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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 Nov 10 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Hybridization Methodology of ARMA-FIGARCH Model to Examine Gasoline Data in Iraq
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Publication Date
Wed Dec 04 2013
Journal Name
1st Post – Graduate Students Conference, Alnahrain University / College Of Engineering
Convection Heat Transfer in Horizontal Annulus Porous Media with Rotating Outer Cylinder
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A numerical investigation of mixed convection in a horizontal annulus filled with auniform fluid-saturated porous medium in the presence of internal heat generation is carried out.The inner cylinder is heated while the outer cylinder is cooled. The forced flow is induced by thecold outer cylinder rotating at a constant angular velocity. The flow field is modeled using ageneralized form of the momentum equation that accounts for the presence of porous mediumviscous, Darcian and inertial effects. Discretization of the governing equations is achieved usinga finite difference method. Comparisons with previous works are performed and the results showgood agreement. The effects of pertinent parameters such as the Richardson number and internalRay

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Global Pharma Technology
GC/MS analysis of terpenes of Boswellia serrata resin found in Iraq
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Objective: The aim of this work was to detect terpenes other than boswellic acid derivatives in olibanum of Boswellia Serrata found in Iraq. Methods: The olibanum of Boswellia Serrata was macerated in methanol for one day, then filtration. Filter at was concentrated till reddish brown syrupy residue was gained, (3%) potassium hydroxide was added till basification. This basic solution was stirred continuously until a uniform emulsion was formed, then extracted with chloroform in a separatory funnel; the chloroform fraction was analyzed by GC /MS spectrometry. Results: GC /MS analysis reveal the presence of terpenes and non-terpenes constituents. Conclusion: Most of the detected terpenes were sesquiterpenes and the least one was di-terpenes.

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Publication Date
Sun Oct 15 2023
Journal Name
Revista Bionatura
Estimation of amino acid concentrations in the kidney of albino mice embryo
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Amino acids are the basic building block for peptides and proteins. They are raw materials for generating hormones, purines, pyrimidines and vitamins. Amino acids also provide the body with energy through their carbon structures. The study analyzed the amino acid in the kidneys of the albino mice embryo at 17 and 19 gestation days, using a high-performance liquid chromatography device (HPLC). Samples were obtained after removing them from the embryo and placing them in an ice bath to prevent cell lysis and acid loss. The study found 18 amino acids in the kidneys of the albino mice embryo. They are Asparagine (Asn), Glutamine (Glu), Serine (Ser), Glycine (Gly), Threonine (Thr), Histidine (His), Cysteine (Cys), Alanine (Ala), Proline

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Publication Date
Fri Aug 30 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
Artificial Intelligence and Cybersecurity in Face Sale Contracts: Legal Issues and Frameworks
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The sale of facial features is a new modern contractual development that resulted from the fast transformations in technology, leading to legal, and ethical obligations. As the need rises for human faces to be used in robots, especially in relation to industries that necessitate direct human interaction, like hospitality and retail, the potential of Artificial Intelligence (AI) generated hyper realistic facial images poses legal and cybersecurity challenges. This paper examines the legal terrain that has developed in the sale of real and AI generated human facial features, and specifically the risks of identity fraud, data misuse and privacy violations. Deep learning (DL) algorithms are analyzed for their ability to detect AI genera

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Estimation levels of CTHRC1and some cytokines in Iraqi patients with Rheumatoid Arthritis
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Collagen triple helix repeat containing-1 (CTHRC1) is an essential marker for Rheumatoid Arthritis (RA), but its relationship with pro-inflammatory, anti-inflammatory, and inflammatory markers has been scantily covered in extant literature. To evaluate the level of CTHRC1 protein in the sera of 100 RA patients and 25 control and compare levels of tumour necrosis factor alpha (TNF-α), interleukin 10 (IL-10), RA disease activity (DAS28), and inflammatory factors. Higher significant serum levels of CTHRC1 (29.367 ng/ml), TNF-α (63.488 pg/ml), and IL-10 (67.1 pg/ml) were found in patient sera as compared to that in control sera (CTHRC1 = 15.732 ng/ml, TNF-α = 33.788 pg/ml, and IL-10 = 25.122 pg/ml). There was no significant correlati

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Publication Date
Thu Aug 20 2020
Journal Name
Talent Development & Excellence
Turn-Taking in Conversation between a Chef and Boss and among Chefs
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DBN Rashid, Talent Development & Excellence, 2020

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Identification of the main causes of risks in engineering procurement construction projects
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Abstract<p>Many risks have adverse consequences for construction projects’ objectives such as quality, schedule, and cost. As engineering procurement construction (EPC) contracts gradually become one of the most common types used in implementing major large-scale construction projects, identifying common risk types and analyzing their root causes is important for developing measures to decrease and eliminate future risks in these types of contracts. The information about the main causes of risks was collected <italic>via</italic> well-structured questionnaires addressed to construction sector professionals and preparing lists of main potential risks in EPC/construction projects throu</p> ... Show More
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Publication Date
Fri Mar 31 2023
Journal Name
Wasit Journal Of Computer And Mathematics Science
Security In Wireless Sensor Networks Based On Lightweight Algorithms : An Effective Survey
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At the level of both individuals and companies, Wireless Sensor Networks (WSNs) get a wide range of applications and uses. Sensors are used in a wide range of industries, including agriculture, transportation, health, and many more. Many technologies, such as wireless communication protocols, the Internet of Things, cloud computing, mobile computing, and other emerging technologies, are connected to the usage of sensors. In many circumstances, this contact necessitates the transmission of crucial data, necessitating the need to protect that data from potential threats. However, as the WSN components often have constrained computation and power capabilities, protecting the communication in WSNs comes at a significant performance pena

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Publication Date
Thu Jan 01 2015
Journal Name
Aip Conference Proceedings
Numerical solution for weight reduction model due to health campaigns in Spain
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This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time t . The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integrated with the FD method t

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