Ni(II), Cu(II), Pd(II), and Pt(IV) metal ions by 1:2 (Metal: ligand) ratio. New ligand and their complexes have been exanimated and Confirmed by Fourier-transform infrared (FT-IR), Ultraviolet-visible (UV-visible), Proton nuclear magnetic resonance (1HNMR), carbon13 nuclear magnetic resonance (13CNMR), carbon-hydrogen nitrogen sulf

Background: Extracorporeal Shock wave lithotripsy (ESWL) is widely used in treating patients with ureteralstones because it is effective, safe, and noninvasive. Based on factors such as size and the location of stones,there is a significant variation in the overall stone-free rate (SFR).Aim of the study: To evaluate the effect of ureteral wall thickness (UWT), stone attenuation, the time fromfirst attack of pain till first session of ESWL and stone/ rib density on the outcome of SWL in the treatmentof upper ureteral stones (UUS).Patient and methods: A prospective study when 127 patients with radio-opaque UUS ranging from 7 to 20mm and treated by ESWL were included in this study. The effect of (stone/ 12th rib) density by KUB, ureter