In this creative thesis project I use digital “scrolleytelling” (an interactive scroll-based storytelling) to investigate diversity & inclusion at big tech companies. I wanted to know why diversity numbers were flatlining at Facebook, Apple, Amazon, Microsoft and Google, and took a data journalism approach to explore the relationship between what corporations were saying versus what they were doing. Finally, I critiqued diversity and inclusion by giving examples of how the current way we are addressing D&I is not fixing the problem.

This thesis proposes hardware and software security enhancements to the robotic explorer of a capstone team, in collaboration with the NASA Psyche Mission Student Collaborations program. The NASA Psyche Mission, launching in 2022 and reaching the metallic asteroid of the same name in 2026, will explore from orbit what is hypothesized to be remnant core material of an early planet, potentially providing key insights to planet formation. Following this initial mission, it is possible there would be scientists and engineers interested in proposing a mission to land an explorer on the surface of Psyche to further document various properties of the asteroid. As a proposal for a second mission, an interdisciplinary engineering and science capstone team at Arizona State University designed and constructed a robotic explorer for the hypothesized surfaces of Psyche, capable of semi-autonomously navigating simulated surfaces to collect scientific data from onboard sensors. A critical component of this explorer is the command and data handling subsystem, and as such, the security of this system, though outside the scope of the capstone project, remains a crucial consideration. This thesis proposes the pairing of Trusted Platform Module (TPM) technology for increased hardware security and the implementation of SELinux (Security Enhanced Linux) for increased software security for Earth-based testing as well as space-ready missions.

Human beings have long sought to conquer the unconquerable and to push the boundaries of human endurance. There are few such endeavors more challenging than venturing into the coldest and harshest environments on the planet. The challenges these adventurers face are nearly countless, but one that is often underestimated is the massive risk of dehydration in high mountains and the lack of sufficient technology to meet this important need. Astronauts and mountaineers of NASA's Johnson Space Center have created a technology that solves this problem: a freeze-resistant hydration system that helps stop water from freezing at sub-zero temperatures by using cutting-edge technology and materials science to insulate and heat enough water to prevent dehydration over the course of the day, so that adventurers no longer need to worry about their equipment stopping them. This patented technology is the basis of the founding of Aeropak, an advanced outdoor hydration brand developed by three ASU students (Kendall Robinson, Derek Stein, and Thomas Goers) in collaboration with W.P. Carey’s Founder’s Lab. The primary goal was to develop traction among winter sport enthusiasts to create a robust customer base and evaluate the potential for partnership with hydration solution companies as well as direct sales through online and brick-and-mortar retail avenues. To this end, the Aeropak team performed market research to determine the usefulness and need for the product through a survey sent out to a number of outdoor sporting clubs on Arizona State University’s campus. After determining an interest in a potential product, the team developed a marketing strategy and business model which was executed through Instagram as well as a standalone website, with the goal of garnering interest and traction for a future product. Future goals of the project will be to bring a product to market and expand Aeropak’s reach into a variety of winter sport subcommunities, as well as evaluate the potential for further expansion into large-scale retailers and collaboration with established companies.

Generating an astounding $110.7 billion annually in domestic revenue alone [1], the world of accounting is one deceptively lacking automation of its most business-critical processes. While accounting tools do exist for the common person, especially when it is time to pay their taxes, such innovations scarcely exist for many larger industrial tasks. Exceedingly common business events, such as Business Combinations, are surprisingly manual tasks despite their $1.1 trillion valuation in 2020 [2]. This work presents the twin accounting solutions TurboGAAP and TurboIFRS: an unprecedented leap into these murky waters in an attempt to automate and streamline these gigantic accounting tasks once entrusted only to teams of experienced accountants.
A first-to-market approach to a trillion-dollar problem, TurboGAAP and TurboIFRS are the answers for years of demands from the accounting sector that established corporations have never solved.

This thesis explores the potential for software to act as an educational experience for engineers who are learning system dynamics and controls. The specific focus is a spring-mass-damper system. First, a brief introduction of the spring-mass-damper system is given, followed by a review of the background and prior work concerning this topic. Then, the methodology and main approaches of the system are explained, as well as a more technical overview of the program. Lastly, a conclusion and discussion of potential future work is covered. The project was found to be useful by several engineers who tested it. While there is still plenty of functionality to add, it is a promising first attempt at teaching engineers through software development.

In the past decade, the use of mobile applications, specifically mobile applications focused on improving the health and fitness of users, has increased exponentially. As more consumers look towards mobile health applications to improve their health through dieting, exercise, and weight management, it is important to analyze how the concept of gamification can encourage sustained interaction and approval of these health-focused applications. This thesis aims to understand the prevalence of gamification amongst a large sample of health and fitness applications, identify and code the gamification features used in these apps, and finally, understand how different gamification features relate to the popularity and willingness to advocate using eWOM on behalf of a mobile app.

"Generating an astounding $110.7 billion annually in domestic revenue alone [1], the world of accounting is one deceptively lacking automation of its most business-critical processes. While accounting tools do exist for the common person, especially when it is time to pay their taxes, such innovations scarcely exist for many larger industrial tasks. Exceedingly common business events, such as Business Combinations, are surprisingly manual tasks despite their $1.1 trillion valuation in 2020 [2]. This work presents the twin accounting solutions TurboGAAP and TurboIFRS: an unprecedented leap into these murky waters in an attempt to automate and streamline these gigantic accounting tasks once entrusted only to teams of experienced accountants.
A first-to-market approach to a trillion-dollar problem, TurboGAAP and TurboIFRS are the answers for years of demands from the accounting sector that established corporations have never solved."

Automated vehicles are becoming more prevalent in the modern world. Using platoons of automated vehicles can have numerous benefits including increasing the safety of drivers as well as streamlining roadway operations. How individual automated vehicles within a platoon react to each other is essential to creating an efficient method of travel. This paper looks at two individual vehicles forming a platoon and tracks the time headway between the two. Several speed profiles are explored for the following vehicle including a triangular and trapezoidal speed profile. It is discovered that a safety violation occurs during platoon formation where the desired time headway between the vehicles is violated. The aim of this research is to explore if this violation can be eliminated or reduced through utilization of different speed profiles.

This research analyzes lesbian, gay, bisexual, transgender, and queer/ questioning (LGBTQ) students’ experiences with sex education in Arizona. This research is a grey literature review of Arizona’s previous state policies, current state sex education curricula law, and legislative proposals within the past few years. Analysis focuses on changes after the repeal of the “no promo homo” law in 2019. Through defining the differences between abstinence only and comprehensive sex education (CSE), this will provide a framework to better understand approaches to sex education. As of now, Arizona stresses abstinence-based education. Delving into LGBTQ students’ general experiences in schools provides a foundation to better understand why these students especially benefit from CSE. Since LGBTQ students are disproportionately affected by bullying and are at increased sexual health risks, it is important to address misperceptions surrounding the LGBTQ community. The purpose of this research is to push for more LGBTQ inclusive sex education curricula in Arizona.

High-entropy alloys possessing mechanical, chemical, and electrical properties that far exceed those of conventional alloys have the potential to make a significant impact on many areas of engineering. Identifying element combinations and configurations to form these alloys, however, is a difficult, time-consuming, computationally intensive task. Machine learning has revolutionized many different fields due to its ability to generalize well to different problems and produce computationally efficient, accurate predictions regarding the system of interest. In this thesis, we demonstrate the effectiveness of machine learning models applied to toy cases representative of simplified physics that are relevant to high-entropy alloy simulation. We show these models are effective at learning nonlinear dynamics for single and multi-particle cases and that more work is needed to accurately represent complex cases in which the system dynamics are chaotic. This thesis serves as a demonstration of the potential benefits of machine learning applied to high-entropy alloy simulations to generate fast, accurate predictions of nonlinear dynamics.