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Deep-Learning-Based Mobile Application for Detecting COVID-19
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Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated using precision, sensitivity, specificity, accuracy, and F-measure to classify CXR images into COVID-19, non-COVID-19 lung opacity, and normal control. Results showed a precision of 92.91%, sensitivity of 90.6, specificity of 96.45%, accuracy of 90.6%, and F-measure of 91.74% in COVID-19 detection. Indeed, the suggested MobileNetV2 deep-learning CNN model can improve classification performance by minimising the time required to collect per-image results for a mobile application.

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Publication Date
Sun Jul 01 2018
Journal Name
Journal Of Network And Computer Applications
L-CAQ: Joint link-oriented channel-availability and channel-quality based channel selection for mobile cognitive radio networks
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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Optimization Algorithms Based on Path Planning and Neural Controller for Mobile Robot
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In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of a Kinematic Neural Controller for Mobile Robots based on Enhanced Hybrid Firefly-Artificial Bee Colony Algorithm
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The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

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Publication Date
Fri Jan 15 2021
Journal Name
المجلة العربية للبحوث الادبية والانسانية
Service Leadership and Customer Satisfaction Under COVID-19 Pandemic Crisis : An Empirical Research for Leaders of Public Organizations in Iraq
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The current research aims to identify the degree to which a sample of managers in public organizations appreciated the level of application of the service leadership style from their point of view, and its relationship to the customer satisfaction index in light of the (Covid-19) pandemic, to achieve this, the researcher followed the experimental approach by applying a questionnaire that included two axes, The first: to measure the level of service leadership according to the scale (D. Van Dierendonck and I. Nuijten, 2011), which includes (8) dimensions (empowerment, stand back, accountability, courage, forgiveness, Authenticity, humility, stewardship). The second axis: to measure the level of customer satisfaction according to (Askim, 2004

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Wed May 28 2025
Journal Name
Oxidation Communications
ESTIMATION OF GALECTIN-3 IN TYPE-2 DIABETIC PATIENTS AFTER VACCINATED AGAINST COVID-19"
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The rapid spread of the COVID-19 coronavirus in 2019 infected many people, primarily affecting the respiratory system. Both COVID-19 and type 2 diabetes have been associated with numerous risks that have become life-threatening. The study studied the link between galectin levels and some clinical characteristics in Iraqis with type 2 diabetes and COVID-19 against those without diabetes. The study included 120 patients and healthy men. Three groups were formed for this study depending on the initial mutant cell line: 80 samples of individuals with type 2 diabetes, aged 40–60 years, with and without COVID-19, were included in each of the first and second groups. The control group consisted of 40 research participants who were matched for ag

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Publication Date
Fri Jul 24 2020
Journal Name
Al-kindy College Medical Journal
Speculations of Immunotherapy in COVID-19 Patients with Practical Applications During Childhood and Pregnancy
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The rapid spread of novel coronavirus disease(COVID19) throughout the world without availablespecific treatment or vaccine necessitates alternativeoptions to contain the disease. Historically, childrenand pregnant women were considered high-riskpopulation of infectious diseases but rarely have beenspotlighted nowadays in the regular COVID-19updates, may be due to low global rates of incidence,morbidity, and mortality. However, complications didoccur in these subjects affected by COVID-19. Weaimed to explore the latest updates ofimmunotherapeutic perspectives of COVID-19patients in general population and some added detailsregarding pediatric and obstetrical practice.Immune system boosting strategy is one of therecently emerging issue

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Publication Date
Fri Sep 15 2023
Journal Name
Technology And Health Care
Clinical management and infection control protocols during the COVID-19 pandemic: An online survey
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BACKGROUND: SARS-CoV-2 (COVID-19) is considered a highly infectious and life threatening disease. OBJECTIVE: The present paper aims to evaluate various aspects of preventive measures and clinical management of the scheduled visits for orthodontic patients to the dental clinics during the outbreak of COVID-19, and to assess how orthodontists dealt with this challenge. METHODS: Orthodontists in private and public clinics were invited to fill a questionnaire that addressed infection control protocols and concerns about clinical management of patients in the clinics during the pandemic. Frequncies and percentages of the responses were obtained and compared using Chi-square tests. RESULTS: About 77% of those working in private clinics, a

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Publication Date
Fri May 20 2022
Journal Name
Al-kindy College Medical Journal
Potential Influence of Parasitic Diseases as Protective Agents from Infection with Pandemic COVID-19
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Parasitic diseases can affect infection with COVID-19 obviously, as protective agents, or by reducing severity of this viral infection. This current review mentions the common symptoms between human parasites and symptoms of COVID-19, and explains the mechanism actions of parasites, which may prevent or reduce severity of this viral infection. Pre-existing parasitic infections provide prohibition against pathogenicity of COVID-19, by altering the balance of gut microbiota that can vary the immune response to this virus infection.  

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Publication Date
Sun Jan 02 2022
Journal Name
Journal Of The College Of Languages (jcl)
A Pragmatic Analysis of Illocutionary Act in a Selected Presidential Speech on COVID-19
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     This paper aims at studying the illocutionary speech acts: direct and indirect to show the most dominant ones in a presidential speech delivered by the USA president. The speech is about the most critical health issue in the world, COVID-19 outbreak.  A descriptive qualitative study was conducted by observing the first speech delivered by president Trump concerning coronavirus outbreak and surveying the illocutionary acts: directive, declarative, commissive, expressive, and representative. Searle's (1985) classification of illocutionary speech acts is adopted in the analysis.

     What are the main types of the illocutionary speech acts performed by Trump in his speech?; Why does

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