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Description
This thesis explores how fundamental variables of business cycles influence commercial real estate cycles and investor behavior within them. Specifically, I address studies correlating key business cycle variables to commercial real estate cycles. Then, I address the Phoenix industrial real estate market and analyze whether or not the predicted or theorized consequences of the changes in the key business cycle variables impacted the Phoenix industrial real estate market. My findings on the topic provide valuable insight into the predictability of industrial real estate behavior throughout cycles, given the changes in fundamental economic variables of business cycles. Specifically, it demonstrates how the Phoenix industrial real estate market has historically behaved in correlation to business cycles and their variables. My findings also highlight the importance of observing the Phoenix market’s continued response to changes in the macro-economy.
ContributorsAronowitz, Ethan (Author) / Stapp, Mark (Thesis director) / Koblenz, Blair (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor)
Created2024-05
Description
The primary goal of our nonprofit organization, Plant-ED, is to deepen the average individual’s knowledge regarding sustainability and to inspire our users to engage in a community of like-minded individuals who share a passion for sustainability. To accomplish this vision, we have created a digital platform where users can easily find information on upcoming events, activities, and alternative products that truly embody a mindset of sustainability. Our team will be the main and constant source of content for our website, however our users are also able to interact with the website through blog posts and subscriptions. Additionally, our platform has a section dedicated to explaining the impact of recycling and shows the devastating effects if humans do not take accountability for their choices and develop more sustainable habits. The ultimate goal for our website is for it to be a place where we can promote our partners’ products which are either alternatives to unsustainable products or companies who donate some of their proceeds to help create a greener world. The profit from the commission we receive from our partners and subscription services will be reinvested into expanding our digital platform and partnerships.
ContributorsMahoney, Emma (Author) / Weiderhoft, Isabella (Co-author) / Meyers, Zoe (Co-author) / Smith, Connor (Co-author) / Byrne, Jared (Thesis director) / Balven, Rachel (Committee member) / Barrett, The Honors College (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Department of Finance (Contributor)
Created2024-05
Description
Arena Report is created to be a teaching and learning application. The app features projection-based Augmented Reality (AR) overlays of sports statistics at meaningful spatial positions to educate coaches and players about how they can use data to make better decisions. It is also meant to enable users to better communicate results and make better decisions. By interacting with immersive, 3-dimensional data visualizations, Arena Report allows users to develop their ability to make sound decisions in sports.
ContributorsHobbs, Caleb (Author) / Johnson-Glenberg, Mina (Thesis director) / Coza, Aurel (Committee member) / Barrett, The Honors College (Contributor) / Department of Marketing (Contributor) / Department of Information Systems (Contributor)
Created2024-05
Description
This thesis investigates the quality and usefulness of "DeepDEMs" from Moon and Mars images, which are Digital Elevation Models (DEMs) created using deep learning from single optical images. High-resolution DEMs of Moon and Mars are increasingly critical for gaining insights into the slope and the elevation of the terrain in the region which helps in identifying the landing sites of possible manned missions and rovers. However, many locations of interest to scientists who use remote sensing to study the Earth or other planetary bodies have only visible image data coverage, and not repeated stereo image coverage or other data collected specifically for DEM generation. Thus, Earth and planetary scientists, geographers, and other academics want DEMs in many locations where no data resources (repeat coverage or intensive remote sensing campaigns) have been assigned for geomorphic or topographic study. One specific use for deep learning-generated terrain models would be to assess probable sites in the lunar south polar area for NASA's future Artemis III mission which aims to return people to the lunar surface. While conventional techniques (for example, needing two stereo pictures from satellites for photogrammetry) work well, this high-resolution data only covers a small portion of the planets. Furthermore, older approaches need lengthy processing durations as well as human calibration and tweaking to achieve high-quality DEMs. To address the coverage and processing time concerns, we evaluated deep learning algorithms for creating DEMs of the Moon and Mars' surfaces. We explore how the findings of this study may be used to create elevation models for planetary mapping in the future using automated methods.
ContributorsJain, Rini (Author) / Rastogi, Anant (Co-author) / Kerner, Hannah (Thesis director) / Adler, Jacob (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / Department of Information Systems (Contributor)
Created2024-05
Description
The paper investigates the efficacy of utilizing artificial intelligence (AI) for code generation, specifically looking into Java and it’s GUI Swing library, and evaluates the quality of the generated code. It presents a comparative analysis of various AI-generated solutions, aiming to determine which approach yields the most optimal results. The study explores different AI techniques, such as machine learning models, employed in code generation tasks. Through rigorous experimentation and evaluation criteria, the paper assesses factors like code efficiency, readability, and functionality to identify the most effective AI-based code generation methods. The findings contribute insights into leveraging AI for code development and offer recommendations for improving code quality in software engineering practices.
Utilizing Java Swing I created a Hangman game and then asked ChatGPT, Gemini, Copilot, and Blackbox to create the same game.
ContributorsConsalvo, Benjamin (Author) / Sopha, Matt (Thesis director) / Mazzola, Daniel (Committee member) / Barrett, The Honors College (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Department of Information Systems (Contributor)
Created2024-05
Description
YumAsia is committed to enriching the Arizona culinary landscape by introducing the distinctive flavors and cultural heritage of Asian cuisines, particularly through the promotion of the Yunnan Rose Pastry. This initiative responds to the growing interest in authentic ethnic foods among college students and the broader community in Arizona. YumAsia’s mission goes beyond mere food provision to offer an immersive cultural experience that highlights the stories and traditions behind Asian pastries. With a strategic positioning as a cultural ambassador, YumAsia leverages a content-driven marketing strategy that combines the power of e-commerce, website building, and community engagement through direct interactions like tabling events. The value proposition centers on delivering authenticity, quality, and educational content, all wrapped in a customer-centric service that offers both delivery and pickup options. This approach aims to not only introduce new flavors to the market but also to foster a deeper understanding and appreciation of Asian culinary diversity.
ContributorsFeng, Qianhui (Author) / Byrne, Jared (Thesis director) / Lee, Peggy (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor)
Created2024-05
Description
Braille Retail is a student-led effort to promote awareness and inclusivity for visually impaired and blind individuals through legible braille designs on fabric. Our mission is to bring awareness to the visually impaired and blind community and increase braille literacy. We plan to reach our mission by placing legible braille and its translation on our sweatshirts. Furthermore, we want to support the visually impaired and blind community by donating 5% of our profits to local blind charities.
ContributorsShereck, Kennedy (Author) / Pearson, Morgan (Co-author) / O'Shea, Hannah (Co-author) / Soto, Tatum (Co-author) / Byrne, Jared (Thesis director) / Giles, Bret (Committee member) / Thomasson, Anna (Committee member) / Barrett, The Honors College (Contributor) / Department of Marketing (Contributor) / Department of Information Systems (Contributor)
Created2024-05
Description
In this three-episode podcast series, we delve into the layers of censorship within the American public school system. Episode one unearths the historical roots of censorship in America, tracing back to pivotal moments and decisions that shaped the landscape of what can and cannot be taught or discussed in classrooms. Moving forward, episode two navigates the complex web of policies, guidelines, and societal pressures that have dictated the boundaries of permissible content in school curricula as of recently. Finally, episode three explores strategies and initiatives aimed at fostering a more inclusive and open learning environment for the future. We examine the role of technology and the role students can take in empowering educators and learners to engage critically with information while respecting diverse viewpoints. Through in-depth analysis and compelling narratives, this podcast series sheds light on the ongoing discourse surrounding censorship in America's public schools, urging listeners to rethink conventional paradigms and advocate for a more transparent and equitable educational experience for all.
ContributorsJeter, Zoe (Author) / Powell, Danielle (Co-author) / Schmidt, Peter (Thesis director) / Voorhees, Matthew (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Department of Management and Entrepreneurship (Contributor)
Created2024-05
Description
This world promises just one thing: continuous change. As humanity has moved through time much has changed in the worlds of science, mathematics, and physics. These shifts in humanity's comprehension often arrive unexpectedly, driven by education, innovation, and experimentation. Such transformative waves resemble a series of technology shocks that are known to cause significant disruptions within an industry and the economy broadly as firms permanently change the ways they produce and distribute goods and services in response to new technologies or information. The recent flurry of innovation and interest in Artificial Intelligence leads us to believe that many industries may be experiencing such a wave of change today. The healthcare industry currently employs the most workers of any other sector in the United States (outside of the government) and is made up of an unprecedented 77% of female workers making the outcomes of changes in its labor market demands particularly important. In this paper we discuss the current state of Artificial Intelligence adoption within the clinical side of healthcare, what sub sectors and occupations are most exposed, and to what extent the FDA approved AI-enabled clinical healthcare products replace or complement those tasks of existing occupations. We also interviewed a few healthcare professionals with different levels of seniority and exposure to AI-enabled products to develop a holistic understanding of current AI adoption, employee preparation, and potential labor market implications over the short and long term. We find that AI implementation within clinical healthcare settings is young in its life cycle yet fast growing. Current use cases are mostly in the earlier stages of the patient’s care journey assisting workers in various capacities in the processes of patient testing, diagnosis, care planning, and post-treatment monitoring. The tasks associated with patient interaction and care administration do not appear to be threatened by AI automation at this point in time. Additionally, approved Artificial Intelligence products for clinical use are disproportionately concentrated in the subsectors of radiology, neurology, and cardiology. Finally, our interviews revealed a concerning lack of consideration and preparation, among healthcare workers, for the potential automation of their fundamental tasks. Going forward, we believe it wise for healthcare workers to monitor the evolution of clinical AI use cases as well as the FDA approval of AI-enabled products and prepare for potential automation by continuing to learn new skills, take on additional responsibilities, and generally inject themselves into as many stages of the patient’s healthcare journey as possible to differentiate among other workers and avoid the coming wave of mass clinical automation.
ContributorsDolasinski, Nicholas (Author) / McElenney, Nicholas (Co-author) / Mehta, Ari (Thesis director) / Asheim, Brody (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Economics (Contributor)
Created2024-05
Description
This project examines entry-level processors Company X. Analyzing their current position and creating recommendations for their future positioning in regard to entry-level processors. Utilizing financial models, our group worked to determine the most effective way to optimize NPV and gross margin for this segment. With extensive step models and sensitivity analysis, we analyzed potential paths that Company X could take. Continuing to be mindful of the limitations that certain projected paths would entail. Through our analysis, we were able to form a comprehensive suggestion that had a positive 8-year NPV and improved gross margin percentage.
ContributorsHuseinovic, Ayla (Author) / Jones, Ciara (Co-author) / Mathias, Chase (Co-author) / Kuo, Ian (Co-author) / Simonson, Mark (Thesis director) / Hertz, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Accountancy (Contributor) / Department of Finance (Contributor) / Dean, W.P. Carey School of Business (Contributor)
Created2024-05