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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Description
#VanLife is a long-time, up and coming lifestyle movement on social media centered around the process of leaving the traditional nine-to-five work week for a life on the road in a camper van. While the ‘hippie-esque’ vagabond lifestyle has its humble roots long before the turn of the century, the inception of social media platforms such as Instagram and Pinterest have fueled the more recent popularization of a full-time life on the road. #VanLifers often freelance on the road, work part time jobs, or gain sponsorships to help fund their traveling and humble lifestyle.
As the #VanLife craze continues to grow, new businesses are finding ways to meet the demand in the market. For #Vanlifers who own and operate their own camper vans, specialized companies like GoWesty, Vanagain, and Boxeer offer a full range of parts, upgrades, and custom mechanical and systems conversion kits to keep these vans on the road as OE manufacturers discontinue production on these parts. For those who have an itch to try out the #VanLife for a shorter period and without the financial commitment, companies like Roamerica, TontoTrails, and adventureRIGS offer nightly and weekly rental opportunities on fully-outfitted campervans ready to hit the road.
For my Honors Project I wrote a complete analysis on the history, development, and modernization of the #VanLife movement. With plans to take to the road for an extended period of time after graduation, I also developed a complete financial plan for a one-year #VanLife experience. The financial plan includes a comprehensive set of budgets that scrutinize the start-up an operational costs of the #VanLife and associated travel.
As the #VanLife craze continues to grow, new businesses are finding ways to meet the demand in the market. For #Vanlifers who own and operate their own camper vans, specialized companies like GoWesty, Vanagain, and Boxeer offer a full range of parts, upgrades, and custom mechanical and systems conversion kits to keep these vans on the road as OE manufacturers discontinue production on these parts. For those who have an itch to try out the #VanLife for a shorter period and without the financial commitment, companies like Roamerica, TontoTrails, and adventureRIGS offer nightly and weekly rental opportunities on fully-outfitted campervans ready to hit the road.
For my Honors Project I wrote a complete analysis on the history, development, and modernization of the #VanLife movement. With plans to take to the road for an extended period of time after graduation, I also developed a complete financial plan for a one-year #VanLife experience. The financial plan includes a comprehensive set of budgets that scrutinize the start-up an operational costs of the #VanLife and associated travel.
ContributorsRischitelli, Noah Gary (Author) / Garverick, Michael (Thesis director) / Dawson, Gregory (Committee member) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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
In Spring 2015, I decided to study abroad in Granada, Spain. After scouring the Internet, I realized there was a lack of resources and information for study abroad students coming to the city. I decided to use my thesis project as an opportunity to create a multimedia, interactive e-book to help prospective study abroad students. This book walks them through what steps they need to take to prepare themselves and functions as a guide for when they arrive. It is a culmination of my own research, interviews with locals and surveys amongst other study abroad students.
ContributorsLongbons, Chandler Tenell (Author) / Thornton, Leslie (Thesis director) / Roschke, Kristy (Committee member) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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
Woman with Wanderlust is a travel blog made to break down the stereotypes of female travelers as they are portrayed in mass media. The idea came to me when I was preparing to study abroad in Morocco and every person I talked to felt the need to remind me how dangerous the world was for a woman on her own. There were many references to the popular movie ‘Taken’ starring Liam Neeson. When I decided I wanted to continue the blog on my backpacking trip through Europe, once again ‘Taken’ was referenced but people also insisted I was going to fall in love with an Italian man and never come home. It felt, to me, that the world saw the female traveler as naive and weak or in need of a man in her life. In contrast men are often encouraged to take years off to travel, to seek adventure or find themselves.
I decided I could use my education from the Cronkite School in writing, photography and social media to produce a resource for women looking to travel abroad. I could tell stories of my personal experiences that could both inspire and prove that a solo trip can be done. I also wanted to touch on topics that are not generally covered by popular travel blogs since they are specific to women. Topics like how to dress, making sure you travel during the day if you’re traveling alone and finding birth control or feminine hygiene products when you are traveling.
I funded the trip myself and currently the blog is designed, written and photographed entirely by me. Moving forward I would like to feature other women on my blog, especially those who have made travel a priority or a career. I plan on continuing to build the blog, hopefully gaining sponsors and becoming a more well known resources, and helping change the landscape of travel and travel blogging to become more female friendly.
I decided I could use my education from the Cronkite School in writing, photography and social media to produce a resource for women looking to travel abroad. I could tell stories of my personal experiences that could both inspire and prove that a solo trip can be done. I also wanted to touch on topics that are not generally covered by popular travel blogs since they are specific to women. Topics like how to dress, making sure you travel during the day if you’re traveling alone and finding birth control or feminine hygiene products when you are traveling.
I funded the trip myself and currently the blog is designed, written and photographed entirely by me. Moving forward I would like to feature other women on my blog, especially those who have made travel a priority or a career. I plan on continuing to build the blog, hopefully gaining sponsors and becoming a more well known resources, and helping change the landscape of travel and travel blogging to become more female friendly.
ContributorsMcfarland, Cydney Grey (Author) / Amparano, Julie (Thesis director) / Hawken-Collins, Denise (Committee member) / Barrett, The Honors College (Contributor) / Walter Cronkite School of Journalism and Mass Communication (Contributor)
Created2015-05
Description
Bots tamper with social media networks by artificially inflating the popularity of certain topics. In this paper, we define what a bot is, we detail different motivations for bots, we describe previous work in bot detection and observation, and then we perform bot detection of our own. For our bot detection, we are interested in bots on Twitter that tweet Arabic extremist-like phrases. A testing dataset is collected using the honeypot method, and five different heuristics are measured for their effectiveness in detecting bots. The model underperformed, but we have laid the ground-work for a vastly untapped focus on bot detection: extremist ideal diffusion through bots.
ContributorsKarlsrud, Mark C. (Author) / Liu, Huan (Thesis director) / Morstatter, Fred (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
Inspired by my own experiences, I began this study to examine students' cultural engagement while studying abroad. Students' motivations to study abroad vastly vary and no two experiences are the same, due to the multitude of factors involved. Study abroad program providers and organizations frequently cite intercultural competence as a vital skill in the 21st century for all young professionals to build, and is often a goal of students to develop through their study abroad experiences. Before departure, some students may have a romanticized, grand vision of integrating themselves in a foreign culture and learning the language. Upon arrival, reality may prove to be quite different and students can get swept up in the novelty of living in a new environment and traveling with their new American friends from the same program. The vision of intercultural competence and foreign language acquisition gradually fades when realizing just how difficult they both are to achieve, especially in such a short time period. My hope is that this study can highlight issues that returned students of study abroad programs faced while abroad and can provide valuable insight for future study abroad participants into how to become more immersed in their host culture. By creating awareness of the merits of intercultural competence and the methods to develop it through study abroad, future students can become better equipped to have a more enriching experience. https://cultureasustudyabroad.wordpress.com/
ContributorsThoesen, Raquel Nathania (Author) / Scott Lynch, Jacquelyn (Thesis director) / Herrera Niesen, Carrie (Committee member) / W. P. Carey School of Business (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05