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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
Wed Mar 01 2023
Journal Name
Baghdad Science Journal
A Study on Nψβ and Nβψ - Closed sets in Neutrosophic Topological spaces
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The aim of this paper is to introduce the concept of N  and Nβ -closed sets in terms of neutrosophic topological spaces. Some of its properties are also discussed.

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Publication Date
Tue Dec 31 2024
Journal Name
Indian Journal Of Clinical Biochemistry
Farnesoid X Receptor-Mediated Bile Acids Regulation in Cholestasis
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The main process, for the elimination of cholesterol from the human body, involves the alteration of cholesterol into bile acid (BA), by the liver. The farnesoid X receptor (FXR), a member of the nuclear receptor superfamily, is essential for the regulation of BA, glucose, and lipid metabolism. It is largely found in the liver, intestines, kidney, and adrenal glands, and to a smaller degree in the heart and adipose tissue. The binding locations, of the FXR, are in close proximity to formerly undisclosed target genes, with distinctive activities associated with transcriptional regulators, autophagy, apoptosis, hypoxia, inflammation, RNA processing, and a number of cellular signaling pathways. The preservation of BA homeostasis, by the FXR, e

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Publication Date
Thu May 30 2024
Journal Name
Iraqi Journal Of Science
A Review Study on Forgery and Tamper Detection Techniques in Digital Images
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Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou

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Publication Date
Mon Nov 01 2010
Journal Name
Iraqi Journal Of Physics
The Effect of Germanium Content(x) on the Electrical Properties of (Gex S1-x) Thin Films
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Thin films of GexS1-x were fabricated by thermal evaporating under vacuum of 10-5Toor on glass substrate. The effect of increasing of germanium content (x) in sulfide films on the electrical properties like d.c conductivity (σDC), concentration of charge carriers (nH) and the activation energy (Ea) and Hall effect were investigated. The measurements show that (Ea) increases with the increasing of germanium content from 0.1to0.2 while it get to reduces with further addition, while charge carrier density (nH) is found to decrease and increase respectively with germanium content. The results were explained in terms of creating and eliminating of states in the band gap

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Review of the Mechanisms for Preventing, Diagnosing, and Treatment of Pipe Sticking in Drilling Operations
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Stuck pipe is a prevalent and costly issue in drilling operations, with the potential to cost the petroleum industry billions of dollars annually. To reduce the likelihood of this issue, efforts have been made to identify the causes of stuck pipes. The main mechanisms that cause stuck pipes include drill cutting of the formation, inappropriate hole-cleaning, wellbore instability, and differential sticking forces, particularly in highly deviated wellbores. The significant consequences of a stuck pipe include an increase in well costs and Non-Productive Time (NPT), and in the worst-case scenario, the loss of a wellbore section and down-hole equipment, or the need to sidetrack, plug, or abandon the well. This paper provides a comprehensive

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Publication Date
Sun May 15 2022
Journal Name
Al-kindy College Medical Journal
A serology conundrum – HIV infection in acute babesiosis infection could merely be a false positive result
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Babesiosis is a tick-borne disease caused by Babesia microti. We present a case of false positive HIV in the setting of confirmed babesiosis infection. An understanding that patients with babesiosis can have a false positive HIV test result is important in management decisions.

 

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Publication Date
Tue Jan 01 2013
Journal Name
Thesis
User Authentication Based on Keystroke Dynamics Using Artificial Neural Networks
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Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

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Publication Date
Thu Aug 02 2012
Journal Name
International Journal Of Advanced Research In Computer Science
User Authentication based on Keystroke Dynamics Using Backpropagation Network
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Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi

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Publication Date
Sat Jun 01 2024
Journal Name
Civil And Environmental Engineering
Constructing a Corrected Stations Network Using Some Geomatic Techniques
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Abstract<p>The major objective of this study is to establish a network of Ground Control Points-GCPs which can use it as a reference for any engineering project. Total Station (type: Nikon Nivo 5.C), Optical Level and Garmin Navigator GPS were used to perform traversing. Traversing measurement was achieved by using nine points covered the selected area irregularly. Near Civil Engineering Department at Baghdad University Al-jadiriya, an attempt has been made to assess the accuracy of GPS by comparing the data obtained from the Total Station. The average error of this method is 3.326 m with the highest coefficient of determination (R<sup>2</sup>) is 0.077 m observed in Northing. While in</p> ... Show More
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Publication Date
Wed Apr 01 2020
Journal Name
Plant Archives
Land cover change detection using satellite images based on modified spectral angle mapper method
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This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

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