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.
In many video and image processing applications, the frames are partitioned into blocks, which are extracted and processed sequentially. In this paper, we propose a fast algorithm for calculation of features of overlapping image blocks. We assume the features are projections of the block on separable 2D basis functions (usually orthogonal polynomials) where we benefit from the symmetry with respect to spatial variables. The main idea is based on a construction of auxiliary matrices that virtually extends the original image and makes it possible to avoid a time-consuming computation in loops. These matrices can be pre-calculated, stored and used repeatedly since they are independent of the image itself. We validated experimentally th
... Show MoreNAA Mustafa, Journal of the Sixth Conference of the Faculty of Languages, 2010
The research aims to how to deal with certain situation to ensure the continuous competitive excellence of business market under the situation of covid-19, especially how to deal with major challenges, identifying the capabilities of tourism industry, investigating the ability of tourism agencies to resist the dynamic change of both internal as well as external environment to ensure their sustainability.
The important here as the paper notice, is how to be efficient and trying to find solutions in order to grow and survive through choosing certain strategies that aligned the critical issues.
Thus to achieve this level, many scenarios planed that could adopt in case of such pande
... Show MoreAutomated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breat
... Show MoreBackground: The SARS-CoV-2 virus causes COVID-19, a respiratory syndrome. It causes inflammation and damages several organs in the body. miRNAs play a role in regulating the infection resulting from SARS-CoV-2. MicroRNA-155, a kind of microRNA linked to viral defences, can affect the immune responses during COVID-19. Objectives: Examination of the involvement of microRNA-155 in the development and severity of COVID-19, as well as finding the correlation between microRNA-155 and viral load (copies/mL) in severe cases of the disease. Materials and Method: A case-control research study was performed between October 2022 and June 2023. It included a cohort of 120 hospitalised individuals with severe cases of COVID-19, together with 115 individu
... Show MoreThis study aims to find the chemosensitive dysfunction incidence in COVID-19-positive patients and its recovery.
We collected the data from sixty-five patients, all COVID-19 positive, quarantined in-hospital between 5 April 2020 and 17 May 2020, by a questionnaire distributed in the quarantine ward.
Smell dysfunction appeared in 89.23% with or without other symptoms of COVID-19. 39.66% of them recovered the sense of smell. Taste dysfunction found in 83.08% patients with other COVID-19 symptoms. Only 29.63% of them recovered. The recovery took 1–3 weeks, and most
The post-Corona Covid-19 world is not the world before it, the problem of perception of personality traits with two axes: the characteristics of psychological and social compatibility, and the second aspect the mental disorder during the pandemic, and the accompanying precautions and prohibitions during the academic year 2020 AD. The aim of the research is to reveal the perception of the personal characteristics of Bisha University employees (students and faculty) during the Corona Covid-19 pandemic, and to reveal statistically significant differences in the perception of the personality traits of Bisha’s members during the Covid 19 according to the scientific qualification variables (female students -faculty members), marital st
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