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Description
This ethnography outlines the live storytelling culture in Phoenix, Arizona, and what each of its sub-cultures contributes to the city's community. Phoenix's live storytelling events incorporate elements of an ancient art form into contemporary entertainment and sophisticated platforms for community building. These events are described and delineated by stylistic, structural, and content-based differences into the following categories: open-mic, curated, scripted, non-scripted, micro-culture, and marginalized groups. Research presented in this report was collected by reviewing scholarly materials about the social power of storytelling, attending live storytelling events across all categories, and interviewing event organizers and storytellers. My research developed toward an auto-ethnographic direction when I joined the community of storytellers in Phoenix, shifting the thesis to assume a voice of solidarity with the community. This resulted in a research project framed primarily as an ethnography that also includes my initial, personal experiences as a storyteller. The thesis concludes with the art form's macro-influences on Phoenix's rapidly-expanding community.
ContributorsNorton, Maeve (Author) / Dombrowski, Rosemarie (Thesis director) / McAdams, Charity (Committee member) / School of International Letters and Cultures (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
The Experimental Data Processing (EDP) software is a C++ GUI-based application to streamline the process of creating a model for structural systems based on experimental data. EDP is designed to process raw data, filter the data for noise and outliers, create a fitted model to describe that data, complete a probabilistic analysis to describe the variation between replicates of the experimental process, and analyze reliability of a structural system based on that model. In order to help design the EDP software to perform the full analysis, the probabilistic and regression modeling aspects of this analysis have been explored. The focus has been on creating and analyzing probabilistic models for the data, adding multivariate and nonparametric fits to raw data, and developing computational techniques that allow for these methods to be properly implemented within EDP. For creating a probabilistic model of replicate data, the normal, lognormal, gamma, Weibull, and generalized exponential distributions have been explored. Goodness-of-fit tests, including the chi-squared, Anderson-Darling, and Kolmogorov-Smirnoff tests, have been used in order to analyze the effectiveness of any of these probabilistic models in describing the variation of parameters between replicates of an experimental test. An example using Young's modulus data for a Kevlar-49 Swath stress-strain test was used in order to demonstrate how this analysis is performed within EDP. In order to implement the distributions, numerical solutions for the gamma, beta, and hypergeometric functions were implemented, along with an arbitrary precision library to store numbers that exceed the maximum size of double-precision floating point digits. To create a multivariate fit, the multilinear solution was created as the simplest solution to the multivariate regression problem. This solution was then extended to solve nonlinear problems that can be linearized into multiple separable terms. These problems were solved analytically with the closed-form solution for the multilinear regression, and then by using a QR decomposition to solve numerically while avoiding numerical instabilities associated with matrix inversion. For nonparametric regression, or smoothing, the loess method was developed as a robust technique for filtering noise while maintaining the general structure of the data points. The loess solution was created by addressing concerns associated with simpler smoothing methods, including the running mean, running line, and kernel smoothing techniques, and combining the ability of each of these methods to resolve those issues. The loess smoothing method involves weighting each point in a partition of the data set, and then adding either a line or a polynomial fit within that partition. Both linear and quadratic methods were applied to a carbon fiber compression test, showing that the quadratic model was more accurate but the linear model had a shape that was more effective for analyzing the experimental data. Finally, the EDP program itself was explored to consider its current functionalities for processing data, as described by shear tests on carbon fiber data, and the future functionalities to be developed. The probabilistic and raw data processing capabilities were demonstrated within EDP, and the multivariate and loess analysis was demonstrated using R. As the functionality and relevant considerations for these methods have been developed, the immediate goal is to finish implementing and integrating these additional features into a version of EDP that performs a full streamlined structural analysis on experimental data.
ContributorsMarkov, Elan Richard (Author) / Rajan, Subramaniam (Thesis director) / Khaled, Bilal (Committee member) / Chemical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Ira A. Fulton School of Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This project analyzes the tweets from the 2016 US Presidential Candidates' personal Twitter accounts. The goal is to define distinct patterns and differences between candidates and parties use of social media as a platform. The data spans the period of September 2015 to March 2016, which was during the primary races for the Republicans and Democrats. The overall purpose of this project is to contribute to finding new ways of driving value from social media, in particular Twitter.
ContributorsMortimer, Schuyler Kenneth (Author) / Simon, Alan (Thesis director) / Mousavi, Seyedreza (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
There is a disconnect between the way people are taught to find success and happiness, and the results observed. Society teaches us that success will lead to happiness. Instead, it is argued that success is engrained in happiness. Case studies of four, established, successful people: Jack Ma, Elon Musk, Ricardo Semler, and William Gore, have been conducted in order to observe an apparent pattern. This data, coupled with the data from Michael Boehringer's story, is used to formulate a solution to the proposed problem. Each case study is designed to observe characteristics of the individuals that allow them to be successful and exhibit traits of happiness. Happiness will be analyzed in terms of passion and desire to perform consistently. Someone who does what they love, paired with the ability to perform on a regular basis, is considered to be a happy person. The data indicates that there is an observable pattern within the results. From this pattern, certain traits have been highlighted and used to formulate guidelines that will aid someone falling short of success and happiness in their lives. The results indicate that there are simple questions that can guide people to a happier life. Three basic questions are defined: is it something you love, can you see yourself doing this every day and does it add value? If someone can answer yes to all three requirements, the person will be able to find happiness, with success following. These guidelines can be taken and applied to those struggling with unhappiness and failure. By creating such a formula, the youth can be taught a new way of thinking that will help to eliminate these issues, that many people are facing.
ContributorsBoehringer, Michael Alexander (Author) / Kashiwagi, Dean (Thesis director) / Kashiwagi, Jacob (Committee member) / Department of Management (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor) / Sandra Day O'Connor College of Law (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The purpose of our research was to develop recommendations and/or strategies for Company A's data center group in the context of the server CPU chip industry. We used data collected from the International Data Corporation (IDC) that was provided by our team coaches, and data that is accessible on the internet. As the server CPU industry expands and transitions to cloud computing, Company A's Data Center Group will need to expand their server CPU chip product mix to meet new demands of the cloud industry and to maintain high market share. Company A boasts leading performance with their x86 server chips and 95% market segment share. The cloud industry is dominated by seven companies Company A calls "The Super 7." These seven companies include: Amazon, Google, Microsoft, Facebook, Alibaba, Tencent, and Baidu. In the long run, the growing market share of the Super 7 could give them substantial buying power over Company A, which could lead to discounts and margin compression for Company A's main growth engine. Additionally, in the long-run, the substantial growth of the Super 7 could fuel the development of their own design teams and work towards making their own server chips internally, which would be detrimental to Company A's data center revenue. We first researched the server industry and key terminology relevant to our project. We narrowed our scope by focusing most on the cloud computing aspect of the server industry. We then researched what Company A has already been doing in the context of cloud computing and what they are currently doing to address the problem. Next, using our market analysis, we identified key areas we think Company A's data center group should focus on. Using the information available to us, we developed our strategies and recommendations that we think will help Company A's Data Center Group position themselves well in an extremely fast growing cloud computing industry.
ContributorsJurgenson, Alex (Co-author) / Nguyen, Duy (Co-author) / Kolder, Sean (Co-author) / Wang, Chenxi (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Department of Management (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Accountancy (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Research has found there is a lack of women present in the IS industry. In order to combat this problem, this research examines why women are not choosing IS majors at the university level. At Arizona State University, the Computer Information Systems undergraduate degree program is only 23 percent female. Many different factors can influence the decision to choose a major, so survey methodology was used to ascertain what factors were the most important to different demographic groups when making this decision. The study found no significant gender difference when making this decision, but rather a difference between specific majors. Genuine interest, interesting work and high career earnings were identified as the most influential reasons for choosing a college major. The results were used to create recommendations for the IS Department at ASU to implement in the next year and encourage more female participation in the CIS undergraduate degree program.
ContributorsJorgenson, Erica Marie (Author) / Santanam, Raghu (Thesis director) / Moser, Kathleen (Committee member) / Department of Information Systems (Contributor) / W. P. Carey School of Business (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The objective of this study was to better understand promising pathways to realizing human rights norms in the context of rapidly developing cities, and the role that the courts play in this process. Scholars have already started to ask these larger questions of social transformation; however, there continues to be a need for further research since the answers are vast and context-dependent. In order to contribute to these larger conversations, this project examined a key social right in Delhi \u2014 the right to housing. This study relied on interviews with key actors in Delhi's housing sector as well as a review of housing rights cases in the Delhi High Court in order to understand what mechanisms various actors utilize in the context of Delhi to realize the human right to housing on the ground. These two types of data were compared and contrasted to past research on human rights scholarship, law and social literature, and studies on urbanization. Two frameworks from these bodies of knowledge, the MAPs framework developed by Haglund and Aggarwal (2011) and the triangular framework created by Gauri and Brinks (2008), were utilized in particular to analyze interview and court data. Overall, this study found that the courts in India are advocates for housing rights, but that their advocacy is often limited, cautious, and influenced by a pattern of bias against populations without legal title to land. This study also found that communities and their allies are often more successful in realizing the right to housing when they combine litigation with other non-legal social change mechanisms. Consequently, it appears that the role of the courts in realizing ESR in Delhi is both complicated and limited, which means that pathways toward ESR realization are more promising when they incorporate non-legal mechanisms alongside court action.
ContributorsHale, Nicole (Author) / Haglund, LaDawn (Thesis director) / Aggarwal, Rimjhim (Committee member) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Limited researches have studied on the dissonance of the representations of a destination by using difference induced agents such as government, trade media tourism articles, and visual representations. This study examines the United Kingdom's image, and determines whether the dissonance exist pre- and post- referendum in the internal imagery of the United Kingdom and imagery portrayed aboard. Leading newspapers from the United States, United Kingdom, and Europe are analyzed to determine the predominant themes. Semi-structured interviews are conducted with the U.S. tour operators and Arizona's travel agents. Tour brochures and user-generated content on TripAdvisor are analyzed to study tourists' responses to Brexit. Skift is analyzed to project future growth in tourism industry. Results show that the leadings newspapers projects similar concerns negatively and positively pre- and post- referendum. Uncertainty in policy changes leads to other themes that are identified such as investment, employment, trade, independence, market growth, etc. It projects the international trade, domestic market growth and global market growth will be significantly impact by Brexit due to higher tariff and regulations on migrants in the United Kingdom. In contrast, travel brochures are marketing UK from heritage, historical attractions, and special events, but they do not reflect the influence of Brexit on how tour operators market UK pre- and post- referendum. Further data is conducted on the semi-structured interviews with travel agents across Arizona, but travel agents responded with Brexit has no influences on US tourists. Additional content analysis on VisitBritain/VisitEngland shows the growth in tourism industry by an increasing provided data collection on tourism performance that reflect there is an increasing departure rate of US tourists in UK after the referendum. User-generated content on TripAdvisor and Skift align with the identified themes in leading newspapers from US, UK, and Europe such as uncertainty in policy change. The present study further outlines preferable method to advance future studies on the destination image of U.K. during and after the Brexit.
ContributorsLuo, Shiyu (Author) / Chhabra, Deepak (Thesis director) / Timothy, Dallen (Committee member) / W. P. Carey School of Business (Contributor) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
As mobile devices have risen to prominence over the last decade, their importance has been increasingly recognized. Workloads for mobile devices are often very different from those on desktop and server computers, and solutions that worked in the past are not always the best fit for the resource- and energy-constrained computing that characterizes mobile devices. While this is most commonly seen in CPU and graphics workloads, this device class difference extends to I/O as well. However, while a few tools exist to help analyze mobile storage solutions, there exists a gap in the available software that prevents quality analysis of certain research initiatives, such as I/O deduplication on mobile devices. This honors thesis will demonstrate a new tool that is capable of capturing I/O on the filesystem layer of mobile devices running the Android operating system, in support of new mobile storage research. Uniquely, it is able to capture both metadata of writes as well as the actual written data, transparently to the apps running on the devices. Based on a modification of the strace program, fstrace and its companion tool fstrace-replay can record and replay filesystem I/O of actual Android apps. Using this new tracing tool, several traces from popular Android apps such as Facebook and Twitter were collected and analyzed.
ContributorsMor, Omri (Author) / Zhao, Ming (Thesis director) / Zhao, Ziming (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
This thesis examines Endgame, a gaming themed bar and restaurant located in the heart of Tempe, Arizona on Mill Avenue. The business serves regular bar fare and offers a wide selection of video games for its customers to play and enjoy. Recently Endgame recognized that it was unsatisfied with its current revenue stream, prompting this investigative study. Upon completing this project, three business problems that are limiting Endgame's revenue growth were identified. The issues identified were: food sales, visibility/access, and alcohol sales. To better understand each of these issues a study was conducted in the form of ethnography research and a survey was distributed to Endgame's target market. Two instances of observational research were conducted and a survey was distributed to 400+ students in the W. P. Carey School of Business. The data collected revealed underlying sentiments about Endgame's food/beverage service and issues related to locating the bar. This investigation revealed that ordering food and beverages at Endgame is difficult and not a straight forward process. This led to a set of recommendations related to creating an efficient and simple ordering process. The study also showed that Endgame (which is on the second floor of a building) lacks the appropriate signage to indicate its location. Using this information, recommendations were made for Endgame to create additional signage near stairs and elevators to indicate their location. The research also revealed a general lack of consumer awareness in relation to alcoholic beverages that contributed to low sales. This led to a strategy to revitalize Endgame's marketing campaign and a redesign of their beverage menu. Outside of the three business problems found during observational research, several other areas were examined in the survey at the request of Endgame's management. These areas revealed additional understandings into consumer behavior and feelings towards Endgame. These customer insights along with the recommendations given in this paper will be used by Endgame to increase their overall business revenues.
ContributorsPaplham, Tyler James (Author) / Eaton, John (Thesis director) / Mokwa, Michael (Committee member) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05