In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial lung CT-scans into two groups (COVID-19 and NonCOVID-19) had been proposed. A dataset used is 960 slices of CT scan collected from Iraqi patients /Ibn Al-Nafis teaching hospital. The performance metrics are used in this study (accuracy, recall, precision, and F1 scores). The results indicate that the proposed approach generated a high-quality model for the collected dataset, with an overall accuracy of 98.95% and an overall recall of 97 %.
Abstract
The extremes effects in parameters readings which are BOD (Biological Oxygen Demands) and DO(Dissolved Oxygen) can caused error estimating of the model’s parameters which used to determine the ratio of de oxygenation and re oxygenation of the dissolved oxygen(DO),then that will caused launch big amounts of the sewage pollution water to the rivers and it’s turn is effect in negative form on the ecosystem life and the different types of the water wealth.
As result of what mention before this research came to employees Streeter-Phleps model parameters estimation which are (Kd,Kr) the de oxygenation and re oxygenation ratios on respect
... Show MoreOne of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th
... Show MoreOne of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca
... Show MoreThe research specified with study the relation between the market share for the sample research banks and the amount of the achieved revenues from the investment, where the dominated belief that there potentiality enhancing the revenue on investment with the increase of the banks shares in their markets after their success in achieving rates of successive growth in their sales of sales and to a suitable achieve market coverage for their products and they have dissemination and suitable promotion activity, the market share represented the competition for the banks, and the markets pay attention to the market share as a strategic objective and to maintain them also increasi
... Show MoreSecurity concerns in the transfer of medical images have drawn a lot of attention to the topic of medical picture encryption as of late. Furthermore, recent events have brought attention to the fact that medical photographs are constantly being produced and circulated online, necessitating safeguards against their inappropriate use. To improve the design of the AES algorithm standard for medical picture encryption, this research presents several new criteria. It was created so that needs for higher levels of safety and higher levels of performance could be met. First, the pixels in the image are diffused to randomly mix them up and disperse them all over the screen. Rather than using rounds, the suggested technique utilizes a cascad
... Show MoreThis research aims to:
1 – Make a proposed module for (aesthetics) for the second stage - Department of Art Education under education theories.
2 - Verification from the effect of the proposed module on student achievement and motivation towards learning aesthetics material.
To verification the second goal we wording these two hypotheses:
1- There are no individual differences with statistically significant at level (0.05) between the student's scores average. (Experimental group ) who studied according to the proposed module and the average student's scores (control group) who studied in the usual way for the achievement test for the Aesthetics material.
2- There are no individual differences with statistically signifi
The key objective of the study is to understand the best processes that are currently used in managing talent in Australian higher education (AHE) and design a quantitative measurement of talent management processes (TMPs) for the higher education (HE) sector.
The three qualitative multi-method studies that are commonly used in empirical studies, namely, brainstorming, focus group discussions and semi-structured individual interviews were considered. Twenty
The research aims mainly to the role of the statement style costs on the basis of activity based on performance (PFABC) to reduce production cost and improve the competitive advantage of economic units and industrial under the modern business environment dominated by a lot of developments and changes rapidly, which necessitates taking them and criticize them to ensure survival and continuity. The research problem is the inability of traditional cost methods of providing useful information to the departments of units to take many administrative decisions, particularly decisions related to the product and calculating the costs of the quality of the sound and the availability of the need and the ability to replace methods capa
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