Over the past twenty years, the United States has experienced what Dr. Thomas Philippon calls "The Great Reversal," or a slow drift away from the free market competition which defined the American economy for the last century, towards an increasingly oligopolistic consolidation of market power. What does this mean? For the average American, prices have increased, wages remain stagnant, quality has declined, and the variety of goods has diminished. The reason? The growing political power of incumbent firms, who use their established economic power to influence the political process in their favor, towards high barriers to entry and decreased antitrust scrutiny, through lobbying and the financing of campaigns. Or have they? "The Great Reversal," and hypotheses like it, are far from a consensus... This Thesis is a meta study of the literature surrounding domestic competition in the United States and the impact that the lobbying activity of industry leaders has on said competition. Analyzing over 20 papers covering economics, political science, and political economy, this Thesis argues that domestic competition in the United States has indeed declined over the past two decades and that the growing political power of firms, rather than "unique" technological or structural changes in the economy, has caused this drift away from free markets. Using this analysis, this Thesis further suggests a few solutions to "The Great Reversal" and restoring competition in the American economy.

Standardization is sorely lacking in the field of musical machine learning. This thesis project endeavors to contribute to this standardization by training three machine learning models on the same dataset and comparing them using the same metrics. The music-specific metrics utilized provide more relevant information for diagnosing the shortcomings of each model.

During a joint ASU-Prescott College visit to the Maasai Mara in Kenya in June-July 2018, it became obvious that many Maasai women produce beadwork sold locally to help support their families. The difficulties they face include inconsistent sales due to lack of customers, lulls in tourism, and unfair competition. During this visit, the idea of selling the crafts online via Etsy was suggested. It received overwhelming support from the community through MERC, the The Maasai Education, Research and Conservation Institute.

A growing body of research suggests that there is more to course assessment than homework scores and test performance. This paper contributes to the empirical literature in economics and education by evaluating the impact of racial and gender congruency on the performance of ASU students. Expanding on previous research which only covered elementary and high school, we are able to draw conclusions and policy recommendations to solve the racial achievement gap in the USA.

The current Solid-State Electrolyte (SSE) used in Li-ion batteries are limited by their current production methods (i.e., die-pressing; tape casting), planar geometries and random porosities. This constrains their use for mass production in manufacturing plants. 3D-printing of SSEs, however, is a new, highly-researched method that shows promise in expanding beyond the laboratory to more large-scale industrial production as rapid prototyping takes place. Indeed, laboratory studies to date suggest that SSE technology is safer than current production methods and provides a safe high energy solid-state battery. For SSE technology to become a reality though, it must be scalable and financially feasible. Therefore, this thesis aids to bridge the gap between laboratory studies and commercialization by examining the financial feasibility of adopting this technology for a hypothetical battery manufacturing plant. In doing this, I develop a model of the incremental net cash flows, and subsequently the Net Present Value (NPV), from such an enterprise. If the present value of future cash flows from the enterprise are anticipated to be greater than the investment costs, the NPV is positive and the investment in this new technology would be considered instantaneously value enhancing and thus financially feasible. However, future cash flows are highly uncertain, which brings into question financial feasibility in a risky environment. To address the riskiness of future cash flows, I model three risk factors: the cost of raw materials, the potential growth in battery sales, as well as the potential mark-up (profit margin) of the SSE enterprise. Using Monte Carlo simulation (MCS) I model the incremental cash flows considering these risk factors and derive probabilistic assessments of NPV. My analysis suggests that despite the uncertainty caused by the volatility of raw metal prices, assumptions on price mark-up, and uncertain market demand for Li-ion batteries, there is a high probability of an investment in SSE batteries being financially feasible. Future research should consider the value of real options (optionality embedded in tangible investments) as traditional NPV analysis may underestimate the potential value of an investment in the presence of uncertain cash flows, especially if management has the ability to respond to the uncertainty.

Spatial audio can be especially useful for directing human attention. However, delivering spatial audio through speakers, rather than headphones that deliver audio directly to the ears, produces the issue of crosstalk, where sounds from each of the two speakers reach the opposite ear, inhibiting the spatialized effect. A research team at Meteor Studio has developed an algorithm called Xblock that solves this issue using a crosstalk cancellation technique. This thesis project expands upon the existing Xblock IoT system by providing a way to test the accuracy of the directionality of sounds generated with spatial audio. More specifically, the objective is to determine whether the usage of Xblock with smart speakers can provide generalized audio localization, which refers to the ability to detect a general direction of where a sound might be coming from. This project also expands upon the existing Xblock technique to integrate voice commands, where users can verbalize the name of a lost item using the phrase, “Find [item]”, and the IoT system will use spatial audio to guide them to it.

Spatial audio can be especially useful for directing human attention. However, delivering spatial audio through speakers, rather than headphones that deliver audio directly to the ears, produces the issue of crosstalk, where sounds from each of the two speakers reach the opposite ear, inhibiting the spatialized effect. A research team at Meteor Studio has developed an algorithm called Xblock that solves this issue using a crosstalk cancellation technique. This thesis project expands upon the existing Xblock IoT system by providing a way to test the accuracy of the directionality of sounds generated with spatial audio. More specifically, the objective is to determine whether the usage of Xblock with smart speakers can provide generalized audio localization, which refers to the ability to detect a general direction of where a sound might be coming from. This project also expands upon the existing Xblock technique to integrate voice commands, where users can verbalize the name of a lost item using the phrase, “Find [item]”, and the IoT system will use spatial audio to guide them to it.

Spatial audio can be especially useful for directing human attention. However, delivering spatial audio through speakers, rather than headphones that deliver audio directly to the ears, produces the issue of crosstalk, where sounds from each of the two speakers reach the opposite ear, inhibiting the spatialized effect. A research team at Meteor Studio has developed an algorithm called Xblock that solves this issue using a crosstalk cancellation technique. This thesis project expands upon the existing Xblock IoT system by providing a way to test the accuracy of the directionality of sounds generated with spatial audio. More specifically, the objective is to determine whether the usage of Xblock with smart speakers can provide generalized audio localization, which refers to the ability to detect a general direction of where a sound might be coming from. This project also expands upon the existing Xblock technique to integrate voice commands, where users can verbalize the name of a lost item using the phrase, “Find [item]”, and the IoT system will use spatial audio to guide them to it.

The process of learning a new skill can be time consuming and difficult for both the teacher and the student, especially when it comes to computer modeling. With so many terms and functionalities to familiarize oneself with, this task can be overwhelming to even the most knowledgeable student. The purpose of this paper is to describe the methodology used in the creation of a new set of curricula for those attempting to learn how to use the Dynamic Traffic Simulation Package with Multi-Resolution Modeling. The current DLSim curriculum currently relates information via high-concept terms and complicated graphics. The information in this paper aims to provide a streamlined set of curricula for new users of DLSim, including lesson plans and improved infographics.

The process of learning a new skill can be time consuming and difficult for both the teacher and the student, especially when it comes to computer modeling. With so many terms and functionalities to familiarize oneself with, this task can be overwhelming to even the most knowledgeable student. The purpose of this paper is to describe the methodology used in the creation of a new set of curricula for those attempting to learn how to use the Dynamic Traffic Simulation Package with Multi-Resolution Modeling. The current DLSim curriculum currently relates information via high-concept terms and complicated graphics. The information in this paper aims to provide a streamlined set of curricula for new users of DLSim, including lesson plans and improved infographics.