Barrett, The Honors College Thesis/Creative Project Collection
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.
Displaying 1 - 10 of 193
Filtering by
- All Subjects: Machine Learning
- All Subjects: Fiction
Leveraging Machine Learning and Wireless Sensing for Robot Localization - Location Variance Analysis
Description
Object localization is used to determine the location of a device, an important aspect of applications ranging from autonomous driving to augmented reality. Commonly-used localization techniques include global positioning systems (GPS), simultaneous localization and mapping (SLAM), and positional tracking, but all of these methodologies have drawbacks, especially in high traffic indoor or urban environments. Using recent improvements in the field of machine learning, this project proposes a new method of localization using networks with several wireless transceivers and implemented without heavy computational loads or high costs. This project aims to build a proof-of-concept prototype and demonstrate that the proposed technique is feasible and accurate.
Modern communication networks heavily depend upon an estimate of the communication channel, which represents the distortions that a transmitted signal takes as it moves towards a receiver. A channel can become quite complicated due to signal reflections, delays, and other undesirable effects and, as a result, varies significantly with each different location. This localization system seeks to take advantage of this distinctness by feeding channel information into a machine learning algorithm, which will be trained to associate channels with their respective locations. A device in need of localization would then only need to calculate a channel estimate and pose it to this algorithm to obtain its location.
As an additional step, the effect of location noise is investigated in this report. Once the localization system described above demonstrates promising results, the team demonstrates that the system is robust to noise on its location labels. In doing so, the team demonstrates that this system could be implemented in a continued learning environment, in which some user agents report their estimated (noisy) location over a wireless communication network, such that the model can be implemented in an environment without extensive data collection prior to release.
Modern communication networks heavily depend upon an estimate of the communication channel, which represents the distortions that a transmitted signal takes as it moves towards a receiver. A channel can become quite complicated due to signal reflections, delays, and other undesirable effects and, as a result, varies significantly with each different location. This localization system seeks to take advantage of this distinctness by feeding channel information into a machine learning algorithm, which will be trained to associate channels with their respective locations. A device in need of localization would then only need to calculate a channel estimate and pose it to this algorithm to obtain its location.
As an additional step, the effect of location noise is investigated in this report. Once the localization system described above demonstrates promising results, the team demonstrates that the system is robust to noise on its location labels. In doing so, the team demonstrates that this system could be implemented in a continued learning environment, in which some user agents report their estimated (noisy) location over a wireless communication network, such that the model can be implemented in an environment without extensive data collection prior to release.
ContributorsChang, Roger (Co-author) / Kann, Trevor (Co-author) / Alkhateeb, Ahmed (Thesis director) / Bliss, Daniel (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
At present, the vast majority of human subjects with neurological disease are still diagnosed through in-person assessments and qualitative analysis of patient data. In this paper, we propose to use Topological Data Analysis (TDA) together with machine learning tools to automate the process of Parkinson’s disease classification and severity assessment. An automated, stable, and accurate method to evaluate Parkinson’s would be significant in streamlining diagnoses of patients and providing families more time for corrective measures. We propose a methodology which incorporates TDA into analyzing Parkinson’s disease postural shifts data through the representation of persistence images. Studying the topology of a system has proven to be invariant to small changes in data and has been shown to perform well in discrimination tasks. The contributions of the paper are twofold. We propose a method to 1) classify healthy patients from those afflicted by disease and 2) diagnose the severity of disease. We explore the use of the proposed method in an application involving a Parkinson’s disease dataset comprised of healthy-elderly, healthy-young and Parkinson’s disease patients.
ContributorsRahman, Farhan Nadir (Co-author) / Nawar, Afra (Co-author) / Turaga, Pavan (Thesis director) / Krishnamurthi, Narayanan (Committee member) / Electrical Engineering Program (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
In this project, the use of deep neural networks for the process of selecting actions to execute within an environment to achieve a goal is explored. Scenarios like this are common in crafting based games such as Terraria or Minecraft. Goals in these environments have recursive sub-goal dependencies which form a dependency tree. An agent operating within these environments have access to low amounts of data about the environment before interacting with it, so it is crucial that this agent is able to effectively utilize a tree of dependencies and its environmental surroundings to make judgements about which sub-goals are most efficient to pursue at any point in time. A successful agent aims to minimizes cost when completing a given goal. A deep neural network in combination with Q-learning techniques was employed to act as the agent in this environment. This agent consistently performed better than agents using alternate models (models that used dependency tree heuristics or human-like approaches to make sub-goal oriented choices), with an average performance advantage of 33.86% (with a standard deviation of 14.69%) over the best alternate agent. This shows that machine learning techniques can be consistently employed to make goal-oriented choices within an environment with recursive sub-goal dependencies and low amounts of pre-known information.
ContributorsKoleber, Derek (Author) / Acuna, Ruben (Thesis director) / Bansal, Ajay (Committee member) / W.P. Carey School of Business (Contributor) / Software Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This thesis dives into the world of artificial intelligence by exploring the functionality of a single layer artificial neural network through a simple housing price classification example while simultaneously considering its impact from a data management perspective on both the software and hardware level. To begin this study, the universally accepted model of an artificial neuron is broken down into its key components and then analyzed for functionality by relating back to its biological counterpart. The role of a neuron is then described in the context of a neural network, with equal emphasis placed on how it individually undergoes training and then for an entire network. Using the technique of supervised learning, the neural network is trained with three main factors for housing price classification, including its total number of rooms, bathrooms, and square footage. Once trained with most of the generated data set, it is tested for accuracy by introducing the remainder of the data-set and observing how closely its computed output for each set of inputs compares to the target value. From a programming perspective, the artificial neuron is implemented in C so that it would be more closely tied to the operating system and therefore make the collected profiler data more precise during the program's execution. The program is designed to break down each stage of the neuron's training process into distinct functions. In addition to utilizing more functional code, the struct data type is used as the underlying data structure for this project to not only represent the neuron but for implementing the neuron's training and test data. Once fully trained, the neuron's test results are then graphed to visually depict how well the neuron learned from its sample training set. Finally, the profiler data is analyzed to describe how the program operated from a data management perspective on the software and hardware level.
ContributorsRichards, Nicholas Giovanni (Author) / Miller, Phillip (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This creative project consists of three short stories with a common theme of release, letting go, and exhalation. Nymphal Instar is a story about Tommy, a young boy, and his encounter with his uncle, a troubled man who has just returned from war. The story explores the idea of growth and maturation, and the ability to move past and let go of trauma. A Cat Goes Away is about a young man, Richard, who is required to simultaneously deal with the loss of his cat and the suicide attempts of his sister. He also runs into his sister's ex-husband and is forced to deal with him. The story explores the difficulty in recognizing one's own emotions and the importance of knowing the difference between what one can change and what one cannot. Since Diagnosis is a story about Kate, a woman who has just been diagnosed with cancer and who is unable to tell her loved ones. The story explores acceptance and the idea that letting go can allow one to live more fully. Though the three stories are disparate in their characters and events, they share a commonality in their endings and in the final realizations of the characters. There is a focus on the importance of breath and breathing, and the essentiality of acceptance and release.
ContributorsMyers, Alan Yutaka (Author) / McNally, T. M. (Thesis director) / Irish, Jenny (Committee member) / School of International Letters and Cultures (Contributor) / Department of English (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
"The Problem of Hope: Literary Tragedy in Mid-Twentieth Century American Fiction" examines Arthur Miller's Death of a Salesman, Ralph Ellison's Invisible Man, and Sylvia Plath's The Bell Jar through the lens of tragedy. This thesis delves into how conflicts between internal and external identities can create a tragic individual, what kinds of success count toward achievement of the "American Dream," and whether the tragic "common man" is the socially normative one or the socially disenfranchised one. It raises a three-dimensional theoretical approach to American tragedy and, most importantly, considers the significance of tragic hope for American literature. This paper questions the construction of American identities across class, race, and gender according to social scripts. It seeks to uncover what forces these scripts exert on American cultural myths and rereads those myths through tragedy to explore Miller's idea of a noble common man. By moving from Miller to Ellison to Plath, this thesis traces the undercurrents of tragedy through some of the most identity-focused novels of mid-twentieth century American fiction to see how the overarching American narrative changed from 1940 to 1969 as the US underwent significant social changes domestically and image changes abroad. Ultimately, this paper concludes that tragedy in mid-twentieth century American fiction points toward a new idea of American success as a success that occurs beyond social scripts.
ContributorsMedeiros, Amy Marie (Author) / Holbo, Christine (Thesis director) / Sadowski-Smith, Claudia (Committee member) / Department of English (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Prince Shendi is a novella set in the semi-fictional continent of Great Africa, specifically in a proud and prosperous region called Serengeti. Our story follows the thrilling adventure of Serengeti's king-to-be, the young and naive Shendi. When Kovalu, the mighty king of Serengeti and Shendi's father, passes away due to old age, Shendi is thrust into the gauntlet of responsibility in an early and unprepared state. After a short foray as the amateur king heavily assisted by the tenured members of Serengeti's Plain Council, Shendi encounters disaster that results in the death of an important council representative and the young king's temporary exile from Serengeti. The journey produced by his one hundred day exile takes Shendi through an arid wasteland, a teeming jungles, a mystic desert, and every terrain in between before his return. Along the way, Shendi unravels the details of a prophecy that means the end of the peaceful and prosperous life his lion kin and other Serengeti dwellers had known for centuries. This prophecy held him at the center of it as the catalyst and ultimately it would be up to Shendi and his actions to stop the ancient evil at work from killing all the lions of his pride and plunging all of Serengeti into a desolate and dismal state. Will Shendi overcome the primal evil looking to dominate the land of Great Africa forevermore? And if so, what will become of him afterwards? Prince Shendi was written over the course of 2015 and early 2016 by Lucas Revelle, a student at Arizona State University studying Exercise and Wellness as well as a student of Barrett, the Honors College. The story was directed, advised, and edited by Honors Fellow Dr. Aviva Dove-Viebahn along with help from the project's 2nd reader, Rebecca Viles.
ContributorsRevelle, Lucas Benjamin (Author) / Dove-Viebahn, Aviva (Thesis director) / Viles, Rebecca (Committee member) / School of Nutrition and Health Promotion (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Abstract "Empty Horizons": A Creative Writing Piece Max Harmon "Empty Horizons" is a creative writing piece composed of two different short stories sharing a common narrator. The first story "Can you dig it?" details a trip the narrator takes to South Dakota to go hunting shortly before starting college. On the trip the narrator contemplates certain aspects of his life and the events of the story serve as a vehicle to explore the narrator's mindset as an eighteen year old about to start a new phase in his life. The second story "Toads, Sharks and Beautiful Encounters with Uncertainty" takes place during the summer before the narrator begins his last semester in college as he attends the funeral of his recently deceased grandmother in Hawaii. During the trip to Hawaii, the narrator meets a girl his age and they are able to bond with each other over feelings of loss and uncertainty. In this story the narrator explores his feelings about life with college graduation on the horizon and comes to terms with some of the anxieties that have been plaguing him since the start of college. By detailing these two distinct and important time periods in the narrator's life the reader is able to gain a sense of understanding in regards to the narrator's own process of beginning life as an adult.
ContributorsHarmon, Max Doyle (Author) / Soares, Rebecca (Thesis director) / Popova, Laura (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2014-12
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 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
Description
The title means nothing because the stories have little in common, aside from the fact that I wrote them. The common theme of anxiety was unintentional, though it is prevalent in the stories, poetry and my life. Each story is written from a different style, with a different interest in mind. The poetry that breaks up the stories is mine, and also free of common bonds. People whom I love inspired some of them; others stem from people with whom I was (or still am) angry. Some of them are just me trying to write poetry like other successful poets, who seem to know something I don't. I wrote this set of stories and poems because I wanted to see if I could do it. I wanted to challenge myself in a new medium (two new mediums really, if you separate literature and poetry). I wanted to prove to myself that I could do it, if I really set my mind to it. I wanted to have some wealth of words, which I could record myself reading. Overall, I hope that you enjoy these stories and words. I wrote them to entertain myself, and they seem to do that pretty well. If you don't like them, stop reading. If you do like them, keep reading and tell everyone you know about this collection. I'm proud of my work here, so anything beyond that is icing on my cake.
ContributorsRagatz, Zachariah Edward (Author) / Scott, Jason Davids (Thesis director) / Espinosa, Micha (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Film, Dance and Theatre (Contributor)
Created2015-05