The research presented in this Honors Thesis provides development in machine learning models which predict future states of a system with unknown dynamics, based on observations of the system. Two case studies are presented for (1) a non-conservative pendulum and (2) a differential game dictating a two-car uncontrolled intersection scenario. In the paper we investigate how learning architectures can be manipulated for problem specific geometry. The result of this research provides that these problem specific models are valuable for accurate learning and predicting the dynamics of physics systems.<br/><br/>In order to properly model the physics of a real pendulum, modifications were made to a prior architecture which was sufficient in modeling an ideal pendulum. The necessary modifications to the previous network [13] were problem specific and not transferrable to all other non-conservative physics scenarios. The modified architecture successfully models real pendulum dynamics. This case study provides a basis for future research in augmenting the symplectic gradient of a Hamiltonian energy function to provide a generalized, non-conservative physics model.<br/><br/>A problem specific architecture was also utilized to create an accurate model for the two-car intersection case. The Costate Network proved to be an improvement from the previously used Value Network [17]. Note that this comparison is applied lightly due to slight implementation differences. The development of the Costate Network provides a basis for using characteristics to decompose functions and create a simplified learning problem.<br/><br/>This paper is successful in creating new opportunities to develop physics models, in which the sample cases should be used as a guide for modeling other real and pseudo physics. Although the focused models in this paper are not generalizable, it is important to note that these cases provide direction for future research.

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.

Enzyme-induced carbonate precipitation (EICP) is a biocementation technique that produces comparatively fewer carbon dioxide emissions than traditional cementation. However, the use of synthetic reagents for EICP is costly, and the process produces an ammonium byproduct which is a harmful pollutant. This study utilizes fresh urine as a source of urea and calcium-rich zeolites as an ammonium adsorbent and a source of calcium ions for the EICP cementation technique. Batch hydrolysis and adsorption experiments were conducted to determine the effects of zeolite type, zeolite form, and solution composition on ammonium adsorption and calcium release. Cementation experiments were then conducted to determine the effects of different hydrolysis and adsorption times on ammonium adsorption and calcium carbonate precipitation. The results showed that calcium-rich chabazite could be used as a source of calcium ions and as an effective adsorbent of ammonium for EICP. Additionally, synthetic, fresh urine and real, fresh urine had comparable ammonium adsorption and calcium release trends. Finally, inclusion of a pre-hydrolysis step reduced the ammonium adsorption and calcium release, but longer adsorption times lead to calcium carbonate precipitation outside of the sand column, which is an undesirable outcome for soil biocementation; even with this limitation, the calcium carbonate content of sand columns ranged from 0.48% to 0.92%, which signifies the potential of the proposed process for cementation, given a higher initial concentration of urea.

This thesis project will be investigating the interactions and organizational theory within the student housing market at Arizona State University. The focus of the project will be around the partnership that makes up many of the communities, the public company known as American Campus Communities, and the auxiliary of Arizona State University Housing. The paper will analyze the organization through the four frames outlined by Bolman and Deal’s Reframing Organizations. These four are the structural, human resource, political, and symbolic frames. The paper will confront two main issues found in the organization. The first is the frequent turnover of staff. The second will be the separation between the departments, leading to unstable communication. Solutions will be proposed that could take some pressure off the problems that are identified. Compensation for staff and adjustments to summer living may allow retention to improve. Adjusted training and top-level management communication and interaction may improve the stark separation between areas of the organization. Analyzing these issues and solutions through the organizational frames allows us to better understand the reasoning behind and possible effects of any decision. This project has been very insightful, and I learned a lot with my studies and am proud to be a part of this organization and its mission to serve the students.

In an age of crisis, division, and ideological representation, it is vital to understand the representative and leadership qualities that made past presidents successful, not in terms of policy, but in terms of character. This interpretation of the American presidency reflects the nation as a whole, not as a political or personal allegiance, but as a symbol of Americanism in the current age. Through the use of scholarly literature and historical accounts of highlighted American Presidents, (Washington, Lincoln, Roosevelt, FDR, and more), insight can be utilized to create a new model of presidential representation that addresses the faults of current methodologies. This thesis aims to identify the critical successful characteristics and strategies enacted by American presidents to relate with the American people, especially in times of hardship, when understanding and connection are needed the most. These attributes can then formulate a blueprint for positive personal relationships and identify qualities for future Presidential leadership. Once determined, these traits can be formatted into a new model of representation to analyze the representative power and ability of the American presidency in order to establish a baseline for successful representation.

This thesis project has been conducted in accordance with The Founder’s Lab initiative which is sponsored by the W. P. Carey School of Business. This program groups three students together and tasks them with creating a business idea, conducting the necessary research to bring the concept to life, and exploring different aspects of business, with the end goal of gaining traction. The product we were given to work through this process with was Hot Head, an engineering capstone project concept. The Hot Head product is a sustainable and innovative solution to the water waste issue we find is very prominent in the United States. In order to bring the Hot Head idea to life, we were tasked with doing research on topics ranging from the Hot Head life cycle to finding plausible personas who may have an interest in the Hot Head product. This paper outlines the journey to gaining traction via a marketing campaign and exposure of our brand on several platforms, with a specific interest in website traffic. Our research scope comes from mainly primary sources like gathering opinions of potential buyers by sending out surveys and hosting focus groups. The paper concludes with some possible future steps that could be taken if this project were to be continued.

Is there a mismatch between urban farmers’ perceptions of their farm’s environmental sustainability and its actual environmental impact? Focusing on the use of water and nutrients on each farm as described by the farmers through interviews, it is evident that there is some level of disconnect between ideals and practices. This project may aid in bridging the gap between the two in regard to the farmers’ sustainability goals. This project will move forward by continuing interviews with farmers as well as collecting soil and water from the farms in order to more accurately quantify the sustainability of the farms’ practices. This project demonstrates that there is some degree of misalignment between perception and reality. Two farms claimed they were sustainable when their practices did not reflect that, while 2 farms said they were not sure if they were sustainable when their practices indicated otherwise. Samples from two farms showed high concentrations of nutrients and salts, supporting the idea that there may be a mismatch between perceived and actual sustainability.

As part of the Founders’ lab program, this thesis explores a social venture idea whose concept is to connect the philanthropic community with individuals and organizations in need of funding a project relating to (Sustainable Development Goals) SDG indicators through a peer to peer donation platform. Through this platform, the philanthropic community will have the possibility to easily access a wide range of projects to support as well as underserved individuals and communities seeking for help, track their impact, donate in a complete transparent donation process, and automate donations through bank card rounds-up. This social venture idea has been named PhilanthroGo.

This study investigated the difference in biofilm growth between pristine polypropylene microplastics and aged polypropylene microplastics. The microplastics were added to Tempe Town Lake water for 4 weeks. Each week the microplastic biofilms were quantified. Comparing the total biofilm counts, the results showed that the aged microplastic biofilms were larger than the pristine each week. By week 3 the aged microplastic counts had almost doubled in size increasing from 324 to 626 Colony Forming Units per gram in just one week. There was a significant difference in the diversity found from week 1 to week 4. About 40% of the diversity for the pristine microplastic biofilm was seen as light-yellow dots and about 60% of these dots were seen on the aged microplastic biofilms in both weeks. As the microplastics were submerged in the lake water, new phenotypes emerged varying from week 1 to week 4 and from pristine to aged microplastic biofilms. Generally, it was found that as the microplastics stay in the environment there is more biofilm on the particles. The aged microplastics have a larger amount of biofouling, and the pristine microplastic biofilms were found to have more diversity of phenotypes.