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Embedded Neural Network like PID Water Heating Controller Implementing Cycle by Cycle Power Control Scheme
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This paper experimentally investigates the heating process of a hot water supply using a neural network implementation of a self-tuning PID controller on a microcontroller system. The Particle Swarm Optimization (PSO) algorithm employed in system tuning proved very effective, as it is simple and fast optimization algorithm. The PSO method for the PID parameters is executed on the Matlab platform in order to put these parameters in the real-time digital PID controller, which was experimented with in a pilot study on a microcontroller platform. Instead of the traditional phase angle power control (PAPC) method, the Cycle by Cycle Power Control (CBCPC) method is implemented because it yields better power factor and eliminates harmonics in the power supply line. The smoothness of the heating process’s output response, which is a result of both empirical experiments and simulation results, demonstrates the efficacy of the suggested control mechanism, where the output response had a small ripple margin. The system performed according to design expectations and had unimpaired unity power factor throughout its operating range and no ripple was detected during its functioning.

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Publication Date
Tue Mar 26 2024
Journal Name
World Electric Vehicle Journal
Fast Finite-Time Composite Controller for Vehicle Steer-by-Wire Systems with Communication Delays
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The modern steer-by-wire (SBW) systems represent a revolutionary departure from traditional automotive designs, replacing mechanical linkages with electronic control mechanisms. However, the integration of such cutting-edge technologies is not without its challenges, and one critical aspect that demands thorough consideration is the presence of nonlinear dynamics and communication network time delays. Therefore, to handle the tracking error caused by the challenge of time delays and to overcome the parameter uncertainties and external perturbations, a robust fast finite-time composite controller (FFTCC) is proposed for improving the performance and safety of the SBW systems in the present article. By lumping the uncertainties, parameter var

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Publication Date
Sat May 01 2021
Journal Name
Https://www.researchgate.net/journal/journal-of-physics-conference-series-1742-6596
The management of water distribution network using GIS application case study: AL-Karada area
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Abstract<p>Clean water supply is one of the major factors contributing significantly to society’s socio-economic transformation by improving living standards, health, and increasing productivity. It is imperative to plan and construct appropriate water supply systems in modern society, which supply various segments of society with safe drinking water according to their requirements to ensure adequate and quality water supply. In the current study, here was an attempt to develop a model for geographic information systems to manage the assets of the water distribution networks in the Karrada region and to evaluate the network geometrically, and from the results of the engineering analysis of the</p> ... Show More
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Publication Date
Sat Jan 01 2022
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees21gr
Effect of non-thermal plasma by FE-DBD scheme on lipids in blood in vivo study
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This study illustrates the impact of non-thermal plasma (Cold Atmospheric Plasma CAP) on the lipids blood, the study in vivo. The lipids are (cholesterol, HDL-Cholesterol, LDL-Cholesterol and triglyceride) are tested. (FE-DBD) scheme of probe diameter 4cm is used for this purpose, and the output voltage ranged from (0-20) kV with variable frequency (0-30) kHz. The effect of non-thermal atmospheric plasma on lipids were studied with different exposure durations (20,30) sec. As a result, the longer plasma exposure duration decreases more lipids in blood.

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Publication Date
Sat Dec 16 2023
Journal Name
2023 14th International Renewable Energy Congress (irec)
Utilizing the Controlled Hydropower System to Harness the Collected Water in Drainage System for Power Generation
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The variety of clean energy sources has risen, involving many resources, although their fundamental principles remain consistent in terms of energy generation and pollution reduction. The using of hydropower system for energy production also has a dynamic impact in which it utilizes to harness the water for the purpose of energy production. As it is important to overcome the problem of accidents in the highway and rural areas in the case of server rainfall and flood by implementation a smart system that used for energy production. This paper aims to develop a controlled hydropower system installed in the drainage sinks allocated in highway roads used for producing. The proposed system consists of storage unit represented by pipes used for t

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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Helical Piles Embedded in Expansive Soil Overlaying Sandy Soil
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In this study, the behavior of square helical piles models (5×5) mm2 embedded in expansive soil bed overlaying a layer of sandy soil was investigated. The sand layer 200mm thickness was compacted into four sub layers in a steel container with diameter 400mm in size. Sandy soil layer was compacted into two relative densities 40% and 80%. The bed of ثءحties 40% and 80%.The bed of o00mm in size.Sandy soil layer was compacted into two relative densities 40% and 80%.The bed of oexpansive soil 300mm thickness was compacted into six sub layers on sandy soil layer. Model tests are performed with helical pile length 350mm, 400mm and 450mm and with helix diameter 15mm and 20mm. Also, one helix and double helix were

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Publication Date
Sun Jan 27 2019
Journal Name
Industrial &amp; Engineering Chemistry Research
Fabrication and Characterizations of Silica Nanoparticle Embedded Carbon Nanofibers
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Publication Date
Tue Oct 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Comparison of Artificial Neural Network and Box- Jenkins Models to Predict the Number of Patients with Hypertension in Kalar
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    Artificial Neural Network (ANN) is widely used in many complex applications. Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.  The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model  and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Je

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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Prediction Using Artificial Neural Network of Bed Porosity and Solid Holdup in Viscous 3-Phase Inverse Fluidization
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In the present investigation, bed porosity and solid holdup in viscous three-phase inverse fluidized bed (TPIFB) are determined for aqueous solutions of carboxy methyl cellulose (CMC) system using polyethylene and polypropylene as  a particles with low-density and diameter (5 mm) in a (9.2 cm) inner diameter with height (200 cm) of vertical perspex column. The effectiveness of gas velocity Ug , liquid velocity UL, liquid viscosity μL, and particle density ρs on bed porosity BP and solid holdups εg were determined. The bed porosity increases with "increasing gas velocity", "liquid velocity", and "liquid viscosity". Solid holdup decreases with increasing gas, liquid

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Publication Date
Thu Mar 01 2007
Journal Name
Al-khwarizmi Engineering Journal
The Inverse Solution Of Dexterous Robot By Using Neural Networks
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The inverse kinematics of redundant manipulators has infinite solutions by using conventional methods, so that, this work presents applicability of intelligent tool (artificial neural network ANN) for finding one desired solution from these solutions. The inverse analysis and trajectory planning of a three link redundant planar robot have been studied in this work using a proposed dual neural networks model (DNNM), which shows a predictable time decreasing in the training session. The effect of the number of the training sets on the DNNM output and the number of NN layers have been studied. Several trajectories have been implemented using point to point trajectory planning algorithm with DNNM and the result shows good accuracy of the end

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Publication Date
Tue Sep 19 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Density and Approximation by Using Feed Forward Artificial Neural Networks
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I n  this  paper ,we 'viii  consider  the density  questions  associC;lted with  the single  hidden layer feed forward  model. We proved  that a FFNN   with   one   hidden   layer  can   uniformly   approximate   any continuous  function  in C(k)(where k is a compact set in R11 ) to any required accuracy.

 

However, if the set of basis function is dense then the ANN's can has al most one hidden layer. But if the set of basis function  non-dense, then we  need more  hidden layers. Also, we have shown  that there exist  localized functions and that there is no t

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