Matching Items (26)
Description
With the advent of sophisticated computer technology, we increasingly see the use of computational techniques in the study of problems from a variety of disciplines, including the humanities. In a field such as poetry, where classic works are subject to frequent re-analysis over the course of years, decades, or even

With the advent of sophisticated computer technology, we increasingly see the use of computational techniques in the study of problems from a variety of disciplines, including the humanities. In a field such as poetry, where classic works are subject to frequent re-analysis over the course of years, decades, or even centuries, there is a certain demand for fresh approaches to familiar tasks, and such breaks from convention may even be necessary for the advancement of the field. Existing quantitative studies of poetry have employed computational techniques in their analyses, however, there remains work to be done with regards to the deployment of deep neural networks on large corpora of poetry to classify portions of the works contained therein based on certain features. While applications of neural networks to social media sites, consumer reviews, and other web-originated data are common within computational linguistics and natural language processing, comparatively little work has been done on the computational analysis of poetry using the same techniques. In this work, I begin to lay out the first steps for the study of poetry using neural networks. Using a convolutional neural network to classify author birth date, I was able to not only extract a non-trivial signal from the data, but also identify the presence of clustering within by-author model accuracy. While definitive conclusions about the cause of this clustering were not reached, investigation of this clustering reveals immense heterogeneity in the traits of accurately classified authors. Further study may unpack this clustering and reveal key insights about how temporal information is encoded in poetry. The study of poetry using neural networks remains very open but exhibits potential to be an interesting and deep area of work.
ContributorsGoodloe, Oscar Laurence (Author) / Nishimura, Joel (Thesis director) / Broatch, Jennifer (Committee member) / School of Mathematical and Natural Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
Creativity is a critical element of human cognition for which any complete explanation of the human mind must account, and it presents a unique problem to cognitive science because the apparent "something from nothing" nature of creativity confounds simple transformations of existing information. Emergentism provides a philosophical framework for explaining

Creativity is a critical element of human cognition for which any complete explanation of the human mind must account, and it presents a unique problem to cognitive science because the apparent "something from nothing" nature of creativity confounds simple transformations of existing information. Emergentism provides a philosophical framework for explaining this feature of creativity by elaborating how novel properties of a system can be created from the complex interactions of simple elements within that system. Previous advances in cognitive science have been built the traditional information processing models of cognition. These models are limited in their ability to explain emergentism or allow for detailed behavioral measurement and understanding of cognition as it unfolds in time. In this study, I piloted the use state-of-the-art dynamical systems models of cognition and motion capture technology to measure information about cognitive and neural processes in the moments preceding creative insight. Insight problem solving refers to the phenomenon of experiencing an impasse when attempting to solve a problem that is later overcome in a flash of insight, sometimes called an "Aha!" or "Eureka!" moment. The use of these techniques to study insight problem solving provides evidence of the dynamical nature of cognition during creative tasks that may help us explore how creativity emerges from neural activity.
ContributorsHart Jr, John Thomas (Author) / Duran, Nicholas (Thesis director) / Nishimura, Joel (Committee member) / School of Social and Behavioral Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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Description

As part of Arizona State University’s net-zero carbon initiative, 1000 mesquite trees were planted on a vacant plot of land at West Campus to sequester carbon from the atmosphere. Urban forestry is typically a method of carbon capture in temperate areas, but it is hypothesized that the same principle can

As part of Arizona State University’s net-zero carbon initiative, 1000 mesquite trees were planted on a vacant plot of land at West Campus to sequester carbon from the atmosphere. Urban forestry is typically a method of carbon capture in temperate areas, but it is hypothesized that the same principle can be employed in arid regions as well. To test this hypothesis a carbon model was constructed using the pools and fluxes measured at the Carbon sink and learning forest at West Campus. As an ideal, another carbon model was constructed for the mature mesquite forest at the Hassayampa River Preserve to project how the carbon cycle at West Campus could change over time as the forest matures. The results indicate that the West Campus plot currently functions as a carbon source while the site at the Hassayampa river preserve currently functions as a carbon sink. Soil composition at both sites differ with inorganic carbon contributing to the largest percentage at West Campus, and organic carbon at Hassayampa. Predictive modeling using biomass accumulation estimates and photosynthesis rates for the Carbon Sink Forest at West Campus both predict approximately 290 metric tons of carbon sequestration after 30 years. Modeling net ecosystem exchange predicts that the West Campus plot will begin to act as a carbon sink after 33 years.

ContributorsLiddle, David Mohacsy (Author) / Ball, Becky (Thesis director) / Nishimura, Joel (Committee member) / School of Life Sciences (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
DescriptionAs an aspiring math teacher, I have created visual representation of my philosophy of education in the form of an embroidered skirt, bringing together my love of sewing and mathematics.
ContributorsOng, Rachel (Author) / Nishimura, Joel (Thesis director) / Johnston, Carmen (Committee member) / Barrett, The Honors College (Contributor) / Division of Teacher Preparation (Contributor)
Created2023-05
Description

As an aspiring math teacher, I have created visual representation of my philosophy of education in the form of an embroidered skirt, bringing together my love of sewing and mathematics.

ContributorsOng, Rachel (Author) / Nishimura, Joel (Thesis director) / Johnston, Carmen (Committee member) / Barrett, The Honors College (Contributor) / Division of Teacher Preparation (Contributor)
Created2023-05
ContributorsOng, Rachel (Author) / Nishimura, Joel (Thesis director) / Johnston, Carmen (Committee member) / Barrett, The Honors College (Contributor) / Division of Teacher Preparation (Contributor)
Created2023-05
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ContributorsOng, Rachel (Author) / Nishimura, Joel (Thesis director) / Johnston, Carmen (Committee member) / Barrett, The Honors College (Contributor) / Division of Teacher Preparation (Contributor)
Created2023-05
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ContributorsOng, Rachel (Author) / Nishimura, Joel (Thesis director) / Johnston, Carmen (Committee member) / Barrett, The Honors College (Contributor) / Division of Teacher Preparation (Contributor)
Created2023-05
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ContributorsOng, Rachel (Author) / Nishimura, Joel (Thesis director) / Johnston, Carmen (Committee member) / Barrett, The Honors College (Contributor) / Division of Teacher Preparation (Contributor)
Created2023-05
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ContributorsOng, Rachel (Author) / Nishimura, Joel (Thesis director) / Johnston, Carmen (Committee member) / Barrett, The Honors College (Contributor) / Division of Teacher Preparation (Contributor)
Created2023-05