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Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback control system using PID controller to stabilize the fuel cell voltage. Particle swarm optimization technique is used to tune the PID controller gains. The voltage error and hydrogen flow rate are input and the actuator of the PID controller respectively. Simulation results showed that using PID controller with proposed model of fuel cell can successfully improve system performance in tracking output voltage under different operating conditions.

 

 

 

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Publication Date
Tue Dec 01 2009
Journal Name
Iraqi Journal Of Physics
Analytical Performance Modeling of InP-InGaAs Hetero-junction Avalanche Photodiode
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In this study, an analytical model depending on experimental results for InPInGaAs
avalanche photodiode at low bias was presented and the characteristics of
gain for this photodiode were determined directly by the impulse response. The
model have considered the most important mechanisms contributing the
photocurrent, they are trapping, photogeneration in the undepleted region and
charge-carriers velocity due to the built-in electrical field. Also, the bandwidth
was determined as a function to the total gain of photodiode and it was mainly
determined by diffusion and trapping processes at low gain regarding to the multilayer
structure considered in this study

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
MODELING DEATH RATE OF THE COVID-19 PANDEMIC IN IRAQ
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Publication Date
Sun Oct 02 2022
Journal Name
Engineering, Technology & Applied Science Research
Statistical Modeling for Traffic Noise: The Case of Kirkuk City
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The auditory system can suffer from exposure to loud noise and human health can be affected. Traffic noise is a primary contributor to noise pollution. To measure the noise levels, 3 variables were examined at 25 locations. It was found that the main factors that determine the increase in noise level are traffic volume, vehicle speed, and road functional class. The data have been taken during three different periods per day so that they represent and cover the traffic noise of the city during heavy traffic flow conditions. Analysis of traffic noise prediction was conducted using a simple linear regression model to accurately predict the equivalent continuous sound level. The difference between the predicted and the measured noise shows that

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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Optimization Algorithms Based on Path Planning and Neural Controller for Mobile Robot
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In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

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Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte

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Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Scopus (69)
Crossref (50)
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Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Scopus (69)
Crossref (50)
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Publication Date
Thu Feb 29 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Design and Development of Powerful Neuroevolution Based Optimized GNNBiLSTM Model for Consumer Behaviour and Effective Recommendation in Social Networks
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Publication Date
Tue Jan 20 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Immunohistochemical expression of E-cadherin and CD44 adhesion molecules in oral squamous cell carcinoma
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Background: Head and neck squamous cell carcinoma is the sixth most common cancer world wide. Despite greater emphasis on multi-modality therapy including surgery, radiation and chemotherapy, advanced stage head and neck squamous cell carcinoma continues to have poor 5-year survival rates (0-40%) that have not significantly improved in the last (30) years. To improve outcomes for this deadly disease , It is required a better understanding of the mechanisms underlying head and neck squamous cell carcinoma tumor growth, metastasis, and treatment resistance. This study evaluates the Immunohistochemical expression of E-cadherin and CD44 adhesion molecules in OSCC and to correlate the expression of either marker with each other, with lymph node

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Publication Date
Sun Aug 01 2021
Journal Name
Biochemical And Cellular Archeves
ABILITY OF CRONOBACTER SAKAZAKII FOR ADHESION AND INVASION TO SKG-GT-4 CELL LINE
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ABSTRACT : Fifteenth isolates of C. sakazakii were obtained from previous studies of the sample (infant formula, cerebrospinal fluid and blood). All isolates C. sakazakii identification based on microscopic, biochemical test and confirmed by 16SrRNA. We studied the movement of all isolates and study adhesion to polystyrene plate, adhesion and invasion to Esophageal adenocarcinoma (SKG-GT-4) for four isolates [Cerebrospinal fluid (CSF5), Bloods (B 1), Dialak (A1c), Novolac Allernova (C1)] and its cytotoxicity. Results showed that all isolates can move after 4 hours of incubation and increased after 8 hours, the isolates moved to different distances strong, medium, and weak. The results showed that the number of C. sakazakii colony adherent t

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