Accurate pose initialization and pose estimation are crucial requirements in on-orbit space assembly and various other autonomous on-orbit tasks. However, pose initialization and pose estimation are much more difficult to do accurately and consistently in space. This is primarily due to not only the variable lighting conditions present in space, but also the power requirements mandated by space-flyable hardware. This thesis investigates leveraging a deep learning approach for monocular one-shot pose initialization and pose estimation. A convolutional neural network was used to estimate the 6D pose of an assembly truss object. This network was trained by utilizing synthetic imagery generated from a simulation testbed. Furthermore, techniques to quantify model uncertainty of the deep learning model were investigated and applied in the task of in-space pose estimation and pose initialization. The feasibility of this approach on low-power computational platforms was also tested. The results demonstrate that accurate pose initialization and pose estimation can be conducted using a convolutional neural network. In addition, the results show that the model uncertainty can be obtained from the network. Lastly, the use of deep learning for pose initialization and pose estimation in addition with uncertainty quantification was demonstrated to be feasible on low-power compute platforms.

As one of the root causes of chronic hunger, it is well-established that food insecurity adversely affects health and economic outcomes of those afflicted (Carmichael et al. 2007; Seligman et al. 2009; Huang, Matta Oshima, and Kim, 2010; Pan et al. 2012; Martinez et al. 2018). More than eleven percent of Americans, uncertain about where their next meal will come from, experienced some degree of food insecurity in 2018 (Coleman-Jensen, 2019). Programs like SNAP and WIC have not only proven to be effective in providing food for households, but they can serve as an example for other countries that struggle to help citizens meet their dietary needs (Gundersen, 2019). non-government entities like food banks and food pantries have played an increasingly important role in addressing food insecurity. While there is a perception that food banks and pantries are only emergency resources, evidence suggests that many individuals regularly rely on private hunger relief organizations for food (Paynter et al., 2011; Kicinski, 2012). Food banks play a crucially important role in distributing food and are uniquely positioned to alleviate hunger. However, these private organizations have been shown, compared to public food assistance programs, to be less effective at specifically addressing the issue of food insecurity (Bazerghi et al., 2016; Loopstra & Tarasuk, 2012; Ratcliffe & McKernan, 2010; Metallinos-Katsaras et al., 2010). Existing research has largely focused on the characteristics of food pantry clients generally, without exploring the socio-economic and experiential variation within this group (Towers, 2009; Kicinski, 2012; Gundersen el al., 2017). This study fills a gap in the literature by examining the characteristics of food pantry users, and how they compare to those not using food pantries but still face food insecurity, using nationally representative survey data. Additionally, I explore whether food pantries and public food assistance programs might be “bundled” together. I focus on gradients of economic vulnerability by examining households who participate in public food assistance programs, are SNAP-eligible but not participating, as well as households who bundle both private and public food assistance to meet their food needs. With this thesis, I hope to contribute this research by providing behavioral insights into understanding the role that food banks play in mitigating challenges associated with food insecurity among US households.

Apple’s HomeKit framework centralizes control of smart home devices and allows users to create home automations based on predefined rules. For example, a user can add a rule to turn off all the lights in their house whenever they leave. Currently, these rules must be added through a graphical user interface provided by Apple or a third-party app on iOS. This thesis describes how a text-based language provides users with a more expressive means of creating complex home automations and successfully implements such a language. Rules created using this text-based format are parsed and interpreted into rules that can be added directly into HomeKit. This thesis also explores how security features should be implemented with this text-based approach. Since automations are run by the system without user interaction, it is important to consider how the system itself can provide functionality to address the unintended consequences that may result from running an automation. This is especially important for the text-based approach since its increase in expressiveness makes it easier for a user to make a mistake in programming that leads to a security concern. The proposed method for preventing unintended side effects is using a simulation to run every automation prior to actually running the automation on real-world devices. This approach allows users to code some conditions that must be satisfied in order for the automation to run on devices in the home. This thesis describes the creation of such a program that successfully simulates every device in the home. There were limitations, however, with Apple's HomeKit framework, which made it impractical to match the state of simulated devices to real devices in the home. Without being able to match the current state of the home to the current state of the simulation, this method cannot satisfy the goal of ensuring that certain adverse effects will not occur as a result of automations. Other smart home control platforms that provide more extensibility could be used to create this simulation-based security approach. Perhaps as Apple continues to open up their HomeKit platform to developers, this approach may be feasible within Apple's ecosystem at some point in the future.

Abstract: Handling the multiple functions of monetary policy that protect the U.S. economy not only on a short term, but also long-term scale is a complicated responsibility assigned to Federal Reserve, in which their actions present a profound impact on consumer confidence towards financial markets and global economies. Specifically, one of the most important goals of the Federal Reserve is to mitigate the risk of the United States to enter a recession, while maintaining a balanced approach when making those policy decisions. In this thesis, we focus on the monetary policy of the Federal Reserve, particularly, their role in controlling interest rates to prevent recessionary sentiment in the current state of the economy. Since 2008, markets have been stronger and previous policies like Dodd-Frank have ensured that market collapses during the Great Recession do not repeat itself. Yet, fluctuations in the yield curve, polarizing investment views, and unsettled consumer confidence has pointed to another recession in the near future. In this case, we will look at the way the Fed has implemented short term policies to lower this risk in order to fight volatile markets, however, fluctuating interest rates has its consequences. The goal of this thesis is to analyze the various ways the Fed has managed interest rates in the past and present, and further, to offer a framework to serve as the most effective policy to combat volatility and recessionary sentiment in the U.S. economy.

This paper, titled “Factors of Economic Development and Implications for the Future” focuses on identifying historical factors that have impacted economic development and analyzing what changes may be important for the future. It uses studies done across the world in energy economics, economic development, economic policy, and more to identify important considerations for evaluating historical growth, as well as concerns for the future, particularly given the threat of climate change. Historically important papers, as well as newer insights both feature heavily. This literary review resulted in the finding that education, energy, trade, policy, institutions, endowments, and culture are all important factors for economic development. Endowments and institutions that arise from them are found to be the most important factor in explaining historical development. The paper also analyzes policy that the existing literature suggests could be beneficial for growth. Next, an analysis of factors that the literature identified as important for growth is carried out to assess which countries may have the highest potentials for future growth. The countries are ranked based upon a composite scoring system created from those factors. Countries in Central Asia feature heavily in the top ten entries, while many African countries narrowly miss out on the top ten but still rank relatively high. Together, the findings of both sections are used to discuss how economies have historically developed as well as possible policies to encourage future sustainable development. Both the literature and statistical findings suggest that for future growth promotion of strong institutions that promote property rights and economic growth will be important. They also suggest that coordinated energy policy to increase green technologies and decouple growth from emissions will be essential.

Juvenile restorative justice has become an increasingly common alternative to punitive justice in recent decades. This project evaluates best practices and strategies that have been effective in reducing recidivism while upholding the key tenets of restoration. The goal of this project is to compile a reference for best practices and recommendations for the implementation of a juvenile restorative justice program at the Tempe Municipal Court. Through a comparison of two court-based restorative programs in the United States and a compilation of relevant research, a recommendation of Circle Conferencing is appropriate for the needs of the Tempe Municipal Court.

Humans are intrigued, drawn to, inspired by beautiful things. Various philosophers and
social commentators have contributed to this essential inquiry: what is Beauty? And
furthermore, are there objective patterns within what different people consider beautiful? I will
explore this through both the lenses of physical beauty and character beauty. In faces, there is the study of physical attractiveness - is it evolutionary, personal preference, or something more universal?

By using the four concepts of judgement of beauty laid out by Kant, supplemented with psychological research on humans' attractiveness ratings of faces, we will be able to get closer to the idea of a truly beautiful face. This face, striking in nature, is not simply attractive, but more. It is a face that is, using Kant's framework, disinterested, universal, purposive without purpose, and necessary.

This research evaluates the capabilities of typical radiological measures and dual-energy systems to differentiate common kidney stones materials: uric acid, oxalates, phosphates, struvite, and cystine. Two different X-ray spectra (80 kV and 120 kV) were applied and the dual-energy ratio of individual kidney stones was used to figure out the discriminability of different materials. A CT cross-section with a prospective kidney stone was analyzed to see the capabilities of such a technique. Typical radiological measures suggested that phosphates and oxalate stones can be distinguished from uric acid stones while dual-energy seemed to prove similar effectiveness.