Open Access. Powered by Scholars. Published by Universities.®

Computer Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Computer and Systems Architecture

Computer Science and Computer Engineering Undergraduate Honors Theses

Theses/Dissertations

2021

Articles 1 - 2 of 2

Full-Text Articles in Computer Engineering

Automated Report Based System To Encourage A Greener Commute To Campus, Ronald Velasquez Dec 2021

Automated Report Based System To Encourage A Greener Commute To Campus, Ronald Velasquez

Computer Science and Computer Engineering Undergraduate Honors Theses

This project consists of the design and implementation of a tool to encourage greener commutes to the University of Arkansas. Trends in commuting of the last few years show a decline in not so environment-friendly commute modes. Nevertheless, ensuring that this trend continues is vital to assure a significant impact. The created tool is an automated report system. The report displays information about different commute options. A Google form allows users to submit report requests, and a web app allows the sustainability office to process them in batches. This system was built in the Apps Script platform. It implements several …


Contrastive Learning For Unsupervised Auditory Texture Models, Christina Trexler Dec 2021

Contrastive Learning For Unsupervised Auditory Texture Models, Christina Trexler

Computer Science and Computer Engineering Undergraduate Honors Theses

Sounds with a high level of stationarity, also known as sound textures, have perceptually relevant features which can be captured by stimulus-computable models. This makes texture-like sounds, such as those made by rain, wind, and fire, an appealing test case for understanding the underlying mechanisms of auditory recognition. Previous auditory texture models typically measured statistics from auditory filter bank representations, and the statistics they used were somewhat ad-hoc, hand-engineered through a process of trial and error. Here, we investigate whether a better auditory texture representation can be obtained via contrastive learning, taking advantage of the stationarity of auditory textures to …