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Description
Salivary cortisol is the least invasive way in measuring hormonal response during exercise without interruption. In nationally ranked fencers (n=21), changes in cortisol were monitored by measurement of salivary cortisol sampled throughout different rounds of three North American Cup tournaments during the 2017-2018 United States fencing season. The changes were also compared when looking at if a bout ended in a victory or defeat; the difference in rank between opponents; and the difference in score at the end of the bout. Immediately before the tournament cortisol levels were sampled, changes were in comparison to the initial sample as well as change from one bout to the next. The primary purpose of this study was to (a) compare how cortisol levels fluctuate during a tournament and (b) analyze cortisol levels to see if there is an optimal rage for performance. Eustress, “good stress” was considered optimal when the athletes were at peak performance. Here, peak performance means accomplishing the task, with the task being the bout ending in a victory. It was hypothesized that (a) cortisol levels would peak after a loss or stressful bout and (b) there would be an optimal range of cortisol for peak performance. This study supports the findings that cortisol peaks after a loss, and could point to optimal cortisol levels being more of an individualized range for each athlete. If these athletes can explicitly see just how their hormones rise and fall, then perhaps being more aware of these levels and being able to embrace them could lead to peak performance.
ContributorsVie, Jerica Nicole (Author) / Baluch, D. Page (Thesis advisor) / Sterner, Beckett (Committee member) / Cataldo, Donna (Committee member) / Arizona State University (Publisher)
Created2018
Description
The current trend of interconnected devices, or the internet of things (IOT) has led to the popularization of single board computers (SBC). This is primarily due to their form-factor and low price. This has led to unique networks of devices that can have unstable network connections and minimal processing power. Many parallel program- ming libraries are intended for use in high performance computing (HPC) clusters. Unlike the IOT environment described, HPC clusters will in general look to obtain very consistent network speeds and topologies. There are a significant number of software choices that make up what is referred to as the HPC stack or parallel processing stack. My thesis focused on building an HPC stack that would run on the SCB computer name the Raspberry Pi. The intention in making this Raspberry Pi cluster is to research performance of MPI implementations in an IOT environment, which had an impact on the design choices of the cluster. This thesis is a compilation of my research efforts in creating this cluster as well as an evaluation of the software that was chosen to create the parallel processing stack.
ContributorsO'Meara, Braedon Richard (Author) / Meuth, Ryan (Thesis director) / Dasgupta, Partha (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This thesis discusses three recent optimization problems that seek to reduce disease spread on arbitrary graphs by deleting edges, and it discusses three approximation algorithms developed for these problems. Important definitions are presented including the Linear Threshold and Triggering Set models and the set function properties of submodularity and monotonicity. Also, important results regarding the Linear Threshold model and computation of the influence function are presented along with proof sketches. The three main problems are formally presented, and NP-hardness results along with proof sketches are presented where applicable. The first problem seeks to reduce spread of infection over the Linear Threshold process by making use of an efficient tree data structure. The second problem seeks to reduce the spread of infection over the Linear Threshold process while preserving the PageRank distribution of the input graph. The third problem seeks to minimize the spectral radius of the input graph. The algorithms designed for these problems are described in writing and with pseudocode, and their approximation bounds are stated along with time complexities. Discussion of these algorithms considers how these algorithms could see real-world use. Challenges and the ways in which these algorithms do or do not overcome them are noted. Two related works, one which presents an edge-deletion disease spread reduction problem over a deterministic threshold process and the other which considers a graph modification problem aimed at minimizing worst-case disease spread, are compared with the three main works to provide interesting perspectives. Furthermore, a new problem is proposed that could avoid some issues faced by the three main problems described, and directions for future work are suggested.
ContributorsStanton, Andrew Warren (Author) / Richa, Andrea (Thesis director) / Czygrinow, Andrzej (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
In the last few years, billion-dollar companies like Yahoo and Equifax have had data breaches causing millions of people’s personal information to be leaked online. Other billion-dollar companies like Google and Facebook have gotten in trouble for abusing people’s personal information for financial gain as well. In this new age of technology where everything is being digitalized and stored online, people all over the world are concerned about what is happening to their personal information and how they can trust it is being kept safe. This paper describes, first, the importance of protecting user data, second, one easy tool that companies and developers can use to help ensure that their user’s information (credit card information specifically) is kept safe, how to implement that tool, and finally, future work and research that needs to be done. The solution I propose is a software tool that will keep credit card data secured. It is only a small step towards achieving a completely secure data anonymized system, but when implemented correctly, it can reduce the risk of credit card data from being exposed to the public. The software tool is a script that can scan every viable file in any given system, server, or other file-structured Linux system and detect if there any visible credit card numbers that should be hidden.
ContributorsPappas, Alexander (Author) / Zhao, Ming (Thesis director) / Kuznetsov, Eugene (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Political polarization is the coalescence of political parties -- and the individuals of which parties are composed -- around opposing ends of the ideological spectrum. Political parties in the United States have always been divided, however, in recent years this division has only intensified. Recently, polarization has also wound its way to the Supreme Court and the nomination processes of justices to the Court. This paper examines how prevalent polarization in the Supreme Court nomination process has become by looking specifically at the failed nomination of Judge Merrick Garland and the confirmations of now-Justices Neil Gorsuch and Brett Kavanaugh. This is accomplished by comparing the ideologies and qualifications of the three most recent nominees to those of previous nominees, as well as analysing the ideological composition of the Senate at the times of the individual nominations.
ContributorsJoss, Jacob (Author) / Hoekstra, Valerie (Thesis director) / Critchlow, Donald (Committee member) / Computer Science and Engineering Program (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
The original version of Helix, the one I pitched when first deciding to make a video game
for my thesis, is an action-platformer, with the intent of metroidvania-style progression
and an interconnected world map.
The current version of Helix is a turn based role-playing game, with the intent of roguelike
gameplay and a dark fantasy theme. We will first be exploring the challenges that came
with programming my own game - not quite from scratch, but also without a prebuilt
engine - then transition into game design and how Helix has evolved from its original form
to what we see today.
for my thesis, is an action-platformer, with the intent of metroidvania-style progression
and an interconnected world map.
The current version of Helix is a turn based role-playing game, with the intent of roguelike
gameplay and a dark fantasy theme. We will first be exploring the challenges that came
with programming my own game - not quite from scratch, but also without a prebuilt
engine - then transition into game design and how Helix has evolved from its original form
to what we see today.
ContributorsDiscipulo, Isaiah K (Author) / Meuth, Ryan (Thesis director) / Kobayashi, Yoshihiro (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
RecyclePlus is an iOS mobile application that allows users to be knowledgeable in the realms of sustainability. It gives encourages users to be environmental responsible by providing them access to recycling information. In particular, it allows users to search up certain materials and learn about its recyclability and how to properly dispose of the material. Some searches will show locations of facilities near users that collect certain materials and dispose of the materials properly. This is a full stack software project that explores open source software and APIs, UI/UX design, and iOS development.
ContributorsTran, Nikki (Author) / Ganesh, Tirupalavanam (Thesis director) / Meuth, Ryan (Committee member) / Watts College of Public Service & Community Solut (Contributor) / Department of Information Systems (Contributor) / Computer Science and 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
As the prevalence and awareness of Autism Spectrum Disorder (ASD) increases, so does the variety of treatment options for primary symptoms (social interaction, communication, behavior) and secondary symptoms (anxiety, hyperactivity, GI problems, and insomnia). Various treatments, from Adderall to Citalopram to Flax Seed Oil promise relief for these symptoms. However, very little research has actually been done on some of these treatments. Additionally, the research that has been done fails to compare these treatments against one another in terms of symptom relief. The Autism Treatment Effectiveness Survey, written by Dr. James Adams, director of the Autism/Asperger's Research Program at ASU, and graduate student/program coordinator Devon Coleman, aims to fill this gap. The survey numerically rates medications based on benefit and adverse effects, in addition to naming specific symptoms that are impacted by the treatments. However, the survey itself was retrospective in nature and requires further evidence to support its claims. Therefore, the purpose of this research paper is to evaluate evidence related to the results of the survey. After the performing an extensive literature review of over 70 different treatments, it appears that the findings of the Autism Treatment Effectiveness Survey are generally well supported. There were a few minor discrepancies regarding the primary benefitted symptom, but there was not enough of a conflict to discount the information from the survey. As research is still ongoing, conclusions cannot yet be drawn for Nutritional Supplements, although the current data looks promising.
ContributorsAnderson, Amy Lynn (Author) / Adams, James (Thesis director) / Coleman, Devon (Committee member) / School of Nutrition and Health Promotion (Contributor) / W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
After freelancing on my own for the past year and a half, I have realized that one of the biggest obstacles to college entrepreneurs is a fear or apprehension to sales. As a computer science major trying to sell my services, I discovered very quickly that I had not been prepared for the difficulty of learning sales. Sales get a bad rap and very often is the last thing that young entrepreneurs want to try, but the reality is that sales is oxygen to a company and a required skill for an entrepreneur. Due to this, I compiled all of my knowledge into an e-book for young entrepreneurs starting out to learn how to open up a conversation with a prospect all the way to closing them on the phone. Instead of starting from scratch like I did, college entrepreneurs can learn the bare basics of selling their own services, even if they are terrified of sales and what it entails. In this e-book, there are tips that I have learned to deal with my anxiety about sales such as taking the pressure off of yourself and prioritizing listening more than pitching. Instead of trying to teach sales expecting people to be natural sales people, this e-book takes the approach of helping entrepreneurs that are terrified of sales and show them how they can cope with this fear and still close a client. In the future, I hope young entrepreneurs will have access to more resources that handle this fear and make it much easier for them to learn it by themselves. This e-book is the first step.
ContributorsMead, Kevin Tyler (Author) / Sebold, Brent (Thesis director) / Kruse, Gabriel (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05