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Full-Text Articles in Physical Sciences and Mathematics
Parameter Estimation For Patient Enrollment In Clinical Trials, Junyan Liu
Parameter Estimation For Patient Enrollment In Clinical Trials, Junyan Liu
Undergraduate Honors Theses
In this paper, we study the Poisson-gamma model for recruitment time in clinical trials. We proved several properties of this model that match our intuitions from a reliability perspective, did simulations on this model, and used different optimization methods to estimate the parameters. Although the behaviors of the optimization methods were unfavorable and unstable, we identified certain conditions and provided potential explanations for this phenomenon and further insights into the Poisson-gamma model.
Bayesian Spatial Model Development Of Soil Core Organic Matter As A Proxy For Blue Carbon Stocks Within The Chesapeake Bay, Christian Longo
Bayesian Spatial Model Development Of Soil Core Organic Matter As A Proxy For Blue Carbon Stocks Within The Chesapeake Bay, Christian Longo
Undergraduate Honors Theses
Blue carbon is carbon captured and stored within bodies of water and their ecosystems. Blue carbon stocks are very important due to their ability to store carbon away from the atmosphere. The destruction of these stocks can accelerate climate change. In particular, we wish to assess blue carbon stock within the Chesapeake Bay. Previous studies have only used geographical features to predict blue carbon stock levels. The big picture question this thesis was meant to answer is: What is the best approach for building a statistical model that factors in both spatial parameters and geographical features to predict blue carbon …
Using Machine Learning To Track The Location Of The Shock Train In Hypersonic Engines, Alison Reynolds
Using Machine Learning To Track The Location Of The Shock Train In Hypersonic Engines, Alison Reynolds
Undergraduate Honors Theses
Proposed hypersonic vehicles would be able to travel at five to ten times the speed of sound, but there are still many problems that need to be solved to construct a functioning vehicle. One such problem involves shocks created in the engine isolator when the vehicle reaches high speeds. These shocks must be contained to the isolator to maximize performance and avoid potential failure. This project attempts to track the location of the leading shock given images of airflow from ground tests of engines using random forests and convolutional neural networks. When the models are trained and tested on data …