Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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- Creators: Electrical Engineering Program
- Creators: School of Community Resources and Development
Description
Few studies have examined the correlations between individual characteristics and other popular forms of social media other than Facebook. This study explored the ways emerging adults use Instagram and Snapchat and examined the relationships between social media and individual characteristics. A sample of 393 participants were recruited from a large university in the Southwestern United States. The participants completed an online questionnaire that included a newly developed social media measure along with established measures that examined the individual characteristics of social comparison orientation, self-esteem, loneliness, contingent self-worth, narcissism, and life satisfaction. In the present study, more participants reported having an active Instagram account than an active Facebook or Snapchat account. Additionally, a higher number of participants also reported preferring Instagram and Snapchat compared to Facebook. Significant correlations were found between various individual characteristics and three aspects of social media use: overall time spent on social media, whether the individual felt that their time spent on social media was meaningful, and how the individual felt emotionally after comparing themselves to others' photos and posts. Potential explanations and implications of the results are discussed.
ContributorsArndorfer, Sydney (Author) / Field, Ryan (Thesis director) / Sechler, Casey (Committee member) / School of Community Resources and Development (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Breast microcalcifications are a potential indicator of cancerous tumors. Current visualization methods are either uncomfortable or impractical. Impedance measurement studies have been performed, but not in a clinical setting due to a low sensitivity and specificity. We are hoping to overcome this challenge with the development of a highly accurate impedance probe on a biopsy needle. With this technique, microcalcifications and the surrounding tissue could be differentiated in an efficient and comfortable manner than current techniques for biopsy procedures. We have developed and tested a functioning prototype for a biopsy needle using bioimpedance sensors to detect microcalcifications in the human body. In the final prototype a waveform generator sends a sin wave at a relatively low frequency(<1KHz) into the pre-amplifier, which both stabilizes and amplifies the signal. A modified howland bridge is then used to achieve a steady AC current through the electrodes. The voltage difference across the electrodes is then used to calculate the impedance being experienced between the electrodes. In our testing, the microcalcifications we are looking for have a noticeably higher impedance than the surrounding breast tissue, this spike in impedance is used to signal the presence of the calcifications, which are then sampled for examination by radiology.
ContributorsWen, Robert Bobby (Co-author) / Grula, Adam (Co-author) / Vergara, Marvin (Co-author) / Ramkumar, Shreya (Co-author) / Kozicki, Michael (Thesis director) / Ranjani, Kumaran (Committee member) / School of Molecular Sciences (Contributor) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The town of Guadalupe, Arizona has a long history of divided residents and high poverty rates. The high levels of poverty in the town can be attributed to numerous factors, most notably high rates of drug abuse, low high school graduation rates, and teen pregnancy. The town has named one of its most pressing issues of today to be youth disengagement. There are currently a handful of residents and community members passionate about finding a solution to this issue. After working with Guadalupe's Ending Hunger Task Force and resident youth, I set out to create a program design for a Guadalupe Youth Council. This council will contribute to combating youth disengagement. The program design will assist the task force in creating a standing youth council and deciding on the structure and role the council has in the town. I will offer learning outcomes and suggestions to the Task Force, youth council staff, and the youth of the youth council. This study contains an analysis of relevant literature, youth focus group results and data, and how the information gathered has contributed to the design of the youth council. The results of this study contain recommendations about four themes within the program design of a youth council: size, recruitment, activities and engagement, and adult support. The results also explore how the youth council will impact the power, policy, and behavior of Guadalupe youth.
ContributorsBalderas, Erica Theresa (Author) / Wang, Lili (Thesis director) / Avalos, Francisco (Committee member) / School of Community Resources and Development (Contributor) / Department of Information Systems (Contributor) / W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Television is currently in a changing state. There is no longer a singular broadcast format for series to follow. Streaming websites such as Netflix, Hulu, and Amazon Prime now release series in their entirety; this is known as a full-season release (FSR). Viewers are now able to act independently and determine the pace they wish to watch a new FSR series. This not only affects how fans engage in social television discussions on social media, but also changes the previously proposed viewer engagement model. Whereas previous research suggests that fans follow a static linear engagement model consisting of pre-communication, parallel communication, and post communication phases, fans are now able to move freely through viewer engagement phases. This creates a new type of engagement model: The Atomized Engagement Model. As fans move freely through the atomized engagement phases, they choose social media platforms to engage in fandom discussion. Research suggests that although there are distinct types of posts that occur in relation to social television discussions, the platforms used have a direct effect on the content and length of the post.
ContributorsPouls, Samantha Rae (Author) / Gilpin, Dawn (Thesis director) / Barrett, Marianne (Committee member) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / School of Community Resources and Development (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
The nonprofit sector has experienced exponential growth in recent decades, thus creating a separate industry for nonprofits—an industry that requires education and training to run efficiently and successfully. As a result, Nonprofit Management Education (NME) at both graduate and undergraduate levels has steadily increased in number and demand. Recent changes in the political climate and changes in the government funding present new challenges to nonprofit professionals, thus enhancing the value of specific NME to prepare professionals for these challenges. To leverage NME and ensure that students are adequately prepared for these challenges, it is important to design curriculum that addresses the needs of the growing nonprofit industry. The Nonprofit Academic Center of Councils is the creator of the NACC Curricular Guidelines, which are currently used as a model all NME curricula should emulate. This study utilizes Arizona State University (ASU) to compare its current curriculum model to the NACC Curricular Guidelines, as well as the current challenges facing the nonprofit sector. In so doing, this study will provide an in-depth overview of NME at ASU through 1) focus groups of nonprofit leaders; 2) survey data from former students; and 3) curriculum mapping.
The comprehensive results indicated areas of opportunity for both ASU and the NACC Curricular Guidelines. According to the feedback of students, nonprofit professionals, and the current state of the ASU curriculum, ASU may wish to increase emphasis on Financial Management, Managing Staff and Volunteers, Assessment, Evaluation, and Decision Making, and Leading and Managing Nonprofit Organizations. After considering feedback from nonprofit professionals, NACC may consider amending some new competencies that reflect an emphasis on collective impact, cross sector leadership, or relationship building and the use of technology for nonprofit impact. The research team recommends accomplishing these changes through enhancing pedagogy by including case studies and an integrated curriculum into the ASU NME program. by applying the suggested changes to both the ASU curriculum and the NACC guidelines, this research prepares both ASU and NACC towards the process of accreditation and formalizing the NLM degree on a national level.
The comprehensive results indicated areas of opportunity for both ASU and the NACC Curricular Guidelines. According to the feedback of students, nonprofit professionals, and the current state of the ASU curriculum, ASU may wish to increase emphasis on Financial Management, Managing Staff and Volunteers, Assessment, Evaluation, and Decision Making, and Leading and Managing Nonprofit Organizations. After considering feedback from nonprofit professionals, NACC may consider amending some new competencies that reflect an emphasis on collective impact, cross sector leadership, or relationship building and the use of technology for nonprofit impact. The research team recommends accomplishing these changes through enhancing pedagogy by including case studies and an integrated curriculum into the ASU NME program. by applying the suggested changes to both the ASU curriculum and the NACC guidelines, this research prepares both ASU and NACC towards the process of accreditation and formalizing the NLM degree on a national level.
ContributorsFindlay, Molly Rebecca (Author) / Legg, Eric (Thesis director) / Ashcraft, Robert (Committee member) / Department of Information Systems (Contributor) / School of Community Resources and Development (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Buck converters are a class of switched-mode power converters often used to step down DC input voltages to a lower DC output voltage. These converters naturally produce a current and voltage ripple at their output due to their switching action. Traditional methods of reducing this ripple have involved adding large discrete inductors and capacitors to filter the ripple, but large discrete components cannot be integrated onto chips. As an alternative to using passive filtering components, this project investigates the use of active ripple cancellation to reduce the peak output ripple. Hysteretic controlled buck converters were chosen for their simplicity of design and fast transient response. The proposed cancellation circuits sense the output ripple of the buck converter and inject an equal ripple exactly out of phase with the sensed ripple. Both current-mode and voltage-mode feedback loops are simulated, and the effectiveness of each cancellation circuit is examined. Results show that integrated active ripple cancellation circuits offer a promising substitute for large discrete filters.
ContributorsWang, Ziyan (Author) / Bakkaloglu, Bertan (Thesis director) / Kitchen, Jennifer (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
This creative project thesis involves electronic music composition and production, and it uses some elements of algorithmic music composition (through recurrent neural networks). Algorithmic composition techniques are used here as a tool in composing the pieces, but are not the main focus. Thematically, this project explores the analogy between artificial neural networks and neural activity in the brain. This project consists of three short pieces, each exploring these concept in different ways.
ContributorsKarpur, Ajay (Author) / Suzuki, Kotoka (Thesis director) / Ingalls, Todd (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The Phoenix CubeSat is a 3U Earth imaging CubeSat which will take infrared (IR) photos of cities in the United Stated to study the Urban Heat Island Effect, (UHI) from low earth orbit (LEO). It has many different components that need to be powered during the life of its mission. The only power source during the mission will be its solar panels. It is difficult to calculate power generation from solar panels by hand because of the different orientations the satellite will be positioned in during orbit; therefore, simulation will be used to produce power generation data. Knowing how much power is generated is integral to balancing the power budget, confirming whether there is enough power for all the components, and knowing whether there will be enough power in the batteries during eclipse. This data will be used to create an optimal design for the Phoenix CubeSat to accomplish its mission.
ContributorsBarakat, Raymond John (Author) / White, Daniel (Thesis director) / Kitchen, Jennifer (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05