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Detecting Damaged Buildings on Post-Hurricane Satellite Imagery based on Transfer Learning
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In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performance measures are used as a criterion to decide which classifier is the best one to detect the images with high accuracy. Eventually, the simulation results show that each classifier detect the damage/no damage image with different performance measures and then makes it easy to select the best one.

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Publication Date
Tue Jun 15 2021
Journal Name
Al-academy
Forms of post-modernism in performance of Iraqi theatre "dream of Baghdad exam": عمار عبد سلمان محمد
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  The effects of postmodernism on theatrical form was managed by the director (Anas Abdul Samad) to be employed in the Iraqi play (Dream in Baghdad) and the researcher sought to study this problem and divided it into four chapters dealt with in the first chapter the problem of research and its need, the importance of research, As well as the definition of terminology, either Chapter II theoretical framework divided by the researcher to the first two is the postmodernism in the theater is the most prominent reference references and the second most important postmodern applications in the world play and then the researcher concluded the second chapter of the most important indicators. In the third chapter, the researcher identified th

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Publication Date
Sat Jan 01 2022
Journal Name
Ssrn Electronic Journal
The Prospective of Artificial Neural Network (ANN’s) Model Application to Ameliorate Management of Post Disaster Engineering Projects
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Currently and under the COVID-19 which is considered as a kind of disaster or even any other natural or manmade disasters, this study was confirmed to be important especially when the society is proceeding to recover and reduce the risks of as possible as injuries. These disasters are leading somehow to paralyze the activities of society as what happened in the period of COVID-19, therefore, more efforts were to be focused for the management of disasters in different ways to reduce their risks such as working from distance or planning solutions digitally and send them to the source of control and hence how most countries overcame this stage of disaster (COVID-19) and collapse. Artificial intelligence should be used when there is no practica

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Publication Date
Mon Oct 17 2022
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Focus Assessment of Transthoracic Echocardiography post septostomy Procedure in Patients Undergoing Ablation of Left Atrial Supraventricular Tachycardia
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Background: Echocardiography has an important role to follow up patients with Iatrogenic atrial septaldefect (IASD) and after Catheter ablation during electro-physiological study.Objectives: evaluating the impact of non-invasive Transthoracic Echocardiography (TTE) parameters(LAVI, LVEF, ASD size and E/e`) post radiofrequency ablation of left atrial arrhythmia.Patients and methods: for the evaluation of the atrial septal defect, a transthoracic echocardiography(TTE) was used in patients who underwent left atrial arrhythmia ablation, enrolled in prospective studyin the Iraqi center for cardiac diseases, in cooperation with university of Baghdad /college of medicineResults: The outcomes of the present study were assessed according to

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Publication Date
Wed Oct 21 2020
Journal Name
British Journal Of Cancer
Epigenome-wide analysis reveals functional modulators of drug sensitivity and post-treatment survival in chronic lymphocytic leukaemia
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Abstract<sec> <title>Background

Chronic lymphocytic leukaemia (CLL) patients display a highly variable clinical course, with progressive acquisition of drug resistance. We sought to identify aberrant epigenetic traits that are enriched following exposure to treatment that could impact patient response to therapy.

Methods

Epigenome-wide analysis of DNA methylation was performed for 20 patients at two timepoints during treatment. The prognostic significance of differentially methylated regions (DMRs) was assessed in independent cohorts of 139 and 1

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Publication Date
Fri Jul 01 2022
Journal Name
Civil Engineering Journal
Behavior of Post-Tensioned Concrete Girders Subject to Partially Strand Damage and Strengthened by NSM-CFRP Composites
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Studies on the flexural behavior of post-tensioned beams subjected to strand damage and strengthened with near-surface mounted (NSM) technique using carbon fiber-reinforced polymer (CFRP) are limited and fail to examine the effect of CFRP laminates on strand strain and strengthening efficiency systematically. Furthermore, a design approach for UPC structures in existing design guidelines for FRP strengthening techniques is lacking. Hence, the behavior of post-tensioned beams strengthened with NSM-CFRP laminates after partial strand damage is investigated in this study. The testing program consists of seven post-tensioned beams strengthened by NSM-CFRP laminates with three partial strand damage ratios (14.3% symmetrical damage, 14.3%

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Publication Date
Sat Dec 24 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Prevalence of AGER gene polymorphism in post menopause Iraqi sample with Osteoporosis and osteopenia in type 2DM
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Osteoporosis (OP)is one of the most important metabolic disorder also affected by interaction of genetic and environmental factors by almost 70% and 30% respectively. Genetic components are identified to strongly effect bone mineral density, bone building and turnover, so they play an important role in determining risk of OP and fragility fractures. This study consists of patient and control group; Group A: (70) postmenopausal women with OP and osteopenia, Group B: (20) control group.  five milliliters of blood sample were divided into three tubes; one tube (1ml) contain gel for obtain serum to measure glucose level, the others tubes containing ethylene-diamine-tetra-acetic acid (EDTA), in 2 tube 2ml stored in deep freeze at (–40

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Publication Date
Tue Apr 30 2024
Journal Name
International Journal On Technical And Physical Problems Of Engineering
Deep Learning Techniques For Skull Stripping of Brain MR Images
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Deep Learning Techniques For Skull Stripping of Brain MR Images

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Publication Date
Sun Mar 26 2023
Journal Name
Wasit Journal Of Pure Sciences
Covid-19 Prediction using Machine Learning Methods: An Article Review
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The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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Publication Date
Tue Dec 28 2021
Journal Name
2021 2nd Information Technology To Enhance E-learning And Other Application (it-ela)
Pedestrian and Objects Detection by Using Learning Complexity-Aware Cascades
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