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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 Jan 14 2021
Journal Name
Iraqi Journal Of Science
FM Based Localization: A Proposed Improvement
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Localization is an essential issue in pervasive computing application. FM performs worse in some indoor environment when its structure is same to some extent the outdoor environment like shopping mall. Furthermore, FM signal are less varied over time, low power consumption and less effected by human and small object presence when it compared to Wi-Fi. Consequently, this paper focuses on FM radio signal technique and its characteristics that make it suitable to be used for indoor localization, its benefits, areas of applications and limitations.

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Development an Anomaly Network Intrusion Detection System Using Neural Network
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Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Rainwater Drainage Service Improvement Using a Number Of Quality Tools at the Directorate of Karbala Sewage
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The basic objective of the research is to study the quality of the water flow service in the Directorate of Karbala sewage and how to improve it after identifying the deviations of the processes and the final product and then providing the possible solutions in addressing the causes of the deviations and the associated quality gaps. A number of quality tools were used and applied to all data Stations with areas and activities related to the drainage of rainwater, as the research community determines the stations of lifting rainwater in the Directorate of the streams of Karbala holy, and the station was chosen Western station to apply the non-random sampling method intended after meeting a number of. It is one of the largest and m

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Publication Date
Thu Jan 14 2021
Journal Name
Iraqi Journal Of Science
Highly-Performed Fuzzily-logicized Edge Detecting Algorithm for Noisy Handwritings
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The main targets for using the edge detection techniques in image processing are to reduce the number of features and find the edge of image based-contents. In this paper, comparisons have been demonstrated between classical methods (Canny, Sobel, Roberts, and Prewitt) and Fuzzy Logic Technique to detect the edges of different samples of image's contents and patterns. These methods are tested to detect edges of images that are corrupted with different types of noise such as (Gaussian, and Salt and pepper). The performance indices are mean square error and peak signal to noise ratio (MSE and PSNR). Finally, experimental results show that the proposed Fuzzy rules and membership function provide better results for both noisy and noise-free

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Hiding Information Using different lighting Color images
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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Science
Copy Move Forgery Detection Using Forensic Images
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     Digital images are open to several manipulations and dropped cost of compact  cameras and mobile phones due to the robust image editing tools. Image credibility is therefore become doubtful, particularly where photos have power, for instance, news reports and insurance claims in a criminal court. Images forensic methods therefore measure the integrity of image  by apply different highly technical methods established in literatures. The present work deals with copy move forgery images of Media Integration and Communication Center Forgery (MICC-F2000) dataset for detecting and revealing the areas that have been tampered portion in the image, the image is sectioned into non overlapping blocks using Simple

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Publication Date
Fri Jul 01 2022
Journal Name
Iraqi Journal Of Science
Extractive Multi-Document Text Summarization Using Multi-Objective Evolutionary Algorithm Based Model
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Automatic document summarization technology is evolving and may offer a solution to the problem of information overload. Multi-document summarization is an optimization problem demanding optimizing more than one objective function concurrently. The proposed work considers a balance of two significant objectives: content coverage and diversity while generating a summary from a collection of text documents. Despite the large efforts introduced from several researchers for designing and evaluating performance of many text summarization techniques, their formulations lack the introduction of any model that can give an explicit representation of – coverage and diversity – the two contradictory semantics of any summary. The design of gener

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Publication Date
Mon Apr 04 2022
Journal Name
Journal Of Educational And Psychological Researches
Constructing a Scale of Emotional Adjustment among Kindergarten Children
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The aim of the current research is to construct a scale of emotional adjustment for kindergarten children and to set a standard for its evaluation. To achieve this, a scale consisting of (19) items was prepared. The mother of the child answered by adopting the method of self-report, which is expressed in the form of reporting terms, as each item represents a situation in the child's life and each situation has three alternatives to answer that represent various responses to the mentioned situation. One of the alternatives represents the emotionally adaptive response, which is given a degree (3), the second response expresses the emotional adjustment partly that took the degree of (2), and the third response expresses the weakness of emot

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Publication Date
Mon Aug 07 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Equilibrium Isotherm Removal OF Chromium From Waste Water By Aquatic Plants Using Batch Process Adsorption
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      This study was carried out in Baghdad (Al-Jadiriya) in 2006 by  detecting ability of aquatic reed plant to remove heavy metals (Chromium) from waste water by batch process of adsorption with considering that acidic solution is best selection for such process with constant initial chromium concentration(60 mg/l),speed of shaking(300 rpm), temperature (30 Co) and constant contact time (4 h) but with different weights of adsorbent (reed) (0.5 ,1 ,2 ,3 and 4 )gm for each 100 ml volume of sample .          The results showed that the percentage of the removed chromium were ( 8% ,17.5% ,31% ,40% and 50%) respectively for each sample according to the mass of adsorb

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Publication Date
Fri Mar 01 2019
Journal Name
Archives Of Plastic Surgery
Surgical outcomes of 14 consecutive bilateral cleft lip patients treated with a modified version of the Millard and Manchester methods
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Background Bilateral cleft lip deformity is much more difficult to correct than unilateral cleft lip deformity. The complexity of the deformity and the sensitive relationships between the arrangement of the muscles and the characteristics of the external lip necessitate a comprehensive preoperative plan for management. The purpose of this study was to evaluate the repair of bilateral cleft lip using the Byrd modification of the traditional Millard and Manchester methods. A key component of this repair technique is focused on reconstruction of the central tubercle.

Methods Fourteen patients with mean age of 5.7 months presented with bilateral cleft lip deformity and were operated on using a mod

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