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.
COVID-19 was declared a pandemic by the World Health Organization in March 2020, and the SARS-CoV-2 virus continues to be a global concern with new variants. Our research focused on the relationship between COVID-19 and air pollution, and we included findings from recently published research. In summary, there is a direct relationship between air pollution and COVID-19 infection and fatality rates. This relationship was evident after many parts of the world declared lockdowns. Research to understand the relationship between infection rates and air pollutants identified indirect factors that contributed to the spread of infection. In this article, we explore studies on air pollutants, the use of face masks, weather conditions, short-
... Show MoreOne of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first
... Show MoreSince June 2020, an explosion in number of new COVID-19 patients has been reported in Iraq with a steady increment in new daily reported cases over the next 3 months. The limited number of PCR kits in the country and the increment in the number of new COVID-19 cases makes the role of CT scan examinations rising and becoming essential in aiding the health institutions in diagnosing and isolating infected patients and those in close contacts. This study will review the spectrum of CT pulmonary changes due to COVID-19 infection and estimate the CT severity score index and its relation to age, sex, and PCR test results
In wireless broadband communications using single-carrier interleave division multiple access (SC-IDMA) systems, efficient multiuser detection (MUD) classes that make use of joint hybrid decision feedback equalization (HDFE)/ frequency decision-feedback equalization (FDFE) and interference cancellation (IC) techniques, are proposed in conjunction with channel coding to deal with several users accessing the multipath fading channels. In FDFE-IDMA, the feedforward (FF) and feedback (FB) filtering operations of FDFE, which use to remove intersymbol interference (ISI), are implemented by Fast Fourier Transforms (FFTs), while in HDFE-IDMA the only FF filter is implemented by FFTs. Further, the parameters involved in the FDFE/
... Show MoreElectronic learning was used as a substitute method for learning during the COVID-19 pandemic to conduct scientific materials and perform student assessment; this study aimed to investigate academic staff opinions toward electronic education. A cross-sectional study with a web-based questionnaire distributed to academic staff in different medical colleges in Iraq. After de-identification, data were collected and analyzed with statistical software to determine the significance between variables. A total of 256 participants were enrolled in the study: 83% were not satisfied or neutral to online learning, 80% showed a poor benefit from delivery of the practical electronic knowledge and 25% for theoretical sessions with a significant difference
... Show MoreThe rapid spread of novel coronavirus disease
(COVID19) throughout the world without available
specific treatment or vaccine necessitates alternative
options to contain the disease. Historically, children
and pregnant women were considered high-risk
population of infectious diseases but rarely have been
spotlighted nowadays in the regular COVID-19
updates, may be due to low global rates of incidence,
morbidity, and mortality. However, complications did
occur in these subjects affected by COVID-19. We
aimed to explore the latest updates of
immunotherapeutic perspectives of COVID-19
patients in general population and some added details
regarding pediatric and obstetrical practice.
Immune system boo
This study discusses risk management strategies caused by pandemic-related (Covid-19) suspensions in thirty-six engineering projects of different types and sizes selected from countries in the middle east and especially Iraq. The primary data collection method was a survey and questionnaire completed by selected project crew and laborers. Data were processed using Microsoft Excel to construct models to help decision-makers find solutions to the scheduling problems that may be expected to occur during a pandemic. A theoretical and practical concept for project risk management that addresses a range of global and local issues that affect schedule and cost is presented and results indicate that the most significant delays are due to a
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