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Browsing Volgenau School of Engineering Graduate Research by Subject "COVID-19"

Browsing Volgenau School of Engineering Graduate Research by Subject "COVID-19"

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  • Analysis of Social Media Comments 
    Mohamed, Mazen (2021-04-28)
    Fighting the COVID-19 is widespread acceptance of the covid-19 vaccines. Achieving the widespread uptake might be challenging and may be obstructed by the misinformation prevalent in social media. The social media platforms ...
  • COVID-19 Vaccine Data Review and Reactions on Social Media 
    Bhandari, Shova; Mohamed, Mazen; Maupin, Jake (2021-04-28)
    The USA is one of the hardest hit areas by COVID-19. As of March 13th, 2021, 29.5M people were infected and 534K have lost their lives [1]. The USA government has authorized Pfizer and Moderna mRNA COVID-19 vaccines for ...
  • Data Analytics Research for COVID19 Pandemic 
    Tran, Thao (2021-04-28)
    The importance of learning about where and how coronavirus has entered the United States will help further our understanding of the disease. According to CDC, the first coronavirus case in the US has been identified ...
  • Financial Impact of Lockdown on Big Business Versus Small Business based on Data Analytics 
    Chekuri, Rohit Varma; Wilkinson, Brady; Xuan, Bach Le (2021-04-28)
    Though everyone was affected by the COVID-19 pandemic in their own ways, some suffered harder financial loss than others. Smaller-sized businesses that once thrived from crowds of people faced a sudden disappearance in ...
  • Flight Data to Predict COVID-19 Cases by Machine Learning 
    Alshabana, Ghadah (2021-04-28)
    Coronavirus can be transmitted through the air in close proximity to infected persons. Commercial aircraft is a likely way to both transmit the virus among passengers and move the virus between locations. Our team utilized ...
  • Machine learning and NLP Models to Predict COVID-19 Cases in US 
    Alshabana, Ghadah; Chitimalla, Ashritha; Tran, Thao; Thompson, Michael (2021-04-28)
    Air travel is an important factor to spread of the coronavirus from more infected regions to those with limited or no prior infections. The importance of learning about where and how coronavirus has entered the United States ...
  • Machine Learning Application in Health 
    Alshabana, Ghadah; Tran, Thao; Chitimalla, Ashritha; Thompson, Michael (2022-06-10)
    Coronavirus can be transmitted through the air by close proximity to infected persons. Commercial aircraft are a likely way to both transmit the virus among passengers and move the virus between locations. The importance ...
  • Machine Learning Models and Transfer Models for Measuring Impact of the Pandemic on Communities 
    Berdibekov, Timur (2021-04-28)
    This paper studies the relationship between the 2019 Novel Coronavirus (COVID-19) pandemic, its public health and economic impact, and rates of economic inclusion and access to banking services throughout the pandemic in ...
  • Machine learning models for Prediction of the need for future Covid-19 vaccine booster 
    Marzook, Ahmad Al; Xu, Ge; Jagannath, Prajna Shetty (2021-04)
    About 4 million Virginia citizens are fully vaccinated against COVID-19. According to medical data from nations like Israel and the United Kingdom, all those people may require another shot in the near future, at least ...
  • Neurological Manifestation of COVID-19: An Updated Literature Review 
    Eltayeb, Sohaib; Peixoto, Nathalia (2022-05)
    SARS-CoV-2, which causes the disease known as Coronavirus Disease 2019 (COVID-19), is a novel coronavirus that arose in Wuhan, China in 2019. Within a short time, it rapidly spread across the world and has been declared ...
  • Stop COVID-19 Cases by Using Data Analytics Approach 
    Chitimalla, Ashritha (2021-04-28)
    The most common way Covid-19 can spread is by human interaction, through respiratory droplets such as talking, coughing, sneezing, and more. Air travelers can come from countries or areas with a high rate of infection ...

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