Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.

Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.

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Description
Epilepsy affects numerous people around the world and is characterized by recurring seizures, prompting the ability to predict them so precautionary measures may be employed. One promising algorithm extracts spatiotemporal correlation based features from intracranial electroencephalography signals for use with support vector machines. The robustness of this methodology is tested

Epilepsy affects numerous people around the world and is characterized by recurring seizures, prompting the ability to predict them so precautionary measures may be employed. One promising algorithm extracts spatiotemporal correlation based features from intracranial electroencephalography signals for use with support vector machines. The robustness of this methodology is tested through a sensitivity analysis. Doing so also provides insight about how to construct more effective feature vectors.
ContributorsMa, Owen (Author) / Bliss, Daniel (Thesis director) / Berisha, Visar (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2015-05
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Description
The marmoset monkey (Callithrix jacchus) is a new-world primate species native to South America rainforests. Because they rely on vocal communication to navigate and survive, marmosets have evolved as a promising primate model to study vocal production, perception, cognition, and social interactions. The purpose of this project is to provide

The marmoset monkey (Callithrix jacchus) is a new-world primate species native to South America rainforests. Because they rely on vocal communication to navigate and survive, marmosets have evolved as a promising primate model to study vocal production, perception, cognition, and social interactions. The purpose of this project is to provide an initial assessment on the vocal repertoire of a marmoset colony raised at Arizona State University and call types they use in different social conditions. The vocal production of a colony of 16 marmoset monkeys was recorded in 3 different conditions with three repeats of each condition. The positive condition involves a caretaker distributing food, the negative condition involves an experimenter taking a marmoset out of his cage to a different room, and the control condition is the normal state of the colony with no human interference. A total of 5396 samples of calls were collected during a total of 256 minutes of audio recordings. Call types were analyzed in semi-automated computer programs developed in the Laboratory of Auditory Computation and Neurophysiology. A total of 5 major call types were identified and their variants in different social conditions were analyzed. The results showed that the total number of calls and the type of calls made differed in the three social conditions, suggesting that monkey vocalization signals and depends on the social context.
ContributorsFernandez, Jessmin Natalie (Author) / Zhou, Yi (Thesis director) / Berisha, Visar (Committee member) / School of International Letters and Cultures (Contributor) / Department of Psychology (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05