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.
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- All Subjects: Machine Learning
- All Subjects: Children
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
The purpose of this project is to raise awareness for children with social anxiety. As a book directed to children around the age of 12, it will give them a character they can relate to, so they can feel less alone. Throughout the story, the main character experiences symptoms of social anxiety and is subject to events that exacerbate those symptoms. Despite her challenges, the main character is able to effectively cope with her social anxiety through her own hard work, and help from her family members, teachers, and peers. The intent is to show children with social anxiety that, contrary to what their disorder makes them feel, they are special and have the capacity to develop skills that are relevant to their talents and interests, and overcome their fears. They should know that parents, teachers, and peers will be there to help and support them and will not judge them as harshly as they suspect. The supporting characters in this story show how a strong support base can influence the success of children with social anxiety. By the end of the story, the main character still has social anxiety, but has gained confidence and her symptoms are less severe. This illustrates that, although social anxiety cannot simply be overcome—that is, it doesn’t go away completely—it can be effectively managed with assistance from close others, and perseverance.
ContributorsDillard, Bethlehem (Author) / Lewis, Stephen (Thesis director) / Gaffney, Cynthia (Committee member) / School of Social and Behavioral Sciences (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
In Arizona, there are virtually no established support groups or services for children on the autism spectrum and their families when experiencing the loss of a loved one. This is due to many factors, including the complexity of autism, an inconsistent belief that children with autism are capable of grieving, and a general lack of research conducted on the crossover of children with autism and grief. This proposal is based on the social work strengths perspective, in which I argue that children living with autism are capable of grieving and need support to do so. The way families and practitioners approach grief among children with autism is with individual counseling based on a therapist's discretion, grief books and guides, and virtual communities. I attempt to compile evidence-based and practical activities, interviews with parents and professionals, and my experience in order to recommend effective support for children with autism experiencing loss. My hope is that caregivers will use this material in order to understand and help a neglected population find the language and means to safely grieve.
ContributorsCohen, Jessica Marie (Author) / Ingram-Waters, Mary (Thesis director) / Stuckey, Michelle (Committee member) / School of Criminology and Criminal Justice (Contributor) / School of Social Work (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
As part of a group project, myself and four teammates created an interactive children's storybook based off of the "Young Lady's Illustrated Primer" in Neal Stephenson's novel The Diamond Age. This electronic book is meant to be read aloud by a caregiver with their child, and is designed for reading over long distances through the use of real-time voice and video calling. While one part of the team focused on building the electronic book itself and writing the program, myself and two others wrote the story and I provided illustrations. Our Primer tells the story of a young princess named Charname (short for character name) who escapes from a tower and goes on a mission to save four companions to help her on her quest. The book is meant for reader-insertion, and teaches children problem-solving, teamwork, and critical thinking skills by presenting challenges for Princess Charname to solve. The Primer borrows techniques from modern video game design, focusing heavily on interactivity and feelings of agency through offering the child choices of how to proceed, similar to choose-your-own-adventure books. If brought to market, the medium lends itself well to expanded quests and storylines for the child to explore as they learn and grow. Additionally, resources are provided for the narrator to help create an engaging experience for the child, based off of research on parent-child cooperative reading and cooperative gameplay. The final version of the Primer included a website to run the program, a book-like computer to access the program online, and three complete story segments for the child and narrator to read together.
ContributorsLax, Amelia Ann Riedel (Author) / Dove-Viebahn, Aviva (Thesis director) / Wetzel, Jon (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Popular culture tends to downplay strong female characters to favor a plethora of male figures that children look up to as heroes. This creates a gender imbalance in exposure to inspirational characters that children can look up to as role models. For our team's creative project, we chose to write and illustrate a children's book mainly targeted at young girls, ages eight to twelve that focuses on the stories of selected female figures of Norse mythology. The five stories in our collection focus on the figures Frigg, Skadi, Elli, Idunn, and Freya and are inspired by the mythology contained in the Prose Edda by Snorri Sturluson and selected medieval texts on the Germanic Lombard tribe. Through our book, Women of Norse Myth: For Little Goddesses, we wanted to introduce children to Norse mythology, a branch of myth that is often overshadowed by more popular mythologies such as Roman and Greek. Additionally, our goal was to bring light to the female figures within Norse myth that are generally given less attention than their male counterparts. Keeping in mind these goals, the stories were adapted from the original myths in a manner that would be suitable for a young audience as well as our aim for female empowerment. The final manuscript contains an introduction to Norse cosmology, introductions to the figures, a glossary of Norse terms used, and the illustrated stories themselves. Together with our combined talents, interests, and goals, Women of Norse Myth: For Little Goddesses was completed, and we hope that someday it can be published and serve as a fun and inspiring storybook for children to read and learn from.
ContributorsFarine, Brittany (Co-author) / Muth, Margaret (Co-author) / Youngjohn, Trystan (Co-author) / Alexander, John (Thesis director) / Wells, Cornelia (Committee member) / Department of English (Contributor) / Department of Psychology (Contributor) / School of Human Evolution and Social Change (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The author examined the relationship between social intelligence and attachment style, specifically how attachment style affects how individuals respond to social intelligence training. Students at the Herberger Young Scholars Academy, a school for the highly gifted, completed an online social intelligence training program through the Social Intelligence Institute and were assessed on a number of items. These items include the Tromso Social Intelligence Scale (TSIS), the Attachment Questionnaire for Children (AQ-C), and a daily diary measure in which they recorded and rated their social interactions day to day. All participants were found to be either securely or insecurely attached, and those that were insecurely attached were further divided into insecure anxious attachment style and insecure avoidant attachment style. It was hypothesized that those with a secure attachment style would have higher initial TSIS scores than those with an insecure attachment style. It was also hypothesized that insecurely attached individuals would benefit more from the social intelligence training program than securely attached individuals indicated by "In tune" scores from the daily diaries, and insecure avoidant individuals would benefit more from the program than insecure anxious individuals indicated by "In tune" scores from the daily diaries. None of these hypotheses were supported by the data, as there was no significant difference between the initial social intelligence scores of the three attachment styles, and none of the variables measured were found to be significant predictors of "In tune" scores. Key Words: social intelligence, social intelligence training, attachment, attachment style, children, adolescents, gifted, IQ, high IQ
ContributorsPrice, Christina Nicole (Author) / Zautra, Alex (Thesis director) / Knight, George (Committee member) / Mickelson, Kristin (Committee member) / Barrett, The Honors College (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor) / Department of Psychology (Contributor)
Created2014-12
Description
Children today are being primed with technology at very young ages, leading to a more digitally focused lifestyle. Tangentially, today's digital culture has led to the increase of online shopping rather than in-store shopping. A group of students at Arizona State University's Innovation Space program, in partnership with Disney Consumer Products, set out to create a children's product that bridged the physical-digital gap, and encouraged outdoor activity. The result of their work was Blitz: a versatile, outdoor gaming console that brings traditional outdoor fun into the digital world. This thesis and paired creative project are an extension of the research and development done by the Blitz team. The purpose of this additional research is to discover how parents and children shop online in to design a website to market and sell the Blitz gaming system. Some of the topics covered include visual design, functionality, user interaction, and marketing tactics. The goal is not to develop advertising tactics to manipulate children, but to find the best ways to design for, and market children's products.
ContributorsPoindexter, Devin Alan (Author) / Fehler, Michelle (Thesis director) / Peck, Sidnee (Committee member) / Barrett, The Honors College (Contributor) / Department of Marketing (Contributor) / Department of Finance (Contributor)
Created2014-12