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Physical Sciences and Mathematics Commons

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Full-Text Articles in Physical Sciences and Mathematics

Creating Project Contrast: A Video Game Exploring Consciousness And Qualia, Pierce Papke May 2023

Creating Project Contrast: A Video Game Exploring Consciousness And Qualia, Pierce Papke

Honors Projects

Project Contrast is a video game that explores how the unique traits inherent to video games might engage reflective player responses to qualitative experience. Project Contrast does this through suspension of disbelief, avatar projection, presence, player agency in storytelling, visual perception, functional gameplay, and art. Considering the difficulty in researching qualitative experience due to its subjectivity and circular explanations, I created Project Contrast not to analyze qualia, though that was my original hope. I instead created Project Contrast as an avenue for player self-reflection and learning about qualitative experience. While video games might be just code and art on a …


Using Deep Neural Networks To Classify Astronomical Images, Andrew D. Macpherson May 2023

Using Deep Neural Networks To Classify Astronomical Images, Andrew D. Macpherson

Honors Projects

As the quantity of astronomical data available continues to exceed the resources available for analysis, recent advances in artificial intelligence encourage the development of automated classification tools. This paper lays out a framework for constructing a deep neural network capable of classifying individual astronomical images by describing techniques to extract and label these objects from large images.


A Machine Learning Approach To Sector Based Market Efficiency, Angus Zuklie Jan 2023

A Machine Learning Approach To Sector Based Market Efficiency, Angus Zuklie

Honors Projects

In economic circles, there is an idea that the increasing prevalence of algorithmic trading is improving the information efficiency of electronic stock markets. This project sought to test the above theory computationally. If an algorithm can accurately forecast near-term equity prices using historical data, there must be predictive information present in the data. Changes in the predictive accuracy of such algorithms should correlate with increasing or decreasing market efficiency.

By using advanced machine learning approaches, including dense neural networks, LSTM, and CNN models, I modified intra day predictive precision to act as a proxy for market efficiency. Allowing for the …