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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 Jan 01 2023
Journal Name
Chemical Engineering And Processing - Process Intensification
Optimization of a combined electrocoagulation-electro-oxidation process for the treatment of Al-Basra Majnoon Oil field wastewater: Adopting a new strategy
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The performance of a synergistic combination of electrocoagulation (EC) and electro-oxidation (EO) for oilfield wastewater treatment has been studied. The effect of operative variables such as current density, pH, and electrolyte concentration on the reduction of chemical oxygen demand (COD) was studied and optimized based on Response Surface Methodology (RSM). The results showed that the current density had the highest impact on the COD removal with a contribution of 64.07% while pH, NaCl addition and other interactions affects account for only 34.67%. The optimized operating parameters were a current density of 26.77 mA/cm2 and a pH of 7.6 with no addition of NaCl which results in a COD removal efficiency of 93.43% and a specific energy c

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Publication Date
Wed May 15 2019
Journal Name
Tikrit Journal Of Pure Science
Improvement of Alert System against Tampering and Theft in Surveillance Cameras
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Use of Surveillance cameras in houses and markets became common, that resulted to minimize theft and make it a difficult task because it let recording and viewing what is going around. The wide application of these cameras, pushed thieves to seek new ways for abolition of the surveillance system and digital recording of events, such as cutting the signal wire between the camera and Digital video recorder or changing the direction of the camera away from the focus spot or damaging the camera or steal the device which means the loss of the recorded media. This paper focuses on such abolitions and fixed it by suggesting a way to notify the administrator immediately and automatically by Email about any violation of the system using MATLAB, whic

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Improvement of thermostable productivity ?-amylase from local isolate Bacillus licheniformis H14.
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(28)Bacterial local isolates of Bacillus sp. were obtained from soil samples. Isolates were tested for thermostable alpha- amylase production on solid media; fifteen isolates were able to develop clear zone around the bacterial growth after floating the plates with iodine reagent (Lugol's solution). There were further tested in submerged culture which led to selection of Bacillus sp. H14since it was the most efficient .Microbial and biochemical tests showed that the local isolate Bacillus sp.H14was refered to the species B.licheniformis that signed as H14 was refered to the species B.licheniformis H14 .,To get ahigher yield of alpha – amylase(48.70unit/mg protein) production from the local isolate B.licheniformis H14 . This study used

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Publication Date
Thu Jun 10 2010
Journal Name
Iraqi Journal Of Laser
Improvement of Nonlinear Optical Properties for Mixture Laser Dyes Doped PMMA
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The spectral characteristics and the nonlinear optical properties of the mixed donor (C-480) acceptor (Rh-6G) have been determined. The spectral characteristics are studied by recording their absorption and fluorescence spectra. The nonlinear optical properties were measured by z-scan technique, using Q-switched Nd: YAG laser with 1064 nm wavelength. The results showed that the optimum concentration of acceptor is responsible for increasing the absorption and the emission bandwidth of donor to full range and to 242 nm respectively by the energy transfer process, also the efficiency of the process was increased by increasing the donor and acceptor concentration. The obtained nonlinear properties results of the mixture C-480/ Rh-6G showed

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Publication Date
Sat Mar 01 2008
Journal Name
Iraqi Journal Of Physics
Comparison between Different Data Image Compression Techniques Applied on SAR Images
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In this paper, image compression technique is presented based on the Zonal transform method. The DCT, Walsh, and Hadamard transform techniques are also implements. These different transforms are applied on SAR images using Different block size. The effects of implementing these different transforms are investigated. The main shortcoming associated with this radar imagery system is the presence of the speckle noise, which affected the compression results.

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Publication Date
Thu Nov 01 2012
Journal Name
Journal Of Computer Science
VOICE ACTIVATION VISUALIZATION FOR ECHOCARDIOGRAPH AND 3D ANGIOGRAPHIC IMAGES IN SURGERY
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In some cases, surgeons need to navigate through the computer system for reconfirmation patients’ details and unfortunately surgeons unable to manage both computer system and operation at the same time. In this paper we propose a solution for this problem especially designed for heart surgeon, by introducing voice activation system with 3D visualization of Angiographic images, 2D visualization of Echocardiography processed video and selected patient’s details. In this study, the processing, approximation of the 3D angiography and the visualization of the 2D echocardiography video with voice recognition control are the most challenging work. The work involve with predicting 3D coronary three from 2D angiography image and also image enhan

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Facial Emotion Images Recognition Based On Binarized Genetic Algorithm-Random Forest
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Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

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Publication Date
Fri Sep 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Coagulation-Flocculation process to treat Pulp and Paper Mill Wastewater by Fenugreek Mucilage Coupled with Alum and Polyaluminum Chloride
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The wastewater arising from pulp and paper mills is highly polluted and has to be treated before discharged into rivers. Coagulation-flocculation process using natural polymers has grown rapidly in wastewater treatment. In this work, the performance of alum and Polyaluminum Chloride (PACl) when used alone and when coupled with Fenugreek mucilage on the treatment of pulp and paper mill wastewater were studied. The experiments were carried out in jar tests with alum, PACl and Fenugreek mucilage dosages range of 50-2000 mg/L, rapid mixing at 200 rpm for 2 min, followed by slow mixing at 40 rpm for 15 min and settling time of 30 min. The effectiveness of Fenugreek mucilage was measured by the reduction of turbidity and Chemical Oxygen Demand

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Publication Date
Mon Oct 17 2016
Journal Name
Proceedings Of The Institution Of Mechanical Engineers, Part B: Journal Of Engineering Manufacture
Development and control of shaped metal deposition process using tungsten inert gas arc heat source in additive layered manufacturing
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Tungsten inert gas arc welding–based shaped metal deposition is a novel additive manufacturing technology which can be used for fabricating solid dense parts by melting a cold wire on a substrate in a layer-by-layer manner via continuous DC arc heat. The shaped metal deposition method would be an alternative way to traditional manufacturing methods, especially for complex featured and large-scale solid parts manufacturing, and it is particularly used for aerospace structural components, manufacturing, and repairing of die/molds and middle-sized dense parts. This article presents the designing, constructing, and controlling of an additive manufacturing system using tungsten inert gas plus wire–based shaped metal deposition metho

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison of Parameters Estimation Methods for the Negative Binomial Regression Model under Multicollinearity Problem by Using Simulation
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This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators

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