This thesis was conducted to study and analyze the fund allocation process adopted by different states in the United States to reduce the impact of the Covid-19 virus. Seven different states and their funding methodologies were compared against the case count within the state. The study also focused on development of a physical distancing index based on three significant attributes. This index was then compared to the expenditure and case counts to support decision making.
A regression model was developed to analyze and compare how different states case counts played out against the regression model and the risk index.

As the return to normality in the wake of the COVID-19 pandemic enters its early stages, the necessity for accurate, quick, and community-wide surveillance of SARS-CoV-2 has been emphasized. Wastewater-based epidemiology (WBE) has been used across the world as a tool for monitoring the pandemic, but studies of its efficacy in comparison to the best-known method for surveillance, randomly selected COVID-19 testing, has limited research. This study evaluated the trends and correlations present between SARS-CoV-2 in the effluent wastewater of a large university campus and random COVID-19 testing results published by the university. A moderately strong positive correlation was found between the random testing and WBE surveillance methods (r = 0.63), and this correlation was strengthened when accommodating for lost samples during the experiment (r = 0.74).

In this thesis paper, the mental health consequences of the COVID-19 pandemic are discussed. Chapter 1 discusses what inspired me to write this thesis and follows with a discussion of social isolation during the COVID-19 pandemic. Chapter 2 takes a step back and discusses biological effects of social isolation in general. Chapter 3 discusses the psychological effects of social isolation. Finally, this thesis concludes with a discussion of what can be done to help those experiencing social isolation during the pandemic.

For my creative project, I explored using natural sound to create a sound score or song. I used contrasting natural sounds to create the sound scores. Most of the sound recordings are from the New York City subways as well as other recordings around different cities in the United States. I created new sounds using sound manipulation techniques. I explored the use of electronic music production to translate the natural noise into the patterns, repetition and other elemental musical techniques to create a song. I used Ableton as the music production platform to develop the three songs.

The product our team is commercializing is a NASA designed technology designed to store waste in space. This product works on Earth as well and has applicable multi-use capabilities. Throughout the last several months, the team has identified different markets to determine which of them would experience the most value from this product. The team conducted 25 interviews to grasp the landscape of the different markets related to this product. After a thorough analysis, it was found that vendors who support the disposal of different types of waste and sludge would be the best fit for this product. Vendors like Waste Management, Sharps, Stericycle, Sludge USA, etc.,” have large contracts with hospitals, biotech firms, labs, and cities to manage a wide spectrum of waste. The companies bring value to their clients by making a difficult process easier. However, the process is not seamless and, with certain types of waste, there are significant costs associated with not following an exact process. Throughout this process and interviews with companies like Sludge USA and Waste Management, the team identified a niche market in supporting sludge processes. Caked: Sludge Management is designed to bring value to this market by making their waste disposal process seamless, and saving these institutions significant costs in the long run, while creating additional value.

Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.

Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.

The ASU COVID-19 testing lab process was developed to operate as the primary testing site for all ASU staff, students, and specified external individuals. Tests are collected at various collection sites, including a walk-in site at the SDFC and various drive-up sites on campus; analysis is conducted on ASU campus and results are distributed virtually to all patients via the Health Services patient portal. The following is a literature review on past implementations of various process improvement techniques and how they can be applied to the ABCTL testing process to achieve laboratory goals. (abstract)