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 …

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.