Analysis and processing of hyperspectral data with the purpose of classification

Logan Smith with Julia DobrosotkayaAnalysis and processing of hyperspectral data with the purpose of classificationHyperspectral imaging is an advanced imaging technique that measures visible and near-infrared light reflecting off a surface. Hyperspectral imagery has a wide range of applications from geospatial sciences to ecology, surveillance and more. A hyperspectral...

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Analysis of Bifurcations and Abrupt Transitions in Energy Balance Models (EBM) coupled to green-house-gas emissions (GHG)

Robert Taylor with David GurarieAnalysis of Bifurcations and Abrupt Transitions in Energy Balance Models (EBM) coupled to green-house-gas emissions (GHG).Simple energy balance models with temperature dependent albedo (reflected fraction of incoming radiation) can exhibit hysteresis and rapid transitions between “warm” and “cold” equilibrium states. Another important factor that affects...

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Advanced Undergraduate Acoustics Experiment

Michael Anderson with Jesse Beresovsky Advanced Undergraduate Acoustics Experiment Acoustics represents a body of science that is rich in theory and new concepts and has many applications in everyday life. Unfortunately, many undergraduates are not afforded the opportunity to explore acoustics past a brief introduction. The purpose of this project, then, is...

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Evaluation of US Renewable Portfolio Standards in Terms of Effectiveness and Intention

Jacob Derzon with Justin Gallagher Evaluation of US Renewable Portfolio Standards in Terms of Effectiveness and Intention In the past several decades, there have been several attempts by lawmakers to increase the use of renewable resources in various states through legislation known as the renewable portfolio standard (RPS), which mandates increased...

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Optimal Current Patterns and Resolution Limitations of the Bayesian Methodology in EIT

Oliver Ernst with Erkki Somersalo Optimal Current Patterns and Resolution Limitations of the Bayesian Methodology in EIT One of the applications of the Bayesian methodology is to the determination of the electrical admittivity distribution from measurement data in Electrical Impedance Tomography (EIT). Since this inverse problem is ill-posed, a spectrum of...

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Stochastic Differential Equations Driven by Compound Poisson and Lévy Processes

Thomas Norton with Wojbor A. Woyczyński Stochastic Differential Equations Driven by Compound Poisson and Lévy Processes Stochastic differential equations (SDEs) provide a rigorous setting for investigating the dynamics of systems subject to “noise,” by which we mean source terms whose behavior is not deterministic, but governed by a probability distribution.  The...

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