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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
Sun Aug 01 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Cascade-Forward Neural Network for Volterra Integral Equation Solution
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The method of solving volterra integral equation by using numerical solution is a simple operation but to require many memory space to compute and save the operation. The importance of this equation appeares new direction to solve the equation by using new methods to avoid obstacles. One of these methods employ neural network for obtaining the solution.

This paper presents a proposed method by using cascade-forward neural network to simulate volterra integral equations solutions. This method depends on training cascade-forward neural network by inputs which represent the mean of volterra integral equations solutions, the target of cascade-forward neural network is to get the desired output of this network. Cascade-forward neural

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Generative Adversarial Network for Imitation Learning from Single Demonstration
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Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

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Publication Date
Sun Jan 02 2022
Journal Name
Journal Of The College Of Languages (jcl)
The Effect of Genderism on the Process and the Product of Translation
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    Many studies have been made and still concerning the field of translation. Since the mid-90's a considerable amount of researches has tackled the problem of gender and its effect on the process and the product of translation. Simon (1996, p 508) points out that when comparing women and men as translators and writers through history, women seem to be the weaker side. This paves the way to feminist movements which produce prominent studies concerning gender as a concept and translator's gender as practice on the quality and the accuracy of the translation.           

     Flotow (in Meschia, 2012, p 1-4) outlines several issues that can be

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
ESTIMATION OF COEFFICIENTS AND SCALE PARAMETER FOR LINEAR (TYPE 1) EXTREME VALUE REGRESSION MODEL FOR LARGEST VALUES WITH APPLICATIONS
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In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients

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Publication Date
Sun Jan 01 2017
Journal Name
Al–bahith Al–a'alami
The Motivations of Using Facebook by Old People and their Achieved Need
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This research deals with the motives of the use of Facebook by elderly people and the achieved needs, which leads the researcher to ask an important question: why an old persons use Facebook and are the achieved needs through   which they got?  The research aims to find out the habits and patterns of using Facebook by old men and stands on the main motives of the elderly in their use of Facebook. It also identifies the most prominent needs that have been made for the elderly as a result of their use of Facebook.

The research is a descriptive one in which the researcher uses survey method to achieve the desired goals. The researcher has chosen a group of old men from Diyala province. The total sample number is about

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Publication Date
Mon Apr 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Measurement of Radioactivity in Some Commercial Porcelain Samples by Using HPGe Detector
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     Estimations of specific activity concentrations in eight commercial porcelain tiles made in different countries were performed by the use of HPGe detector. We have found that the highest specific activity concentrations for 238U, 40K were equal to (21.120 Bq/kg) and (283.862 Bq/kg) respectively, Iranian origin, while the highest specific activity concentration for 232Th was found to be equal to (29.292 Bq/kg), Iraqi origin; all of which were less than their corresponding recommended values given by (UNSCEAR, 2000). The radiation hazard indices [IÉ£ , Hin ,Hex , Raeq ,DÆ” , (AEDE) in and (AEDE) out] w

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Spatial Distribution of Heavy Element in Erbil's Municipal Landfills by Using GIS
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Untreated municipal solid waste (MSW) release onto land is prevalent in developing countries. To reduce the high levels of harmful components in polluted soils, a proper evaluation of heavy metal concentrations in Erbil's Kani Qrzhala dump between August 2021 and February 2022 is required. The purpose of this research was to examine the impact of improper solid waste disposal on soil properties within a landfill by assessing the risks of contamination for eight heavy elements in two separate layers of the soil by using geoaccumulation index (I-geo) and pollution load index (PLI) supported. The ArcGIS software was employed to map the spatial distribution of heavy element pollution and potential ecological risks. The I-geo values in summe

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Publication Date
Thu Jan 05 2012
Journal Name
مجلة كلية التربية الأساسية/ جامعة بابل / بحوث المؤتمر العلمي الرابع لكلية التربية الأساسية/جامعة بابل 2011 م
THE DYNAMIC EVOLUTION OF THE SHELL NEBULAE BY USING INTERACTING WIND MODEL
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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Turbid of Water By Using Fuzzy C- Means and Hard K- Means
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In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected  from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.

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Publication Date
Wed Jul 09 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Immunohistochemical study of CD34 in tooth eruption by using amniotic stem cells
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Background: Tooth eruption is a more general process, however, which includes certain posteruptive tooth movements. There are two fundamental requirements for both tooth eruption to occur: (1) Require soft tissue, intervening between tooth structure and alveolar bone, which plays an important role in regulating the remodeling of adjacent tissues. (2) Require bone turnover that is temporally and spatially regulated to facilitate specific translocations of teeth through alveolar bone These amniotic stem cells are multipotent and able to differentiate into various tissues, which may be useful for human application and recently it used in many medical branches. CD34 is an endothelial marker that is extensively used in immunohistochemistry a

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