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: Sanford School of Social and Family Dynamics
- Creators: Electrical Engineering Program
Description
The inherent risk in testing drugs has been hotly debated since the government first started regulating the drug industry in the early 1900s. Who can assume the risks associated with trying new pharmaceuticals is unclear when looked at through society's lens. In the mid twentieth century, the US Food and Drug Administration (FDA) published several guidance documents encouraging researchers to exclude women from early clinical drug research. The motivation to publish those documents and the subsequent guidance documents in which the FDA and other regulatory offices established their standpoints on women in drug research may have been connected to current events at the time. The problem of whether women should be involved in drug research is a question of who can assume risk and who is responsible for disseminating what specific kinds of information. The problem tends to be framed as one that juxtaposes the health of women and fetuses and sets their health as in opposition. That opposition, coupled with the inherent uncertainty in testing drugs, provides for a complex set of issues surrounding consent and access to information.
ContributorsMeek, Caroline Jane (Author) / Maienschein, Jane (Thesis director) / Brian, Jennifer (Committee member) / School of Life Sciences (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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
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 current study investigated whether intermittent restraint stress (IRS) would impair fear extinction learning and lead to increased anxiety and depressive- like behaviors and then be attenuated when IRS ends and a post- stress rest period ensues for 6 weeks. Young adult, male Sprague Dawley rats underwent restraint stress using wire mesh (6hr/daily) for five days with two days off before restraint resumed for three weeks for a total of 23 restraint days. The groups consisted of control (CON) with no restraint other than food and water restriction yoked to the restrained groups, stress immediate (STR-IMM), which were restrained then fear conditioned soon after the end of the IRS paradigm, and stress given a rest for 6 weeks before fear conditioning commenced (STR-R6). Rats were fear conditioned by pairing a 20 second tone with a footshock, then given extinction training for two days (15 tone only on each day). On the first day of extinction, all groups discriminated well on the first trial, but then as trials progressed, STR-R6 discriminated between tone and context less than did CON. On the second day of extinction, STR- IMM froze more to context in the earlier trials than compared to STR-R6 and CON. As trials progressed STR-IMM and STR-R6 froze more to context than compared to CON. Together, CON discriminated between tone and context better than did STR-IMM and STR-R6. Sucrose preference, novelty suppressed feeding, and elevated plus maze was performed after fear extinction was completed. No statistical differences were observed among groups for sucrose preference or novelty suppressed feeding. For the elevated plus maze, STR-IMM entered the open arms and the sum of both open and closed arms fewer than did STR- R6 and CON. We interpret the findings to suggest that the stress groups displayed increased hypervigilance and anxiety with STR-R6 exhibiting a unique phenotype than that of STR-IMM and CON.
ContributorsShah, Vrishti Bimal (Author) / Conrad, Cheryl (Thesis director) / Newbern, Jason (Committee member) / Judd, Jessica (Committee member) / School of Life Sciences (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
22q11.2 Deletion Syndrome (22q11.2DS) is one of the most frequent chromosomal microdeletion syndromes in humans. This case study focuses on the language and reading profile of a female adult with 22q11.2 Deletion Syndrome who was undiagnosed until the age of 27 years old. To comprehensively describe the participant's profile, a series of assessment measures was administered in the speech, language, cognition, reading, and motor domains. Understanding how 22q11.2DS has impacted the life of a recently diagnosed adult will provide insight into how to best facilitate long-term language and educational support for this population and inform future research.
ContributorsPhilp, Jennifer Lynn (Author) / Scherer, Nancy (Thesis director) / Peter, Beate (Committee member) / Department of Speech and Hearing Science (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Same Bed is a twelve-piece book of poetry that explores the theme of sexual violence. The speaker of the poems is processing the trauma surrounding her rape which leads her to explore her own family's dynamics regarding gender, power, and acknowledgment of sexuality. The speaker also observes the broader issue of how society reacts to rape and the effects that can have on a survivor of sexual violence. In the peak of the manuscript, the speaker pieces together part of her own police report, pinning her own voice and perspective against her rapists.
ContributorsPetersen, Gabrielle Nicole (Author) / Ball, Sally (Thesis director) / Kelsey, Meghan (Committee member) / Sanford School of Social and Family Dynamics (Contributor) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Researchers suggests that college students' involvement and use of resources on campus are important for success, in the form of satisfaction and GPA, in the first year. College officials invest substantial resources in activities to encourage freshmen students to become involved in campus activities and utilize resources that promote successful outcomes, yet we do not know which activities best relate to success. Using a self-report survey, we sought to corroborate previous research that has shown that overall levels of involvement and use of resources relate to satisfaction/GPA. Furthermore, we disentangled which individual types of involvement and use of resources are most highly correlated with satisfaction and GPA. And finally, we identified the barriers and benefits to involvement and resource use, according to the students themselves. We found evidence that higher levels of involvement were related to satisfaction and attending faculty office hours appears to be particularly important, given a significant relation to both satisfaction and GPA. Implications for program promotion and resource allocation are discussed.
ContributorsPaley, Madeleine (Author) / Foster, Stacie (Thesis director) / Spinrad, Tracy (Committee member) / Sanford School of Social and Family Dynamics (Contributor) / School of Life Sciences (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