Physical Sciences and Mathematics Commons^™

Semi-Supervised Regression With Generative Adversarial Networks Using Minimal Labeled Data, Greg Olmschenk

Dissertations, Theses, and Capstone Projects

This work studies the generalization of semi-supervised generative adversarial networks (GANs) to regression tasks. A novel feature layer contrasting optimization function, in conjunction with a feature matching optimization, allows the adversarial network to learn from unannotated data and thereby reduce the number of labels required to train a predictive network. An analysis of simulated training conditions is performed to explore the capabilities and limitations of the method. In concert with the semi-supervised regression GANs, an improved label topology and upsampling technique for multi-target regression tasks are shown to reduce data requirements. Improvements are demonstrated on a wide variety of vision …

Garch Modeling Of Value At Risk And Expected Shortfall Using Bayesian Model Averaging, Ismail Kheir

Theses and Dissertations

This thesis conducts Value at Risk (VaR) and Expected Shortfall (ES) estimation using GARCH modeling and Bayesian Model Averaging (BMA). BMA considers multiple models weighted by some information criterion. Through BMA, this thesis finds that VaR and ES estimates can be improved through enhanced modeling of the data generation process.

Raman And Surface Enhanced Raman Spectroscopy For Forensic Analysis: Case Studies On The Identification Of Illicit Substances And Artist Pigments, Abed Haddad

Dissertations, Theses, and Capstone Projects

Raman spectroscopy is an effective tool for detecting trace amounts of material by fingerprint-like vibrational spectra. At times, the weak intensity of Raman scattering can make it difficult to distinguish trace materials. This shortcoming is addressed by surface‐enhanced Raman spectroscopy (SERS), which produces strong signal enhancements when target compounds are near metal nanoparticles. For the first part of this thesis, the identification of fentanyl and carfentanil, main culprits in the opioid epidemic, was done using normal Raman and the SERS spectroscopy. As an aid in the assignment of the spectral lines, a computational model was built using Density Functional Theory …

One-Dimensional Excited Random Walk With Unboundedly Many Excitations Per Site, Omar Chakhtoun

Dissertations, Theses, and Capstone Projects

We study a discrete time excited random walk on the integers lattice requiring a tail decay estimate on the number of excitations per site and extend the existing framework, methods, and results to a wider class of excited random walks.

We give criteria for recurrence versus transience, ballisticity versus zero linear speed, completely classify limit laws in the transient regime, and establish a functional limit laws in the recurrence regime.

An Overview And Evaluation Of Synthetc: A Statistical Model For Extra-Tropical Cyclones, Rafael Uryayev

Dissertations and Theses

Extratropical cyclones (ETCs) are the most common weather phenomena affecting the United States, Canada, and Europe. They can pose serious hazards over large swaths of area. In this thesis, a statistical model of ETCs, called SynthETC, is discussed. The model accounts for the for genesis, track path, termination, and intensity of statistically generated ETCs. Genesis is modeled as a Poisson process, whose mean is determined by climate and historical information. Tracks are modeled as a regression-mean determined by climate and historical information plus a stochastic component. Lysis is modeled using logistic regression, with climate states as covariates. Intensity is modeled …

Hydroclimate Drivers And Atmospheric Dynamics Of Floods, Nasser Najibi

Dissertations and Theses

Our preliminary survey showed that most of the recent flood-related studies did not formally explain the physical mechanisms of long-duration and large-peak flood events that can evoke substantial damages to properties and infrastructure systems. These studies also fell short of fully assessing the interactions of coupled ocean-atmosphere and land dynamics which are capable of forcing substantial changes to the flood attributes by governing the exceeding surface flow regimes and moisture source-sink relationships at the spatiotemporal scales important for risk management. This dissertation advances the understanding of the variability in flood duration, peak, volume, and timing at the regional to the …