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Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  This research results showed that rapidly evolved Artificial Intelligence (AI) -based image analysis can accomplish high accuracy in detecting coronavirus infection as well as quantification and illness burden monitoring.

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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Estimate the Nonparametric Regression Function Using Canonical Kernel
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    This research aims to review the importance of estimating the nonparametric regression function using so-called Canonical Kernel which depends on re-scale the smoothing parameter, which has a large and important role in Kernel  and give the sound amount of smoothing .

We has been shown the importance of this method through the application of these concepts on real data refer to international exchange rates to the U.S. dollar against the Japanese yen for the period from January 2007 to March 2010. The results demonstrated preference the nonparametric estimator with Gaussian on the other nonparametric and parametric regression estima

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Publication Date
Sat Jan 01 2022
Journal Name
Lecture Notes In Electrical Engineering
Handling Mobility with Network Virtualization in IoT WAVE Context
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Realizing robust interconnectivity in a rapidly changing network topology is a challenging issue. This problem is escalating with the existence of constrained devices in a vehicular environment. Several standards have been developed to support reliable communication between vehicular nodes as the IEEE 1609 WAVE stack. Mitigating the impact of security/mobility protocols on limited capability nodes is a crucial aspect. This paper examines the burden of maintaining authenticity service that associated with each handover process in a vehicular network. Accordingly, a network virtualization-based infrastructure is proposed which tackles the overhead of IEEE 1906 WAVE standard on constrained devices existed in vehicular network. The virtualized

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Publication Date
Sat Jan 10 2015
Journal Name
British Journal Of Applied Science & Technology
The Use of Cubic Bezier Interpolation, Biorthogonal Wavelet and Quadtree Coding to Compress Color Images
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In this paper, an efficient method for compressing color image is presented. It allows progressive transmission and zooming of the image without need to extra storage. The proposed method is going to be accomplished using cubic Bezier surface (CBI) representation on wide area of images in order to prune the image component that shows large scale variation. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, bi-orthogonal wavelet transform is applied to decompose the residue component. Both scalar quantization and quad tree coding steps are applied on the produced wavelet sub bands. Finally, adaptive shift coding is applied to handle the remaining statistical redundancy and attain e

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
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Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

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Publication Date
Sat Jan 01 2022
Journal Name
3rd International Scientific Conference Of Alkafeel University (iscku 2021)
Prevalence of Entamoeba histolytica among enteric infection in Al-Furat general hospital in Baghdad/Iraq
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Publication Date
Wed Dec 14 2011
Journal Name
Journal Of Faculty Of Medicine Baghdad
The correlation between FEV1/ FVC with Arm span to height or chest to waist ratio as an index of pulmonary function in healthy subject.
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Abstract

Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Synthesis, Characteristics and Study the Photoluminscience of the CdSxSe1-x Nanocrystaline Thin Film
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 The present work focuses on the changing of the structural characteristics of the grown materials through different material characterization methods. Semiconductor CdSxSe 1-x nano crystallines have been synthesized by chemical vapor depostion. (X- ray Diffraction; XRD), (Field Emission Scanning Electron Microscopy; FESEM), measured the characterization of Semiconductor CdSxSe1-x nano crystallines. The optical properties of semiconductor CdSxSe1-x nanocrystallines have been studied by the photoluminescence (PL) (He-Cd pulsed ultraviolet laser at 325nm excitation wavelength) at room temperature. The results showed the change rule of photoluminsence peak at different S

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Publication Date
Sun Feb 10 2019
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Pregnant Women Knowledge toward Urinary Tract Infection in Primary Health Care Centers at Kirkuk City
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Abstract
Objective: To assess pregnant women Knowledge toward Urinary Tract Infection at Kirkuk City.


Methodology: A descriptive and analytical study was conducted from 1st of November 2013 and up to the 19 th of August 2014 in five typical primary health care centers at Kirkuk City. A Probability (randomly sample) was used to select the sample of 180 women aged (15-44) years. A questionnaire format was used as a tool for data collection , content validity of the questionnaire achieved through reviewing it by (24) experts in numerous scientific fields and reliability of the questionnaire was determined through a pilot study. Descriptive and inferential statistics were used to analyze the data.

 

Resul

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Publication Date
Tue Nov 11 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Validity of Hounsfield Units from computed tomographic images of mandibular bone in detection of osteoporosis
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Background: The figure for the clinical application of computed tomography have been increased significantly in oral and maxillofacial field that supply the dentists with sufficient data enables them to play a main role in screening osteoporosis, therefore Hounsfield units of mandibular computed tomography view used as a main indicator to predict general skeleton osteoporosis and fracture risk factor. Material and Methods: Thirty subjects (7 males &23 females) with a mean age of (60.1) years underwent computed tomographic scanning for different diagnostic assessment in head and neck region. The mandibular bone quality of them were determined through Hounsfield units of CT scan images and were correlated with the bone mineral density v

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Publication Date
Fri Feb 17 2023
Journal Name
Sustainability
Sustainable Utilization of Machine-Vision-Technique-Based Algorithm in Objective Evaluation of Confocal Microscope Images
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Confocal microscope imaging has become popular in biotechnology labs. Confocal imaging technology utilizes fluorescence optics, where laser light is focused onto a specific spot at a defined depth in the sample. A considerable number of images are produced regularly during the process of research. These images require methods of unbiased quantification to have meaningful analyses. Increasing efforts to tie reimbursement to outcomes will likely increase the need for objective data in analyzing confocal microscope images in the coming years. Utilizing visual quantification methods to quantify confocal images with naked human eyes is an essential but often underreported outcome measure due to the time required for manual counting and e

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