Physical Sciences and Mathematics Commons^™

Computer Simulation Of The Light Absorption Band Of The Jumping Spider Isorhodopsin, Noah Zoldak

Honors Projects

In order to simulate the photoisomerization of the 9-cis Jumping Spider Isorhodopsin (JSiR-1) it is necessary to first simulate its light-absorption band. Here we report on the absorption band simulated using protein models constructed using the advanced Automatic Rhodopsin Modeling (a-ARM) program. A population of S₀ models was created and the corresponding S₀ to S₁ transitions were determined for each member of the resulting population. The calculation resulted in a Gaussian plot showing that the wavelength of the absorption maximum of 560 nm (a violet color) that is consistent, but red-shifted, with respect the experimentally observed value.

Behaviors For Which Deinonychosaurs Used Their Feet, Alexander King

Honors Projects

This paper seeks to show for what purpose deinonychosaurs used their feet. Fowler et al., (2011) showed that D. antirrhopus’s feet were closest in function to accipitrids, as they found it was more built for grasping prey than running.

I answered this question by using 2D images of the feet of three modern birds (Buteo jamaicensis, Phasianus colchicus, and Gallus gallus domesticus), one eudromaeosaur (Deinonychus antirrhopus), and one troodontid (Borogovia gracilicrus). I used ImageJ to apply 73 landmarks to each foot, capturing the variation between species in the metatarsals and pedal phalanges. These data were then uploaded to the software …

Read This: A Content Analysis Framework For Book Recommendation Applications, Cypress S. Payne

Honors Projects

Book recommendation applications combine word-of-mouth recommendations with algorithms that can suggest books based on a user’s account activity, creating a robust system for finding new books to read. Current research on recommendation systems is purely quantitative, focusing on the efficacy of the system, and content analyses are only just beginning to be performed on mobile applications. I use previous content analyses on applications as a basis for creating a content analysis framework for book recommendation applications. This framework can be used to analyze what users find important in book recommendation apps and inform app creators about their users’ wants and …

The Quest For New Music: A Recommendation Algorithm For Spotify Users, Ian Curtis

Honors Projects

Music is one of the rare forms of communication that can be understood on a profound level by anyone; it has the power to cause significant emotional effects, to spark inspiration, to ignite change, to spread knowledge, and more, even regardless of song language. A popular subject of research in music pertains to recommendations; determining a song a listener would enjoy is not an easy task. Moreover, certain factors may influence a user's satisfaction with recommended songs and their likelihood to continue using a service. Focusing on the major streaming service Spotify, we build a K-Means clustering algorithm to recommend …

Outlier Detection In Energy Datasets, Stephen Crawford

Honors Projects

In the past decade, numerous datasets have been released with the explicit goal of furthering non-intrusive load monitoring research (NILM). NILM is an energy measurement strategy that seeks to disaggregate building-scale loads. Disaggregation attempts to turn the energy consumption of a building into its constituent appliances. NILM algorithms require representative real-world measurements which has led institutions to publish and share their own datasets. NILM algorithms are designed, trained, and tested using the data presented in a small number of these NILM datasets. Many of the datasets contain arbitrarily selected devices. Likewise, the datasets themselves report aggregate load information from building(s) …

Exploiting Context In Linear Influence Games: Improved Algorithms For Model Selection And Performance Evaluation, Daniel Little

Honors Projects

In the recent past, extensive experimental works have been performed to predict joint voting outcomes in Congress based on a game-theoretic model of voting behavior known as Linear Influence Games. In this thesis, we improve the model selection and evaluation procedure of these past experiments. First, we implement two methods, Nested Cross-Validation with Tuning (Nested CVT) and Bootstrap Bias Corrected Cross-Validation (BBC-CV), to perform model selection and evaluation with less bias than previous methods. While Nested CVT is a commonly used method, it requires learning a large number of models; BBC-CV is a more recent method boasting less computational cost. …