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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
Thu Oct 01 2009
Journal Name
Iraqi Journal Of Physics
Gray-Scale Image Brightness/Contrast Enhancement with Multi-Model Histogram linear Contrast Stretching (MMHLCS) method
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Gray-Scale Image Brightness/Contrast Enhancement with Multi-Model
Histogram linear Contrast Stretching (MMHLCS) method

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Publication Date
Mon May 01 2023
Journal Name
Chemical Engineering Research And Design
Treatment of petroleum refinery wastewater by electrofenton process using a low cost porous graphite air-diffusion cathode with a novel design
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Publication Date
Sat Jun 03 2023
Journal Name
Iraqi Journal Of Science
Alteration of cell aggregation and adhesion in Dictyostelium amoeba by an overexpression of paracaspase protein
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Dictyostelium discoideum amoeba is a powerful system to study gene function through genetic and functional analysis. Paracaspase (Pcp) is a caspase-like protein that has recently identified in D. discoideum. Study paracaspase molecular function in Dictyostelium will provide insight into its cellular role in more complex organisms and the possibility to use it as a drug target against the parasitic amoeba. In this study, pcp was tagged with Green Fluorescent Protein (GFP) and over-expressed in the cell. The knockout version of pcp (pcp-) was also investigated. In the course of our examination, it was observed that cells overexpress Pcp was unable to complete the developmental process, leading us to examine its role in development. Those c

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Distinguishing Shapes of Breast Cancer Masses in Ultrasound Images by Using Logistic Regression Model
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The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

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Publication Date
Wed Nov 28 2018
Journal Name
International Journal Of Engineering & Technology
Improvement of Gypsum Soil by Using Polyurethane to Reduce Erosion and Solubility of Irrigation Canals
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The reducing of erosion and the solubility of irrigation canals soils which constructed on gypsum soil is important in civil and water resources engineering. The main problem of gypsum soils is the presence of gypsum which represents one of most complex engineering problems, especially when accompanied by the moving of water which represent dynamic load along the canal. There are several solutions to this problem, in this research “Poly urethane” is used to give the gypsum soil sufficient hardness to reduce the solubility and erosion, after compacting the soil in the canal, percentages of Poly urethane was used to making cover to the soil by mixing percent of soil with Poly urethane, and the ratio was as follows: (5 and 10) % an

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Publication Date
Mon Mar 01 2010
Journal Name
Basrah Journal Of Science
Hiding Three Images at one image by Using Wavelet Coefficients at Color Image
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Publication Date
Thu May 05 2016
Journal Name
Global Journal Of Engineering Science And Researches
EVALUATE THE RATE OF CONTAMINATION SOILS BY COPPER USING NEURAL NETWORK TECHNIQUE
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The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

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Publication Date
Sat Feb 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Solve travelling sales man problem by using fuzzy multi-objective linear programming
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   The main focus of this research is to examine the Travelling Salesman Problem (TSP) and the methods used to solve this problem where this problem is considered as one of the combinatorial optimization problems which met wide publicity and attention from the researches for to it's simple formulation and important applications and engagement to the rest of combinatorial problems , which is based on finding the optimal path through known number of cities where the salesman visits each city only once before returning to the city of departure n this research , the benefits  of( FMOLP)   algorithm is employed as one of the best methods to solve the (TSP) problem and the application of the algorithm in conjun

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Context and its influence in direction of reference by Abi Hussein Al Basri
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Context and its influence in direction of reference by Abi Hussein Al Basri

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Publication Date
Wed Mar 20 2019
Journal Name
Al-khwarizmi Engineering Journal
Improvement of Mechanical and Fatigue Properties for Aluminum Alloy 7049 By Using Nano Composites Technique
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The aim of present work is to improve mechanical and fatigue properties for Aluminum alloy7049 by using Nano composites technique. The ZrO2 with an average grain diameter of 30-40 nm, was selected as Nano particles, to reinforce Aluminum alloy7049 with different percentage as, 2, 4, 6 and 7 %. The Stir casting method was used to fabricate the Nano composites materials due to economical route for improvement and processing of metal matrix composites. The experimental results were shown that the adding of zirconium oxide (ZrO2) as reinforced material leads to improve mechanical properties. The best percentage of improvement of mechanical properties of 7049 AA was with 4% wt. of ZrO2 about (7.76% ) for ultim

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