The COVID-19 pandemic has had a huge influence on human lives all around the world. The virus spread quickly and impacted millions of individuals, resulting in a large number of hospitalizations and fatalities. The pandemic has also impacted economics, education, and social connections, among other aspects of life. Coronavirus-generated Computed Tomography (CT) scans have Regions of Interest (ROIs). The use of a modified U-Net model structure to categorize the region of interest at the pixel level is a promising strategy that may increase the accuracy of detecting COVID-19-associated anomalies in CT images. The suggested method seeks to detect and isolate ROIs in CT scans that show the existence of ground-glass opacity, which is frequent in COVID-19 patients. This can assist healthcare practitioners in identifying and monitoring illness development, as well as making treatment decisions. Scale U-Net is a strong U-Net design modification that can increase the performance of semantic segmentation tasks. Our model, Normalized-UNet, uses batch normalization after each convolutional layer to decrease the internal covariate shift, which dramatically improves the network's learning efficiency.
Three seismic instantaneous attributes (phase, frequency, and variance) were utilized on 3D-seismic poststack migrated data, covering 617.31 km2, integrated with data of two wells (Du-1 and Du-2) in Dujaila oil field, southeast of Iraq. They gave good results in detecting reef buildups and confirmed the existence of the stratigraphic hydrocarbon trap that was not obvious in the conventional seismic amplitude sections. They display several seismic criteria in attribute sections for recognizing reef buildups and hydrocarbon accumulation, such as phase reversal, low frequency, and high amplitude variance. The seismic attributes emphasized that the stratigraphic trap of reef rudist buildups with hydrocarbon content is con
... Show MoreFire is one of the most critical risks devastating to human life and property. Therefore, humans make different efforts to deal with fire hazards. Many techniques have been developed to assess fire safety risks. One of these methods is to predict the outbreak of a fire in buildings, and although it is hard to predict when a fire will start, it is critical to do so to safeguard human life and property. This research deals with evaluating the safety risks of the existing building in the city of Samawah/Iraq and determining the appropriateness of these buildings in terms of safety from fire hazards. Twelve parameters are certified based on the National Fire Protection Association (NFPA20
In The Bluest Eye (1970), the American-African writer, Toni Morrison explores how
Western standards of ideal beauty are created and propagated with and among the black
community. The novel not only portrays the lives of those whose dark skinned and Negroid
features blight their lives; it also shows how the standard of white beauty, when imposed on
black youth, can drastically damage one’s self-love and esteem which usually occurs when
beauty goes unrecognized. Morrison in this novel focuses on the damage that the black
women characters suffer through the construction of femininity in a racialised society where
whiteness is used as a standard of beauty.
This study carry’s out the correlation and the effect of two main variables, these variables are Job Satisfaction included six sub: wages - salaries and justice and yield, working conditions and services, pattern of supervision and the relationship with the manger, Relationship with colleagues, the content of the work and the variety of tasks, development and promotion opportunities available to an individual, and Organizational Performance included two sub variables: Efficiency, Effectiveness. This research was conducted using a questioner as a main tool, This questioner was distributed randomly to a research community composed of
... Show MoreNowadays, a strong relationship between the agriculture sectors and digital technologies is really interesting. The article describes how recent intelligent technologies can improve agricultural fields. Mobile applications are software programs created on smartphones, tablets, and computers. Agricultural fields mainly represent the pillar of the economy and the business sector that fulfills the world's food requirements. The United States has a valuable rank in potato production, which depends on this production economically.
Nevertheless, so many insects affect potato yield production quantitatively and qualitatively. So, a smartphone App was created to help potato growers diagnose insects that directly attack potato cro
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