Waste pickers are the victims of harsh economic and social factors that have hurt many<br/>developing countries and billions of people around the world. Due to the rise of industrialization<br/>since the 19th century, waste and disposable resources have been discarded around the world to<br/>provide more resources, products, and services to wealthy countries. This has put developing<br/>countries in a precarious position where people have had very few economic opportunities<br/>besides taking on the role of waste pickers, who not only face physical health consequences due<br/>to the work they do but also face exclusion from society due to the negative views of waste<br/>pickers. Many people view waste pickers as scavengers and people who survive off of doing<br/>dirty work, which creates tensions between waste pickers and others in society. This even leads<br/>to many countries outlawing waste picking and has led to the brutal treatment of waste pickers<br/>throughout the world and has even led to thousands of waste pickers being killed by anti-waste<br/>picker groups and law enforcement organizations in many countries.<br/>Waste pickers are often at the bottom of supply chains as they take resources that have<br/>been used and discarded, and provide them to recyclers, waste management organizations, and<br/>others who are able to turn these resources into usable materials again. Waste pickers do not have<br/>many opportunities to rise above the situation they are in as waste picking has become the only<br/>option for many people who need to provide for themselves and their families. They are not<br/>compensated very well for the work they do, which also contributes to the situation where waste<br/>pickers are forced into a position of severe health risks, backlash from society and governments,<br/>not being able to seek better opportunities due to a lack of earning potential, and not being<br/>connected with end-users. Now is the time to create new business models that solve these large<br/>problems in our global society and create a sustainable way to ensure that waste pickers are<br/>treated properly around the world.

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.

Though about 75 percent of American waste is recyclable, only 30 percent of it is actually recycled and less than ten percent of plastics disposed of in the United States in 2015 were recycled. A statistic like this demonstrates the immense need to increase recycling rates in order to move towards cultivating a circular economy and benefiting the environment. With Arizona State University’s (ASU) extensive population of on-campus students and faculty, our team was determined to create a solution that would increase recycling rates. After conducting initial market research, our team incentives or education. We conducted market research through student surveys to determine the level of knowledge of our target audience and barriers to entry for local recycling and composting resources. Further, we gained insight into the medium of recycling and sustainability programs they would be interested in participating in. Overall, the results of our surveys demonstrated that a majority of students were interested in participating in these programs, if they were not already involved, and most students on-campus already had access to these resources. Despite having access to these sustainable practices, we identified a knowledge gap between students and their information on how to properly execute sustainable practices such as composting and recycling. In order to address this audience, our team created Circulearning, an educational program that aims to bridge the gap of knowledge and address immediate concerns regarding circular economy topics. By engaging audiences through our quick, accessible educational modules and teaching them about circular practices, we aim to inspire everyone to implement these practices into their own lives. Though our team began the initiative with a focus on implementing these practices solely to ASU campus, we decided to expand our target audience to implement educational programs at all levels after discovering the interest and need for this resource in our community. Our team is extremely excited that our Circulearning educational modules have been shared with a broad audience including students at Mesa Skyline High School, ASU students, and additional connections outside of ASU. With Circulearning, we will educate and inspire people of all ages to live more sustainably and better the environment in which we live.

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.

Colorimetric assays are an important tool in point-of-care testing that offers several advantages to traditional testing methods such as rapid response times and inexpensive costs. A factor that currently limits the portability and accessibility of these assays are methods that can objectively determine the results of these assays. Current solutions consist of creating a test reader that standardizes the conditions the strip is under before being measured in some way. However, this increases the cost and decreases the portability of these assays. The focus of this study is to create a machine learning algorithm that can objectively determine results of colorimetric assays under varying conditions. To ensure the flexibility of a model to several types of colorimetric assays, three models were trained on the same convolutional neural network with different datasets. The images these models are trained on consist of positive and negative images of ETG, fentanyl, and HPV Antibodies test strips taken under different lighting and background conditions. A fourth model is trained on an image set composed of all three strip types. The results from these models show it is able to predict positive and negative results to a high level of accuracy.

The contemporary world is motivated by data-driven decision-making. Small 501(c)3 nonprofit organizations are often limited in their reach due to their size, lack of funding, and a lack of data analysis expertise. In an effort to increase accessibility to data analysis for such organizations, a Founders Lab team designed a product to help them understand and utilize geographic information systems (GIS) software. This product – You Got GIS – strikes the balance between highly technical documentation and general overviews, benefiting 501(c)3 nonprofits in their pursuit of data-driven decision-making. Through the product’s use of case studies and methodologies, You Got GIS serves as a thought experiment platform to start answering questions regarding GIS. The product aims to continuously build partnerships in an effort to improve curriculum and user engagement.

Student academic performance has far-reaching implications, such as lifetime earnings potential, that are beyond the immediate impact it may have on any individual student (Bureau of Labor Statistics [BLS], 2019). Colleges and universities also have a shared interest in the retention of their students as a poor reputation can depress enrollment and tarnish their brand. Public institutions have an especially large incentive for student success as many state and federal funding opportunities consider student retention and performance when allocating taxpayer dollars (Li, 2018). To assist in the mutual desire for students to succeed, the Calm Connection start-up venture formed with the goal of seamlessly integrating biofeedback therapy with a student’s unique education needs. Forming the foundation of the resulting Calm Connection app is software patented by NASA which allows for the collection and manipulation of biofeedback monitoring data on mobile devices with distinguishing features such as geolocation. For students, one of the largest barriers to effective learning is issues of focus and information retention, whether due to problems at home, conditions such as ADHD, or the high prevalence of test anxiety among students (Committee on Psychosocial Aspects of Child and Family Health et al., 2012). The repeated use of biofeedback therapy trains students to overcome these focus issues and works in conjunction with our app’s study aid and scheduling ability (Henriques et al., 2011). Among those surveyed and participants in follow-up focus groups, the Calm Connection app and its use of biofeedback monitoring has generated much interest and documented traction.

Music streaming services have affected the music industry from both a financial and legal standpoint. Their current business model affects stakeholders such as artists, users, and investors. These services have been scrutinized recently for their imperfect royalty distribution model. Covid-19 has made these discussions even more relevant as touring income has come to a halt for musicians and the live entertainment industry. <br/>Under the current per-stream model, it is becoming exceedingly hard for artists to make a living off of streams. This forces artists to tour heavily as well as cut corners to create what is essentially “disposable art”. Rapidly releasing multiple projects a year has become the norm for many modern artists. This paper will examine the licensing framework, royalty payout issues, and propose a solution.

The ongoing Global Coronavirus Pandemic has been upheving social norms for over a year at this point. For countless people, our lives look very different at this point in time than they did before the pandemic began. Quarantine, Shelter in Place, Work from Home, and Online classes have led global populations to become less active leading to an increase in sedentary lifestyles. The final impact of this consequence is unknown, but emerging studies have led to concrete evidence of decreased physical and mental wellbeing, particularly in children. VirusFreeSports was the brainchild of three ASU Honors students who sought to remedy these devastating consequences by creating environments where children can participate in sports and exercise safely, free of the threat COVID-19 or other transmissible illnesses. The ultimate goal for the project team was to build traction for their idea, which culminated in a video pitch sent to potential investors. Although largely created as an exercise and we did not create a full certification course, merely a prototype through a website with sample questions to gauge interest, the project was a success as a large target market for this product was identified that showed great promise. Our team believes that early entrance to the market, as well as the lack of any other competitors would give the team a tremendous advantage in creating an impactful and influential service.