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Snubber Network Design for Triac Driving Single – Phase Industrial Heater by Applying Fuzzy Logic Method
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Power switches require snubbing networks for driving single – phase industrial heaters. Designing these networks, for controlling the maximum allowable rate of rise of anode current (di/dt) and excessive anode – cathode voltage rise (dv/dt) of power switching devices as thyristors and Triacs, is usually achieved using conventional methods like Time Constant Method (TCM), resonance Method (RM), and Runge-Kutta Method (RKM). In this paper an alternative design methodology using Fuzzy Logic Method (FLM) is proposed for designing the snubber network to control the voltage and current changes. Results of FLM, with fewer rules requirements, show the close similarity with those of conventional design methods in such a network of a Triac driving 1.2 kW heater of an industrial plastic extruder machine. The similarity, between Fuzzy Logic results and conventional techniques results, is confirming the applicability of the fuzzy logic in designing these snubbing networks.

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Publication Date
Wed Sep 01 2021
Journal Name
International Scientific Congress Of Pure, Applied And Technological Sciences (minar Congress)
Evaluation Of Electromagnetic Pollution Of Cellular Mobile Network
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Wireless communications are characterized by their fastest growth in history, as they used ever-evolving and renewed technologies, which have allowed them to spread widely. Every day, communication technology introduces a new invention with features that differ from its predecessor. Bell Laboratories first suggested mobile wireless communication services to the general population in the late 1940s. Still, it wasn't easy at that time to use on a large scale due to its high costs. This paper aims to describe the state of cellular mobile networks; by comparing the sources of electromagnetic pollution caused by these networks, measure the level of power density in some residential areas, and compare them with international standards adopted in

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Publication Date
Sat Dec 31 2022
Journal Name
International Journal On “technical And Physical Problems Of Engineering”
Age Estimation Utilizing Deep Learning Convolutional Neural Network
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Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

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Publication Date
Sat Jan 01 2011
Journal Name
Trends In Network And Communications
Header Compression Scheme over Hybrid Satellite-WiMAX Network
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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
Modified W-LEACH Protocol in Wireless Sensor Network
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In this paper, a Modified Weighted Low Energy Adaptive Clustering Hierarchy (MW-LEACH) protocol is implemented to improve the Quality of Service (QoS) in Wireless Sensor Network (WSN) with mobile sink node. The Quality of Service is measured in terms of Throughput Ratio (TR), Packet Loss Ratio (PLR) and Energy Consumption (EC). The protocol is implemented based on Python simulation. Simulation Results showed that the proposed protocol provides better Quality of Service in comparison with Weighted Low Energy Cluster Hierarchy (W-LEACH) protocol by 63%.

  

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Optimized Artificial Neural network models to time series
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        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

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Publication Date
Thu Aug 01 2024
Journal Name
Water Practice & Technology
Artificial neural network and response surface methodology for modeling oil content in produced water from an Iraqi oil field
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ABSTRACT<p>The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value &lt;0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe</p> ... Show More
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Publication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Development of Intelligent Control Strategy for an Anesthesia System Based on Radial Basis Function Neural Network Like PID Controller
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Publication Date
Wed Oct 18 2023
Journal Name
Ieee Access
A New Imputation Technique Based a Multi-Spike Neural Network to Handle Missing Data in the Internet of Things Network (IoT)
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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Optical Design of Laser Zoom Beam Expander at near & far Ranges for Tracked Atmospheric Target
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In this research, beam expander, BEX, is explained and designed for illuminating the
remote flying target. The BEX is optically designed to be suited for Nd:YAG laser of given
specifications. The BEX is modified to be zoom one to meet the conditions of preventing the
receiving unit; i.e the photodetector, from getting saturated at near and far laser tracking.
Decollimation could be achieved by automatic motor, which controls zoom lens of the BEX
according to the required expansion ratio of beam expander

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Publication Date
Sun Dec 25 2022
Journal Name
International Journal Of Drug Delivery Technology
Design and Evaluation of Solid Lipid Nanoparticle Eye Drops Containing VRN for Ocular Drug Delivery
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As a well-known oral and intravenous antifungal, voriconazole (VRN) has an extensive history of usage in the medical field. Solid lipid nanoparticles (SLNs) have been produced to treat ocular fungal keratitis in the eye. A 32Box-behnken design was used to produce a variety of new formulas for hot-melt extrusion. The SLNs were evaluated by entrapment efficiency (EE percent), particle size (PS), polydispersity index (PDI), and zeta potential (ZP). A series of in-vitro and in-vivo studies were carried out on the new formula. The produced vesicles’ EE, PS, PDI, and ZP values were all good. SLNs eye drops were numerically adjusted to include carbopol, a stabilizer, lipids, and a surfactant, among other substances. ZP of -36.5 ± 0.20 m

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