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Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for de-noising noisy CCTV images. Data-store is used tomanage our dataset, which is an object or collection of data that are huge to enter in memory, it allows to read, manage, and process data located in multiple files as a single entity. The CAN architecture provides integral deep learning layers such as input, convolution, back normalization, and Leaky ReLu layers to construct multi-scale. It is also possible to add custom layers like adaptor normalization (µ) and adaptive normalization (Lambda) to the network. The performance of the developed CAN approximation operator on the bilateral filtering noisy image is proven when improving both the noisy reference image and a CCTV foggy image. The three image evaluation metrics (SSIM, NIQE, and PSNR) evaluate the developed CAN approximation visually and quantitatively when comparing the created de-noised image over the reference image.Compared with the input noisy image, these evaluation metrics for the developed CAN de-noised image were (0.92673/0.76253, 6.18105/12.1865, and 26.786/20.3254) respectively

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Publication Date
Tue Feb 01 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Finger Vein Recognition Based on PCA and Fusion Convolutional Neural Network
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Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Wireless Network Control System for Electro Stati Precipitator in Cement Plants
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    Wireless control networks (WCNs), based on distributed control systems of wireless sensor and actuator networks, integrate four technologies: control, computer network and wireless communications. Electrostatic precipitator (ESP) in cement plants reduces the emissions from rotary kiln by 99.8% approximately. It is an important thing to change the existing systems (wireline) to wireless because of dusty and hazardous environments. In this paper, we designed a wireless control system for ESP using Truetime 2 beta 6 simulator, depending on the mathematical model that have been built using identification toolbox of Matlab v7.1.1. We also study the effect ofusing wireless network on performance and stability of the closed l

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Publication Date
Fri Apr 28 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Design Optimal Neural Network for Solving Unsteady State Confined Aquifer Problem
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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Lead acetate deteriorates the improvement effect of L-arginine and tetrahydrobiopterin on endothelin-1 receptors activity in rat aorta
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Endothelin-1 (ET-1) is a potent vasoconstrictor hormone that has been identified as an important factor
responsible for the development of cardiovascular dysfunctions. ET-1 exerts its vasoconstrictor activity
through two pharmacologically distinct receptors, ETA and ETB that are found in vascular smooth muscle
cells (VSMCs) and the vasodilator activity through an ETB receptor located on endothelial cells. This study
aimed to show the impact of 1µM L-arginine (LA), 100µM tetrahydrobiopterin (BH4), and their combined
effect on ET-1 activity in both lead-treated and lead-untreated rat aortic rings. This means, investigating how
endothelial dysfunction reverses the role of nitric oxide precursor and cofa

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Publication Date
Sun Dec 31 2023
Journal Name
College Of Islamic Sciences
The relationship between the rule of mental improvement and ugliness and the objectives of Sharia And its impact on rulings
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The research addresses a fundamental Islamic jurisprudential Purposeful issue, which is (Sharia), and to indicate the impact of this on Islamic jurisprudence, deriving rulings and extracting purposes, and to repel the illusion that this issue is only doctrinal, and clarifying the aspects of similarities and links between them by explaining the origin of deriving the purposes of Islamic Law (Sharia) through the meanings and wisdom learned from the texts and the explanation of the rulings. The rulings of Islamic Law (Sharia) have urged bringing benefits and repelling harms, and that the path to do so is reason and its production. I began the research by defining the purposes of Islamic Law (Sharia), then defining the rule of rational right

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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
Mono-Multi Vision and Its Relationship to Psychological Rebellion and Personality Traits of University Students
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The current research seeks to identify mono-multi Vision and its relation to the psychological rebellion and personality traits of university students. To achieve this aim, the researcher has followed all the procedures of the descriptive correlational approach, as it is the closest approach to the objectives of the current research. The researcher has determined his research community for Baghdad University students for the academic year 2019-2020. As for the research sample, it was chosen by the random stratified method with a sample of (500) male and female students. In order to collect data from the research sample, the researcher adopted a mono-multi-dimensional scale

(Othman, 2007), the researcher designed a psychological r

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Publication Date
Tue Dec 20 2022
Journal Name
Iraqi Journal Of Biotechnology
Synergistic Effect of Conocarpus erectus Extract and some Antibiotics against Multi-Drug Resistant Pseudomonas aeruginosa
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Over the past few decades, the health benefits are under threat as many commonly used antibiotics have become less and less effective against certain illnesses not only because many of them produce toxic reactions but also due to the emergence of drug-resistant bacteria. The clinical use of a combination of antibiotic therapy for Pseudomonas aeruginosa infections is probably more effective than monotherapy. The present study aims to estimate the antibacterial and antibiofilm activity of Conocarpus erectus leaves extracts against multi-drug resistant P. aeruginosa isolated from different hospitals in Baghdad city. One hundred fifty different clinical specimens were collected from patients from September 2021 to January 2022. All samples were

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Publication Date
Thu Jan 16 2025
Journal Name
International Journal Of Data And Network Science
Multi-objective of wind-driven optimization as feature selection and clustering to enhance text clustering
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Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t

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Publication Date
Wed Feb 06 2019
Journal Name
International Journal Of Dynamics And Control
Biomechanics, actuation, and multi-level control strategies of power-augmentation lower extremity exoskeletons: an overview
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Publication Date
Tue Jan 30 2018
Journal Name
Iraqi Journal Of Science
An Improve Image Encryption Algorithm Based on Multi-level of Chaotic Maps and Lagrange Interpolation
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Currently no one can deny the importance of data protection, especially with the proliferation of hackers and theft of personal information in all parts of the world .for these reasons the encryption has become one of the important fields in the protection of digital information.
This paper adopts a new image encryption method to overcome the obstacles to previous image encryption methods, where our method will be used Duffing map to shuffled all image pixels ,after that the resulting image will be divided into a group of blocks for perform the shuffling process via Cross Chaotic Map.
Finally, an image called key image was created by using Quadratic number spirals which will be used to generate nu

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