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Computational Fluid Dynamics Visualization For Unmanned Aerial Systems In Bridge Inspections, Kristoffer B. Borgen, John Mott
Computational Fluid Dynamics Visualization For Unmanned Aerial Systems In Bridge Inspections, Kristoffer B. Borgen, John Mott
Journal of Aviation Technology and Engineering
Bridge inspections are an expensive and time-consuming process, varying significantly with a bridge’s style, height, width, and length. Inspections create interruptions that interfere with bridge use, as the examination requires partial or total closure, causing traffic delays. Unmanned aerial system (UAS) use has increased significantly over the past decade, including assistance and coordination during bridge inspections. However, the impact on a UAS from high winds and turbulent airflows induced by a bridge’s structure can decrease flight safety during inspections. Visualization of these hazards is difficult for UAS operators; therefore, a process to estimate the velocity and locations of these hazardous …
A Machine Learning Model Of Perturb-Seq Data For Use In Space Flight Gene Expression Profile Analysis, Liam F. Johnson, James Casaletto, Lauren Sanders, Sylvain Costes
A Machine Learning Model Of Perturb-Seq Data For Use In Space Flight Gene Expression Profile Analysis, Liam F. Johnson, James Casaletto, Lauren Sanders, Sylvain Costes
Graduate Industrial Research Symposium
The genetic perturbations caused by spaceflight on biological systems tend to have a system-wide effect which is often difficult to deconvolute it into individual signals with specific points of origin. Single cell multi-omic data can provide a profile of the perturbational effects, but does not necessarily indicate the initial point of interference within the network. The objective of this project is to take advantage of large scale and genome-wide perturbational datasets by using them to train a tuned machine learning model that is capable of predicting the effects of unseen perturbations in new data. Perturb-Seq datasets are large libraries of …