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An Adaptive Digital Neural Network-Like-PID Control Law Design for Fuel Cell System Based on FPGA Technique
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This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fuel cell system and to achieve the stability of the desired output voltage of fuel cell. The numerical simulation results (MATLAB) package along with the schematic design experimental work using Spartan-3E xc3s500e-4fg320 board with the Xilinx development tool Integrated Software Environment (ISE) version 14.7 and using Verilog hardware description language for design testing are illustrated the performance enhancement of the proposed an adaptive intelligent FPGA-PID-NN controller in terms of error voltage reduction and generating optimal value of the hydrogen partial pressure action (PH2) without oscillation in the output and no saturation state when these results are compared with other controllers.

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Publication Date
Thu Mar 01 2007
Journal Name
Al-khwarizmi Engineering Journal
Image restoration using regularized inverse filtering and adaptive threshold wavelet denoising
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Although the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose .

                In this paper  a new image restoration scheme is proposed, the scheme contains two separate steps : Fourier-domain inverse filtering  and wavelet-domain image denoising. The first stage is Wiener filtering of the input image , the filtered image is inputted to adaptive threshold wavelet

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Publication Date
Wed Feb 29 2012
Journal Name
Al-khwarizmi Engineering Journal
Color Image Denoising Using Stationary Wavelet Transform and Adaptive Wiener Filter
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The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing.  Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds.  This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

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Publication Date
Mon Oct 17 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

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Publication Date
Tue Jun 22 2021
Journal Name
Expert Systems
Hybrid intelligent technology for plant health using the fusion of evolutionary optimization and deep neural networks
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Publication Date
Thu Sep 12 2019
Journal Name
Al-kindy College Medical Journal
Toll like receptor 2(TLR2) in acne vulgaris patients before and after oral isotretinion therapy
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Background: Acne vulgaris is one of the top three most commonly encountered dermatological problems worldwide in both primary and secondary care. Human keratinocytes express functional TLR2 heterodimers. An increased expression of TLR2 was detected in the epidermis of inflammatory acne lesions, as observed in normal skin; the expression level increased with the degree of differentiation of the keratinocytes. TLR2 expression is upregulated in inflammatory acne lesions and induced by C. acnes. The current study conducted to assess the oral isotretinion treatment effect on the acne vulgaris patients by  evaluated the Toll Like Receptor 2 as a major  immune system marker in Acne vulgaris immune re

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Publication Date
Fri Feb 01 2019
Journal Name
Indian Journal Of Public Health Research
Determination of Glucagon-Like Peptide-1 and Dipeptidyl Peptidase-4 Levels in Diabetic Nephropathy Patients
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Publication Date
Fri Jun 16 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Ameliorating Effect of Oral Paquinimod Administration against Imiquimod Induced Psoriasis-like Inflammation in Mice
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               Psoriasis is a chronic, inflammatory condition that primarily affects the skin, hair, and joints and is associated with significant humanistic and economic consequences. Psoriasis was induced in mice in this work using an imiquimod 5% cream, an immune response modifier that can cause psoriasis-like skin inflammation when given orally. Paquinimod is prepared as a suspension and has been orally given to mice before imiquimod application. The current study found that paquinimod suspension reduced psoriasis area and severity index, spleen index, skin thickness ,TNF-α,IL-23,IL17 level and gene expression of TN

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Publication Date
Wed Mar 15 2023
Journal Name
Bionatura
Immune-protective effect of topical paquinimod administration against imiquimod-induced psoriasis-like inflammation in mice
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Psoriasis is a chronic, inflammatory condition that primarily affects the skin, hair, and joints and is associated with significant humanistic and economic consequences. This work induced psoriasis in mice using an imiquimod 5% cream, an immune response modifier that can cause psoriasis-like skin inflammation when given orally. Paquinimod is prepared as an ointment and has been topically given to mice before imiquimod application. In this study, albino mice were allocated into five groups and treated as follows: the control group received only a daily application of cream based on shaved back (62.5mg/2cm) with a daily topical dose of ointment for 14 consecutive days with the oral vehicle. The Imiquimod group received a daily topical

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Publication Date
Sat Nov 01 2014
Journal Name
I-manager's Journal On Information Technology
AN ENHANCED METHOD FOR SPRITE EXTRACTING
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The extracting of personal sprite from the whole image faced many problems in separating the sprite edge from the unneeded parts, some image software try to automate this process, but usually they couldn't find the edge or have false result. In this paper, the authors have made an enhancement on the use of Canny edge detection to locate the sprite from the whole image by adding some enhancement steps by using MATLAB. Moreover, remove all the non-relevant information from the image by selecting only the sprite and place it in a transparent background. The results of comparing the Canny edge detection with the proposed method shows improvement in the edge detection.