Honors Projects
Showing 81 - 90 of 298 Items
The Best and the Brightest?: Race, Class, and Merit in America's Elite Colleges
Date: 2017-05-01
Creator: Walter Chacon
Access: Open access
The Body Negotiating Unprecedented Movement
Date: 2024-01-01
Creator: Mei Bock
Access: Open access
- A collection of poems exploring threads including the Lower East Side, immigration, stray animals, art, and Chinese-American identity.
Modulation of the crustacean cardiac neuromuscular system by the SLY neuropeptide family
Date: 2024-01-01
Creator: Grant Griesman
Access: Open access
- Central pattern generators (CPGs) are neuronal networks that produce rhythmic motor output in the absence of sensory stimuli. Invertebrate CPGs are valuable models of neural circuit dynamics and neuromodulation because they continue to generate fictive activity in vitro. For example, the cardiac ganglion (CG) of the Jonah crab (Cancer borealis) and American lobster (Homarus americanus) contains nine electrochemically coupled neurons that fire bursts of action potentials to trigger a heartbeat. The CG is modulated by neuropeptides, amines, small molecule transmitters, gases, and mechanosensory feedback pathways that enable flexibility and constrain output. One such modulator, the SLY neuropeptide family, was previously shown to be expressed in hormonal release sites and within the CG itself and has unusual processing features. However, its physiological effect was unknown. Here, I performed dose-response experiments in the crab and lobster whole heart and isolated CG to determine the threshold concentration of SLY neuropeptides to which these systems respond. The crab isoform had strong, excitatory effects in the crab whole heart and weakly modulated the crab CG. The lobster isoform weakly modulated the lobster whole heart and CG. Surprisingly, the crab isoform exerted large, variable effects on the lobster system, which suggests that SLY neuropeptides, their receptors, and their signaling pathways may be evolutionarily conserved across these two species. This research contributes to our understanding of how neural circuits can generate flexible output in response to modulation. It may also offer insight into processes influenced by peptidergic neurotransmission in the nervous systems of other animals, including mammals.
Basins of Attraction and Metaoptimization for Particle Swarm Optimization Methods
Date: 2024-01-01
Creator: David Ma
Access: Open access
- Particle swarm optimization (PSO) is a metaheuristic optimization method that finds near- optima by spawning particles which explore within a given search space while exploiting the best candidate solutions of the swarm. PSO algorithms emulate the behavior of, say, a flock of birds or a school of fish, and encapsulate the randomness that is present in natural processes. In this paper, we discuss different initialization schemes and meta-optimizations for PSO, its performances on various multi-minima functions, and the unique intricacies and obstacles that the method faces when attempting to produce images for basins of attraction, which are the sets of initial points that are mapped to the same minima by the method. This project compares the relative strengths and weaknesses of the Particle Swarm with other optimization methods, namely gradient-descent, in the context of basin mapping and other metrics. It was found that with proper parameterization, PSO can amply explore the search space regardless of initialization. For all functions, the swarm was capable of finding, within some tolerance, the global minimum or minima in fewer than 60 iterations by having sufficiently well chosen parameters and parameterization schemes. The shortcomings of the Particle Swarm method, however, are that its parameters often require fine-tuning for different search spaces to most efficiently optimize and that the swarm cannot produce the analytical minimum. Overall, the PSO is a highly adaptive and computationally efficient method with few initial restraints that can be readily used as the first step of any optimization task.
A Machine Learning Approach to Sector Based Market Efficiency
Date: 2023-01-01
Creator: Angus Zuklie
Access: Open access
- 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 basic comparisons of the weak form efficiency of four sectors over the same time period: utilities, healthcare, technology and energy. Finally, Within these sectors, I was able to detect inefficiencies in the stock market up to four years closer to modern day than previous studies.
Real-Time Object Recognition using a Multi-Framed Temporal Approach
Date: 2018-05-01
Creator: Corinne Alini
Access: Open access
- Computer Vision involves the extraction of data from images that are analyzed in order to provide information crucial to many modern technologies. Object recognition has proven to be a difficult task and programming reliable object recognition remains elusive. Image processing is computationally intensive and this issue is amplified on mobile platforms with processor restrictions. The real-time constraints demanded by robotic soccer in RoboCup competition serve as an ideal format to test programming that seeks to overcome these challenges. This paper presents a method for ball recognition by analyzing the movement of the ball. Major findings include enhanced ball discrimination by replacing the analysis of static images with absolute change in brightness in conjunction with the classification of apparent motion change.
Geochemical and Stratigraphic Analysis of the Linnévatnet Sediment Record: A Study of Late Holocene Cirque Glacier Activity in Spitsbergen, Svalbard
Date: 2014-05-01
Creator: Graham Harper Edwards
Access: Open access
- Morainal and lacustrine sediments in Linnédalen, Spitsbergen, Svalbard, record the fluctuations of a glacier in a currently unglaciated mountain cirque during the Little Ice Age (LIA). This study attempts to reconstruct Late Holocene glacial activity within this cirque from geochemical, physical, and visual stratigraphic variation of the Linnévatnet lacustrine sediment record. A 57 cm lacustrine sediment core (D10.5) from Linnévatnet was analyzed at a high-resolution for variations in X-Ray Fluorescence (XRF)-measured elemental composition, spectral reflectance, and magnetic susceptibility. The visual stratigraphy was observed at a microscopic scale. An age-depth model for D10.5 is developed by extrapolating sedimentation rates from dated horizons, measured by 239+240Pu radionuclide fallout dating and chemostratigraphic enrichment of atmospheric anthropogenic pollutants. Visual stratigraphy of the sediment record indicates two periods of cirque glacier sediment delivery to Linnévatnet during the LIA (1329-1363 CE, 1816 CE-Present) and a third period of sediment delivery during the Medieval Climate Anomaly (MCA; 984-1082 CE). During non-glacial periods, stratigraphic variation in XRF-measured Ti and K appear to be associated with fluctuations in North Atlantic Oscillation (NAO)-regulated precipitation. Within the LIA glacial intervals, decadal-scale variations in sediment Ti and K geochemistry may result from advance and retreat of the cirque glacier ice-margin or fluctuations in precipitation. Stratigraphic variation in Fe content indicates complex erosional and hydrological processes associated with MCA precipitation and glacial meltwater. Stratigraphic and geochemical variations in the lacustrine record of Linnévatnet indicate that both cirque glacier activity and sediment transport in Linnédalen are more sensitive to climatological change than previously thought.
Seize the Memes: Community, Personal Expression, and Everyday Feminist Politics Through Instagram Memes
Date: 2018-01-01
Creator: Tessa Westfall
Access: Open access
ALGOrhythms: Leveraging Markov Chain-Based Generation of Functional Harmonies with User-Defined Musical Corpus as a Compositional Tool
Date: 2021-01-01
Creator: Coleman Brockmeier
Access: Open access
- Music forms the soundtrack to daily life and serves as an important cultural marker for people around the world. As the world becomes digitized and connected via the internet, the opportunity is increasingly accessible for anyone to share music with the world and to create chart-topping music that defines the cultural vernacular. Many prominent producers have little to no formal musical training, especially in Western music theory. As a result, loop-based music dominates the lists of most-played music on the radio and streaming services, often not deviating from basic functional harmony. With this project, I have created a compositional tool in the form of an iOS app which identifies the harmonic “fingerprint” behind a given set of songs. The app then leverages this understanding to create sequences of chords in the style of that fingerprint. To accomplish this, the app employs web scraping to create a corpus of musical information in the form of Markov chains — a transition table which underlies the data set. I introduce the idea of musical “chunks” defining a harmonic “fingerprint” and various methods of traversing the transition table to create chord progressions employing the fingerprint as a guide. The tool allows for specification of corpus, chunk size, traversal method, and the ability to listen to, share, and save generated results. The resulting app is a tool that allows the user to answer the question: “What would happen if Stevie Wonder and Billie Eilish wrote a song together?”
Economic Analysis of the Critical Habitat Designation Process for Endangered and Threatened Species Under the Endangered Species Act of 1973
Date: 2022-01-01
Creator: Katherine Fosburgh
Access: Open access
- Habitat destruction is the leading cause of biodiversity loss in the US. Under the Endangered Species Act (ESA), habitat deemed essential to endangered and threatened species recovery is proposed as critical habitat (CH). CH areas are subject to regulations that could alter land development plans or increase costs. The potential economic opportunity cost created by CH regulations may lead to the exclusion of land proposed for CH designation, thereby reducing the conservation benefits of the CH rule. In this paper, I use a unique dataset collected from Federal Register (FR) documents to estimate the reduction in CH acreage from proposed to final ruling, both on the extensive and intensive margin. I find a negative relationship between the level of household income in an area proposed for CH and the probability that a CH gains acreage or maintains acreage during the establishment process. I also find some evidence that higher household income in a CH area is associated with a greater relative loss in acreage between proposal and finalization. I also find that private land proposed for CH designation is less likely to be in the final designation than federal land. Overall, my results suggest that economic considerations influence CH allocation decisions. Whether reducing the amount of private land subject to CH designations is socially efficient depends on the unknown economic benefit of private land exclusions versus the cost of biodiversity and ecosystem service loss that may result from not protecting all land deemed vital to species recovery.