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Understanding Volume Transport In The Jordan River: An Application Of The Navier-Stokes Equations, Gwyneth E. Roberts
Understanding Volume Transport In The Jordan River: An Application Of The Navier-Stokes Equations, Gwyneth E. Roberts
Honors College
This study aims to characterize the circulation patterns in short and narrow estuarine systems on various temporal scales to identify the controls of material transport. In order to achieve this goal, a combination of in situ collected data and analytical modeling was used. The model is based on the horizontal Reynolds Averaged Navier-Stokes equations in the shallow water limit with scaling parameters defined from the characteristics of the estuary. The in situ measurements were used to inform a case study, seeking to understand water level variations and tidal current velocity patterns in the Jordan River and to improve understanding of …
Predictive Diagnostic Analysis Of Mammographic Breast Tissue Microenvironment, Dexter G. Canning
Predictive Diagnostic Analysis Of Mammographic Breast Tissue Microenvironment, Dexter G. Canning
Honors College
Improving computer-aided early detection techniques for breast cancer is paramount because current technology has high false positive rates. Existing methods have led to a substantial number of false diagnostics, which lead to stress, unnecessary biopsies, and an added financial burden to the health care system. In order to augment early detection methodology, one must understand the breast microenvironment. The CompuMAINE Lab has researched computational metrics on mammograms based on an image analysis technique called the Wavelet Transform Modulus Maxima (WTMM) method to identify the fractal and roughness signature from mammograms. The WTMM method was used to color code the mammograms …
Fitting The Sir Epidemiological Model To Influenza Data, Madeline Dorr
Fitting The Sir Epidemiological Model To Influenza Data, Madeline Dorr
Honors College
This project sought to provide thorough instructions to fitting the SIR epidemiological model to influenza data and defend its use in this context. Directions for coding the SIR model in the R programming language are detailed. This includes estimating parameter values, such as infection and recovery rate, and how to double check these values. This project also included analysis of problems that can arise when fitting this model. This includes accounting for vaccination rate and issues with the nature of this type of data. Either these problems were explored, and solutions were provided, or suggestions were provided for future research.