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.
The aim of this investigation is to study the rote of alkaline phosphatase in mammogenesis and lactogenesis. A total of fortyfemalealbino rats were used and divided according to their physiological states into four groups [ten rats each]. From each deeply ether anesthetized rat, the mammary gland was removed, fixed, quenched in liquid nitrogen and sectioned using SLEE cryostat. The sections were employed for routine haematoxylin and eosin stain and alkaline phosphatase demonstration using the calcium–cobalt method. The obvious finding in the mammary glands of pregnant rat was the presence of thick black rings indicating strong alkaline phosphatase activityaround the basal part of the secretory epithelium of the alveoli. In lactating mamma
... Show MoreCurrently 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
... Show MoreBackground: 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
... Show MorePurpose: Studying the activity of acid phosphatase, which is the marker of lysosomal activity in the mammary glands of rats at different stages of the physiological maturation [virgih, pregnancy, lactation and Post lactation] Methods: Forty, female, albino rats were used in this study. They were divided into four groups according to their physiological states [virgin, pregnancy, lactation and post lactation]. The mammary glands, after suitable fixation and sectioning, were employed for routine haematoxylin and eosin stain and for acid phosphatase demonstration Results: Acid phosphatase activity was weakly diffuse in the secretory tubules of virgin rats, the diffuse and granular activity of this enzyme was increased during pregnancy in the s
... Show MoreOsteoporosis (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
... Show MoreInvestigating the strength and the relationship between the Self-organized learning strategies and self-competence among talented students was the aim of this study. To do this, the researcher employed the correlation descriptive approach, whereby a sample of (120) male and female student were selected from various Iraqi cities for the academic year 2015-2016. the researcher setup two scales based on the previous studies: one to measure the Self-organized learning strategies which consist of (47) item and the other to measure the self-competence that composed of (50) item. Both of these scales were applied on the targeted sample to collect the required data
Idioms are a very important part of the English language: you are told that if you want to go far (succeed) you should pull your socks up (make a serious effort to improve your behaviour, the quality of your work, etc.) and use your grey matter (brain).1 Learning and translating idioms have always been very difficult for foreign language learners. The present paper explores some of the reasons why English idiomatic expressions are difficult to learn and translate. It is not the aim of this paper to attempt a comprehensive survey of the vast amount of material that has appeared on idioms in Adams and Kuder (1984), Alexander (1984), Dixon (1983), Kirkpatrick (2001), Langlotz (2006), McCarthy and O'Dell (2002), and Wray (2002), among others
... Show MoreThe 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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