This project will consist of designing an AI application. The application will use a deep learning algorithm able to take attendance of the class as students are joining the classroom. I will further expand the patent to recognize the individual students and measure their temperature. Furthermore, the system will classify different emotions during the lecture and give helpful feedback to the professors. This tool will assist with time management, as professors spend several minutes to take attendance, and it will act as an extra tool for the prevention of spreading COVID-19 and any new virus. The patent will further provide useful feedback for the improvement of lectures through emotion detection. An external camera will be used hand in hand with the Open-CV package in python that will allow us to detect the students and identify them. The students' temperature will be measured by an infrared forehead thermometer and welcome them in the class. The algorithm will be using cascade classifiers, and transfer learning. Data for the training process of the algorithm will be collected from volunteering TCU student subjects.

The process of successful skin healing from a wound involves different combinations of interactions. Moreover, by clearly understanding this process, we can provide and determine the appropriate amount of medicine to give to patients with varying types of wounds. Thus, this can improve the healing process of patients. In this research, we use the ADI method to solve a partial differential equation that models the wound healing process. Moreover, we try to explore the relationship between parameters in the model for different patients. Wound images are used as our dataset experiment. To segment the image's wound, we implement U-Net, a deep learning-based model, as our model for this segmentation problem. We believe the combination of ADI and Deep Learning helps us understand the process of wound healing.

Markov chains are stochastic models characterized by the probability of future states depending solely on one's current state. Google's page ranking system, financial phenomena such as stock market crashes, and algorithms to predict a company's projected sales are a glimpse into the array of applications for Markov models. In this research, we analyzed the board game "The Settlers of Catan" using transition matrices. Transition matrices are composed of the current states which represent each row i and the proceeding states across the columns j with the entry (i,j) containing the probability the current state i will transition to the state j. Using these transition matrices, we delved into addressing the question of which starting positions are optimal. Furthermore, we worked on determining optimality in conjunction with a player's gameplay strategy. After building a simulation of the game in python, we tested the results of our theoretical research against the mock run throughs to observe how well our model prevailed under the limitations of time (number of turns before winner is reached).

In the field of Riemannian geometry, the condition on the Riemannian metric so that a manifold has positive scalar curvature (PSC) is important for a number of reasons. Many famous researchers have contributed gradually to this area of geometry, and in this project, we study more about PSC metrics on such manifolds. Specifically, we refine and provide some details to the proof of Gromov and Lawson that the connected sum of 2 n-dimensional manifolds will admit a PSC metric, provided each of the manifolds has a metric with the same condition. We then derive some useful formulas related to the Riemann curvature tensor, the Ricci tensor, and the scalar curvature in many different scenarios. We compute the quantities for a manifold equipped with an orthonormal frame and its dual coframe, namely the connection one-form and the curvature two-form. Then, we observe the change in the structure functions, defined as a function that determines the Lie derivative of the orthonormal frame, under a nearly conformal change of the said frame. The aim of these calculations is that, by expressing the scalar curvature of a manifold M entirely in terms of the structure functions, we can determine a condition on the conformal factor so that when dividing the tangent bundle of M into two sub-bundles, then the scalar curvature restricted to one sub-bundle will “dominate” that of the other one, so that if we know the scalar curvature of the former sub-bundle is positive, we c

Impact of the COVID-19 pandemic on diet and health-related behaviors of adults

Background:
Study objectives were to describe how diet and health habits changed and identify factors impacting diet and health behaviors during the pandemic.

Methods:
An electronic, anonymous survey was developed and distributed via local social media and through a community food-bank following IRB approval. Data were coded into and analyzed for frequencies and correlations using SPSS.

Results:
Participants (n=80) were 97% (n=77) female and 41.37+/-11.7 years. Participants receiving food assistance primarily accessed community food/mobile pantries (22%, n=17). Participants (54%, n=43) agreed that, “I was healthier before the pandemic”, while 15% (n=12) disagreed. Participants (52%, n=42) reported 13.2+/-6.8 pounds unwanted, pandemic weight gain, while 22.5% (n=18) reported 14.1+/-13.9 pounds desired, weight loss. Among participants earning <$50,000/year, 89.5% (n=17) reported inability to afford healthy food, while 2.6% (n=1) earning >$150,000/year reported inability to afford healthy food. Inability to afford healthy food correlated with BMI (ρ=.40, p<.01). Income negatively correlated with pandemic weight gain (ρ=-0.31, p<0.05) and ability to afford healthy foods (ρ=-.73, p<0.01). Participants reported increased pandemic snacking (61.25%, n=49) and alcohol consumption (37.5%, n=30). Higher pandemic stress levels correlated with increased pandemic alcohol and snack consumption, (ρ=.30, p<.01) and (ρ=.44, p<.01), respectively.

Conclusion:
Changes in health perceptions and weight were common. BMI and income impacted ability to afford healthy foods. Increased stress levels were significantly associated with increased alcohol intake and snacking, although weight changes were not associated with alcohol or snacking. This research provides information about pandemic dietary and health behavior changes and how impacts differ based upon income level.