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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
Mon Jul 11 2022
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Dynamic Background Subtraction in Video Surveillance Using Color-Histogram and Fuzzy C-Means Algorithm with Cosine Similarity
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The background subtraction is a leading technique adopted for detecting the moving objects in video surveillance systems. Various background subtraction models have been applied to tackle different challenges in many surveillance environments. In this paper, we propose a model of pixel-based color-histogram and Fuzzy C-means (FCM) to obtain the background model using cosine similarity (CS) to measure the closeness between the current pixel and the background model and eventually determine the background and foreground pixel according to a tuned threshold. The performance of this model is benchmarked on CDnet2014 dynamic scenes dataset using statistical metrics. The results show a better performance against the state-of the art

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Publication Date
Sat Jan 01 2022
Journal Name
3rd International Scientific Conference Of Alkafeel University (iscku 2021)
Exposure and etching time effects on the fission track density in CR-39 detectors using teeth samples
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Publication Date
Sat Apr 01 2017
Journal Name
2017 International Conference On Environmental Impacts Of The Oil And Gas Industries: Kurdistan Region Of Iraq As A Case Study (eiogi)
Inverse fluidized bed for chromium ions removal from wastewater and produced water using peanut shells as adsorbent
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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Dynamic algorithm (DRBLTS) and potentially weighted (WBP) to estimate hippocampal regression parameters using a techniqueBootstrap (comparative study)
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Bootstrap is one of an important re-sampling technique which has given the attention of  researches recently. The presence of outliers in the original data set may cause serious problem to the classical bootstrap when the percentage of outliers are higher than the original one. Many methods are proposed to overcome this problem such  Dynamic Robust Bootstrap for LTS (DRBLTS) and Weighted Bootstrap with Probability (WBP). This paper try to show the accuracy of parameters estimation by comparison the results of both methods. The bias , MSE and RMSE are considered. The criterion of the accuracy is based on the RMSE value since the method that provide us RMSE value smaller than other is con

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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
comparison between the methods estimate nonparametric and semiparametric transfer function model in time series the Using simulation
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 The transfer function model the basic concepts in the time series. This model is used in the case of multivariate time series. As for the design of this model, it depends on the available data in the time series and other information in the series so when the representation of the transfer function model depends on the representation of the data In this research, the transfer function has been estimated using the style nonparametric represented in two method  local linear regression and cubic smoothing spline method The method of semi-parametric represented use semiparametric single index model, With four proposals, , That the goal of this research is comparing the capabilities of the above mentioned m

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Publication Date
Wed Mar 01 2023
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Design and implementation monitoring robotic system based on you only look once model using deep learning technique
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<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Publication Date
Sun Mar 06 2011
Journal Name
Baghdad Science Journal
Studying of the optical properties of poly (vinyl alcohol) films using Aluminum sulphate as additive by measuring allowed direct transition energy gap
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The change in the optical band gap and optical activation energy have been investigated for pure Poly (vinyl alcohol)and Poly (vinyl alcohol) doped with Aluminum sulphate to proper films from their optical absorption spectra. The absorption spectra were measured in the wave range from (200-700) nm at temperature range (25-140) 0C. The optical band gap (Eg) for allowed direct transition decrease with increase the concentration of Aluminum sulphate. The optical activation energy for allowed direct transition band gap was evaluated using Urbach- edges method. It was found that ?E increases with increasing the concentration of Al2 (SO4)3 and decreases when temperature increases.

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Publication Date
Thu Jun 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Drilling Optimization by Using Advanced Drilling Techniques in Buzurgan Oil Field
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Efficient and cost-effective drilling of directional wells necessitates the implementation of best drilling practices and advanced techniques to optimize drilling operations. Failure to adequately consider drilling risks can result in inefficient drilling operations and non-productive time (NPT). Although advanced drilling techniques may be expensive, they offer promising technical solutions for mitigating drilling risks. This paper aims to demonstrate the effectiveness of advanced drilling techniques in mitigating risks and improving drilling operations when compared to conventional drilling techniques. Specifically, the advanced drilling techniques employed in Buzurgan Oil Field, including vertical drilling with mud motor, managed pres

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Publication Date
Mon Mar 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Petrophysical Properties of an Iraqi Carbonate Reservoir Using Well Log Evaluation
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This research was aimed to determine the petrophysical properties (porosity, permeability and fluid saturation) of a reservoir. Petrophysical properties of the Shuiaba Formation at Y field are determined from the interpretation of open hole log data of six wells. Depending on these properties, it is possible to divide the Shuiaba Formation which has thickness of a proximately 180-195m, into three lithological units: A is upper unit (thickness about 8 to 15 m) involving of moderately dolomitized limestones; B is a middle unit (thickness about 52 to 56 m) which is composed of dolomitic limestone, and C is lower unit ( >110 m thick) which consists of shale-rich and dolomitic limestones. The results showed that the average formation water

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